Open Access Open Access  Restricted Access Subscription or Fee Access

A Markov-fuzzy Combination Model For Stock Market Forecasting

Dao Xuan Ky, Luc Tri Tuyen

Abstract



This paper presents a simple combination of Markov model and fuzzy time series model (called MC-fuzzy) for forecasting stock market data. The fuzzy time series model is used to partition the dataspace into states and also solves the fuzzy data in stock index future price. The Markov model then is used to identify data patterns and forecast future states. The appropriate fuzzy rule then defuzzies the data for forecast value. Experimental results of
the proposed model show that the performance is better than other forecasting models such as, ARIMA, artificial neural network (ANN), Hidden Markov Model (HMM) -based models and equivalent to HMM-Fuzzy models.

Keywords


imakov chain, fuzzy time series, stock market, forecasting, hidden markov model.

Full Text:

PDF

Refbacks

  • There are currently no refbacks.


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.