fHMM: Advancing Financial Time Series Analysis in R

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This research discusses the application of the fHMM package for financial analysis, highlighting model definition, data preparation, and validation processes. It explores Hidden Markov Models (HMMs) for market regime identification, hierarchical concepts, and financial time series simulation. Estimation methods using maximum likelihood, parameter optimization challenges, and model fit diagnostics are analyzed. Practical insights include state decoding via the Viterbi algorithm, forecasting...