Analysis of Enhanced Hidden Markov Models for Improved Stock Market Price Forecasting and Prediction

Author:

Saxena Rishabh1ORCID,Upadhayay Adarsh1ORCID,Raj Gaurav1ORCID,Choudhury Tanupriya2ORCID,Kotecha Ketan3ORCID,Sar Ayan4ORCID,Ozseven Turgut5ORCID

Affiliation:

1. Sharda University, India

2. CSE Dept., Graphic Era Deemed to be University, India

3. Symbiosis Institute of Technology, Lavale, Pune, 412115, India., Symbiosis Centre for Applied Artificial Intelligence (SCAAI), Symbiosis International (Deemed University) (SIU), India

4. University of Petroleum and Energy Studies, India

5. Tokat Gaziosmanpasa University, Turkiye

Funder

We thank to receive the funding for this research work from RSF (Research Support funding) from Symbiosis Institute of Technology, Symbiosis International (Deemed University) (SIU),Lavale Campus, Pune, Maharashtra,412115, India.

Publisher

ACM

Reference26 articles.

1. A graph-based big data optimization approach using hidden Markov model and constraint satisfaction problem

2. Kheiri, A., & Keedwell, E. (2017). A hidden Markov model approach to the problem of heuristic selection in hyper-heuristics with a case study in high school timetabling problems. Evolutionary computation, 25(3), 473-501.

3. A Higher-order Markov model for time series forecasting;Ky D. X.;International Journal of Applied Mathematics and Statistics,2018

4. A Novel Hybrid Model for Stock Price Forecasting Based on Metaheuristics and Support Vector Machine

5. Aghakhani, K., & Karimi, A. (2016, July). A new approach to predict stock big data by a combination of neural networks and harmony search algorithm. In 5th International Conference on Computer Science, Electrical and Electronics Engineering, Malaysia.

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