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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
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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

Summary

In this chapter, we have covered a few of the most popular sources of financial data. However, this is just the tip of the iceberg. Below, you can find a list of other interesting data sources that might suit your needs even better.

Additional data sources are:

  • IEX Cloud (https://iexcloud.io/)—a platform providing a vast trove of different financial data. A notable feature that is unique to the platform is a daily and minutely sentiment score based on the activity on Stocktwits—an online community for investors and traders. However, that API is only available in the paid plan. You can access the IEX Cloud data using pyex, the official Python library.
  • Tiingo (https://www.tiingo.com/) and the tiingo library.
  • CryptoCompare (https://www.cryptocompare.com/)—the platform offers a wide range of crypto-related data via their API. What stands out about this data vendor is that they provide order book data.
  • Twelve Data (https://twelvedata.com/).
  • polygon.io (https://polygon.io/)—a trusted data vendor for real-time and historical data (stocks, forex, and crypto). Trusted by companies such as Google, Robinhood, and Revolut.
  • Shrimpy (https://www.shrimpy.io/) and shrimpy-python—the official Python library for the Shrimpy Developer API.

In the next chapter, we will learn how to preprocess the downloaded data for further analysis.

Join us on Discord!

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https://packt.link/ips2H

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Python for Finance Cookbook – Second Edition - Second Edition
Published in: Dec 2022
Publisher: Packt
ISBN-13: 9781803243191
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