final-issues concerning algorithmic trading in india

7/31/2019 Final-Issues Concerning Algorithmic Trading in India

1/55

Chapter1

AlgorithmTrading

DefinitionandtypeofalgorithmtradingAlgorithmtradingreferstoautomatedtradingbasedonalgorithm.Thepurposeof

usingautomatic

trading

is

to

analyze

price

and

market

conditions

in

order

to

trade

at

the

minimumcostbasedontherelevantalgorithmmethod.

Algorithmic Trading can be defined as the use of computer programs for entering

trading orders where the computer algorithm decides on aspects of the trade execution

such as the timing, price, or quantity of the order. Algorithm Trading is also known as

automatedtrading,algotrading,blackboxtradingorrobotrading.Algorithmsdynamically

monitormarketconditionsacrossdifferentsecuritiesandtradingvenuestomakethetrade

executiondecision.Algorithmictrading(AT) ismorecomplexthanelectronictradingand it

encompassesmanyformofcomputeraidedtradingincludingHighFrequencyTrading.

Algorithmic

Trading

is

widely

used

by

pension

funds,

mutual

funds,

and

other

buy

side(investordriven)institutionaltraders,todividelargetradesintoseveralsmallertrades

inordertomanagemarketimpact,andrisk.Infact,algorithmswereoriginallydevelopedfor

use by the buyside to manage orders and to reduce market impact by optimising trade

executiononcethebuyandselldecisionshadbeenmadeelsewhere.Sellsidetraders,such

asmarketmakersandsomehedgefunds,provideliquiditytothemarketbygeneratingand

executingordersautomaticallywiththehelpofalgorithms.

AlgorithmTradingisbroadlycategorisedintoHighfrequencytrading,BasketTrading,

MultiExchangetradingandothercategory.BasketTrading(Programtrading)isgenerally

usedforstockbaskettrading.Multiexchangetradingistradingaproductacrossdifferent

exchangesusingcomputeralgorithm.MultiexchangetradingisfacilitatedbySmartOrder

Routingalgorithms.

Smart

order

routing

is

atechnique

of

using

the

close

correlation

of

majorexchangesandcrosslistingofacompanyi.e.,placingordersonanexchangewhere

themostfavourableconditionsareseen.InIndia,SEBIalloweduseofSmartOrderrouting

inAugust2010andcurrentlyitisoperationalinbothCapitalMarketaswellasCurrency

DerivativeSegmentOthercategoryheretoreferredasAlgorithmTrading/Algorithmic

Trading/ATinterchangeably,referstoanyandallkindofcomputeraidedtradingwhichdoes

notfallunderfirstthreecategories.Algorithmtradingfocusesonminimizingthemarket

impactbysplittingtrades.Algorithmtradingwasoriginallydevelopedasanorderplacement

systemforthepurposeofminimizingtradingcost,butitisnowbeingusedasanoverall

termtodescribeitsstrategyandprocess.


2/55

Strategiesoralgorithmsusedbythecomputertoautomate(enter,modifyorcancel)trade

ordersarecalledalgorithmictradingstrategiesandtheyarebroadlyclassifiedasexecution

strategies,profitseekingstrategies(Alphastrategies)andarbitragestrategies.

Arbitragestrategies

AlphaSeekingstrategies

Executionstrategies

Algorithmtrading

is

widely

used

among

institutional

investors

like

pension

funds

and

investmentcompaniesbecausecostcanbesavedthroughbulkorders,reducingtheimpact

onthemarketandpreventingtheexposureoftradinginformation.Algorithmtradingalso

helpsreducetradingcost.

ThemostcommontypesofexecutionalgorithmareVWAPandTWAP.VWAPsplitsorder

volumebasedonhistoricaldata.TWAPsplitsorderovertime.Themarketparticipation

strategyismanipulatingtradingvolumesothatspecificordersdonotaccountfora

significantpartoftotaltradingvolumeonthemarket.Ontheotherhand,theinlinestrategy

ismanipulatingordersorpricessothattheydonotsurpassalimitprice.

AlgorithmTrading

HighFrequency

Trading

BasketTrading

(ProgrammTrading)

MultiExchangeTrading(Trading

usingSOR)

OtherAlgorithmic

Trading


3/55

Whatar

Buyside

securitie

propriet

Buyside

firmspa

moveme

Sellside

theorde

mostco

Sellside

required

Sellside

andthe

Arbit

Delt

Nuet

EventBArbitr

Buysidefi

firmsrefer

s.Privateeq

rytrading

firmsusuall

ticipateina

nts.

firmsrefers

rsbyslicing

monexam

brokerages

tobemark

firmsprofit

idoffersp

agestrat

alStaAr

sedge

rmsandSe

toinstitutio

uityfunds,

esksareth

ytakespec

smallernu

toinstituti

thenintos

plesofsell

areregister

tmakersin

fromCom

ead.

egies

tisticalitrage

llsidefirms

nsconcerne

mutualfun

mostcom

lativeposit

berofove

nsthattak

allorders.

idefirms.

dmember

agivensec

ission(brok

Alpha

Stra

DirectionalTrading

Strategies

ScalpingStrategies

?

dwithbuyi

s,unittrust

ontypeso

ionsormak

ralltransact

ordersfro

Brokeragefi

ofastock

urity.

erage),advi

Seeking

tegies

MeanRevesio

Strategi

DarkLiquiditSeekin

Strategi

ng,rathert

s,hedgefu

fbuysidee

relativeva

ions,andai

buysidef

irmsandM

xchange,a

soryfeecha

ns

y

s

Ex

Ben

alg

(VImpleonSParti(%VTarg

TWA

anselling,

ds,pension

ntities.

luetrades.

mtoprofitf

irmsandth

rketmakin

ndsometim

rgedtobuy

ost

RedcutionS

hmarkrithms

WAP,mentati

hortfall,ipation

olume),tClose,

,InLine,

tc)

ssetsor

funds,and

Buyside

rommarket

n"work"

firmsare

estheyare

sidefirm

ction

/

trategies

Liquidityseeking

algorithm

(CrossFireHunt,Icebe

etc)

,rg,


4/55

Algorithmtradingsystem

Source:Exchangehandbook


5/55

Chapter2

AT WherewestandgloballyandinAsia?

OnMarketEnvironmentFront

Singapore&HongKongScoreTopinchart

India

Japan

Australia

Taiwan

China

OnRegulatoryForcesFront

HongKong

Australia

Singapore

Japan

Taiwan

India

China(MostRestrictedmarketinworldfortrading)

OnTechnologyEnablersFront

Singapore(HighestinvestmentontechnologyfrontinAsia)

Australia

Japan

HongKong

India

Taiwan

China

OnAlgorithmicTradingFront

HongKong(48%ofvolumetradedalgorithmically)

Singapore

Australia

India&Japan

China


6/55

AlgorithmicTradinginAsiaPacific

Amongasiapacificcountries,algorithmicactivityishighestinHongKong(39%)followedby

Singapore(31%),Japan(26%),Australia(20%) andIndia(15%).Algorithmictradingin

HongKongisslatedtoreach61%in2012fromcurrent39%.Indiawascautiousinitsuseof

AlgoTrading,

but

has

lot

of

potential

to

grow.

By

the

end

of

2012,

AT

activity

in

India

is

expectedat30%fromcurrent12%.

Source:CelenetResearch

Asiaisaveryexcitingmarketforelectronictradingofcashequityandderivatives.Whilethelevelofdevelopmentofeachmarketdiffers,theleadingexchangesinJapan,Australia,Singapore,HongKong,andIndiashouldsetthetone,withfastermatchingengines,enhancedmarketdata,andcolocationservices.Withahighproportionofitsdomesticbuysidebeginningtousealgorithmictrading,HongKongisbestpoisedtogrowintheregion.ItisfollowedbySingapore,wheretheregulatoryenvironmentisveryconducivetoalgotrading.Similarly,Japan,andAustraliaareexpectedtohavehigheralgotradingincomingyears.Finally,Indiahasbeenaslowstarterbutisrapidlycatchingupwithsomeofitscounterpartsandisexpectedtohavealgotradinglevelsofaround30%by2012 AnshumanJaswal,CelentSeniorAnalyst


7/55

EvolutionofElectronicTradinginIndia

HFTisnotyetintroducedinIndia.

Thefollowing

is

the

solution

presented

by

the

Singapore

Stock

Exchange

to

reduce

order

fulfillmenttime:1)improvingdataqualitybyusingColocationandexpandingnetwork

bandwidth;and2)reducingorderfulfillmenttimebycombiningdifferenttechnologiesvia

efficientapplicationsolutionsandlayerednetworks.Inaddition,theexchangeisusing

advancedsoftware,whiledevelopingappliancebasedchiptechnology.

1994' 200001 200304 2008' 2010' 201011 2011'

MilestonesinIndianEquityMarkets

DomesticBuySide startedAlgoTradingoperations

SmartOrderRoutingIntroduced

(DomesticSellSide startedAlgoTradingoperations)

DMAIntroduced

AlgorithmicTradingBegins

IntroductionofDerivativesinIndia

InceptionofNSEandStartofelectronicTrading


8/55


9/55

DirectMarketAccessFacility

DirectMarketAccess(DMA)isafacilitywhichallowsbrokerstoofferclientsdirectaccessto

theexchangetradingsystemthroughthebrokersinfrastructurewithoutmanual

interventionbythebroker.

Someof

the

advantages

offered

by

DMA

are

direct

control

of

clients

over

orders,

faster

executionofclientorders,reducedriskoferrorsassociatedwithmanualorderentry,

greatertransparency,increasedliquidity,lowerimpactcostsforlargeorders,betteraudit

trailsandbetteruseofhedgingandarbitrageopportunitiesthroughtheuseofdecision

supporttools/algorithmsfortrading.

