---
title: Time-Varying Equity Premia & Sentiment
url: https://www.ml-quant.com/papers/ssrn/4505699/
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 4505699
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4505699
featured: 2023-07-12
citations: unknown
topic: LLMs & Text
---


# Time-Varying Equity Premia & Sentiment

From 1990 to 2022, equity market returns can be predicted using a simple model, with higher returns following high implied volatility and lower returns after high market sentiment.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4505699
- Identifier: SSRN 4505699
- Released: 2023-06-19
- First featured: Quant Letter No. 7 (2023-07-12): https://www.ml-quant.com/issues/2023-07-12/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: LLMs & Text

## Related

- [VIX and Global Consciousness in Market Sentiment](https://www.ml-quant.com/papers/repec/eme-jespps-jes-11-2023-0663/): The research finds a significant correlation between Global Consciousness Project data and the S&P 500 Volatility Index, suggesting its potential in predicting market sentiment.
- [Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models](https://www.ml-quant.com/papers/ssrn/4412788/): ChatGPT predicts stock market returns using sentiment analysis, outperforming traditional methods.
- [Instruct-FinGPT: Financial Sentiment Analysis by Instruction Tuning of General-Purpose Large Language Models](https://www.ml-quant.com/papers/arxiv/2306.12659/): A new approach improves financial sentiment analysis by addressing limitations of language models.
- [Designing Heterogeneous LLM Agents for Financial Sentiment Analysis](https://www.ml-quant.com/papers/arxiv/2401.05799/): A study suggests using large language models without fine-tuning for financial sentiment analysis, offering a design framework that enhances accuracy.
- [Sentiment trading with large language models](https://www.ml-quant.com/papers/doi/10-1016-j-frl-2024-105227/): The OPT model, a large language model, has proven superior in predicting stock market returns using sentiment analysis of U.S. financial news, outdoing traditional methods like the Loughran-McDonald dictionary model.
- [Application of Fundamental Analysis in Stock Valuation in the Capital Market and Investment Decisions by Price Methods Earnings Ratio (PER)](https://www.ml-quant.com/papers/ssrn/4509690/): The study finds that while fundamental analysis methods are useful in stock valuation, external factors like market sentiment and economic policy changes also influence stock prices.
