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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
Tools
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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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Toc

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

Summary

In this chapter, we have learned about technical analysis. We started by calculating some of the most popular technical indicators (and downloading precalculated ones): the SMA, the RSI, and the MACD. We have also explored identifying patterns in candlesticks. Lastly, we learned how to create and deploy an interactive app for technical analysis.

In further chapters, we will put this knowledge into practice by creating and backtesting trading strategies based on the technical indicators we have already covered.

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