DMAtrafficaccountsfor15 18percentoftotaltradingvolumesintheUSand8percentin

Europe.DirectMarketAccesstradersinhighfrequencyprogramshavethegreatest

demand.

SEBIallowedTradingMemberstoprovideDMAfacilityinApril2008fortradinginequities,

futuresand

options

segment.

Connectivity

IndianbrokersneedFIXconnectivitytoattractinternationalorderflowandmanyhave

madesignificantinvestmentsinFIXnetworksandordermanagementsystems(OMSes).The

widespreadadoptionoftheFIXprotocoloverthelasttwoyears,allowedmanycountriesto

allowDMAfacility.

InIndiabothNSEandBSEhaveFIXconnectivity.

Colocation

IndianExchangeshavestartedprovidingcolocationfacilitytotheirmemberbrokers,

wherebytheycanplacetheirtradingserversclosetotheexchangesengineonafirstcome

firstservedbasis.Colocationsavescrucialmillisecondsfromthetimeittakestoplacean

orderanditsreceiptattheotherend.Thebrokerwithhisservernexttotheexchange

enginegetsapricefeedthatisupdatedeverythreefourmilliseconds,whileabrokerata

remoteplacewillgetthisfeedupdatedevery3040milliseconds.

NSEstartedcolocationfacilitiesforitsmembersinJanuary2010andthepaceofadoption

isfascinating.

With

co

location

facilities,

members

can

set

up

automated

trading

systems

in

thesamebuildingastheexchange.Withthis,thetimetakenformarketdatagoingoutfrom

theexchangeandforordermessagestocomeinfrommembers(alsoknownaslatency)

reducesconsiderably


10/55

K

80

Inarece

National

colocat

Latency

Latency

relyonv

exchang

NYSETe

TimeLa

TimeLa

Acknowl

TimeLa

at(time

executio

R

microse

Ordersp

Capacity

Capacity

Withint

pacewit

increase

Inrespo

to20,00

RX

,000S

H

10,

ntFuturesI

StockExcha

dservers.

refersto

am

erylowlate

sareinves

hnologies

fordatafe

fororder&

edgment

forRound

fromorder

nto

trade

c

ecently,NY

ondslatenc

eed(Round

refersto

ab

oductionof

heverincre

capacityin

setochan

ordersper

KE

000S

SG

10,0

dustryAss

nge(NSE)s

ountof

tim

ncy(i.every

inginnew

niversalTr

d

cancel

ripExecuti

confirmatio

nfirmation

Elaunched

yatrateso

TripExecu

ilityof

an

e

Algorithm

asingcapaci

rdertofaci

ingenviron

second.NS

X

00BS

10,0

S

ciation(FIA

aid60%oft

taken

to

e

quickdata

echnologyt

adingPlatf

n

ntotrade

Ethernetb

1million2

ionTime)a

changeto

radingnow

tydemands

ilitateMultil

ment,BSEi

Ealsoiswo

0LSE

6,00

S

)conferenc

heordersc

lectronicallytransmissio

oreducela

rm

Nasdaq

NYSElis

BATS:4

DirectEd

sedmarke

0bytemes

tmajorexc

andleorde

manystoc

.Theyarei

lateralTradi

creasedca

rkingtowar

TSE

5,000S

inMumba

mingintot

send

or

rec

)fortradin

ency.

3mi

2mi

listedissue

edissue

0microsec

ge:30050

datadeliv

sagesperse

anges

flowat

an

exchanges

vestinginn

ngFacility.

acityfrom

sincreasin

NSE

5,000S

i,anofficial

heexchang

eiveinform

gstrategies.

lliseconds

lliseconds

650micro

50microse

nds

microseco

rysolution

condperc

given

poin

arestruggli

ewtechnol

1000orders

capacity.

ASX

250

S

fromthe

werefrom

ation.HFTs

.Worldwide

econds

onds

ds

thathas25

re.

intime.

ngtokeep

giesto

persecond

NDAQ

143S

NYSE

25

S


11/55

AverageTradesizeandNumberoftrades

Averagesharespertrade(AverageTradesize)decreasedby83%from1,477sharesin1997

to244sharesin2009,whileAveragetradesperDay(NumberofTrades)increasedby26

timesfrom743tradesin1997to19,943tradesin2009.AveragesharesPerDayincreased

from1.09

mn

(1477*743)

in

1997

to

4.86

mn(19943*244)

in

2009.

The

figures

show

that

thereisbeenincreaseinnumberoftradesexecutedanddecreaseinordersize.Thiscanbe

attributedtointroductionofalgotradingwhichslicelargeorderintomanysmallorders.The

negativeimpactofthisisthatitmayfloodthesystemwithlargenumberoforders

increasingtheloadonexchangestradingsystem.Alsoitincreasesclearingandsettlement

costsfortraders.

AverageOrderCancellationRate

SinceintroductionofAT,OrdertoTraderatiohassignificantlygoneupinmanycountriesincluding

India. AtNYSEordertotraderatiois30:1,whichmeansonlyoneorder,outof30ordersentered,

getsexecutedand29othersareeithermodifiedorcancelled.ATBSEordertotraderatiois19:1.

Theincreaseintheaverageordertotraderatioandaverageordercancellationratemaynobethe

concern

as

long

as

exchanges

have

built

sufficiently

large

capacity

and

have

limited

order

entry

rate

throughalgorithms.

0

200

400

600

800

1,000

1,200

1,400

1,600

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

Avg.

Shares/Trade

US Equity Share volume and trades

Avg Shares Per Day (mm) Avg Trades Per Day Shares / Trade


12/55

Chapter2

RegulatoryActionsWorldwide


13/55

Chapter3

Reasonsforusingalgorithmsintrading

TypesofAlgorithmsUsedbythebuysidefirms


14/55

Source:Algorithm

Trading

Survey

2010

conducted

by

Trading

screen

Overtheyears,algousagehasevolvedfromlesssophisticatedparticipation

strategiessuchasVWAPandTWAPtomorecomplexpriceimprovementapproachesthat

seektominimiseslippagefromatargetprice.Asaresultin2010,Implementationshortfall

(IS)forsinglestockshasriseninpopularity,upfrom39%in2008to68%.VWAPsawthefirst

notabledeclinesince2008initsuseamongbuysiderespondentsdownfrom64%to58%.

UseofTWAPalsodeclinedmarginallyfrom23%in2010to20%in2009.

Darkliquidityseekingalgorithmssearchesallthedarkpoolseliminatingtheneedto

splitanorderinsearchofliquidity.Darkliquidityseekingalgorithmsaremostwidelyused

algorithmsbybuysidefirmsin2010,constituting81%ofrespondentsuse,upfrom51%a

yearago.Similarly,albeitfromalowbase,therehasbeenafivefoldincreaseintheuseof

algorithmsto

take

advantage

of

internal

crossing

opportunities,

up

from

5%

in

2009

to

25%

in2010.Percentageofrespondentsusingvolumeparticipationstrategyandbasket

implementationshortfallstandat62%and20%respectively.


15/55

61%volumeinUS

39%volumeinUS

SourceTABBGroup

HFTs(MarketMakers/LiquidityProviders/SellSidefirms)

NonHFTs(Investors/BuySidefirms)

4%

28% 29%

3%

7%

13%16%

HFTHedge

Funds

HFTBroker/

MarketMakers

Independent

HFT R

etail

HedgeFunds

LongOnly

Investment

BankProp

US Equity Share Volume by Market Participant-2009


16/55

AlgorithmicTrading HighFrequencyTrading

AT istheuseofcomputerprogramsforentering

trading orders with the computer algorithm

deciding on aspects of the order such as the

timing,price,orquantityoftheorder

HFT is highly quantitative, employing

computerized algorithms to analyze incoming

market data and implement proprietary trading

strategies

Algorithmic Trading is computer aided but not

necessarilyHighfrequencyorlowlatencytrading

HFTispartofAlgorithmicTrading

Accounts for70%volume traded inUSequity in

2010.NonHigh frequencyAlgorithmicTrading is

only14%inUS.

Accounts for56%volume traded inUSEquity in

2010.

ATfirmsholdingperioddependsonstrategythey

employ.Theymayholdpositionsforfewminutes

or for few years or they might never sell it.

Typicallyaverageholdingperiodislong.

HFT usually implies a firm holds an investment

positiononlyforverybriefperiodsoftime even

justseconds andrapidlytrades intoandoutof

thosepositions

AT firms include both DayTraders and Position

Traders

and

may

carry

overnight

position

dependingonstrategytheyuse

HFT firms are typically DayTraders and end a

trading

day

with

no

net

investment

position

in

thesecuritiestheytrade.

AToperationsareusuallyfoundinBuySidefirms

(such as Mutual funds, Insurance companies,

Pension funds, FII, Investment Banks, some

HedgefundsandsomeProprietarytradingfirms)

HFT operations are usually found in proprietary

firms or on proprietary trading desks in larger,

diversifiedfirms

Selecting High Profit Making and properly

backtested algorithms is more important than

speed.SpeeddoesmatterinATtoo,butneedfor

speed

is

not

an

utmost

priority.

HFT strategies are usually very sensitive to the

processingspeedofmarkets(alsocalledLatency)

andoftheirownaccesstothemarket.

