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This thesis examines the dynamic interplay between global economic variables and art market performance, focusing on how factors such as global GDP, inflation rates, auction sales data, and the wealth of the top 50 billionaires influence pricing and managerial decisions in the art auction industry. Utilizing data from Christie's and Sotheby's auctions held in key global locations (Hong Kong, London, Paris, and New York) from 2020 to 2022, this research employs descriptive and regression analyses to explore these relationships.

The study integrates global GDP data sourced from the World Bank, annual inflation and consumer price data, and the wealth data of the top 50 billionaires from Forbes. The findings reveal that economic downturns, such as those experienced during the COVID-19 pandemic, significantly impact auction sales and pricing strategies. The economic conditions of different phases, including Pre-COVID, the COVID-19 Impact period, and the Recovery Phase, are examined to illustrate their effects on the art markets in Hong Kong, the United States, the United Kingdom, and France.
A structured analysis of this data was conducted to derive insights into how these economic factors influence art market dynamics. The analysis highlights that GDP contractions during the pandemic significantly affected art market performance, while the post-pandemic recovery saw a resurgence in auction sales and market confidence, driven by vaccination efforts and fiscal stimuli.

This research also proposes a decision-making model for art auction managers, integrating insights from global economic trends, auction sales data, and market dynamics. This model aims to enhance the accuracy of artwork price estimations and optimize the timing of auctions to maximize value for stakeholders. By providing a comprehensive understanding of the economic influences on the art market, this thesis contributes to more informed managerial strategies and better market performance amidst global economic fluctuations.

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