Market forecasting using Hidden Markov Models
This work addresses market forecasting for financial analysts, but it is incremental as it reviews existing methods without presenting new results.
The authors tackled the problem of forecasting EUR/USD Futures prices using Hidden Markov Models (HMMs) by analyzing daily closing prices and log returns, with the result being an evaluation of how HMMs describe financial time series and a comparison of forecasting methods from literature.
Working on the daily closing prices and logreturns, in this paper we deal with the use of Hidden Markov Models (HMMs) to forecast the price of the EUR/USD Futures. The aim of our work is to understand how the HMMs describe different financial time series depending on their structure. Subsequently, we analyse the forecasting methods exposed in the previous literature, putting on evidence their pros and cons.