Quantitative Trading: How to Build Your Own Algorithmic Trading Business
by Ernie Chan · 17 Nov 2008
tremendous benefits, but also And for those who want to keep up with the some of the pitfalls, in utilizing many of the recently implemented quantitative trading techniques.” latest news, ideas, and trends in quantitative —PETER BORISH, Chairman and CEO, Computer Trading Corporation trading, you’re welcome to visit Dr.
…
Chan and as long as you adhere to the discipline of highlights the essential cornerstones of a successful automated trading operation and shares lessons he quantitative trading, you can achieve significant learned the hard way while offering clear direction to steer readers away from common traps that both returns. With this
…
LY E A —STEVE HALPERN, founder, HCC Capital, LLC How to Build Your Own Algorithmic Trading Business trader and consultant who advises clients on how Quantitative Trading or sophisticated theories. Instead, he highlights the Wiley Trading B y some estimates, quantitative (or algorithmic) trading now accounts for over one-third of
…
trading volume in the United States. While institutional traders continue to implement this highly effective approach, many independent traders—with Quantitative Trading limited resources and less computing power—have wondered if they can still challenge powerful industry professionals at their own game? The answer is “yes,”
…
and in Quantitative Trading, author Dr. Ernest Chan, a respected independent trader and consultant, will show you how. Whether you’re an independent “retail” trader looking to start
…
your own quantitative trading business or an individual who aspires to work as a quantitative trader at a major financial institution, this practical guide contains the information you need
…
books. For more information about Wiley products, visit our web site at www.wiley.com. Library of Congress Cataloging-in-Publication Data Chan, Ernest P. Quantitative trading: how to build your own algorithmic trading business / Ernest P. Chan. p. cm.–(Wiley trading series) Includes bibliographical references and index. ISBN 978-0
…
103 Psychological Preparedness 108 Summary 111 Appendix: A Simple Derivation of the Kelly Formula when Return Distribution Is Gaussian 112 CHAPTER 7 Special Topics in Quantitative Trading 115 Mean-Reverting versus Momentum Strategies 116 Regime Switching 119 Stationarity and Cointegration 126 Factor Models 133 What Is Your Exit Strategy? 140 Seasonal
…
: Yet to come P1: JYS fm JWBK321-Chan September 24, 2008 13:43 Printer: Yet to come Acknowledgments uch of my knowledge and experiences in quantitative trading come from my colleagues and mentors at the various investment banks (Morgan Stanley, Credit Suisse, Maple Securities) and hedge funds (Mapleridge Capital, Millennium Partners,
…
pattern” might not be included in a quantitative trader’s arsenal because they are quite subjective and may not be quantifiable. Yet quantitative trading includes more than just technical analysis. Many quantitative trading systems incorporate fundamental data in their inputs: numbers such as revenue, cash flow, debt-toequity ratio, and others. After all,
…
the picture: As long as you can convert information into bits and bytes that the computer can understand, it can be regarded as part of quantitative trading. WHO CAN BECOME A QUANTITATIVE TRADER? It is true that most institutional quantitative traders received their advanced degrees as physicists, mathematicians, engineers, or computer
…
quite poor trading complex mortgage-backed securities, as the financial crisis of 2007–08 and the demise of Bear Stearns have shown.) The kind of quantitative trading I focus on is called statistical arbitrage trading. Statistical arbitrage deals with the simplest financial instruments: stocks, futures, and sometimes currencies. One does not
…
-Chan September 24, 2008 13:47 Printer: Yet to come 10 QUANTITATIVE TRADING TABLE 2.1 Sources of Trading Ideas Type Academic Business schools’ finance professors’ web sites Social Science Research Network National Bureau of Economic Research Business schools’ quantitative finance seminars Mark Hulbert’s column in the New York Times’ Sunday business
