FIA European Principal Traders

Association

MiFID II Review –

Algorithmic and high frequency trading

1

08 May 2012

2

Agenda

Introduction to FIA EPTA A Brief History of Markets Why is Speed Important? Improvements to Market Quality The Role of High Frequency Trading FIA EPTA position on MiFID II

3

Introduction to FIA EPTA

FIA EPTA membership includes:

• Allston Trading

• Chopper Trading

• Citadel Securities

• DRW

• Flow Traders

• Getco Europe

• Hudson River Trading

• IAT Int.

• IMC Financial Markets

• Jump Trading

• Knight Capital

• Mako Group

• Optiver

• Positive Equity

• Quantlab Financial

• RGM Trading

• RSJ

• Spire Europe

• Sun Trading

• Tibra

• Virtu

• XR Trading

3

FIA EPTA Principles :

• Regulation

• Stability

• Transparency

• Risk Management

• Competition

• FIA EPTA supports transparent, robust and safe markets with a level playing field for

all. We believe these goals are promoted by opening markets to competition and

guaranteeing fair access to participants.

• FIA EPTA members believe principal traders contribute significantly to this goal by

providing liquidity and enabling immediate risk transfer by others.

FIA EPTA Mission Statement :

• Equality of access

• Equality of information

• Efficiency

• Integrity

A Brief History of Markets

4

The Old Days

• Monopoly position of Specialists and privileged position of Market Makers

• High spreads and high commissions. High frictional costs

• High barriers to entry for new participants, closed shop

Broker sales trader

Runner/floor broker

Specialist

Broker trader

BrokerBroker

$

$

$

Trading Desk Fund manager

ExchangeInstitution Institution

$

Trading DeskFund manager

$

Broker sales trader

Broker trader

5

Today – 2007 to Present

Trading Desk Fund manager

Exchange / ATSInstitution Institution

Trading DeskFund manager

Liquidity Providers

• Fewer intermediaries lead to lower frictional costs

• Multiple Liquidity Providers compete with each other

• Lower barrier to entry for new participants

6

Why is Speed important ?

A market maker’s quote…

…is valid until he cancels it

…needs to be updated when

the market moves

…results in exposure/risk for

the time the exchange takes to

process its cancellation

The higher the speed…

…the more immediate the

transfer of risk

…the more liquidity the market

maker is prepared to offer

…the tighter the bid-ask spread

he is willing to quote

Reduction in

frictional costs

to end-users

Speed is a risk management tool

7

Technology, Speed and Stability?

Exchange traded markets have functioned exemplary throughout the crisis

There is no indication that markets have become less stable as a result of

increased automation

In fact there is overwhelming evidence that markets have become more

efficient and substantially cheaper for the end users*

8

*Vanguard calculates that savings in transaction costs over the last 15 years have meant that an average pensioner will have 30%more funds in their investment account over a 30 year period.

Improvements to Market Quality through Use of Technology

Much academic evidence

supports the conclusion that –

as technology is used by an

increased number of market

participants - market quality has

improved over the past 20 years

Expands and lowers costs of access to information and markets

Reduces spreads

Adds liquidity

Maintains pricing efficiency in markets

Reduces volatility

9

Average Institutional Commissions - Europe

High touch (brokerage/ phone) is now less used by institutional traders (only 20%) with an average fee of 10-15 bps.

No touch (DMA) accounts now for approximately 80% of total value due to reduced fees and fast connectivity.

Source: IMC estimates

2000 2005 2011

Method of execution % of trades fee (bps) % of trades fee (bps) % of trades fee (bps)

High touch 100 % 25 – 40 70 % 15 – 20 30 - 40 % 10 – 15

No touch (DMA) N.A. 30 % 7 – 8 60 - 70 % 1 - 3

10

Trading Costs according to Oxera Report

Source: Monitoring prices, Costs and volumes of tradingand post-trading services by Oxera, May 2011

• Reduction in the costs of trading in all major financial centers (weighted average decrease of 21%

• The cost of trading corresponds to the sum of fees charged by:

• Trading platforms• Central counter-parties (CCP’s)• Central Securities Depositories (CSD’s)

11

Execution Costs for Institutions

12Sources: ITG global trading cost and YahooFinance

Imp

lem

en

tati

on

sh

ort

fall

(bp

s)

0

10

20

30

40

50

60

70

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

US Europe exUK VIX index

Vix

ind

ex

Deutsche Börse uses XLM to measure the liquidity of assets

traded in the Xetra limit order book on the basis of implicit

transaction costs.

The lower the XLM the lower the cost of trading an

instrument measured by market impact.

