tjef volume 2 issue 3 - … · 1 contents papers impact of black box trading in indian stock market...

1

CONTENTS

Papers

IMPACT OF BLACK BOX TRADING IN INDIAN

STOCK MARKET Gomathy Venkateswara & Rachana Bhat, T. A. PAI MANAGEMENT INSTITUTE, MANIPAL

PEER-TO-PEER LENDING: WHAT IS IT AND

WHERE IS IT GOING? Srajan Shrivastava, T. A. PAI MANAGEMENT INSTITUTE, MANIPAL

OIL-PRICE TRENDS: MAJOR FACTORS AND EFFECTS ON STOCK MARKETSNilesh Sagar & Yayati Mishra, T. A. PAI MANAGEMENT INSTITUTE, MANIPAL

THESIS ON MERGERS& ACQUISITIONS IN THE CREDIT-RATING SECTOR

Aadithyaa & Tanushree Mahapatra, SYMBIOSIS CENTRE FOR MANAGEMENT STUDIES,

PUNE

Page no. 5

14

28

37

2

Joel Pannikot Bloomberg

Prabhakar Reddy Patil

Securities and Exchange Board of India

Peter Kien Pham University of New South Wales, Sydney

Kok Fai Phoon

Singapore Management University

Edward Podolski La Trobe University, Melbourne

Arati Porwal CFA Institute

Sridhar Seshadri

Development Credit Bank

Cameron Truong Monash University, Melbourne

C. Vasudevan

Bombay Stock Exchange Limited

Jayaraman. K. Vishwanath DCB Bank Limited

Managing Editor

Editors

Advisory Editors

Isha Varma

Sponsored by

Tamal Bandyopadhyay Mint, Bandhan Bank Ltd

Yangyang Chen

Hong Kong Polytechnic University

Michael E. Drew Drew, Walk & Co.

Ravi Gautham Northern Trust

Anil Ghelani

DSP BlackRock

Anjan Ghosh ICRA Limited

Viswanathan Iyer

National Australia Bank

Madhu Veeraraghavan T. A. Pai Management Institute

Madhav Nair

Mashreq Bank

Suman Neupane Griffith University, Brisbane

Production Team Prasun Banerjee

Anil Shankar A P Animesh Gupta

Gandhali Inamdar Ishan Kekre

Junitha Johnson Kriti Sinha

Laxmi Mishra Nimisha Khattar Prasun Banerjee

Subhajit Bhattacharjee Vasudeva Kamath Vishaka Sivanainar

3

EDITORIAL

In the past few months, we have witnessed some historical events, which have the

potential to transform economies around the world.

From a global perspective, we saw Saudi Arabia and United Arab Emirates becoming

the first countries of Gulf Cooperation Council (GCC) to introduce Value Added Tax (VAT).

Economies around the world continue to explore new ways to extract oil hence making the

oil and gas sector unsettled and oil prices volatile. Venezuela became first sovereign country

to officially launch its own cryptocurrency called Petro backed by oil, gas, gold and diamond

reserves to overcome the US-led financial sanctions.

On the domestic front, we saw the finance minister Mr. Arun Jaitley presenting the

Union Budget just ahead of the upcoming elections in 8 states and the general elections to be

held next year. There were no changes made in the personal income tax however there were

some striking changes made in the other sectors. The fiscal deficit is at 3.5% of the GDP at

present and is projected to be 3.3% for the next fiscal year. The banking and financial sector

continues to leverage technology to come up with new innovations, one such evolving

concept being the Peer-To-Peer lending or P2P digital platforms. Another technology which

is expected to take over the financial markets in the near future is the Black box trading which

is a pre-programmed algorithm which generates buy or sell signals for a trader.

The Punjab National bank of India reported a fraud of $1.8 billion at a Mumbai

branch. This event sent shockwaves to the country’s financial sector and adversely affected

the stock market. The Idea-Vodafone merger is still under process; however the overall

outlook for M&A in India for the year 2018 seems promising as stated by Deloitte in a public

report.

Against this backdrop, we present 4 papers in this issue of TJEF on some of the above

key topics. We hope that the readers benefit from the insights of the papers published.

Managing Editor

Isha Varma

4

Aims and Scope

1. TAPMI Journal of Economics and Finance is a peer-reviewed journal. We seek

research papers in the areas of Banking, Economics and Finance.

2. The main purpose of the journal is to encourage quality submissions from business

students.

3. We encourage submissions from students enrolled in leading business schools in

India and abroad.

4. We also encourage submissions from practitioners.

5. Our aim is to provide constructive feedback on all submissions.

Disclaimer 1. Intellectual Property Rights – unless otherwise stated, the Editorial Board and the

authors own the intellectual property rights of the journal.

2. The decisions of the editorial board are final and binding.

3. You should not reproduce, duplicate, copy, sell, resell, visit, or otherwise exploit our

material without our written consent.

4. You should not republish material from this journal or reproduce or store material

from this journal in any public or private electronic retrieval system.

5. The authors must ensure that the sources are properly identified.

5

IMPACT OF BLACK BOX TRADING IN INDIAN STOCK MARKET

GomathyVenkateswaran

RachanaBhat

T.A.PAIMANAGEMENTINSTITUTE

INTRODUCTION Electronics and technology have always caused a paradigm shift in the world of

securitiesmarketstrading.Theorganizedfinancialmarketswereunsettledduringthe

evolutionfromtheopenoutcrysystemtothepresentelectronictradingsystem.This

brought an end to the era of trading floor and dealers. Similarly, there are several

controversies surrounding the advent of “Algorithmic Trading or High-Frequency

Trading”.Insimplewords,Algorithmictradingisaman-machinehybridsystem,where

ahumancontrolledprogramrapidlytransmitsinformationintomarketprices.These

systemsarelesserror-proneandmuchfasterthanhumansare.Thedownsideisthat

thislightningspeedtechnologyleadstoconcernsaboutmarketqualityandefficiency.

Theimpactofalgorithmictradingonmarketqualitycanbeanalyzedbycomparingthe

patterns when the algorithmic trading was low versus when the presence of AT

(Algorithmic Trading)was high. In this research paper,we have concentrated on a

datasetoftradesfromNSEforafive-yearperiodfrom2009-2013.Thedatasampleis

aptforthisstudyasNSEaccountsfor75%oftradesinIndia.Moreover,NSEidentifies

everyordercomingfromanalgorithmicsourceasATandtherestasnon-AT.

There are various concerns surrounding the increasing usage of AT. This research

paperthrowslightupontheinfluenceofATontheIndianstockmarketsandthemyths

associatedwithitalongthefollowinglines:

1. TheintensityofATinIndianstockmarkets

2. Impactonthemarketqualityandefficiency

We acknowledge the helpful comments and suggestions of the editors. Editor’s note: Accepted by Kriti Kanchan Sinha

⋅ Submitted on: 15/02/2018 ⋅ Accepted on: 16/02/2018 ⋅ Published on: 08/03/2018

6

ABOUTALGORITHMICTRADING

Asthestandarddefinitiongoes,analgorithmisaspecificsetofinstructionsaimedto

carryouta taskorprocess. Suchalgorithmsbasedon timing,price,quantityorany

mathematicalmodel for placing a trade in order to generate profits at a speed and

frequencythatisimpossibleforahumantraderiscalledasAlgorithmictrading(Black-

Boxtrading)[7].ExamplesofsomepopularstrategiesimplementedusingATare:

1. Movingaveragestrategy

• Buy100sharesofastockwhenits100-daymovingaveragegoesabove

200-daymovingaverage.

• Sell100sharesofastockwhenits100-daymovingaveragegoesbelow

200-daymovingaverage.

2. Arbitragestrategy

• Buysharesfromoneexchangeatalowprice;sellsharesinanother

exchangeatahigherprice.Itmakesuseofthedifferenceinmarket

prices.

Suchhigh-speedtradingalgorithmsmadeupofsimpleinstructionscanbeexploitedin

making profits. TheAT systems automatically keeps awatch on the live prices and

graphsandputsintheordermanuallybasedontheinstructions.ATspredominantly

arecodedbasedontechnicalanalysis.ApartfromthisATcangatherinformationfrom

microblogs, social networking sites, news sites andmany other sources distributed

acrosstheglobe.Similartohowanon-ATtradercannotcompletelyrelyontheabove

sourcesoranalysis,ATalsoneedstobeselectivebasedonthecredibilityofsources.

ThisputsbothATandnon-ATonthesamepedestalbutATisnotsubjecttohumanerrs

andismuchfaster,thushavinganedge.

Algorithmic trading andHigh-frequency trading are used interchangeably however,

there is a subtle difference between the two. High-frequency trading relies on low

latency environment and is a subset of Algorithmic trading. HFT leads to rapid

transmissionofinformationintomarketprices.

TheriseinATactivityhasledtomanyconcernswithregulatorsandinvestors.Thereis

ambiguityonwhetherATdemandsliquidityorsuppliesit,causesmarketdisruptions

likeflashcrashesorpreventsit. Inthesubsequentsections,thispaperdiscussesthe

aboveissues.

7

EXTENT OF ALGORITHMIC TRADING IN INDIAN STOCK MARKETS

Thoughlatetoadapttothetechnologicaladvancementsintrading,Indianstockmarket

hasnowtaken inalgorithmic trading.DirectMemoryAccess (DMA)wasallowedby

SEBIinApril2008.Thisdecisionwhichenabledclientstoaccesstheexchangetrading

systemsthroughbrokers’infrastructurewasawelcomedchangebythebankingand

securities market in India. Following this a year later, algorithmic trading was

permittedinIndia.CreditSuisse’sadvancedexecutionservices(AES)launchedATin

Indiaon22ndJune2009.AlgorithmictradinggainedmomentuminIndiaonlyafterthe

introductionofco-locationfacilitiesin2010.Initially,automatedtradingwasusedfor

equityspotarbitragebetweenNSEandBSEalone.Asignificantchangeoccurredafter

NSE allowed independent brokerages to set up their serverswithin their premises

whichimprovedlatencyfrom10-30millisecondsto2-6milliseconds.Thisinstigation

ofco-locationfacilityincreasedATintensityconsiderablyascanbeseeninFig1.The

abovegraphdisplaystheATintensityintheequityspotmarketfortheperiod2009-

2013.ATintensityismeasuredasthefractionofthetotalvalueofalgorithmictradesin

adaybythetotalvalueoftradesinthatday.Thelinedenotesthedayco-locationwas

introducedbyNSEintheIndianStockMarket.Priortoitsintroduction,ATintensity

wasaslowas20%.Inevitablypost2011ATintensityrosesharply.January2010toJuly

2011canbeviewedasanadoptionperiod,whereinmarketplayerswereprocuring

8

infrastructure to utilize the co-location facility. In 2012, the average value of AT

intensitywas50%anditsurgedfurtherto60%in2013.TheU.S.Marketstookadecade

toadapttoATincomparisontoIndianmarketswhereittooklessthanfiveyears.

