bis working papers · bis working papers no 564 ... led moore to extrapolate an incr ease in...

BIS Working PapersNo 564

Moorersquos Law vs Murphyrsquos Law in the financial system whorsquos winning by Andrew W Lo

Monetary and Economic Department

May 2016

JEL classification G20 G28 G01

Keywords Financial technology systemic risk macroprudential policy risk management

BIS Working Papers are written by members of the Monetary and Economic Department of the Bank for International Settlements and from time to time by other economists and are published by the Bank The papers are on subjects of topical interest and are technical in character The views expressed in them are those of their authors and not necessarily the views of the BIS

This publication is available on the BIS website (wwwbisorg)

copy Bank for International Settlements 2016 All rights reserved Brief excerpts may be reproduced or translated provided the source is stated

ISSN 1020-0959 (print) ISSN 1682-7678 (online)

WP564 Moorersquos Law vs Murphyrsquos Law in the financial system whorsquos winning iii

Foreword

The 14th BIS Annual Conference took place in Lucerne Switzerland on 26 June 2015 The event brought together a distinguished group of central bank Governors leading academics and former public officials to exchange views on the topic ldquoTowards lsquoa new normalrsquo in financial marketsrdquo The papers presented at the conference and the discussantsrsquo comments are released as BIS Working Papers nos 561 to 564

BIS Papers no 84 contains the opening address by Jaime Caruana (General Manager BIS) the keynote address by John Kay (London School of Economics) and remarks by Paul Tucker (Harvard Kennedy School)

WP564 Moorersquos Law vs Murphyrsquos Law in the financial system whorsquos winning 1

Moorersquos Law vs Murphyrsquos Law in the financial system whorsquos winning1

Andrew W Lo2

Abstract

Breakthroughs in computing hardware software telecommunications and data analytics have transformed the financial industry enabling a host of new products and services such as automated trading algorithms crypto-currencies mobile banking crowdfunding and robo-advisors However the unintended consequences of technology-leveraged finance include firesales flash crashes botched initial public offerings cybersecurity breaches catastrophic algorithmic trading errors and a technological arms race that has created new winners losers and systemic risk in the financial ecosystem These challenges are an unavoidable aspect of the growing importance of finance in an increasingly digital society Rather than fighting this trend or forswearing technology the ultimate solution is to develop more robust technology capable of adapting to the foibles in human behaviour so users can employ these tools safely effectively and effortlessly Examples of such technology are provided



1 Prepared for the 14th BIS Annual Conference 26 June 2015 I thank John Guttag Andrei Kirilenko

Eric Rosenfeld Hyun Song Shin and conference participants for helpful comments and discussion and Jayna Cummings for editorial assistance Research support from the MIT Laboratory for Financial Engineering is gratefully acknowledged The views and opinions expressed in this article are those of the author only and do not necessarily represent the views and opinions of any institution or agency any of their affiliates or employees or any of the individuals acknowledged above

2 Charles E and Susan T Harris Professor MIT Sloan School of Management director MIT Laboratory for Financial Engineering principal investigator MIT Computer Science and Artificial Intelligence Laboratory 100 Main Street E62ndash618 Cambridge MA 02142 E-mail alo-adminmitedu Other affiliations including all commercial relationships are disclosed at httpalomitedu

2 WP564 Moorersquos Law vs Murphyrsquos Law in the financial system whorsquos winning

1 Introduction

In 1965 ndash three years before he co-founded Intel now the largest semiconductor chip manufacturer in the world ndash Gordon Moore published an article in Electronics Magazine in which he observed that the number of transistors that could be placed onto a chip seemed to double every year This simple observation implying a constant rate of growth led Moore to extrapolate an increase in computing potential from 60 transistors per chip in 1965 to 60000 in 1975 This number seemed absurd at the time but it was realised on schedule a decade later Later revised by Moore to a doubling every two years ldquoMoorersquos Lawrdquo has forecasted the growth of the semiconductor industry over the last 40 years with remarkable accuracy as Figure 1 confirms

Illustration of Moorersquos Law via transistor counts on various semiconductor chips from 1971 to 2011 which seems to double every two years Figure 1

Source ldquoTransistor Count and Moorersquos Law ndash 2011 by Wgsimonrdquo CC BY-SA 30

Technological change is often accompanied by unintended consequences The Industrial Revolution of the 19th century greatly increased the standard of living but it also increased air and water pollution The introduction of chemical pesticides greatly increased the food supply but it also increased the number of birth defects before we understood the risks And the emergence of an interconnected global financial system greatly lowered the cost and increased the availability of capital to businesses and consumers around the world but those same interconnections also served as vectors of financial contagion that facilitated the Financial Crisis of 2007ndash09 As a result the financial industry must weigh Moorersquos Law against Murphyrsquos Law ldquowhatever can go wrong will go wrongrdquo as well as Kirilenko and Lorsquos (2013)


technology-specific corollary ldquowhatever can go wrong will go wrong faster and bigger when computers are involvedrdquo

Some of the unintended consequences of financial technology include firesales flash crashes botched initial public offerings cybersecurity breaches catastrophic algorithmic trading errors and a technological arms race that has created new winners losers and systemic risk in the financial ecosystem The inherent paradox of modern financial markets is that technology is both the problem and ultimately the solution Markets cannot forswear financial technology ndash the competitive advantages of algorithmic trading and electronic markets are simply too great for any firm to forgo ndash but rather must demand better more robust technology technology so advanced it becomes foolproof and invisible to the human operator Every successful technology has gone through such a process of maturation the rotary telephone versus the iPhone paper road maps versus the voice-controlled touchscreen GPS and the kindly reference librarian versus Google and Wikipedia Financial technology is no different To resolve the paradox of Moorersquos Law versus Murphyrsquos Law we need version 20 of the financial system

2 Moorersquos Law and finance

Moorersquos Law now influences a broad spectrum of modern life It affects everything from household appliances to biomedicine to national defense and its impact is no less evident in the financial industry As computing has become faster cheaper and better at automating a variety of tasks financial institutions have been able to greatly increase the scale and sophistication of their services The emergence of automated algorithmic trading online trading mobile banking crypto-currencies like Bitcoin crowdfunding and robo-advisors are all consequences of Moorersquos Law

At the same time the combination of population growth and the complexity of modern society has greatly increased the demand for financial services In 1900 the total human population was an estimated 15 billion but little more than a century later ndash a blink of an eye in the evolutionary timescale ndash the worldrsquos population has grown to 7 billion (see Figure 2) The vast majority of these 7 billion individuals are born into this world without savings income housing food education or employment All of these necessities today require financial transactions of one sort or another well beyond the capacity of the financial industry in 1900 Therefore it should come as no surprise that innovations in computer hardware software telecommunications and storage continue to shape Wall Street as a necessary part of its growth

In fact technological innovation has always been intimately interconnected with financial innovation New stamping and printing processes used to prevent clipping counterfeiting and other forms of financial fraud directly led to the modern system of paper banknotes and token coinage The invention of the telegraph sparked a continent-spanning communications revolution that led the creation of the modern futures market in nineteenth-century Chicago And improvements to the ticker tape machine ndash symbolic of Wall Street for over a century ndash made Thomas Edison his early fortune


Semi-logarithmic plot of estimated world population from 10000 BC to 2011 AD Figure 2

Source US Census Bureau (International Data Base) and authorrsquos calculation

Technology and derivatives

Not very long ago most trades were made through traders and specialists on the floors of the exchanges The first electronic exchange NASDAQ opened in 1971 but it was originally only a quotation system for the slow-moving over-the-counter market Most trades were placed over the telephone and executed on the trading floor well into the 1980s Today however nearly all trades on the major financial exchanges are consummated electronically Moorersquos Law made the floor specialist obsolete and trading volume increased exponentially to meet this increase in trading capacity If the modern financial system had to rely on human specialists to manage even a fraction of this market volume it would need a trading floor larger than a sports arena

The symbiosis between technology and finance has accelerated the pace of the financial markets beyond mere human capacity at all levels of the financial system One elegant example comes from the options market The Chicago Board Options Exchange (CBOE) the first of its kind opened just before Fischer Black Myron Scholes and Robert Merton published their foundational papers in 19733 However the rapid growth of the CBOE would have been impossible had financial professionals lacked an easy way to use the Black-ScholesMerton option pricing formula As luck would have it in 1975 Texas Instruments introduced the SR-52 the first programmable handheld calculator and one capable of handling the logarithmic and exponential functions of the Black-ScholesMerton formula (see Figure 3)

3 Black and Scholes (1973) Merton (1973)


The Texas Instruments SR-52 programmable calculator introduced in 1975 and used tocompute the Black-ScholesMerton option-pricing formula by CBOE floor traders Figure 3

At $395 ($1737 in 2015 dollars) the SR-52 was a technological marvel that could

store programs of up to 224 keystrokes on a thin magnetic strip that was fed through a motorised slot in the calculator Shortly after the SR-52 debuted one of the founders of the CBOE a savvy options trader named Irwin Guttag purchased one for his teenage son and asked him to program the Black-ScholesMerton formula for it4 Within a year many CBOE floor traders were sporting SR-52s of their own By 1977 Texas Instruments introduced a new programmable TI-59 with a ldquoSecurities Analysis Modulerdquo that would automatically calculate prices using the Black-ScholesMerton formula When Scholes confronted Texas Instruments about their unauthorised use of the formula they replied that it was in the public domain When he asked for a calculator instead Texas Instruments replied that he should buy one5

A financial Moorersquos Law

The Black Scholes and Merton publications launched well over a thousand subsequent articles (eg Lim and Lo (2006)) becoming the intellectual foundation for three sectors of the derivatives industry exchange-traded options over-the-counter structured products and credit derivatives As of September 2015 there were $36 trillion of exchanged-traded options outstanding and as of the first half of 2015 there were $553 trillion in notional value of foreign exchange interest rate credit and other over-the-counter derivatives6 As Lo (2013) observed ldquoIn the modern history of all the social sciences no other idea has had more impact on both theory and practice in such a short time spanrdquo The reason cited is serendipity the convergence of science with the Black-ScholesMerton formula technology with the formation of the CBOE and need for risk mitigation created by the economic turmoil of the mid-1970s

4 Private communication with John V Guttag ndash Irwin Guttagrsquos son and SR-52 programmer ndash who

became a computer scientist eventually serving as chair of MITrsquos Department of Electrical Engineering and Computer Science and currently Dugald C Jackson Professor of Electrical Engineering and Computer Science at MIT

5 Scholes (2006)

6 Bank for International Settlements (2015 Table D1 at httpstatsbisorgstatxsrstabled1 and Table D51 at httpstatsbisorgstatxsrstabled51 accessed 16 Jan 2016)


Figure 4 highlights just one consequence of such serendipity the annual raw and log average daily trading volume of exchange listed options and futures from the Options Clearing Corporation from 1973 to 2014 A simple log-linear regression yields the financial equivalent of Moorersquos Law the volume of exchange-traded derivatives doubles approximately every five years Even the Financial Crisis of 2007ndash09 could only temporarily halt this growth for a couple of years after which the trend seems to continue unabated

It should be clear from these examples that Moorersquos Law and the exponential growth of computing power have utterly transformed the financial system7 The collective intelligence of the market dependent as it is on the rapid collection of accurate information has been greatly magnified by the advances in telecommunications processing power and data storage that Moorersquos Law has made possible The consequent easy access to financial services throughout the developed world has transformed the modern consumer lifestyle in a thousand small and large ways from everyday purchases at the local coffee shop through a frictionless global electronic payment network to investing for the life-changing events in onersquos future with a combinatorially vast variety of individualised financial products

Financial Moorersquos Law Raw and natural logarithm of average daily trading volume by yearof exchange-listed options and futures from the Options Clearing Corporation 1973ndash2014 and linear regression estimate of geometric growth rate which implies a doubling everylog 2(014) = 495 years Figure 4

7 Kirilenko and Lo (2013)


Four illustrations of the growing importance of finance (a) aggregate US employment in manufacturing vs finance and insurance sectors (b) value-added per capita in manufacturing vs finance and insurance (cd) annual income of college-graduate and post-graduate engineers and financiers (all wages are in 2000 US dollars and are weighted using sampling weights) from Phillipon (2009 Figure 7) Figure 5

(a) (b)

(c) (d)

The inexorable march of technological progress is part of a much broader trend of finance increasing its role in modern society Figure 5 presents four illustrations of this trend Figure 5(a) shows that aggregate employment in the finance and insurance sectors has been increasing steadily over time unlike the manufacturing sector which employs about the same number of workers today as it did in the 1940s The manufacturing sector is able to produce a much greater GDP with the same amount of labour because of technological progress especially automation This explanation is confirmed in Figure 5(b) which shows an upward-sloping graph of the value-added per capita in the manufacturing sector a clear measure of increasing productivity in manufacturing However Figure 5(b) also shows that the finance and insurance sectors have an even more steeply sloped productivity curve This difference in value-

0

5000

10000

15000

20000

25000

0

20000

40000

60000

80000

100000

120000

140000

160000

1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

Sect

or E

mpl

oyee

s (1

000

s)

Agg

rega

te E

mpl

oyee

s (1

000

s)

Aggregate Employment in Finance amp Insurance vs Manufacturing 1947 to 2008

GovernmentPrivate Services-Producing IndustriesPrivate Goods-Producing IndustriesManufacturingFinance amp Insurance

