---
title: CNN2D-MV Stock Model
url: https://www.ml-quant.com/papers/ssrn/4895067/
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 4895067
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4895067
featured: 2024-07-17
citations: unknown
topic: Portfolio & Allocation
---


# CNN2D-MV Stock Model

The article introduces a hybrid model that combines a 2D convolutional neural network with the mean-variance model to improve asset selection and portfolio performance.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4895067
- Identifier: SSRN 4895067
- Released: 2024-07-15
- First featured: Quant Letter No. 57 (2024-07-17): https://www.ml-quant.com/issues/2024-07-17/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Portfolio & Allocation

## Related

- [DSPO: An End-to-End Framework for Direct Sorted Portfolio Construction](https://www.ml-quant.com/papers/arxiv/2405.15833/): The paper showcases Direct Sorted Portfolio Optimization (DSPO), a framework using neural networks to process stock data and construct sorted portfolios, proven effective on various markets.
- [Causal Portfolio Optimization: Principles and Sensitivity-Based Solutions](https://www.ml-quant.com/papers/arxiv/2504.05743/): The article introduces a new risk management framework that uses Bayesian and neural networks for efficient portfolio optimization, based on Common Causal Manifolds.
- [End-to-End, Decision-based, Cardinality-Constrained Portfolio Optimization](https://www.ml-quant.com/papers/ssrn/4598167/): The article introduces a comprehensive framework for portfolio optimization using a neural network, and compares three different problem-solving methods within this framework.
- [Mean-Variance Optimization for Participating Life Insurance Contracts](https://www.ml-quant.com/papers/arxiv/2407.11761/): The study provides formulas for optimal wealth and strategy for equity holders in life insurance contracts, suggesting increased risky investments during poor economic conditions.
- [Set risk measures](https://www.ml-quant.com/papers/arxiv/2407.18687/): The study presents set risk measures, which extend traditional risk measures to sets of random variables, and establishes an axiom scheme for them, demonstrating their use in systemic risk, portfolio optimization, and decision-making under uncertainty.
- [Constrained mean-variance investment-reinsurance under the Cramér-Lundberg model with random coefficients](https://www.ml-quant.com/papers/arxiv/2406.10465/): The study offers solutions to an optimal investment-reinsurance problem for insurers under a specific model, using a system of complex mathematical equations.