Fromtheabovegraph,itcanbeobservedthatmajorchunkofordersthatNSEreceives

arefromalgorithmictraders.Moreover,mostofthesearelimitordersastheyaremore

flexible in comparison to the other special orders Nifty offers. Limit orders can be

modifiedorcanceledeasilyascomparedtomarketorders.Theusageofthestop-loss

orderhasbecomeobsoleteastheATitselfcomprisesofinstructionsonwhenthetrade

hastobesquared-off.Hence, fromtheabovedata, itcanbeconcludedthatwiththe

introduction of co-location, the volume of AT in the Indian market increased

exorbitantly.Theopennessofthemarketparticipantsandregulatorsisevidentfrom

such an overwhelming increase in algorithmic trades. However, this has led to

increasingconcernsbytheregulatorsinfearofill-effectsofAT.Inthenextsection,the

impactofATonthemarkethasbeenanalyzed.

IMPACT OF ALGORITHMIC TRADING ON LIQUIDITY IN THE MARKET Marketliquidityismeasuredbythenatureofordersexecuted.Whenanorderenters

the market and trades against an existing order, the new order is said to demand

liquidity,whereastheexistingorderissaidtohavesuppliedliquidity.

9

Fromtheabovegraph,itisevidentthatalgoonetrades(eitherthebuyerorselleris

Non-AT)formasignificantpartoftotaltradesexecuted.ThisconfirmsthatATdoesnot

overruleNon-Algorithmic trading. There is a healthybalancebetweenAT andNon-

Algorithmic traders even after a significant increase in the intensity of algorithmic

trades. In spiteof a rise inAT intensity, thevolumeof ‘Non-algoboth’ trades is the

highestinthemarket.Thisre-iteratesthatNon-ATtradersarenotdisadvantaged.

Investorsandregulatorshavealwaysbeenconcernedthatalgorithmictradersgainat

thecostofnon-algorithmictraders.Therearealsoalotoftalksthatalgorithmictraders

consumeliquiditymoreoftenthantheyprovideit.Inordertogatherinsightsonthe

above,tradescanbeclassifiedasATtoAT,ATtoNon-AT,Non-ATtoATandNon-ATto

Non-AT.Fore.g.,ATtoNon-ATreferstoatradewhereintheformer(AT)issupplying

liquidityandlatter(Non-AT)isabsorbingtheliquidity.

Allthetradesaredenotedasapercentageoftotaltradedvalueinthepiechartshown

above.ATtoATandATtoNon-ATarecaseswhereATsuppliesliquiditytothemarket,

similarlyintheothertwocombinationsATdemandsliquidityfromthemarket.Onan

averageATabsorbedordemandedliquidity64.05%timesoutofthetotal55.86%of

10

algorithmictradesthattookplace.Ontheotherhand,itsuppliedliquidityin65.49%of

thetotalalgorithmictrades.ThisshowsanearperfectbalancebetweenATandNon-AT

trades.WecanhenceinferthatATsuppliesasmuchliquidityasitdemands.

Is Algorithmic Trade responsible for ‘fleeting orders’ and ‘quote stuffing’? ThefirstqualmraisedbyopponentsofAlgorithmicTradingwasregardingthemarket

liquidity concerns. The next is that the liquidity provided by AT’s is “Apparent” or

“Fleeting”asitvanishesasthetraderwishestoexecutethetrade.

SEBIinordertoprotectthenormaltraderfromthefearofunfairandinequitableaccess

byAT,recentlyintroducedarule,“MinimumRestingTimeforOrders”.Inthissection,

theresearchpaperbringsevidencetobearonthisregulatoryintervention.Asperthe

rule,noordercanbemodifiedorcancelledwithin500msofbeingplaced.Theaimof

anymarketregulatoristopreventmarketabuse.Afleetingorderisonewhichisplaced

withintenttofalsifytheliquidityandprice.Oneoftheformsof‘fleetingorder’is“order

spoofing”. In this, a traderplaces anorder in theoppositedirectionof the tradehe

desirestobein.Forexample,asellermayplaceabuyorderpricedabovethecurrent

bidprice,andhenceinstigatetheotherbuyerstobidatthispriceoraboveit.Oncethis

occurs, the trader sells into this (higher) price. The order placed in the opposite

directionwillbecancelledimmediatelyandiscalledthespoofedorder.Fleetingorders

canbelegitimateaswell.Onesuchexampleis:

Traders who want to trade within the bid and ask price, continuously compute

(bid+ask)/2andrepeatedlyrefreshthelimitordertosellat0.1%abovethisprice.

Theabovestrategymodifiestheordereverytimethe(bid+ask)/2ratiochanges,which

ismoreoftenthanachangeinthelasttradedprice.Hencethistradingstrategyleadsto

morerevisionsperunittimewhencomparedtothenumberoftradesperunittime.

Evidenceof‘fleetingorder’canbeobtainedfromreal-timedata.NSEdataforNovember

and December 2013 has been made use for this purpose. The method used for

identifyingfleetingordersisasfollows:

• Identifyallthecancelledorders

• Outoftheabove,filterouttheordersthatwerecancelledwithinasecond

• Studythosedatathatwerecancelledwhennearthetouch((bid+ask)/2)

Inordertogetadeepinsight,thesecuritiesaregroupedaspermarketcapitalization.

ThesecuritieswithhighestmarketcapitalizationareinQ1andtheoneswithlowestare

11

inQ4.Thebelowgraphshowstotalno.oforderscancelledversusnumberoforders

cancelled within a second in the spot equity market. This is a more conservative

approachascomparedtoSEBI’s500ms.

The amount of orders cancelled within a second is maximum for highest market

capitalisation securities. The difference between the bid-ask price for highmarket

capitalisationsecuritiesiswidewhichstandstosupporttheabovetrendofhighest

cancellation.Todeterminewhatpartofthesecancellationsaccountto“fleetingorder”,

thefocusisshiftedtoorderscancelledwithinonesecondoftheirarrival.Theseorders

cancelledwithinasecondaredividedintofourcategoriesasfollows:

12

ThedatainTable2confirmsthatthepresenceoffleetingorderisminusculeinNSE

spot equitymarkets.Anoverwhelmingmajority of fast cancellationshappen away

fromthebestpricesanddonotfallunderthepurviewoffleetingorders.Thethree

categoriesotherthan“AtBestPrice”aretheonesthatshowhighercancellations.In

ordertogetthebestdeal,ATscancelordersinthiscategorymorerapidly.Hence,a

nearlytrueestimateoffleetingorderscanbeattributedtothecancellationsin“AtBest

Price” category. However, this 7.12 % seen for Q3 stocks on the spot market is

negligible.Thedataalsosuggeststhathighlyintensealgorithmictradeismaximum

for large market capitalization securities but they experience a low incidence of

cancellations.Thesefindingsre-iteratethatATsdonotcausefleetingordersthereby

theliquiditybroughtinbyATsisnottransitory.

IMPACT OF ALGORITHMIC TRADING ON PRICE EFFICIENCY

Extremepricemovementshavebeenamatterof concern in caseofAT. Inorder to

analyzethis,threethresholdvaluesforpricemovements2%,5%and10%havebeen

takenintoconsideration.Exampleifasharepriceis25,a10%pricechangewouldlead

tofluctuationbetween22.5and27.5(10%upordown).Ifthepricefluctuatesbeyond

thisrangewithina5-minuteinterval,thenitindicatesextremepricemovement.The

numberofsuchinstancesbyAThavebeenrecordedforthestudy.Forexample, if5

suchmovementsoccurwitha totalof25 trades ina5-minute interval, thevalueof

extremepricemovementmeasurewouldbe5*100/25=20%.Withthisextremeprice

movementmeasureasthedependentvariableandATandco-locationasindependent

variables,aregressionwasrun.Thecoefficientsoftheseindependentvariableswere

observedtobenotsignificantlydifferentfromzero.TheevidencesuggeststhatATdoes

nothaveasignificantimpactonextremepricemovementsandhence,leadstoasharp

dropinpricevolatilityinthemarket.

CONCLUSION Thequantumofordersplacedbyalgorithmictradingisstaggeringandaheadofnon-

algorithmic tradebyahugemargin.Clearly, algorithmic tradingandhigh-frequency

tradingrequireahugeinvestmentbuthasledtoarevolutionintheworldoftrading.

Thispaperaddressestheongoingfalsemythssurroundingthealgorithmictrading.It

can be established that AT is just a programmed, faster version of usual strategies

13

implemented by retail non-algorithmic traders.Market players and regulators have

beenconcernedabouttheimpactofATonmarketquality.OurfindingsshowthatAT

balancesoutliquidityinthemarketandalso,leadtomoreefficientpricediscoveryby

immediateincorporationofinformation.

Asisthecasewithalltechnologies,ATcomeswithitsownsetofcons.ATcanalsobe

manipulatedtoextractmaximumbenefitsandmayleadtodistortioninpricediscovery

process.Hence,itisofutmostimportancethattheregulatorscloselymonitorATand

levyasetofguidelinestoprotectthemarket.ItwasalsoobservedthatATintensityin

Indianmarketshasremainedfairlyconstantsince2013todate.Anotherbreakthrough

inATistheopportunitythatbrokerageshavebeguntooffertoretailinvestors.Multiple

IndianbrokeragessuchasZerodhaallowclientstoprogramalgorithmiccodes.Despite

this,HFTisstilloutofreachtomundaneindividualtraders.HFTrequireshugeamounts

ofinvestmentsandishighlyscrutinizedbytherespectiveexchanges.Lastly,itcanbe

concludedthatwiththerightamountofregulations,algorithmictradecanaddflavour

andqualitytothemarketandmakeitmoreefficient.