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

200000

1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

Valu

e-A

dded

Per

Cap

ita ($

)

Value-Added Per Capita ofManufacturing vs Finance amp Insurance Sectors

1947 to 2008

Manufacturing

Finance and Insurance


added per capita should translate into higher wages for finance and insurance professionals and this prediction is confirmed by Figure 5(c) and 5(d) which contain plots comparing the average annual income of college graduate and post-graduate engineers and financiers Finance is becoming more and more important Therein lies the problem

3 Moorersquos Law meets Murphyrsquos Law

Moorersquos Law has an unspoken corollary The rapid growth of financial innovation also means that much of this innovation is adopted without understanding the full risks It follows then that financial innovation is peculiarly susceptible to Murphyrsquos Law ldquoAnything that can go wrong will go wrongrdquo Murphyrsquos Law originally comes from the postwar aviation industry a time when aerospace engineers were finding ways to break the sound barrier and fly faster than the speed of sound then a new and untested technology Today financial engineers are finding ways to move markets faster than the speed of thought There is one important difference between the two industries however Aerospace engineers could test their designs through the efforts of brave test pilots before moving to production Financial innovation necessarily relies on simulation and past market statistics before it is implemented into the financial system As participants in the financial system we ourselves are the test pilots for the accelerated pace of financial innovation

From this perspective perhaps the real surprise is that the financial system has not suffered more technological ldquoprangsrdquo in recent years to borrow another term from the aerospace industry But markets are resilient in a way that aircraft are not Self-interest motivates the investor in a market to take advantage of any technological lapse in its functioning and in doing so the investor incorporates that information into market activity It is only when the market innovation causes a system-wide malfunction that the market fails to compensate Unfortunately these breakdowns although temporary seem to be occurring at an accelerating rate Moorersquos Law has apparently increased the risk of Murphyrsquos Law in the financial system and the following are some sobering examples8

The quant meltdown of August 2007

Beginning on Monday 6 August 2007 and continuing through Thursday 9 August some of the most successful hedge funds in the industry suffered record losses Despite the secretive nature of hedge funds and proprietary trading desks the Wall Street Journal was able to report that some had lost 10ndash30 of their value in a single week9 What made these losses even more extraordinary was the fact that they seemed to be concentrated almost exclusively among quantitatively managed equity market-neutral or ldquostatistical arbitragerdquo hedge funds giving rise to the eventrsquos nickname of the ldquoquant quakerdquo or ldquoquant meltdownrdquo

8 Some of these examples are drawn from Lo and Kirilenko (2013) with permission

9 Zuckerman Hagerty and Gauthier-Villars (2007) Sender Kelly and Zuckerman (2007)


Although many outside observers were willing to speculate no institution suffering such losses was willing to comment publicly on the causes of the quant meltdown To address this lack of transparency Khandani and Lo analysed the events of the meltdown by simulating the returns of the contrarian trading strategy of Lehmann and Lo and MacKinlay on the historical data10 Their ldquoUnwind Hypothesisrdquo proposed that the losses during the second week of August 2007 were initially due to the forced liquidation of one or more large equity market-neutral portfolios However this large portfolio was not unique but one of many portfolios that had converged on a similar selection presumably as a result of a widely adopted financial innovation within the hedge fund industry The price impact of this massive and sudden unwinding caused these similar but independent portfolios to experience losses These losses in turn caused some funds to deleverage their portfolios yielding an additional price impact that led to further losses and more deleveraging and so on in a deadly feedback loop Many of the affected funds were considered to be at the vanguard of industry practice The quant meltdown suggests that for a time they became victims of their financial innovation

The flash crash

At approximately 132 pm Central Time 6 May 2010 US financial markets experienced one of the most turbulent periods in their history This period lasted all of about 33 minutes The Dow Jones Industrial Average suffered its biggest one-day point decline on an intraday basis at one point plunging 600 points in the space of five minutes And the prices of some of the worldrsquos largest companies traded at incomprehensible prices ndash Accenture traded at a penny a share whereas Apple traded at $100000 per share This remarkable event has been seared into the memories of investors and market-makers and because of the speed with which it began and ended is now known as the ldquoflash crashrdquo

But the most disturbing aspect of the flash crash is that the subsequent investigation by the staffs of the Commodity Futures Trading Commission (CFTC) and the Securities and Exchange Commission (SEC) concluded that these events occurred not because of any single organisationrsquos failure but rather as a result of seemingly unrelated activities across different parts of the financial system that fed on each other to generate a perfect financial storm11 In other words there is no single ldquoculpritrdquo than can be punished for this debacle nor any new regulation that can guarantee such an event will never happen again

The joint CFTCSEC report traced the event to an atypical automated sale of 75000 E-mini SampP 500 June 2010 stock index futures contracts which occurred over an extremely short time period creating a large order imbalance that apparently overwhelmed the small risk-bearing capacity of the high-frequency traders acting as market-makers After accumulating E-mini contracts over a 10-minute interval these high-frequency traders began to unwind their long positions rapidly and aggressively passing contracts back and forth like a ldquohot potatordquo At the same time cross-market arbitrage trading algorithms quickly propagated the price decline in E-mini futures to the markets for stock index exchange-traded funds like the Standard amp Poorrsquos Depository Receipts SampP 500 individual stocks and listed stock options In a manner

10 Khandani and Lo (2007 2011) Lehmann (1990) Lo and MacKinlay (1990)

11 CFTCSEC (2010) Kirilenko Kyle Samadi and Tuzun (2014)


reminiscent of the 19 October 1987 stock market crash sell orders in the futures market triggered by an automated selling program cascaded into a systemic event for the entire US financial market system The difference is that the October 1987 crash took an entire day the flash crash came and went in the space of a television sit-com episode

This was the narrative as of 30 September 2010 when the joint CFTCSEC report was published However the narrative has changed On 21 April 2015 the US Department of Justice filed charges against Navinder Singh Sarao a British national12 The criminal complaint made with the CFTC alleged that Sarao had attempted to manipulate the price of E-Mini SampP 500 futures contracts on the Chicago Mercantile Exchange specifically using the tactic of ldquospoofingrdquo that is transmitting orders that he intended to cancel Sarao allegedly used a financial innovation called ldquodynamic layeringrdquo reportedly convincing an automated trading software company to customise his software to submit orders to give the illusion of a deep market before they were cancelled To quote from the Department of Justicersquos affidavit ldquoSARAOrsquos activity created persistent downward pressure on the price of E-Minis Indeed during the dynamic layering cycle that ran from 1117 am to 140 pm [Central Time] SARAOrsquos offers comprised 20 to 29 of the CMErsquos entire E-Mini sell-side order book significantly contributing to the order book imbalance During that period of time alone the E-Mini price fell by 361 basis points In total SARAO obtained approximately $879018 in net profits from trading E-Minis that dayrdquo13

These charges have not yet been decided upon in a court of law so they must necessarily remain hypothetical but there is nothing prima facie implausible about these allegations as a possible component of an explanation for the flash crash Even without fraudulent intent adding to a large order imbalance in an exchange where market-makers were overwhelmed would make the conditions for a flash crash more likely If these allegations hold however they show that the financial system also must be able to cope with innovations that are deliberately antagonistic to the wellbeing of the system

The BATS and Facebook IPOs

On 23 March 2012 BATS Global Markets held its IPO Founded in 2005 as a ldquoBetter Alternative Trading Systemrdquo to the New York Stock Exchange and NASDAQ BATS operated the third largest stock exchange in the United States at the time and did it from the suburbs of Kansas City As one of most technologically sophisticated companies in the financial industry BATS naturally decided to launch its IPO on its own exchange That was a mistake Shortly after its IPO debuted at an opening price of $1525 the price plunged to less than a tenth of a penny in a second and a half Apparently a software bug affecting stocks with ticker symbols from A to BFZZZ created an infinite loop that made these symbols inaccessible on the BATS system including its own ticker symbol BATS14 No information about the glitch was made public during the day Despite the quick deployment of a software patch by that

12 Brush Schoenberg and Ring (2015) CFTC (2015)

13 Department of Justice (2015)

14 Dornbrook (2012) Oran Spicer Mikolajczak and Mollenkamp (2012) Schapiro (2012)


afternoon the confusion was so great that BATS suspended trading in its own stock and ultimately cancelled its IPO altogether

An even bigger glitch occurred on 18 May 2012 when the pioneering social network company Facebook launched the most highly anticipated IPO in recent financial history As a company with over $18 billion in projected sales Facebook could have easily listed on the New York Stock Exchange alongside older blue-chip companies like IBM and Coca-Cola Instead Facebook chose to list on NASDAQ quite a coup for that exchange in an era of increasingly fragmented markets Although Facebookrsquos opening was expected to generate huge order flows NASDAQ prided itself on its ability to accommodate a high volume of trades so that capacity was not a concern In fact NASDAQrsquos IPO Cross software was reputed to be able to compute an opening price from a stockrsquos initial bids and offers in less than 40 microseconds approximately 10000 times faster than the blink of an eye

At the start of the Facebook IPO demand was so heavy that it took NASDAQrsquos computers up to five milliseconds to calculate its opening price more than 100 times slower than usual As these computations were running NASDAQrsquos order system allowed investors to change their orders up the moment the opening trade was printed on the tape These few milliseconds before the print were more than enough for new orders and cancellations to enter NASDAQrsquos auction book causing the IPO software to recalculate the opening trade price during which time even more orders and cancellations entered its book compounding the problem15 Software engineers call this situation a ldquorace conditionrdquo a race between new orders and the print of an opening trade created an infinite loop that could only be broken by manual intervention something that hundreds of hours of testing had apparently missed

Although scheduled to begin at 1100 am Facebookrsquos IPO opened a half hour late because of these delays As of 1050 am traders had not yet received acknowledgments of pre-opening order cancellations or modifications Even after NASDAQ formally opened the market many traders still had not received these critical acknowledgements creating more uncertainty and anxiety16 By the time the system was reset NASDAQrsquos programs were running 19 minutes behind real time Seventy-five million shares changed hands during Facebookrsquos opening auction but orders totalling an additional 30 million shares took place during this 19-minute limbo Many customer orders from both institutional and retail buyers went unfilled for hours or were never filled at all while other customers ended up buying more shares than they had intended17 The SEC ultimately approved a plan for NASDAQ to pay its customers $62 million for losses in its handling of Facebookrsquos offering eclipsing its achievement in handling the third largest IPO in US history18

Knight Capital Group

At market open on 1 August 2012 the well known US broker-dealer Knight Capital Group ndash one of the largest equity traders in the industry at the time and among the

15 Benoit (2012) Schapiro (2012)

16 Strasburg Ackerman and Lucchetti (2012)

17 Strasburg and Bunge (2012)



most technologically sophisticated ndash issued a surge of unintended orders electronically Many of these orders were executed resulting in a rapid accumulation of positions ldquounrestricted by volume capsrdquo that created significant swings in the prices of 148 stocks between 930 am and 1000 am19 Unable to void most of these unintentional trades Knight Capital was forced to liquidate them at market prices resulting in a $4576 million loss that wiped out its entire capital base Its share price plunged 70 and Knight was forced to seek a rescuer it was eventually acquired by competing broker-dealer GETCO in December 2012

What could have caused this disaster Knight subsequently attributed it to ldquoa technology issuehellip related to a software installation that resulted in Knight sending erroneous orders into the marketrdquo Apparently the SEC later determined that this was the result of a program functionality called ldquoPower Pegrdquo which had not been used since 2003 and had not been fully deleted from Knightrsquos systems20 The most surprising aspect of this incident was the fact that Knight was widely considered to be one of the best electronic market-makers in the industry with telecommunications systems and trading algorithms far ahead of most of their competition

The Treasury flash crash

Perhaps the most startling of the recent malfunctions took place in one of the cornerstones of the global financial system the US Treasury market on 15 October 2014 On that day yields in benchmark 10-year Treasuries traded in a range of 35 basis points between market open and close a seven-sigma intraday event with no obvious smoking gun Like other flash crashes much of this swing took place in a very brief interval Market observers attributed an initial sharp decline at 830 am Eastern Time to sell-offs precipitated by poor US retail sales in September Shortly after 933 am Eastern Time however the yield in 10-year Treasuries fell an additional 15 basis points to 186 only to rebound to its former level all in a space of 10 minutes21

Coincidentally enough the following day saw the monthly meeting of the Treasury Market Practices Group sponsored by the Federal Reserve Bank of New York The group had no immediate explanation for the flash crash in Treasuries but hypothesised that it was driven by rdquolarge scale repositioning by leveraged investors activities of electronic trading algorithms and dealer balance sheet and risk management constraintsrdquo22 This was clearly a stopgap account before more information became available Six months later however the New York Fed had not settled on a cause for that dayrsquos events Did automated trading firms ldquounpluggingrdquo their systems contribute to the plunge or did they protect the market from greater volatility Were regulatory changes that inhibited the traditional ability of dealers to buffer sudden changes in price a factor Was there a liquidity crunch or was the Treasuries market able to meet its orders despite the heavy trading volume No clear answer yet exists to these and other important questions about that dayrsquos events23