ApplicationofAlgoTrading

Directional Trading : Trend Following, Pair

Trading,MeanReversion,Scalping

Arbitrage : Delta Neutral Strategies, Statistical

Arbitrage

Transaction cost reduction(Trade Execution) :

VWAP,TWAP,Liquidityseeking, Implementation

shortfall

ApplicationofHFT

RebateTrading,MarketMaking,

FilterTrading,MomentumTrading,

StatisticalArbitrageandTechnicalTrading


17/55

4.1Dat

Datasa

areasfo

AA

AAPL

ABD

ADBE

AGN

AINV

AMAT

AMED

AMGN

AMZN

ANGO

APOG

aSample

plechosen

llows

Sa

ARCC

AXP

AYI

AZZ

BARE

BAS

BHI

BIIB

BRCM

BRE

BW

BXS

HFTand

forstudyin

ple:List

Z C

B C

BEY C

BT C

BZ C

CO C

DR C

ELG C

ETV C

HTT C

KH C

MCSA C

Ch

itsimpa

impactof

f120stock

NQR CTS

OO DC

OST DE

PSI DIS

PWR DK

R DO

RI EB

RVL EBF

SCO ERI

SE ES

SL EW

TRN FC

apter4

tonMa

FTinstock

listedone

H FFIC

M FL

L FME

FPO

FRED

FULT

Y GAS

GE

E GEN

X GILD

BC GLW

GOO

rketQua

listedone

itherNASD

GPS

HON

HPQ

IMGN

INTC

IPAR

ISIL

ISRG

JKHY

KMB

KNOL

KR

lity

itherNASD

QorNYSE

KTII

LANC

LECO

LPNT

LSTR

MAKO

MANT

MDCO

MELI

MFB

MIG

MMM

QorNYSE

MOD

MOS

MRTN

MXWL

NC

NSR

NUS

NXTM

PBH S

PFE S

PG S

PNC S

NY

PD

TP

IGL

OC

OCK

OG

VI

F

FG

JW

WN


18/55

Source:HighFrequencyTradingandItsImpactonMarketQualitybyJonathanBrogaard,

Sept2010

Note:Thesestatisticsareanaggregatefor26HFTfirmstradingactivityin120stocksfor

fiscalyearendingonDecember31,2009.

4.2HFTactivityinUS

HFTsareinvolvedin68.5%ofalldollarvolumetradedinthesample.Theirlevelofdaily

involvementvariesfrom60.4%to75.9%.Theydemandliquidityin42.7%ofalldollar

volumetradedandsupplyitin41.1%.

HFTsparticipatein73.8%ofalltradesandparticipationvariesatthedaylevelfrom65.1%to

81.9%.Theydemandliquidityin43.6%ofalltradesandsupplyitin48.7%.

PanelA >DollarVolumetradedbyHFTsaspercentageofTotalDollarVolumetradedinthe

sample

of

120

stocks

PanelB >QuantitytradedbyHFTsaspercentageofTotalQuantitytradedinthesampleof

120stocks

Source:HighFrequencyTradingandItsImpactonMarketQualitybyJonathanBrogaard,

Sept2010

Note:Thesestatisticsareanaggregatefor26HFTfirmstradingactivityin120stocksfor

fiscalyearendingonDecember31,2009.

4.3DoHFTsfleeinvolatilemarkets?

WhileHFTmaybeincreasinglyprovidingliquiditytothemarketintheplaceofmore

traditionalmarketmakingactivities,someinvestorssuggestedthatunlikeregisteredmarket

makersontradingvenuesthereisnoobligationorincentiveforhighfrequencytradersto


19/55

continuetoprovideliquiditytothemarketintheeventofadversemarketconditions(high

volatility).

ResearchshowsasindicatedinGraph1,HFTsactivityappearstobealmostflat

acrossvolatilitylevels.EvenonthemostvolatiledaysHFToverallactivitydoesnotseemto

increaseordecreasesubstantially.However,whenvolatilityislowHFTsactivityislessthan

average.

Where,

HFT%ChangePercentchangeinHFTactivity

HFT%MA(9) 9DaymovingaverageofpercentchangeinHFTactivity

95%confMA(9)UpperandLowerpricebandofHFT%MA(9)

Source:

HFTprovide

about

10%

more

liquidity

than

usual

on

very

low

volatility

days.

The

level

of

HFT

liquidityslowlydeclinesasvolatilitypicksup,atthehighestvolatilitytheHFTliquidityis

about10%lessthanonanaverageday.

HFTactivitymorethanaverage

HFTactivityLessthanaverage




20/55

OntheleastvolatiledaysHFTtakeabout7%lessliquiditythannormal,andonthemost

volatiledaystheytakearound5%moreliquiditythannormal.

TheseresultsshowthatHFTactivitydoeschangewithvolatility,butnotprecipitously.In

particularonthemostvolatiledays,HFTdonotpulloutofthemarket.Onthesedays,there

doesseemtobea510%transferofHFTactivityfromsupplyingliquiditytodemanding

liquidity.

4.4DoHFTscontributetoPriceDiscoveryProcess?

Ofthe118stocks,68stocksshowashavinggreatercontributiontopricediscoveryprocess

and28

of

those

stocks

HFT

Non

HFT

contribution

is

statistically

significant.

In

the

50

stocks,

wherenonHFTcontributionisgreaterthanthatofHFT,thedifferenceisstatistically

significantfor7firms.

OnaverageHFTcontribute86%,[(0.1950.105)/0.105*100],moretopricediscoverythando

nonHFT.BasedontheseresultswecansafelysaythatHFTcontributetopricediscovery

process.

Table14:HFT nonHFTVarianceDecomposition




21/55

WhereHFT%showsVariance(EfficientPrice,HFTtradeprice)

NonHFT%showsVariance(EfficientPrice,NonHFTtradeprice)

TStattstatisticsfordifferencebetweenHFTandNonHFTcontributiontopricediscovery

Source:

4.5WhatroleHFTplaysinprovidingmarketliquidity?

ThissectionanalyzesHFTandthesupplyofliquidity.

a) DoHFTordersprovideinsidequotesmoreoftenthanNonHFTorders?

Insidequoteiseitherbestbuyquoteorbestsellquote

Table16:TablereportsnumberofminutesduringwhichHFTsareatthebestbidoroffer.


22/55

(ThetimeduringwhichbothHFTsandnonHFTsarebothatthebestquotesisalsoincluded

inthevalue.)

PanelAallstocksatalltimes,

PanelBthestocksthatareofferinglowerspreadsthanaveragealltime

PanelCthestocksthatareofferinglowerspreadsthanaveragealltime

IneachPanelthedataaredividedintothreegroups,with40firmseach,basedonfirmsize

Viz.Small,MediumandLarge

Sample=780=2(Providingeitherinsidebid/offerevery

minute)*60(minutes/hour)*6.5(tradinghours)=NumberofminutesthataHFTcould

potentiallybeprovidingatleastoneinsidequote

PanelAshowsthatHFTfirmsfrequently(ataround65.3%(=509.3/780*100)ofthetimeof

theday)providethebestbidorofferquotes.AsthefirmsizeincreasesHFTsaremore

competitiveintheirquotes,matchingorbeatingnonHFTsquotesforasignificantportionof

theday.

AlsothereisnosignificantdifferencebetweenliquidityprovidedbyHFTfirmsinHighspread

&Lowspreadstocks


23/55

b) DoesHFTprovidedepthtotheorderbook?

Inprevioussection,theanalysisonliquidityhasbeenbylookingatthebestinsidebidand

asks.AnotherwayoflookingatHFTimpactonliquidityisbylookingatthedepthofthe

booksuppliedbyHFT.PanelAandBshowsincreaseinimpactcostduetowithdrawalof

eitherHFTordersorNonHFTorders.

Firmsare

divided

based

on

their

market

capitalizations.

Very

Small

includes

firms

under

$

400million,Smallarethosebetween$400millionand$1.5billion,Mediumarethose

between$1.5billionand$3billion,andlargeareforfirmsvaluedatmorethan$3billion.

DollarDollarincreaseinimpactcost

BasisPercentincreaseinimpactcost

PanelAshowstheresultsofremovingHFTfromthebook.Asthetradesizeincreases,the

priceimpactincreasesacrossfirmsofallsizesandforalltentradesizeincreases.TheSmall

categorytendstobemoreimpactedbythewithdrawalofHFTliquiditythanistheVery

Smallcategory.

PanelB

shows

the

results

of

removing

non

HFTs

from

the

book.

AcrossallcategoriestheremovingofnonHFTshasamuchlargerimpactthandoesthe

removalofHFTs.ThismeansthatalthoughHFTssupplyliquidityin41%ofalldollarstraded,

theyprovideonlyafractionofthedepthcomparedtononHFTs.


24/55

Conclusion:Beyondsupplyingliquidityin51.4%ofalltrades,HFTsfrequentlysupplythe

insidequotesthroughouttheday.Whileremovingeithertypeoftraderwouldresultina

priceimpactsoftrades,removingnonHFTshasalargerimpact

4.6DoHFTgenerateordampenvolatility?

Assumption:Prices

would

have

achieved

their

actual

levels

even

in

the

absence

of

high

frequencytradesbutwouldjumparoundmore.

Ofthe120firms,72ofthemhaveahighervolatilitywhenHFTrinitiatedtradesare

removed.Further,AsmallmajorityoffirmsexperienceslightlyhighervolatilitywithoutHFTr

initiatedtrades.Howeverofthese72stocks,onlyoneisstatisticallysignificant.This

indicatesvolatilitywouldhaveincreasedintheabsenceofHFT.

Ofthe48stockswheretheremovalofHFTrinitiatedtradesreducesvolatility,suggestiveof

HFTscausingvolatility,noneshowastatisticallysignificantdifferenceinvolatility.


25/55

Conclusion:TheoverallresultsshowthatwhenHFTrinitiatedtradesareremoved,volatility

increasesandthisdifferenceisstatisticallysignificant.Admittedlytheresultsarenotstrong

inonedirectionoranother;theyleaninfavourofHFTreducingvolatility.


26/55

Chapter5

PossibleManipulationsUsingHFT/AlgorithmicTrading1) FrontRunning

Frontrunningisanillegalactivityinwhichatradertakesapositioninanequityin

advanceofanactionwhichhe/sheknowshis/herbrokeragewilltakethatwillmove

theequity'spriceinapredictablefashion.