REFERENCES

1. Thomas,S.,Aggarwal,N.(2014,July).TheCausalImpactofAlgorithmicTradingonMarket

Quality.IndiraGandhiInstituteofDevelopmentResearch.

2. Aggarwal, N., Thomas, S. (2014, December 14). Algorithmic Trading and the NSE Equity

Markets: Has the market changed for the better? Indira Gandhi Institute of Development

Research.

3. Dubey,R.K.,Chauhan,Y.,Syamala,S.R.,(2017,December).EvidenceofAlgorithmicTrading

fromIndianEquityMarket:InterpretingtheTransactionVelocityElementofFinancialization.

ResearchinInternationalBusinessandFinance,42,31-38.

4. Securities andExchangeBoard of India. (2016,August 5).Strengthening of theRegulatory

frameworkforAlgorithmicTrading&Co-location.

5. Brogaard,J.(2010,November22).High-FrequencyTradinganditsimpactonMarketQuality.

6. Hendershott,T.,Riordan,R.(2013,August).AlgorithmicTradingandtheMarketforLiquidity.

TheJournalofFinancialandQuantitativeAnalysis,48(4),1001-1024.

7. Seth,S.(2017,May2).BasicsofAlgorithmicTrading:ConceptsandExamples.Retrievedfrom:

https://www.investopedia.com/articles/active-trading/101014/basics-algorithmic-

trading-concepts-and-examples.asp.

14

Peer-to-PeerLending:Whatitisandwhereisitgoing?

SrajanShrivastava

T.A.PAIMANAGEMENTINSTITUTE

ABSTRACT

Inthispaper,themajordiscussionprovidedishowP2Pisgoingtocompetewithits

classofNBFC’s,cantheyco-existandwhatroleRBIholdsforthefutureofthisdigital

platform through its regulation. There are also points of discussion on the lines of

differencefromcrowdfunding,whatledtothegenesisofP2Plendingandhowitgrew

fromothereconomies.P2Plendingisthenewestkidontheblockintermsofsecuring

small loans. It runs on a digital platform which matches two parties called the

borrowersandthelenders.Thelendersprovidetheloanstotheborrowersthroughthe

P2P lendingsite.WithP2P lendingplatforms leveraging technology to createanew

segment in securing loans, theyarepoised forahigher rateofgrowth theextentof

whichwillbeevaluatedinthispaper.

INTRODUCTION

With the recognition of Peer-to-Peer (P2P) lending companies as Non-Banking

FinancialCompanies (NBFC)by theReservebankof India (RBI) lastSeptemberand

formation of the first official body of P2P lenders, it is clear that the trend of peer

lendinginIndiahasfinallyarrivedandisheretostay.WithglobalP2Ppaymentsand

remittances touching a staggering $1 trillion globally towards the end of 2017 and

researchersestimatingaCompoundedAnnualGrowthRate(CAGR)ofamassive48.2%,

P2P lending businesses are the most attractive platforms currently in the finance

industry.

We acknowledge the helpful comments and suggestions of the editors. Editor’s note: Accepted by Vasudeva Kamath H and Subhajit Bhattacharjee


15

IntheIndiancontext,withanincreaseindemandforpersonalloansandmicrofinance

needs,theP2Plendingplatformcanserveasanaggregatorofmoneyandhelpcomplete

theborrowingprocessquicker as compared to the traditionalborrowingplatforms.

This iswhere lies the strengthofP2P lending,where it candifferentiate itself from

everyotherborrowingmediumthatcamebeforeit.

Figure1:Growth(in£billion)ofP2Plendingbusinesses

Source:RBI(April2016)

WHATISP2PLENDING?

Supposeyouhaveaquickcapitalrequirementoffivelakhsanddonotknowhowto

procuresuchalargeamountinashortduration.Youapproachyourfriend, let'scall

himMr.P,whoknowsofafewcontactswhoarewillingtolendbutsincetheirmoney

willbelockedawaywithyou,needsomereturnonthemoneytheyhavegiven.Your

friend negotiates with them and gets you the interest rate each lender desires.

Ultimatelyyoureceivethefivelakhsandputthemtouse.Apartfromthelendersyou

alsopayMr.Pasmallamountasatokenofgratitudeforhishelpingoutintimeofneed.

ConverttheabovescenariointoanonlinemodelanditiscalledPeer-to-Peerlending

whereMr.Prunsthesitetobringtogetherborrowersandlenders,youregisteryourself

asaborroweronthesiteandlendersarealreadyregistered.Onceyouputinarequest

forborrowing,lenderscanfundyourneed.Afterthis,youcaneitherdirectlynegotiate

withyour lenderormakeMr.Pdo it for you regarding the interest rates.Once the

16

contractislegallybindingtheamountistransferredtoyouraccountfromthelender's

account.Nootherpartycomesinbetween.

Source:HabileTechnologies.comSincethisonlygivesabriefabouttheprocess,letuslookintohoweachpartyinvolved

interactswiththeP2Pplatform:

• Borrower-Thefirstthingaborrower,inneedofmoney,needstodoisregister

tothesite.Theborrowerwillhavetopayaregistrationfee(whichismostlya

one-timedeal)anduploadthenecessarylegaldocuments.Oncetheregistration

isdone,theborrowerisanalysedforidentityproof,creditworthinessandrisk

bytheP2Pplatform.Basedontheanalysesbythesystem,analgorithmdecides

howmuchtheborrowerwillbeabletopaywithoutanyriskofdefault.Thisalso

servesasthelimittowhichamountcanbeaborrowedbyaspecificborrower.

Theborrowershavetomentionthemaximumrateatwhichtheyarewillingto

borrow.

• Lender -Lenderstoo, likeborrowers, followtheprocessofregisteringtothe

siteandpayingaone-timefee.Thelenders,however,areprovidedwithoptional

facilitiesfromtheP2Pwebsitelikelegaladvice;creditprofileoftheborrower

etc.thatcanincreasethefeesofthelenderaccordingtotheoptionavailed.The

P2Pplatformprovidestheserviceofcollectingthe loanrepayments fromthe

17

borrowerandhelpskeeptrackofthelender'smoney.Thelendersalsohaveto

mentionatwhatinterestratetheyarewillingtolend.

• P2PPlatform-Theyareresponsibleforrunningthesite,performingathorough

checkofthelenderandborrower,negotiatingtheinterestratesbetweenthetwo

partiesandfacilitatingloancollection.Apartfromthese,eachsitecanhavetheir

own value proposition to differ from its competitors. The platform is also

responsibleforthealgorithmtodeterminetheborrower'scredit limitsothat

defaults areminimized. They have tomake sure that all conditions and pre-

requisitesarefollowedbyboththelenderandtheborrower.

Incaseofadefaulttheyhavetoassistthelenderintherecoveryprocess,which

islimitedtothelegalprocedurementionedontheirsite,alsoreadbythelender

atthetimeofsigningup.Thereisanotherimportantfunctionthattheplatform

has to perform, and that is matching of the interest rates of borrowers and

suppliers.Asboththepartieshavespecifiedtheirchoiceof interestrates,the

companyhas tobuildanalgorithmtomatchboth thepartiesafterwhich the

lenderscanproceedtoacceptance.Amethodcalled‘reverseauction’isusedto

hedgethelevelofexposure.Eachlendercanonlycontributeaportionofthetotal

requirement of the borrower. Hence, the platform has to have an algorithm

where each portion of the borrower’s requirement is funded in amanner of

increasingratetillitisfullyfundedfromeachlender,accordingtotheirdesired

rate,butisbelowthemaximuminterestratesetbytheborrower.

WHYWASAP2PLENDINGPLATFORMCREATED?Peer-to-PeerreferstosharingamongstusersoftheinternetandhenceP2Pcameabout

firstinthetechnologyindustry,specificallycomputernetworking.Wearealreadyprivy

tosomemajorP2Psharingplatforms,themostmajorbeingBitTorrentwherefilesare

sharedamongsttheuserswithoutanydependenceonacentralhostingserver.Itcan

becalledmoreofaConsumer-to-Consumermodelandhereinliesitsstrength.Thereis

nointermediarystoppingtheflowordelayingtheprocessofinteractionbetweenpeers,

hencethecommunicationbetweenpartiesisfasterandmorepersonal.Itcanbesaid

thattheentireinternetisinitselfalargeP2Pnetwork.

The firstP2P lendingplatformoriginated in theyear2005.ThecompanywasaUK-

basedP2PfinanceplatformcalledZopaandexiststilldate.Overtheyearsithaslenta

18

totalof£3.03billion(Rs.27000Crore)toUKconsumersandhasaround60,000active

investors.(Zopa,2018)ThesewerefollowedbyAmericanP2Plendingcompanieslike

Prosper(2006)andTheLendingClub(2007)whicharenowgiants intheAmerican

P2Plendingindustry.Thisgrowthhasbeenpossibleduetocertainfactorsuniqueto

P2Plendingplatforms:

• TechnologyInnovation-Usingalgorithmstoautomatecreditreviewprocess

ofborrowersandlendersaswellasuploadingofnecessarydocumentsinstead

ofphysicallyreproducingitspeedsuptheentireprocessoflendingandmakes

ithassle-free.

• Providing credit to all kinds of borrowers - Certain borrowers are

disqualified from borrowing from Financial Institutions. In P2P lending,

everyoneisallowedtoborrowandtherearenorestrictionsplacedonthem.

• Higherinterestratestolenders-Forborrowerstheinterestratescurrently

fluctuate between 12%-35%, providing returns to lenders which are much

higherthantraditionalsourcesofinvestmentsinbanks.

• Transparency-Sincetheentireprocessofseeingwhotheborrowersare,the

interestratesbeingcharged,andnegotiationbetweenlendersandborrowersis

completelytransparent,theentireP2Plendingfeelsmoretrustworthyamongst

thetwoparties.

CROWDFUNDINGV/SP2PLENDINGAcommonmisnomeramongmanywhichevenRBIhad toclarify in itsconsultation

paperwasthedifferencebetweencrowdfundingandP2Plending(oftenreferredtoas

crowdlendingaggravatingtheconfusion):

Crowdfunding P2PLending

Modeofraising

In Crowdfunding, individuals back a

project because they either need the

outcomeof thatprojectorwant to take

ownershipinthecompany.Thereturnto

theinvestorisultimatelyintheformofa

productorownershipandnotintheform

Modeofraising

InP2Plending,lendersexpectliquidcash

backoncetheyhavetoaborroweralong

with a certain amount of interest. It is

moresimilartodebtfinancing.

