This fact states that most measures of asset volatility are negatively correlated with their returns. To investigate it, we used the moving standard deviation (calculated using the rolling method of a pandas DataFrame) as a measure of historical volatility. We used windows of 21 and 252 days, which correspond to one month and one year of trading data.
- Title Page
- Copyright and Credits
- Dedication
- About Packt
- Contributors
- Preface
- Financial Data and Preprocessing
- Technical Analysis in Python
- Time Series Modeling
- Multi-Factor Models
- Modeling Volatility with GARCH Class Models
- Monte Carlo Simulations in Finance
- Asset Allocation in Python
- Identifying Credit Default with Machine Learning
- Loading data and managing data types
- Exploratory data analysis
- Splitting data into training and test sets
- Dealing with missing values
- Encoding categorical variables
- Fitting a decision tree classifier
- Implementing scikit-learn's pipelines
- Tuning hyperparameters using grid searches and cross-validation
- Advanced Machine Learning Models in Finance
- Deep Learning in Finance
- Other Books You May Enjoy
Fact 5
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