…
leverage is beneficial only if you have a consistently profitable P1: JYS c02 JWBK321-Chan 14 September 24, 2008 13:47 Printer: Yet to come QUANTITATIVE TRADING strategy.) Trading futures, currencies, and options can offer you higher leverage than stocks; intraday positions allow a Regulation T leverage of 4, while interday
…
completely arbitraged away by the gigantic hedge funds. P1: JYS c02 JWBK321-Chan 28 September 24, 2008 13:47 Printer: Yet to come QUANTITATIVE TRADING SUMMARY Finding prospective quantitative trading strategies is not difficult. There are: r Business school and other economic research web sites. r Financial web sites and blogs focusing on
…
presented to illustrate the principles and techniques described. 31 P1: JYS c03 JWBK321-Chan September 24, 2008 13:52 Printer: Yet to come 32 QUANTITATIVE TRADING COMMON BACKTESTING PLATFORMS There are numerous commercial platforms that are designed for backtesting, some of them costing tens of thousands of dollars. In keeping with
…
www.lim.com) r Alphacet’s Discovery (www.alphacet.com) P1: JYS c03 JWBK321-Chan September 24, 2008 13:52 Printer: Yet to come 36 QUANTITATIVE TRADING Of all these, I have personal experience with only Logical Information Machines and Alphacet Discovery. Logical Information Machines is excellent for testing futures trading strategies
…
analysis (see, e.g., epchan.blogspot.com/2006/11/ P1: JYS c03 JWBK321-Chan September 24, 2008 56 13:52 Printer: Yet to come QUANTITATIVE TRADING reader-suggested-possible-trading.html). Here, however, I will defer until Chapter 7 the cointegration analysis on the training set, which demonstrates that the spread
…
)<=1; % initialize positions array positions=NaN(length(tday), 2); 57 P1: JYS c03 JWBK321-Chan September 24, 2008 13:52 Printer: Yet to come 58 QUANTITATIVE TRADING % long entries positions(shorts, :)=... repmat([-1 1], [length(find(shorts)) 1]); % short entries positions(longs, :)=repmat([1 -1], [length(find(longs)) 1]); % exit positions
…
as their access of the so-called “dark-pool” P1: JYS c04 JWBK321-Chan September 24, 2008 13:53 Printer: Yet to come 72 QUANTITATIVE TRADING TABLE 4.1 Retail versus Proprietary Trading Issue Retail Trading Proprietary Trading Legal requirement to open account. None. Initial capital requirement. Available leverage or buying
…
PFG Futures (for futures trading), and Oanda (for currency trading). P1: JYS c04 JWBK321-Chan 74 September 24, 2008 13:53 Printer: Yet to come QUANTITATIVE TRADING In addition to paper trading accounts, some brokerages provide a “simulator” account (an example is the demo account from Interactive Brokers), where quotes from the
…
-performance programming languages such as Java, C#, or C++ in order to connect to your brokerage’s application programming interface (API). For lower-frequency quantitative trading strategies, there is a semiautomated alternative: One can generate the orders using programs such as Excel or MATLAB, then submit those orders using built-in
…
brokerage Your brokerage account FIGURE 5.1 Semiautomated Trading System P1: JYS c05 JWBK321-Chan September 24, 2008 82 13:55 Printer: Yet to come QUANTITATIVE TRADING updates an Excel input file. Most brokerages that cater to serious traders provide such DDE links. Interactive Brokers, Genesis Securities, and Goldman Sachs’s
…
underperforms your backtest? You can start by addressing the usual P1: JYS c05 JWBK321-Chan 94 September 24, 2008 13:55 Printer: Yet to come QUANTITATIVE TRADING problems: Eliminate bugs in the strategy or execution software; reduce transaction costs; and simplify the strategy by eliminating parameters. But, fundamentally, your strategy still
…
models prematurely in the following section on psychological preparedness). P1: JYS c06 JWBK321-Chan September 24, 2008 13:57 Printer: Yet to come 108 QUANTITATIVE TRADING Software risk refers to the case where the automated trading system that generates trades every day actually does not faithfully reflect your backtest model. This