19

ofliquidcash.Thisresemblesequityand

reward-basedfinancing.

Detailsoffinancingneed

Incrowdfunding,detailsoftheprojectfor

which financing is needed has to be

mentioned.Itisinawayanelevatorpitch

toallprospectiveinvestorsoftheproject.

Detailsoffinancingneed

InP2Plending,thepurposeofloandoes

not have to be revealed. The necessary

details to perform a creditworthiness

analysis of the borrower is all that is

required.

Purpose

This platform is mostly used to fund

projects that require some major

investment either in a creative project,

innovativetechnologyorrealestate.

Purpose

Mostof theP2Pborrowingsare to fulfil

personalneedslikerefinancingpersonal

loans, small yet immediate cash

requirements.

REGULATIONSSETBYRBIAfterreleasingitsdiscussionpaperinApril2016,RBIfinallycameupwiththenorms

toregulatetheP2PlendingenvironmentinSeptember2017.RBImandatedthataP2P

lending company has to be treated as an NBFC and is given the title Peer-to-Peer

LendingNBFC(NBFC-P2P).SomeothernotablerulessetforanNBFC-P2Pare:

• Registration

Acompanyhastoberegisteredasacompanyandthenapplyforacertificatewiththe

RBIforanNBFC-P2PtocommencetheactivitiesofP2Plending.

• Net-ownedfunds

ForabusinesstoapplyforanNBFC-P2Plicense,thecompanyshouldfirsthavenet-

ownedfundsofRs.2Croreorhigherfailingwhichthelicensecannotbegranted.

• Activities

Thecompanyshouldonlyactasanintermediaryprovidinganonlinemarketplaceto

the parties involved in P2P lending. It should not provide any credit guarantee or

securedloans.Alltheloansprovidedhavetobeclean.Thecompanyshouldnotholdon

20

itsbalancesheetfundsprovidedbythelendersorborrowers.Anotherimportantpoint

is that thereshouldbeno international flowof fundsand thecompany is limited to

fundswithinthecountry.Atthesametime,allthehardwareandprocessingcapabilities

havetobesituatedwithinthecountry.

• PrudentialNorms

LeverageratiowhichisTotalOutsideLiabilitiesdividedbyNet-OwnedFundsshould

notexceed2.Thereisacapputontheamountoflendingandborrowingapersoncan

doatatimeandthatisRs.10,00,000.Also,asinglelendercannotlendmorethanRs.

50,000toasingleborrower.Thisisdonetoreducethelevelofexposureofalender.

RecoveryprocessesofNBFC’shavetobefollowedwithaproperredressalmechanism.

Tokeepacheckmoneylaundering,theP2Pcompanyshouldmakesurethatthefunds

aretransferredfromlender’sbankaccounttotheborrower.

TheseareafewofthenotablenormssetbytheRBIwhichwewillusetofurtheranalyse

the P2P lending platform. The complete notification is available on RBI’s official

website.

CanP2PlendingaffecttheNBFCbusiness?

ThoughP2P lending is consideredanNBFCby theRBI, it innowayoperates like a

traditionalNBFC.Ratheritcanbecalledanewformoflendingbusinessthatdirectly

competes with the traditional model of NBFC’s as we will see in the comparison

mentionedbelow:

NBFCv/sP2PLending:

Non-BankingFinancialInstitution P2PLending

CreditApproval

In an NBFC a conventional format of

creditappraisalisfollowedwhereinyour

credit score (CIBIL Score) matters.

Hence, if it is below their minimum

requirementaloancannotbesanctioned.

CreditApproval

P2Pplatformsusetechnologytoevaluate

the creditworthiness of a borrower and

arenotreliantonacreditscore.

ApprovalTime ApprovalTime

21

InanNBFCitusuallytakesafewweeks

to complete the loan approval and

disbursement process after all the

verificationisdone.

In a P2P platform the funds are readily

available and as soon as the lender

acceptswhichborrowertolendto,there

isanonlinetransfermakingtheprocess

restrictedtolessthanaweek.

Targetcustomer

NBFC’s mostly target rural and semi-

urbanpopulationandplayavitalrolein

the financial inclusion of the Indian

population.

TargetCustomer

P2P lending at present is targeting the

tech-savvypartof thepopulationwhich

will mostly consist of people from the

urbanandsemi-urbanpopulation.

PreviouslyNBFC’swerecompletelytraditionalintheirapproachtoprovidingloans,but

nowtheyhavestartedleveragingtechnologytoquickentheprocessofloansanctioning.

ButthisadoptionofNBFCisstillalaggardwhencomparedtoP2Plendingcompanies.

ApartfromallthereasonsmentionedonwhyP2Pcanbepreferred,thereisonemore

reason that ismaking people (mostlymillennials) shift towards this platform. That

reasonisReturnonInvestment(ROI).Thevolatilityofmarketsalongwithdeclining

returnsontimedepositsinbankshavemadepeopleshifttolendingintheP2Pplatform.

This is because lenders can generate interest returns of up to 35%. Theminimum

return too isabove10%which iswayabovea traditionalbank investment scheme.

Borrowersalsoarerewardedwithlowerinterestratesiftheircreditworthinessishigh.

It might seem convincing that P2P lending platforms can easily outperform and

takeoverNBFC’s,buttherearecertainreasonswhereP2Plendingfallsshort.Sincethe

borrowersregisteredonanyP2Pwebsiteareoftenmorethanthelenders,thereare

financingneedsofmanytobefulfilledbythelenders.Thisincreasesthechancesofrisks

since P2P financing is mostly used for personal purposes and not in an income

generatingactivity.Henceborrowersalwayscarrytheriskofdefault.Also,thecredit

requirementsandmicro-financingneedsoftheruralandsemi-ruralareascannotbe

fulfilledbyP2Plendingasitiscompletelyadigitalplatform.Theseareashavetorely

onlyonNBFC’sfortheirrequirements.ThereachofP2Plendingsitesisalsoabigissue

as theyhavetorelyononly investors for theirgrowthsince thiskindofbusiness is

toughtounderstandandcanbeperceivedbythe‘BabyBoomers’and‘GenerationX’to

22

be unsafe. Hence, these points serve against P2P lending companies making the

presenceofNBFC’sequallyimportant.

CurrentAdoptionandFutureofP2P

Currently,thereare50registeredonlineP2Plendingplatformsandfewnotableones

arefaircent.com,Lendenclub,Lendbox,i2ifundingetc.

Source:Faircent.com

Fromthegraph,itisclearhowquicklytheplatformisexpandingasfromfaircent.com

alone the loanrequestshavegoneupbyclose to40% inaperiodof6months.The

IndianP2Pmarketisexpectedtogrowto$4-$5Billionby2023.Globallytoo,theyear-

on-yeargrowthfrom2016-2022isexpectedtogrowat51.5%.ThismeansthatP2P

lendingisthefastestgrowingbusinessintheworld.

ApartfromIsraelandJapan,whereP2Plendingplatformshavebeenbanned,mostof

theworldisembracingthisfast-growingindustry.InIndia,italignsperfectlywiththe

vision of Prime Minister Mr. Narendra Modi to digitize the Indian economy.

Demonetization,ontheotherhand,wasalsoamajorcontributortothemovementof

peopletoP2Plendingastheydidnotwanttorelyonbanks.Thefutureadoptionseems

tobestrongfortheIndianP2PindustrywhichwillbecloselymonitoredbyRBInow

thatitisbeingregulated.Overtime,lawswillberevisedbytheRBItomakeP2Plending

anevenmoresecureandtrustworthyplatform.

WhatisevenmoreimportantishowNBFC’sandP2Plendingcompaniesevolve.Will

theyberivalsorwilltheylearntoco-exist?Bothareinasimilarlineofbusinesswhere

NBFC’scanbeconsideredthetraditionalarmandP2Pcanbeconsideredasthedigital

arm. A probable future can bewhere bothNBFC’s and P2P lending companies join

23

hands fusingtheexpertiseofNBFC in lendingwiththetechnicalcompetenceofP2P

lendingcompaniestocatertoallsetsofcustomers.

Conclusion

ItallboilsdowntohowP2Plendingplatformsareabletomodifytheperceptionofthe

Indian population towards the safety of their platform. P2P lending platforms are

laudedfortheirlowdefaultanddelinquencyrates.MostP2Plendingplatformsglobally

statethattheyhaveclosetozerodefaultrate.Thesestatementsshouldbetakenwitha

pinchofsaltasthecurrentaveragefordefaultratesinP2Pplatformsrangefrom10-

20%withdelinquencyratesbeinglessthan5%.(TheLendingClubusedforreference

asitisabigplayerintheP2Pindustry)

LendingClubDelinquencyRate

Source:NSRInvestIn India, the default rate is currently less than 10% which is due to only a small

populationbeingexposedtothisavenue.Asmorepeoplejoininthedefaultratesare

expectedtoincreaseandhencesupportfromRBIwillbeakeyfactor.

NBFC’s in2017hadadelinquencyrateofaround24%andaGrossNon-Performing

AssetRatio(GNPA)of5%.Also,theNBFCindustry(excludingNBFC-P2P)isexpected

tohavea22%growthintermsofcredit(CARE,2017).Thisisaverygoodgrowthrate

considering how long NBFC’s have existed in India. However, compare this to P2P

lendingplatformswhichareexpectedtogrowy-o-yatcloseto50%andwecansee

which platform the economy is most excited about. In the coming years, the P2P

24

platform can eat into the business of NBFC’s unless they evolve their current

architecturetoleveragetechnologyfortheirbenefit.

RBI in itsdiscussionpaper inApril2016hadhighlightedavery importantaspectof

regulatingP2Plendingplatforms.Itwasawarethatifitinterveneswiththebusinessof

theplatformtherewouldbechancesoftheadoptionratebeinglow.Thesamereason

iswhatattractsinvestorstothecryptocurrencyworld,i.e.,lackofregulation.However,

RBIwithitslatestregulationshasdecidedtoregulatetheP2Plendingplatformwithout

affecting the businessmodel. It ismore of a hands-off approach to help the Indian

investordevelopfaithandatthesametimenotaffectthefunctioningoftheplatform.

