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Quantitative trading : how to build yourown algorithmic trading business / Ernest P. Chan.

O'Reilly Online Learning: Academic/Public Library Edition Available online

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Format:
Book
Author/Creator:
Chan, Ernest P., author.
Series:
Wiley Trading
Language:
English
Subjects (All):
Investment analysis.
Stockbrokers.
Stocks.
Physical Description:
1 online resource (256 pages)
Edition:
Second edition.
Place of Publication:
Hoboken, New Jersey : John Wiley & Sons, Inc., [2021]
Summary:
Master the lucrative discipline of quantitative trading with this insightful handbook from a master in the field In the newly revised Second Edition of Quantitative Trading: How to Build Your Own Algorithmic Trading Business, quant trading expert Dr. Ernest P. Chan shows you how to apply both time-tested and novel quantitative trading strategies to develop or improve your own trading firm. You'll discover new case studies and updated information on the application of cutting-edge machine learning investment techniques, as well as: * Updated back tests on a variety of trading strategies, with included Python and R code examples * A new technique on optimizing parameters with changing market regimes using machine learning. * A guide to selecting the best traders and advisors to manage your money Perfect for independent retail traders seeking to start their own quantitative trading business, or investors looking to invest in such traders, this new edition of Quantitative Trading will also earn a place in the libraries of individual investors interested in exploring a career at a major financial institution.
Contents:
Cover
Title Page
Copyright Page
Contents
Preface to the 2nd Edition
Preface
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
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?
Does the Strategy "Fly under the Radar" of Institutional Money Managers?
Summary
References
Chapter 3 Backtesting
Common Backtesting Platforms
Excel
MATLAB
Python
R
QuantConnect
Blueshift
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 ExecutionSystems
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
Model Risk
Software Risk
Natural Disaster Risk
Psychological Preparedness
Appendix: A Simple Derivation of the Kelly Formula when Return Distribution Is Gaussian
Chapter 7 Special Topics in Quantitative Trading
Mean-Reverting versus Momentum Strategies
Regime Change and Conditional Parameter Optimization
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-Beta Portfolio?
Chapter 8 Conclusion: Can Independent Traders Succeed?
Next Steps
A Quick Surveyof MATLAB
Bibliography
About the Author
Index
EULA.
Notes:
Description based on print version record.
ISBN:
9781119800088
1119800080
9781119800071
1119800072
9781119800064
1119800064
OCLC:
1259592331

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