---
title: Prices Analyst Impact on Cash Flow
url: https://www.ml-quant.com/papers/ssrn/4818320/
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 4818320
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4818320
featured: 2024-05-08
citations: unknown
topic: LLMs & Text
---


# Prices Analyst Impact on Cash Flow

The article suggests that analyst cash flow predictions are swayed by price changes not related to cash flow news, using a model that aligns subjective beliefs data with asset pricing models.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4818320
- Identifier: SSRN 4818320
- Released: 2023-05-10
- First featured: Quant Letter No. 48 (2024-05-08): https://www.ml-quant.com/issues/2024-05-08/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: LLMs & Text

## Related

- [ECC Analyzer: Extracting Trading Signal from Earnings Conference Calls using Large Language Model for Stock Volatility Prediction](https://www.ml-quant.com/papers/arxiv/2404.18470/): Stock Volatility Prediction: ECCAnalyzer, a new tool, uses advanced language models to extract data from earnings conference calls, enhancing stock volatility predictions and surpassing traditional analysis methods.
- [Getting Inspiration for Feature Elicitation: App Store- vs. LLM-based Approach](https://www.ml-quant.com/papers/arxiv/2408.17404/): A study comparing AppStore and large language model approaches for refining app features finds both are effective, but LLMs excel in novel unseen app scopes, emphasizing the role of human analysts.
- [Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on mock CFA Exams](https://www.ml-quant.com/papers/arxiv/2310.08678/): The study assesses the financial understanding of Large Language Models (LLMs) like ChatGPT and GPT-4 using CFA Program mock exam questions to improve their use in finance.
- [RAG-IT: Retrieval-Augmented Instruction Tuning for Automated Financial Analysis - A Case Study for the Semiconductor Sector](https://www.ml-quant.com/papers/arxiv/2412.08179/): The study introduces a new method for automating earnings reports analysis using Large Language Models, with promising initial findings.
- [Credit Information in Earnings Calls](https://www.ml-quant.com/papers/arxiv/2209.11914/): A new method has been developed to predict credit spread changes and company profitability using information from quarterly earnings calls, indicating that investors may not be fully exploiting this data.
- [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.