…
this book covered most of the basic knowledge needed to research, develop, and execute your own quantitative strategy. This chapter explains important themes in quantitative trading in more detail. These themes form the bases of statistical arbitrage trading, and most quantitative traders are conversant in some if not most of these
…
through higher leverage or trading higher-beta stocks? T 115 P1: JYS c07 JWBK321-Chan September 24, 2008 14:4 116 Printer: Yet to come QUANTITATIVE TRADING MEAN-REVERTING VERSUS MOMENTUM STRATEGIES Trading strategies can be profitable only if securities prices are either mean-reverting or trending. Otherwise, they are randomwalking, and
…
generated by these two causes (private liquidity needs and herdlike behavior) have highly P1: JYS c07 JWBK321-Chan September 24, 2008 Special Topics in Quantitative Trading 14:4 Printer: Yet to come 119 unpredictable time horizons. How could you know how big an order an institution needs to execute incrementally? How
…
parameters that specify the regime probability distributions and the transition probabilities by fitting the P1: JYS c07 JWBK321-Chan September 24, 2008 Special Topics in Quantitative Trading 14:4 Printer: Yet to come 121 model to past prices, using standard statistical methods such as maximum likelihood estimation. 4. Based on the
…
tday2=.. datestr(datenum(tday2, ’mm/dd/yyyy’), ’yyyymmdd’); P1: JYS c07 JWBK321-Chan September 24, 2008 14:4 Printer: Yet to come Special Topics in Quantitative Trading % convert the date strings first into cell arrays and % then into numeric format. tday2=str2double(cellstr(tday2)); adjcls2=num2(:, end); % find all the days when
…
to benefit from tax losses, which creates additional downward P1: JYS c07 JWBK321-Chan September 24, 2008 14:4 Printer: Yet to come 144 QUANTITATIVE TRADING pressure on their prices. When this pressure disappeared in January, the prices recovered somewhat. This strategy did not work in 2006–07, but worked wonderfully
…
)=[];% Ensure each lastdayofJan date after each % lastdayofDec date P1: JYS c07 JWBK321-Chan September 24, 2008 14:4 Printer: Yet to come Special Topics in Quantitative Trading 145 assert(all(tday(lastdayofJan) > tday(lastdayofDec))); eoy=find(years∼=nextdayyear); % End Of Year indices eoy(end)=[]; % last index is not End of Year %
…
2007. clear; load(’SPX 20071123’, ’tday’, ’stocks’, ’cl’); P1: JYS c07 JWBK321-Chan September 24, 2008 14:4 Printer: Yet to come Special Topics in Quantitative Trading 147 % find the indices of the days that are at month ends. monthEnds=find(isLastTradingDayOfMonth(tday)); monthlyRet=.. (cl(monthEnds,:)-lag1(cl(monthEnds,:)))./.. lag1(cl(monthEnds
…
-date array is the last trading day of a month. P1: JYS c07 JWBK321-Chan September 24, 2008 148 14:4 Printer: Yet to come QUANTITATIVE TRADING function isLastTradingDayOfMonth=.. isLastTradingDayOfMonth(tday) % isLastTradingDayOfMonth= % isLastTradingDayOfMonth(tday) returns a logical % array. True if tday(t) is last trading day of month. tdayStr=datestr(datenum
…
. You can access that area using “sharperatio” as username and password. P1: JYS c07 JWBK321-Chan September 24, 2008 14:4 Special Topics in Quantitative Trading Printer: Yet to come 151 Commodity futures seasonal trades do suffer from one drawback despite their consistent profitability: they typically occur only once a year
…
should be quite wary of using too much leverage on normally low-beta stocks. SUMMARY This book has been largely about a particular type of quantitative trading called statistical arbitrage in the investment industry. Despite this fancy name, statistical arbitrage is actually far simpler than trading derivatives (e.g., options) or
…
com), a consulting firm focusing on trading strategy and software development for money managers. He also co-manages EXP Quantitative Investments, LLC and publishes the Quantitative Trading blog (epchan.blogspot.com), which is syndicated to multiple financial news services including www.tradingmarkets.com and Yahoo! Finance. He has been quoted by
