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Guest Lecturer: Technische Universität Chemnitz
Robert Balikrobert.balik@wmich.edu
Lecture on Tuesday, 12 May 2015
Professor Emeritus of FinanceWestern Michigan UniversityKalamazoo, Michigan, U.S.A.
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Thanks for enrolling Hope to meet your expectations
Willkommen/Welcome
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Presenter sweats Not the temperature Old age Disease Medication Side effect
Apologies
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Prof. Dr. Friedrich Thießen
Thanks
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James R. Palmitessa, Ph.D., Western Michigan University
Thanks
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Dipl.-Kfm. Thomas Maurer
Thanks
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Youth, in Iowa, Ph.D., University of Iowa
My Background
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1967 – 1970, Hanau, Germany, Fliegerhorst Kaserne
My Background
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Western Michigan University, 1985 – 2014, Finance Professor
My Background
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FIN 3450, Computer Applications in Finance Required course for undergraduate finance
majors Course taught most frequently Developed course: emphasized design, why
and how Included use of Excel, Access, and SAP
My Background
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FIN 6910, Finance Seminar Elective MBA finance course Entrepreneurship through acquisition of a
small to medium size business Practical finance meets academic “big firm”
finance
My Background
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Number: 5 Where: This lecture hall
These lectures
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Tuesday, 12 May 2015, 13:45 – 15:15 Wednesday, 13 May 2015, 13:45 – 15:15 Tuesday, 19 May 2015, 13:45 – 15:15 Wednesday, 20 May 2015, 13:45 – 15:15 Thursday, 21 May 2015, 11:30 – 13:00
Lectures: Dates and Times
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High Frequency Trading, HFT Data Visualization/Charts Time Value of Money Stock and Bond Valuation Capital Budgeting Excel Best Practices, 100+
May carry over from one lecture to next
Topics in 5 lectures
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https://homepages.wmich.edu/~balik/Chemnitz Copies of presentations◦PowerPoint◦Excel
PowerPoint slide shows have web addresses in notes section
Web site
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Pivo Balik
Important Czech Words
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Czech words, 1:
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German = Bier
English = Beer
Czech = Pivo
Czech words, 2
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Czech words, 2, continued
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Czech words, 2, continued
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Summary Overview Basics Definitions Speed Textbooks Motivation Trading
Outline
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HFT firms Communication firms Nanex Flash Crash Knight Dark Pools Exchanges Benefits and Costs Summary
Outline, continued
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Joseph Stiglitz Economist Nobel Prize Economics Speaking at Atlanta Fed 2014 Video https://www.frbatlanta.org/news/conferenc
es/2014/140415-fmc/media/stiglitz.aspx
Summary
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Overview: Past, NYSE
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Arbitrage Pure Competition Asymmetric Information Adverse Selection Moral Hazard Efficient Markets Insider trading Time units
Overview: Past, NYSE
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Overview: Public Companies
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Overview: Public Companies
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This chart displays the number of domestic U.S. companies listed on the NYSE, AMEX, and NASDAQ markets since 1997.
The chart does not include ADRs, ETFs, preferred stocks, “penny stocks,” warrants, or closed-end funds.
The number has dropped steadily from 7,337 in January 1997 to 3,626 at the end of 2012.
Overview: High Frequency Trading
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60 Minutes March 2014 Michael Lewis Video http://www.cbsnews.com/news/michael-lewis
-explains-his-book-flash-boys/
Overview: Video
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Arbitrage Pure Competition Asymmetric Information Adverse Selection Financial Markets Efficient Markets Insider trading Time units
Basics
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Same or equivalent good(s) Different markets Different prices What to do: Buy low, sell high
Basics: Arbitrage
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Option expiration date, minutes before end Observe following◦Price, Call option on ABC, 1 share = 4.75◦Price, Option exercise on ABC = 45◦Market price of ABC stock = 50
Ignore bid ask spreads, taxes, transaction costs No position in option or stock What is arbitrage opportunity?
Basics: Arbitrage, Finance Example
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But call, cost = 4.75 Exercise call, cost = 45 Result is one share of stock Cost of one share = 4.75 + 45 = 49.75 Sell one share, gain = 50.00 Gain = 0.25 = 50.00 – 49.75
Basics: Arbitrage, Example, cont.
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There is perfect knowledge, with no information failure or time lags. Knowledge is freely available to all participants, which means that risk-taking is minimal and the role of the entrepreneur is limited.
There are no barriers to entry into or exit out of the market.
Firms produce homogeneous, identical, units of output that are not branded.
