Alpha Algorithms Based on the Ability of Repaying Current Debt and the Level of Research and Development

This paper explores two alphas to predict stock price movements based on companies' financial health and innovation capabilities. The first alpha, How-Much-You-Can-Pay-Back (HMUCPB) Alpha, utilizes the ratio of Operating Income to Short-Term Debt to assess a company's ability to repay current debts. The second alpha, R&D Alpha, examines the ratio of Research and Development Expenses to Operating Expenses alongside returns generated from R&D investments to evaluate a company's innovation performance. Findings indicate that while HMUCPB Alpha lacks precision in forecasting due to evolving financial complexities, the R&D Alpha demonstrates strong predictive power and practical relevance in today's technology-driven market. This work emphasizes the importance of incorporating R&D metrics into investment decision-making to achieve more profitable outcomes.

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Publication Details

Journal
Applied and Computational Engineering
Published
2025-04-24
DOI
https://doi.org/10.54254/2755-2721/2025.22420
Primary Topic
Economic Development and Digital Transformation
Type
article
Field-Weighted Citation Impact
0.00
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article

Alpha Algorithms Based on the Ability of Repaying Current Debt and the Level of Research and Development

Xiaoqi Zhao, Yaqun Fu, Jiahang Zhang
Applied and Computational Engineering
Economic Development and Digital Transformation
article

Alpha Algorithms Based on the Ability of Repaying Current Debt and the Level of Research and Development

Xiaoqi Zhao, Yaqun Fu, Jiahang Zhang
article en

Abstract

This paper explores two alphas to predict stock price movements based on companies' financial health and innovation capabilities. The first alpha, How-Much-You-Can-Pay-Back (HMUCPB) Alpha, utilizes the ratio of Operating Income to Short-Term Debt to assess a company's ability to repay current debts. The second alpha, R&D Alpha, examines the ratio of Research and Development Expenses to Operating Expenses alongside returns generated from R&D investments to evaluate a company's innovation performance. Findings indicate that while HMUCPB Alpha lacks precision in forecasting due to evolving financial complexities, the R&D Alpha demonstrates strong predictive power and practical relevance in today's technology-driven market. This work emphasizes the importance of incorporating R&D metrics into investment decision-making to achieve more profitable outcomes.

Applied and Computational EngineeringVol. 134(1)
Santa Monica College (US), University of Wisconsin–Madison (US), New York University Shanghai (CN)
Openalex Percentile: Top 87%
Economic Development and Digital Transformation
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Alpha Algorithms Based on the Ability of Repaying Current Debt and the Level of Research and Development — Xiaoqi Zhao, Yaqun Fu, et al. · Applied and Computational Engineering (2025) | TGRS Research Map | TGRS