Algorithmic Trading

Valdi Algorithms e-Book

Algorithmic Trading for Busy People

Volume 1: Fundamentals & Execution algorithms

by Benjamin Becar

©2011 SunGard. First published, April 2011. Second edition, June 2011.

Trademark information: SunGard and the SunGard logo are trademarks or registered trademarks of SunGard Data Systems Inc. or its subsidiaries in the

U.S. and other countries. All other trade names are trademarks or registered trademarks of their respective holders.

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Table of contents

What does algorithmic trading really mean?

Global usage of algorithms in 2011

Why do people use algorithms?

What are the most popular algos?

Providers and naming conventions

Glossary and Resources

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3

What does it really mean ?

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Too many words…

Over the last five years or so, we have

been inundated with documents and

articles about algorithmic trading: often

these have created confusion for many

people working in the market: traders,

technologists and regulators….

It‟s not uncommon to hear “I want to do

algorithmic trading” when the real objective

is market making, High Frequency Trading,

index arbitrage, or a dozen other things.

Automated

Blackbox HFT Flashcrash

Algorithmic Arbitrage

Low latency VWAP quantitative

Percentage Volume Micro-Second

Stat Arbitrage CEP regulation

PTA

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Automated Trading Strategies

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Algorithmic Trading

High Frequency Trading

Market Making

Program Trading

Index Arbitrage

Smart Order Routing

Decision-making Algorithms

The main reason for confusion is that for some people, Algorithmic Trading is a

specific trading strategy, while for others, it‟s just a broad category involving any

application of software to support trading. The term AUTOMATED TRADING is more

correctly used for this broad category, to include all strategies that rely on computers,

algorithms or automation of some kind.

The most common types of automated

trading strategies are briefly described

in the following slides:

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Automated Trading Strategies

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Algorithmic Trading

Automated execution of a block trade, in search of optimization. Also referred as

“execution algorithms”, this trading strategy is usually applied to single instruments.

Example:

VWAP, Percentage Volume, Iceberg

High Frequency Trading (HFT)

Framework aimed at profit by trading quickly, based on low-latency technology. A

HFT strategy involves optimizing all aspects of the trade flow to be as fast as

possible, including hardware, network, and distance from the trading engine to the

exchange servers.

Example:

A HFT strategy could be to quote thousands of times per second the same

instrument, hoping to be hit at a competitive price, and subsequently resell it

higher. In a typical HFT strategy, less than 5% of the quotes sent to market result

in actual trades.

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HFT controversy

6

There is controversy around HFT: some market participants, politicians and

regulators view it as unfair.

The charts below indicate how a small number of High Frequency Trading firms

dominate US equities trading.

High Frequency

56%High Frequency

1%

Traditional

99% Traditional

44%

Percentage of US trading firms

with a HF strategy

Percentage of US equity volume

driven by HF strategies

Source: TABB Group, Aug 2009

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Automated Trading Strategies

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Market Making

A market maker is a company, or an individual, that quotes both bid and offer prices

in a range of financial instruments or commodities held in inventory, with the

objective of making a profit on the bid/offer spread.

Smart Order Routing (SOR)

Looking for best/improved execution by making use of the price discrepancies that

can occur between venues. As the number and specificities of venues expands in

certain markets (60 venues in US equity markets, including dark pools,

exchanges, systematic internalizers…), smart routing strategies need to be more

and more sophisticated. The associated algorithms are sometimes referred to as

Liquidity Seeking Algorithms

What is a

quant?

A quant, or “quantitative analyst”, is a

mathematical and financial expert who

analyses the market and defines

trading algorithms to benefit from it.

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Automated Trading Strategies

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Program Trading

A program trader trades multiple instruments at the same time, in a „basket‟.

Some program traders focus on a single instrument type (e.g. equities-only

baskets), while others trade derivatives of these instruments at the same time

(options or futures). Cf. Index Arbitrage, described below.

Index Arbitrage

Index arbitrage is a specific type of Program Trading, aimed at profiting from

temporary discrepancies between the value of an index and the net asset value

of the underlying components. Opportunities for index arbitrage tend to

decrease over time in a given market, as the market becomes more

competitive and the technology more sophisticated. On newer markets (like

CFFEX at the present time, for example) there can be significant scope for

index arbitrage.

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Automated Trading Strategies

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Decision-making Algorithms

While all of the strategies described before take some sort of decision, “decision-

making algorithms” describes a category of algorithms that encode a complete

trading strategy, and then operate entirely automatically. In an ideal world, you

could turn on the strategy in the morning, turn it off in the afternoon, and just cash

in your profit. In reality, because most markets are complex and changeable, you

have to monitor the algorithm‟s progress, and modify it regularly. Decision-making

algorithms rely on charts, statistics, historical and real-time data as the basis for

each trading decision.

