The Role of Partisan Conflict in Forecasting the U.S. Equity Premium: A Nonparametric Approach
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References listed on IDEAS
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CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Rangan Gupta & Christian Pierdzioch & Refk Selmi & Mark E. Wohar, 2017. "Does Partisan Conflict Predict a Reduction in US Stock Market (Realized) Volatility? Evidence from a Quantile-on-Quantile Regression Model," Working Papers 201744, University of Pretoria, Department of Economics.
More about this item
Keywords: Equity Premium; Partisan Conflict Index; Linear and Nonparametric Predictive Regressions;
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G1 - Financial Economics - - General Financial Markets
- G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2016-12-11 (All new papers)
- NEP-FOR-2016-12-11 (Forecasting)
- NEP-ORE-2016-12-11 (Operations Research)
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