Statistics and Practice on the Trend’s Reversal and Turning Points of Chinese Stock Indices Based on Gann’s Time Theory and Solar Terms Effect

• Main Authors: Tianbao Zhou, Xinghao Li, Peng Wang
• Format: Article
• Language: English
• Published: MDPI AG 2021-07-01
• Series: Mathematics
• Subjects: <i>n</i>-day extreme point; valid time radius; ARIMA–ARCH model; efficient-market hypothesis; adaptive market hypothesis
• Online Access: https://www.mdpi.com/2227-7390/9/15/1713

Despite the future price of individual stocks has long been proved to be unpredictable and irregular according to the EMH, the turning points (or the reversal) of the stock indices trend still remain the rules to follow. Therefore, this study mainly aimed to provide investors with new strategies in buying ETFs of the indices, which not only avoided the instability of individual stocks, but were also able to get a high profit within weeks. Famous theories like Gann theory and the Elliott wave theory suggest that as part of the nature, market regulations and economic activities of human beings shall conform to the laws of nature and the operation of the universe. They further refined only the rules related to specific timepoints and the time cycle rather than the traditional analysis of the complex economic and social factors, which is, to some extent, similar to what the Chinese traditional culture proposes: that every impact on and change in the human society is always attributable to changes in the nature. The study found that the turns of the stock indices trend were inevitable at specific timepoints while the strength and intensity of the turns were uncertain, affected by various factors by then, which meant the market was intertwined with both certainty and uncertainty at the same time. The analysis was based on the data of the Shanghai Index, the Second Board Index and the Shenzhen Index, the three major indices that represent almost all aspects of the Chinese stock market, for the past decades. It could effectively reduce the heteroscedasticity, instability and irregularity of time series models by replacing 250 daily high-frequency data with the extreme points near every twenty-four solar terms per year. The forecasts focusing on the future stock trend of the all-solar-terms group and the eight-solar-terms group were proved accurate. What is more, the indices trend was at a high probability to turn in a range of four days at each solar term. The alert period also provided the readers with a practical example of how it works in the real investment environment.