Eric Ghysels - Working Papers

WORKING PAPERS

You will find some of my recent research - working papers and published - arranged by themes. Links to older papers appear at the bottom of the page.

New working papers (across my different areas of research)

Conditional Skewness of Stock Market Returns in Developed and Emerging Markets and its Economic Fundamentals, (with Alberto Plazzi and Rossen Valkanov) (New Version)

The Low-Frequency Impact of Daily Monetary Policy Shocks, (with Neville Francis and Michael Owyang) (New Version)

Stigma in Financial Markets - Evidence from Liquidity Auctions and Discount Window Borrowing During the Crisis , (with Olivier Armantier, Asani Sarkar and Jeffrey Shrader)

Some Useful Densities for Risk Management and their Properties (with Fangfang Wang)

HYBRID-GARCH: A Generic Class of Models for Volatility Predictions using Mixed Frequency Data (Long Version), (with Xilong Chen and Fangfang Wang)

HYBRID-GARCH A Generic Class of Models for Volatility Predictions using Mixed Frequency Data (Short Version), (with Xilong Chen and Fangfang Wang)

Forecasting Volatility with MIDAS, (with Ross Valkanov) To appear in Volatility Models and their Applications, Bauwens, Haffner and Laurent (eds.), Wiley (New Version)

Should macroeconomic forecasters use daily financial data and how?, (with Elena Andreou and Andros Kourtellos) (New Version)

Technical Appendix: Should macroeconomic forecasters use daily financial data and how?, (with Elena Andreou and Andros Kourtellos) (New)

State Space Models and MIDAS Regressions, (with Jennie Bai and Jonathan Wright) Econometric Reviews (forthcoming)

In-sample Asymptotics and Across-sample Efficiency Gains for High Frequency Data Statistics, (with Per Mykland and Eric Renault)

Econometric Analysis of Volatility Component Models (with Fangfang Wang)

Ex Ante Skewness and Expected Stock Returns, (with Jennifer Conrad and Bob Dittmar)

Momentum Cycles and Limits to Arbitrage - Evidence from Victorian England and Post-Depression Us Stock Markets, (with Ben Chabot and Ravi Jagannathan)

Working, forthcoming and published papers by area of research

Mixed Data Sampling (MIDAS)

MIDAS entry to Wikipedia (Entry written by Dirk Nachbar)

Regression models involving data sampled at different frequencies are of general interest. In the document link below we describe Matlab code for running such regressions based on a framework put forward in recent work by Ghysels, Santa-Clara, and Valkanov (2002), Ghysels, Santa- Clara, and Valkanov (2006) and Andreou, Ghysels, and Kourtellos (2008a) using so called MIDAS, meaning Mi(xed) Da(ta) S(ampling), regressions.

Matlab Toolbox for Mixed Sampling Frequency Data Analysis us\ ing MIDAS Regression Models

The code can be obtained by contacting me, email: eghysels@unc.edu

Working papers

Conditional Skewness of Stock Market Returns in Developed and Emerging Markets and its Economic Fundamentals, (with Alberto Plazzi and Rossen Valkanov) (New Version)

The Low-Frequency Impact of Daily Monetary Policy Shocks, (with Neville Francis and Michael Owyang) (New Version)

HYBRID-GARCH: A Generic Class of Models for Volatility Predictions using Mixed Frequency Data (Long Version), (with Xilong Chen and Fangfang Wang)

HYBRID-GARCH A Generic Class of Models for Volatility Predictions using Mixed Frequency Data (Short Version), (with Xilong Chen and Fangfang Wang)

Should macroeconomic forecasters use daily financial data and how?, (with Elena Andreou and Andros Kourtellos) (New Version)

Technical Appendix: Should macroeconomic forecasters use daily financial data and how?, (with Elena Andreou and Andros Kourtellos) (New)

Multi-Period Forecasts of Volatility: Direct, Iterated, and Mixed-Data Approaches (with Antonio Rubia and Rossen Valkanov)

On the Economic Sources of Stock Market Volatility (with Robert Engle and Bumjean Sohn)

Econometric Analysis of Volatility Component Models (with Fangfang Wang)

Forthcoming papers

State Space Models and MIDAS Regressions, (with Jennie Bai and Jonathan Wright) Econometric Reviews (forthcoming)

Forecasting Volatility with MIDAS, (with Ross Valkanov) To appear in Volatility Models and their Applications, Bauwens, Haffner and Laurent (eds.), Wiley (New Version)

Forecasting with mixed-frequency data, (with Elena Andreou and Andros Kourtellos) - Chapter prepared for Oxford Handbook on Economic Forecasting edited by Michael P. Clements and David F. Hendry

Published papers

There is a Risk-return Trade-off After All (with P. Santa Clara and R. Valkanov) Journal of Financial Economics, 76, 509-548.

Predicting volatility: How to get most out of returns data sampled at different frequencies (with P. Santa-Clara and R. Valkanov) Journal of Econometrics 131, 59-95

MIDAS Regressions: Further Results and New Directions (with A. Sinko and R. Valkanov) Econometric Reviews, 26, 53-90

Why Do Absolute Returns Predict Volatility So Well? (with Lars Forsberg) Journal of Financial Econometrics, 5, 31-67

Valuation in the US Commercial Real Estate (with A. Plazzi and Ross Valkanov) European Financial Management, 13, 472-497.

The Impact of Risk and Uncertainty on Expected Returns (with E. Anderson and J. Juergens) Journal of Financial Economics, 94, 233-263.

