---
title: Interpretive Earnings Forecasts via Machine Learning: A High-Dimensional Financial Statement Data Approach
url: https://www.ml-quant.com/papers/ssrn/4619313/
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 4619313
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4619313
featured: 2023-11-02
citations: 2
topic: Econometrics & Forecasting
---


# Interpretive Earnings Forecasts via Machine Learning: A High-Dimensional Financial Statement Data Approach

Using machine learning models and comprehensive Compustat financial statement data for earnings forecasting can yield predictions that are up to 13% more accurate than traditional linear approaches.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4619313
- Identifier: SSRN 4619313
- Released: 2023-10-31
- First featured: Quant Letter No. 24 (2023-11-02): https://www.ml-quant.com/issues/2023-11-02/
- Citations (Semantic Scholar): 2
- Published in: not yet
- Topic: Econometrics & Forecasting

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