Auctions, Microstructure Noise, and Weekly Patterns in Housing Markets

69 Pages Posted: 8 Jun 2017 Last revised: 27 Apr 2022

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

Abstract

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 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 sales and listings in the Los Angeles metro area stems from the intra-week patterns in the data and endogenous dynamics in the models with the microstructure noise. The remaining volatility can be generated from 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, Auctions, Microstructure Noise, and Weekly Patterns in Housing Markets (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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