Thiscanbeseenfromalltheregistrationandprudentialnormsset(mentionedinthe

regulationssubheadabove)whicharemostlytosafeguardtheinterestsoftheborrower

and lender on the platform. The cap of Rs. 10,00,000 is to promote only individual

investorsandnotbringinHigh-NetIndividuals(HNI’s)andlargebodycorporatesinto

thesystem.Theinabilitytoappealtoaforeign

Aninvestorisjustifiedasthatisanindustrystandard.EveryP2Pplatformislimitedto

itscountry itself.RBIshouldbeapplaudedfor itsbeautifullycraftedpolicies forthis

platform which will allow it to grow organically and become a relevant source of

investmentinthenearfuture.Ultimately,onethingisclear:P2Plendingisheretostay,

whetherit’llbelikedornotissomethingthispaperattemptedtoclarify.Onlythefuture

willmakeitclearwhichsideofthecoinprevails.

References

1. ReserveBankofIndia.(2016,April).ConsultationpaperonPeertoPeerLending.

2. Hernandez,R.,Altham,R.(2015,February).Peerpressure:Howpeer-to-peerlending

platformsaretransformingtheconsumerlendingindustry.Retrievedfrom:

https://www.pwc.com/us/en/consumer-finance/publications/assets/peer-to-peer-

lending.pdf

3. Milne,A.,Parboteeah,P.(2016,November).TheBusinessModelsandEconomicsofPeer-

to-PeerLending.EuropeanCreditResearchInstitute,17.

4. Roure,C.,Pelizzon,L.,Tasca,P.(2016).HowdoesP2PlendingfitintotheConsumerCredit

Market?DeutscheBundesbank,30.

5. AssochamIndia(2016).Non-BankingFinanceCompanies:TheChangingLandscape.

Retrievedfrom:https://www.pwc.in/assets/pdfs/publications/2016/non-banking-

finance-companies-the-changing-landscape.pdf

25

6. Statistics.(2018).Retrievedfromhttps://www.faircent.com/view/stats

7. Simpleloans,SmartInvestments.(2018).Retrievedfromhttps://www.zopa.com/about

8. Bhuvaneswaran,S.(2017).IsP2PLendingreallyathreattoNBFC’s?Retrievedfrom:

https://habiletechnologies.com/blog/is-P2P-lending-really-a-threat-to-nbfcs/

9. Peer-to-PeerLending(P2P)(2018).Retrievedfrom:

https://www.investopedia.com/terms/p/peer-to-peer-lending.asp

10. Saleem,S.Z.(2017).Peer-to-peerlendersarenowNBFC’s.Retrievedfrom:

http://www.livemint.com/Money/eNi7qnKVQvZTSyxbuDxNTP/Peertopeer-lenders-are-

now-NBFCs.html

11. Chamolee,S.(2017).CanP2PlendingkillNBFC’s?Retrievedfrom:

https://www.techbullion.com/can-P2P-lending-kill-nbfcs/

26

OIL-PRICE TRENDS: MAJOR FACTORS ANDEFFECTSONSTOCKMARKETSNileshSagarYayatiMishraT.A.PAIMANAGEMENTINSTITUTEINTRODUCTION

Oilisthelargesttradedcommodityanditsglobalpriceshavebeeneverunpredictable

withtheoilmarketspronetoinnumerouscyclesofboomandbust.Thenotionofwhole

supply-demand tactics being controlled by the nations possessing oil reserves have

beenputtowasteasnewnationscameupexpandingnewpossibilitiestodigoil,the

recentmostexamplebeingUSAwithitsshalegas.Thewholefundamentalofacycleis

elaboratedahead.Whennewprojectsofoilextractionstartcomingupwhilethereisa

supplyshortage,investorsinvestmoreandmoreduringthehighpricetime-frame,only

toseethevalueoftheiroutputcrashoncealargenumberofnewfieldsbeginoperation.

Thisphenomenonforcescompaniestocutbacktheircapitalexpenditure,reducingthe

growthinsupply.Ultimately,thepricesstarttoriseagainandthewholecyclebegins

anew.Theperiodofrecession(2008-09)sawWTIoilpricesreachaslowas35$per

barrelwheneconomicdemand stoodat its lowest ebb.Again theprices sawsteady

incrementthrough2010-2014whenpricescrossed100$perbarrelmarkduetorapid

increaseindemandbytheoil-importingdevelopingnations.Thecyclewasbrokenin

2015andcurrently,weseearisingpricewithpresentWTIoilpricehoveringaround

60$perbarrelrange.

We acknowledge the helpful comments and suggestions of the editors. Editor’s note: Accepted by Prasun Banerjee and Laxmi Mishra


27

WTIoilprices(2006-2018)Any formof certainty can’t bederived that this cyclewill again see theprice levels

crossingthe100$perbarrelmarkbecausethedynamicsischangingmakingthesector

everunpredictable.GoldmanSachsrecentlyputforwardanoutlandish6-monthprice

targetof82.50$perbarrelexpectingasimilarcycletorepeatbasedonthepasttrend.

But,thisistotallyquestionableandit’samatteroftimetoseehowthedynamicsunfold.

TheglutofsupplybytheUSAmaynotletthepricelevelsexceedthe60$markandOPEC

willhavetocutbackonproductionifitwantstoretainitslion’sshareofthemarket.

While the uncertainties on all these speculations prevail, we in this article, try to

establish a relationbetween theseprice shocks and the stockmarketswithvarying

investorsentimentsbecauseoilplaysasignificantroleineveryeconomy.Thiscanbe

illustratedusingthefollowingdiagram:

28

OPEC’SMARKETDOMINANCE

WebuilduponthepaperbystatingtheedgeenjoyedbyOPECinthecompetitiveoil

sector.Itwasonlyin2015thatUSfoundnewwaysofexploitingitsshalegasreserves

andenteredthescenarioasagamechanger.Thegraphclearlysuggeststhedegreeof

OPEC’s market power. Several studies have shown that OPEC is envisioned as a

dominant firm,always setting itspriceasamark-upovermarginal cost,whilenon-

OPEC nations just act as a competitive fringe. The extent to which OPEC member

countriesutilizetheiravailableproductioncapacityisoftenusedasanindicatorofthe

tightnessofglobaloilmarkets,aswellasanindicatoroftheextenttowhichOPECis

exertingupward influenceonprices.A cleardepictionof this canbe seenas theoil

pricesshotupduringtheperiod2003-2008whenOPECwasn’tabletomeettheglobal

demandsduetoasteepriseintheconsumptionbyUS,ChinaandIndia.Thegeneral

livingstandardswere increasingandcountries likeChinaand India,alongwithGulf

nationswhoseretailoilpricesarekeptbelowglobalprices,contributed61percentof

the increase in global consumption of crude oil from 2000 to 2006, according to

JPMorgan.

OilpricesstartedrisingasOPECdecidedtoenactonitsproductioncutsin2018.OPEC

initiateditsproductioncutsby1.2Millionbarrelsperday(MBPD)fromJanuary2017.

Tradersinresponsetothis,bid$65perbarrel,a30-monthhigh.OPECisbattlingUnited

StatesShaleoilformarketshare.DuetoShaleproducers,U.Soilproductionincreased

to9.4mbpdin2015.ThisstephittheOPECmarketshareandincreasedsupplycaused

oilpricestofall.Thatcreatedadisruptioninoilindustry.

29

OPECtargetsthepriceforoilataround$75abarrel,butdoesn’twantpricetojumptoo

high,asanalternative fuelsourcewill start to lookgoodagain.On thecontrary,U.S

shale producers need $40-$50 a barrel to pay the high yield bonds they used for

financing.Tomaintainmarketshare,OPECkeptitspricelowuntil2016.

Usually,oilandgaspricescanbepredictedbyaseasonaltrendastheyseemtorisein

springanddipinwinters.Futurestradersanticipateincreaseddemandforthesummer

vacationdrivingseason.Dollardecline isonemorefactorthat leadstodecline inoil

prices. MOST oil contracts around the world are traded in dollars. Therefore, oil-

exportingnationsusuallypegtheircurrencytothedollar.Asthedollarvaluedeclines,

hencetherevenuesfall,butthecostsshootup.Tomaintainitsprofitmarginsandkeep

thecostsofimportedgoodssame,OPECmustraisethepriceofoil.

OPECstillenjoysthemostdominantmarketshareintheworld’soilproductionandit

canbeinferredthatanydynamicschangeintheOPECnationswillhaveasignificant

impactontheoilpricesglobally.

30

DOESOILPRICEUNCERTAINTYMATTERTOMARKETS

Escalatinguncertaintyisgenerallyaccompaniedwithdecliningstockprices,because,

whenuncertaintyescalatesstockvaluationand investmentdecisionmakingbecome

more difficult. Uncertainty-averse investors require a premium for investing in the

stocks that are exposed to the systematic uncertainty factor. Oil is a similar,

unpredictableanduncertainsector.

Since oil price uncertainty negatively affects macroeconomic variables such as

investment,aggregateoutputanddurablesconsumption,itisalsoanimportantfactor

for stock valuations. Studies show that an oil price shock affects the stockmarkets

negatively,however,oilpriceshockisnotapricedriskfactoranditdoesnotaffectthe

discountrateortheequityriskpremium.Documentingthesameresultsforoilprice

uncertaintywecanconcludethat,althoughit isrelevantfortheoveralleconomy,oil

priceuncertaintyisnotasystematicallypricedfactorthataffectstheexpectedreturn

ofeverystockacrossevery industry.Oil-price-basedreturnpredictabilitycannotbe

explainedbyatime-varyingriskpremium.Although,oiluncertaintyisnotapricedrisk

factorforalltypesofstocksandthereforeitisdiversifiableacrossindustries,itactsas

31

priced within oil-relevant industries. In each of these industries, stocks that are

negativelyaffectedbyoilpriceuncertaintyshocksarecompensatedwithsignificantly

higher returns. Hence, based on priced risk premium on oil, we can have a clear

segmentationofthemarketofstocksthatrespondtooilpriceuncertaintiesandthose

which do not. Hence, oil price uncertainty is a sector-specific factor which can be

diversifiedacrossindustries.Industry-specializedinvestorswhoholdportfoliosofoil-

relevantstocksmustconsidertheirexposuretotheoilpriceuncertaintyshocks.

