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Detecting bearish and bullish markets in financial time series using hierarchical hidden Markov models
Financial markets exhibit alternating periods of rising and falling pric...
07/29/2020 ∙ by Lennart Oelschläger, et al. ∙
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Unified Treatment of Hidden Markov Switching Models
Many real-world problems encountered in several disciplines deal with th...
04/11/2011 ∙ by Silvia Chiappa, et al. ∙
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Residual Value Forecasting Using Asymmetric Cost Functions
Leasing is a popular channel to market new cars. Pricing a leasing contr...
07/10/2017 ∙ by Korbinian Dress, et al. ∙
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Multiclass Classification of Cervical Cancer Tissues by Hidden Markov Model
In this paper, we report a hidden Markov model based multiclass classifi...
12/18/2015 ∙ by Sabyasachi Mukhopadhyay, et al. ∙
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Improve Orthogonal GARCH with Hidden Markov Model
Orthogonal Generalized Autoregressive Conditional Heteroskedasticity mod...
09/23/2019 ∙ by Yufan Li, et al. ∙
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Exploring the Predictability of Cryptocurrencies via Bayesian Hidden Markov Models
In this paper, we consider a variety of multi-state Hidden Markov models...
11/07/2020 ∙ by Constandina Koki, et al. ∙
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A Comprehensive Hidden Markov Model for Hourly Rainfall Time Series
For hydrological applications, such as urban flood modelling, it is ofte...
06/10/2019 ∙ by Oliver Stoner, et al. ∙
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Market forecasting using Hidden Markov Models
04/29/2015 ∙ by Sara Rebagliati, et al. ∙
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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.
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