Bayesian Drift Update - Quant Researcher Interview Question

Problem Description

Estimating the drift of an asset is a fundamental challenge in quantitative finance, often addressed using Bayesian inference to combine prior beliefs with noisy market data. This approach models the drift as a hidden parameter and updates the probability distribution of expected returns as new observations become available. By utilizing a Normal-Normal conjugate prior, analysts can analytically derive the posterior distribution to refine return estimates and quantify uncertainty. Task Implemen