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Empirical Financial Economics
The Efficient Markets Hypothesis Stephen J. Brown NYU Stern School of Business 2009 Merton H. Miller Doctoral Seminar
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Major developments over last 35 years
Portfolio theory
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Major developments over last 35 years
Portfolio theory Asset pricing theory
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Major developments over last 35 years
Portfolio theory Asset pricing theory Efficient Markets Hypothesis
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Major developments over last 35 years
Portfolio theory Asset pricing theory Efficient Markets Hypothesis Corporate finance
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Major developments over last 35 years
Portfolio theory Asset pricing theory Efficient Markets Hypothesis Corporate finance Derivative Securities, Fixed Income Analysis
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Major developments over last 35 years
Portfolio theory Asset pricing theory Efficient Markets Hypothesis Corporate finance Derivative Securities, Fixed Income Analysis Market Microstructure
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Major developments over last 35 years
Portfolio theory Asset pricing theory Efficient Markets Hypothesis Corporate finance Derivative Securities, Fixed Income Analysis Market Microstructure Behavioral Finance
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Efficient Markets Hypothesis
which implies the testable hypothesis ... where is part of the agent’s information set In returns: where
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Efficient Markets Hypothesis
Tests of Efficient Markets Hypothesis What is information? Does the market efficiently process information? Estimation of parameters What determines the cross section of expected returns? Does the market efficiently price risk?
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Tests of Efficient Markets Hypothesis
Weak form tests of Efficient Markets Hypothesis Example: trading rule tests Semi-strong form tests of EMH Example: Event studies Strong form tests of EMH Example: Insider trading studies (careful about conditioning!)
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Random Walk Hypothesis
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Random Walk Hypothesis
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Random Walk Hypothesis
Serial covariance tests
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Random Walk Hypothesis
Serial covariance tests:
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Random Walk Hypothesis
Serial covariance tests
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Random Walk Hypothesis
Serial covariance tests Variance Ratio tests
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Random Walk Hypothesis
Serial covariance tests Variance Ratio tests Momentum literature
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Random Walk Hypothesis
Serial covariance tests Variance Ratio tests Momentum literature
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Random Walk Hypothesis
Serial covariance tests Variance Ratio tests Momentum literature Zero investment portfolio
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Random Walk Hypothesis
Serial covariance tests Variance Ratio tests Momentum literature Assumes stationarity
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Random Walk Hypothesis
Serial covariance tests Variance Ratio tests Momentum literature Assumes stationarity
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Random Walk Hypothesis
Serial covariance tests Variance Ratio tests Momentum literature Assumes stationarity Neither necessary nor sufficient for EMH
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Trading rule tests of EMH
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Trading rule tests of EMH
Timmerman (2007) survey Naïve models using past sample means hard to beat Recent financial data is most relevant Short lived episodes of limited predictability
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Trading rule tests of EMH
Timmerman (2007) survey Naïve models using past sample means hard to beat Recent financial data is most relevant Short lived episodes of limited predictability Predictability is not profitability Necessity: Do not consider all possible patterns of returns Sufficiency: Cannot profit if all markets rise and fall together
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Trading rule tests of EMH
Timmerman (2007) survey Naïve models using past sample means hard to beat Recent financial data is most relevant Short lived episodes of limited predictability Predictability is not profitability Necessity: Do not consider all possible patterns of returns Sufficiency: Cannot profit if all markets rise and fall together How can we examine significance of trading profits?
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An important seminal reference …
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Trading Rules: Cowles 1933 Cowles, A., 1933 Can stock market forecasters forecast? Econometrica William Peter Hamilton’s Track Record Classify editorials as Sell, Hold or Buy Novel bootstrap in strategy space Return on DJI
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Factor-augmented AR logit based on prior 120 month rolling window
Trading rule predicting sign of excess return January December 2005 Trading rule value S&P500 value Factor-augmented AR logit based on prior 120 month rolling window
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Cowles Bootstrap Jan 1970-Dec 2005
Annualized excess fund return 2.203% Sharpe ratio of fund 0.063 Sharpe ratio of S&P500 0.049 Peseran & Timmermann (1992) p-value 4.83% Cowles bootstrap p-value 6.32%
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Standard Event Study approach
rt1 u01 u11 u21 … EVENT rt2 u02 u12 u22 … EVENT rt3 u03 u13 u23 … EVENT EVENT rt4 u04 u14 u24 … u05 u15 u25 … 5 10 15 20 25 30 t
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Orthogonality condition
Event studies measure the orthogonality condition using the average value of the residual across all events where is good news and is bad news If the residuals are uncorrelated, then the average residual will be asymptotically Normal with expected value equal to the orthogonality condition, provided that the event zt has no market wide impact
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Fama Fisher Jensen and Roll
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FFJR Redux
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Original FFJR results
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Asset pricing models: GMM paradigm
Match moment conditions with sample moments Test model by examining extent to which data matches moments Estimate parameters
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Example: Time varying risk premia
imply a predictable component of excess returns where the asset pricing model imposes constraint
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Estimating asset pricing models: GMM
Define residuals Residuals should not be predictable using instruments zt-1 that include the predetermined variables Xt-1 Choose parameters to minimize residual predictability
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Estimating asset pricing models: Maximum likelihood
Define residuals Choose parameters to minimize Relationship to GMM: when instruments zt include the predetermined variables Xt-1
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Conclusion Efficient Market Hypothesis is alive and well
EMH central to recent developments in empirical Finance EMH highlights importance of appropriate conditioning in empirical financial research in practical applications
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