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)

Visualizing time series data

After learning how to download and preprocess financial data, it is time to learn how to plot it in a visually appealing way. We cover two approaches using the following:

  • The default plot method of a pandas DataFrame
  • A combination of the plotly and cufflinks libraries

The plotly library is built on top of d3.js (a JavaScript library used for creating interactive visualizations in web browsers) and is known for creating high-quality plots with a significant degree of interactivity (inspecting values of observations, viewing tooltips of a given point, zooming in, and so on). Plotly is also the company responsible for developing this library and provides hosting for our visualizations. We can create an infinite number of offline visualizations and up to 25 free ones to share online (with a limited number of views per day).

The cufflinks library also...