How accurate are auction house estimates? A market-wide assessment
Auction house estimates occupy a central role in structuring expectations, anchoring pricing, and signalling value within the art market. Yet their accuracy, defined here as the ability to predict realised prices within a stated range, remains limited and highly conditional.
Across a dataset of more than 1.18 million sold lots, only around one-third of works transact within their published estimate range, with the remainder split almost evenly between above- and below-estimate outcomes. Estimates frame expectations without tightly determining realised prices; they centre expectations, but outcomes disperse systematically around them.
Figure 1. Above- and below-estimate outcomes occur in nearly equal proportions, indicating that realised prices systematically diverge around published expectations.
Source: Artscapy | Visualisation: Darden Gildea
The divergence is not random. It resolves into a clear structural asymmetry. In high-value, high-demand segments, including major auction houses, top-tier artists, and core market centres, estimates are systematically conservative, with realised prices consistently exceeding expectations. In weaker and less liquid segments, the pattern reverses: estimates become persistently over-ambitious, with a disproportionate share of works failing to meet their low estimate.
These opposing outcomes suggest that in practice, the same estimate signal implies a different risk profile depending on where the work sits in the market. In stronger segments, estimate-setting is more demand-driven, positioned conservatively to stimulate competition within deep buyer pools. In weaker segments, estimates become more supply-driven, functioning to sustain or communicate value despite fragmented demand.
Other factors, including geography, category, and sale format, introduce variation, but their effects remain secondary to demand depth, liquidity, and market concentration. Estimates are therefore best understood not as uniformly reliable indicators, and more as context-dependent pricing tools.
