Why Min, Max, Opening, and Closing Stock Prices Are Empirically Most Appropriate for Predictions, and Why Their Linear Combination Provides the Best Estimate for Beta

Authors

Somsak Chanaim, Chiang Mai UniversityFollow
Olga Kosheleva, The University of Texas at El PasoFollow
Vladik Kreinovich, The University of Texas at El PasoFollow

Publication Date

11-2020

Comments

Technical Report: UTEP-CS-20-116

Abstract

While we have moment-by-moment prices of each stock, we cannot use all this information to predict the future stock prices, we need to combine them into a few characteristics of the daily stock price. Empirically, it turns out that the best characteristics are the lowest daily price, the highest daily price, the opening price, and the closing price. In the paper, we provide a theoretical explanation for this empirical phenomenon. We also explain why empirically, it turns out that the best way to find the stock's beta coefficient is to consider a convex combination of the about four characteristics.