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Python For Finance Cookbook, 2nd Edition
Publication date: December 30th, 2022
Paperback: 740 pages
Publisher: Packt Publishing
Language: English
- Acquiring Financial Data
- Data Preprocessing
- Visualizing Financial Time Series
- Exploring Financial Time Series Data
- Technical Analysis and Building Interactive Dashboards
- Time Series Analysis and Forecasting
- ML-based Approaches to Time Series Forecasting
- Multi-Factor Models
- Modeling Volatility with GARCH Class Models
- Monte Carlo Simulations in Finance
- Asset Allocation
- Backtesting Trading Strategies
- Applied Machine Learning: Identifying Credit Default
- Advanced Concepts for ML Projects
- Deep Learning in Finance
- Sometimes when working with the
yfinance
library you can see that the downloaded data differs by a single day. Hence, you might spot that when you execute the same code, the function will download a single day less than what is presented in the book, which will also impact the results of various recipes. Apparently, this is cause by the library not working well with timezones. You can read more about it in this issue. As this issue might be fixed soon and is only visible in some cases, we decided to describe it here and remove the note when the issue is fixed in theyfinance
library.
Eryk Lewinson. Python For Finance Cookbook, 2nd Edition. Packt Publishing, 2022.
@book{Lewinson2022,
address = {Birmingham, UK},
author = {Lewinson, Eryk},
edition = {2},
isbn = {9781803243191},
publisher = {Packt Publishing},
title = {{Python For Finance Cookbook, 2nd Edition}},
year = {2022}
}
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