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Optimal Portfolio Choice with Predictability in House Prices and Transaction Costs

Author

Listed:
  • Stefano Corradin
  • José L. Fillat
  • Carles Vergara-Alert

Abstract

We develop and solve a model of optimal portfolio choice with transaction costs and predictability in house prices. We model house prices using a process with a time-varying expected growth rate. Housing adjustments are infrequent and characterized by both the wealth-to-housing ratio and the expected growth in house prices. We find that the housing portfolio share immediately after moving to a more valuable house is higher during periods of high expected growth in house prices. We also find that the share of wealth invested in risky assets is lower during periods of high expected growth in house prices. Finally, the decrease in risky portfolio holdings for households moving to a more valuable house is greater in high-growth periods. These findings are robust to tests using household-level data from the Panel Study of Income Dynamics (PSID) and Survey of Income and Program Participation (SIPP) surveys. The coefficients obtained using model-simulated data are consistent with those obtained in the empirical tests.

Suggested Citation

  • Stefano Corradin & José L. Fillat & Carles Vergara-Alert, 2014. "Optimal Portfolio Choice with Predictability in House Prices and Transaction Costs," The Review of Financial Studies, Society for Financial Studies, vol. 27(3), pages 823-880.
    • Handle: RePEc:oup:rfinst:v:27:y:2014:i:3:p:823-880.
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    File URL: http://hdl.handle.net/10.1093/rfs/hht062
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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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