Оглавление
Ernest P. Chan. Quantitative Trading
Table of Contents
List of Tables
List of Illustrations
Guide
Pages
Quantitative Trading. How to Build Your Own Algorithmic Trading Business
Preface to the 2nd Edition
REFERENCES
Preface
WHO IS THIS BOOK FOR?
WHAT KIND OF BACKGROUND DO YOU NEED?
WHAT WILL YOU FIND IN THIS BOOK?
REFERENCES
Acknowledgments
CHAPTER 1 The Whats, Whos, and Whys of Quantitative Trading
WHO CAN BECOME A QUANTITATIVE TRADER?
THE BUSINESS CASE FOR QUANTITATIVE TRADING
Scalability
Demand on Time
The Nonnecessity of Marketing
THE WAY FORWARD
CHAPTER 2 Fishing for Ideas: Where Can We Find Good Strategies?
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 Its Returns?
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 the Years?
Does the Strategy Suffer from Data-Snooping Bias?
ARTIFICIAL INTELLIGENCE AND STOCK PICKING1
Does the Strategy “Fly under the Radar” of Institutional Money Managers?
SUMMARY
REFERENCES
CHAPTER 3 Backtesting
COMMON BACKTESTING PLATFORMS
Excel
MATLAB
Example 3.1: Using MATLAB to Retrieve Yahoo! Finance Data
Python
Example 3.1: Using Python to Retrieve Yahoo! Finance Data
R
Example 3.1: Using R to Retrieve Yahoo! Finance Data
QuantConnect
Blueshift
FINDING AND USING HISTORICAL DATABASES
Are the Data Split and Dividend Adjusted?
Example 3.2: Adjusting for Splits and Dividends
Are the Data Survivorship-Bias Free?
Example 3.3: An Example of How Survivorship Bias Can Artificially Inflate a Strategy's Performance
Does Your Strategy Use High and Low Data?
PERFORMANCE MEASUREMENT
Example 3.4: Calculating Sharpe Ratio for Long-Only Versus Market-Neutral Strategies
Using Excel
Using MATLAB
Using Python
Using R
Using Excel
Using MATLAB
Using PYTHON
Using R
Example 3.5: Calculating Maximum Drawdown and Maximum Drawdown Duration
Using Excel
Using MATLAB
Using Python
Using R
COMMON BACKTESTING PITFALLS TO AVOID
Look-Ahead Bias
Data-Snooping Bias
PARAMETERLESS TRADING MODELS1
Example 3.6: Pair Trading of GLD and GDX
Using MATLAB
Using Python
Pair Trading of GLD and GDX
Using R
TRANSACTION COSTS
Example 3.7: A Simple Mean-Reverting Model with and without Transaction Costs
Using MATLAB
Using Python
Using R
STRATEGY REFINEMENT
Example 3.8: A Small Variation on an Existing Strategy
SUMMARY
REFERENCES
NOTE
CHAPTER 4 Setting Up Your Business
BUSINESS STRUCTURE: RETAIL OR PROPRIETARY?
BOX 4.1 SHOULD YOU INCORPORATE BEFORE YOU TRADE?
CHOOSING A BROKERAGE OR PROPRIETARY TRADING FIRM
PHYSICAL INFRASTRUCTURE
SUMMARY
REFERENCES
CHAPTER 5 Execution Systems
WHAT AN AUTOMATED TRADING SYSTEM CAN DO FOR YOU
Building a Semiautomated Trading System
Building a Fully Automated Trading System
HIRING A PROGRAMMING CONSULTANT
MINIMIZING TRANSACTION COSTS
TESTING YOUR SYSTEM BY PAPER TRADING
WHY DOES ACTUAL PERFORMANCE DIVERGE FROM EXPECTATIONS?
SUMMARY
CHAPTER 6 Money and Risk Management
OPTIMAL CAPITAL ALLOCATION AND LEVERAGE
Example 6.1: An Interesting Puzzle (or Why Risk Is Bad for You)1
Example 6.2: Calculating the Optimal Leverage Based on the Kelly Formula
Example 6.3: Calculating the Optimal Allocation Using the Kelly Formula
Using MATLAB
Using Python
Using R
RISK MANAGEMENT
IS THE USE OF STOP LOSS A GOOD RISK MANAGEMENT PRACTICE?
Model Risk
Software Risk
Natural Disaster Risk
PSYCHOLOGICAL PREPAREDNESS
BOX 6.1 LOSS AVERSION IS NOT A BEHAVIORAL BIAS*
SUMMARY
APPENDIX: A SIMPLE DERIVATION OF THE KELLY FORMULA WHEN RETURN DISTRIBUTION IS GAUSSIAN
REFERENCES
NOTES
CHAPTER 7 Special Topics in Quantitative Trading
MEAN-REVERTING VERSUS MOMENTUM STRATEGIES
REGIME CHANGE AND CONDITIONAL PARAMETER OPTIMIZATION
Example 7.1: Conditional Parameter Optimization applied to an ETF trading strategy
Unconditional vs. Conditional Parameter Optimizations
Performance Comparisons
Endnote: Definitions of and
STATIONARITY AND COINTEGRATION
Example 7.2: How to Form a Good Cointegrating (and Mean-Reverting) Pair of Stocks
Using MATLAB
Using Python
Using R
Example 7.3: Testing the Cointegration versus Correlation Properties between KO and PEP
Using MATLAB
Using Python
Using R
FACTOR MODELS
Example 7.4: Principal Component Analysis as an Example of the Factor Model
Using MATLAB
Using Python
Using R
WHAT IS YOUR EXIT STRATEGY?
Example 7.5: Calculation of the Half-Life of a Mean-Reverting Time Series
Using MATLAB
Using Python
Using R
SEASONAL TRADING STRATEGIES
Example 7.6: Backtesting the January Effect
Using MATLAB
Using Python
Using R
Example 7.7: Backtesting a Year-on-Year Seasonal Trending Strategy
Using MATLAB
Using Python
Using R
A SEASONAL TRADE IN GASOLINE FUTURES
A SEASONAL TRADE IN NATURAL GAS FUTURES
HIGH-FREQUENCY TRADING STRATEGIES
IS IT BETTER TO HAVE A HIGH-LEVERAGE VERSUS A HIGH-BETA PORTFOLIO?
SUMMARY
REFERENCES
CHAPTER 8 Conclusion: Can Independent Traders Succeed?
NEXT STEPS
REFERENCES
APPENDIX A Quick Survey of MATLAB
Bibliography
About the Author
INDEX
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If the Sharpe ratio is such a nice performance measure across different strategies, you may wonder why it is not quoted more often instead of returns. In fact, when a colleague and I went to SAC Capital Advisors (assets under management then: $14 billion) to pitch a strategy, their then-head of risk management said to us: “Well, a high Sharpe ratio is certainly nice, but if you can get a higher return instead, we can all go buy bigger houses with our bonuses!” This reasoning is quite wrong: A higher Sharpe ratio will actually allow you to make more profits in the end, since it allows you to trade at a higher leverage. It is the leveraged return that matters in the end, not the nominal return of a trading strategy. For more on this, see Chapter 6 on money and risk management.
(And no, our pitching to SAC was not successful, but for reasons quite unrelated to the returns of the strategy. In any case, at that time neither my colleague nor I were familiar enough with the mathematical connection between the Sharpe ratio and leveraged returns to make a proper counterargument to that head of risk management. SAC pleaded guilty to insider trading charges and ceased to be a hedge fund in 2013.)
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