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

2004 2005 2006 2007 2008 2009 2010 2011

XL

M (

bp

)

XLM - €25k

DAX XLM (€25,000 Order)

The Xetra Liquidity Measure

0

20

40

60

80

ALV EON BAS DTE SIE DAI SAP BAY

€500k

Oct-01

Aug-11

0

20

40

60

80

100

120

140

ALV EON DTE BAS SIE SAP DAI BAY

€1MN

Oct-01

Aug-11

0

50

100

150

200

250

ALV EON DTE BAS SIE SAP DAI BAY

€2MN

Oct-01

Aug-11

XL

M (

bp

s)

XL

M (

bp

s)

XL

M (

bp

s)

Execution cost - FTSE

0

5

10

15

20

25

30

35

40

201120102009200820072006

Execution cost

25k 500k 1M

Execution cost is calculated by using the real effective spread.

(dividing the absolute value of the difference between

execution price and spread mid-point by the stock price.)

Analysis on the FTSE 8 biggest stocks. (ex-BP)

Re

f ft

(bp

s)

Ref ft

(bps)

Ref ft

(bps)

Ref ft

(bps)

0

5

10

15

20

25

201120102009200820072006

Execution cost

25k 500k 1M

Ref

ft

(bp

s)

Execution cost - CAC

Similar Analysis on the CAC 8 biggest stocks.

Ref ft

(bps)

Tokyo Stock Exchange – introduction of Arrowhead

Enhanced

Depth

Depth: November 2009 versus March 2010; within 50 bps from mid-price

0 2 4 6 8

0 250 500 750+88%

+126%

+62%

+139%

0 50 100 150 200+64%

+51%

0 20 40 60+67%

+72%

0 250 500 750

M ar.-10 Ask N ov.-09 Ask M ar.-10 B id N ov.-09 B id

Source: Tokyo Stock Exchange, Inc.; Depth is the total value of orders within 50bps of the BBO (number of orders × price)

Largest Cap (Core 30)

Mid Cap (Mid 400)Small Cap (Small)

Large Cap (Large 70)

(JPY millions)

(JPY millions)

(JPY millions)

(JPY millions)

Ask

Ask Ask

Ask

Bid

BidBid

Bid

After the introduction of Arrowhead, liquidity has increased for almost all stocks

16

The Role of High Frequency

Trading

17

What is High Frequency Trading ?

Evolution of methods used for decades

Used by many market participants

brokers, banks, hedge firms, principal traders

There is no definition possible because it is not about a type of activity

but about the frequency and speed of it, as a result any definition is

totally subjective

Principal trading firms use only publicly available information for their

strategies 18

High Frequency Trading Strategies

19

Strategies Basis Examples Result

Market Making /

Liquidity Providing

Inventory

management

• Options

• Equities

• Futures

• FX

• More liquidity

• Less volatility

• Better prices for customers

Market Making/

ArbitrageFungibility

• ETF’s versus futures

• Equities versus

futures

• ADR’s versus ordinary

shares

• More liquidity

• Less volatility

• Better prices for customers

• Keeps prices in equilibrium

Statistical

Arbitrage

Historical short

term correlations

• Phillips versus

Siemens

• CAC index versus

DAX index

• Adds liquidity

• Limits short term

demand/supply dislocations

20

An Example of Market Making/ Arbitrage

New York Amsterdam

Buy Phillips ADR’s Sell Phillips shares

• FX• Conversion• Market making

21

A Grossly Oversimplified View of the Markets

Multiple participants using different rationales to buy and sell make a market. If all participants

would use the same rationale to trade there would never be one

Intraday <1 year 1-3 years >3 years

Principal traders

Liquidity providing

Arbitrage

ManualMethod of Execution

Fundamental

Catalysts

Demand/Supply

Imbalances

Algorithms

Participants

Rationale

Institutional investors

Hedge Funds

Technical

StrategiesInvesting

Retail

FIA EPTA Position on MiFID II

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FIA EPTA Position on MiFID II

23

The revised regulatory environment should:

Regulate all direct market participants

Promote risk management

Support resilient and safe markets

And preserve the gains that have been made by automation and competition:

Lower trading costs

Reduced bid-ask spreads

Higher liquidity

Lower barriers to entry/more choice to investors

FIA EPTA Position on MiFID II (cont’d)

24

• Regulating electronic platforms

• Regulation of market access

• Risk controls

• Clearing competition

• Moving OTC traded

derivatives onto centrally

cleared exchanges

MiFID II / MiFIR could be

more ambitious:

Better alternatives

for some proposals:

• Best execution

requirements

• Transparency

• Consolidated tape

• Continuous quoting

obligations

• Order to trade ratios

FIA EPTA Supports :

