Python for Finance Cookbook (ebook)

Python for Finance Cookbook (ebook) - Opis

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. Spis treści: 1. Financial Data and Preprocessing2. Technical Analysis in Python3. Time Series Modelling4. Multi-factor Models5. Modeling Volatility with GARCH class models6. Monte Carlo Simulations in Finance7. Asset Allocation in Python 8. Identifying (...) więcej Credit Default with Machine Learning9. Advanced Machine Learning Models in Finance10. Deep Learning in Finance O autorze: Eryk Lewinson received his master's degree in Quantitative Finance from Erasmus University Rotterdam. In his professional career, he has gained experience in the practical application of data science methods while working in risk management and data science departments of two "big 4" companies, a Dutch neo-broker and most recently the Netherlands' largest online retailer.Outside of work, he has written over a hundred articles about topics related to data science, which have been viewed more than 3 million times. In his free time, he enjoys playing video games, reading books, and traveling with his girlfriend. mniej