1 / 40

Chapter 9

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

cid
Download Presentation

Chapter 9

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


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

  2. 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 random pattern is a natural outcome of markets that are highly efficient and respond quickly to changes in material information

  3. Random Walks and Efficient Markets (cont’d) Efficient Market: a market in which securities reflect all possible information quickly and accurately To have an efficient market, you must have: Many knowledgeable investors actively analyzing and trading stocks Information is widely available to all investors Events, such as labor strikes or accidents, tend to happen randomly Investors react quickly and accurately to new information

  4. Efficient Market Hypothesis Efficient Market Hypothesis (EMH): information is reflected in prices—not only the type and source of information, but also the quality and speed with which it is reflected in prices. The more information that is incorporated into prices, the more efficient the market becomes. Levels of the EMH Weak Form EMH Semi-strong Form EMH Strong Form EMH

  5. Levels of EMH Weak Form EMH 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 EMH Abnormally large profits cannot be consistently earned using public information Any price anomalies are quickly found out and the stock market adjusts Strong Form EMH There is no information, public or private, that allows investors to consistently earn abnormally high returns

  6. Market Anomalies Calendar Effects Stocks returns may be closely tied to the time of year or time of week Questionable if really provide opportunity Examples: January effect, weekend effect Small-Firm Effect Size of a firm impacts stock returns Small firms may offer higher returns than larger firms, even after adjusting for risk

  7. Market Anomalies (cont’d) Earnings Announcements Stock price adjustments may continue after earnings adjustments have been announced Unusually good quarterly earnings reports may signal buying opportunity P/E Effect (Value Effect) Uses P/E ratio to value stocks Low P/E stocks may outperform high P/E stocks, even after adjusting for risk

  8. 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

  9. 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

  10. Investor Behavior and Security Prices (cont’d) 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

  11. Investor Behavior and Security Prices (cont’d) 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

  12. 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

  13. Behavioral Finance at Work in the Markets (cont’d) 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

  14. Behavioral Finance at Work in the Markets (cont’d) 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

  15. Using Behavioral Finance to Improve Investment Results (Table 9.1) 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

  16. 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

  17. Technical Analysis (cont’d) 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

  18. 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

  19. Figure 9.1 The Dow Theory in Operation

  20. Big Picture:Technical Indicators (cont’d) 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

  21. Big Picture Technical Indicators (cont’d) 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

  22. 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

  23. Volume • The volume of trading supporting a given market movement is important • A stock price (or the general market) making a new high on heavytrading volume is viewed as bullish • A stock price (or the general market) making a new low on heavy trading volume is viewed as very bearish • A stock price (or the general market) making a new high or low on lighttrading volume may indicate a temporary move likely to be reversed

  24. Key Indicator Series • A number of technical indicator series may be watched for bearish ( )and bullish ( ) trends • Contrary opinion rules • React opposite to the indicator • Reflection of individual investors • Wrong most of the time • Smart money rules • “best info” gathered by these “experts” • Overall market indicators

  25. Market Technical Indicators (cont’d) 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

  26. Market Technical Indicators (cont’d) 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

  27. Short Sales Position • A rule based on the volume of short sales in the market • Short sell when you think the stock price will fall • The contrary opinion stems from two sources: • Short seller are sometimes emotional and may overreact to the market, • more importantly; there is now a built-in demand for stocks that have been sold short by investors who will have to repurchase shares to cover their short positions • Daily short sale totals for the NYSE are reported in the Wall Street Journal

  28. Short Sales Position • Technical analysts compute a ratio of total short sales positions on an exchange to average daily exchange volume for the month • Normal ratio is between 2.0 and 3.0 • A ratio of 2.5 indicates current short sales are equal to 2 ½ times the day’s average trading volume • As the ratio (called the short interest ratio) approaches the higher end of the normal range, this would be considered bullish • Use of the ratio has produced mixed results

  29. Market Technical Indicators (cont’d) 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

  30. Odd-Lot Theory • An odd-lot trade is one of less than 100 shares — only small investors tend to engage in odd-lot transactions • The odd-lot trader is presumed to be a strong seller right before the bottom of a bear market • A corollary to the odd-lot theory says that Monday odd-lot trades are particularly suspect • If purchases > sales, a bad signal • watch what the small investor is doing andthen do the opposite • The weekly Barron’sreports odd-lot trading on a daily basis in its “Market Laboratory – Stocks” section

  31. Put-Call Ratio • ILL-CONCEIVED speculation in the options market suggests that a “put-call” ratio may tell you to do the opposite of what option traders are doing • Puts and calls represent options to buy or sell stock over a specified period of time at a given price: • A put is an option to sell (expect prices to fall) • A call is an option to buy (expect prices to rise) • Put-call ratio data is found in the “Market Week – Options” section of Barron’s

  32. Put-Call Ratio • The ratio of put (sell) to call (buy) options is normally about 0.60 • there are generally fewer traders of put options than call options • When the ratio gets up to 0.65 to 0.70 or higher, this indicates increasing pessimism by option traders and the contrary rules suggests a buy signal • When the ratio goes down to 0.40, decreasing pessimism (increasing optimism) may indicate that it is time to sell if you are a contrarian • The put-call ratio has a better than average record for calling market turns.

  33. 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

  34. Trading Rules and Measures (cont’d) 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

  35. Trading Rules and Measures (cont’d) The Arms Index or 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

  36. Trading Rules and Measures (cont’d) 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

  37. Trading Rules and Measures (cont’d) 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

  38. Using Technical Analysis (cont’d) 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

  39. Figure 9.7 A 100-Day Moving Average Line

  40. How The Pros Use Moving Averages. http://www.youtube.com/watch?feature=player_detailpage&v=L3EzXzofRtI What are Bollinger Bands http://www.youtube.com/watch?feature=player_detailpage&v=7PY4XxQWVfM

More Related