ApartfromFlashTrades(discussedbelow),whichsomebelieveispartofFront

Running,thereisnooccurrenceoffrontrunningusingAlgorithmicTrading.

FlashTradingServicesshowstockpricinginformationtosomeselectmember

around500millisecondsbeforeroutingittopublicmarket.Ifsuchordersareoflarge

quantity,fewmemberscantakeadvantageofitbyfrontrunning.

In2008,SEBIallowedstockexchangestoofferDMAfacility,whichmanybelieve

helpsInstitutionswithlargeorderstoexecutethetradesdirectlyonstockexchange

withoutmanualinterventionofTradingMember.

ThereisnoconclusiveevidencethatwoulddefinerelationshipbetweenFront

runninganduseofAlgotrading.Andhence,useofAlgorithmicTrading(without

usingDMA)willnothaveanysignificantimpactonIncreaseordecreaseofnumber

ofinstancesoffrontrunning.

2) Orderstuffing/Quotestuffing

Quotestuffingisessentiallyadenialofserviceattack,aimedattryingtoslowdown

amarketinanenvironmentwheremillisecondsmatter.

Withquotestuffing,highfrequencytradersenteranenormousnumberofbidsand

offers,significantlyoutsidethecurrentbidofferspread,justtointroduceavast

amountofnoiseintothequotefeed.Allthatnoisetakestime(maybejustafew

extrananoseconds)forrivalHFTshopsandExchangesTradingSystemstoprocess,

givingthequotestufferacrucialtimeadvantage.

TheSECislookingintowhetherquotestuffingexists,andwhetheritsastrategythat

anybodyhasactuallyusedtomakemoney.Theyarealsoinvestigatingwhether

Quote

stuffinghasanyinvolvementinFlashCrashthathappenedonMay6,2010.

InIndia,myguessisquotestuffingmaynotexistsatthispointintime,givenvery

lowparticipationbyHFTsbutagainwecannotruleoutchanceofhappeninginthe

futurewith

more

and

more

penetration

by

HFTs.

Quote

stuffing

is

worldwide

regardedasveryseriousactandshouldbepunishedseriouslyifattemptedbyany

marketparticipants.

3) FlashTrades


27/55

Flashordersshowsstockpricinginformationforabriefperiodtoalimitedgroupof

membertraderswhocanthendecidewhethertofillanorderbeforeitisroutedout

tothepublicmarket.

DirectEdge,anelectroniccommunicationsnetworkbackedbyGoldmanSachs,

CitadelandKnightTrading,wasthefirsttooffersuchanordertypetoitsmembers

in2006.

NASDAQ

and

Bats

(U.S.

exchanges)

created

their

own

flash

market

in

early

2009inresponsetotheDirectEdgemarket.Bothvoluntarilydiscontinuedthe

practiceinAugust2009.

DirectEdgebecameaU.S.exchangeinJuly2010andusedflashtradingtogreat

successinsiphoningmarketvolumeawayfromNYSE,BatsandNasdaqandnowit

claimsthirdlargestexchangeinUS.CurrentlySECisconsideringbanningFlash

TradinginUSfollowingcomplaintbyEuronextoperatorofNYSEandGletcoOneof

thetopmarketmakersinUS.

Officially,sofar,nostockexchangeinIndiaisofferingthisservicebutintroductionof

SORmay

open

the

gates

of

opportunities

for

stock

exchanges

to

attract

institutional

tradersbyprovidingflashtradingfacility.Flashtradingservicegivesunfairadvantage

toselectgroupofpeople/institutionsattheexpenseretailinvestors.Thisserviceis

detrimentaltothedevelopmentofsecuritiesmarketandSEBIshouldenact

regulationstobanitsoperationinIndia.

4) Internalisation

Internalisationreferstoabilityofbrokerstomatchcustomersawayfrompublic

markets.

InIndia,SEBIhasbannedinternalcrossingofordersandmandatedthatall

ordersenteredbyclientsmustbesubmittedtocentralordermatchingsystemofthe

exchanges.Thispreventssettingupofstealthstockexchanges,darkpoolsorprivate

tradingvenues,stealingliquidityawayfromthemarket.

Inspiteofhavingsuchstrongregulations,Icannotruleoutthepossibilityof

useofalgorithmstodevelopInternalCrossingsystems,whichIamsuremany

brokeragefirmswouldbeetchingtostartinordertoreducetransactioncostfor

theirproprietarytrades.HighcostoftransactioninIndiacouldactuallyworkasan

impetusforuseofsuchsystems.

5) Layering

LayeringisatechniqueofenteringLimitOrderswithlargequantityatdifferentprice

levelonanysideoforderbookinordertocreateafalseappearanceofbuy orsell

sidepressure.


28/55

Person,whowantstobuyastock,entershiddenbuyorderatbestbidandenters

numerousselllimitorderwithlargequantityatsuchapricelevelsthathavelow

probabilityofgettingexecuted.Thiscreatesanimpressionthattherearemany

sellersinthescriptandhenceitmaygodowninducingotherpeopletoselltheir

stockstobuyer(manipulator)

InIndia,Layeringmaynotbeusedthatextensivelymainlybecauseabsenceof

DeepOrderBook.Only5bestbidsand5bestoffersareprovidedinIndiafora

particularscriptasagainstallpossibleordersprovidedinUS.Thislimitstheabilityof

DayTraderstotakeacallbasedondemandandsupplyofthestock. Layering

requiresasmanylimitorderstobevisibletoeffectivelyimplementit.

Havingsaidthis,IstillsuspectmanycasesofmanipulationusinglayeringinIndiain

LowVolumeorilliquidscriptswithoutthehelpofHFT.Permittinguseofalgorithmic

tradinginLowVolumestocks,mayaggravatethisproblem.Soifpermitted,itshould

beverifiedthatLayeringalgosarenotpermittedtouse.

FINRAimposed$1millionpenaltyonTrilliumBrokerageServices,LLCforusinganillicithighfrequencytradingstrategy

Trillium,throughnineproprietarytraders,enterednumerouslayered,nonbonafide

marketmovingorderstogeneratesellingorbuyinginterestinspecificstocks.By

enteringthenonbonafideorders,ofteninsubstantialsizerelativetoastock's

overalllegitimatependingordervolume,Trilliumtraderscreatedafalseappearance

ofbuy orsellsidepressure.

Thistradingstrategyinducedothermarketparticipantstoenterorderstoexecute

againstlimitorderspreviouslyenteredbytheTrilliumtraders.Oncetheirorders

werefilled,theTrilliumtraderswouldthenimmediatelycancelordersthathadonly

beendesignedtocreatethefalseappearanceofmarketactivity.Asaresultofthis

improperhighfrequencytradingstrategy,Trillium'stradersobtainedadvantageous

pricesthatotherwisewouldnothavebeenavailabletothemon46,000occasions.

Othermarketparticipantswereunawarethattheywereactingonthelayered,

illegitimateordersenteredbyTrilliumtraders.


29/55

6) Darkpools

7) WashTrades

Anillegalstocktradingpracticewhereaninvestorsimultaneouslybuysandsells

sharesinacompanythroughtwodifferentbrokersinordertoincreaseturnoverand

inturncapturetheattentionofgeneralpublicenticingthemtotradethestock.

Theresearch

conducted

by

ASX

suggests

that

there

is

been

an

increase

in

the

numberoftradesbeingcancelled,majorityofwhichwereWashTrades,from0.16%

inJan2009to0.39%inAug2009.ThereasonbehindthisismanyAlgoTradingfirms

employdifferenttradingStrategiesvizarbitragestrategies,marketmaking

strategies,directionalstrategiessimultaneously.Thisincreaselikelihoodthatbids

andoffersenteredfromthosealgoswillinadvertentlyexecuteagainsteachother.

8) Liquidity Detection

Liquiditydetectionisanumbrellatermfortradingstrategiesthatinvolvesendingsmall

ordersto

look

for

where

large

undisclosed

orders

might

be

resting,

on

the

assumption

that

Whenasmallorderisfilledquicklythereislikelytobealargeorderbehindit.Someofthe

commonliquiditydetectionstrategiesare:

Pinging:sendingoutlargenumbersofsmallorderswiththeintentionofgettingafillorto

gaininformationaboutelectroniclimitorderbooks;

Sniper:anAlgorithmthattriestodetecthiddenliquiditybytradinginroundoroddlots

untilitcompletesorreachesaninvestorslimitprice;

Sniffing:Usedtosniffoutalgorithmictradingandthealgorithmsbeingusedbysendinga

smallportionofanorderwaitingtoseeifsomeonecomesandgetsit.Sniffersattemptto

outsmartmanybuysidealgorithmictechniqueslikeiceberging.

AsurveywasconductedbyTABBgrouptofindwhetherliquiditydetectionisaformof

manipulation.

74%

of

market

participants

said

that

they

did

not

regard

liquidity

detection

as

aformofmanipulation,becausethetraderdoesnothavedirectknowledgeofanorder.


30/55

Concerns:

a) AreNSEandBSEequippedforpotentialattackontheirservers/Ordermatching

systemsbyQuoteStuffers?Ifyes,havetheydonestresstesting?

b) Havetheybuiltsufficientlystrongordermatchingsystemwithlargecapacity,

Highthroughout&LowLatency(TurnaroundTime)tohandleLargeOrderFlow

attremendous

speed?

c) Arestockexchangescapabletodetectandstopalloftheabovemanipulations

onrealtimebasis?AndIfyes,How?

d) HowstockexchangeswillensuresApprovedLimitsarenotviolatedbytrading

membersandtheirclientsonrealtimebasis?

e) Whatpunitiveactionswillbetakenifexchangesfoundanyofthe

abovementionedmalpracticesusedbyTMortheirclients?Orwilltheyoncase

tocasebasis?

