Maths in Motion: The Quant's Guide to Finance…

Here are the main mathematical tools 🧰 and techniques forming the backbone of quantitative analysis in finance, helping professionals in the field to model, analyze, and make informed decisions on complex financial products and strategies.

1. Calculus: 
- Example: Calculating the delta of an option, which indicates how the price of the option changes concerning a change in the underlying stock price. Delta is the first derivative of the option's price with respect to the stock price.

2. Linear Algebra:
- Example: Portfolio optimization using Markowitz's Efficient Frontier, which relies on matrices to compute portfolio variances and covariances.

3. Probability and Statistics:
- Example: Value at Risk (VaR) is a statistical technique used to measure and quantify the level of financial risk within a firm or investment portfolio over a specified time frame.

4. Stochastic Calculus:
- Example: The Black-Scholes-Merton model, which prices European options by using a stochastic differential equation.

5. Partial Differential Equations (PDEs):
- Example: The heat equation used in finance to model how the prices of a financial derivative evolves over time.

6. Time Series Analysis:
- Example: Using ARIMA (Autoregressive Integrated Moving Average) models to forecast stock prices based on past price datas.

7. Numerical Methods:
- Example: Using the Monte Carlo simulation to estimate the price of an American option, which cannot be priced analytically like European options.

8. Optimization:
- Example: Determining the optimal weights of assets in a portfolio to achieve the highest expected return for a giving level of risk using the Sharpe Ratio.

9. Graph Theory:
- Example: Analyzing interbank lending to identify potential system-wide financial risks, where each bank is a node and lending relationships are edges.

10. Machine Learning and Data Science:
- Example: Utilizing neural networks to predict stock price movements based on various input features, such as past prices, trading volume, and other financial indicators.

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About the Author

 

 Florian Campuzan is a graduate of Sciences Po Paris (Economic and Financial section) with a degree in Economics (Money and Finance). A CFA charterholder, he began his career in private equity and venture capital as an investment manager at Natixis before transitioning to market finance as a proprietary trader.

 

In the early 2010s, Florian founded Finance Tutoring, a specialized firm offering training and consulting in market and corporate finance. With over 12 years of experience, he has led finance training programs, advised financial institutions and industrial groups on risk management, and prepared candidates for the CFA exams.

 

Passionate about quantitative finance and the application of mathematics, Florian is dedicated to making complex concepts intuitive and accessible. He believes that mastering any topic begins with understanding its core intuition, enabling professionals and students alike to build a strong foundation for success.