---
title: Economic Narratives in Portfolio Management
url: https://www.ml-quant.com/papers/ssrn/4783643/
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 4783643
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4783643
featured: 2024-04-10
citations: unknown
topic: Portfolio & Allocation
---


# Economic Narratives in Portfolio Management

Machine learning models incorporating economic narratives into market portfolio management have been found to outperform benchmarks, particularly during recessions and high investor sentiment periods.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4783643
- Identifier: SSRN 4783643
- Released: 2023-11-16
- First featured: Quant Letter No. 44 (2024-04-10): https://www.ml-quant.com/issues/2024-04-10/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Portfolio & Allocation

## Related

- [Foreign Portfolio Investment and Index Crash Risk](https://www.ml-quant.com/papers/repec/taf-oaefxx-v-12-y-2024-i-1-p-2305481/): Research shows that exchange rate fluctuations and investor sentiment significantly impact country index crash risk, while net foreign portfolio investment has minimal effect.
- [Winners vs. Losers: Momentum-based Strategies with Intertemporal Choice for ESG Portfolios](https://www.ml-quant.com/papers/arxiv/2505.24250/): The study introduces a new momentum framework that adjusts to changing ESG sentiment, showing that portfolios with poor ESG performance outperform those with good ESG performance in pro-ESG regimes due to market overreaction, challenging traditional ESG investment beliefs.
- [From Headlines to Holdings: Deep Learning for Smarter Portfolio Decisions](https://www.ml-quant.com/papers/arxiv/2509.24144/): A new deep learning framework for portfolio optimization, which combines LSTM networks, Graph Attention Networks, and financial news sentiment analysis, outperforms traditional benchmarks by directly learning portfolio weights, resulting in higher cumulative returns and Sharpe ratios.
- [ESG and Behavioral Finance: Why ESG Investing Is Primarily a Psychological Phenomenon](https://www.ml-quant.com/papers/ssrn/4786610/): A Psychological Phenomenon: The study expands traditional portfolio selection and asset pricing theory to include ESG investing, introducing two behavioral innovations related to investor preferences and biased judgments about ESG impact and return distributions.
- [Optimal Rebalancing in Dynamic AMMs](https://www.ml-quant.com/papers/arxiv/2403.18737/): A new method for optimally rebalancing asset ratios in Dynamic Automated Market Maker pools could potentially increase pool profit and loss by about 25% for a BTC-ETH-DAI pool from July 2022 to June 2023.
- [Deep Reinforcement Learning: Extending Traditional Financial Portfolio Methods](https://www.ml-quant.com/papers/ssrn/4780026/): The paper suggests that deep reinforcement learning can potentially improve traditional portfolio allocation strategies by incorporating contextual data and future rewards.