This thesis aims to identify which economic indicators best foreshadow movements in the global art market so as to provide timely counsel to investors looking to enter or exit the market. This research compares a series of economic indicators - Gross Domestic Product (GOP), stock market performance, interest rates, inf1ation, and residential housing to identify potential correlations with the Mei Moses All Art Index, the most widely cited gauge of art market performance. Linear regression models are applied across two historic data sets of economic indicators, yielding data from Japan during 1984-1995 and from China over the 2000-2011 period. The results of regression models applied to both Japanese and Chinese data sets indicate that, of all economic indicators studied, residential housing performance demonstrates the strongest correlation to art index performance. Furthermore, residential housing data demonstrate significant statistical worth as a predictor of future art market outcomes. These conclusions lead to this study'S recommendation that art investors looking to act in the near term of 20 12-20 13 would be well advised to take cues from the Chinese housing market prior to making a transaction.