Stock Market Trend Analysis Using Hidden Markov Model and Long Short Term Memory
Not on the map. Why?
Abstract (arXiv)
This paper intends to apply the Hidden Markov Model into stock market and and make predictions. Moreover, four different methods of improvement, which are GMM-HMM, XGB-HMM, GMM-HMM+LSTM and XGB-HMM+LSTM, will be discussed later with the results of experiment respectively. After that we will analyze the pros and cons of different models. And finally, one of the best will be used into stock market for timing strategy.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 0 of its 4 references that are in the map. First posted on arXiv 20 Apr 2021.
Builds on
0 of 4 references.
No references here yet.
Built on by
Citing papers per year: 2024: 1.
1 paper.
- 2024Financial Fine-tuning a Large Time Series Modelcited by 8
- 2024Financial Fine-tuning a Large Time Series Model13 Dec 2024