Modeling Online Art Auction Dynamics Using Functional Data Analysis

Statistical Science, Vol. 21, No. 2, pp. 179-193, May 2006

Posted: 6 Jan 2020

See all articles by Srinivas K. Reddy

Srinivas K. Reddy

University of Georgia - Department of Marketing

Mayukh Dass

Texas Tech University - Area of Marketing

Abstract

In this paper, we examine the price dynamics of online art auctions of Modern Indian Art using Functional Data Analysis. The purpose here is not just to understand what determines the final prices of art objects but also the price movement during the entire auction. We identify several factors such as artist characteristics (established or emerging artist; prior sales history), art characteristics (size; painting medium - canvas or paper), competition characteristics (current no. of bidders; current no. of bids) and auction design characteristics (opening bid; position of the lot in the auction) that explain the dynamics of price movement in an online art auction. We find that the effects on price vary over the duration of the auction, with some of these effects being stronger at the beginning of the auction (such as the opening bid and historical prices realized). In some cases, the rate of change in prices (velocity) increases at the end of the auction (for canvas paintings and paintings by established artists). Our analysis suggests that the opening bid is positively related to online auction price levels of art at the beginning of the auction but its effect declines towards the end of the auction. The order in which the lots appear in an art auction is negatively related to the current price level with this relationship decreasing towards the end of the auction. This implies that lots that appear earlier have higher current prices during the early part of the auction but that effect diminishes by the end of the auction. Established artists show a positive relationship with the price level at the beginning of the auction. Reputation or popularity of the artists and their investment potential as assessed by previous history of sales are positively related to the price levels at the beginning of the auction. The medium (canvas or paper) of the painting did not show any relationship with art auction price levels, but the size of the painting was negatively related to the current price during the early part of the auction. Important implications for auction design are drawn from the analysis.

Keywords: Functional Data Analysis, Online Auctions, Hedonic Products, Modern Indian Art

Suggested Citation

Reddy, Srinivas K. and Dass, Mayukh, Modeling Online Art Auction Dynamics Using Functional Data Analysis. Statistical Science, Vol. 21, No. 2, pp. 179-193, May 2006, Available at SSRN: https://ssrn.com/abstract=948991

Srinivas K. Reddy

University of Georgia - Department of Marketing ( email )

GA
United States

Mayukh Dass (Contact Author)

Texas Tech University - Area of Marketing ( email )

Box-42101
Rawls College of Business
Lubbock, TX Lubbock 79409
United States
806 742 1924 (Phone)

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

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