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Chapter 9

Chapter 9. Technical Analysis, Market Efficiency, and Behavioral Finance. Market Price Behavior. Learning Goals Discuss the purpose of technical analysis and why market performance is important to stock valuation.

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Chapter 9

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  1. Chapter 9 Technical Analysis, Market Efficiency, and Behavioral Finance

  2. Market Price Behavior • Learning Goals • Discuss the purpose of technical analysis and why market performance is important to stock valuation. • Describe approaches to technical analysis, such as the Dow Theory, moving averages, charting and indicators of the technical condition of the market. • Compute and use technical trading rules. • Explain the idea of random walks and efficient markets and note the challenges these theories hold for the stock valuation process.

  3. Market Price Behavior • Learning Goals • Describe the weak, semi-strong, and strong versions of the efficient market hypothesis and explain what market anomalies are. • Demonstrate a basic understanding of how psychological factors can affect investors’ decisions, and how behavioral finance presents a challenge to the concept of market efficiency.

  4. Technical Analysis • Before financial data/financial statements were required to be disclosed, investors could only watch the stock market itself to determine buy-or-sell decisions • Investors began keeping “charts” of stock market movements to look for patterns, or “formations” that indicated whether to buy or sell • Studies have shown that anywhere from 20% to 50% of the price behavior of a stock can be traced to overall market forces

  5. Technical Analysis • Technical Analysis is the study of the various forces at work in the marketplace and their affect on stock prices. • Focus is on trends in a business’ stock price and the overall stock market • Stock prices are a function of supply and demand for shares of stock • Used to get a general sense of where the stock market is going in the next few months • Several technical indicators may be used together

  6. Big Picture Technical Indicators • The Dow Theory • Market’s performance is based upon long-term price trend (primary trend) in overall market • Used to signal end of both bull and bear markets • An after-the-fact measure with no predictive power

  7. Big Picture:Technical Indicators • Trading Action • Looks at minor trading characteristics in market over long periods of time • Assumes the market moves in cycles and these cycles repeat themselves • Trading rules are formed from patterns: • January indicator • Presidential election indicator • Super Bowl indicator

  8. Big Picture Technical Indicators • Confidence Index • Looks at ratio between yields on high-grade corporate bonds compared to low-grade corporate bonds • Optimism and pessimism about the future outlook is reflected in the bond yield spread • Trend of “smart money” is revealed in bond market before it shows up in stock market

  9. Market Technical Indicators • Market Volume • Pure supply and demand analysis for common stocks • Strong market when volume goes up • Weak market when volume goes down

  10. Market Technical Indicators • Breadth of the Market • Looks at number of stock prices that go up (advances) versus number of stock prices that go down (declines) • Strong market when advances outnumber declines • Weak market when declines outnumber advances

  11. Market Technical Indicators • Short Interest • Looks at number of stocks that have been sold short at any given time • Can give two different interpretations: • Measure of Future Demand for Stock • Strong market when short sales are high since guarantees future stock sales to cover the short positions • Measure of Present Market Optimism or Pessimism • Weak market when short sales are high since professional short sellers think stocks will decline

  12. Market Technical Indicators • Contrary Opinion and Odd-Lot Trading • Measures the volume of small traders • Assumes that small traders will do just the opposite of what should be done • Panic and sell when market is low • Speculate and buy when market is high • Bull market when odd-lot sales significantly outnumber odd-lot purchases • Bear market when odd-lot purchases significantly outnumber odd-lot sales

  13. Trading Rules and Measures • Advance-Decline Line • Measures the difference between stocks closing higher and stocks closing lower than previous day • Difference is plotted on graph to view trends • Used as signal to buy or sell stocks • Bull market when advances outnumber declines • Bear market when declines outnumber advances

  14. Trading Rules and Measures • New Highs–New Lows • Measures the difference between stocks reaching a 52-week high and stocks reaching a 52-week low • 10-day moving average is plotted on graph to view trends • Used as signal to buy or sell stocks • Bull market when highs outnumber lows • Bear market when lows outnumber highs

  15. Trading Rules and Measures • The Trading Index (TRIN) • Combines advance-decline line with trading volume • Used as signal to buy or sell stocks • Bull market when TRIN values are lower • Bear market when TRIN values are higher

  16. Trading Rules and Measures • Mutual Fund Cash Ratio (MFCR) • Tracks cash position of mutual funds • High cash positions in mutual funds provides liquidity for future stocks purchases or protection from future mutual fund withdrawals • Bull market when MFCR values are higher • Bear market when MFCR values are lower

  17. Trading Rules and Measures • On Balance Volume • Tracks the volume to price change relationship as a running total • Up-volume occurs when stock closes higher and is added to running total; down-volume occurs when stock closes lower and is subtracted from running total • Direction of indicator is more important than actual value • Used to confirm price trends • Bull market when OBV values are higher • Bear market when OBV values are lower

  18. Using Technical Analysis • Charting • Shows visual summary of stock activity over time • Easy to use and to understand • Use to spot developing trends • Major types • Bar Charts • Point-and-Figure Charts • Chart Formations

  19. Using Technical Analysis • Bar Charts • Shows changes in stock price over period of time • Often used to compare current stock price with moving average • When current price goes above or below a moving average, indicates significant price change

