Bayesian Drift Update - Quant Researcher Interview Question
Difficulty: Medium
Category: statistical_analysis
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Topics: bayesian, statistics, estimation, probability
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.
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