sciresНаучные исследования экономического факультета. Электронный журналScientific Research of Faculty of Economics. Electronic Journal2078-3809Moscow State University10.38050/2078-3809-2022-14-1-40-67scires-211Research ArticleМАРКЕТИНГMARKETINGИнструменты управления ценой лотов аукционными домами на арт-рынкеFinancial returns, price determinants, and genre effects in American art investmentДурмушД. А.DurmushD. A.

Дурмуш Дерья Адильевна, бакалавр экономики,Москва

Derya A. Durmush, Bachelor of EconomicsMoscow

 

МирзоянА. Г.MirzoyanA. G.

Мирзоян Ашот Гамлетович, ассистент кафедры экономики инноваций

Москва

Ashot G. Mirzoyan, Assistant

Moscow

МГУ имени М.В. Ломоносова, Экономический факультетРоссияLomonosov Moscow State University, Faculty of EconomicsRussian Federation2022060420221414067Copyright © Дурмуш Д.А., Мирзоян А.Г., 20222022Дурмуш Д.А., Мирзоян А.Г.Durmush D.A., Mirzoyan A.G.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://scires.elpub.ru/jour/article/view/211

Рынок искусства обладает особыми характеристиками, выделяющими его среди других рынков: фиксированный объем предложения, высокая гетерогенность и низкая ликвидность товаров, высокие транзакционные издержки. Это сказывается на инструментах управления ценой, используемых основными участниками рынка. Целью данной работы является выявление ключевых инструментов, которые используются участниками рынка для оказания влияния на цену продажи картин, а также выделение устойчивых комбинаций этих инструментов. В качестве инструментов анализа используется гедонистическая регрессия, метод главных компонент и иерархическая кластеризация. На примере рынка русского искусства выявлено 4 группы аукционных домов, отличающихся набором инструментов управления ценой продажи картин.

The art market has special characteristics that distinguish it from other markets: a fixed volume of supply, high heterogeneity and low liquidity of goods, high transaction costs. This affects the price management tools used by the main market participants. The purpose of this work is to identify key tools that are used by market participants to influence the sale price of paintings, as well as to highlight stable combinat,ions of these tools. Hedonic regression, principal component analysis and hierarchical clustering are used as analysis tools. On the example of the Russian art market, 4 groups of auction houses were identified, differing in the set of tools for managing the sale price of paintings.

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The authors declare that there are no conflicts of interest present.