Andrew J. Patton

Duke University

United States

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Andrew J. Patton created these companion sites

Monotonicity in Asset Returns: New Tests with Applications to the Term Structure, the CAPM, and Portfolio Sorts
Abstract
Many theories in finance imply monotonic patterns in expected returns and other financial variables. The liquidity preference hypothesis predicts higher expected returns for bonds with longer times to maturity; the Capital Asset Pricing Model(CAPM)implies higher expected returns for stocks with higher betas; and standard asset pricing models imply that the pricing kernel is declining in market returns. The full set of implications of monotonicity is generally not exploited in empirical work, however. This paper proposes new and simple ways to test for monotonicity in financial variables and compares the proposed tests with extant alternatives such as t-tests, Bonferroni bounds, and multivariate inequality tests through empirical applications and simulations.
Patton, J. A., and A. Timmermann, "Monotonicity in Asset Returns: New Tests with Applications to the Term Structure, the CAPM, and Portfolio Sorts", Journal of Financial Economics, 98, 605-625.
Authors: Patton
Timmermann
Coders: Patton
Timmermann
Last update
11/17/2012
Ranking
63
Runs
19
Visits
116
Copula-Based Models for Financial Time Series
Abstract
This paper presents an overview of the literature on applications of copulas in the modelling of financial time series. Copulas have been used both in multivariate time series analysis, where they are used to charaterise the (conditional) cross-sectional dependence between individual time series, and in univariate time series analysis, where they are used to characterise the dependence between a sequence of observations of a scalar time series process. The paper includes a broad, brief, review of the many applications of copulas in finance and economics.
Patton, J. A., "Copula-Based Models for Financial Time Series", Handbook of Financial Time Series, Springer Verlag, -.
Authors: Patton
Coders: Patton
Last update
10/08/2012
Ranking
3
Runs
38
Visits
572
Volatility Forecast Comparison Using Imperfect Volatility Proxies
Abstract
The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable outcomes in standard methods for comparing conditional variance forecasts. We motivate our study with analytical results on the distortions caused by some widely used loss functions, when used with standard volatility proxies such as squared returns, the intra-daily range or realised volatility. We then derive necessary and sufficient conditions on the functional form of the loss function for the ranking of competing volatility forecasts to be robust to the presence of noise in the volatility proxy, and derive some useful special cases of this class of “robust” loss functions. The methods are illustrated with an application to the volatility of returns on IBM over the period 1993 to 2003.
Patton, J. A., "Volatility Forecast Comparison Using Imperfect Volatility Proxies", Journal of Econometrics, 160, 246-256.
Authors: Patton
Coders: Patton
Last update
11/17/2012
Ranking
1
Runs
90
Visits
993