N-gated Hacker NewsApr 16, 2025
🎩✨ Ah, yet another thrilling tale of someone tripping into stochastic calculus while pursuing the Holy Grail of machine learning and #finance. 🐇📉 Naïve enthusiasm meets the harsh reality of trying to compress a semester-long headache into a blog post. 🙃📝
https://bjlkeng.io/posts/an-introduction-to-stochastic-calculus/ #stochasticcalculus #machinelearning #blogpost #techenthusiasm #dataanalysis #HackerNews #ngated
An Introduction to Stochastic Calculus

Through a couple of different avenues I wandered, yet again, down a rabbit hole leading to the topic of this post. The first avenue was through my main focus on a particular machine learning topic th

Bounded Rationality
Hacker NewsApr 16, 2025

An Introduction to Stochastic Calculus

https://bjlkeng.io/posts/an-introduction-to-stochastic-calculus/

#HackerNews #StochasticCalculus #Introduction #MathFinance #ProbabilityTheory #Education

An Introduction to Stochastic Calculus

Through a couple of different avenues I wandered, yet again, down a rabbit hole leading to the topic of this post. The first avenue was through my main focus on a particular machine learning topic th

Bounded Rationality
Fabio CapelaApr 12, 2025
Geometric Brownian Motion is the stochastic differential equation used to model stock prices: dS = μSdt + σSdW. This forms the mathematical foundation for options pricing, Monte Carlo market simulations, and much of modern finance theory. Fascinating intersection of math and markets! #StochasticCalculus #FinancialModeling #RandomWalk
Hacker NewsFeb 24, 2025
Introduction to Stochastic Calculus — https://jiha-kim.github.io/posts/introduction-to-stochastic-calculus/
#HackerNews #Introduction #to #Stochastic #Calculus #StochasticCalculus #MathFinance #DataScience #Learning
Introduction to Stochastic Calculus

A beginner-friendly introduction to stochastic calculus, focusing on intuition and calculus-based derivations instead of heavy probability theory formalism.

Ji-Ha’s Blog
Francis HoDec 5, 2023

Here is a concrete visualization/example of a filtration for a stochastic process. Using the spreadsheet "filter" function makes it clear why we call it a filtration, because we are filtering out the outcomes that are no longer possible.

https://docs.google.com/spreadsheets/d/1UwKdcoTnfMDEeWOClWN9zuSwCDKrcmM7pVBlMvx0vgI/edit?usp=sharing

#probability #stochasticcalculus

Francis HoDec 3, 2023

My distance and number of steps for a walk are approximations of the variation over the interval of my location, AKA total variation.

https://en.wikipedia.org/wiki/Total_variation

They are finite because even though you may think it is so, I am not really doing a random walk (which would have infinite variation and finite quadratic variation). 😎

#BrownianMotion #stochasticCalculus

Total variation - Wikipedia

Dr. James HowardOct 30, 2023
Chaos theory and stochastic calculus might seem like strange bedfellows, but researchers are finding intersections between them. Imagine combining deterministic chaos with inherent randomness to understand complex systems like climate models or financial markets! 🌀🎲 #ChaosTheory #StochasticCalculus
Almost SureJul 14, 2023

#StochasticCalculus notes: Cadlag Modifications

https://almostsuremath.com/2009/12/18/cadlag-modifications/

Cadlag Modifications

As was mentioned in the initial post of these stochastic calculus notes, it is important to choose good versions of stochastic processes. In some cases, such as with Brownian motion, it is possible…

Almost Sure
Almost SureJul 10, 2023

#StochasticCalculus notes: Upcrossings, Downcrossings, and Martingale Convergence.

https://almostsuremath.com/2009/12/06/upcrossings-downcrossings-and-martingale-convergence/

Upcrossings, Downcrossings, and Martingale Convergence

The number of times that a process passes upwards or downwards through an interval is refered to as the number of upcrossings and respectively the number of downcrossings of the process. Consider a…

Almost Sure
Almost SureJul 9, 2023

New almostsure blog post: Model-Independent discrete barrier adjustments.

When monitoring a continuous barrier, but sample discretely, adjustments are required for good convergence.
This looks at how it can be done in a generic way

#StochasticCalculus

https://almostsuremath.com/2023/07/09/model-independent-discrete-barrier-adjustments/

Model-Independent Discrete Barrier Adjustments

I continue the investigation of discrete barrier approximations started in an earlier post. The idea is to find good approximations to a continuous barrier condition, while only sampling the proces…

Almost Sure