Identifying the turning point of stock prices utilizing Gann’s time study theory

Tsolmon Sodnomdavaa¹ , Erdenetsogt Gurbazar ^2* , Azzaya Bataa³ 

*Corresponding Author: Erdenetsogt Gurbazar 

¹Economics and Business Department, School of Engineering and Economics, Mandakh University, Mongolia, tsolmon@mandakh.edu.mn,

²Economics and Business Department, School of Engineering and Economics, Mandakh University, Mongolia, erdenetsogt@mandakh.edu.mn

³Investment advisor, Golomt Capital Securities company, Mongolia, zaya8220@gmail.com

Digital Object Identifier: https://doi.org/10.53468/mifyr.2025.05.02.21

Abstract– This study introduces a novel time-based approach for identifying turning points in stock prices using Gann’s Time Study Theory, applied to four publicly traded mining companies: Erdene Resource Development, Mongolian Mining Corporation, Steppe Gold, and Xanadu Mines. The research combines technical cycle analysis with statistical validation through one-way ANOVA and Games-Howell tests to assess whether price changes around Gann-identified dates are non-random and statistically significant. The findings reveal that turning points occur with over 70% probability within a four-day effective radius of Gann’s predicted cycle dates. Moreover, price movements surrounding eight key temporal clusters showed distinct rhythmic patterns. These results confirm the applicability of Gann’s theory in emerging markets like Mongolia and offer practical insights for investors in timing medium- and long-term trades. The study highlights the potential for integrating cyclical time analysis with statistical methods to enhance financial forecasting accuracy.

Keywords– Gann’s Time Study Theory, Turning point, Statistical validation, ANOVA, Stock market, Time-based strategy

Article History: Received 17 May 2025, Received in revised form 21 May 2025, Accepted 10 June 2025

Download file: httpsdoi.org10.53468mifyr.2025.05.02.21