19 McCrank (2012) Telegraph (2012) Schapiro (2012)

20 SEC (2013)

21 Alloway and MacKenzie (2014) Potter (2015)

22 TMPG (2014)

23 Potter (2015)


The Bloomberg terminal outage

Financial markets increasingly rely on technologies that are not strictly part of the financial system but whose failure may still have a systemic effect Major exchanges now have uninterruptible power sources multiple modes of communication and offsite backup storage in case of natural or manmade disaster Despite this redundancy however when the Bloomberg terminal system was disrupted on 17 April 2015 for a period of two and a half hours many of the systemrsquos over 300000 subscribers were unable to function effectively bringing transactions in some markets to a standstill Bloomberg blamed ldquoa combination of hardware and software failures in the network which caused an excessive volume of network traffic This led to customer disconnections as a result of the machines being overwhelmedrdquo24

The Bloomberg terminal system a subscription-only data and communications network is the financial information system of choice for many traders globally Beginning shortly after market open in much of Europe the terminal outage had little effect on traders in the United States but affected markets throughout the eastern hemisphere leading to the postponement of a multibillion buy-back of government debt by the UK Debt Management Office Although alternative systems such as the Thomson Reuters network were available to many these systems lacked the customised messaging capability of the Bloomberg terminal which had developed into an important form of communication between traders Some enterprising traders returned to making deals over the phone a reversion to an earlier form of technology To turn a potential financial tragedy into farce one compelling but unverified rumour blamed the outage on a can of soda that was spilled onto a critical Bloomberg server25

4 Technology to the rescue

In her introductory speech to the SECrsquos Market Technology Roundtable in 2012 SEC chair Mary Schapiro condemned the increasing number of ldquoTechnology 101 issuesrdquo in the exchanges while emphasising that contagion across markets and venues is still rare26 Solving these Technology 101 issues is a crucial first step in lowering this new form of financial risk There is a saying in software engineering ldquoGiven enough eyeballs all bugs are shallowrdquo27 Presumably more eyeballs could have prevented the simple software bug that confounded the BATS IPO and the race condition that disrupted Facebookrsquos debut on NASDAQ

However as the flash crash and the quant meltdown demonstrate it is entirely possible to cause financial disruption when all systems are operating normally It is all too easy to imagine chains of financial contagion transmitting themselves through widely traded stocks such as Apple or Facebook both of which have been badly disrupted by market glitches or even more catastrophically through the global cornerstone market for US Treasuries whose plunge in October 2014 is still

24 Cox (2015) Cox and Trivedi (2015)

25 Brinded (2015)

26 Schapiro (2012)

27 Raymond (1999 p 30)


unexplained Moreover while solving Technology 101 issues is clearly important a financial system that relies on all of its parts functioning at 100 efficiency is vulnerable to both accident and malice The linkages made possible by technological innovation may have increased systemic financial risk in unforeseen ways but to reduce this new form of systemic risk the solution must be to make financial technology more robust not to reach for an illusory perfection Better software engineering in our financial system is analogous to improvements in our public health system to prevent the ill effects of bugs but we also need a financial immune system that is able to adapt to circumstances to prevent system-wide catastrophes

What do the financial failures in the preceding section have in common The common hallmark is a coordinated response to unexpected loss Under normal conditions unanticipated financial losses affect market participants narrowly eg the individual investor faced with a margin call they are unable to make When the losers are sufficiently large in size or number however their responses can threaten the financial stability of the system as a whole Unanticipated losses can cause widespread panic ndash in the form of flights to safety rapid price declines andor the evaporation of liquidity ndash that once triggered is impossible to contain Technological innovation changes the probability of these losses in unanticipated ways

Adaptive regulation

One way that the financial system can adapt to these changing circumstances is to employ dynamic regulation in the financial markets Consider an example from the private sector The Chicago Mercantile Exchange one of the worldrsquos largest organised financial exchanges has developed dynamic margin requirements so as to protect both the exchange and market participants from default due to extreme losses28 To do this it uses its in-house risk management system Standard Portfolio Analysis of Risk (SPAN) a software suite originally developed in 1988 now in its fourth generation and widely adopted as an industry standard29 SPAN calculates the maximum market loss of a portfolio under multiple scenarios (typically 16 however the number is user-defined) and then determines what the appropriate margin requirement should be30 Lo and Brennan have shown that the SPAN-calculated margin requirements for currency futures at the CME strongly correlate with recent volatility for US dollars in the euro market and other currencies indicating that SPAN has many of the properties needed for dynamic regulation

Risk management systems such as SPAN serve as a useful proof of concept for the importance of dynamic loss probabilities The SPAN system is critical to the Chicago Mercantile Exchange for protecting its clearing house against defaults and it incorporates the type of adaptive regulation that the financial system should also incorporate However the SPAN system is only concerned with mesoscale risks to the financial system It is designed to protect individual clearing houses with highly liquid instruments for which changes in volatility and price processes may be readily observed and incorporated into new margin requirements It is not concerned with managing systemic risk and it is difficult to see how it could be given its

28 Brennan and Lo (2014)

29 CME Group (2015)

30 CME Group (2010)


informational limitations It is adaptive regulation but at the level of the organ not the organism

Adaptive financial regulation needs to account for the macroeconomy It should be informed by private sector examples like the Chicago Mercantile Exchange and implement systems in the same spirit as SPAN but the focus of macroprudential policies must necessarily be the entire financial system the organism as a whole The CME is able to treat activities outside its purview as exogenous events while the financial system must address the endogenous nature of systemic risk and the impact of the regulatory requirements themselves

Law is code

Therefore to regulate the financial system as a whole we need to better understand financial regulation as a whole The US legal system is a working example of adaptive regulation based on principles of common law that date back to the Middle Ages and it incrementally changes in response to societal needs and political pressure However it was not designed for periods of rapid change and many of the Founders saw a deliberative pace in legal change as a positive goal Codification of federal law began startlingly late in American history (1926) and federal statutes are still poorly organised

It is fruitful to think of the law as the software of the American operating system ndash yet if a team of software engineers were to analyse the corpus of federal law they would see thousands of pages of poorly documented code with a multitude of complex spaghetti-like dependencies between individual modules31 Using metrics for measuring the quality of software (see Table 1) Li Azar Larochelle Hill and Lo (2015) analysed the entire text of the US legal code (all the permanent laws of the United States) and drew some sobering conclusions about its complexity and potential for unintended consequences

One particularly informative measure is a network-based measure of complexity using the degree of ldquoconnectivityrdquo across different sections of the US legal code where a ldquoconnectionrdquo between two sections of the code is defined as a simple cross-reference of one section by another Li et al (2015) cite the example of Section 37 USC sect 329 which involves an incentive bonus for retired or former members of the military This section cites exactly two other sections 37 USC sect 303a(e) (general provisions of special pay in the military) and 10 USC sect 101(a)(16) (a definition of ldquocongressional defense committeesrdquo) while 37 USC sect 329 is cited by one other section 10 USC sect 641 which notes that other laws in Title 10 of the US legal code do not apply to the officers to whom the bonus in 37 USC sect 329 applies The interconnections are shown in Figure 6 Now consider a much longer chain with multiple branches some of which refer back to the section being modified These chains may contain complex sequences of legal ramifications that even the most intelligent and knowledgeable human cannot fully grasp without some form of technological assistance

31 Li et al (2015)


Principles of good software design and corresponding metric Table 1

Source Li Azar Larochelle Hill and Lo (2015)

The layout of these connections ndash often called the ldquonetwork topologyrdquo in the jargon of mathematical graph theory ndash can also be used to construct quantitative measures of complexity One such measure is the notion of a ldquostrongly connectedrdquo set of nodes defined to be a set of nodes in which there is a path from every node to every other node in the set For example in Figure 7 nodes B and E form a strongly connected set but nodes (B E A) do not because there is no path from E to A within the subset of these three nodes

Network representation of references to and from a section of the US legal code (37 USC sect 329) Figure 6


When applied to an entire network it can be shown that the nodes can be partitioned into a finite number of disjoint subsets each of which is strongly connected and the union of all these strongly connected subsets is the entire network

Principle Proposed Metric

1 Conciseness Good code should be as long as it needs to be but no longer

Number of words

2 Cohesion Modules in code should do one thing well not multiple things badly

Language perplexity

3 Change Code that exhibits large or frequent change may suggest defects

Number of sectionssubsections affected

4 Coupling Modular code is more robust and easier to maintain than code with unnecessary cross-dependencies

Size of cross-reference network core versus periphery

5 Complexity Code with a large number of conditions cases and exceptions is difficult to understand and prone to error

Number of condition statements in code (McCabersquos complexity)

10 USC sect 101(a)(16)

37 USC sect 303a (e)

37 USC sect 329

10 USC sect 641


A natural measure of complexity can then be defined as the size of the largest strongly connected subset which is called the ldquocorerdquo In Figure 7 the core is the subset (D F G H) and its size is four nodes The larger the size of the core the more interconnected is the network changes to one part of the core could affect every other part of the core (because there exists at least one path from every node to every other node) As the core increases in size the possible interactions between different nodes grow exponentially

Illustration of the concept of strong connectedness in a directed graph and the ldquocorerdquo which is the largest strongly connected set of nodes Figure 7


Li et al (2015) apply this complexity measure to various parts of the US legal code and document some extraordinary levels of interconnectedness Figure 8 displays three small examples from their more comprehensive analysis In Figure 8(a) the network formed by the Omnibus Appropriations Act of 2009 is depicted with blue nodes representing peripheral sections and red nodes representing the core This network is relatively simple ndash a very small core surrounded by peripheral sections that are mostly isolated indicating very few cross-references This simplicity is not surprising in a bill that is largely a sequence of appropriations for a number of unrelated programmes

However Figure 8(b) shows a much more complex network representing the Dodd-Frank Wall Street Reform Act a piece of legislation spanning 2319 pages that was passed on 21 July 2010 Of the 390 rule-making requirements imposed by Dodd-Frank only 267 have been satisfied by finalised rules as of end-December 201532 However the complexity of Dodd-Frank does not compare with that of Title 12 of the US legal code which governs the entire banking industry its network structure is displayed in Figure 8(c) With an extremely large core and many connections between the core and the periphery it is easy to see how small changes can lead to unpredictable and unintended consequences in other parts of the network

32 Davis Polk (2015 p2)


Core-periphery network maps of (a) sections of the US legal code modified by the Omnibus Appropriations Act of 2009 (b) sections of the US legal code modified by the Dodd-Frank Wall Street Reform Act and (c) Title 12 of the US legal code (Banks and Banking) Blue dots indicate peripheral sections red dots indicate the core Figure 8

(a) (b) (c)


These new tools provide an X-ray of the hidden structures within current banking regulation It is perhaps unsurprising that the core sections on banking regulation have to do with the powers of the corporation insurance funds and holding companies since that is where the vast majority of financial assets are organised These sections of the law are of critical importance to the US financial system To pursue the software analogy further any effort to reform banking regulation should begin with a systematic ldquorefactoringrdquo and simplification of these sections improving their internal structure without altering their external behaviour rather than adding increasingly complicated patches to the law whose systemic effects are unknown

Transparency vs privacy

One compelling concern about a systemic macroprudential approach to financial regulation is financial privacy Most of the financial industry relies on unpatentable business processes to make a living as Myron Scholes discovered when he confronted Texas Instruments about its infringement on the Black-Scholes formula As a result the financial industry necessarily practises security through obscurity preferring to use trade secrets to protect its intellectual property Hedge funds and proprietary trading desks take this to an extreme essentially serving as ldquoblack boxesrdquo for investors as opaque as the law will allow However even the average financial institution has a need to limit disclosure of their business processes methods and data if only to protect the privacy of their clients Accordingly government policy has tread carefully on the financial industryrsquos disclosure requirements

How can financial institutions provide the information that adaptive regulation requires without feeling burdened or threatened by regulatory intrusion One solution is to make the interactions between financial institutions and regulators secret However this fails to provide the public with the transparency about systemic risk it increasingly wants from the financial system while putting an enormous burden on regulators

Fortunately developments in cryptography made possible by the acceleration in computing power under Moorersquos Law show a way to solve to this dilemma A well known technique from the computer science literature called ldquosecure multi-party computationrdquo provides an elegant solution to the need for sharing certain types of


information while preserving the confidentiality of each partyrsquos data A simple illustration of this technique involves the indelicate task of computing the average salary of a roomful of n conference attendees a very intrusive computation given the sensitive nature of individual salary figures

Suppose person 1 takes his salary S1 and adds to it a random number of his choosing X1 to obtain the sum Y1 = S1 + X1 and then shares this sum (but not the components) with person 2 Person 2 then performs the same calculation adding a random number of her choosing X2 to her salary S2 and then adding these two values to person 1rsquos information to obtain Y2 = Y1 + S2 + X2 She then passes Y2 to person 3 who adds his random number and salary to it before passing it to the next person and so on This process continues from one person to the next until the last person n adds his salary and random number to it yielding Yn = S1 + S2 + + Sn + X 1 + X2 + + Xn

Now suppose person n passes this sum to person 1 and asks him to subtract his random number X1 from it before passing it to person 2 Person 2 does the same operation subtracting her random number X2 from the cumulative sum before passing the value to person 3 and so on Once the process returns to person n who subtracts his random number Xn from the cumulative sum the value remaining is the sum of all the salaries S1 + S2 + + Sn which when divided by the number n which is observable yields the average salary in the room Figure 9 summarises this simple algorithm At no point during this process did anyone have to reveal his or her private information yet by the end of the process the average salary was computed Such algorithms are the essence of secure multi-party computation

Illustration of a simple secure multi-party computation algorithm for computing theaverage salary of a group of individuals without requiring any individual to reveal his orher salary Figure 9


