Trading Strategy for Market Situation Estimation Based on Hidden Markov Model

Peng Chen, Dongyun Yi and Chengli Zhao
Additional contact information
Peng Chen: College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410073, China
Dongyun Yi: College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410073, China
Chengli Zhao: College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410073, China

Mathematics, 2020, vol. 8, issue 7, 1-13

Abstract: Determining states of the market and scientific laws of transfer between these states is an important subject in the field of financial mathematics. According to the results of market situation estimation, formulating corresponding trading strategies can gain profits in the market through machine trading. The market situation is mainly divided into three types: bull market, mixed market and bear market, and it can be further subdivided into multiple types. Using the hidden Markov model (HMM) to estimate the market situation is not restricted by linear conditions compared to the traditional use of linear models. In this paper, we first use HMM to model the market situation, perform feature analysis on the hidden state of the model input, and then estimate the three market situations, and propose the Markov situation estimation trading strategy. On this basis, we have made a more fine-grained division of the market situation and increased the number of hidden sequences in the model. Experiments verify that this method can improve the profitability of the strategy.

Keywords: hidden Markov model; market situation; situation estimation; trading strategy (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2227-7390/8/7/1126/pdf (application/pdf)
https://www.mdpi.com/2227-7390/8/7/1126/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:8:y:2020:i:7:p:1126-:d:382308

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().