Spectral Based Testing of the Martingale Hypothesis / Steven N. Durlauf.

By:

Durlauf, Steven N

Contributor(s):

National Bureau of Economic Research

Material type: Text

TextSeries: Technical Working Paper Series (National Bureau of Economic Research) ; no. t0090.Publication details: Cambridge, Mass. National Bureau of Economic Research 1992.Description: 1 online resource: illustrations (black and white)Online resources:

Available additional physical forms:

Hardcopy version available to institutional subscribers

Abstract: This paper proposes a method of testing whether a time series is a martingale. The procedure develops an asymptotic theory for the shape of the spectral distribution function of the first differences. Under the null hypothesis, this shape should be a diagonal line. several tests are developed which determine whether the deviation of the sample spectral distribution function from a diagonal line, when treated as an element of a function space, is too erratic to be attributable to sampling error. These tests are consistent against all moving average alternatives. The testing procedure possesses the additional advantage that it eliminates discretion in choosing a particular H[sub 1] by the researcher and therefore guards against data mining, The tests may further be adjusted to analyze subsets of frequencies in isolation, which can enhance power against particular alternatives. Application of the test to stock prices finds some evidence against the random walk theory.

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Item type	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Working Paper	Biblioteca Digital	Colección NBER	nber t0090 (Browse shelf(Opens below))	Not For Loan

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Previous	nber t0087 Simulated Moments Estimation of Markov Models of Asset Prices /	nber t0088 Does Correcting for Heteroskedasticity Help? /	nber t0089 Implications of Security Market Data for Models of Dynamic Economies /	nber t0090 Spectral Based Testing of the Martingale Hypothesis /	nber t0091 Testing For Common Features /	nber t0092 Testing The Autocorrelation Structure of Disturbances in Ordinary Least Squares and Instrumental Variables Regressions /	nber t0093 Sorting Out the Differences Between Signaling and Screening Models /	Next

April 1992.

This paper proposes a method of testing whether a time series is a martingale. The procedure develops an asymptotic theory for the shape of the spectral distribution function of the first differences. Under the null hypothesis, this shape should be a diagonal line. several tests are developed which determine whether the deviation of the sample spectral distribution function from a diagonal line, when treated as an element of a function space, is too erratic to be attributable to sampling error. These tests are consistent against all moving average alternatives. The testing procedure possesses the additional advantage that it eliminates discretion in choosing a particular H[sub 1] by the researcher and therefore guards against data mining, The tests may further be adjusted to analyze subsets of frequencies in isolation, which can enhance power against particular alternatives. Application of the test to stock prices finds some evidence against the random walk theory.