Example of secure multi-party computation of the aggregate size of the real-estate loan portfolios of Bank of America JP Morgan and Wells Fargo Graph (a) contains the raw time series for the three individual banks as well as the aggregate sum graph (b) contains threeencrypted time series which when summed yields the same aggregate sum as theunencrypted data Figure 10

(a) (b)

Source Abbe Khandani and Lo (2012)

Now of course two participants could easily collude so as to infer the salary of a third individual For example if persons 1 and 3 compared their cumulative sums before and after person 2 subtracted her random number they could infer her random number and deduce her salary However there are simple ways of constructing cheat-proof algorithms that allow all parties to share certain kinds of information while keeping their raw data confidential In Abbe Khandani and Lo (2012) we construct secure multi-party computation algorithms that can be used to encrypt proprietary information from banks broker-dealers and other financial institutions while still allowing regulators to compute aggregate risk measures such as sums averages value-at-risk loss probabilities and Herfindahl indexes

Figure 10 contains a concrete illustration of this technology applied to the sizes of the real-estate loan portfolios of Bank of America JP Morgan and Wells Fargo Figure 10(a) contains the individual time series for these three institutions (the line graphs) which are the proprietary information of each institution and only publicly disclosed with a lag From a systempic risk perspective the individual values are of less importance than the aggregate sum depicted by the area graph in Figure 10(a) Using a particular algorithm designed just for this purpose Abbe et al (2012) show that the individual time series can be encrypted as in the line graphs in Figure 10(b) yet the sum of the encrypted time series yields the very same bar graph as in Figure 10(a) Aggregate sums can be shared by financial institutions while maintaining the privacy of each institution

Using secure multi-party computation tools it is possible to construct mathematical protocols that allow aggregate measures to be computed without

-

200

400

600

800

1000

1200

1400

1600

-

100

200

300

400

500

600

700

800

Jun

-86

Jun

-87

Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo


revealing any of the individual components of that aggregate33 Thus the aggregate risk exposures of a group of financial institutions can be calculated and made public while preserving the privacy of any individual financial institution This method is ideal for use in macroprudential regulation Furthermore since the cost-benefit ratio to financial institutions is so low there is even reason to believe that the financial industry may adopt such disclosures voluntarily if informational incentives are structured correctly

Of course techniques like secure multi-party computation certainly do not eliminate the need for regulations or regulators ndash for example there is no way to ensure that institutions report truthfully other than through periodic examination ndash but they can lower the economic cost of sharing certain types of information and provide incentives for the private sector to do so voluntarily If financial institutions can maintain the privacy of their trade secrets while simultaneously sharing information that leads to more accurate measures of threats to financial stability they stand to benefit as much as the regulators and the public

5 Conclusion

These examples show how technology can reduce the additional systemic financial risk brought about by technological innovation This is not a paradox Rather it is a consequence of the symbiotic relationship between finance and technology Not very long ago the financial markets were the most informationally intensive places on Earth the collective intelligence of the markets incorporating the worldrsquos data into prices faster than any computer of the time Today the financial markets are one informationally intensive system among many in a symbiotic relationship with search engines social networks messaging systems and the growing colossus of Big Data

In this brave new networked world we will need to adopt a more advanced systems approach to financial technology No financial engineer or programmer or designer of exchange servers should assume that a new product will function in isolation but should rather imagine a changing financial environment where past statistics almost certainly will not apply Similarly no financial regulator should assume that an innovator will not find a way to circumvent a regulation perhaps in a more disruptive way than what the regulation originally intended to prevent To return to the analogy of software engineering perhaps we should be assembling tools for financial system administrators to monitor and troubleshoot problems in the markets similar to the way a sysadmin monitors and troubleshoots problems in a computer system

To do this effectively however we need more and better information about the operation of financial markets Going back to the example of the flash crash the CFTC investigators were unable to find signs of Saraorsquos alleged activities because they were only given a list of completed transactions ldquoSpoofingrdquo however cancels the transactions before they are executed leaving no evidence in the market print All important market failures and events need to be analysed scrupulously and no data must be withheld from investigators

33 Abbe Khandani and Lo (2012)


One potential model for this scrupulous form of analysis already exists34 The National Transportation Safety Board (NTSB) has an excellent track record in analysing and determining the causes of transportation accidents in the United States The NTSB has no regulatory authority freeing the agency to criticise regulations and regulators that it believes may have contributed to the cause of an accident In addition the NTSB has subpoena power to obtain the information it needs to make a full analysis of an accident The NTSBrsquos accident report is not admissible as evidence in lawsuits for civil damages which allows the stakeholders to be much more candid about their role in an accident As a result the NTSB can address the systemic causes of an accident as it did in its report on USAir Flight 405 which put the ultimate cause of that flightrsquos crash in 1993 on a system-wide failure in de-icing procedures35 Under an NTSB-like system stakeholders in financial system failures would have less reason not to be candid about their possible shortcomings ndash but if this is still insufficient secure multi-party methods may allow financial information to be observed without identifying specific financial institutions in a form of cryptographic redaction

Better information about financial system failures will require better tools to remedy those failures Here mention must be made of the Food and Drug Administrationrsquos (FDArsquos) call for greater ldquoregulatory sciencerdquo36 Like the financial system the human body is also an immensely complicated and hyperconnected assemblage of disparate parts The FDArsquos mission for over a century has been to protect that body by prohibiting certain dangerous or fraudulent products and by testing the efficacy of others To continue to do so effectively in the future the FDA has proposed a broad strategy to harness science to serve regulation For example many models and assays currently used in toxicology are of limited accuracy in predicting adverse events in human beings They are still in use however because they are still considered best practice ndash a state of affairs that should be uncomfortably familiar to many financial regulators The FDArsquos regulatory science proposal would clearly define the reliability of these tests and their limitations ndash also something that should be familiar to financial regulators

The global financial system has experienced exponential growth as a result of its intimate symbiotic relationship with Moorersquos Law and new technologies This has resulted in an unfortunate expansion of new forms of systemic risk as new linkages made possible by these new technologies changed previously well understood probabilities of risks in unexpected ways However the same technologies that created these linkages also allow us to monitor and supervise the financial system in ways that would have been unthinkable in earlier years Because of Moorersquos Law it is now possible to regulate margin requirements dynamically analyse financial regulation as though it were a recalcitrant piece of computer code and oversee aggregate financial data publicly without violating financial privacy or confidentiality requirements Although it is too soon to tell it may be that the past few years have been a temporary blip in the symbiotic Red Queenrsquos Race between finance and technology Just as technology can add risk to a system technology can remove it as well

34 Fielding et al (2011)

35 NTSB (1993)

36 FDA (2011)


References

Abbe E A Khandani and A W Lo (2012) ldquoPrivacy-preserving methods for sharing financial risk exposuresrdquo American Economic Review Papers and Proceedings vol 102 pp 65ndash70

Alloway T and M MacKenzie (2014) ldquoBonds anatomy of a market meltdownrdquo Financial Times 17 November

Benoit D (2012) ldquoNasdaqrsquos blow-by-blow on what happened to Facebookrdquo Wall Street Journal Deal Journal 21 May httpblogswsjcomdeals20120521 nasdaqs-blow-by-blow-on-what-happened-to-facebook

Black F and M Scholes (1973) ldquoThe pricing of options and corporate liabilitiesrdquo Journal of Political Economy vol 81 pp 637ndash54

Brinded L (2015) ldquoRUMOUR the Bloomberg outage was caused by a spilled can of Cokerdquo Business Insider 17 April wwwbusinessinsidercomreason-for-the-global-bloomberg-outage-2015-4

Brennan T and A W Lo (2014) ldquoDynamic loss probabilities and implications for financial regulationrdquo Yale Journal on Regulation no 31 pp 667ndash94

Brush S T Schoenburg and S Ring (2015) ldquoHow a mystery trader with an algorithm may have caused the flash crashrdquo Bloomberg 21 April wwwbloombergcomnewsarticles2015-04-22mystery-trader-armed-with-algorithms-rewrites-flash-crash-story

CFTC (Commodity Futures Trading Commission) (2015) US Commodity Futures Trading Commission v Nav Sarao Futures Limited PLC and Navinder Singh Sarao wwwcftcgovucmgroupspubliclrenforcementactionsdocumentslegalpleadingenfsaraocomplaint041715pdf

CFTCSEC (Commodity Futures Trading CommissionSecurities and Exchange Commission) (2010) Preliminary Findings Regarding the Market Events of May 6 2010 Report of the Staffs of the CFTC and SEC to the Joint Advisory Committee on Emerging Regulatory Issues 18 May wwwsecgovsec-cftc-prelimreportpdf

CME Group (2010) CME SPAN Standard Portfolio Analysis of Risk wwwcmegroupcomclearingfilesspan-methodologypdf

mdashmdashmdash (2015) Risk Management Overview Available at wwwcmegroupcom clearingrisk-managementhttpwwwcmegroupcomclearingrisk-management

Cox J (2015) ldquoDeals postponed after Bloomberg terminals go down globallyrdquo Wall Street Journal 17 April httpblogswsjcommoneybeat20150417deals-postponed-after-bloomberg-terminals-go-down-in-europe-and-asia

Cox Josie and Anjani Trivedi 2015 ldquoBloomberg Terminals Go Down Globallyrdquo Wall Street Journal April 17 httpwwwwsjcomarticlesbloomberg-terminals-go-down-globally-1429262782

Davis P (2015) Dodd Frank Progress Report Fourth Quarter 2015 Davis Polk httpproddavispolkcomsitesdefaultfilesQ4_2015_Dodd-Frank_Progress_Reportpdf (accessed 16 January 2016)


Department of Justice (2015) Criminal complaint United States v Navinder Singh Sarao 11 February wwwjusticegovsitesdefaultfilesopapress-releases attachments20150421sarao_criminal_complaintpdf

Dornbrook J (2012) ldquoBATS CEO We solved the problem werenrsquot dependent on the IPOrdquo Kansas City Business Journal 29 March wwwbizjournalscom kansascitynews20120329bats-ceo-we-solved-the-problemhtml

FDA (Food and Drug Administration) (2011) Advancing Regulatory Science at FDA wwwfdagovdownloadsScienceResearchSpecialTopicsRegulatoryScienceUCM268225pdf

Fielding E A W Lo and J Yang (2011) ldquoThe National Transportation Safety Board A model for systemic risk managementrdquo Journal Of Investment Management vol 9 pp 17ndash49

Khandani A and A W Lo (2007) ldquoWhat happened to the quants in August 2007rdquo Journal of Investment Management vol 5 pp 29ndash78

mdashmdashmdash (2011) ldquoWhat happened to the quants in August 2007 Evidence from factors and transactions datardquo Journal of Financial Markets vol 14 pp 1ndashndash46

Kirilenko A and A W Lo (2013) ldquoMoorersquos Law versus Murphyrsquos Law Algorithmic trading and its discontentsrdquo Journal of Economic Perspectives vol 27 pp 51ndash72

Kirilenko A A Kyle M Samadi and T Tuzun (2014) ldquoThe flash crash the impact of high frequency trading on an electronic marketrdquo httppapersssrncomsol3paperscfmabstract_id=1686004

Lehmann B (1990) ldquoFads martingales and market efficiencyrdquo Quarterly Journal of Economics vol 105 pp 1ndash28

Li W P Azar D Larochelle P Hill and A W Lo (2015) ldquoLaw is code a software engineering approach to analyzing the United States coderdquo Journal of Business amp Technology Law vol 10 no 2

Lim T and A W Lo (2006) The Derivatives Sourcebook Now Publishers

Lo A W (2013) ldquoIntroduction to Volume 5 of the Annual Review of Financial Economicsrdquo Annual Review of Financial Economics vol 5 pp 1ndash7

Lo A W and C MacKinlay (1990) ldquoWhen are contrarian profits due to stock market overreactionrdquo Review of Financial Studies vol 3 pp 175ndash205

Merton R (1973) ldquoTheory of rational option pricingrdquo Bell Journal of Economics and Management Science vol 4 pp 141ndash83

McCrank J (2012) ldquoKnight glitch likely to lead to regulatory changes CEOrdquo Reuters 11 September wwwreuterscomarticle20120911us-knight-ceo-idUSBRE88A1GW20120911

Moore G (1965) ldquoCramming more components onto integrated circuitsrdquo Electronics vol 38 pp 114ndash7

NTSB (National Transportation Safety Board) (1993) ldquoTakeoff stall in icing conditions USAir Flight 405 Fokker F-28 N485US LaGuardia Airport Flushing New York March 22 1992rdquo NTSBAAR-9302

Oran O J Spicer C Mikolajczak and C Mollenkamp (2012) ldquoBATS Exchange withdraws IPO after stumblesrdquo Reuters March 24 wwwreuterscomarticle20120324us-bats-trading-idUSBRE82M0W020120324


Philippon T and A Reshef (2009) ldquoWages and human capital in the US financial industry 1909ndash2006rdquo NBER Working Paper no 14655 wwwnberorgpapersw14644

Potter S (2015) ldquoChallenges posed by the evolution of the Treasury marketrdquo remarks at the 2015 Primary Dealer Meeting New York City 13 April wwwnewyorkfedorgnewseventsspeeches2015pot150413html

Raymond E (1999) The cathedral amp the bazaar musings on Linux and open source by an accidental revolutionary OReilly

