Open AccessApplication of Extreme Value of Nonlinear Regression Function Based on RSI Expert System
Author(s) -
Shaohe Zhang,
Hui Liu,
Zongna Xiao,
Pin Wang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1650/3/032014
Subject(s) - waveform , extreme value theory , value (mathematics) , stock (firearms) , function (biology) , econometrics , mathematics , regression , index (typography) , statistics , computer science , engineering , mechanical engineering , telecommunications , radar , evolutionary biology , world wide web , biology
This paper defines the waveform function and its corresponding concepts and axioms. The extreme value of stock price function is obtained from 24 known regression functions by using the method of seeking the extreme value, which is proven by the Shanghai stock index rising by 458.43%, 487.83% and 133.30% respectively in three different periods. This paper optimizes the expert RSI trading system with the method of mathematical extreme value, and writes the source code of the optimization formula, which provides a graphical and intuitive tool for investors. The average annual return, average winning rate and average net interest rate of waveform increasing function samples are 67.52%, 96.88% and 84.40%, respectively. The average annual return, average winning rate and average net interest rate of waveform decreasing function samples are 22.27%, 83.33% and 26.03%, respectively.