Basics: Pure Competiton
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Each unit of input, such as units of labor, are also homogeneous.
No single firm can influence the market price, or market conditions. The single firm is said to be a price taker, taking its price from the whole industry.
There are a very large numbers of firms in the market.
Basics: Pure Competiton, continued
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There is no need for government regulation, except to make markets more competitive.
There are assumed to be no externalities, that is no external costs or benefits.
Firms can only make normal profits in the long run, but they can make abnormal profits in the short run.
Basics: Pure Competiton, continued
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A situation in which one party in a transaction has more or superior information compared to another. This often happens in transactions where the seller knows more than the buyer, although the reverse can happen as well. Potentially, this could be a harmful situation because one party can take advantage of the other party's lack of knowledge.
Basics: Asymmetric Information
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Risk of trading with a more informed counterparty
Consequence of asymmetric information
Basics: Adverse selection
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Convert information to prices
Information about cash flows
Cash flows, when, how much, risk
Efficient Market Hypothesis: speed & accuracy
Basics: Financial Markets
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First tenet is that you can’t predict the future from the past
Second tenet is that “price is right”
Basics: Efficient Market Hypothesis
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Markets convert information to prices Efficient markets relate to “speed” and
“accuracy” Even when information is public, who can act
the fastest can benefit If certain investors/traders consistently have
an “edge” what is impact?
Basics: Efficient Markets
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Term includes both legal and illegal conduct. The legal version is when corporate insiders—
officers, directors, and employees—buy and sell stock in their own companies. When corporate insiders trade in their own securities, they must report their trades to the SEC.
Basics: Insider Trading
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Illegal insider trading is buying or selling a security, in breach of a fiduciary duty or other relationship of trust and confidence, while in possession of material, nonpublic information about the security.
Insider trading violations can also be "tipping" such information, securities trading by the person "tipped," and securities trading by those who misappropriate such information.
Basics: Insider Trading, continued
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1/10 = 10-1 = ds = decisecond 1/100 = 10-2 = cs = centisecond 1/1,000 = 10-3 = ms = millisecond 1/1,000,000 = 10-6 = ms = microsecond 1/1,000,000,000 = 10-9 = ns = nanosecond
Basics: Time, Fractions of second
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EU = European Union MiFID, II MIFID = Markets in Financial Instruments
Directive Published in the Official Journal of the
European Union 6 December 2014 Implemented by 2017
Basics: Time, EU
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Clocks of trading venues and their customers be synchronized, standardizing the recorded time for post-trade data, transaction reporting and order event auditing
According to a summary posted by Fidessa, a British firm that provides investment infrastructure, technology tools and support services for traders.
Basics: Time requirements, EU
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The European Securities and Markets Authority wants high-frequency trading venues to synchronize their clocks to within a nanosecond, or one-billionth of a second, to help supervisors better track potential market manipulation
Basics: Time, EU, continued
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Subset of algorithmic trading, AT The use of extraordinarily high-speed and
sophisticated computer programs to generate, route, and execute orders
Use of co-location services and individual data feeds offered by exchanges and others to minimize network and other types of latencies;
Definition: HFT
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Very short time-frames for establishing and liquidating positions
Submission of numerous orders that are cancelled shortly after submission
Ending the trading day in as close to a flat position as possible (that is, not carrying significant, unhedged positions overnight)
Definition (continued): HFT
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Computer hardware and software Fast communication (fiber optic, micro-wave,
laser) Co-location (have computer at exchange)
Summary: HFT
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Co
Historic Example of Speed
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Paul Julius Reuter (Israel Beer Josaphat) Aachen terminal points of the German
telegraph Brussels terminal for French-Belgian
telegraph lines. Used pigeons to send messages (stock prices)
between Brussels and Aachen within two hours, beating the railroad by six hours.
