Mastering pandas for Finance will teach you how to use Python and pandas to model and solve real-world financial problems using pandas, Python, and several open source tools that assist in various financial tasks, such as option pricing and algorithmic trading. This book brings together various diverse concepts related to finance in an attempt to provide a unified reference to discover and learn several important concepts in finance and explains how to implement them using a core of Python and pandas that provides a unified experience across the different models and tools. You will start by learning about the facilities provided by pandas to model financial information, specifically time-series data, and to use its built-in capabilities to manipulate time-series data, group and derive aggregate results, and calculate common financial measurements, such as percentage changes, correlation of timeseries, various moving window operations, and key data visualizations for finance. After establishing a strong foundation from which to use pandas to model financial time-series data, the book turns its attention to using pandas as a tool to model the data that is required as a base for performing other financial calculations. The book will cover diverse areas in which pandas can assist, including the correlations of Google trends with stock movements, creating algorithmic trading systems, and calculating options payoffs, prices, and behaviors. The book also shows how to model portfolios and their risk and to optimize them for specific risk/return tolerances.