…
-Chan October 2, 2008 14:7 Printer: Yet to come Index A Abnormal Returns, 10 Aegis System (Barra), 35 Alea Blog, 10 Algorithmic trading. See Quantitative trading Alphacet, 35, 36, 55, 85, 122–126 Alpha Testing (FactSet), 35 Amaranth Advisors, 110, 150, 157 Application programming interface (API), 73, 84 Arbitrage pricing
…
Specific return, 134 Split and dividend-adjusted data, 36–40 Standard & Poor’s small-cap index, 19, 87 Stationarity, 126–133 Statistical arbitrage trading. See Quantitative trading Status quo bias, 108–109 Sterge, Andrew, 91 Stocks, Futures and Options magazine, 10 Stop loss, as risk management practice, 106–107 Strategies, finding,
…
Chan and as long as you adhere to the discipline of highlights the essential cornerstones of a successful automated trading operation and shares lessons he quantitative trading, you can achieve significant learned the hard way while offering clear direction to steer readers away from common traps that both returns. With this
…
LY E A —STEVE HALPERN, founder, HCC Capital, LLC How to Build Your Own Algorithmic Trading Business trader and consultant who advises clients on how Quantitative Trading or sophisticated theories. Instead, he highlights the Wiley Trading B y some estimates, quantitative (or algorithmic) trading now accounts for over one-third of
…
trading volume in the United States. While institutional traders continue to implement this highly effective approach, many independent traders—with Quantitative Trading limited resources and less computing power—have wondered if they can still challenge powerful industry professionals at their own game? The answer is “yes,”
…
and in Quantitative Trading, author Dr. Ernest Chan, a respected independent trader and consultant, will show you how. Whether you’re an independent “retail” trader looking to start
…
your own quantitative trading business or an individual who aspires to work as a quantitative trader at a major financial institution, this practical guide contains the information you need
Traders, Guns & Money: Knowns and Unknowns in the Dazzling World of Derivatives
by Satyajit Das · 15 Nov 2006 · 349pp · 134,041 words
real. Risk management at the front line, and unlike anything you’ll have seen in the textbooks.” Paul Wilmott, writer, mathematician and author of the quantitative finance website www.wilmott.com Warren Buffet once memorably described derivatives as “financial weapons of mass destruction”. Read this sensational and controversial account of the often
…
, but they were the exceptions. Serious research moved into the private domain and was mainly applied to prop trading. Salomon’s research effort drove the quantitative trading of its Arbitrage Group and subsequently that of its alumni in Long Term Capital Management (LTCM). But for the most part, the research distributed by
How I Became a Quant: Insights From 25 of Wall Street's Elite
by Richard R. Lindsey and Barry Schachter · 30 Jun 2007
an effort to get to know the quant research guys. We became friends and he was eventually a big influence on my decision to pursue quantitative trading. Quant Research and the Mathematics of Portfolio Trading I want to start with some general comments about how I view research in financial mathematics. I
Nerds on Wall Street: Math, Machines and Wired Markets
by David J. Leinweber · 31 Dec 2008 · 402pp · 110,972 words
it just did what you told it to do, no matter how stupid that might be. If you had actually found the holy grail of quantitative trading, but had made only one little mistake—you were buying when you should sell, and selling when you should buy—the system would never notice
The Crisis of Crowding: Quant Copycats, Ugly Models, and the New Crash Normal
by Ludwig B. Chincarini · 29 Jul 2012 · 701pp · 199,010 words
