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Analysis of Technical Trends

Analysis of Technical Trends. Ryan Weikert. Asset Valuation. Pricing, Buying , and Selling of Assets Methods of Appraisal What stocks, when? Fundamental Analysis Technical Analysis. Fundamental Analysis. Quality Sector/Industry Financial Statements Peer and Historical Comparisons

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Analysis of Technical Trends

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  1. Analysis of Technical Trends Ryan Weikert

  2. Asset Valuation • Pricing, Buying, and Selling of Assets • Methods of Appraisal • What stocks, when? • Fundamental Analysis • Technical Analysis

  3. Fundamental Analysis • Quality • Sector/Industry • Financial Statements • Peer and Historical Comparisons • Earnings • Management • Fair Value

  4. Technical Analysis • Study trends and the state of the market • Behavioral Indicators • Anticipate price movements

  5. Examples • Support/Resistance Levels • Moving Averages and Momentum • Overbought and Oversold Signals • Buy and Sell

  6. Is it possible to earn greater profits using pure technical analytics?

  7. Process • Generate Random Walks • Geometric Brownian Motion • Apply certain technical indicators to these random walks • Generate buy and sell signals • Record asset price at the time of those signals • Calculate profit

  8. Moving Average Convergence Divergence (MACD) • Signals upward and downward momentum • Exponential Moving Average (EMA) • Xi=(Pi - Xi-1)*[2/(# of periods + 1)]+Xi-1 • MACD=12 day EMA – 26 day EMA • Signal Line=9 day EMA MACD • MACD Histogram = MACD – Signal Line • Buy if MACD Histogram > 0 (upward momentum) • Sell if MACD Histogram < 0 (downward momentum)

  9. Apple MACD Chart

  10. MACD Results • E(profit) ≈ ½ (mu)(S0) • SD ≈ 2/3 (sigma)(S0) • If mu = .08, S0 = 100, sigma=.3 • E(profit)=3.95 • SD = 22.15 • ½ expected profit of a long position • Only slightly less risk • Inferior

  11. Distribution

  12. Relative Strength Index (RSI) • Overbought and Oversold signals • RSI = 100 – 100/(1+Relative Strength) • Relative Strength = Average Gain/Average Loss • Agi = [Agi-1 * 13 + current gain] / 14 • 0<RSI<100 • Oversold if RSI <30  Buy • Overbought if RSI >70  Sell

  13. BBVA RSI Chart

  14. RSI Results – Perfect Timing • E(profit) ≈ sigma* S0

  15. Distribution

  16. RSI Results – Quick Trigger E(profit) ≈ 0

  17. Histogram of profit 4000 3000 2000 Frequency 1000 0 -200 -150 -100 -50 0 50 profit Distribution

  18. Overall RSI Results • Further technical analysis would be required • Impossible to receive returns of Perfect Investor • If it were possible, technical indicators wouldn’t be needed • Expected profit won’t be as high • Closer to 0

  19. Commodity Channel Index (CCI) • Overbought and Oversold signals • CCI = (Typical Price – 20 day SMA of TP) (.015 * Mean Deviation) TP = (High + Low + Close)/3 Overbought if CCI > 100  Sell Oversold if CCI < -100  Buy

  20. Apple CCI Chart

  21. Results • Similar to RSI • Perfect Timing • E(profit) ≈ 2*sigma*S0 • SD ≈ 2/3 * sigma • Quick Trigger • E(profit) ≈ 0 • SD ≈ 2/3 * sigma

  22. CCI Conclusion • Still impossible to attain perfect timing • Expected profit likely to be closer to 0

  23. Conclusion • Technical analysis • Geometric Brownian Motion • Not useful

  24. Upcoming • What must be true for these indicators to yield a statistically significant profit? • Other Distributions • How are real world returns distributed? • How do they vary in different situations? • Other Processes • Autoregressive process • Lévy Process • Applied to actual graphs

  25. Questions?

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