ABSTRACT

Quantitative Finance with Python: A Practical Guide to Investment Management, Trading and Financial Engineering bridges the gap between the theory of mathematical finance and the practical applications of these concepts for derivative pricing and portfolio management. The book provides students with a very hands-on, rigorous introduction to foundational topics in quant finance, such as options pricing, portfolio optimization and machine learning. Simultaneously, the reader benefits from a strong emphasis on the practical applications of these concepts for institutional investors.

Features

  • Useful as both a teaching resource and as a practical tool for professional investors.
  • Ideal textbook for first year graduate students in quantitative finance programs, such as those in master’s programs in Mathematical Finance, Quant Finance or Financial Engineering.
  • Includes a perspective on the future of quant finance techniques, and in particular covers some introductory concepts of Machine Learning.
  • Free-to-access repository with Python codes available at www.routledge.com/ 9781032014432 and on https://github.com/lingyixu/Quant-Finance-With-Python-Code.

part I|152 pages

Foundations of Quant Modeling

chapter 2Chapter 1|20 pages

Setting the Stage: Quant Landscape

chapter Chapter 4|12 pages

Python Programming Environment

chapter Chapter 5|30 pages

Programming Concepts in Python

chapter Chapter 6|18 pages

Working with Financial Datasets

chapter Chapter 7|8 pages

Model Validation

part II|162 pages

Options Modeling

chapter 154Chapter 8|28 pages

Stochastic Models

chapter Chapter 9|40 pages

Options Pricing Techniques for European Options

chapter Chapter 10|42 pages

Options Pricing Techniques for Exotic Options

chapter Chapter 11|32 pages

Greeks and Options Trading

chapter Chapter 12|18 pages

Extraction of Risk Neutral Densities

part III|142 pages

Quant Modeling in Different Markets

chapter 316Chapter 13|46 pages

Interest Rate Markets

chapter Chapter 14|38 pages

Credit Markets

chapter Chapter 15|32 pages

Foreign Exchange Markets

chapter Chapter 16|24 pages

Equity & Commodity Markets

part IV|170 pages

Portfolio Construction & Risk Management

chapter 458Chapter 17|40 pages

Portfolio Construction & Optimization Techniques

chapter Chapter 18|24 pages

Modeling Expected Returns and Covariance Matrices

chapter Chapter 19|22 pages

Risk Management

chapter Chapter 20|48 pages

Quantitative Trading Models

chapter Chapter 21|34 pages

Incorporating Machine Learning Techniques