Schapiro M (2012) ldquoIntroductory remarks at SECrsquos market technology roundtablerdquo 2October wwwsecgovnewsspeech2012spch100212mlshtm

Scholes M (2006) ldquoDerivatives in a dynamic environmentrdquo in T Lim A W Lo R Merton M Scholes and M Haugh (eds) 2006 The Derivatives sourcebook Now Publishers

SEC (Securities and Exchange Commission) (2013) Administrative proceeding in the matter of Knight Capital Americas LLC Order Instituting Administrative And Cease-And-Desist Proceedings Pursuant To Sections 15(B) and 21c Of The Securities Exchange Act Of 1934 Making Findings And Imposing Remedial Sanctions And A Cease-And-Desist Order 16 October wwwsecgovlitigationadmin201334-70694pdf

Sender H K Kelly and G Zuckerman (2007) ldquoGoldman wagers on cash infusion to show resolverdquo Wall Street Journal 14 August p A1

Strasburg J A Ackerman and A Lucchetti (2012) ldquoNasdaq CEO lost touch amid Facebook chaosrdquo Wall Street Journal 11 June p A1

Strasburg J and J Bunge (2012) ldquoSocial networkrsquos debut on Nasdaq disrupted by technical glitches trader confusionrdquo Wall Street Journal 19 May p A2

mdashmdashmdash (2013) ldquoNasdaq is still on hook as SEC backs payout for Facebook IPOrdquo Wall Street Journal 25 March

The Daily Telegraph (2012) ldquoKnight Capitalrsquos $440m trading loss lsquocaused by disused softwarersquordquo 14 August wwwtelegraphcoukfinancenewsbysectorbanksandfinance 9475292Knight-Capitals-440m-trading-loss-caused-by -disused-softwarehtml

Treasury Market Practices Group (2014) TMPG Meeting Minutes 16 October wwwnewyorkfedorgtmpgoctober_minutes_2014pdf

Zuckerman G J Hagerty and D Gauthier-Villars (2007) ldquoImpact of mortgage crisis spreads Dow tumbles 28 as fallout intensifies moves by central banksrdquo Wall Street Journal 10 August p A1


Comments by Darrell Duffie1

Unfinished work on CCP failure resolution planning

A central counterparty (CCP) is a financial market utility that lowers counterparty default risk on each trade that it clears by becoming the buyer to each seller and the seller to each buyer The main regulatory goal for this central clearing technology is to enhance financial stability by setting uniform high and transparent standards for counterparty risk mitigation and by lowering the risk of propagation of systemically important defaults The ldquonew normalrdquo for the regulation of financial markets globally is that standard over-the-counter (OTC) derivatives are now centrally cleared by CCPs Central clearing is also heavily used in exchange-based markets and is increasingly applied in other financial markets such as those for repurchase agreements

A key concern is how to manage the risk of a CCP failure When it becomes unable to meet its obligations a CCP could be forced into a normal insolvency process such as bankruptcy or alternatively into a government-administered failure resolution process The ongoing global regulatory reform of financial markets envisions effective failure resolution processes for all systemically important financial firms Yet despite this intent and despite the reality that central clearing is now mandated for a vast amount of derivatives under the G20 Pittsburgh Declaration of 20092 there is still slim progress on the design of specific government-administered failure resolution plans for CCPs In some jurisdictions even though the principles have been established government entities responsible for administering the actual failures of CCPs have yet to provide specific implementing operational plans or procedures These plans and procedures should include methods for (1) deciding when to override the contractual loss allocation process (2) how to obtain the liquidity required during the failure resolution process (3) how to allocate final losses and (3) how to provide for continuity of clearing services (whether at the same CCP or at an alternative venue)

How CCPs recover from clearing member defaults

A CCPrsquos balance sheet is quite different from those of other major types of systemically important financial institution such as banks broker-dealers and insurance companies The bulk of the financial risk of a CCP is not represented by its own legal assets and liabilities Rather a CCP is essentially a nexus of contracts by which its clearing members net and mutualise their counterparty default risk In the

1 Dean Witter Distinguished Professor of Finance Graduate School of Business Stanford University

This note summarises the discussion of CCP failure resolution that I provided during the session ldquoHas technology changed the nature of risks in financial marketsrdquo The author for this session was Professor Andrew Lo In addition to the topic of this note this session covered a range of other technology issues This note is based in part on D Duffie (2016) For other related work see wwwstanfordedu~duffie

2 See G20 (2009)


normal course of business the daily payment obligations of a CCP automatically sum to zero Because of this a CCP tends to have tiny amounts of equity and conventional debt relative to its largest potential clearing obligations Most of the tail risk of a CCP is allocated to its clearing members The clearing members tend to be systemically important Moreover clearing members tend to be members of many different CCPs

When the market value of a centrally cleared derivatives contract increases on a given day any clearing member who is a buyer of that contract type collects a variation margin payment from its CCP on the next day equal to the assessed change in market value of the position Any seller is likewise required to make a variation margin payment to the CCP Because the total amounts of cleared bought and sold contracts are identical the CCPrsquos positions are exactly balanced long against short leaving the CCP with zero net payment obligations If however one or more clearing members fail to meet their payment obligations the CCP has unbalanced exposures and must find the resources necessary to liquidate the failed positions and rebalance itself If it cannot its failure must be resolved

The greatest associated risks are (a) contagion by which the failure of a clearing member could cause the CCP to fail to meet its obligations to other systemically clearing members (b) firesales of collateral or derivatives contracts exacerbating broad market volatility and (c) loss of continuity of critical clearing services on which the financial system has come to depend

As an example of the significant counterparty risk managed by a single CCP SwapClear a cross-border central counterparty operated by LCHClearnet currently has a total notional amount of cleared interest-rate swaps of approximately $360 trillion3 Notional positions do not translate directly to risk More commensurate with the amount of the risk managed by a CCP is the total amount of balances held at the CCP by its clearing members which constitute mainly the funds available to cover the defaults of clearing members At the end of 2014 this amount for LCH Clearnet Group was euro407 billion4 Large CCPs are systemically important and are becoming ever more important as the implementation of new regulations forces more and more positions into CCPs

The failure of a major CCP would probably come at an extremely stressful moment because it is most likely to be precipitated by the failure of one or more systemically important clearing members who would probably have also failed to meet their payment obligations to many other major financial firms including other CCPs Ironically the better is the quality and depth of the risk-management resources of a CCP the more likely it is that its failure could only have been caused by the collapse of extremely large clearing members and probably by more than one of them Under CPSS-IOSCO principles a globally systemically important CCP must have the resources necessary to cover the failures of its two largest clearing members5

At the failure of one or more clearing members of a CCP if the cost of liquidating the failed membersrsquo positions exceeds the margin and default guarantee funds

3 See wwwlchclearnetcomswapsswapclear_for_clearing_members

4 See Consolidated Financial Statements of LCH Clearnet Group p 13 wwwlchclearnetcomdocuments731485762550lch+group+financial+statements+2014+signedpdf0bb5f0db-8c4b-4120-9cdc-439eea1129c9

5 See Principle 4 of Committee on Payment and Settlement Systems-International Organization of Securities Commissions ldquoPrinciples for Financial Market Infrastructuresrdquo April 2012


provided by the failed members the surviving members and the CCP operator absorb the remaining cost of liquidating the failed positions if that is actually possible with the available resources While the contribution of CCP capital to the default management resources is not negligible it is typically most important as a means of giving the CCP operator some ldquoskin-in-the-gamerdquo incentive to design and manage the CCP safely

In a recovery process a CCP might assign losses to its surviving members (and perhaps their clients) in a manner that causes significant distress costs The existence of a contractual recovery approach that avoids the insolvency of a CCP does not imply that the contractual recovery approach should be followed to its end regardless of the situation There may be unforeseen circumstances in which total distress costs can be lowered by winding down or restructuring a CCP with a procedure that overrides contracts such as bankruptcy or a government-administered resolution process

The ldquowaterfallrdquo of recovery resources of some CCPs extends beyond the guarantee fund by permitting the CCP to contractually restructure its clearing payment obligations to clearing members

One such procedure is ldquovariation margin gains haircuttingrdquo (VMGH) By this approach the CCP can conserve or accumulate cash by cancelling or reducing the variation margin payments that it would otherwise have been required to make to clearing members At the same time the CCP collects 100 of the variation margin payments that it is due to receive from clearing members6 Beyond its role as a short-term liquidity backstop VMGH could in some cases continue until the CCP has enough resources to pay for the liquidation of failed positions There is no assurance that VMGH would be sufficient to entirely rebalance the CCP although experts believe that VMGH would suffice in most scenarios7 Those clearing members suffering losses from VMGH could in principle be given compensating claims for example equity or debt issued by the CCP

Another potential contractual restructuring approach is a ldquotear-uprdquo by which the CCP could cancel some or all of its outstanding notional derivatives positions with selected clearing members For example suppose the failure of a clearing member has left the CCP with a net short position in some specific class of derivatives that is 90 of the total of its outstanding long positions In this case the CCP could assuming that it has the necessary contractual right rebalance its exposure by stipulating that all long positions shall henceforth be 90 of their former notional size An alternative is to simply tear up 100 of all outstanding positions of the affected type

Variation margin gain haircuts and partial tear-ups have the disadvantage of sharing losses unpredictably given that it would be difficult to predict much more than a day in advance whether it would be long or short position holders that would be allocated the losses This is unlike the situation facing normal creditors who know they are line for losses at the borrowerrsquos default and know the priority order in which they will take losses In terms of sharing distress costs one would prefer to have losses

6 A version of this approach has been adopted by the Japanese Securities Clearing Association See

Japanese Securities Association wwwjscccojpencashirslosshtml

7 For more details on VMGH see Elliott (2013) ISDA (2013) LCH (2015) and Singh (2014)


borne by all CCP members perhaps pro rata with some measure of the expected amount of potential loss that a clearing member would impose on the CCP conditional on both the failure of the clearing member and the failure of the CCP8

On a risk-corrected basis this might suggest end-of-waterfall loss-sharing that is proportional to total initial margins In the same way as VMGH and tear-ups loss-sharing in proportion to total initial margins would also encourage clearing members to reduce their positions with weak CCPs Initial margins moreover are held by the CCP in the form of ldquopaid-inrdquo assets usually in a liquid form Unfortunately there is no obvious method for exploiting assets of this sort during the recovery process Initial margin funds are the property of clearing members and are not legally accessible to CCPs absent voluntary contracting that would make them available at the end of the default-management waterfall9

It is not clear to me why CCPs and their clearing members prefer to use VMGH or tear-ups rather than to adjust their clearing agreements so as to allow legal end-of-waterfall access to initial margin funds In any case more predictable loss-sharing is normally more efficient There are no clear incentive benefits associated with disproportionate and unpredictable loss-sharing by clearing members who happen to be buyers or who happen to be sellers Moreover economic principles suggest that it is better for a clearing member to suffer a moderate loss with certainty when a CCP fails to meet its clearing obligations than to ldquoflip a coinrdquo to determine whether the size of the loss is zero or not The marginal cost to a clearing member of bearing an incremental unit of unexpected loss is normally increasing in the total amount of loss a ldquoconvexity effectrdquo that suggests losses should be shared across all clearing members pro rata to the loss exposures they impose on the CCP This is one of the reasons that CCPs are supposed to ensure adequately sized paid-in guarantee funds which do share losses predictably and broadly When the default guarantee fund is revealed to be inadequate and when it is deemed appropriate to attempt recovery through further contractual loss-sharing rather than failure resolution I have seen persuasive arguments for switching to a form of unequal and unpredictable loss-sharing

Principles for government-administered CCP failure resolution

Failure-resolution administrators may one day be faced with a decision of whether and when to halt the contractual recovery process of a distressed or failed CCP forcing the CCP into an administered resolution The right to do so exists in principle in the United Kingdom and arguably in the United States10 and will likely soon exist

8 Both conditioning events are relevant as explained by Dembo Deuschel and Duffie (2004)

9 See European Parliament (2012) which states that ldquoA CCP shall have a right of use relating to the margins or default fund contributions collected via a security financial collateral arrangement within the meaning of Article 2(1)(c) of Directive 200247EC of the European Parliament and of the Council of 6 June 2002 on financial collateral arrangements provided that the use of such arrangements is provided for in its operating rulesrdquo

10 In the United States it seems likely that Title II of the Dodd-Frank Act assigns the administration of the failure resolution process of systemically important CCPs to the Federal Deposit Insurance


throughout the European Union whenever financial stability is threatened even if the CCP is currently meeting its contractual obligations

Failure resolution procedures should be designed so as to minimise the total expected distress costs of all market participants including clearing members CCP operators as well as unrelated market participants and taxpayers that could suffer from failure spillover costs

While the government bailout of a systemically important CCP should not be legally impossible reliance on government capital should not be part of the failure resolution design given the attendant moral hazard In order to align incentives in a socially efficient manner the CCP operator and its clearing members should expect that they are on the hook for all of the losses one way or another

The key questions facing the failure resolution administrator are (a) how to efficiently allocate the CCPrsquos losses (b) how to mitigate firesales and (c) how to arrange for the prompt continuation of clearing services

At the point of resolution of a CCP most or all of its waterfall of contractually available resources has likely been exhausted As the resolution procedure begins the CCP may therefore have limited remaining resources with which to restructure its obligations to clearing members