trading desk would have to be shut down. In fact, Morgan Stanley has already begun preparing for these new rules and the head of their quantitative trading desk, Peter Muller, and the rest of his team have left Morgan to start their own hedge fund. Some Thoughts The purpose of the Volker
Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined
by Lasse Heje Pedersen · 12 Apr 2015 · 504pp · 139,137 words
labor-intensive method implies that only a limited number of securities can be analyzed in depth, and the discretion exposes the trader to psychological biases. Quantitative trading has the advantage of being able to apply a trading idea to thousands of securities around the globe, benefiting from significant diversification. Furthermore, quants can
…
funds rely on a fundamental analysis of companies in a similar way to other discretionary equity investors. Discretionary trading can be seen in contrast to quantitative trading, which invests systematically based on a model. Both types of traders may seek lots of data and use valuation models, but whereas discretionary traders make
…
labor-intensive method implies that only a limited number of securities can be analyzed in depth, and the discretion exposes the trader to psychological biases. Quantitative trading has the advantage of discipline, an ability to apply a trading idea to a wide universe of securities with the benefits of diversification, and efficient
Adaptive Markets: Financial Evolution at the Speed of Thought
by Andrew W. Lo · 3 Apr 2017 · 733pp · 179,391 words
: “Over time, things evolved. I don’t know how much of that was due to our influence. The general comment I can make is that quantitative trading became more challenging with every passing year.” In fact, Shaw inspired legions of talented computer scientists, mathematicians, and other quants to pursue careers in finance
The Quants
by Scott Patterson · 2 Feb 2010 · 374pp · 114,600 words
. Chaos ruled. Fischer Black watched the disaster with fascination from his perch at Goldman Sachs in New York, where he’d taken a job managing quantitative trading strategies. Robert Jones, a Goldman trader, dashed into Black’s office to report on the carnage. “I put in an order to sell at market
…
at the wiseass Morgan Stanley salesman who’d barged into his office as though he owned it. Muller had only recently begun setting up a quantitative trading group at Morgan, and this was the reception he got? It had been like this since the day he arrived at the bank. After accepting
…
Griffin was starting up Citadel in Chicago, Peter Muller was hard at work at Morgan Stanley in New York trying to put together his own quantitative trading outfit using the models he’d devised at BARRA. In 1991, he pulled the trigger, flipping on the computers. It was a nightmare. Nothing worked
…
out to be a bad move. “Always trust the machine” was the mantra. One day in 1994, Muller came across some old records from a quantitative trading group at Morgan Stanley that had briefly shot the moon in the 1980s. He’d heard stories about the group, trading-floor legends about a
…
University, had planned to follow in his father’s footsteps and pursue a career in academia. But his time at Trout, where he worked building quantitative trading models, changed his mind. One day he was talking to Krail about their work at Trout Trading. “This actually isn’t that bad; this is
Red-Blooded Risk: The Secret History of Wall Street
by Aaron Brown and Eric Kim · 10 Oct 2011 · 483pp · 141,836 words
the subject are Algorithmic Trading and DMA: An Introduction to Direct Access Trading Strategies by Barry Johnson, Inside the Black Box: The Simple Truth about Quantitative Trading by Rishi K. Narang, and Multifractal Volatility: Theory, Forecasting, and Pricing by Laurent E. Calvet. The view of quantitative finance described in Red-Blooded Risk
Alpha Trader
by Brent Donnelly · 11 May 2021
, too fast.” That is not a valid trading strategy. Remember we are using these technicals as guidance and tactical inputs and not as a systematic quantitative trading framework. MORNING QUICK TECHS Most trading jobs are busiest in the morning. Markets are already moving when you sit down but still, you need to
