Housing Markets: Auctions, Microstructure Noise, and Weekly Patterns

71 Pages Posted: 8 Jun 2017 Last revised: 21 Aug 2023

See all articles by Alina Arefeva

Alina Arefeva

UW Madison - Wisconsin School Business

Multiple version iconThere are 2 versions of this paper

Date Written: January 15, 2020


This paper studies volatility in the housing markets by developing dynamic
search and matching models with bidding wars, or auctions. The models’ moments
are aggregated to the statistics on the offer acceptance dates and the closing dates
to emphasize the differences between these statistics in the data. I find that up to
70% of the volatility of monthly home sales and listings in the Los Angeles metro
area stems from the intra-week patterns in the data and the microstructure noise
in the models. The remaining volatility can be generated by adding exogenous
shocks to the models.

Keywords: housing, real estate, volatility, microstructure, search and matching, pricing, liquidity, Nash bargaining, auctions, bidding wars

JEL Classification: E30, C78, D44, R21, E44, R31, D83

Suggested Citation

Arefeva, Alina, Housing Markets: Auctions, Microstructure Noise, and Weekly Patterns (January 15, 2020). Available at SSRN: https://ssrn.com/abstract=2980095 or http://dx.doi.org/10.2139/ssrn.2980095

Alina Arefeva (Contact Author)

UW Madison - Wisconsin School Business ( email )

975 University Avenue
Madison, WI 53706
United States

HOME PAGE: http://www.aarefeva.com

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