倒向微分方程在金融中的应用（BSDE in finance） by 山东大学彭实戈院士，1997

Mastering Python for Finance: Implement advanced state-of-the-art financial statistical applications using Python, 2nd Edition Author: James Ma Weiming Pub Date: 2019 ISBN: 978-1789346466 Pages: 426 Language: English Format: EPUB Take your financial skills to the next level by mastering cutting-edge mathematical and statistical financial applications The second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples. You will start by setting up your Jupyter notebook to implement the tasks throughout the book. You will learn to make efficient and powerful data-driven financial decisions using popular libraries such as TensorFlow, Keras, Numpy, SciPy, and sklearn. You will also learn how to build financial applications by mastering concepts such as stocks, options, interest rates and their derivatives, and risk analytics using computational methods. With these foundations, you will learn to apply statistical analysis to time series data, and understand how time series data is useful for implementing an event-driven backtesting system and for working with high-frequency data in building an algorithmic trading platform. Finally, you will explore machine learning and deep learning techniques that are applied in finance. By the end of this book, you will be able to apply Python to different paradigms in the financial industry and perform efficient data analysis. What you will learn Solve linear and nonlinear models representing various financial problems Perform principal component analysis on the DOW index and its components Analyze, predict, and forecast stationary and non-stationary time series processes Create an event-driven backtesting tool and measu

c++ for quantitative finance quantstart

《随机微积分应用于金融学概论》 此文档仅用于学习交流使用，请勿用做商业用途，违者后果自负

My primary intent in writing this book is to provide the reader with basic programming, financial, and mathematical tools that can be successfully leveraged both in industry and academia. I cover the use of the R programming language, as well as the R environment as a means for manipulating financial market data and for solving a subset of problems that quants and traders typically encounter in their day-to-day activities. The chapters that follow should be treated as a tutorial on a recommended set of tools that I have personally found useful and that have served me well during the last few years of my career as a quant trader/developer. I am writing this book from the vantage point of a quant practitioner and not that of an academic. A significant portion of the content is based on my lecture notes from a graduate level class in quantitative finance that I teach on a part-time basis at Loyola University in Chicago.

Arbitrage Theory in Continuous Time

Computational methods in Finance, Hirsa。计算金融必备的入门书籍