fHMM

Fitting (hierarchical) hidden Markov models to financial data via maximum likelihood estimation. See Oelschläger, L. and Adam, T. "Detecting Bearish and Bullish Markets in Financial Time Series Using Hierarchical Hidden Markov Models" (2021, Statistical Modelling) doi:10.1177/1471082X211034048 for a reference on the method. A user guide is provided by the accompanying software paper "fHMM: Hidden Markov Models for Financial Time Series in R", Oelschläger, L., Adam, T., and Michels, R. (2024, Journal of Statistical Software) doi:10.18637/jss.v109.i09.

Last 30 days

This package has been downloaded 563 times in the last 30 days. This could be a paper that people cite without reading. Reaching the medium popularity echelon is no small feat! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 17 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 8,677 times in the last 365 days. That's a lot of interest! Someone might even write a blog post about it. The day with the most downloads was Aug 22, 2024 with 86 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.