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Daily House Price Indices: Construction, Modeling, and Longer-Run Predictions

Author

Listed:
  • Tim Bollerslev

    (Duke University, NBER and CREATES)

  • Andrew J. Patton

    (Duke University, NBER and CREATES)

  • Wenjing Wang

    (Moody’s Analytics, Inc.)

Abstract

We construct daily house price indices for ten major U.S. metropolitan areas. Our calculations are based on a comprehensive database of several million residential property transactions and a standard repeat-sales method that closely mimics the methodology of the popular monthly Case-Shiller house price indices. Our new daily house price indices exhibit dynamic features similar to those of other daily asset prices, with mild autocorrelation and strong conditional heteroskedasticity of the corresponding daily returns. A relatively simple multivariate time series model for the daily house price index returns, explicitly allowing for commonalities across cities and GARCH effects, produces forecasts of monthly house price changes that are superior to various alternative forecast procedures based on lower frequency data.

Suggested Citation

  • Tim Bollerslev & Andrew J. Patton & Wenjing Wang, 2015. "Daily House Price Indices: Construction, Modeling, and Longer-Run Predictions," CREATES Research Papers 2015-02, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2015-02
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Data aggregation; Real estate prices; Forecasting; Time-varying volatility;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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