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Andrew J. Patton

Andrew J. Patton

D-Index & Metrics

Economics and Finance

D-Index
52
Citations
17781
World Ranking
1232
National Ranking
741

Overview

Andrew J. Patton is affiliated with Duke University in the United States. Their primary research contributions lie within the fields of economics, econometrics, and finance, with a focus on finance and economics subfields.

The scientist's work concentrates on topics such as:

  • Financial Risk and Volatility Modeling
  • Monetary Policy and Economic Impact
  • Financial Markets and Investment Strategies
  • Complex Systems and Time Series Analysis
  • Market Dynamics and Volatility
  • Stochastic processes and financial applications
  • Stock Market Forecasting Methods

Andrew J. Patton has contributed to multiple scholarly journals, frequently publishing in venues including:

  • SSRN Electronic Journal
  • Journal of Econometrics
  • Finance and Economics Discussion Series
  • Journal of Business and Economic Statistics
  • Journal of Financial Economics

Their recent papers include:

  • What you see is not what you get: The costs of trading market anomalies, 2020, Journal of Financial Economics
  • Risk Price Variation: The Missing Half of Empirical Asset Pricing, 2022, Review of Financial Studies

Andrew J. Patton has also collaborated extensively with other researchers. Frequent co-authors include:

  • Tim Bollerslev
  • Dong Hwan Oh
  • Rogier Quaedvlieg
  • Brian Weller
  • Haozhe Zhang

Their collaborative engagements reflect interests closely related to econometrics and financial econometrics, reinforcing their contributions to the understanding of market dynamics and risk factors in financial contexts.

Best Publications

  • MODELLING ASYMMETRIC EXCHANGE RATE DEPENDENCE

    Andrew J. Patton

  • Volatility forecast comparison using imperfect volatility proxies

    Andrew J. Patton;Andrew J. Patton

  • What good is a volatility model

    R.F. Engle;A.J. Patton

  • On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation

    Andrew J. Patton

  • Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility

    Andrew J. Patton;Kevin Sheppard

  • A review of copula models for economic time series

    Andrew J. Patton

  • Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes

    Lily Y. Liu;Andrew J. Patton;Kevin Sheppard

  • Estimation of multivariate models for time series of possibly different lengths

    Andrew J. Patton

  • Exploiting the errors: A simple approach for improved volatility forecasting

    Tim Bollerslev;Andrew J. Patton;Andrew J. Patton;Rogier Quaedvlieg

  • Copula-Based Models for Financial Time Series

    Andrew J. Patton

  • Correction to “Automatic Block-Length Selection for the Dependent Bootstrap” by D. Politis and H. White

    Andrew Patton;Dimitris N. Politis;Halbert White

  • Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion

    Andrew J. Patton;Allan Timmermann

  • Copula Methods for Forecasting Multivariate Time Series

    Andrew Patton

  • Time-Varying Systemic Risk: Evidence From a Dynamic Copula Model of CDS Spreads

    Dong Hwan Oh;Andrew J. Patton

  • Monotonicity in asset returns: New tests with applications to the term structure, the CAPM, and portfolio sorts

    Andrew J. Patton;Allan Timmermann

  • Modelling Dependence in High Dimensions with Factor Copulas

    Dong Hwan Oh;Andrew J. Patton

  • Does Beta Move with News? Firm-Specific Information Flows and Learning about Profitability

    Andrew J. Patton;Michela Verardo

  • Dynamic semiparametric models for expected shortfall (and Value-at-Risk)

    Andrew J. Patton;Johanna F. Ziegel;Rui Chen

  • Multivariate GARCH Modeling of Exchange Rate Volatility Transmission in the European Monetary System

    Colm Kearney;Andrew J. Patton

  • Evaluating Volatility and Correlation Forecasts

    Andrew J. Patton;Kevin Sheppard

  • On the out-of-sample importance of skewness and asymetric dependence for asset allocation

    Andrew Patton

  • (IAM Series No 001) On the Out-Of-Sample Importance of Skewness and Asymetric Dependence for Asset Allocation

    Andrew Patton

Frequent Co-Authors

Allan Timmermann
Allan Timmermann University of California, San Diego
Tarun Ramadorai
Tarun Ramadorai Imperial College London
Tim Bollerslev
Tim Bollerslev Duke University
Robert F. Engle
Robert F. Engle New York University
Clive W. J. Granger
Clive W. J. Granger University of California, San Diego
Timo Teräsvirta
Timo Teräsvirta Aarhus University
Halbert White
Halbert White University of California, San Diego

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