---
title: Predicting Implicit Patterns and Optimizing Market Entry and Exit Decisions in Stock Prices using integrated Bayesian CNN-LSTM with Deep Q-Learning as a Meta-Labeller
url: https://www.ml-quant.com/papers/ssrn/4794069/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 4794069
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4794069
featured: 2024-04-17
citations: 0
topic: Econometrics & Forecasting
---


# Predicting Implicit Patterns and Optimizing Market Entry and Exit Decisions in Stock Prices using integrated Bayesian CNN-LSTM with Deep Q-Learning as a Meta-Labeller

The piece introduces a hybrid model that combines various AI techniques for predicting stock prices and optimizing trading decisions.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4794069
- Identifier: SSRN 4794069
- Released: 2024-03-05
- First featured: Quant Letter No. 45 (2024-04-17): https://www.ml-quant.com/issues/2024-04-17/
- Citations (Semantic Scholar): 0
- Published in: not yet
- Topic: Econometrics & Forecasting

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