In principle a resolution authority addressing a CCP in this financial condition could simply declare that the CCP will discontinue clearing and return any remaining assets to its clearing members pro rata to unmet clearing obligations This liquidation approach is more easily contemplated when continuity of clearing services can be provided by an alternative CCP handling the same classes of trades During a wind-down a CCP may need to haircut variation margin gains as a cash management strategy

The alternatives to liquidating an insolvent CCP are

1 Reorganise the CCP through some combination of new capital injections and restructuring of its clearing obligations The debt of the CCP can also be restructured but in practice CCPs do not usually have much debt

2 Transfer the clearing obligations of the CCP if necessary after some restructuring to another existing CCP or to a ldquobridgerdquo CCP

There is a critical decision as to when to trigger this form of resolution balancing the harm caused by lack of access of the original CCP to additional default fund contributions from clearing members that could prevent a CCP failure relative to the harm caused by draining capital from systemically important clearing members without necessarily the prospect of emerging with a viable CCP

Even if pre-funded and escrowed funds are available to set up a new guarantee fund11 the CCP (or its successor or bridge) may need additional capital to cover the

Corporation (FDIC) (Whether this is in fact the case however is not a completely settled matter as explained by Steigerwald and DeCarlo (2014)) Assuming that Title II applies the FDIC can become the receiver of a CCP in the event that the Secretary of the Treasury the Federal Reserve Board and the FDIC find that there would be otherwise be a risk of financial instability In that case the FDIC could liquidate the CCP or alternatively could assign its assets and obligations to another CCP or to a ldquobridgerdquo which in principle could become a successor CCP In Europe directives principles and plans or enabling legislation are described in European Commission (2012) European Securities and Markets Authority (2012) European Union (2012) European Union (2014) and HM Treasury (2014)

11 For example see JPMorgan Chase (2014)


cost of liquidating failed positions Several approaches for this have been suggested including tear-ups and VMGH along the same lines that could be applied contractually in a recovery process

Until the completion of the resolution process the failure administrator needs access to liquidity to manage cash payments In addition to its immediately available cash a CCP could obtain liquidity through financing that is secured by non-cash assets These include assets held in the default-management waterfall as initial margin (to the extent legally permitted) or paid-in guarantee fund contributions and claims to future contributions to the default guarantee fund A further potential source of liquidity is VMGH to the extent legally permitted Some government sources of liquidity may be available12 including in the form of central bank lending of last resort In the United Kingdom central bank liquidity to financial market infrastructure is explicitly available13

If restructuring is an option failure resolution administration authorities could be given the legal authority to apply VMGH or tear-ups even if that option is not contractually recognised in clearing agreements Under a US Title II failure administration procedure the FDIC has the legal right to reject contracts provided that rejection is not applied selectively across contracts with the same counterparty It is not clear whether or how the FDIC could conduct VMGH or partial tear-ups To this point the FDIC has not described the failure-resolution strategies that it would use in the case of CCPs

Outline of a CCP failure resolution process

Based on our discussion an administrative CCP failure resolution process could have the following basic steps

1 Verify the conditions for initiating a failure resolution process and initiate the process Consult with relevant foreign authorities

2 Stay the termination of clearing agreements and other contracts with the likely exception of interoperability agreements with other CCPs

3 Replace the senior CCP management if that is deemed appropriate while taking steps to retain key personnel

4 Assess the immediate cash needs of the CCP and the available sources of liquidity Make a plan to access liquidity in priority order Obtain the necessary cash whether for orderly wind down or for continuity of clearing

5 In the event of insufficient cash interrupt payments to clearing members as legally feasible under contracts or stays and as appropriate to mitigating the aggregate losses of all parties including unrelated market participants

6 Enter claims on the estates of failed clearing members

7 In a restructuring aimed at the continuation of clearing services

12 In the United States restrictions on government sources of liquidity are outlined by Skeel (2014)

13 See Bank of England (2014ab)


a If the CCP undergoing resolution is not suitable for restructuring and continuation as a single entity then transfer unrejected clearing agreements and other CCP property and agreements to a bridge or other successor CCP

b Replenish the default guarantee fund using pre-funded assets as available and additional replenishment contributions from clearing members to the extent permitted by contract and judged systemically safe from the viewpoint of contagion risk

c Rebalance the derivatives positions of the CCP For example conduct tear-ups or allocate failed derivatives positions to surviving members for example by auction

d Assign the equity and any debt claims of the recapitalised or bridge CCP

e Resume clearing new trades

f Make appropriate changes to the CCPrsquos rules clearing agreements and risk management procedures

g Permit clearing member resignations after a ldquocooling-offrdquo period

8 In a liquidation and wind-down

a Tear up remaining positions or novate them to other CCPs

b Evaluate claims against the assets of the CCP held by clearing members and other creditors

c Liquidate the CCPrsquos remaining assets

d Assign the liquidated assets of the CCP to claimants

It is not clear whether a CCP should continue clearing new derivatives trades while undergoing resolution This should presumably be determined by the circumstances at the time with the objective of mitigating the total distress costs of clearing members and other market participants An inability to clear new trades could present some difficulty to market participants who have come to rely on straight through processing of trades (including clearing) and are attempting to quickly add or replace hedges Moreover US regulations may require that a ldquodesignated clearing organizationrdquo (DCO) continues to provide clearing services and require (subject to exemptions) that market participants continue centrally clearing designated ldquostandardisedrdquo derivatives Whether waivers of these regulations can be obtained and under what circumstances is not clear If a CCP is unable to clear during its reorganisation then regulatory clearing requirements should if possible be temporarily waived for those types of derivatives for which there are no alternative CCPs

In closing I would say that much work remains to be done by failure administrative authorities So far most of the progress has been in the form of international standards and coordination of planning activities among international bodies as described by the Financial Stability Board (2014 2015) In particular it was agreed in 2015 by the chairs of the FSB Standing Committee on Supervisory and Regulatory Cooperation the FSB Resolution Steering Group the Basel Committee on Banking Supervision the CPMI and IOSCO that the FSB Resolution Steering Group ldquoshould serve as the focal point for work on the resolution of CCPs working in close cooperation with CPMI and IOSCOrdquo At the national level particularly in some


jurisdictions progress on the development of plans for the failure resolution of CCPs should be better disclosed for public consideration

References

Bank of England (2014a) ldquoThe Bank of Englandrsquos Sterling Monetary Frameworkrdquo (also known as ldquoThe Red Bookrdquo) November wwwbankofenglandcoukmarkets Documentsmoneypublicationsredbookpdf

mdashmdashmdash (2014b) ldquoThe Bank of Englandrsquos Supervision of Financial Market Infrastructuresrdquo in Bank of England Annual Report March 2014 wwwbankofenglandcoukpublicationsDocumentsfmifmiap1403pdf

CDS Default Management Working Group (2011) ldquoPrinciples and best practices for managing a defaulting clearing memberrsquos remaining portfolio and shortfall in available fundsrdquo January

The Clearinghouse (2012) ldquoCentral counterparties recommendations to promote financial stability and resiliencerdquo December 2012 httpwwwtheclearinghouseorg indexhtmlf=074643

Committee on Payment and Settlement Systems Board of the International Organization of Securities Commissions (2012a) ldquoPrinciples for financial market infrastructurerdquo Bank for International Settlements April 2012 wwwbisorg cpmipubld101apdf

mdashmdashmdash (2012b) ldquoRecovery and resolution of financial market infrastructuresrdquo Consultative Report July 2012 wwwbisorgpublcpss103pdf Comments at wwwbisorgpublcpss103commentshtm

mdashmdashmdash (2014) ldquoRecovery of financial market infrastructuresrdquo Consultative Report October 2014

Davies G and M Dobler (2011) ldquoBank resolution and safeguarding the creditors left behindrdquo Research and Analysis Bank of England Quarterly Bulletin Q3 2011 pp 213ndash23

Dembo A J-D Deuschel and D Duffie (2004) ldquoLarge portfolio lossesrdquo Finance and Stochastics vol 8 pp 3ndash16

Duffie D (2016) ldquoResolution of failing central counterpartiesldquo in K Scott and J Taylor (eds) Making failure feasible how bankruptcy reform can end lsquotoo big to failrsquo Hoover Institution Press

Elliott D (2013) ldquoCentral counterparty loss-allocation rulesrdquo Bank of England Financial Stability Paper no 20 April 2013 wwwbankofenglandcoukpublications Documentsfsrfs_paper20pdf

European Commission (2012) ldquoConsultation on a possible recovery and resolution framework for financial institutions other than banksrdquo Directorate General Internal Markets and Services

European Securities and Markets Authority (2012) ldquoDraft technical standards under the Regulation (EU) No 6482012 of the European Parliament and of the Council of 4 July 2012 on OTC Derivatives CCPs and Trade Repositories Final Reportrdquo September ESMA2012600 wwwesmaeuropaeusystemfiles2012-600_0pdf


European Union (2012) ldquoRegulation (EU) No 6482012 of the European Parliament and of the Council of 4 July 2012 on OTC Derivatives Central Counterparties and Trade Repositoriesrdquo Official Journal of the European Union 12 June 2012 httpeurlexeuropaeuLexUriServLexUriServdouri=OJL201220100010059ENPDF

mdashmdashmdash (2014) ldquoDirective 201459EU of The European Parliament and of the Council of 15 May 2014 Establishing a Framework for the Recovery and Resolution of Credit Institutions and Investment Firmsrdquo Official Journal of the European Union 12 June 12 2014 httpeur-lexeuropaeulegal-contentENTXTuri=uriservOJL_201417301 019001ENG

Financial Stability Board (2014) ldquoKey attributes of effective resolution regimes for financial institutionsrdquo Basel 15 October 2014 wwwfinancialstabilityboardorg 201410r_141015page_moved=1

mdashmdashmdash (2015) ldquo2015 CCP Workplanrdquo Financial Stability Board 15 April 2015 wwwfsborgwp-contentuploadsJoint-CCP-Workplan-for-2015-For-Publicationpdf

G20 (2009) ldquoPittsburgh Declarationrdquo G20 httpsg20orgwp-contentuploads 201412Pittsburgh_Declaration_0pdf

HM Treasury (2014) ldquoSecondary legislation for non-bank resolution regimesrdquo Consultation Outcome 9 June 2014 wwwgovukgovernmentconsultations secondary-legislation-for-non-bank-resolution-regimessecondary-legislation-for-non-bank-resolution-regimes

ISDA (2013) ldquoCCP loss allocation at the end of the waterfallrdquo August 2013 www2isdaorgattachmentNTc5Nw==CCP_loss_allocation_waterfall_0807pdf

JPMorgan Chase (2014) ldquoWhat is the resolution plan for CCPsrdquo JPMorgan Chase Office of Regulatory Affairs September

LCH Clearnet (2015) ldquoCCP risk management recovery and resolutionrdquo LCH Clearnet White Paper

Singh M (2014) ldquoLimiting taxpayer puts ndash an example from CCPsrdquo IMF Working Paper October 2014

Skeel D (2014) ldquoFinancing systemically important financial institutions in bankruptcyrdquo University of Pennsylvania Law School this volume

Steigerwald R and D DeCarlo (2014) ldquoResolving central counterparties after Dodd-Frank Are CCPs eligible for lsquoorderly liquidationrsquordquo working paper Federal Reserve Bank of Chicago November 2014


Written contribution by Benoicirct Cœureacute1

Has technology changed the nature of risks in financial markets

Information technology has undoubtedly transformed financial markets over the last few decades While both the scope and the pace of change vary greatly across different market segments it is hard to think of any financial activity that still works in the way that it did when computers were large slow and expensive

There are many ways in which technology affects the way markets work I will focus on four different areas highlighting both the benefits and the concerns associated with each

Automation

Powerful computers have transformed securities trading Todayrsquos modern exchanges are fully electronic and algorithmic and high-frequency trading have grown to dominate the marketplace Computers have proven to be particularly useful for the automation of repetitive tasks such as submitting new quotes comparing prices across different trading platforms and monitoring newswires This naturally entails efficiency gains as traditional activities (market-making arbitrage optimal order execution etc) are now carried out more quickly and cheaply than ever before

However this rapid transformation also entails some risks Markets now function almost at the speed of light which requires instantaneous reactions when things go wrong Incidents such as the 2010 ldquoFlash Crashrdquo show that reliance on technology is not a one-way street and new safeguards need to be adopted in order to keep up with the changing environment Computers now perform tasks that are critical to the functioning of the market and the effects of operational failures have to be kept in check in order to mitigate the resulting tail risks

One example of such an operational failure was the so-called ldquoKnightmarerdquo during which the system used by New York Stock Exchange market-maker Knight Capital sent erroneous orders into the market for around 30 minutes2 As Sağlam (2015)3 explains this trading glitch led to an increase in institutional trading costs for stocks where Knight Capital was acting as the designated market-maker Such incidents speak to some of the concerns voiced by critics of high-frequency trading and ultimately pose a threat to the integrity of the markets in question It is clear that

1 Executive Board member of the European Central Bank and Chairman of the Committee on Payments

and Market Infrastructures (CPMI)

2 This incident resulted in a loss of more than USD 400 million for the firm (see ldquoKnight Capital glitch loss hits $461mrdquo Financial Times (online edition) 17 October 2012) It was subsequently acquired by Getco another electronic trading firm

3 M Sağlam ldquoThe rogue algorithm and its discontents evidence from a major trading glitchrdquo unpublished working paper 2015


the ongoing arms race in the financial industry presents a serious challenge for regulators as they need to upgrade their human capital and the tools they have available in order to preserve an efficient and reliable market structure