  20. A Bar Chart

  21. Using Technical Analysis • Point-and-Figure Charts • Only shows significant changes in stock price patterns • Up patterns are shown as an “X” and down patterns are shown as an “O”

  22. A Point-and-Figure Chart

  23. Using Technical Analysis • Chart Formations • Looking for patterns, or formations, that historically meant that stocks were going up or down • Buy when stocks break through a “line of resistance” • Sell when stocks break through a “line of support”

  24. Some Popular Chart Formations

  25. Using Technical Analysis • Moving Averages • Tracks data (usually stock price) as average value over time • Used to “smooth out” daily fluctuations and focus on underlying trends • Usually calculated over periods ranging from 10 to 200 days

  26. A 100-Day Moving Average Line

  27. Random Walks and Efficient Markets • Random Walk: the theory that stock price movements are unpredictable, so there is no way to know where prices are headed • Studies of stock price movements indicate that they do not move in neat patterns • This could be an indication that markets are highly efficient and respond quickly to changes in the current situation

  28. Random Walks and Efficient Markets • Efficient Market: a market in which securities reflect all possible information quickly and accurately • Efficient Market Hypothesis: markets have a large number of knowledgeable investors who react quickly to new information, causing securities prices to adjust quickly and accurately

  29. Random Walks and Efficient Markets • To have an efficient market, you must have: • Many knowledgeable investors active in analyzing and trading stocks • Information is widely available to all investors and is free and or easy to obtain • Events, such as labor strikes or accidents, tend to happen randomly • Investors react quickly and accurately to new information, causing prices to adjust

  30. Levels of Efficient Markets • Weak Form • Past data on stock prices are of no use in predicting future stock price changes • Everything is random • Should simply use a “buy-and-hold” strategy • Semi-strong Form • Abnormally large profits cannot be consistently earned using public information • Any price anomalies are quickly found out and the stock market adjusts

  31. Levels of Efficient Markets • Strong Form • There is no information, public or private, that allows investors to consistently earn abnormally high returns

  32. Market Anomalies • Calendar Effects • Stocks returns may be closely tied to the time of year or time of week • Examples: January effect (small stock prices go up during Jan), weekend effect (Monday’s Open is Lower than Friday Close) • Small-Firm Effect • Size of a firm impacts stock returns • Small firms may offer higher returns than larger firms, even after adjusting for risk

  33. Market Anomalies • Earnings Announcements • Stock price adjustments may continue after earnings adjustments have been announced (Lots of adjustment prior to announcement) • Unusually good quarterly earnings reports may signal buying opportunity • P/E Effect • Uses P/E ratio to value stocks • Low P/E stocks may outperform high P/E stocks, even after adjusting for risk

  34. Technical vs. Fundamental:So Who is Right? • There is growing consensus that markets may not be perfectly efficient, but they may be at least reasonably efficient • Individual investor must determine which approach has merits for their investing decisions

  35. Investor Behavior and Security Prices • Overconfidence • Investors tend to be overconfident in their judgment, leading them to underestimate risks • Biased Self-Attribution • Investors tend to take credit for successes and blame others for failures • Investors will follow information that supports their beliefs and disregard conflicting information

  36. Investor Behavior and Security Prices • Loss Aversion • Investors dislike losses much more than gains • Investors will hang on to losing stocks hoping they will bounce back • Representativeness • Investors tend to draw strong conclusions from small samples • Investors tend to underestimate the effects of random chance

  37. Investor Behavior and Security Prices • Narrow Framing • Investors tend to analyze a situation in isolation, while ignoring the larger context • Belief Perseverance • Investors tend to ignore information that conflicts with their existing beliefs

  38. Behavioral Finance at Work in the Markets • Stock Return Predictability • It maybe profitable to buy underperforming stocks when they are out-of-favor • Momentum of stock prices up and down tends to continue over 6- to 12-month time horizons • Value stocks may outperform growth stocks

  39. Behavioral Finance at Work in the Markets • Investor Behavior • Investors who believe they have superior information tend to trade more, but earn lower returns • Investors tend to sell stocks that have risen in value rather than declined • Investors acting on emotions instead of facts may reduce market efficiency

  40. Behavioral Finance at Work in the Markets • Analyst Behavior • Analysts may be biased by “herding” behavior, where they tend to issue similar recommendations for stocks • Analysts may be overly optimistic about a favorite stock’s future

  41. Using Behavioral Finance to Improve Investment Results • Don’t hesitate to sell a losing stock • Don’t chase performance • Be humble and open-minded • Review the performance of your investment on a periodic basis • Don’t trade too much

  42. Review • Goals • Discussed the purpose of technical analysis and why market performance is important to stock valuation. • Described approaches to technical analysis. • Computed and used technical trading rules. • Explained the idea of random walks and efficient markets.

  43. Review • Goals • Described the weak, semi-strong, and strong versions of the efficient market hypothesis and explained what market anomalies are. • Showed a basic understanding of how psychological factors could affect investors’ decisions, and how behavioral finance presents a challenge to the concept of market efficiency.

  44. The End!

  45. Chapter 9 Additional Chapter Art

  46. Figure 9.2 Some Market Statistics

  47. Table 9.1 Using Behavioral Finance to Improve Investment Results

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