2012/12/30 by Younes Ben-Ghabrit, Ben-Ghabrit, Younes
Decision Sciences · Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #FOS: Economics and business #Statistical Finance (q-fin.ST) #Stock Market Forecasting Methods #Trading and Market Microstructure (q-fin.TR) #q-fin.ST #q-fin.TR
paper · pdf · doi:10.48550/arxiv.1212.6791
arxiv created 2012/12/30 · openalex publication_date 2012/12/30 · arxiv updated 2013/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this report, we talked about a new quantitative strategy for choosing the optimal(s) stock(s) to trade. The basic notions are generally very known by the financial community. The key here is to understand 1) the standard score applied to a sample and 2) the correlation factor applied to different time series in real life. These notions are the core of our research. We are going to begin with the introduction section. In this part, we talked about variance, covariance, correlation factor, daily returns in stock trading and the Shapiro-Wilk test to test the normality of a time serie. Next to that, I talked about the core of my method (what do you do if you want to pick the optimal(s) stock(s) to trade). At the end of this report, I talked about a new idea if you want to analyze more than one stock at the time. All my work goes with a primary reflexion : forecasting a stock direction is a random walk and nobody can be 100 % sure where a stock is going. All we can do, is to pretend to have a technic with a win/loss ratio greater than 51 %.