Master of Science in Business Analytics
Master of Science in Business Analytics
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Projects
2021-2022
Improve Trading Strategies With Forecasting Models
Student Team
Wenbo Xiao, Zhenghao Gu, Sung Jin Kim
Faculty Advisors
Dr. Mohammad Salehan, Dr. Mehrdad Koohikamali
Purpose
The stock market is complicated, and a small change is a signal before a huge price move. The research wanted to predict the price of a stock in the market over a period of time. The period covered can be a minute, an hour, a day, a week, or a season. Our client company is an American multinational investment banks and financial services holding company - JPMorgan and Chase. This report will use machine learning models to improve four popular trading strategies to help JPMorgan and Chase to increase their short-term trading rewards.
Study Design/Methodology/Approach
1) Using QQQ data to backtest four trading strategies' winning rate. 2) Using prediction models to predict QQQ prices and comparing four models to find the most accurate forecasting model. 3) Using the most accurate forecasting model in the four trading strategies' buy-in day, then comparing the short-term prediction price with real data.
Findings
A good forecasting model can help the traders avoid potential loss. For example, the ARIMA model has the potential to improve the support and resistance trading strategy's winning rate from 63.66% to 87.5%.
Research Limitations/Implications
The prediction model output depends on the performance of the forecasting model. The prediction will become meaningless if we choose a bad performance model to do the forecasting.
Originality/Value
Combining trading strategies and predictive models presents the first important theoretical and practical contribution.
Practical Implications
We combine trading strategies with machine learning prediction to minimize the risk and maximize profit in trading to our client - JPMorgan and Chase's short-term gains.
Keywords
Stock forecasting, Trading strategies, Forecasting models, JPMorgan, Stocks trading, Buy the dip, Bottom to buy, VPC, Support, resistance, Hit the high to sell