Recommendations:

Iseenorealdangerinallowinginternalisationofproprietarytradingasit

avoidsextracostssuchasSTTonintradaytransactionsforTM.However,internal

matchingofclientsorderinternallyoracrossdifferentTradingMembershouldnever

beallowedasitraisesseveralClearingandSettlementissuesandalsothereisreal

riskofnewunregulatedtradingvenuessuchasdarkpoolbeingsetup.

SEBIneedstobeproactiveindefiningalloftheaboveoperationsas

fraudulentpracticesandhencebanningitsoperationinIndia.


31/55

Chapter6

HighFrequencyTradingHighfrequencytrading(HFT)isasubsetofalgorithmictradingwherealargenumber

oforders(whichareusuallyfairlysmallinsize)aresentintothemarketathighspeed,with

roundtripexecutiontimesmeasuredinmicroseconds.Programsrunningonhighspeed

computersanalyse

massive

amounts

of

market

data,

using

sophisticated

algorithms

to

exploittradingopportunitiesthatmayopenupformillisecondsorseconds.Participantsare

constantlytakingadvantageofverysmallpriceimbalances;bydoingthatatahighrateof

recurrence,theyareabletogeneratesizeableprofits.

Typically,ahighfrequencytraderwouldnotholdapositionopenformorethanafew

seconds.EmpiricalevidencerevealsthattheaverageU.S.stockisheldfor22seconds.

TABBgroup,afinancialservicesindustryresearchfirm,estimatesthatHFTnow

accountsfor56%ofturnoverinUSAand38%turnoverinEuropeintheequity

segment.

AsperLondonstockExchangesresponsetoCESRquestionnaire,inthefirstquarter

of2010,numberofordersexecutedthroughHighFrequencyTradingaccountedfor

33%oftotalturnoverintheEuropeanmarket.


32/55

(Details

algorith

Arbit

DeltaN

EventBArbitr

boutTradi

sandLiqui

ragestra

etralStA

asedage

gstrategie

dityseeking

tegies

atisticalrbitrage

Ch

lgorithmic

areoutline

algorithms

AlphSt

DirectionaTrading

Strategies

ScalpingStrategies

apter6

radingstra

dinAnnexu

areprovide

aSeekinategies

l MeReve

Strat

DarkLiSee

Strat

egies

re3&Deta

inannexu

ansiongies

uidityinggies

V

Sh

Vo

Cl

ilsaboutBe

re2)

CostRExecutio

enchmarklgorithms

(AP,Impleentationortfall,Partipation(%lume),Targ

tose,TWAP,InLine,etc)

nchMark

ductionnStrate

i

Liqui

see

algori(CrossF

nt,Iceb)

/ies

ditying

hmsire,Hurg,etc


33/55

HighFrequencytradingstrategies


34/55

Chapter7

CurrentRiskManagementframeworkinIndia

PriceBandsinEquityandF&OSegment

InIndia,therearepricebandsof2%,5%,10%and20%onindividualsecurity.

Nopricebandisapplicableonscripsonwhichderivativeproductsareavailable.Restall

securitiesarecategorisedindifferentcategoriesbasedontheirdailyvolumeandimpact

cost.2%,5%,10%and20%bandsareapplicableonthosecategories.

Oncescriphitapricebandoneitherside,tradingishaltedforremainingday.

InF&O,therearenopricebandsbuttopreventerroneoustradeentry.Operationalprice

bandsaredefinedas10%forIndexfutures,20%forstockfuturesandDeltabasedvaluefor

Stock&indexoptions.

Indexwise

Circuit

Filter/

Circuit

Breakers

IndexwiseCircuitFilterisanautomatedtradinghaltmechanism,whichstopstradingonthe

exchangeforspecifiedperiodoftime.

Thereare10%,15%and20%circuitbreakersontwomainindicesNifty&Sensex.

9:15am 1.00pm 1.00pm 2.30pm 2.30pm3.30pm

10%movement 1HrmarketHalt 1/2HrmarketHalt NoTradingHalt

9:15am1.00pm 1.00pm2.00pm 2.00pm3.30pm

15%movement 2HrmarketHalt 1HrmarketHalt TradingHalted

20%movement

Trading

Halted

for

rest

of

the

day

MarginingSysteminEquityandF&O

IndianmarketsaremuchbetterplacedvisvistheUSmarkets,thankstothepracticeof

collectingmarginsonarealtimebasis.Ifamemberfirmexhaustsitsmarginwithan

exchange,itisbarredfromtakingfreshpositions.IfclientortradingmemberorClearing

membercrossesspecifiedlimits,tradingfacilityissuspendedforallclientstradingthrough

TM(incaseTMviolateslimit)andalltradingmemberclearingthroughCM(incaseCM

violateslimit).

StocksarecategorizedinGroupI,II&IIIonthebasisofimpactcostandstockstradedinlast

6monthsforthepurposeofassigningdifferentmarginsondifferentcategorieshaving

differentrisk.

InEquity,InitialMargin=VaRmargin+Exposuremarginiscollectedonupfrontbasis,

TypicallyVaRMarginisintherangeof7.5 15%andExposuremarginrangesbetween5

10%.Sotypically,totalinitialMarginVariesfrom12.525%.MTMmarginiscalculatedby


35/55

markingeachtransactioninsecuritytotheclosingpriceofthesecurityattheendoftrading.

Andcollectedbeforestartofnexttradingday

InF&O,InitialMarginandExposuremarginarecollectedupfront.InitialMargin=Total

SPANMargin(VaRmargin)+BuyPremium+AssignmentMargin. AndExposureMargin3%

of

the

notional

value

of

a

futures

contract

(for

futures)

&

The

higher

of

5%

or

1.5

standard

deviationofthenotionalvalueofgrossopenposition (foroptions).TotalInitialMarginis

typically1520%ofTransactionValue.MTMmarginsarecollectedbeforestartofnext

tradingday.

PositionLimits

AttheendofeachdaytheExchangedisseminatestheaggregateopeninterestacrossall

Exchangesinthefuturesandoptionsonindividualscripsalongwiththemarketwide

positionlimitforthatscripandtestswhethertheaggregateopeninterestforanyscrip

exceeds95%ofthemarketwidepositionlimitforthatscrip.Ifyes,theExchangetakesnote

ofopen

positions

of

all

client/

TMs

as

at

the

end

of

that

day

in

that

scrip,

and

from

next

day

onwardstheclient/TMsshouldtradeonlytodecreasetheirpositionsthroughoffsetting

positionstillthenormaltradinginthescripisresumed.

InIndia,wehaveTMwise&clientwisepositionlimits,whichpreventasingleTMora

singleInvestorfromtakinghugepositioninasinglestock.Forclientsitis1%ofTotalFree

floatcapitalisation(forcash)and5%ofMWPL(forF&O)

NSEAlsomonitorFIIandMFpositionsforsectoralandcompanyspecificlimitssetbyRBI&

SEBI.

Thereare

stiff

penalties

for

violation

of

any

of

the

above

mentioned

limits

and

margining

requirements.

PretradeControlinF&Osegment

QuantityFreeze: AnyordercomingtotheexchangefortradeinNIFTY,S&P500,

BANKNIFTY,CNXITorMINIFTYfuture/optionwithquantitymorethan15,000willbeFreezed

untilbrokerconfirmitasagenuineorder.Fortradeinfuture/optiononindividualstocks,

freezequantityisasdecidedbyexchangefromtimetotime.

PriceFreeze: PricefreezeisoperationalonlyintheF&Osegment.Operationalpricebands

aredefined

as

10%

for

Index

futures,

20%

for

stock

futures

and

Delta

based

value

for

Stock

&indexoptions.

PretradeControlinEquitysegment

Apartfrompricebandstherearenopretradecontrolsinequitysegmenttocheck

erroneoustrades.InUSerroneoustradesthatareexecutedwayoutsidelasttradedprice


36/55

FirstcasewasofpunchingerrorinTulipITservicesonJan5,2006.TulipITServicessawtwo

unusualtradeshappeningonitslistingday.Onedealsaw4,04,800sharessoldat25paiseeach

againsttheaveragepriceofRs185attheBombayStockExchange,whiletheothersaw5,95,575

sharessoldatRs100each.ThosedealscausedtheselleralossofRs12.69croreinjust38

seconds.ThefirsttransactionledtoanetlossofRs7.40crorewhilethesecondtransactioncost

Rs5.06crore.

ThesecondcaseisfreaktradeinRelianceonJune1,2010.Amarketordertosell1.6lakhshares

wasenteredinReliancebyadealeratabrokermemberfirmwhichgotmatchedwithlimit

purchaseordersinthetradingsystem.Withinfewsecondsofenteringorder,Reliancestock

plungedtoRs840.55frompretradepriceofRs1,010causingscripttofallby19.56%.Many

analystsbelievethistrademighthavecostbrokingfirmamorethanRs1crore.

maybecontestedandcancelledaftercomplainingtotherespectivestockexchange.Ihave

giventwocaseswheretradeswerecancelled.

PersonallyIdontthinkanytradeshouldbecancelledevenifitisthepunchingerror.

Recommenduseof5%DynamicPriceBand

Whyis

it

important

to

implement

such

stringent

operational

dynamic

price

bands?

ThereweretwocasesinthehistoryofIndianSecuritiesMarketthatcausedtremendousloss

tothebrokingfirmsandtheirclientsduetopunchingerrorsbyoperators.

Bothofthesecasescouldhavebeenavoided,hadtherebeen5%pricebandoperational.

Havingnarrowpricebandof5%ensuresthatasingletradecantmakeanystockfallbymore

than5%.

Case1:NYSEEuronextcancelledalltradesinthe$74.8billionSPDRS&P500ETFTrustthat

occurredatalmost10percentbelowthesecuritysopeningprice,accordingtoanemailsentby

theexchange.

