Advanced Valuation Analysis Tools and Simulation

Brian Stonerock

CGU EMP Independent Study

December Update

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

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

The Potential Rewards

How can market timing can benefit returns? The only problem is that you have to be very good at it….

Alternative Market Strategies (1964 to 1984)Strategy Avg. Annual Gain $10,000 Grows ToBuy and Hold 11.46% 87,500$ Avoid Bear Markets 21.48% 489,700$ Long and Short Major Swings 27.99% 1,391,200$ Long and Short Every 5% Swing 93.18% 5,240,000,000$

Based on work from Norman Fosbeck 1984

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)

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

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

Technology Overview

VaadinJava / TomcatJFreeChartData Sources

JStock Interactive Brokers

Trader Work Station JBookTrader

http://code.google.com/p/cgu-emp

Technology Overview

Vaadin Architecture http://vaadin.com

Technology Overview

Development Process

Technology Overview: Eclipse

Dynamic Web Project

Data Sources

Real Time & Historical Data Servers Interactive Brokers Yahoo EOD, ID for various all countries Google EOD

Tickers, Quotes, and more

Demo

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)

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)

Next Steps (Cont)

Bubble Equation9 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)