Decentralisation

Technology also enables the decentralisation of markets as it obviates the need for economic agents to be physically located together in a single marketplace in order to reap the benefits of liquidity externalities Today IT systems enable market participants to virtually consolidate fragmented markets This development with the support of regulators on both sides of the Atlantic has broken long-standing monopolies and fostered competition among financial market infrastructure providers (exchanges central counterparties etc)4 This has undoubtedly benefited investors through increases in both diversity and innovation and reductions in fees However this new landscape also poses some challenges Infrastructure is becoming more interconnected which allows local shocks to spread throughout the system and market fragmentation can lead to opacity and increased complexity which can hamper efficient regulatory oversight Moreover the combination of reliance on technology and competitive pressure creates the potential for operational failures and resulting market breakdowns It also increases vulnerability to cyber threats which now feature prominently on the agendas of financial regulators The industrial organisation of financial market infrastructures deserves close attention from both regulators and academics especially because the provision of public goods such as price discovery can run counter to the private incentives of profit-maximising firms5 This trade-off was at the heart of the discussion surrounding the updated rules for markets in financial instruments (ldquoMiFID IIrdquo) in Europe

Shift of activities

The use of technology also allows certain activities to move away from the traditional banking sector For example hedge funds and other shadow banks frequently rely on quantitative investment strategies which are greatly facilitated by the use of IT systems More generally technological innovations such as the internet reduce search costs thereby lowering barriers to entry for innovative adaptations of long-standing business models across the entire spectrum of financial services from consumer finance to securities trading While this again entails significant benefits for investors and consumers through increased competition it also implies certain risks In particular some activities may not be subject to efficient regulation and supervision ndash an issue that is well known to all of us not least since the subprime mortgage crisis The Financial Stability Board has been addressing these risks in its workstream on

4 Regulation National Market System in the United States and the Markets in Financial Instruments

Directive (MiFID) in Europe paved the way for fierce competition among stock exchanges

5 For example the joint pricing of trading fees and market data by exchanges can distort price discovery (see G Cespa and T Foucault ldquoSale of price information by exchanges does it promote price discoveryrdquo Management Science vol 60 2015 pp 148ndash65)


shadow banking In addition sufficient transparency is also important for investor and consumer protection including as regards privacy issues

New activities

Finally technological progress inevitably leads to the emergence of new financial activities A prime example of this is the emergence of virtual currency schemes such as Bitcoin While these schemes have many of the features of a regular currency ndash being for example a unit of account and a means of payment ndash they are not legal tender and are not backed by a state or government Moreover their value tends to be rather volatile meaning that they could instead be considered to be a commodity

Most virtual currency schemes include a payment system such as Bitcoinrsquos distributed ledger the blockchain This is a beneficial feature which can exert competitive pressure on existing payment systems (particularly those used for costly transactions such as international money transfers to and from developing countries) and could foster the introduction of faster and cheaper payment systems This feature is also helpful in terms of financial inclusion

However there are also several risks First Bitcoin is opaque that is to say there is no supervision or oversight as there is with regular currencies Moreover there is no investordepositor protection so that users have no recourse to a legal framework or judicial enforcement (for example in cases of hacking and other such crimes) Finally Bitcoin is entirely based on trust While this is in principle also the case for a fiat currency Bitcoin is not backed by a sovereign state with the right to levy taxes and it has no legalpolitical basis This can be attractive for small communities but it cannot support economic activity in larger jurisdictions

Finally the rise of digital finance poses the same challenges for the financial industry that digitalisation and disintermediation (in more mundane terms ldquoUberisationrdquo) pose for other parts of the economy will established players be capable of reaping the benefits of exploiting consumer and investor data or will these benefits be captured by new less well regulated actors operating at the retail end of the system Do financial intermediaries need to grow even bigger to reap the benefits of scale potentially running counter to regulatorsrsquo desire to avoid any organisation being ldquotoo big to failrdquo I very much look forward to financial and industry organisations providing answers to these questions in the years to come

Summary

Technology has a fundamental impact on financial markets as it changes the way in which transactions are handled and information is processed Overall technological progress leads to considerable efficiency gains and reduced costs for investors and consumers through automation innovation and competition However it also results in new risks and it is important that regulators keep up to speed in order to ensure that the benefits are reaped by society as a whole

All volumes are available on our website wwwbisorg

Previous volumes in this series

No Title Author

563 May 2016

Who supplies liquidity how and when Bruno Biais Fany Declerck and Sophie Moinas

562 May 2016

Expectations and investment Nicola Gennaioli Yueran Ma and Andrei Shleifer

561 May 2016

Mobile collateral versus immobile collateral Gary Gorton and Tyler Muir

560 May 2016

Has the pricing of stocks become more global

Ivan Petzev Andreas Schrimpf and Alexander F Wagner

559 April 2016

A comparative analysis of developments in central bank balance sheet composition

Christiaan Pattipeilohy

558 April 2016

Why bank capital matters for monetary policy Leonardo Gambacorta and Hyun Song Shin

557 April 2016

How Does Bank Capital Affect the Supply of Mortgages Evidence from a Randomized Experiment

Valentina Michelangeli and Enrico Sette

556 April 2016

Threat of Entry and Debt Maturity Evidence from Airlines

Gianpaolo Parise

555 March 2016

The causal effect of house prices on mortgage demand and mortgage supply evidence from Switzerland

Christoph Basten and Catherine Koch

554 March 2016

Can a Bank Run Be Stopped Government Guarantees and the Run on Continental Illinois

Mark Carlson and Jonathan Rose

553 March 2016

What drives the short-run costs of fiscal consolidation Evidence from OECD countries

Ryan Banerjee and Fabrizio Zampolli

552 March 2016

Fiscal sustainability and the financial cycle Claudio Borio Marco Lombardi and Fabrizio Zampolli

551 March 2016

When the Walk is not Random Commodity Prices and Exchange Rates

Emanuel Kohlscheen Fernando H Avalos and Andreas Schrimpf

550 March 2016

A new dimension to currency mismatches in the emerging markets non-financial companies

Michael Chui Emese Kuruc and Philip Turner

549 March 2016

Monetary policy spillovers and currency networks in cross-border bank lending

Stefan Avdjiev and Előd Takaacutets

548 March 2016

Moving in tandem bank provisioning in emerging market economies

Andres Murcia and Emanuel Kohlscheen

547 March 2016

When pegging ties your hands Intertemporal considerations in currency crises

Nikola Tarashev and Anna Zabai

Moorersquos Law vs Murphyrsquos Law in the financial system whorsquos winning

Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References

Comments by Darrell Duffie




References

Written contribution by Benoicirct Coeureacute

Automation

Decentralisation

Shift of activities

New activities

Summary


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PDFX3Check false PDFXCompliantPDFOnly false PDFXNoTrimBoxError true PDFXTrimBoxToMediaBoxOffset [ 000000 000000 000000 000000 ] PDFXSetBleedBoxToMediaBox true PDFXBleedBoxToTrimBoxOffset [ 000000 000000 000000 000000 ] PDFXOutputIntentProfile (None) PDFXOutputConditionIdentifier () PDFXOutputCondition () PDFXRegistryName () PDFXTrapped False CreateJDFFile false Description ltlt ARA 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 BGR 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 CHS ltFEFF4f7f75288fd94e9b8bbe5b9a521b5efa7684002000410064006f006200650020005000440046002065876863900275284e8e55464e1a65876863768467e5770b548c62535370300260a853ef4ee54f7f75280020004100630072006f0062006100740020548c002000410064006f00620065002000520065006100640065007200200036002e003000204ee553ca66f49ad87248672c676562535f00521b5efa768400200050004400460020658768633002gt CHT ltFEFF4f7f752890194e9b8a2d7f6e5efa7acb7684002000410064006f006200650020005000440046002065874ef69069752865bc666e901a554652d965874ef6768467e5770b548c52175370300260a853ef4ee54f7f75280020004100630072006f0062006100740020548c002000410064006f00620065002000520065006100640065007200200036002e003000204ee553ca66f49ad87248672c4f86958b555f5df25efa7acb76840020005000440046002065874ef63002gt CZE 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 DAN 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 DEU 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 ESP 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 ETI 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 FRA 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 GRE ltFEFF03A703C103B703C303B903BC03BF03C003BF03B903AE03C303C403B5002003B103C503C403AD03C2002003C403B903C2002003C103C503B803BC03AF03C303B503B903C2002003B303B903B1002003BD03B1002003B403B703BC03B903BF03C503C103B303AE03C303B503C403B5002003AD03B303B303C103B103C603B1002000410064006F006200650020005000440046002003BA03B103C403AC03BB03BB03B703BB03B1002003B303B903B1002003B103BE03B903CC03C003B903C303C403B7002003C003C103BF03B203BF03BB03AE002003BA03B103B9002003B503BA03C403CD03C003C903C303B7002003B503C003B103B303B303B503BB03BC03B103C403B903BA03CE03BD002003B503B303B303C103AC03C603C903BD002E0020002003A403B1002003AD03B303B303C103B103C603B10020005000440046002003C003BF03C5002003B803B1002003B403B703BC03B903BF03C503C103B303B703B803BF03CD03BD002003B103BD03BF03AF03B303BF03C503BD002003BC03B50020004100630072006F006200610074002003BA03B103B9002000410064006F00620065002000520065006100640065007200200036002E0030002003BA03B103B9002003BD03B503CC03C403B503C103B503C2002003B503BA03B403CC03C303B503B903C2002Egt HEB 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 HRV 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 HUN 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 ITA (Utilizzare queste impostazioni per creare documenti Adobe PDF adatti per visualizzare e stampare documenti aziendali in modo affidabile I documenti PDF creati possono essere aperti con Acrobat e Adobe Reader 60 e versioni successive) JPN 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 KOR ltFEFFc7740020c124c815c7440020c0acc6a9d558c5ec0020be44c988b2c8c2a40020bb38c11cb97c0020c548c815c801c73cb85c0020bcf4ace00020c778c1c4d558b2940020b3700020ac00c7a50020c801d569d55c002000410064006f0062006500200050004400460020bb38c11cb97c0020c791c131d569b2c8b2e4002e0020c774b807ac8c0020c791c131b41c00200050004400460020bb38c11cb2940020004100630072006f0062006100740020bc0f002000410064006f00620065002000520065006100640065007200200036002e00300020c774c0c1c5d0c11c0020c5f40020c2180020c788c2b5b2c8b2e4002egt LTH 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 LVI 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 NLD (Gebruik deze instellingen om Adobe PDF-documenten te maken waarmee zakelijke documenten betrouwbaar kunnen worden weergegeven en afgedrukt De gemaakte PDF-documenten kunnen worden geopend met Acrobat en Adobe Reader 60 en hoger) NOR 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 POL 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 PTB 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 RUM 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 RUS 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documents suitable for reliable viewing and printing of business documents Created PDF documents can be opened with Acrobat and Adobe Reader 60 and later) gtgtgtgt setdistillerparamsltlt HWResolution [600 600] PageSize [595276 841890]gtgt setpagedevice

BIS Working Papers are written by members of the Monetary and Economic Department of the Bank for International Settlements and from time to time by other economists and are published by the Bank The papers are on subjects of topical interest and are technical in character The views expressed in them are those of their authors and not necessarily the views of the BIS

This publication is available on the BIS website (wwwbisorg)

copy Bank for International Settlements 2016 All rights reserved Brief excerpts may be reproduced or translated provided the source is stated

ISSN 1020-0959 (print) ISSN 1682-7678 (online)


Foreword





Andrew W Lo2

Abstract








1 Introduction



























5 Scholes (2006)









(a) (b)

(c) (d)


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1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

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1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

Valu

e-A

dded

Per

Cap

ita ($

)


1947 to 2008

Manufacturing













The flash crash

































20 SEC (2013)


22 TMPG (2014)

23 Potter (2015)









25 Brinded (2015)

26 Schapiro (2012)

27 Raymond (1999 p 30)




Adaptive regulation




29 CME Group (2015)

30 CME Group (2010)




Law is code




31 Li et al (2015)










Number of words


Language perplexity







10 USC sect 101(a)(16)


37 USC sect 329

10 USC sect 641










(a) (b) (c)














(a) (b)





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Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary


