Mastering Python for Finance: Understand, design, and implement state-of-the-art mathematical and statistical applications used in finance with Python
About this ebook
- Perform interactive computing with IPython Notebook
- Solve linear equations of financial models and perform ordinary least squares regression
- Explore nonlinear modeling and solutions for optimum points using rootfinding algorithms and solvers
- Discover different types of numerical procedures used in pricing options
- Model fixedincome instruments with bonds and interest rates
- Manage big data with NoSQL and perform analytics with Hadoop
- Build a highfrequency algorithmic trading platform with Python
- Create an eventdriven backtesting tool and measure your strategies
If you are an undergraduate or graduate student, a beginner to algorithmic development and research, or a software developer in the financial industry who is interested in using Python for quantitative methods in finance, this is the book for you. It would be helpful to have a bit of familiarity with basic Python usage, but no prior experience is required.
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About the author
James Ma Weiming is a software engineer based in Singapore. His studies and research are focused on financial technology, machine learning, data sciences, and computational finance. James started his career in financial services working with treasury fixed income and foreign exchange products, and fund distribution. His interests in derivatives led him to Chicago, where he worked with veteran traders of the Chicago Board of Trade to devise high-frequency, low-latency strategies to game the market. He holds an MS degree in finance from Illinois Tech's Stuart School of Business in the United States and a bachelor's degree in computer engineering from Nanyang Technological University.