Because of the fierce competition in the automated world,

those strategies evolve very quickly. More and more, you can

see bridges between them, creating “super algorithms”:

market makers add execution algorithms, index arbitrageurs

use Smart Order Routers for improved efficiency, and so on.

And these moves can influence how the markets behave for

other participants, so vigilance is necessary!

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Automated Trading Strategies

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Algorithmic Trading now accounts for a large share of

the daily volume, as you can see in the below table.

Following the 2010 flash crash (see glossary), a slight

decline in algorithmic trading usage has been noticed

in the US and in Europe. However if we compare to

2005 figures, we can see that this is just a minor

trend in the overall growth pattern.

If we look back to 2001, at Chicago Mercantile

Exchange 90% of trades were handled… manually!

In just five years, meanwhile, Europe has multiplied

its algorithmic trading usage by more than 30 times.

2005 2009 2010 2011

US 21% 61% 56% 54%

Europe 1% 29% 38% 35%

Source: TABB Group, Apr 2011

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Usage in Asia

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Algorithmic

Trading

%

70%

60%

50%

40%

30%

20%

10%

0%

Singapore Hong Kong Japan Australia India

Source: Celent, October 2010

* Note: 2011 & 2012 figures are estimations based on market analysis.

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Usage in Asia

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In Asia, Hong Kong is clearly leading the

pack. Estimated usage is expected to reach

US levels within two years.

Apart from Singapore, which will be following

closely, and Japan, for which the chart

seems to understate the reality, the other

Asian markets are still well behind in terms of

usage, leading to big opportunities for new

entrants in this area.

However, there are some hurdles, mostly

regulatory, which continue to put a brake on

the rate of adoption.

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Hurdles

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All around the world, the economic crisis, followed by the flash

crash in May 2010, created a skeptical approach towards

algorithms at various levels.

After some concerns raised by legislators and general public

opinion, regulators worldwide have begun to move. In

European and US markets, this is the #1 source of concern for

2011.

In Asia, some of the hurdles include:

Requirements for pre-approval of algorithms (India,

Indonesia),

Ensuring “fair trading”, i.e. providing the same price for orders

received within the same time frame. (China)

Exchanges resisting the rise of alternative trading venues:

potential competitors transform into new entities such as the

Chi-East joint venture between SGX and Chi-X. In other

countries, alternative venues may have to wait a long time to

have their approval (eg, Australia), or enjoy the facilities of the

main exchange, like a central clearing (eg, Japan).

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Why use algorithms?

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Most businesses can profit from algorithmic

trading, with a variety of objectives:

Sell-side Improve performance of executions,

provide additional services to clients

Buy-side Route orders to the most effective

sell-side, spread the risk, obtain better prices

Market makers Improve strategies

Hedge funds React immediately to trend

changes, defining proprietary strategies quickly

Most businesses Access multiple markets

with the same or similar strategies

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Impact at the trading desk

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Respondents to a recent survey*

were asked to consider which

factors affecting their trading

desks were important.

Ease of use and trader

productivity were seen as being

almost equally important

considerations.

This reflects the role of algorithms

in changing workflows in the

trading environment.

*SunGard conducted a survey in 2011 with 150 buy-side firms. There were 500 individual responses: 45%

of respondents are heads of trading desks.

Source: SunGard Business Intelligence, Mar 2011

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Impact on Execution

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Survey respondents clearly consider that reduced market impact is a key

benefit. This received 37% of all mentions, well ahead of Execution consistency

(27%). Reducing latency was the area of least perceived importance , gaining

only 17% of mentions. What Is clear from responses is that different firms are

looking to achieve quite different things via algorithmic trading. Providers need

to be sensitive to these differences, as they impact the views that different

customers have of services.

Source: SunGard Business Intelligence, Mar 2011

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Other factors

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Among other considerations in the use of algorithms, anonymity and access to

internal crossing received the highest proportion of mentions. These scores are

consistent with the importance of reduced market impact noted earlier.

Customization received somewhat fewer mentions. Given the amount of

resources devoted to creating „custom‟ solutions for clients, this may be

regarded as disappointing.

Source: SunGard Business Intelligence, Mar 2011

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Client satisfaction

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George and his demanding client

George is the head of trading for a famous broker. He‟s calling one of his software

vendors: it seems something is wrong.

George Hello Jack, I need to do algo trading!

Jack Well sure, what do you want to do with it? Improve your executions?

George No!

Jack I see - it’s to be more productive then?

George No, it’s not.

Jack Then what?

George I have this client, a very large insurance firm and they told me: “George, if you

don’t have these simple algorithms within three months, I’m going with another

broker!”

Jack Let’s see what we can do!

With the buy-side becoming more and more educated in electronic

trading techniques, this situation is now very common.