IMPACT OF DEMAND-SUPPLY OIL SHOCKS ON CORRELATIONBETWEENOILPRICESANDSTOCKMARKETINDICESWefurthertakeadeeperlookintothisrelationbetweenoilpricesandthemarketand

trytofindwhetherthereismuchrelevanceinthefactornot.Ifuncertaintiesintheoil

pricesreallyhaveaconsiderableeffect,thiswouldbeevidentinthecorrelationalmodel

tests. The prices have varied considerably all along since 2000’s. There have been

several instances when the prices dropped drastically due to economic crises and

occasionswherepricesshotupoutofcontrol.Governmentsubsidizedmarketshave

beenrelativelysecurebutstill,notbyagreatextent.Effectshavebeenthereandhave

beenprominent.TherecentglutofoilsupplybyUSisagainindicatingapriceshock

although,presentlyweseerisingprices.Theeffectwillbevisiblesoonandcertainly,

the correlation between the prices and the market will get affected. This can be

elaboratedbystatingtheeffectofoilpriceshocksontheeconomyinthreeprominent

ways.Firstistheeffectoninflation,whichcauseschangesinproductioncosts,thereby

shiftingsupplycurves.Second is theeffectonbalanceofpayments foroil importing

countries, further affecting exchange rate. Third effect is on the micro level of

householdsasoilformsamajorcomponentofanyhouseholdconsumption.

ArecentresearchpaperbyNadal,SzkloandLucena(UniversidadFederaldoRiode

Janeiro,RJ,Brazil)triedtoquantifythiseffectbyadoptingaDCC-GARCHcorrelation

model.TheresearchwasprimarilybasedonS&P500stockindex.Thefindingsrevealed

thataggregateandprecautionarydemandshockspositivelyaffectedthecorrelations

betweenchangesincrudeoilpricesandstockmarketreturnsmainlyfromtheendof

2007untilmid-2008,duringtheapexoffinancialmarketvolatility;fromthebeginning

of2009untilmid-2013,duringglobaleconomyrecoveryfromthefinancialcrisis;and

after 2015, when uncertainties about the Chinese growth and the US economy

32

upturningarose.Theinfluenceofaggregateandprecautionaryshocksonthereturnsof

WTIoilpricesandS&P500stockindexshowedacorrelationcoefficientof0.18.Even

after the removal of demand shocks effects, the average dynamic conditional

correlationbetweenthereturnsofWTIcrudeoilpricesandS&P500indexremained

positiveat0.13.Theresearchpaperconcludeswith its findingsthatstock indicesof

majoroilexportingnationsshowhighpricedependencyandtheemergingoilimporting

nationsarelessvulnerabletothechanges,mainlybecauseofgovernmentsubsidies.

Itcanbeinferredagainwhatwestatedinourprevioussectionthatinvestorshaving

oil-relevant stocks in their portfolios must be watchful of the economic turmoils

affecting thepricesofoil and tryhedging risksbydiversifying intonon-oil-relevant

sectors.FromanIndiancontext,wecanhavesomeassuranceofsafety,thankstothe

government

DemandshockseffectsondynamiccorrelationsbetweenS&P500returnsandWTI

crudeoilpriceschanges,fromJune2006toJune2016

INVESTORSENTIMENTANDTHEPRICEOFOILWesawhowOPEChasbeenaprimefactorinthevolatilityofpricesofoilglobally.Any

demandsupplymismatchby theOPECcausesrippleeffectsallover themarketand

makesitvolatile.Whiletheliteraturedealingwiththequestionofhowoilpricesareset

andwhichfactorsaffectthemconcentratesonrational(i.e.,economic)factorssuchas

33

macroeconomicandmonetaryshocks,itseemsthattheliteraturegenerallydisregards

any“behaviouralfactors”inexplainingoilpricemovements.Aftertheearly2000s,oil-

based financialproductsbecameapopularasset class formany fundsandportfolio

managers. So, it’s important to analyse as towhat extent fluctuations originating in

investor sentiment contribute to the variance in oil prices. Therehasbeen a recent

growingattentionofbothretailandinstitutionalinvestorstofinancialoilproductsin

the form of ETFs, futures and derivatives. Index and Hedge fund managers have

increased theirenergycommodityholdings in recentyears, indicatingan increasing

involvementofoilintheirportfoliochoices.Whensucharadicalshiftishappeningin

theportfoliosofinvestors,itisimportanttoacknowledgetwoimportantfactorsand

theireffectsoninvestorsentiments:

• Therecentsharpchangesinthepricesofoil

• Thefadingwisdomthatexpansion(stagnation)ineconomicactivityleadstoa

decrease(increase)inoilpriceseventuallyleadingtoanincrease(decrease)in

stockpriceindices

ArecentstudybyQadanandNama(UniversityofHaifa)in2018shedlightonthesetwo

factorsandconcludedintheirstudythatvolatilityininvestorsentimentspillsoverinto

theoilmarket,which,inturn,resultsinaparallelreactioninreturnsandvolatility.They

alsoprovideevidencethatinvestorsentimentiscapableofpredictingnotonlytheprice

of oil but also the stock prices of the leading companies involved in the petroleum

industry.Thesharpoilmarketmovementsattractinvestors'attentiontotheoilmarket

andthatanincreaseinthisattentionisfollowedbygreatervolatilityinthepriceofoil.

Thesefindingscanhaveseveralpracticalimplicationslikethetimingofinvestmentand

hedgingrisksagainstadversepricemovements.

IMPLICATIONS ON PORTFOLIO MANAGEMENT OF INDIANSTOCKS

Wepreviouslystatedthatstockindicesofoilimportingnationsarecomparativelyless

vulnerable tooilpricechangeswhencompared tooil exportingnations,westilldig

deepertoexamineastowhatextentaninvestorinIndiacandiversifyinabullanda

34

bearmarketwhiletheoilpricesfluctuate.ThemakeinIndiacampaignbyIndianprime-

ministerNarendraModimakesall the13sectors inIndiaattractiveopportunitiesto

investastheeconomicgrowthiskickinginandIndiaisexpectedtogrowataCAGRof

6.5% for the next 25 years compared to 5% estimated for China. This humongous

growthwilldirectlyaffecttheoilconsumptiontoo.Indiapresentlyimports80%ofits

crudeoilneedsandannuallyspendsINR9126croremoreforevery1USDincreasein

crudeoilprices.ThesenumbersshedsomelightonthekindofdependencyIndiahas

onoilimportsanditsglobalprices.Therippleeffectsaretosomeextenttransferredto

thestockmarketstoo.ArecentpaperbyTiwari,Jena,MitraandMin-Yoon(Montpellier

Business School,Montpellier, France andDepartmentofEconomics, IBSHyderabad,

IFHE University, India) highlighted the oil price fluctuation effects on the different

sectorsduringbothbullandbearmarketsinIndia.Thefindingsoftheirresearchcan

besummarizedbelow:

BULLMARKETSCENARIO-

• Duringoilpricefluctuation,healthsectorshouldbecompletelyavoidedasan

investmentsectorinabullmarket.

• Theenergy,material,andITsectorsrespondpositivelytothedeclineinoilprice

inbullmarkets,thusprovidinganinvestmentopportunityforinvestors.

• The remaining nine sectors are unaffected by any changes in oil price, they

provideasafehaveninvestmentopportunitytoreduceoilpricerisk inabull

market.

BEARMARKETSCENARIO–

• Thegreensectorisinfluencedbothbypositiveandnegativechanges,whilethe

energyandbankingsectorsareaffectedbynegativeoilpricechanges;allthree

sectorsareunaffectedbyaggregateoilpricechanges.

• Theindustrial,consumerdiscretionary,andcapitalgoodssectorsareunaffected

by changes in oil price, these three sectors hold potential for diversification

opportunitiesforPMstominimizeoilpriceriskinbearmarkets.

35

• Thecarbonsectorisunaffectedbyoilpricechanges,irrespectiveofthemarket

conditionorthetypeofoilshock.Therefore,duringbothbearandbullmarkets,

thecarbonsectorisasafehavenforinvestmentagainstoilpricerisk.

CONCLUSION

Thisarticletriestotouchupononeofthemajordrivingfactorsoftoday’seconomy–

oil.Thereservesarebeingdepleteddaybydayandcountriesaretryingtofindnew

ways to exploit the planet’s resources towin the oil game.We started offwith the

present scenario ofUSA suddenly coming inwith its shale gas and climbing up the

charts.We saw the decade’s history of price ups and downs and highlighted some

reasonscontributingtoit.Then,wereinstatedthedominanceofOPECandstressedon

thefactthatOPECnationsplayaveryvitalroleinthewholedemand-supplygameof

oil.Themajorchunkofthearticletriedtoestablisharelationbetweenthepricesof

suchaprizedfactorandthestockmarkets.Severalresearchpaperfindingshelpedus

concludethatanentity,soimportantforaneconomyhasitseffectstransferredtothe

markets.Countriesthatexportoilhavetheirstockindicesmuchmorevulnerabletothe

price wars compared to the oil importing nations. The investors need to clearly

segregate oil-relevant and non-oil-relevant sectors and diversify their portfolio for

maximumreturnsandminimumexposuretooilpricefluctuations.

