Financial Mathematics with Python: Methods for Interest Rates, Bonds, Derivatives, Risk, and Portfolios
Financial Mathematics with Python is a practical guide to the quantitative methods used in modern finance, investment analysis, and risk modeling. Written for readers who want to connect financial theory with computational implementation, this book introduces core mathematical concepts through clear explanations and Python-based examples.
The book covers interest rate calculations, bond pricing, yield measures, duration, convexity, derivative valuation, risk modeling, and portfolio analysis. Each topic is presented with an emphasis on understanding the logic behind the calculations, translating formulas into code, and applying financial mathematics in structured analytical workflows.
Rather than treating Python as an afterthought, this book uses programming as a natural extension of financial reasoning. Readers will learn how to build reusable calculations, model cash flows, evaluate securities, simulate financial outcomes, and analyze risk across different financial instruments.
Inside, readers will explore:
Interest rate mathematics and time value of money
Bond pricing, yield curves, duration, and convexity
Derivative pricing concepts and computational valuation methods
Risk measures, volatility, scenario analysis, and model assumptions
Portfolio calculations, returns, covariance, diversification, and allocation logic
Python workflows for financial modeling and quantitative analysis
Financial Mathematics with Python is designed for students, analysts, finance professionals, and technically minded readers who want a rigorous but accessible foundation in computational finance. Whether used for study, professional development, or independent research, this book provides a structured pathway into the mathematics that supports financial decision-making.
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