ThetradesoccurredontheNYSEsArcaplatformat4:15p.m.NewYorktimeon18/10/2010and

pricedthe

exchange

traded

fund

that

tracks

the

Standard

&

Poors

500

Index

at

$106.46

comparedwithitsopeningpriceof$117.74.TheETFplunged9.6percentovereightsecondsas

7.2millionsharestradedonNYSEArca,accordingtodatacompiledbyBloomberg.TheS&P500

rose0.7percenttocloseat1,184.71today.Theglitchoccurredaftertheclosingauctionwas

delayedduetoasoftwareupgradeattheexchange.Officialclosingpriceineachsecurityis

decidedinanauctionprocessconductedaftercloseofthemarket.

Case2:Nasdaq&NYSEcancelledalltradesin296securitiesthatwereexecutedatgreateror

lessthan60%oftheirpricesat2:40p.m.ETonMay6,2010


37/55

ProcedureforgrantingpermissiontoTradingMemberforAlgorithmTrading

a) NSE,onMay17,2011,issuedacirculartosmoothentheprocessandfacilitateearly

approvalofdecisionsupporttools/algorithmsfortradingthroughnonneatfront

end. Itcategorisedapplicationforseekingapprovalinalgotradinginthreemain

categories

viz.

Approved

Algorithms

through

CTCL,

Non

Approved

Algorithms

throughCTCLandDMAAlgorithms.ThiscategorisationgivesNSEoptiontoscrutinize

newalgosmorefortheirpretradeandposttraderiskcontrolsthanalready

approvedalgos.

b) OnfulfilmentofconditionsassatisfactoryandmeetingSEBIandExchangesminimum

requirements,theexchangewillidentifythevendors/membersalgorithmas

Approvedalgorithm.

c) Totalproceduretakesaround30daystogetalgoapprovedfromdayofapplication.

(Fordetailsrefertoannexure4.

Concerns

1) NSEis

not

disclosing

risk

control

limits

to

public.

So

it

raises

concerns

that

process

maynotbetransparentandtheremayexistdifferentlimitsfordifferentclients.

Recommendations

1) NSEshoulddiscloseriskcontrollimitsontheirwebsiteasspecifiedintheformat

below.

AlgorithmWise FirmWise

MaxNumberofAlgosallowedto

operatesimultaneously

NA

MaxNumberofOrderspersecond

2) NSEtoprepareMonthlyReportonAlgoTradinginformatsspecifiedinTable1and

shouldprovidetoSEBIasandwhenneeded.Sinceturnoverbeingcompanyspecific

datawecannotpublishitinourMonthlyBulletinandannualReports.

3) ButfortheinformationofInvestors,exchangesneedtopublishtotalturnover

throughalgotradingeverydayonitswebsite.TheyshouldalsoprovidedatatoSEBI

informatspecifiedinTable2.ThishelpsSEBIensurethattherequiredinfrastructure

forAlgoTradingisinplaceandalsoitprovidesInvestorsanoptiontoexitthe

market,iftheyfeelthereishighamountofAlgoTradingActivity,whichisnot

suitabletotheirriskprofile.


38/55

Table1

Nameof

theFirm

Typeoffirm

(BuySide/

Sellside)

Dateof

approving

1stalgo

Numberof

algos

approved

Orders

entered

Orders

Cancelled

Orders

Traded

1 2 3 4 5 6 7

Average

Size(Qty)

ofthe

order

Average

Valueofthe

Order

TotalTurnover

(Monthly) Optedfor

DMA

facility?

OptedForCo

Location?Through

Active

Orders

Through

Passive

Orders

8

9

10 11 12 13

Table2

BSE NSE

Capacity(Orderspersecond)

Latency(RoundtripExecution

time)

Latency(Datafeeds/Info

disseminationtime)

AverageDailyOrders

OrderFlow(throughDMA

facility)

Orderflow(throughAlgo

Trading)

AlgoTradingvolumeas

PercentageofTotalVolume

OrderFlow(throughCoLocation

facility

Numberofordersdivertedto

other

Stock

Exchanges

through

SOR

NumberofAlgosregistered

NumberofBuysideFirms

registeredforAT

NumberofSellsideFirms

registeredforAT


39/55


40/55

Directcontroloffilters:DeterminedbywhethertheParticipanthasexclusiveandcontinualaccess

tosetandamendavailableprereleaseorderfilters.

Presubmissionorderlevelfilters:Filtersthatassessanorderasadiscreteunitratherthanaspart

ofanaccount.Filtersaredesignedtopreventerrorsinprice,valueanddirectcompliancesuchas

shortselling.

Presubmissionaccountlevelfilters:Filtersthatassessanorderinthecontextofaccountlevel

exposure.Such

filters

depend

on

aconsolidate

account

position

irrespective

or

execution

venue.

Exchange Filtered

1. Introduction

of

5%

dynamic

price

bands

on

all

securities

OperationalPriceBandrequirementshouldbemadestringentforalgorithmtrading

topreventsystemsfromenteringerroneoustrades.

Forstockswithpricelessthanorequalto10,operationalpricebandshouldbe5%of

thelasttradedpriceinallscriptslistedatNSE&BSE.Thispricebandwillchange

everysecondwitheverynewtradehappening.

Justforexample: IfaXYZstockiscurrentlytradingatRs100,Anyalgotrading

systemwillnotbeabletoenterbuyorderatmorethanRs105andsellorderatless

than95.

Placingabuyorderbelowcurrentmarketprice&placingasellorderaboveCMPwill

improveliquidity

as

this

would

increase

number

of

passive

orders

sitting

in

the

order

book.SoinourexamplebuyerwouldbeabletoenterbuyorderatlessthanRs95

andsellorderatmorethanRs105.

However,thisrulewillbeanexceptionforstoplossorder.InstopLossordertrader

canplacetriggerpriceandlimitpriceatanypricehedesires.

ThisruleshouldalsobeapplicableonthefirsttradingdayoftheIPO.

2. Mechanismtoflushoutallthependingorders

3. IntroductionofMakerTakerStructureAnexampleofanewtradingstrategythathasemergedoverseasandattractedthelabel

predatoryisa

Form

of

arbitrage

designed

to

ensure

that

the

HFT

receives

a

rebate

for

providing

liquidity

to

aretailorinstitutionalinvestor.Thisstrategyistheresultofmarketmicrostructurechanges

whichmakecertaintypesoftradingprofitableforhighfrequencytraders,wherepreviously

thiswasnotthecase.


41/55

Chapter9

Conclusion

Highfrequencytraderstendtosticktoliquidstocksandliquidderivativescontracts.Hence,

theyhavent

yet

contributed

meaningfully

in

enhancing

liquidity

of

the

other

stocks

and

illiquidderivativescontractssuchasstockoptions.

Needlesstosay,thelargerconcernabouthighfrequencytrading(HFT)isthatitcould

destabilizemarkets,especiallyaftertheflashcrashintheUSon6May2010.Itmustbe

notedthatsuchasituationcanariseeveninaworldwithoutHFT.Aflashcrashsituation

ariseswhenalargeorderisplacedintoathinorderbookinadvertently.

Therearemixedviewsontheimpactsofalgorithmtradingwillbeonthemarket.Positive

Impactsmayincludeenhancedliquidityandtransactioncostsavings,whilenegativesmay

Includeundermined

market

stability

due

to

frequent

trading.

Ibelievethatactivealgorithmictradingwillservegreatlytomanagethemarketimpact,as

wellasreducinganysideeffectscausedbyalgorithmsniffing.Howeveritistruethat

algorithmtradingitselfhascreatedsomenegativessuchaslowsettlementratesandsystem

overloadissues,whichneedtoberesolved.

SGXemphasizeshighspeedmessaging,theshorteningofmarketdatadelays,andresearch

onnew

products.


42/55

AnnexureIII

A) GeneralAlgorithmicStrategies

1) TrendFollowing

Trendfollowingisaninvestmentstrategythattriestotakeadvantageoflongterm

movesthatseemtoplayoutinvariousmarkets.Thesystemaimstoworkonthemarket

trendmechanismandtakebenefitfrombothsidesofthemarketenjoyingtheprofitsfrom

theupsanddownsofthestockorfuturesmarkets.Traderswhousethisapproachcanuse

currentmarketpricecalculation,movingaveragesandchannelbreakoutstodeterminethe

generaldirectionofthemarketandtogeneratetradesignals.Traderswhosubscribetoa

trendfollowingstrategydonotaimtoforecastorpredictspecificpricelevels;theysimply

jumponthetrendandrideit.

2) PairTrading

Thepairtradingisamarketneutraltradingstrategyenablingtraderstoprofitfrom

virtuallyanymarketconditions:uptrend,downtrend,orsidewisemovement.Thistrading

strategyiscategorizedasastatisticalarbitrageandconvergencetradingstrategy.

3) DeltaNeutralStrategies

DeltaNeutralstrategyisalsoknownasCash F&Oarbitragestrategy.Deltadenotes

changeinoptionpricewithonerupeechangeintheunderlyingassets.Deltaforcalloption

isintherangeof0to1,whereasforputoptionitvariesfrom 1to0.Deltaforstock/future

isalways

1.

So

buying/

selling

any

of

the

three

assets

in

specific

quantity

can

make

our

portfoliodeltaneutral.

Arbitragerbenefitsfromdecayingoptionvalue(theta)ifheisshort.Arbitragercanalso

benefitfromincreaseinvolatilityifheislongvolatilityandviceversa.

4) Arbitrage

Basically,arbitrageisexploitingbenefitofmispricedassetstoearnriskfreeprofit.


43/55


44/55


45/55

currentpriceinordertoprovideliquiditytoothermarketplayersand,inthisway,benefit

fromthebidaskspread.

Profitabilityisenhancedbythefactthatmanytradingcentresapplythemakertakerfee

structure.Thisstrategyisoftencalledmarketmakingbuttodosomaybeinappropriate.