References

1. Business Insider. (2018, Feb). WTI price chart. Retrieved from:

http://markets.businessinsider.com/commodities/oil-price?type=wti

2. Energy InformationAdministration. (2018, Feb).WHATDRIVES CRUDEOIL PRICES?

Retrievedfrom:https://www.eia.gov/finance/markets/crudeoil/supply-opec.php

3. OPECOrganisation.(2017,Dec).OPECshareofworldcrudeoilreserves,2016.Retrieved

from:http://www.opec.org/opec_web/en/data_graphs/330.htm

4. The Economist. (2018, Jan). Why the oil price is so high. Retrieved from:

https://www.economist.com/news/finance-and-economics/21735059-and-why-it-

might-not-fall-very-much-soon-why-oil-price-so-high

5. TheEconomist.(2018,Feb).Risingoilpricesaremakingmoreextractionmethodsviable.

Retrieved from: https://www.economist.com/news/finance-and-

36

economics/21735059-and-why-it-might-not-fall-very-much-soon-why-oil-price-so-

high

6. Economics Help Org. (2017, Oct). Effect of higher oil prices. Retrieved from:

https://www.economicshelp.org/blog/1919/oil/effect-of-higher-oil-prices/

7. Qadan,M.,Nama,H.(2018,Jan).“Investorsentimentandthepriceofoil”.Retrievedfrom:

https://www.sciencedirect.com/science/article/pii/S0140988317303766

8. Alfonso,R., Irarrazabal,A.(2018,Feb).“OPEC’Smarketpower:anempiricaldominant

firm model for the oil market” Retrieved from:


9. Ezgi D., Coskun, C. (2017, Jan). “The impact of crude oil prices on financial market

indicators- a copula approach. Retrieved from:


10. Nadal,R.,Szklo,A.(2017,Dec).“Time-varyingimpactsofdemandandsupplyoilshocks

on correlations between crude oil prices and stock market indices”. Retrieved from:


11. Bams,D.,Honarvar, I.(2017,Dec).“Doesoilandgoldpriceuncertaintymatter forthe

stock market?” Retrieved from:


12. Tao,L., long, JandChengL.(2017,Dec).“Empiricalstudyofthefunctionalchangesin

price discovery in the Brent crude oil market”. Retrieved from:


13. Forbes. (2018, Feb). Record U.S. production makes a $70 oil price target seem odd.

Retrieved from: https://www.forbes.com/sites/gauravsharma/2018/02/02/record-

u-s-production-vs-hedge-funds-bets-why-a-70-oil-price-appears-

odd/#7d89ba4c57dd

37

Thesis on Mergers & Acquisitions in the Credit-rating sector

AadithyaaandTanushreeMahapatra

InstitutionalAffiliation-SymbiosiscentreforManagementStudies,Pune

Abstract

TheIndianeconomyismovingonapathtocreateuniversalinstitutionsthroughthe

processofmergers&acquisitions(M&A) invarioussectorsof theeconomy.Butthe

sameM&AprocessisapointofcontentionwhenappliedtotheCredit-ratingsector.To

studywhatwouldbethe likelyconsequencesofapossibleM&Ain theCredit-rating

sector, our study - Firstly, analyses the inherent risk in the ratingmethodologiesof

different Credit-rating agencies. Secondly, it aims to evaluate the control of Credit-

ratingagenciesintheeconomywithspecificreferencesto-Graham&HarveyandAri

&Bolte’sresearchwork,the2008financialcrisisandRelianceCommunications&IDBI

Bank’s recent examples. Following this, the study primarily focuses on the case of

CRISIL(CreditRatingInformationServicesofIndiaLimited)acquiring8.9%stakeinits

rivalCARE(CreditanalysisandresearchAgency)inJune,2017.Finally,thestudyaims

todevelopathesisasperthecurrentM&Apatternandexistingbusinessenvironment

inCredit-ratingsector.Toachieve theobjectivesof thestudy, secondarydata in the

formofnewsreports,casearticlesandresearchpaperswereconsultedandexisting

literatureonthesubjectwasthoroughlyreviewed,theimplicationsofthesamewere

discussedwhileshapingandpresentingthethoughtsontheproblemidentified.

Keywords-Acquisitions,CARE,Credit-rating,CRISIL,Mergers

JELclassification-G3

We acknowledge the helpful comments and suggestions of the editors. Editor’s note: Accepted by Junitha Johnson and Animesh Gupta


38

Introduction

IntroductiontoCredit-ratingagencies

SecuritiesandExchangeBoardofIndia(SEBI)definesCreditratingagencyas‘anentity

whichassessestheabilityandwillingnessoftheissuercompanyfortimelypaymentof

interestandprincipalonadebtinstrument(SEBI,FAQsonCreditRating,2017).These

ratings are based on a concise evaluation of the strengths and weaknesses of the

company’s fundamentals including financials along with an in depth study of the

industry as well as macro-economic, regulatory and political environment of the

business.Themajorfactorswhichdeterminetheratingsofacompanyare-operational

efficiency,leveloftechnologicaldevelopment,financials,competence,effectivenessof

management, past record of debt servicing etc.Different credit-rating agenciesmay

take in different factors and associate varying weightages to the same to study a

particular company. As a result of which each credit-rating agency has a different

perceptionandmeaningtoitsratings.Forexample,S&PRatingsaimstomeasureonly

theprobability of default anddoesnot focuson the time that the issuer is likely to

remainindefault,theexpectedwayinwhichthedefaultwillberesolved,whatwillthe

recoveryvaluebe-theamountofmoneythatinvestorsendupwithaftertheissuerhas

defaultedetc.Moody’sontheotherhandaimstorevealtheexpectedlossesoverthe

defaultprobability.Ittakesintoaccountwhat’slikelytohappenifandwhenadefault

occurs(Salmon,2011).Asaresultofthesefunctions,Credit-ratingagenciesplayavery

important role in affecting the investor decision-making and as a result the whole

investmentsentimentinthemarket.Tosimplyput,ifCRISILgivesaAAArating(Rating

scale for Long-Term Instruments indicating Highest Safety - Lowest credit risk) to

National InsuranceCo. or its instruments itwill drive the investors to invest in the

companyandboostthemarketsentimenttohighlypositiveforthebusinessconcern

andvice-e-versa.

IntroductiontoCRISILandCARE

CRISIL-CRISIListhemainandforemostproviderofratings,data,research,analytics

and solutions in India and in other emergingmarkets thus fulfilling themission of

39

makingmarketsfunctionbetter.Itwasincorporatedintheyear1987andismajorly

heldby S&PGlobal Inc., a leadingprovider of transparent and independent ratings,

benchmarks,analyticsanddatatothecapitalandcommoditymarketsworldwide.

CARE - CARE Ratings is the second-largest credit rating agency in India. It was

incorporated in the year 1993. CARE Ratings has emerged as a leading agency for

covering many rating segments such as banks, sub-sovereigns and Initial Public

Offerings(IPOs).CARERatingshelpsthecorporatestoraisecapital fortheirvarious

requirementsandassiststheinvestorstoformaninformedinvestmentdecisionbased

onthecreditriskandtheirownrisk-returnexpectations.

IntroductiontoMergers&Acquisitions

Mergers - In a merger, the boards of directors of two companies approve the

combinationandseekshareholders'approval.Afterthemerger,theacquiredcompany

ceasestoexistandbecomespartoftheacquiringcompany.

Acquisitions-Inasimpleacquisition,theacquiringcompanyobtainsthemajoritystake

intheacquiredfirm,whichdoesnotchangeitsnameorlegalstructure(Investopedia,

n.d.).

Literaturereview

Existing researches have shown how the credit-rating can affect fortunes of the

companytoagreatextent.Creditratingsplaythesecondmostimportantrolewhenit

comestocapitalstructurethroughthedeterminationofaccesstofundsinthecapital

market(Graham&Harvey,2001).Asaresultofhigherratings,firmshaveeasieraccess

tofunding,whichisshownintheleverageratio.Numerousstudieshaveshownthereis

a direct relationship between high credit rating and lower cost of debt and other

variables,which leads to an increased debt capacity (Ari & Bolte, 2015). The three

major credit-rating agencies accused for contributing to the 2008 Financial crisis -

StandardandPoor’s (S&P) -Majorityholder inCRISIL,Moody’s -Majorityholder in

InvestmentInformation&CreditRatingAgency(ICRA),andFitchRatingswereaccused

of fraud by offering highly favourable ratings to default financial institutions and

approving extremely risky mortgage-related securities. The “Big Three” even after

40

being held accountable for violations, paying out penalties etc. continue to be the

primaryreliancefactorforinvestordecision-makingonthelargelyunchangedratings

services(CouncilonForeignRelations,2015).Thisjustgoesontoprovewhatamount

ofcontrolaCredit-ratingagencyhasinthefunctioningoftheeconomy.

Inthesecondquarterof2017,InvestmentInformation&CreditRatingAgency(ICRA)

downgraded IDBIbank’sbondratingswhich lead toamassive fallof5.5% inaBSE

intra-daytradeand22%inthemonthMay-June.Similarly,ratingagenciesFitchand

Moody'sdowngradedcreditratingofRelianceCommunicationsforthesecondtimein

quicksuccessiononaccountof itsfragileliquiditypositionandlimitedabilitytopay

back debt. Reliance Communications responded in its statement saying “We

respectfullydisagreewiththerecentratingactionsbyboththeseagencies,andbelieve

thattheseratingactionsdonotreflecttheservicingtrackrecordofthecompany".Asa

resultof thedowngradeRelianceCommunications fell4% inan intra-day tradeand

40%inthemonthMay-June.

Thereviewofliteratureprovesthateventhoughtheratingsmayormaynotrepresent

the true picture of the instrument/company, it surely plays a massive role in the

functioningoftheeconomyatbothmicroandamacrolevel.Also,theliteraturepoints

out to the increasing cases of non-acceptance of ratings by companies and a weak

Indian ratingmechanism on account of the shortening time period between rating

allotmentanddowngradationofthesame.

CaseExample

Out of various mergers and acquisitions taking place around the world, CRISIL

acquiring8.9%stake forRs435.26 crore inCARE throughblockdeals fromCanara

Bank,cameasasurprisepackage.ItisrarelyheardthatM&A’stakeplaceintheCredit-

rating sectors asM&As have always been a commonplace for banks and corporate

sector for achievingprofitability and expansion. CRISIL said in anofficial statement

"Thisstakepurchaseisaninvestmentintheexcellentlong-termprospectsofthecredit

ratingsectorinthecountry.Theprospectsforthesectoraredrivenbythesignificant

demand for capital investments and infrastructure financing in India over the long

term,muchofwhichshouldbenefitthesector”.

However,thisstakepurchasedidn’treceiveapositivereactionfromothersectionsof

theeconomy.CAREofficialssaidthattheagencyisn’thappywithCRISIL’s‘predatory’

41

approach and fears that a ‘hostile takeover’ is on cards sooner or later. The stake

purchasealsoreceivedcriticismfromSEBIasitconsidersthattheratingssectorassuch

doesnotneedanymergersandstatesittobeanunnecessaryandnon-feasibledecision.

Thepossiblemotivesandconsequencesofthiscombination,asspeculatedbyexperts

couldbeanyofthefollowing-

CRISIL-CAREcombinationcanleadtoafootholdof65%ofmarketshareintheratings

market (Mohit Bhalla, Reena Zachariach, 2017). Rating agencies acquiring other

agenciesandcontrollingmajorityofthemarketleadstodevelopmentofmonopolistic

characteristics which is a negative sign for the economy. Unlike banking sector,

regulationspertainingtoratingagenciesaren’tclearasfarasstakepurchasesbyone

ratingagencyinanotherareconcerned(Unnikrishnan,2017).

