Math for Quant Finance (Calculus)
Calculus, linear algebra, statistics, optimization and more.
I get a lot of people asking what math they should learn for quant finance so I’m gonna summarize all of the most common and useful math that I use in quant finance in a series of articles!
Calculus is probably what people think of first whenever someone mentions math.
It’s also the most important type of math and mostly what you learn in high school.
In the previous article, we’ve looked at a bunch of different clustering algorithms and coded up the k-means algorithm from scratch.
Clustering Algorithms - An in-depth view
In the previous article, we looked at latency arbitrage / lead-lag. We went through the techniques commonly found in literature, starting from simple techniques like linear regression to more complex ones like looking for curvature in the shortest path of a distance matrix.
Imo learning math should be done similarly, you don’t just read about it once and remember it. You keep applying it and practicing it.
That’s also why studying complicated mathematics isn’t necessary for a quant.
You won’t ever be applying it and will end up forgetting it anyway.
Table of Content
(Univariate) Calculus
Sequences
Functions
Complex Functions
Series
Exponential Function, Trigonometric Functions and Logarithm
Derivatives
Maximization/Minimization
Integrals
Multivariate Calculus
Norms
Derivatives
Maximization/Minimization
Final Remarks