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I have started reading about HMM it gives an intuitive idea about what HMM is all about. I am looking out for example where its applied to Equity model using R / Excel. The material which I read so far is about its application to speech recognition.

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Am curious about this too as I am working on HMM right now, interesting question. –  Matt Wolf Dec 26 '12 at 11:05
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up vote 5 down vote accepted

Systematic Investor also did a two part series implementation in R which is also quite helpful as he details the pitfalls too.

Post One: http://systematicinvestor.wordpress.com/2012/11/01/regime-detection/

Part Two: http://systematicinvestor.wordpress.com/2012/11/15/regime-detection-pitfalls/

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The clearest and most intuitive article I have seen so far is
Kritzman et al., Regime Shifts: Implications for Dynamic Strategies in FAJ (May / June 2012)

It not only shows how you can use HMM for financial modelling but it also goes through the actual estimation algorithm (Baum-Welch) step-by-step and even gives full MATLAB-code.

From the abstract:

Regime shifts present significant challenges for investors because they cause performance to depart significantly from the ranges implied by long-term averages of means and covariances. But regime shifts also present opportunities for gain. The authors show how to apply Markov-switching models to forecast regimes in market turbulence, inflation, and economic growth. They found that a dynamic process outperformed static asset allocation in backtests, especially for investors who seek to avoid large losses.

I brought the paper to the attention of the renowned blog Quantivity and they started a series on reproducing the results in R: Here.

(I am not aware of a freely accessible copy of the paper - if you find one, please include it in a comment - I will change the answer accordingly.)

For your own experiments with HMM in R you can use the RHmm package.

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This is very nice –  pyCthon Dec 27 '12 at 19:54
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Have a look at the following two papers, one from Chris Rogers and Liang Zhang where they introduce a model using HMM which captures stylized facts of financial returns. And the second where we extended this model to risk measures.

Implementation in R is strait forward using ML as mentioned in the paper.

http://www.statslab.cam.ac.uk/~chris/papers/UAR.pdf

http://arxiv.org/pdf/1212.4126.pdf

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