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Hard · machine_learning · Quant Researcher interview question · hmm, viterbi, regime_detection, dynamic_programming, machine_learning
Hidden Markov Models (HMMs) are used in quantitative finance to model systems with unobserved states, such as bull and bear market regimes. The Viterbi algorithm provides an efficient dynamic programming solution to decode the most likely sequence of these hidden states from a series of observed data, like asset returns. This process, known as Viterbi decoding, is crucial for regime detection and tactical asset allocation strategies. Task Implement the function hmm_viterbi(observations, pi, A,