SomeHFTfirmsregisterwiththetradingvenuesonwhichtheyarememberstomeetthe

ongoingobligations

associated

with

being

an

official

market

maker.

However,

this

is

often

notthecase,asHFTfirmsmayactinsteadasinformalliquidityproviders,avoiding

prescribedmarketmakingobligationsandenjoyingbenefitsofthetraditionalmarket

makers.Bylookingattradedvolumes,HFTfirmshavebecomesignificantparticipantsinthe

liquidityandpriceformationprocessinmanymarketsandinstrumentsand,evenwhen

actinginformallyinthisrole,havepartlyreplacedtraditionalmarketmakers.Lowlatencyis

oftheutmostimportanceforthisstrategysinceprovidingliquiditymightinvolveholdinga

riskyinventorypositiononaninstrumentforsometime.Marketriskisminimizedbyrapidly

adjustingpostedquotestoreflectthearrivalofnewinformationortoadjustinventory.Asa

consequence,theratiooforderstotradesandthenumberofcancelledordersareveryhigh

inthisstrategy.

2) ArbitrageStrategies

Arbitragestrategiestakeadvantageofpricingdiscrepanciesandmayinvolvepurearbitrage

betweenthesameinstrumentstradedacrossdifferenttradingvenues(e.g.thesamestock

tradedatanexchangeandanATS/MTF),betweenanindexandtheunderlyingbasketof

securities,orbetweenrelatedinstruments(e.g.asecurityandanassociatedderivative).

Otherformsofarbitragelookatstatisticaldeviationsfromlongterm,historicalstatistical

relationships(e.g.correlations)amongsecurities.Assumingreversiontothemean,

significantdeviationsfromtheserelationshipsofferprofitabletradingopportunities.

Arbitragestrategiestendtoimprovepriceefficiencybyeliminatinginconsistenciesbetween

prices.They

also

tend

to

consume

rather

than

provide

liquidity

to

the

market,

as

the

short

livednatureofarbitrageopportunitiesmakesrapidexecutionoftradescritical.

3) Directionalstrategies

Directionalstrategies, includingeventstrategies,involveunhedgedpositionsbeingcarried

for some (albeit often short) period of time, in anticipation of small but lasting intraday

pricechanges.Basedonpastpatterns,HFTfirmsestimateexpectedpricechangestriggered

bythereleaseofmacroeconomicnews,corporateannouncementsorindustryreportswith

asignificantimpactonmarketprices.Aspasteventsgeneraterecognizableandstatistically

robust patterns, HFT firms estimate expected price responses to anticipated events.

Anotherdirectional

strategy

is

aliquidity

detection

strategy

which

involves

afirm

searching

forhiddendemand for liquidity in themarket.Undiscloseddemand is liquidity that isnot

reflectedintheorderbookandinthemarketprice.Thestrategyprofitsbymovingtheprice

againstlargehiddenbuyingorsellinginterest.

(SourceIOSCOreportonregulatoryissuesraisedbytheimpactoftechnologicalchanges

onmarketintegrityandefficiency)


46/55

AnnexureIV

ProcedureforgrantingpermissiontoTradingMemberforAlgorithmTrading

1. Procedureformakinganapplication

Tradingmember

desirous

of

seeking

approval

for

trading

using

algorithms

should

make

anapplicationinformatasspecifiedinAnnexure1

NSEcategorizedalgorithmapplicationsforapprovalinthreecategories,whichareas

follows

d) ApprovedAlgorithmsthroughCTCL

TradingMember,desirousofusingalgorithmswhicharealreadyapprovedbyNSEto

thevendors,canmakeanapplicationinthiscategory.Memberneednotgive


47/55


48/55

The Stocks which have traded at least 80% of the days for the previous six months shall

constitutetheGroupIandGroupII.

Outofthescripsidentifiedabove,thescripshavingmeanimpactcostoflessthanorequal

to1%arecategorizedunderGroupIandthescripswherethe impactcost ismorethan1,

arecategorizedunderGroupII.

TheremainingstocksareclassifiedintoGroupIII.

The impactcost iscalculatedonthe15thofeachmonthonarollingbasisconsideringthe

order book snapshots of the previous six months. On the basis of the impact cost so

calculated, the scrips move from one group to another group from the 1st of the next

month.

B) MarginsintheEquitysegments

Dailymarginspayablebymembersconsistsofthefollowing:

1. ValueatRiskMargin

2. ExtremeLossMargin

3. MarktoMarketMargin

AllthreeMarginsarecollectedonthegrossopenpositionofthemember.Thegrossopen

positionforthispurposemeansthegrossofallnetpositionsacrossalltheclientsofa

memberincludingitsproprietaryposition.

ValueatRiskMargin:

AllsecuritiesareclassifiedintothreegroupsforthepurposeofVaRmargin

ForthesecuritieslistedinGroupI,scripwisedailyvolatilitycalculatedusingthe

exponentiallyweightedmovingaveragemethodology.ThescripwisedailyVaRis3.5

timesthevolatilitysocalculatedsubjecttoaminimumof7.5%.

ForthesecuritieslistedinGroupII,theVaRmarginishigherofscripVaR(3.5sigma)

orthreetimestheindexVaR,anditisscaledupbyroot3.

ForthesecuritieslistedinGroupIIItheVaRmarginisequaltofivetimestheindex

VaRandscaledupbyroot3.

TheindexVaR,forthepurpose,isthehigherofthedailyIndexVaRbasedonS&PCNXNIFTY

orBSESENSEX,subjecttoaminimumof5%.

TheVaRmarginiscollectedonanupfrontbasisbyadjustingagainstthetotalliquidassetsof

thememberatthetimeoftrade.

TheVaRmarginsocollectedisreleasedoncompletionofpayinofthesettlement.


49/55


50/55

NSCCLhasdevelopedacomprehensiveriskcontainmentmechanismfortheFutures&

Optionssegment.ThemostcriticalcomponentofariskcontainmentmechanismforNSCCL

istheonlinepositionmonitoringandmarginingsystem.Theactualmarginingandposition

monitoringisdoneonline,onanintradaybasis.NSCCLusestheSPAN(StandardPortfolio

AnalysisofRisk)systemforthepurposeofmargining,whichisaportfoliobasedsystem.

InitialMargin

a.SpanMargin

NSCCLcollectsinitialmarginupfrontforalltheopenpositionsofaCMbasedonthe

marginscomputedbyNSCCLSPAN.ACMisinturnrequiredtocollecttheinitialmargin

fromtheTMsandhisrespectiveclients.Similarly,aTMshouldcollectupfrontmarginsfrom

hisclients.

Initialmarginrequirementsarebasedon99%valueatriskoveraonedaytimehorizon.

However,inthecaseoffuturescontracts(onindexorindividualsecurities),whereitmay

notbe

possible

to

collect

mark

to

market

settlement

value,

before

the

commencement

of

tradingonthenextday,theinitialmarginiscomputedoveratwodaytimehorizon,

applyingtheappropriatestatisticalformula.ThemethodologyforcomputationofValueat

RiskpercentageisaspertherecommendationsofSEBIfromtimetotime.

Initialmarginrequirementforamember:

Forclientpositions isnettedatthelevelofindividualclientandgrossedacrossallclients,

attheTrading/ClearingMemberlevel,withoutanysetoffsbetweenclients.

Forproprietarypositions isnettedatTrading/ClearingMemberlevelwithoutanysetoffs

betweenclient

and

proprietary

positions.

b.PremiumMargin

InadditiontoSpanMargin,PremiumMarginischargedtomembers.Thepremiummarginis

theclientwisepremiumamountpayablebythebuyeroftheoptionandisleviedtillthe

completionofpayintowardsthepremiumsettlement.

c.AssignmentMargin

AssignmentMargin

is

levied

on

aCM

in

addition

to

SPAN

margin

and

Premium

Margin.

It

is

leviedonassignedpositionsofCMstowardsinterimandfinalexercisesettlement

obligationsforoptioncontractsonindexandindividualsecuritiestillthepayintowards

exercisesettlementiscomplete.

TheAssignmentMarginisthenetexercisesettlementvaluepayablebyaClearingMember

towardsinterimandfinalexercisesettlementandisdeductedfromtheeffectivedepositsof

theClearingMemberavailabletowardsmargins.


51/55

AssignmentmarginisreleasedtotheCMsforexercisesettlementpayin.

InitialMarginrequirement=TotalSPANMarginRequirement+BuyPremium+Assignment

Margin

ExposureMargin

Theexposuremarginsforoptionsandfuturescontractsonindexareasfollows:

i.ForIndexoptionsandIndexfuturescontracts:

3%ofthenotionalvalueofafuturescontract.Incaseofoptionsitischargedonlyonshort

positionsandis3%ofthenotionalvalueofopenpositions.

ii.ForoptioncontractsandFuturesContractonindividualSecurities:

Thehigherof5%or1.5standarddeviationofthenotionalvalueofgrossopenpositionin

futuresonindividualsecuritiesandgrossshortopenpositionsinoptionsonindividual

securitiesin

aparticular

underlying.

MTMMargin

MTMmarginforF&OsegmentissameasthatofEquitysegment.

D) PositionLimits

ClearingMembersaresubjecttothefollowingpositionlimitsinadditiontoinitialmargins

requirements.

MarketWide

Position

Limits

(for

Derivative

Contracts

on

Underlying

Stocks)

TradingMemberwisePositionLimit

ClientLevelPositionLimits

FII/MFpositionlimits

MarketWidePositionLimits(forDerivativeContractsonUnderlyingStocks)

AttheendofeachdaytheExchangedisseminatestheaggregateopeninterestacrossall

Exchangesinthefuturesandoptionsonindividualscripsalongwiththemarketwide

positionlimitforthatscripandtestswhethertheaggregateopeninterestforanyscrip

exceeds95%

of

the

market

wide

position

limit

for

that

scrip.

