Analysis of Technical Trends
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Transcript of 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• Earnings• Management• Fair Value
Technical Analysis
• Study trends and the state of the market• Behavioral Indicators• Anticipate price movements
Examples
• Support/Resistance Levels• Moving Averages and Momentum• Overbought and Oversold Signals• Buy and Sell
Is it possible to earn greater profits using pure technical analytics?
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
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)
Apple MACD Chart
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
DistributionHistogram of profvec
profvec
Frequency
-50 0 50 100 150
0500
1000
1500
2000
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3500
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
BBVA RSI Chart
RSI Results – Perfect Timing
S0 100 100 100 100mu 0.08 0.04 -0.02 0.08sigma 0.3 0.3 0.3 0.1mean 29.08 29.17 28.63 9.28sd 21.37 20.97 20.64 7.42lb 28.66 28.66 28.23 9.13ub 29.50 29.50 29.04 9.43
E(profit) ≈ sigma* S0
DistributionHistogram of profit
profit
Frequency
-50 0 50 100 150
0500
1000
1500
RSI Results – Quick Trigger
E(profit) ≈ 0
S0 100 100 100 100mu 0.08 0.02 -0.02 0.08sigma 0.3 0.3 0.3 0.1mean -1.32 -0.02 0.23 -2.68sd 25.69 23.68 22.46 9.836lb -1.83 -0.48 -0.20 -2.87ub -0.82 0.44 0.67 -2.49
Distribution
Histogram of profit
profit
Frequency
-200 -150 -100 -50 0 50
01000
2000
3000
4000
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
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 SellOversold if CCI < -100 Buy
Apple CCI Chart
Results
• Similar to RSI
• Perfect Timing– E(profit) ≈ 2*sigma*S0
– SD ≈ 2/3 * sigma• Quick Trigger– E(profit) ≈ 0– SD ≈ 2/3 * sigma
Histogram of profit
profit
Frequency
-150 -100 -50 0 50 100
01000
2000
3000
Histogram of profit
profit
Frequency
0 50 100 150 200 250
01000
2000
3000
4000
CCI Conclusion
• Still impossible to attain perfect timing• Expected profit likely to be closer to 0
Conclusion
• Technical analysis• Geometric Brownian Motion• Not useful
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
Questions?