Forecasting Professional Forecasters (with J. Wright) Journal of Business and Economic Statistics, 27, 504-516.

Which Power Variation Predicts Volatility Well? (with Bumjean Sohn) Journal of Empirical Finance, 16, 686-700

A Component Model of Dynamic Correlations (with Riccardo Colacito and Robert Engle) Journal of Econometrics, 164, 45-59

News - Good or Bad - and its impact on volatility predictions over multiple horizons (with Xilong Chen) Review of Financial Studies, 24, 46-81

Regression Models With Mixed Sampling Frequencies (with Elena Andreou and Andros Kourtellos) Journal of Econometrics, 158, 246-261.

Volatility Forecasting and Microstructure Noise (with Arthur Sinko) Detailed Appendix: Forecasting and Microstructure Noise Journal of Econometrics, 160, 257-271.

HYBRID GARCH Models and Intra-Daily Return Periodicity, (with Xilong Chen and Fangfang Wang) Journal of Time Series Econometrics, 3, 1, Article 11

Research on Volatility

Working papers

HYBRID-GARCH: A Generic Class of Models for Volatility Predictions using Mixed Frequency Data (Long Version), (with Xilong Chen and Fangfang Wang)

HYBRID-GARCH A Generic Class of Models for Volatility Predictions using Mixed Frequency Data (Short Version), (with Xilong Chen and Fangfang Wang)

Econometric Analysis of Volatility Component Models (with Fangfang Wang)

In-sample Asymptotics and Across-sample Efficiency Gains for High Frequency Data Statistics, (with Per Mykland and Eric Renault)

Multi-Period Forecasts of Volatility: Direct, Iterated, and Mixed-Data Approaches (with Antonio Rubia and Rossen Valkanov)

On the Economic Sources of Stock Market Volatility (with Robert Engle and Bumjean Sohn)

Forthcoming papers

Forecasting Volatility with MIDAS, (with Ross Valkanov) To appear in Volatility Models and their Applications, Bauwens, Haffner and Laurent (eds.), Wiley (New Version)

Published papers

There is a Risk-return Trade-off After All (with P. Santa Clara and R. Valkanov) Journal of Financial Economics, 76, 509-548.

Predicting volatility: How to get most out of returns data sampled at different frequencies (with P. Santa-Clara and R. Valkanov) Journal of Econometrics 131, 59-95

Why Do Absolute Returns Predict Volatility So Well? (with Lars Forsberg) Journal of Financial Econometrics, 5, 31-67

The Impact of Risk and Uncertainty on Expected Returns (with E. Anderson and J. Juergens) Journal of Financial Economics, 94, 233-263.

Which Power Variation Predicts Volatility Well? (with Bumjean Sohn) Journal of Empirical Finance, 16, 686-700

A Component Model of Dynamic Correlations (with Riccardo Colacito and Robert Engle) Journal of Econometrics, 164, 45-59

News - Good or Bad - and its impact on volatility predictions over multiple horizons (with Xilong Chen) Review of Financial Studies, 24, 46-81

Volatility Forecasting and Microstructure Noise (with Arthur Sinko) Detailed Appendix: Forecasting and Microstructure Noise Journal of Econometrics, 160, 257-271.

HYBRID GARCH Models and Intra-Daily Return Periodicity, (with Xilong Chen and Fangfang Wang) Journal of Time Series Econometrics, 3, 1, Article 11

Quality Control for Risk Management

Working papers

Some Useful Densities for Risk Management and their Properties (with Fangfang Wang)

Forthcoming papers

Published papers

Detecting multiple breaks in financial market volatility dynamics (with E. Andreou) Journal of Applied Econometrics, 17, 579-600.

Tests for breaks in the conditional co-movements of asset returns (with E. Andreou) Statistica Sinica, 13, 1045-1074.

The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests (with E. Andreou) Journal of Financial Econometrics, 2, 290-318.

Monitoring Distortions in Financial Markets (with E. Andreou) Journal of Econometrics, 135, 77-124.

Quality Control for Structural Credit Risk (with E. Andreou) Journal of Econometrics, 146, 364-375.

Structural Breaks in Financial Time Series (with E. Andreou) Handbook of Financial Time Series, Torben G. Andersen, Richard A. Davis, Jens-Peter Kreiss, Thomas Mikosch (eds), 839-870.

Heterogeneity, Model Uncertainty and Asset Pricing

Working papers

On Portfolio Separation Theorems with Heterogeneous Beliefs and Attitudes towards Risk (with F. Chabi-Yo and E. Renault)

Published/forthcoming papers

Do Heterogeneous Beliefs Matter for Asset Pricing? (with E. Anderson and J. Juergens) Review of Financial Studies, 18, 875-924.

The Impact of Risk and Uncertainty on Expected Returns (with E. Anderson and J. Juergens) Journal of Financial Economics, 94, 233-263.

Skewness

Conditional Skewness of Stock Market Returns in Developed and Emerging Markets and its Economic Fundamentals, (with Alberto Plazzi and Rossen Valkanov) (New Version)

Ex Ante Skewness and Expected Stock Returns, (with Jennifer Conrad and Bob Dittmar)

On Portfolio Separation Theorems with Heterogeneous Beliefs and Attitudes towards Risk (with F. Chabi-Yo and E. Renault)

Financial History

Price Momentum in Stocks: Using Data from the Victorian Age to Evaluate Competing Theories, (with Ben Chabot and Ravi Jagannathan)