Document Type
Thesis
Date of Award
Spring 5-31-2016
Degree Name
Master of Science in Bioinformatics - (M.S.)
Department
Computer Science
First Advisor
Zhi Wei
Second Advisor
Usman W. Roshan
Third Advisor
Jason T. L. Wang
Abstract
Mean Reversion is the most commonly used model in quantitative trading. This model is associated with several factors, like ma5 and ma10 line. These factors are the most significant in stock markets. However, the disadvantages of this model are lag and inaccuracy.
In this research, we get the historical and current stock data by web crawler, analyze the quantitative data and build a new model involved with the KDJ. Taking biotech companies marketed in the United States and B-share marketed in China as the research subjects, the result shows increased profits compared with the Mean Reversion model. It also shows that as long as we clearly understand the relationship between the turnover and fluctuation of share price, we can find the trading signals more accurately and generate more profit.
Recommended Citation
Zha, Shijie, "Uusing the KDJ as a trading strategy on biotech companies" (2016). Theses. 283.
https://digitalcommons.njit.edu/theses/283