CRISILmightbepreventingatakeoverofCAREbyotherratingagencies.Itcanbedone

by making the shares of the target company unattractive or less desirable to the

prospective acquirer - This strategy is often termed as Poison-Pill strategy

(Bandyopadhyay,WhatNext,CRISIL:Bymovingahead,Crisilhasnowmadeitdifficult

foranyotherentity,includingIndiaRatings,toplaninorganicgrowththroughacquiring

CareRatings.,2017).ThethreelargestratingagenciesinIndiaareCRISIL,CAREand

ICRA(coveringover85%oftheratingmarketinIndia).SinceCRISILbyacquiringstake

inCAREhasnowmadeitdifficultforanyotherentity(ForeignratingentityorIndian

RatingEntity)toplantheirgrowthprospectsthroughacquiringstakeinCARERatings.

Theotherpossibilityisthatthroughthisacquisition,CRISILgrowsitsratingbusiness

exponentially in terms ofmarket share and control in themarket. Usually, when a

companyacquires a stake in another company toprevent competition fromgaining

control over it or if the company itself is planning a takeover bid, it goes for

warehousing-aprocedurewherebyacompanygraduallybuildsupaholdingofshares

inafirmitwishestotakeoverinthefuture.(Bandyopadhyay,WhatNext,CRISIL:By

moving ahead, Crisil has nowmade it difficult for any other entity, including India

Ratings, to plan inorganic growth through acquiring Care Ratings., 2017). A similar

42

strategywasusedbyS&PtoacquireCRISIL.S&Pacquired9.68%stake inCRISILIN

May,1997andby2005S&PacquiredamajoritystakeinCRISIL.

ThereisalsoapossibilityofpotentialtakeoverbyCRISILovertheotherratingagencies.

Currently,Even ifSEBIcriticizeson thisstakepurchase,SEBInormsdonotprevent

CRISILfrombuyinga10%oracquiringamajoritystakeinCARERatings.Regulations

of theSecuritiesandExchangeBoardof India(SEBI)prohibitaregisteredmerchant

bankertosetupanothermerchantbankthroughitselfor itsassociates,butnosuch

restrictionsarethereintheCredit-ratingsector.Plus,theCompetitionCommissionof

India (CCI) does not have any specific normswhich prohibit CRISIL from acquiring

stakeinCARERatingsoranyotherratingagency.(Bandyopadhyay,WhatNext,CRISIL

:Bymovingahead,Crisilhasnowmadeitdifficultforanyotherentity,includingIndia

Ratings,toplaninorganicgrowththroughacquiringCareRatings.,2017)

S&Pholds67.05%inCRISILandMoody’sowns50.54%inICRAhenceCARERatingsis

largelyperceivedasanIndianownedcreditratingentityinIndiaandacquiringCARE

wouldmeantakingoveramajorchunkintheIndianmarketinalongtermscenario.

EvenifCRISILstopsatholding10%inCARERatings,itwillbesuccessfulinpreventing

arivalagencyfromacquiringtheCARERatingsbecause‘Ashareholderholding10%or

moreofacompanyassumesthestatusofa“minority”shareholderandcanhavecertain

statutory rights and protections’ (Companies Act, 2013). There are rights which

supportminorityinterestsinacompanybutiftheyareavailabletoashareholderwho

isalsothefirm’slargestcompetitor,itcouldleadtopotentialmisuse.(Bandyopadhyay,

WhatNext, CRISIL :Bymoving ahead, Crisil has nowmade it difficult for any other

entity, including India Ratings, to plan inorganic growth through acquiring Care

Ratings.,2017)

Followingtheconcernsraisedintheeconomy,SEBIissuedaConsultationpapertitled

‘ConsultationpaperonReviewoftheRegulatoryFrameworkforCreditRatingAgencies’

onSeptember8,2017whichproposesthefollowingpointsrelevanttoourproblem–

43

TheminimumnetworthrequirementtobeeligibleforgrantofregistrationasaCredit-

ratingagencymaybeincreasedtoRs.50Croresfromexisting5croresonaccountof

theincreasingsystemicimportanceofCredit-ratingagency.

NoCredit-ratingagencyshouldhavemorethan10%shareholdinginanotherCredit-

ratingagencydirectlyorindirectly.

Any acquisition of shares and/or voting rights in a Credit-rating agency may be

permittedwiththepriorapprovalofSEBI.

Also,ashareholderholding10%ormoresharesand/orvotingrightinaCredit-rating

agencyshallnothold10%ormoresharesand/orvotingrights,directlyorindirectly,

inanyotherCredit-ratingagency.(SEBI,2017)

The Case example provides comprehensive insights from all the sections of the

economyregardingthecurrentM&Apatterninthecredit-ratingsector.

ResearchMethodology

Toachievetheobjectivesofthestudy,secondarydatawasextensivelyusedtosupport

the viewpoint of the authors. Existing literature on the subject was thoroughly

reviewed to understand the scattered ideas on the subject and also present a

comprehensive analysis and conclusion of the problem at hand.News reports, case

articlesandresearchpaperswereconsultedtocollecttherelevantfactsrelatedtothe

problemwhichprovedtobequiteusefulinshapingandpresentingthethoughtsonthe

problemidentified.Theavailableliteraturehelpedinthedevelopmentofthesiswith

respect to certain constraints and assumptions as per the existing business

environment.

ResultsandDiscussion

Thefollowingaretheresultsofthestudy–

Stakepurchase/Votingrights–Asofnow, legallythereisnorestrictioninaCredit-

ratingagencyacquiringstakeorhavingvotingrightsinanotherCredit-ratingagency.

TheConsultationpaperaimstocontrolsuchconsolidationpracticesinthesectorbut

anymagnitudeofM&AintheCredit-ratingsectorisanegativesignintheeconomyas

awhole.Also,theConsultationpaperdoesn’tproposeanyretrospectivemeasurestobe

44

takenasa resultof change in theregulatory frameworkwithrespect to theCRISIL-

CAREstakepurchase.

Systemicrisk– Instanceswhereratingshavebeenreduced from ‘AA’ to ‘D’ just ina

matterof fourmonths like in thecaseofAmtekAutoLtdpoints towards the failing

Indianratingswhichmaybearesultofincompetenceorthelackofpredictiveabilityof

ratingmodels,unforeseeableeventsorpreferentialratingallotmentbyIndianratersto

acquire clients. This has also resulted in a greater non-acceptance of ratings by

companies.BetweenJanuarytoJune,2017-650listedandunlistedcompaniesdidnot

acceptratingsallottedbythetopfourratingagencies–CRISIL,CARE,ICRAandIndian

ratings.Suchpossibilityoffudging/miscalculation/preferenceinawardingratingsby

raterscanleadto2008-likescenarioswherehigherratingswereawardedtootherwise

defaultinstruments/companiesbuildinguptosystemicrisk-theriskofcollapseofan

entirefinancialsystemorentiremarket.(Bandyopadhyay,Livmint,2017)

Foreign rating problem–There is no clarity on FDI in Credit-rating sector and any

restriction imposed by SEBI relating to stake purchase by foreign raters. Even the

Consultationpaperdoesn’tspecifyanythingrelated to foreignratersstakepurchase

limitsoranyretrospectivepoliciesrelatingtothesame.Asaresulttheforeignrating

agencyproblemintheIndianratingmarketremainstopersist.

Assumptions

1. Themarket is similar to an oligopoly market - a form of market where the

industry is dominated by a small number of sellers i.e. there are only a few

numberofCredit-ratingagenciesintheindustrywhichcontrolorholdmajority

controlinthesector.

2. The economy is assumed to be static i.e. there are small/insignificant

movementsbutnomajorchanges.Also,staticeconomyincludesallcomponents

likelegal,environment,socialetc.

3. Thereisnochangeincredit-ratingbeinganimportantfactoraffectinginvestor-

decisionmaking/lendingdecisionintheeconomy.

4. Thistheoryisonlyapplicabletothefieldofcredit-ratingandnoothersectorin

particular.

5. Thetimeperiodisassumedtobelong-runi.e.atleastmorethanoneyearforthe

theorytoholdtrue.

45

References1. Ari,&Bolte.(2015).TheInfluenceofCreditRatingsontheChoiceofPaymentinthe

GermanMerger&Acquisitionmarket.

2. Bandyopadhyay,T.(2017,September25).Retrievedfrom:http://www.livemint.com/Opinion/NpJzJ6ZiDDhZHLHMAXb2CI/How-to-stop-rating-shopping.html

3. Bandyopadhyay,T.(2017,August17).WhatNext,CRISIL:Bymovingahead,Crisilhasnowmadeitdifficultforanyotherentity,includingIndiaRatings,toplaninorganicgrowththroughacquiringCareRatings.

4. Bolte,A.a.(2015).TheInfluenceofCreditRatingsontheChoiceofPaymentintheGermanMerger&Acquisitionmarket.Sweden.

5. CouncilonForeignRelations.(2015,February19).TheCreditRatingControversy.Retrievedfrom:https://www.cfr.org/backgrounder/credit-rating-controversy

6. Graham,&Harvey.(2001).Thetheoryandpracticeofcorporatefinance:evidencefromthefield.

7. Investopedia.(n.d.).MergersandAcquisitions-M&A.Retrievedfrom:https://www.investopedia.com/terms/m/mergersandacquisitions.asp

8. MohitBhalla,ReenaZachariach.(2017,August14).SebiquestionsCRISILinvestmentinCARERatings.Retrievedfrom:https://economictimes.indiatimes.com/markets/stocks/policy/sebi-takes-care-ratings-to-question-crisil-deal/articleshow/60050138.cms

9. Salmon,F.(2011,August9).ThedifferencebetweenS&PandMoody's.

10. SEBI.(2017,September8).Retrievedfrom:https://www.sebi.gov.in/reports/reports/sep-2017/consultation-paper-on-review-of-the-regulatory-framework-for-credit-rating-agencies_35896.html

11. SEBI.(2017).FAQsonCreditRating.

12. Unnikrishnan.(2017,July10).CrisilstakebuyinCare:Whyregulatorsneedtocheckforeignagencies’predatoryapproachonIndianraters.

tjef volume 2 issue 3 - … · 1 contents papers impact of black box trading in indian stock market...

Documents