Speed: Reuter, 1850
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Video 60 Minutes 2010 Computers in New Jersey Link to video: http
://www.cbsnews.com/news/robot-traders-of-the-nyse/
Speed Today
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Investments, 10 Edition, Bodie, Kane, Marcus McGraw-Hill/Irwin, September 2013 Index: High Frequency Trading, 71 – 73 Section 3.5 New Trading Strategies HFT part of algorithmic trading, Dark pools,
Bond trading, Flash Crash of May 2010
HFT: Textbooks, Not much discussion
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Investment Analysis & Portfolio Management Reilly and Brown Cengage Learning, December 2011 Index: High Frequency Trading, 111
HFT: Investment Textbooks
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SEC Regulation NMS 2007 Brokers execute trades at the best price Best price had to be obtained, no matter
where quoted or by whom All exchanges to make their quotations and
trade executions public
HFT: Primary motivation
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SEC 16 registered exchanges, 2014
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SEC, other exchanges, 2014
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U.S. HFT Trading
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Friday, June 1, 2012, 8:30 a.m. EST E-Mini futures, ESM12, traded on CME E-Mini = 1/5 S&P 500 futures 1 contract = $50*Value of E-Mini E-Mini about 1,290 1 contract = $64,500 = 1,290*50 500 contracts = $32,250,000 = 1,290*50*500 Negative news, Bids can’t adjust Example of asymmetric information arbitrage
HFT: Example, Job Numbers
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Video Job Numbers 8:30 a.m. EST Link to video:
http://premarketinfo.com/2012/06/01/hft-and-the-jobs-number/
HFT: Example, Job Numbers
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Handles: 1 point in contract Sample calculation◦Sell Futures at 1,290◦Cover, Buy, Futures at 1,285◦Did on 500 contracts◦Gain = $125,000 = (1,290 – 1,285)*50*500◦Time between sell and buy, less than 1 second◦
HFT: Example Job Numbers
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Allston Trading LLC, Chicago Hudson River Trading LLC, New York City Jump Trading LLC, Chicago Latour Trading LLC, affiliate of Tower Trading,
New York City Merrill Lynch, Pierce, Fenner & Smith, owned
by Bank of America Group; Charlotte, North Carolins
HFT firms, United States
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Octeg LLC, merged into KCG Holdings Inc., Jersey City, New Jersey
Tradebot Systems Inc., Kansas City, Missouri Two Sigma Investments LLC, New York City Two Sigma Securities LLC, New York City Virtu Financial, Austin Texas.
HFT firms, United States
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Oc
HFT firms: Two Sigma Securities
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Market Maker in over 8,000 securities
IPO April 16, 2015 Offering Price: $19 per share Ticker symbol: VIRT Trades on NASDAQ
HFT firms: Virtu
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HFT firms: VIRT
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Oc
HFT firms: Virtu
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HFT firms: Virtu
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Profitatiliby: Net Income/Revenue Virtu: 81/210 = 39% Apple: 9 months, Sep 2014, 40/183 = 22%
HFT firms: Virtu (SEC filing)
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HFT firms: Virtu (SEC filing)
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International Marketmakers Combination Privately-held company Founded in Amsterdam in 1989 Offices in Amsterdam, Chicago, Sydney, New
York, Hong Kong and Zug Employ more than 450 people Two independent businesses: ◦Financial Markets◦Asset Management.
HFT firms outside U.S.A., IMC
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GETCO
IMC
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HFT: IMC
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IMC is a leading Designated Market Maker (DMM) on the New York Stock Exchange (NYSE)
Providing liquidity in over 600 NYSE listed securities
Spread Networks, Fiber Optic Cable
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GETCO Citadel Virtu Financial Hull Trading
Save three milliseconds Estimated cost: > $200 million Completed June 2010
Spread Networks: Fiber optic cable
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http://www.quincy-data.com/expand-lowest-latency-microwave-services/
McKay and Quincy, Microwave
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http://www.quincy-data.com/expand-lowest-latency-microwave-services/
OAKLAND, Calif., Nov. 21, 2014 /PRNewswire/ — McKay Brothers Microwave service connected the last major co-location center on the Illinois-New Jersey long-haul network at the lowest known latency.
McKay and Quincy, continued 2
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HFT, Anova Tecnologies, Lasers
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HFT, Anova Tecnologies
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Anova, use laser devices for fast communication of market data
Lasers to Link the NYSE and Nasdaq data centers in New Jersey
Lasers to link London and Frankfurt
http://www.nanex.net/company.html
HFT: Nanex
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It's not high frequency trading (HFT) that concerns us. It's High Frequency Quoting (HGQ), and it should concern everyone.
http://www.nanex.net/aqck/2804.html
HFT: Nanex, Firm that keeps data
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Red = Quotes Blue = Trades A = Oct 10, 2008,
Financial Crisis B = May 6, 2010,
Flash Crash C = Aug 8, 2011,
U.S. Government Bond Downgrade
HFQ: Nanex
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Red = Volume Blue = Quotes CME All Contracts 2005 – Early 2015
HFQ: Nanex
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HFQ: Nanex
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April 24, 2012 15:51:44 Eastern time PSS World Medical (PSSI) Quotes for a single second in one stock set a
new record: 47,138. PSSI is not active: only 1,992 trades (317,127
shares) traded the entire day.