If

yes,

the

Exchange

takes

note

ofopenpositionsofallclient/TMsasattheendofthatdayinthatscrip,andfromnextday

onwardstheclient/TMsshouldtradeonlytodecreasetheirpositionsthroughoffsetting

positionstillthenormaltradinginthescripisresumed.

Thenormaltradinginthescripisresumedonlyaftertheaggregateopeninterestacross

Exchangescomesdownto80%orbelowofthemarketwidepositionlimit.


52/55

Afacilityisavailableonthetradingsystemtodisplayanalertoncetheopeninterestonthe

NSEinthefuturesandoptionscontractinasecurityexceeds60%ofthemarketwide

positionlimitspecifiedforsuchsecurity.Suchalertsarepresentlydisplayedattimeintervals

of10minutes.

TradingMemberwisePositionLimit

Thetradingmemberwisepositionlimitinequityindexoptionandindexfuturesisasunder:

IndexFutures

ThetradingmemberpositionlimitsinequityindexfuturescontractsishigherofRs.500

croresor15%ofthetotalopeninterestinthemarketinequityindexfuturescontracts.This

limitisapplicableonopenpositionsinallfuturescontractsonaparticularunderlyingindex.

IndexOptions

ThetradingmemberpositionlimitsinequityindexoptioncontractsishigherofRs.500

croresor15%ofthetotalopeninterestinthemarketinequityindexoptioncontracts.This

limitwould

be

applicable

on

open

positions

in

all

option

contracts

on

aparticular

underlying

index

FuturesandOptioncontractsonindividualsecurities:

Thetradingmemberwisepositionlimitinfuturesandoptionsinindividualstocksisrelated

tothemarketwidepositionlimitfortheindividualstocks.

i.Forstockshavingapplicablemarketwidepositionlimit(MWPL)ofRs.500croresormore,

thecombinedfuturesandoptionspositionlimitis20%ofapplicableMWPLorRs.300

crores,whicheverislowerandwithinwhichstockfuturespositioncannotexceed10%of

applicableMWPLorRs.150crores,whicheverislower.

ii.Forstockshavingapplicablemarketwidepositionlimit(MWPL)lessthanRs.500crores,

thecombinedfuturesandoptionspositionlimitis20%ofapplicableMWPLandfutures

positioncannotexceed20%ofapplicableMWPLorRs.50crorewhicheverislower.

ClientLevelPositionLimits

Thegrossopenpositionforeachclient,acrossallthederivativecontractsonaunderlying,

shouldnotexceed:

1%ofthefreefloatmarketcapitalization(intermsofnumberofshares)or

5%oftheopeninterestinallderivativecontractsinthesameunderlyingstock(intermsof

numberof

shares)

whicheverishigher

Clientlevelpositionlimitsunderlyingwise,areavailabletomembersonNSE'swebsite.

E) Violations


53/55

PRISM(ParallelRiskManagementSystem)istherealtimepositionmonitoringandrisk

managementsystemfortheFuturesandOptionsmarketsegmentatNSCCL.Theriskofeach

tradingandclearingmemberismonitoredonarealtimebasisandalerts/disablement

messagesaregeneratedifthemembercrossesthesetlimits.

InitialMargin

Violation

ExposureLimitViolation

TradingMemberwisePositionLimitViolation

ClientLevelPositionLimitViolation

MarketWidePositionLimitViolation

Violationarisingoutofmisutilisationoftradingmember/constituentcollaterals

and/ordeposits

ViolationofExercisedPositions

Clearingmembers,whohaveviolatedanyrequirementand/orlimits,mayreducethe

positionbyclosingoutitsexistingpositionor,bringinadditionalcashdepositbywayof

cashor

bank

guarantee

or

FDR

or

securities.

Similarly,

in

case

of

margin

violation

by

Trading

members,clearingmemberhastosetitslimitforenablement.

InitialMarginviolation

TheinitialmarginonpositionsofaCMiscomputedonarealtimebasisi.e.foreachtrade.

TheinitialmarginamountisreducedfromtheeffectivedepositsoftheCMwiththeClearing

Corporation.Forthispurpose,effectivedepositsarecomputedbyreducingthetotal

depositsoftheCMbyRs.50lakhs(referredtoasminimumliquidnetworth).TheCM

receiveswarningmessagesonhisterminalwhen70%,80%,and90%oftheeffective

depositsareutilised.At100%theclearingfacilityprovidedtotheCMiswithdrawn.

Withdrawalof

clearing

facility

of

aCM

in

case

of

aviolation

will

lead

to

withdrawal

of

tradingfacilityforallTMsand/orcustodialparticipantsclearingandsettlingthroughthe

CM.

Similarly,theinitialmarginsonpositionstakenbyaTMarecomputedonarealtimebasis

andcomparedwiththeTMlimitssetbyhisCM.Theinitialmarginamountisreducedfrom

theTMlimitsetbytheCM.OncetheTMlimithasbeenutilisedtotheextentof70%,80%,

and90%,awarningmessageisreceivedbytheTMonhisterminal.At100%utilization,the

tradingfacilityprovidedtotheTMiswithdrawn.

Amemberisprovidedwithwarningsat70%,80%and90%levelbeforehistrading/clearing

facilityis

withdrawn.

A

CM

may

thus

accordingly

reduce

his

exposure

to

contain

the

violationoralternatelybringinAdditionalBaseCapital.

ExposureLimitViolation

ThisviolationoccurswhentheexposuremarginofaClearingMemberexceedshisliquid

networth,atanytime,includingduringtradinghours.Theliquidnetworthmeansthe

effectivedepositsasreducedbyinitialmarginandnetbuypremium.Incaseofviolation,the

clearingfacilityoftheclearingmemberiswithdrawnleadingtowithdrawalofthetrading


54/55

facilitiesofalltradingmembersand/orclearingfacilityofcustodialparticipantsclearing

throughtheclearingmember.

TradingMemberwisePositionLimitViolation

Thisviolationoccurswhentheopenpositionofthetradingmember/custodialparticipant

exceedstheTradingMemberwisePositionLimitatanytime,includingduringtradinghours.

Incase

of

violation

the

trading

facility

of

the

trading

member

is

withdrawn.

Inrespectofinitialmarginviolation,exposuremarginviolationandpositionlimitviolation,

penaltyisleviedonamonthlybasisbasedonslabsasmentionedbelow.

ClientLevelPositionLimitViolation

Thisoccurswhentheopenpositionofanyclientexceedsthe clientwidepositonlimit

TheTM/CMthroughwhomtheclienttrades/clearshisdealsisliableforsuchviolation.

Inthe

event

of

such

aviolation,

TM

/CM

should

immediately

ensure,

(i)thattheclientdoesnottakefreshpositionsand

(ii)reducesthepositionsofsuchclientstobewithinpermissiblelimits.

Additionally,intheeventofsuchaviolation,penaltywouldbechargedtoClearing

Membersforeverydayofviolation.

1%ofthevalueofthequantityinviolation(i.e.,excessquantityovertheallowedquantity,

valuedattheclosingpriceoftheunderlyingstock)perclientor

Rs.1,00,000perclient,whicheverislower,subjecttoaminimumpenaltyofRs.5,000/ per

violation/perclient.whentheclientlevelviolationisonaccountofopenpositionofclient

exceeding5%ofopeninterest,apenaltyofRs.5,000/ perinstanceischargedtoclearing

member.

TheClearingMembercanrecoverthepenaltysochargedfromtherespectiveTrading

Member/Clientviolatingtherequirementofpositionlimitsandincaseswhereitislevied

andcollectedfromTradingMember,suchtradingmember,inturn,canrecoverthesame

fromtherespectiveclientswhoviolatedthepositionlimits.

DisclosureforClientPositionsinIndexbasedcontracts

Anypersonorpersonsactinginconcertwhotogetherown15%ormoreoftheopen

interestonaparticularunderlyingindexisrequiredtoreportthisfacttotheExchange/

ClearingCorporation.Failuretodosoistreatedasaviolationandattractsappropriatepenal

anddisciplinary

action

in

accordance

with

the

Rules,

Byelaws

and

Regulations

of

the

ClearingCorporation.

Forfuturescontracts,openinterestisequivalenttotheopenpositionsinthefutures

contractmultipliedbylastavailabletradedpriceorclosingprice,asthecasemaybe.For

optioncontracts,openinterestisequivalenttothenotionalvaluewhichiscomputedby

multiplyingtheopenpositioninthatoptioncontractwiththelastavailableclosingpriceof


55/55

theunderlying.

MarketWidePositionLimitsforderivativecontractsonunderlyingstocks

Attheendofeachdayduringwhichthebanonfreshpositionsisinforceforanyscrip,when

anymemberorclienthasincreasedhisexistingpositionsorhascreatedanewpositionin

thatscrip

the

client/

TMs

are

charged

apenalty.

Thepenaltyisrecoveredfromtheclearingmemberaffiliatedwithsuchtrading

members/clientsonaT+1daybasisalongwithpayin.Theamountofpenaltyisinformedto

theclearingmemberattheendoftheday..

Violationarisingoutofmisutilisationoftradingmember/constituentcollateralsand/or

deposits

ThisviolationtakesplacewhenaclearingmemberutilisesthecollateralofoneTMand/or

constituenttowardstheexposureand/orobligationsaTM/constituent,otherthanthe

sameTM

and/

or

constituent.

ViolationofExercisedPositions

WhenoptioncontractsareexercisedbyaCM,wherenoopenlongpositionsforsuchCM/

TMand/orconstituentexistattheendoftheday,atthetimetheexerciseprocessingis

carriedout,itistermedasviolationofexercisedpositions.

final-issues concerning algorithmic trading in india

Documents