top of page

Journey through Quantitative Finance, Computational Methods, and Use of Python in Finance

The world of finance has significantly transformed over the years, particularly in the domains of Quantitative Finance, Computational Methods, and Python programming. As someone who has dedicated considerable time and resources to mastering these domains, I've unearthed a wealth of knowledge that I believe can benefit everyone, from budding analysts to seasoned professionals. I've curated a list of resources that will help you navigate these fields.


Security Analysis and Portfolio Management

Portfolio management and security analysis form the bedrock of the financial world. these are crucial areas that deal with the evaluation of securities and the construction of portfolios.

Security Analysis and Portfolio Management

(by Ranganatham): and (by Fischer):

Advanced Portfolio Management: A Quant's Guide for Fundamental Investors:

Quantitative Equity Portfolio Management: Modern Techniques and Applications:

Applied Equity Analysis and Portfolio Management:

Quantitative Portfolio Management: Art and Science of Statistical Arbitrage:


Fixed-Income Securities and Derivatives

Understanding fixed income is important for anyone looking to dive deep into the financial market landscape. these securities, typically bonds, are essential components of a diversified portfolio.

Fixed Income Securities: Tools for Today's Markets

Stochastic Interest Rates

Analysing and Interpreting the Yield Curve

Fixed Income Markets: Management, Trading and Hedging:

Fixed-Income Securities and Derivatives: Analysis and Valuation:

Bond Market Analysis and Strategies:

Stochastic Interest Rate Modeling With Fixed Income Derivative:


Quantitative Finance

Quantitative Finance blends mathematics, statistics, and programming to create models that predict market behavior.

Introduction to Quantitative Finance:

Frequently Asked Questions in Quantitative Finance:

Quantitative Finance with Python: A Practical Guide to Investment Management, Trading, and Financial Engineering:

Stochastic Volatility Modeling:

Discrete & Continuous-Time Stochastic Process: not available

Numerical Solution of Stochastic Differential Equations with Jumps:

Stochastic Simulation and Monte Carlo Methods:

Option, Futures, and Other Derivatives

FX Options and Structured Products:

Value at Risk: The New Benchmark for Managing Financial Risk:

Backtesting Value at Risk and Expected Shortfall:


Time Series, Statistics and Its Practical Applications in Finance

Statistics play a central role in financial analysis, helping experts discern patterns, predict future trends, and make informed decisions.

Modern Time Series Forecasting:

Introduction to Statistical Learning: Applications:

The Elements of Statistical Learning:

Introduction to Probability for Data Science:

Statistics and Machine Learning in Python

(by Edouard): not available


Python for Finance and Machine Learning

Python, due to its simplicity and extensive libraries, has become the go-to language for financial analysis and machine learning.

Mastering Data-Driven Finance:

Financial Models and Quantitative Analysis:

Machine Learning for Financial Risk Management: Algorithms for Modeling Risk:

Machine Learning using Python:

727 views0 comments
bottom of page