HFT: Nanex, 11 Exchanges
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Video 11 Exchanges Merck, Ticker = MRK 16 May 2013 10 milliseconds 11:17 a.m. 9.960 seconds Link:
https://www.youtube.com/watch?v=L5cZaIZ5bWc
HFT: Flash Crash, 10 May 2010
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HFT: Flash Crash
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April 2015 UK trader arrested for role in U.S. 'flash crash‘ The U.S. Justice Department had criminally
charged Navinder Singh Sarao, 36, of London, with wire fraud, commodities fraud and manipulation.
HFT: Knight
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Market Making firm August 1, 2012 Computer bug Lost $440 million $440 million = 4x 2011 net income 30 minutes Subsequent impact on stock: down 62%
HFT: Knight
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“Trades alternate between buying at the offer and selling at the bid, which means losing the difference in price. In the case of EXC (Exelon), that means losing about 15 cents on every pair of trades. Do that 40 times a second, 2,400 times a minute, and you now have a system that’s very efficient at burning money.” (Nanex, Eric Hunsader)
HFT: Dark Pools
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In dark pools, pre-trade prices – the price at which shares are offered for sale – are not visible to anyone, even the participants in them, and the price at which shares change hands is only revealed after the trade is done.
HFT: Dark Pools
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Buyers and sellers in dark pools hidden Trades may not be reported If reported, may be lumped with other
trades to obscure information about participants
HFT: Dark Pools, Trading, U.S.
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HFT: Dark Pools, Trading, Europe
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For first six months of 2013
Founded 2000 Headquarters: Atlanta, Georgia IPO, November 2005, Offering price = $26 Ticker symbol = ICE In S&P 500 index Price per share, 12 May 15 = $239.94 Market Cap = $26.+ billion (12 May 15) Owns and operates 23 regulated exchanges
and marketplaces (Wikipedia)
Exchanges: Intercontinental Exchange
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ICE Futures: United States, Canada, Europe, Singapore
NYSE NYSE ARCA (all electronic) NYSE MKT (small cap) NYSE AMEX Options NYSE ARCA Options NYSE Bonds
Exchanges: ICE Exchanges
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Exchanges: ICE, Web, Homepage
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https://www.intercontinentalexchange.com/index
Exchanges: BATS, Web, Homepage
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https://www.intercontinentalexchange.com/index
http://www.batstrading.com/
BATS = Best Alternative Trading System Stated as ECN in 2005 Location: Lenexa, Kansas U.S.: four equity exchanges — BZX Exchange,
BYX Exchange, EDGA Exchange, and EDGX Exchange — and regularly ranks as the top market for ETF
Europe: BATS Chi-X Europe, largest pan-European equities trading venue in terms of value traded
Exchanges: BATS
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HFT: Benefit, Increased Liquidity
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http://noahpinionblog.blogspot.com/2014/04/no-one-really-knows-if-hft-is-good-or.html
Summary
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High Frequency Trading costs real resources. It consumes computing power and the mental effort of smart people. When we decide if HFT benefits the world, we have to weigh these costs against whatever benefits HFT provides.
Noah Smith, blog
HFT: Costs
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The impact of HFT on informational efficiency is not well-understood, because it depends on adverse selection, whose action in financial markets is not well-understood.
HFTs effect on market stability No one really knows how much market
quality at high frequencies affects the economic efficiency of corporate investment decisions.
HFT: Research issues, Noah Smith
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Economist: Paul Samuelson Nobel Price Economics, 1957 Trading something one second before
everyone else is personally profitable and socially pointless
Source: Inter-temporal Price Equilibrium: A Prologue to the Theory of Speculation, Paul A. Samuelson, Weltwirtschaftliches Archiv, Bd. 79 (1957), pp. 181-221
Summary
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Economist: Paul Krugman Nobel Price Economics, 2008 Share of G.D.P. accruing to bankers, traders,
and so on has nearly doubled since 1980 Lot of money is going to speculative activities
that are privately profitable but socially unproductive
It’s the whole financial industry, not just HFT, that’s undermining our economy and our society.
Summary
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Two ways to reduce HFT Tax trades Change continuous market to, say, 1 second
intervals
Summary
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This slide show only a start to topic of HFT HFT firms use other strategies, such as front
running
Summary
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High-Frequency Trading Gives Way to Hyper-Contextual Trading (Juniper Networks)
Market data, news, and social media must be analyzed in real time to assess credibility and accuracy
Firms need to analyze and process a staggeringly massive quantity of information—a billion messages a second
What’s Next
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