Detrimental to liquidity

and market efficiency:

• Minimum order resting

times

Algorithmic Trading Art. 17, MiFID2

25

Articles Safer/more resilient markets

Comments

17.1 Risk controls √ • FIA EPTA Principles

17.2 Disclosure ? • Sensible, but some practical issues

17.3 Quoting obligations ?

• Increases systemic risk• Contradictory to 17.1• Harms liquidity

17.4 Risk controls for brokers√

• FIA EPTA principles

17.5 GCM obligations√

• Largely already common practice

Algorithmic Trading Art. 17, MiFID2

26

FIA EPTA members believe that regulators should

1) Ensure that market participants have effective risk controls in place

2) Ensure that markets are stable and resilient for all participants

Article 17(3) is inconsistent with both these principles.

“imposing a quoting obligations on a subset of firms in any piece of

legislation is we believe without precedent. It is akin to mandating all

banks to provide credit continuously to whoever demands it, regardless

of credit history or any other regular credit considerations”

Systems resilience, circuit breakers and electronic trading -Art. 51, MiFID

27

Articles Safer/more resilient markets

Comments

51.1 & 51.2Systems & controls of RM’s

√ • FIA EPTA Principles

51.3 & 51.7Order to trade ratios & tick sizes

?

• One size fits all order to trade ratio is potentially anti-competitive and harmful to liquidity

51.5 Co-location services √ • FIA EPTA principles

28

Why are Order Messages High in a Competitive Market ?

ask

askbid bid

Wide quote

Only need to update

few times a day

Narrow quote

Need for updating

many times a day

29

What Determines an Order to Trade Ratio?

Characteristic Order to Trade Ratio

Trading Volume Low High

Volatility High High

Spread/tick size Wide Low

30

Typical Order to Trade Ratios for an Electronic Exchange

Liquid

Equities

Exchange

New/Startup

MTF

Options

Markets

ETF

Markets

10 to 1 1000 to 1 1000 to 1

12,000 to 1800 to 1

31

Market Abuse and Order Messages / Updates

There is no evidence of a link between market abuse and excessive

order messages*.

There is a very considerable evidence of better markets as a result of automation

Order messages are a by-product of more efficient, screen traded markets.

Screen traded markets compete on price with OTC markets

Though high message rates are not market abuse, there are certainly

inefficient message practices. Exchanges have developed effective

ways to deal with this issue.

*The SEC/CFCT report on the flash crash states: ‘the evidence does not support the hypothesis that delays in the CTS and CQS feeds triggered or otherwise caused the extreme volatility in security prices observed that day’

What is Volatility and what

causes it ?

32

What is Volatility and what causes it ?

Volatility is a measure of variation in price of an instrument.

It reflects the uncertainty about the future price of an asset or the market as a whole.

It is amplified by the breadth of possible outcomes.

Inflation

Sovereign default

Q.E. Austerity

Deflation

Fiscal consolidation

Possible outcomes

33

AEX index (2000-2011) DAX index (2004-2011)

Stability: Intraday versus overnight volatility

CAC index (2000-2011)

34

• Trading value by minutes on 9 Aug, 2011

• This was the first session after the U.S. credit rating downgrade.

• Co-located traders, associated with high-frequency trading strategies, have dampen volatility by buying

the non-co-located clients sell orders.

Source: Tokyo Stock Exchange

Tokyo Stock Exchange – Volatility spike

35

Volatility Comparison – 30 Day Volatility in Equities

Index Eurostoxx 50

36

Volatility Comparison

WTI Crude Itraxx Europe CDS

IR Swap annual (EUR)

As shown here, asset classes

with no HFT involvement have

experienced the same or a

higher increase in volatility as

equities.

37

30 Day Volatility in OTC traded asset classes

Does HFT cause Volatility ?

38

Price

Caused by sellers

Dampened by buyers

Caused by sellers

Dampened by buyers

Caused by buyers

Dampened by sellers

Caused by buyers

Dampened by sellers

Caused by buyers

Dampened by sellers

Causing intraday volatility is a loss making business

Mean reversion is the basic strategy of most liquidity providers/market makers

38

Caused by sellers

Dampened by buyers

What do Academics say?

