Alternative estimates of the presidential premium
AbstractSince the early 1980s much research, including the most recent contribution of Santa-Clara and Valkanov (2003), has concluded that there is a stable, robust and significant relationship between Democratic presidential administrations and robust stock returns. Moreover, the difference in returns does not appear to be accompanied by any significant differences in risk across the presidential cycle. These conclusions are largely based on OLS estimates of the difference in returns across the presidential cycle. We re-examine this issue using more efficient estimators of the presidential premium. Specifically, we exploit the considerable and persistent heteroskedasticity in stock returns to construct more efficient weighted least squares (WLS) and generalized autoregressive conditional heteroskedasticity (GARCH) estimators of the difference in expected excess stock returns across the presidential cycle. Our findings provide considerable contrast to the findings of previous research. Across the different WLS and GARCH estimates we find that the point estimates are considerably smaller than the OLS estimates and fluctuate considerably across different sub samples. We show that the large difference between the WLS, GARCH and OLS estimates is driven by differing stock market performance during very volatile market environments. During periods of elevated market volatility, excess stock returns have been markedly higher under Democratic than Republican administrations. Accordingly, the WLS and GARCH estimators are less sensitive to these episodes than the OLS estimator. Ultimately, these results are consistent with the conclusion that neither risk nor return varies significantly across the presidential cycle.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Board of Governors of the Federal Reserve System (U.S.) in its series Finance and Economics Discussion Series with number 2004-69.
Date of creation: 2004
Date of revision:
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002.
"Parametric and Nonparametric Volatility Measurement,"
NBER Technical Working Papers
0279, National Bureau of Economic Research, Inc.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," Center for Financial Institutions Working Papers 02-27, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Hentschel, Ludger & Campbell, John, 1992.
"No News is Good News: An Asymmetric Model of Changing Volatility in Stock Returns,"
3220232, Harvard University Department of Economics.
- Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
- John Y. Campbell & Ludger Hentschel, 1991. "No News is Good News: An Asymmetric Model of Changing Volatility in Stock Returns," NBER Working Papers 3742, National Bureau of Economic Research, Inc.
- Neil Shephard, 2005.
Economics Series Working Papers
2005-W17, University of Oxford, Department of Economics.
- Pedro Santa-Clara & Rossen Valkanov, 2003. "The Presidential Puzzle: Political Cycles and the Stock Market," Journal of Finance, American Finance Association, vol. 58(5), pages 1841-1872, October.
- Shleifer, Andrei, 1986. " Do Demand Curves for Stocks Slope Down?," Journal of Finance, American Finance Association, vol. 41(3), pages 579-90, July.
- Whitney K. Newey & Kenneth D. West, 1986.
"A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix,"
NBER Technical Working Papers
0055, National Bureau of Economic Research, Inc.
- Newey, Whitney K & West, Kenneth D, 1987. "A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix," Econometrica, Econometric Society, vol. 55(3), pages 703-08, May.
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
- Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
- Pagan, A.R. & Schwert, G.W., 1989.
"Alternative Models For Conditional Stock Volatility,"
89-02, Rochester, Business - General.
- Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
- Adrian R. Pagan & G. William Schwert, 1990. "Alternative Models For Conditional Stock Volatility," NBER Working Papers 2955, National Bureau of Economic Research, Inc.
- Hsieh, David A & Miller, Merton H, 1990. " Margin Regulation and Stock Market Volatility," Journal of Finance, American Finance Association, vol. 45(1), pages 3-29, March.
- G. William Schwert, 1990.
"Why Does Stock Market Volatility Change Over Time?,"
NBER Working Papers
2798, National Bureau of Economic Research, Inc.
- Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-53, December.
- Tim Bollerslev & Jeffrey M. Wooldridge, 1988. "Quasi-Maximum Likelihood Estimation of Dynamic Models with Time-Varying Covariances," Working papers 505, Massachusetts Institute of Technology (MIT), Department of Economics.
- French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
- Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range-Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, 06.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Kris Vajs) The email address of this maintainer does not seem to be valid anymore. Please ask Kris Vajs to update the entry or send us the correct address.
If references are entirely missing, you can add them using this form.