Book Image

Python for Finance Cookbook

By : Eryk Lewinson
Book Image

Python for Finance Cookbook

By: Eryk Lewinson

Overview of this book

Python is one of the most popular programming languages used in the financial industry, with a huge set of accompanying libraries. In this book, you'll cover different ways of downloading financial data and preparing it for modeling. You'll calculate popular indicators used in technical analysis, such as Bollinger Bands, MACD, RSI, and backtest automatic trading strategies. Next, you'll cover time series analysis and models, such as exponential smoothing, ARIMA, and GARCH (including multivariate specifications), before exploring the popular CAPM and the Fama-French three-factor model. You'll then discover how to optimize asset allocation and use Monte Carlo simulations for tasks such as calculating the price of American options and estimating the Value at Risk (VaR). In later chapters, you'll work through an entire data science project in the financial domain. You'll also learn how to solve the credit card fraud and default problems using advanced classifiers such as random forest, XGBoost, LightGBM, and stacked models. You'll then be able to tune the hyperparameters of the models and handle class imbalance. Finally, you'll focus on learning how to use deep learning (PyTorch) for approaching financial tasks. By the end of this book, you’ll have learned how to effectively analyze financial data using a recipe-based approach.
Table of Contents (12 chapters)

Multi-Factor Models

This chapter is devoted to estimating various factor models in Python. The idea behind these models is to explain the excess returns (over the risk-free rate) of a certain portfolio or asset using one or more factors (features). These risk factors can be considered a tool for understanding the cross-section of (expected) returns.

In general, factor models can be used to identify interesting assets that can be added to the investment portfolio, which— in turn—should lead to better performing portfolios.

By the end of this chapter, we will have constructed some of the most popular factor models. We will start with the simplest, yet very popular, one-factor model (the Capital Asset Pricing Model, or CAPM) and then explain how to estimate more advanced three-, four-, and five-factor models. We will also cover the interpretation of what these factors...