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Lecture Not

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Markets and Information
Market Efficiency

Overview
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So far we have considered a number of asset pricing models These have all required that price is a good reflection of value Is this likely to be the case? How? Why?

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Today
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Trend and predictability Efficient market hypothesis
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Implications Supporting evidence Behavioural biases


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Barriers to the EMH


Anomalies Can we build a fully efficient market?

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Market Efficiency
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Efficiency in engineering: the best possible use of the inputs. An efficient market: investors make the best possible use of information. A useful initial perspective:
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As speculators we are trying to predict where a stock price will be in the future. Do we know anything today that will help us make this prediction?

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Price of GE
104 102 100 98 96 94 92 90 88 0
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20

40
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60

80

100
5

Are Prices Predictable?


There are apparently short-run trends
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If we know we are at the start of a downward trend, sell short If we know we are at the start of an upward trend, buy





How do you know when a trend is starting? ending? Can we devise rules (statistical or “technical”)?

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Trend and Predictability




The price path is simulated: Price(Today) = Price(Yesterday) + x, where x is a standard normal random variable This process is called a random-walk
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By construction, any trends that appear in a particular sample price path arise purely from chance There are no rules that will help us identify trends in time for us to profit by them



Do trends imply predictability?

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Efficient Market Hypothesis (EMH)


Stock prices reflect all available information:






Weak-form efficiency Price fully reflects all information contained in trading history (price, volume, etc) Semi-strong-form efficiency Price fully reflects all public information on the firm (accounting information, etc.) Strong-form efficiency Price reflects all public and private information known to investors

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What makes a market efficient?
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BIG oil closed yesterday at 100 After trading closed, BIG announced larger than expected reserves:


extra value = $10 per share 109.90 bid, 110.10 offer


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BIG jumps to 110 immediately at the open


No trading is needed The semi-strong form of market efficiency Timely and accurate disclosure improves market efficiency.
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Week 5

What makes a market efficient?
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Institutional participation:


Research and economies of scale Suppose that P(today) = 100 A reliable technical rule indicates that P(tomorrow) = 110 Anyone who knows this rule will buy the stock today, driving P(today) up to 110, i.e., today’s stock price already impounds the information in the rule

Competition defeats conventional trading strategies







Insider trading regulation and enforcement

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Trading and Private Information


CEO of BIG oil knows the additional reserves and trades before the announcement:
    

Buy at the ask (100.10) Quotes revised to 100 bid, 100.20 offered Buy more at 100.20 Quotes revised to 100.10 bid, 100.30 offered Stop buying when the offer reaches 110

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Closing price (110) is driven by and reflects private information The strong form of market efficiency

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Market Impact of Insider Trading
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Incorporating information quicker Greater information asymmetry


May lead to larger spread, higher volatility, and lower liquidity

Insider trading discourages research and information production Insider trading discourages market participation


If information asymmetries are extreme, people simply will not trade.



If unregulated, insider trading may be detrimental to the company and its shareholders.
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Week 5

Implications: Stock Analysis


Technical Analysis - using prices and volume information to predict future prices


The McClellan Oscillator: the smoothed difference between the numbers of advances and declines:




A strong bull market: a large number of stocks making moderate upward advances in price. A weak bull market: a small number of stocks making large advances in price.



Weak-form efficiency



Fundamental Analysis - using economic and accounting information to predict stock prices


Semi-strong-form efficiency
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Week 5

Implications: Portfolio Management


It takes a lot to beat the market:
 

Money, research, education/talent, hard work, luck, etc. Unique insights



Passive investment: buy and hold diversified portfolios

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Most managers do not have unique insights. No one has unique insights every quarter and every year. It is hard to know who has unique insights next. Growth of index funds
Invest in funds, not stocks. Invest in index funds.
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Small investors should
 

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Supporting Evidence


Do prices reflect up-to-date information?
    

Event studies Abnormal return: et = rt – (a+b×rM,t) News impact: Cumulative abnormal return (CAR) = Σtet Most of the information is incorporated into price quickly There are cases of over- or under-reaction Performance measures Fund expenses Most funds underperform the market index. Good performances do not persist.
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Do professional fund managers beat the index funds?



 

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Earnings Announcements

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Performance Measures


Jensen’s measure p  r  [rf  p (rM  rf )] P Sharpe’s measure Sp  Treynor’s Measure r  rf p p





Tp 


rp  rf p

P  TM  P

Appraisal (or information) ratio = P/(eP)
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Fund Performance
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On average, over 70% of mutual funds underperform the market index. Cumby and Glen (1990, JF) find that international mutual funds may outperform the domestic market index, but not an international index. Blake, Elton, and Gruber (1993, JB) find that bond funds generally underperform the bond indices, and there is a direct relationship between the size of the underperformance and the expense ratio. Brown and Goetzmann (1995, JF) find that bad performances persist and good performances do not.
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Survivorship Bias


“If you consider at all the mutual funds in today’s WSJ, and examine their performance over the past 10 years, you’ll see that on average they had superior returns.”
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The funds in today’s WSJ are the survivors If we look at all the mutual funds that were in existence 10 years ago, there will be some who (by stupidity or bad luck) compiled bad records The poor performers went out of business (and so they don’t enter into our study)

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“Star” Performers
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Peter Lynch, manager of the Magellan Fund, beat S&P500 11 out of 13 years from 1977 to 1989 Between 79-89, Magellan returned 28% per year, vs. 17.5% for the S&P500 The high mean and low variance make the performance highly statistically significant

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Next Star?


Manager characteristics predict future performance:
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Younger managers do better Managers with an MBA do better Undergraduate institution matters Higher composite SAT score managers do better



One cannot identify the good active managers exante

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Barriers to the EMH


Limits to arbitrage
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Model risk Noise-trader risk Implementation costs Short-term memory bias, representativeness, anchoring, mental shortcuts, mental accounting, framing, overconfidence, regret avoidance Evidence: DeBondt and Thaler (1987, JF), Odean (1998, JF), Nofsinger and Sias (1999, JF), Barber and Odean (1999, FAJ; 2000, JF; 2001, QJE), etc.



Behavioural biases




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Anomalies


January effect (turn-of –the-year effect)


Small stocks outperform large stocks by 3% and ¾ of this out-performance comes in first 5 trading days in January
Large returns on the last trading day Large negative returns on Mondays

  

End-of-the month effect


Weekend effect (day-of-the week effect)


Time-of-day effect


Price rises at the beginning (first 45 minutes) and end (last 15minutes) of the trading day
Price rises on the trading day before a holiday
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Holiday effect


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Anomalies
      




Size effect (small firm effect) Low beta firm effect Neglected firm effect Book-to-market effect Price-to-earnings effect Dividend yield effect Short-term price reversals Intermediate-term price momentum Long-term price reversals

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Market Efficiency: A Paradox
 

Is it possible to have a fully efficient market where all information is correctly reflected in price? What is the implication of full information efficiency?




No research, no analysts, no MCom program Then how do prices incorporate new information?



A balance between costs and benefits?

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Summary
Efficient market hypothesis
 

Implications Supporting evidence






Barriers to the EMH Anomalies Impossibility of fully efficient markets

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