Quantitative Trading : How to Build Your Own Algorithmic Trading Business / Edition 1

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By some estimates, quantitative (or algorithmic) trading nowaccounts for over one-third of trading volume in the United States.While institutional traders continue to implement this highlyeffective approach, many independent traders—with limitedresources and less computing power—have wondered if they canstill challenge powerful industry professionals at their own game'The answer is "yes," and in Quantitative Trading, author Dr. ErnestChan, a respected independent trader and consultant, will show youhow.

Whether you're an independent "retail" trader looking to startyour own quantitative trading business or an individual who aspiresto work as a quantitative trader at a major financial institution,this practical guide contains the information you need tosucceed.

Organized around the steps you should take to start tradingquantitatively, this book skillfully addresses how to:

  • Find a viable trading strategy that you're both comfortable withand confident in
  • Backtest your strategy—with MATLAB®, Excel, and otherplatforms—to ensure good historical performance
  • Build and implement an automated trading system to execute yourstrategy
  • Scale up or wind down your strategies depending on theirreal-world profitability
  • Manage the money and risks involved in holding positionsgenerated by your strategy
  • Incorporate advanced concepts that most professionals use intoyour everyday trading activities
  • And much more

While Dr. Chan takes the time to outline the essential aspectsof turning quantitative trading strategies into profits, he doesn'tget into overly theoretical or sophisticated theories. Instead, hehighlights the simple tools and techniques you can use to gain amuch-needed edge over today's institutional traders.

And for those who want to keep up with the latest news, ideas,and trends in quantitative trading, you're welcome to visit Dr.Chan's blog, epchan.blogspot.com, as well as his premium contentWeb site, epchan.com/subscriptions, which you'll have free accessto with purchase of this book.

As an independent trader, you're free from the con-straintsfound in today's institutional environment—and as long as youadhere to the discipline of quantitative trading, you can achievesignificant returns. With this reliable resource as your guide,you'll quickly discover what it takes to make it in such a dynamicand demanding field.

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Product Details

  • ISBN-13: 9780470284889
  • Publisher: Wiley
  • Publication date: 11/17/2008
  • Series: Wiley Trading Series, #381
  • Edition number: 1
  • Pages: 208
  • Sales rank: 693,825
  • Product dimensions: 6.10 (w) x 9.10 (h) x 0.90 (d)

Meet the Author

Ernest P. Chan, PhD, is a quantitative trader and consultant who advises clients on how to implement automated statistical trading strategies. He has worked as a quantitative researcher and trader in various investment banks including Morgan Stanley and Credit Suisse, as well as hedge funds such as Mapleridge Capital, Millennium Partners, and MANE Fund Management. Dr. Chan earned a PhD in physics from Cornell University.

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Table of Contents



Chapter 1: The Whats, Whos, and Whys of QuantitativeTrading.

Who Can Become A Quantitative Trader?

The Business Case for Quantitative Trading.


Demand on Time.

The Nonnecessity of Marketing.

The Way Forward.

Chapter 2: Fishing for Ideas.

How to Identify a Strategy That Suits You.

Your Working Hours.

Your Programming Skills.

Your Trading Capital.

Your Goal.

A Taste for Plausible Strategies and Their Pitfalls.

How Does It Compare with a Benchmark and How Consistent Are ItsReturns?

How Deep and Long is the Drawdown?

How Will Transaction Costs Affect the Strategy?

Does the Data Suffer from Survivorship Bias?

How Did the Performance of the Strategy Change Over theYears?

Does the Strategy Suffer from Data-Snooping Bias?

Does the Strategy “Fly under the Radar” ofInstitutional Money Managers?


Chapter 3: Backtesting.

Common Backtesting Platforms.




High-End Backtesting Platforms.

Finding and Using Historical Databases.

Are the Data Split- and Dividend-Adjusted?

Are the Data Survivorship Bias Free?

Does Your Strategy Use High and Low Data?

Performance Measurement.

Common Backtesting Pitfalls to Avoid.

Look-Ahead Bias.

Data-Snooping Bias.

Transaction Costs.

Strategy Refinement.


Chapter 4: Setting up Your Business.

Business Structure: Retail or Proprietary?

Choosing a Brokerage or Proprietary Trading Firm.

Physical Infrastructure.


Chapter 5: Execution Systems.

What an Automated Trading System Can Do for You.

Building a Semiautomated Trading System.

Building a Fully Automated Trading System.

Minimizing Transaction Costs.

Testing Your System by Paper Trading.

Why Does Actual Performance Diverge from Expectations?


Chapter 6: Money and Risk Management.

Optimal Capital Allocation and Leverage.

Risk Management.

Psychological Preparedness.


Appendix: A Simple Derivation of the Kelly Formula when ReturnDistribution is Gaussian.

Chapter 7: Special Topics in Quantitative Trading.

Mean-Reverting versus Momentum Strategies.

Regime Switching.

Stationarity and Cointegration.

Factor Models.

What Is Your Exit Strategy?

Seasonal Trading Strategies.

High-Frequency Trading Strategies.

Is it Better to Have a High-Leverage versus a High-BetaPortfolio?


Chapter 8: Conclusion: Can Independent TradersSucceed?

Next Steps.

Appendix: A Quick Survey of MATLAB.


About the Author.


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