• A library for state-of-the-art Markov Chain Monte Carlo (MCMC) simulations applied to AI LLM streaming responses.

• Evaluate the financial-value of any given prompt-response pair.

• Designed to learn temporally or improve in accuracy with respect to (w.r.t.) time.

• Black-Scholes warning 🦆

• Install the Library, via the instructions below to learn more and apply the model to your own LLM streaming...

Complexity: computed via Replicate | stability-ai/stable-diffusion-3.5-large.

Installation Instructions

To install dependencies:

To run:

This project was created using bun init in bun v1.2.16. Bun is a fast all-in-one JavaScript runtime.

What is a Markov Chain Monte Carlo sim.?

Basic History and Motivation

Written in the mid 20th-century, the Markov Chain Monte Carlo (MCMC) can, "handle complex, high-dimensional, and non-standard distributions in financial modeling... it's a powerful tool for pricing, risk management, and uncertainty quantification". [1]

Markov Chain Monte Carlo (MCMC) methods have become a cornerstone of many modern scientific analyses by providing a straightforward approach to numerically estimate uncertainties in the parameters of a model using a sequence of random samples. [2]

[1] Mistral: "codestral-latest", computed via a Geneva: Abstract.

[2] "A Conceptual Introduction to Markov Chain Monte Carlo Methods" offers a comprehensive intro to the theory: Joshua S. Speagle | Center for Astrophysics | Harvard & Smithsonian.