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Python for Finance Cookbook – Second Edition

You're reading from   Python for Finance Cookbook – Second Edition Over 80 powerful recipes for effective financial data analysis

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Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781803243191
Length 740 pages
Edition 2nd Edition
Languages
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Author (1):
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Eryk Lewinson Eryk Lewinson
Author Profile Icon Eryk Lewinson
Eryk Lewinson
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Table of Contents (18) Chapters Close

Preface 1. Acquiring Financial Data FREE CHAPTER 2. Data Preprocessing 3. Visualizing Financial Time Series 4. Exploring Financial Time Series Data 5. Technical Analysis and Building Interactive Dashboards 6. Time Series Analysis and Forecasting 7. Machine Learning-Based Approaches to Time Series Forecasting 8. Multi-Factor Models 9. Modeling Volatility with GARCH Class Models 10. Monte Carlo Simulations in Finance 11. Asset Allocation 12. Backtesting Trading Strategies 13. Applied Machine Learning: Identifying Credit Default 14. Advanced Concepts for Machine Learning Projects 15. Deep Learning in Finance 16. Other Books You May Enjoy
17. Index

Backtesting Trading Strategies

In the previous chapters, we gained the knowledge necessary to create trading strategies. On the one hand, we could use technical analysis to identify trading opportunities. On the other, we could use some of the other techniques we have already covered in the book. We could try to use knowledge about factor models or volatility forecasting. Or, we could use portfolio optimization techniques to determine the optimal quantity of assets for our investment. One crucial thing that is still missing is evaluating how such a strategy would have performed if we had implemented it in the past. That is the goal of backtesting, which we explore in this chapter.

Backtesting can be described as a realistic simulation of our trading strategy, which assesses its performance using historical data. The underlying idea is that the backtest performance should be indicative of future performance when the strategy is actually used on the market. Naturally, this will...

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