Li Wang Ross School of Business Ann Arbor, MI 48105 The Stock Market Forecasting and Risk Management System using Genetic Programming Li Wang Ross School of Business Ann Arbor, MI 48105

Technical Analysis Technical analysis identifies trading opportunities by studying the historical prices and their statistics Major proponents are practitioners Traders, money managers, brokers, etc. They believe: Buyers and sellers on the financial market are human beings, who always tend to bid things up beyond or sell them below their reasonable values Psychological factors are important and studying the past stock prices can help understand these factors

Fundamental Analysis Fundamental analysis forecasts the future performance of stocks based on economic information P/E ratio, book values, cash flows, GDP, etc. The majority of researchers in finance and economics are proponents of fundamental analysis They believe: The stock market is efficient and investors are rational The stock price always reflects all the information available to the public The value of the stock only depends on the fundamentals of the business

The Debate between Technical Analysis and Fundamental Analysis There has been extensive debate and research on whether technical analysis is valid Academic researchers argue that: Stock prices follow random walk They are memoryless – what happened in the past has no impact on the future There are a myriad of academic papers demonstrating that technical analysis does not work

The Debate between Technical Analysis and Fundamental Analysis (cont.) Technical analysis practitioners believe: Stock price movement is generated by collective activities of market participants, so it is a consequence of human behavior Although human behavior can not be perfectly predicted, it is far from random walk The ineffectiveness of technical analysis reported in academic papers is due to the following mistakes: Only simple rules are tested in the papers Technical rules are blindly applied on every chart signal Effective rules evolve over time …

Purpose of this project Use Genetic Programming Technique Explore if we can use historical stock prices, volumes and statistics on them to: Forecast future movement of stock prices Manage risk of portfolios Make profits!

Exp1: Forecasting Overnight Gap Stock prices are not continuous Usually there is a gap between yesterday’s close price and today’s open price It is associated with a significant amount of risk Traders tend to avoid this risk e.g. day traders

Exp1: Forecasting Overnight Gap (cont.) Purpose of this experiment: Explore if we can predict the overnight gap and take advantage of it (make profits from it) If we succeed: Overnight trading strategy A new trading strategy Opposite to day trading If we predict there will be a gap up tomorrow, we buy before market is closed and sell immediately after the market is open on the next day If we predict there will be a gap down, we short sell before market is closed and buy back on the next day

Exp1: Forecasting Overnight Gap (cont.) Software package: lil-gp Written in C Free download from MSU Experiment setup: XOM, historical prices and volumes on 230 trading days No obvious uptrend or downtrend over this period Training data: the first 150 days Testing data: the rest 80 days

Exp1: Forecasting Overnight Gap (cont.) One of the training results: A large tree -> a trading strategy Highly nonlinear

Exp1: Forecasting Overnight Gap (cont.) Testing Result X-axis: my prediction Y-axis: real overnight gap The prediction doesn’t look accurate However …

Exp1: Forecasting Overnight Gap (cont.) Ignore the small valued prediction Only trade when the prediction has larger absolute value than the threshold In 14 out of 18 (78%) trades, we can make profits If we strictly follow this strategy, we can make 5.23% in 3~4 months => Beat the market and many mutual funds !

Exp1: Forecasting Overnight Gap (cont.) Another trading strategy Make profits in 5 out of 6 trades (83%) If strictly follow this strategy, we can make 2.5% with only 6 trades on this single stock How should we use this technique: Monitor hundreds of stocks Pick the most significant stocks for trading at the end of every day

Thank you! Questions?