Does Partisan Conflict Predict a Reduction in US Stock Market (Realized) Volatility? Evidence from a Quantile-on-Quantile Regression Model
Download full text from publisherTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
References listed on IDEAS
- Cheng, Chak Hung Jack & Hankins, William B. & Chiu, Ching-Wai (Jeremy), 2016. "Does US partisan conflict matter for the Euro area?," Economics Letters, Elsevier, vol. 138(C), pages 64-67.
- Lubos Pástor & Pietro Veronesi, 2012.
"Uncertainty about Government Policy and Stock Prices,"
Journal of Finance,
American Finance Association, vol. 67(4), pages 1219-1264, August.
- Lubos Pastor & Pietro Veronesi, 2010. "Uncertainty about Government Policy and Stock Prices," Working Papers 2010-008, Becker Friedman Institute for Research In Economics.
- Pástor, Luboš & Veronesi, Pietro, 2010. "Uncertainty about Government Policy and Stock Prices," CEPR Discussion Papers 7897, C.E.P.R. Discussion Papers.
- Pietro Veronesi & Lubos Pastor, 2011. "Uncertainty about Government Policy and Stock Prices," 2011 Meeting Papers 86, Society for Economic Dynamics.
- Lubos Pastor & Pietro Veronesi, 2010. "Uncertainty about Government Policy and Stock Prices," NBER Working Papers 16128, National Bureau of Economic Research, Inc.
- repec:eee:finlet:v:25:y:2018:i:c:p:131-136 is not listed on IDEAS
- Azzimonti, Marina, 2018. "Partisan conflict and private investment," Journal of Monetary Economics, Elsevier, vol. 93(C), pages 114-131.
- Ma, Lingjie & Koenker, Roger, 2006.
"Quantile regression methods for recursive structural equation models,"
Journal of Econometrics,
Elsevier, vol. 134(2), pages 471-506, October.
- Lingjie Ma & Roger Koenker, 2004. "Quantile regression methods for recursive structural equation models," CeMMAP working papers CWP01/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Pástor, Ľuboš & Veronesi, Pietro, 2013.
"Political uncertainty and risk premia,"
Journal of Financial Economics,
Elsevier, vol. 110(3), pages 520-545.
- Lubos Pastor & Pietro Veronesi, 2011. "Political Uncertainty and Risk Premia," NBER Working Papers 17464, National Bureau of Economic Research, Inc.
- Pástor, Luboš & Veronesi, Pietro, 2011. "Political Uncertainty and Risk Premia," CEPR Discussion Papers 8601, C.E.P.R. Discussion Papers.
- Lubos Pastor & Pietro Veronesi, 2011. "Political Uncertainty and Risk Premia," Working Papers 2011-007, Becker Friedman Institute for Research In Economics.
- Dopke, Jorg & Pierdzioch, Christian, 2006.
"Politics and the stock market: Evidence from Germany,"
European Journal of Political Economy,
Elsevier, vol. 22(4), pages 925-943, December.
- Pierdzioch, Christian & Döpke, Jörg, 2004. "Politics and the Stock Market: Evidence from Germany," Kiel Working Papers 1203, Kiel Institute for the World Economy (IfW).
- Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
- 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.
- Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
- Roger Koenker & Zhijie Xiao, 2002. "Inference on the Quantile Regression Process," Econometrica, Econometric Society, vol. 70(4), pages 1583-1612, July.
- Gupta, Rangan & Mwamba, John W. Muteba & Wohar, Mark E., 2018.
"The role of partisan conflict in forecasting the U.S. equity premium: A nonparametric approach,"
Finance Research Letters,
Elsevier, vol. 25(C), pages 131-136.
- Rangan Gupta & John W. Muteba Mwamba & Mark E. Wohar, 2016. "The Role of Partisan Conflict in Forecasting the U.S. Equity Premium: A Nonparametric Approach," Working Papers 201686, University of Pretoria, Department of Economics.
- Martin T. Bohl & Jörg Döpke & Christian Pierdzioch, 2008. "Real-Time Forecasting and Political Stock Market Anomalies: Evidence for the United States," The Financial Review, Eastern Finance Association, vol. 43(3), pages 323-335, August.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Jamal Bouoiyour & Refk Selmi & Mark Wohar, 2018.
"Measuring the response of gold prices to uncertainty: An analysis beyond the mean,"
- Jamal Bouoiyour & Refk Selmi & Mark Wohar, 2018. "Measuring the response of gold prices to uncertainty: An analysis beyond the mean," Post-Print hal-01817067, HAL.
More about this item
KeywordsPartisan Conflict; Realized Volatility; Quantile Regressions;
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2017-06-18 (All new papers)
- NEP-MAC-2017-06-18 (Macroeconomics)
- NEP-ORE-2017-06-18 (Operations Research)
- NEP-RMG-2017-06-18 (Risk Management)
StatisticsAccess and download statistics
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pre:wpaper:201744. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Rangan Gupta). General contact details of provider: http://edirc.repec.org/data/decupza.html .
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.