39

Credit Suisse (2010)

CME Group (2010)

Brogaard (2011)

Castura, Litzenberger, Gorelick,

Dwivedi (2009)

Hasbrouck and Saar (2011)

Chaboud, Chiquoine, Hjalmarsson and Vega (2009)

Frino, Lepone, Mistry (2010)

Hendershott and Riordan (2009)

UK Treasury Foresight Committee (2011)

Groth (2010)

Bank of international Settlements (2011)

Jarnecic, Snape (2010)

Zhang (2010)

Boehmer (2011)

Dampens volatility : No effect on volatility : Causes volatility :

Appendix

40

High Frequency Trading

Literature Review

41

42

Author(s) / Title Dataset Findings

Markets Committee, Bank for International Settlements (BIS) “High-frequency trading in the foreign exchange market”, September 2011

Various FX venues, notably Reuters and EBS, and various dates, notably May 6, 2010 and March 17, 2011

HFT is found to be beneficial during normal market periods, with similar behavior to traditional market participants during high volatility periods

Brogaard"High frequency trading and its impact on market quality", August 2010

HFT vs. other trades. U.S. equities on NASDAQ, various periods in2008 –2010

HFT helped to narrow bid – ask spreads, improved price discovery and may have reduced volatility

Brogaard“High Frequency Trading and Volatility”, October 2011

HFT vs. other trades. U.S. equities on NASDAQ, various periods in2008 –2010

HFT activity tends to decrease idiosyncratic and intraday volatility.

Hendershott, Riordan “High Frequency Trading and Price Discovery” (working paper)

HFT vs. other trades. U.S. equities on NASDAQ, various periods in2008 –2010

HFT trades were positively correlated with permanent price changes and negatively correlated with transitory price changes, Suggesting that HFT improves price discovery

Jarnecic, Snape"An analysis of trades by high frequency participants on the London Stock Exchange", June 2010

HFT vs. other trades. LSE equities, April – June, 2009

HFT improved liquidity and was unlikely to have increased volatility

CME Group "Algorithmic trading and market dynamics", July 2010

Automated vs. other trades. CME futures, May 2008 – May 2010

Automated trading was associated with improved liquidity and reduced volatility

Literature Review

43

Author(s) / Title Dataset Findings

Angel, Harris, Spatt"Equity trading in the 21st century", February 2010

U.S. equities, 1993 - 2009 Trading costs have declined, bid - ask spreads have narrowed and available liquidity has increased

RGM Advisors “Market Efficiency and Microstructure Evolution in US Equity Markets: A High Frequency Perspective”, October 2010

U.S. equities, 2006 - 2010 Bid-ask spreads have narrowed, available liquidity has increased and price efficiency has improved

Credit Suisse“Sizing Up US Equity Microstructure”, April 2010

U.S. equities, 2003 - 2010 Bid -ask spreads have narrowed, available liquidity has increased and short-term volatility (normalized by longer term volatility) has declined

Hasbrouck, Saar"Low-Latency Trading“, May 2011

U.S. equities, full NASDAQ order book June 2007 and October 2008

Low latency automated trading was associated with lower quoted and effective spreads, lower volatility and greater liquidity

Hendershott, Riordan“Algorithmic Trading and Information”, August 2009

Automated vs. other trades. Deutsche Börseequities, January 2008

Automated trades made prices more efficient and did not contribute to higher volatility

Chaboud, Hjalmarsson, Vega and Chiquoine“Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market”, October 2009

Automated vs. other trades. EBS forex market, 2006-2007

Automated trades increased liquidity and may have lowered volatility

Literature Review (cont’d)

44

Author(s) / Title Dataset Findings

Menkveld“High Frequency Trading and the New-Market Makers”, April 2011

Dutch equities traded on Chi-X And Euronext, 2007 A single high frequency trader played an important role in the development of a competitive market center, resulting in better liquidity and lower trading costs

Lepone“The Impact of High Frequency Trading (HFT): International Evidence”, September 2011

HFT vs. other trades. Singapore Exchange(SGX), Australia Securities Exchange(ASX), NASDAQ and London Stock Exchange

HFT has become a major provider of liquidity, particularly during periods of market uncertainty

Hendershott, Jones, Menkveld“Does Algorithmic Trading Improve Liquidity?”, February 2011

Automated quoting facility, NYSE equities, 2003 Automated trading narrowed bid ask spreads, lowered trading costs, and improved price efficiency

Riordan, Storkenmairm“Latency, Liquidity and Price Discovery”, 2009

Xetra high-speed trading system, Deutsche Börse, 2007

Higher system speeds led to increased liquidity and improved price discovery

Hendershott, Moulton “Automation, Speed and Stock Market Quality: The NYSE’s Hybrid”, February 2010

NYSE TAQ database plus others, June 1, 2006 M May 31, 2007

Introduction of automation via the NYSE hybrid system improved price discovery and made prices more efficient

Gomber, Arndt, Lutat, Uhle“High-Frequency Trading”, March 2011

Various Survey paper that highlights beneficial aspects of HFT, while noting that perceived problems are largely a result of U.S. market structure

Literature Review (cont’d)