1. Advanced Valuation Analysis Tools and Simulation Brian Stonerock CGU EMP Independent Study December Update

2. Overview Objective: Evaluate advanced investing and valuation concepts for investments through the development of robust cutting edge platform using the latest technologies December Update  Project Plan and Progress  Technical Analysis  Technology / Data Sources  Demo  Next Steps

3. Project Plan  Research and Plan  Develop Framework – Vaadin / Java  Implement Simple Tools  Implement Stock and Technical Analysis  Connect to Historical Servers  Implement Analysis Tools Data Mining (IP) Back Casting (IP) Bubble Bursting Documentation and Deployment

4. The Potential Rewards How can market timing can benefit returns? The only problem is that you have to be very good at it…. Based on work from Norman Fosbeck 1984

5. The Potential Rewards (Cont) The benefit of being smart enough to miss the worst 5 days of the year between Feb ‘66 and Oct ‘01 Source: “The Truth About Timing,” by Jacqueline Doherty, Barron’s (November 5, 2001)

6. Technical Analysis Technical analysis: The attempt to forecast stock prices on the basis of market-derived data Technicians (also known as quantitative analysts or chartists) usually look at price, volume and psychological indicators over time Basic Tools  Trend Lines  Moving Averages  Price Patterns  Indicators  Cycles Support Resistance Breakout

7. Technical Indicators There are, literally, hundreds of technical indicators used to generate buy and sell signals We will look at just a few that I use:  SMA – Simple Moving Average  EMA – Exponential Moving Average  RSI - Relative Strength Index (by Welles Wilder) 0 to 100 measurement the speed and change of price movements, >70 overbought and <30 oversold  MFI - Money Flow Index Similar to RSI but volume weighted  CCI - Commodity Channel Index Identifies cyclical turns in commodities seeking overbought and oversold conditions

8. Technology Overview Vaadin Java / Tomcat JFreeChart Data Sources  JStock  Interactive Brokers Trader Work Station  JBookTrader http://code.google.com/p/cgu-emp

9. Technology Overview Vaadin Architecture  http://vaadin.com http://vaadin.com

10. Technology Overview Development Process

11. Technology Overview: Eclipse Dynamic Web Project

12. Data Sources Real Time & Historical Data Servers  Interactive Brokers  Yahoo EOD, ID for various all countries  Google EOD Tickers, Quotes, and more

13. Demo

14. Next Steps: Emotionless Trading Back Casting  JStockTrader Demo Bollinger Bands Example Source: Stock Market Prediction Using Online Data:Fundamental and Technical Approaches By Nikhil Bakshi (2008)

15. Next Steps (Cont): Predicting Bubbles Ideal Type 3: Irrational institutions Bubble  Principal-agent problem, where Speculators have incentives to pay higher prices than what is supported by historical patterns or strong evidence Source: Price Bubbles on the Housing Market: Concept, theory and indicators Hans Lind (2008) Ideal Type 1: Pure Speculative Bubble  Asset price today is too high and the price eventually will fall…. Speculators believe that the price will continue to rise for some time, with potential to sell with a profit before the price falls Ideal Type 2:Irrational Expectations Bubble  Speculators become overoptimistic and think the price will continue to grow rapidly. The growth is expected to outperform history or fundamentals…. Therefore it seems rational to pay a high price "the basic intuition is straightforward: if the reason that the price is high today is only because investors believe that the selling price will be high tomorrow-when "fundamental" factors do not seem to justify such a price-then a bubble exists." (Stiglitz 1990, p 13)

16. Next Steps (Cont) Bubble Equation 9 Parameter equation that requires iterative “fitting” algorithm to predict falls http://frog-numerics.com/blog/2009-12_blog.html Source: D. Sornette and A. Johansen ('Large Financial Crashes', Physica A 245,pp. 411-422, 1997)