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ltFEFF005500740069006c0069006300650020006500730074006100200063006f006e0066006900670075007200610063006900f3006e0020007000610072006100200063007200650061007200200064006f00630075006d0065006e0074006f0073002000640065002000410064006f00620065002000500044004600200061006400650063007500610064006f007300200070006100720061002000760069007300750061006c0069007a00610063006900f3006e0020006500200069006d0070007200650073006900f3006e00200064006500200063006f006e006600690061006e007a006100200064006500200064006f00630075006d0065006e0074006f007300200063006f006d00650072006300690061006c00650073002e002000530065002000700075006500640065006e00200061006200720069007200200064006f00630075006d0065006e0074006f00730020005000440046002000630072006500610064006f007300200063006f006e0020004100630072006f006200610074002c002000410064006f00620065002000520065006100640065007200200036002e003000200079002000760065007200730069006f006e0065007300200070006f00730074006500720069006f007200650073002egt ETI 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 FRA 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 GRE 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 HEB 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 HRV 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 HUN 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 ITA (Utilizzare queste impostazioni per creare documenti Adobe PDF adatti per visualizzare e stampare documenti aziendali in modo affidabile I documenti PDF creati possono essere aperti con Acrobat e Adobe Reader 60 e versioni successive) JPN 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 KOR ltFEFFc7740020c124c815c7440020c0acc6a9d558c5ec0020be44c988b2c8c2a40020bb38c11cb97c0020c548c815c801c73cb85c0020bcf4ace00020c778c1c4d558b2940020b3700020ac00c7a50020c801d569d55c002000410064006f0062006500200050004400460020bb38c11cb97c0020c791c131d569b2c8b2e4002e0020c774b807ac8c0020c791c131b41c00200050004400460020bb38c11cb2940020004100630072006f0062006100740020bc0f002000410064006f00620065002000520065006100640065007200200036002e00300020c774c0c1c5d0c11c0020c5f40020c2180020c788c2b5b2c8b2e4002egt LTH 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 LVI 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 NLD (Gebruik deze instellingen om Adobe PDF-documenten te maken waarmee zakelijke documenten betrouwbaar kunnen worden weergegeven en afgedrukt De gemaakte PDF-documenten kunnen worden geopend met Acrobat en Adobe Reader 60 en hoger) NOR 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 POL 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 PTB ltFEFF005500740069006c0069007a006500200065007300730061007300200063006f006e00660069006700750072006100e700f50065007300200064006500200066006f0072006d00610020006100200063007200690061007200200064006f00630075006d0065006e0074006f0073002000410064006f00620065002000500044004600200061006400650071007500610064006f00730020007000610072006100200061002000760069007300750061006c0069007a006100e700e3006f002000650020006100200069006d0070007200650073007300e3006f00200063006f006e0066006900e1007600650069007300200064006500200064006f00630075006d0065006e0074006f007300200063006f006d0065007200630069006100690073002e0020004f007300200064006f00630075006d0065006e0074006f00730020005000440046002000630072006900610064006f007300200070006f00640065006d0020007300650072002000610062006500720074006f007300200063006f006d0020006f0020004100630072006f006200610074002000650020006f002000410064006f00620065002000520065006100640065007200200036002e0030002000650020007600650072007300f50065007300200070006f00730074006500720069006f007200650073002egt RUM 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 RUS ltFEFF04180441043F043E043B044C043704430439044204350020044D044204380020043F043004400430043C043504420440044B0020043F0440043800200441043E043704340430043D0438043800200434043E043A0443043C0435043D0442043E0432002000410064006F006200650020005000440046002C0020043F043E04340445043E0434044F04490438044500200434043B044F0020043D0430043404350436043D043E0433043E0020043F0440043E0441043C043E044204400430002004380020043F043504470430044204380020043104380437043D04350441002D0434043E043A0443043C0435043D0442043E0432002E00200421043E043704340430043D043D044B043500200434043E043A0443043C0435043D0442044B00200050004400460020043C043E0436043D043E0020043E0442043A0440044B0442044C002C002004380441043F043E043B044C04370443044F0020004100630072006F00620061007400200438002000410064006F00620065002000520065006100640065007200200036002E00300020043B04380431043E00200438044500200431043E043B043504350020043F043E04370434043D043804350020043204350440044104380438002Egt SKY 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 SLV 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 SUO 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 SVE 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 TUR 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 UKR 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 ENU (Use these settings to create Adobe PDF documents suitable for reliable viewing and printing of business documents Created PDF documents can be opened with Acrobat and Adobe Reader 60 and later) gtgtgtgt setdistillerparamsltlt HWResolution [600 600] PageSize [595276 841890]gtgt setpagedevice


Foreword





Andrew W Lo2

Abstract








1 Introduction



























5 Scholes (2006)









(a) (b)

(c) (d)


0

5000

10000

15000

20000

25000

0

20000

40000

60000

80000

100000

120000

140000

160000

1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

Sect

or E

mpl

oyee

s (1

000

s)

Agg

rega

te E

mpl

oyee

s (1

000

s)



0

20000

40000

60000

80000

100000

120000

140000

160000

180000

200000

1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

Valu

e-A

dded

Per

Cap

ita ($

)


1947 to 2008

Manufacturing













The flash crash

































20 SEC (2013)


22 TMPG (2014)

23 Potter (2015)









25 Brinded (2015)

26 Schapiro (2012)

27 Raymond (1999 p 30)




Adaptive regulation




29 CME Group (2015)

30 CME Group (2010)




Law is code




31 Li et al (2015)










Number of words


Language perplexity







10 USC sect 101(a)(16)


37 USC sect 329

10 USC sect 641










(a) (b) (c)














(a) (b)





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800

1000

1200

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100

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400

500

600

700

800

Jun

-86

Jun

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Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary





Andrew W Lo2

Abstract








1 Introduction



























5 Scholes (2006)









(a) (b)

(c) (d)


0

5000

10000

15000

20000

25000

0

20000

40000

60000

80000

100000

120000

140000

160000

1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

Sect

or E

mpl

oyee

s (1

000

s)

Agg

rega

te E

mpl

oyee

s (1

000

s)



0

20000

40000

60000

80000

100000

120000

140000

160000

180000

200000

1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

Valu

e-A

dded

Per

Cap

ita ($

)


1947 to 2008

Manufacturing













The flash crash

































20 SEC (2013)


22 TMPG (2014)

23 Potter (2015)









25 Brinded (2015)

26 Schapiro (2012)

27 Raymond (1999 p 30)




Adaptive regulation




29 CME Group (2015)

30 CME Group (2010)




Law is code




31 Li et al (2015)










Number of words


Language perplexity







10 USC sect 101(a)(16)


37 USC sect 329

10 USC sect 641










(a) (b) (c)














(a) (b)





-

200

400

600

800

1000

1200

1400

1600

-

100

200

300

400

500

600

700

800

Jun

-86

Jun

-87

Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary




1 Introduction



























5 Scholes (2006)









(a) (b)

(c) (d)


0

5000

10000

15000

20000

25000

0

20000

40000

60000

80000

100000

120000

140000

160000

1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

Sect

or E

mpl

oyee

s (1

000

s)

Agg

rega

te E

mpl

oyee

s (1

000

s)



0

20000

40000

60000

80000

100000

120000

140000

160000

180000

200000

1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

Valu

e-A

dded

Per

Cap

ita ($

)


1947 to 2008

Manufacturing













The flash crash

































20 SEC (2013)


22 TMPG (2014)

23 Potter (2015)









25 Brinded (2015)

26 Schapiro (2012)

27 Raymond (1999 p 30)




Adaptive regulation




29 CME Group (2015)

30 CME Group (2010)




Law is code




31 Li et al (2015)










Number of words


Language perplexity







10 USC sect 101(a)(16)


37 USC sect 329

10 USC sect 641










(a) (b) (c)














(a) (b)





-

200

400

600

800

1000

1200

1400

1600

-

100

200

300

400

500

600

700

800

Jun

-86

Jun

-87

Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary

























5 Scholes (2006)









(a) (b)

(c) (d)


0

5000

10000

15000

20000

25000

0

20000

40000

60000

80000

100000

120000

140000

160000

1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

Sect

or E

mpl

oyee

s (1

000

s)

Agg

rega

te E

mpl

oyee

s (1

000

s)



0

20000

40000

60000

80000

100000

120000

140000

160000

180000

200000

1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

Valu

e-A

dded

Per

Cap

ita ($

)


1947 to 2008

Manufacturing













The flash crash

































20 SEC (2013)


22 TMPG (2014)

23 Potter (2015)









25 Brinded (2015)

26 Schapiro (2012)

27 Raymond (1999 p 30)




Adaptive regulation




29 CME Group (2015)

30 CME Group (2010)




Law is code




31 Li et al (2015)










Number of words


Language perplexity







10 USC sect 101(a)(16)


37 USC sect 329

10 USC sect 641










(a) (b) (c)














(a) (b)





-

200

400

600

800

1000

1200

1400

1600

-

100

200

300

400

500

600

700

800

Jun

-86

Jun

-87

Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary










(a) (b)

(c) (d)


0

5000

10000

15000

20000

25000

0

20000

40000

60000

80000

100000

120000

140000

160000

1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

Sect

or E

mpl

oyee

s (1

000

s)

Agg

rega

te E

mpl

oyee

s (1

000

s)



0

20000

40000

60000

80000

100000

120000

140000

160000

180000

200000

1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003

Valu

e-A

dded

Per

Cap

ita ($

)


1947 to 2008

Manufacturing













The flash crash

































20 SEC (2013)


22 TMPG (2014)

23 Potter (2015)









25 Brinded (2015)

26 Schapiro (2012)

27 Raymond (1999 p 30)




Adaptive regulation




29 CME Group (2015)

30 CME Group (2010)




Law is code




31 Li et al (2015)










Number of words


Language perplexity







10 USC sect 101(a)(16)


37 USC sect 329

10 USC sect 641










(a) (b) (c)














(a) (b)





-

200

400

600

800

1000

1200

1400

1600

-

100

200

300

400

500

600

700

800

Jun

-86

Jun

-87

Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary














The flash crash

































20 SEC (2013)


22 TMPG (2014)

23 Potter (2015)









25 Brinded (2015)

26 Schapiro (2012)

27 Raymond (1999 p 30)




Adaptive regulation




29 CME Group (2015)

30 CME Group (2010)




Law is code




31 Li et al (2015)










Number of words


Language perplexity







10 USC sect 101(a)(16)


37 USC sect 329

10 USC sect 641










(a) (b) (c)














(a) (b)





-

200

400

600

800

1000

1200

1400

1600

-

100

200

300

400

500

600

700

800

Jun

-86

Jun

-87

Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary






























20 SEC (2013)


22 TMPG (2014)

23 Potter (2015)









25 Brinded (2015)

26 Schapiro (2012)

27 Raymond (1999 p 30)




Adaptive regulation




29 CME Group (2015)

30 CME Group (2010)




Law is code




31 Li et al (2015)










Number of words


Language perplexity







10 USC sect 101(a)(16)


37 USC sect 329

10 USC sect 641










(a) (b) (c)














(a) (b)





-

200

400

600

800

1000

1200

1400

1600

-

100

200

300

400

500

600

700

800

Jun

-86

Jun

-87

Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary











25 Brinded (2015)

26 Schapiro (2012)

27 Raymond (1999 p 30)




Adaptive regulation




29 CME Group (2015)

30 CME Group (2010)




Law is code




31 Li et al (2015)










Number of words


Language perplexity







10 USC sect 101(a)(16)


37 USC sect 329

10 USC sect 641










(a) (b) (c)














(a) (b)





-

200

400

600

800

1000

1200

1400

1600

-

100

200

300

400

500

600

700

800

Jun

-86

Jun

-87

Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary






Adaptive regulation




29 CME Group (2015)

30 CME Group (2010)




Law is code




31 Li et al (2015)










Number of words


Language perplexity







10 USC sect 101(a)(16)


37 USC sect 329

10 USC sect 641










(a) (b) (c)














(a) (b)





-

200

400

600

800

1000

1200

1400

1600

-

100

200

300

400

500

600

700

800

Jun

-86

Jun

-87

Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary






Law is code




31 Li et al (2015)










Number of words


Language perplexity







10 USC sect 101(a)(16)


37 USC sect 329

10 USC sect 641










(a) (b) (c)














(a) (b)





-

200

400

600

800

1000

1200

1400

1600

-

100

200

300

400

500

600

700

800

Jun

-86

Jun

-87

Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary












Number of words


Language perplexity







10 USC sect 101(a)(16)


37 USC sect 329

10 USC sect 641










(a) (b) (c)














(a) (b)





-

200

400

600

800

1000

1200

1400

1600

-

100

200

300

400

500

600

700

800

Jun

-86

Jun

-87

Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary












(a) (b) (c)














(a) (b)





-

200

400

600

800

1000

1200

1400

1600

-

100

200

300

400

500

600

700

800

Jun

-86

Jun

-87

Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary










(a) (b)





-

200

400

600

800

1000

1200

1400

1600

-

100

200

300

400

500

600

700

800

Jun

-86

Jun

-87

Jun

-88

Jun

-89

Jun

-90

Jun

-91

Jun

-92

Jun

-93

Jun

-94

Jun

-95

Jun

-96

Jun

-97

Jun

-98

Jun

-99

Jun

-00

Jun

-01

Jun

-02

Jun

-03

Jun

-04

Jun

-05

Jun

-06

Jun

-07

Jun

-08

Jun

-09

Jun

-10

Ag

gre

ga

te V

alu

e

Ind

ivid

ua

l B

an

k V

alu

e

Aggregate

Bank of America

JPMorgan

Wells Fargo




5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary






5 Conclusion










35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary








35 NTSB (1993)

36 FDA (2011)


References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary




References

























































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary













































2 See G20 (2009)












































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary














































































References
































Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary





















Automation










Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary





Decentralisation


Shift of activities







New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary





New activities





Summary




No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary





No Title Author

563 May 2016


562 May 2016


561 May 2016


560 May 2016



559 April 2016



558 April 2016


557 April 2016



556 April 2016


Gianpaolo Parise

555 March 2016



554 March 2016



553 March 2016



552 March 2016


551 March 2016



550 March 2016



549 March 2016



548 March 2016



547 March 2016




Foreword


Abstract

1 Introduction






The flash crash






Adaptive regulation

Law is code


5 Conclusion

References





References


Automation

Decentralisation

Shift of activities

New activities

Summary