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What are the most popular algorithms?

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Dozens of algorithms are created and advertised by brokers

and software vendors. Their names can range from descriptive

to technical, not forgetting strange names involving wildlife…

There are two major categories of popular algorithms:

Benchmark Seeking

Liquidity Seeking

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The 2 majors

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Liquidity Seeking AlgorithmsDark only

Aggressive inside a price (all venues)

Benchmark Seeking AlgorithmsVWAP

TWAP

Percentage of Volume

Implementation shortfall

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Execution Trading Algorithms

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Execution Algorithms provide various benefits to dealers when they have to

work their orders. Benchmark seeking algorithms, as described previously,

are a kind of execution algorithm.

Hide your interest from the market

Send your order at the right time

Cover your position

Be sure to be executed

Follow a trend

Meet key benchmarks

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Providers and Naming Conventions

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Provider Liquidity Seeking Percentage

Volume

Hidden Dark only

UBS Tap, Tap Now Volume Inline Hidden

Credit Suisse Pathfinder,

Crossfinder

Workit, Workit

IW, Inline

Guerrilla, Sniper,

Reserve

Deutsche Bank Stealth

Barclays Work & Pounce

Hydra

With Volume Ghost

BNP Killer, Grab pvol, volscaler Dark Peg,

Dark IOC

Citi Dagger Participate

Nomura Float & Pounce, Hide

& Pounce

With Volume Dark Cross

Others Hunt, Snake, Eclipse VOLINL Dark

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Providers and Naming Conventions

Similar algorithms tend to be given the same names by different

providers, but variations are not uncommon. For example:

BWAP (Bloomberg)

DWAP (Bloomberg),

ALPHA (Barclays)

IS

Arrival Price

Aqua/Arrid (JPMorgan)

Tex (Credit Suisse)

MOC

At Close

Tclose

Target Close

VWAP

Implementation

Shortfall

Market On Close

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Glossary

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Algorithmic Trading: Automated execution of a block

trade, in search of optimization. Also referred as “execution

algorithms”, this trading strategy is usually applied to single

instruments.

Arbitrage: Any trading strategy whose purpose is to profit

from market discrepancy.

> Index Arbitrage is when you trade the index against

its underlying components.

> Statistical Arbitrage‟s goal is to identify correlated

instruments, and buy/sell them at appropriate time for a

profit.

ATS – Alternative Trading System: A trading platform

which is not considered as a stock exchange.

Automated Trading: Any automated order manipulation

(order creation, modification, cancellation). Algorithmic

Trading, High Frequency Trading, Pairs Trading, Basket

trading are all various kinds of Automated Trading.

CEP - Complex Event Processing:

Dark Pool: Crossing venues where some or all information

is hidden (bid/ask prices, volume, participants). Used by

traders with large order to avoid showing their interest.

Decision Making Algorithms: Complex strategies, usually

used by hedge funds and prop desk, to trade based on

various information, including real-time and historical data.

Index Arbitrage, Pairs Trading, MACD-based strategies are

all decision making algorithms.

ECN – Electronic Clearing Network: See ATS.

Execution Algorithms: Check “Algorithmic Trading”

Flashcrash: Event that happened on 6th May 2010, in

NYSE. In just a couple of minutes, the price of some stocks

went crazy (from 0.01$ to 100,000$) before returning to

normal.

HFT - High Frequency Trading: Framework aimed at

profit by trading quickly, based on low-latency technology.

Latency: Usually defined as the time taken from the

trading system to the exchange. Latency can be impacted

by various factors including software performance,

hardware, network, location, etc.

MTF – Multi-lateral Trading Facility: See ATS.

PTA – Post Trade Analysis: Analyze the performance of

your order.

PTS – Proprietary Trading System: See ATS.

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Resources

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There are many online information resources

relevant to algorithmic trading. Some useful

starting points are given below.

Automated Trader

www.automatedtrader.com

Advanced Trading

www.advancedtrading.com

To find out how SunGard can help you

implement algorithmic trading solutions with

Valdi Algorithms, please contact

[email protected]

Or visit

www.sungard.com/globaltrading

Valdi Algorithms

About the author

Benjamin Becar heads

product management for

algorithmic trading

solutions at SunGard.

With a strong background

in mathematics, and

knowledge of international

markets, he drives

product strategy.

About SunGard

SunGard is one of the world‟s leading

software and technology services

companies. Our four businesses serve

25,000 customers in over 70 countries.

SunGard‟s global trading business

provides multi-asset, front- to back-

office trading solutions for equities,

fixed income, derivatives and

commodities on exchanges worldwide.

These solutions support full-lifecycle

trading and trade processing activities

including information services, market

connectivity and order management

that help improve trade efficiency and

risk monitoring.

Learn more at sungard.com/globaltrading

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