1. 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

2. 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

3. 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

4. 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

5. 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 …

6. 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!

7. 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

8. 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

9. 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

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

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

12. 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 !

13. 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

14. Thank you!
Questions?