Finding Alphas: A Quantitative Approach to Building Trading Strategies
by Igor Tulchinsky · 30 Sep 2019 · 321pp
Making Sense of Chaos: A Better Economics for a Better World
by J. Doyne Farmer · 24 Apr 2024 · 406pp · 114,438 words
More Money Than God: Hedge Funds and the Making of a New Elite
by Sebastian Mallaby · 9 Jun 2010 · 584pp · 187,436 words
The Blockchain Alternative: Rethinking Macroeconomic Policy and Economic Theory
by Kariappa Bheemaiah · 26 Feb 2017 · 492pp · 118,882 words
High-Frequency Trading
by David Easley, Marcos López de Prado and Maureen O'Hara · 28 Sep 2013
Learn Algorithmic Trading
by Sebastien Donadio · 7 Nov 2019
High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems
by Irene Aldridge · 1 Dec 2009 · 354pp · 26,550 words
Hedge Fund Market Wizards
by Jack D. Schwager · 24 Apr 2012 · 272pp · 19,172 words
The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution
by Gregory Zuckerman · 5 Nov 2019 · 407pp · 104,622 words
The Joys of Compounding: The Passionate Pursuit of Lifelong Learning, Revised and Updated
by Gautam Baid · 1 Jun 2020 · 1,239pp · 163,625 words
Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals
by David Aronson · 1 Nov 2006
Electronic and Algorithmic Trading Technology: The Complete Guide
by Kendall Kim · 31 May 2007 · 224pp · 13,238 words
Chaos Kings: How Wall Street Traders Make Billions in the New Age of Crisis
by Scott Patterson · 5 Jun 2023 · 289pp · 95,046 words
The Ethical Algorithm: The Science of Socially Aware Algorithm Design
by Michael Kearns and Aaron Roth · 3 Oct 2019
A First-Class Catastrophe: The Road to Black Monday, the Worst Day in Wall Street History
by Diana B. Henriques · 18 Sep 2017 · 526pp · 144,019 words
A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation
by Richard Bookstaber · 5 Apr 2007 · 289pp · 113,211 words
The Extended Phenotype: The Long Reach of the Gene
by Richard Dawkins · 1 Jan 1982 · 506pp · 152,049 words
Crapshoot Investing: How Tech-Savvy Traders and Clueless Regulators Turned the Stock Market Into a Casino
by Jim McTague · 1 Mar 2011 · 280pp · 73,420 words
Market Sense and Nonsense
by Jack D. Schwager · 5 Oct 2012 · 297pp · 91,141 words
Only Humans Need Apply: Winners and Losers in the Age of Smart Machines
by Thomas H. Davenport and Julia Kirby · 23 May 2016 · 347pp · 97,721 words
Python for Algorithmic Trading: From Idea to Cloud Deployment
by Yves Hilpisch · 8 Dec 2020 · 1,082pp · 87,792 words
Transaction Man: The Rise of the Deal and the Decline of the American Dream
by Nicholas Lemann · 9 Sep 2019 · 354pp · 118,970 words
Doing Good Better: How Effective Altruism Can Help You Make a Difference
by William MacAskill · 27 Jul 2015 · 293pp · 81,183 words
Value Investing: From Graham to Buffett and Beyond
by Bruce C. N. Greenwald, Judd Kahn, Paul D. Sonkin and Michael van Biema · 26 Jan 2004 · 306pp · 97,211 words
Trend Commandments: Trading for Exceptional Returns
by Michael W. Covel · 14 Jun 2011
Fortunes of Change: The Rise of the Liberal Rich and the Remaking of America
by David Callahan · 9 Aug 2010
How the World Ran Out of Everything
by Peter S. Goodman · 11 Jun 2024 · 528pp · 127,605 words
The Big Short: Inside the Doomsday Machine
by Michael Lewis · 1 Nov 2009 · 265pp · 93,231 words
The Contrarian: Peter Thiel and Silicon Valley's Pursuit of Power
by Max Chafkin · 14 Sep 2021 · 524pp · 130,909 words
Making Globalization Work
by Joseph E. Stiglitz · 16 Sep 2006
You've Been Played: How Corporations, Governments, and Schools Use Games to Control Us All
by Adrian Hon · 14 Sep 2022 · 371pp · 107,141 words
Reinventing Organizations: A Guide to Creating Organizations Inspired by the Next Stage of Human Consciousness
by Frederic Laloux and Ken Wilber · 9 Feb 2014 · 436pp · 141,321 words
Breaking Twitter: Elon Musk and the Most Controversial Corporate Takeover in History
by Ben Mezrich · 6 Nov 2023 · 279pp · 85,453 words
Supremacy: AI, ChatGPT, and the Race That Will Change the World
by Parmy Olson · 284pp · 96,087 words