The nominal share price anchor: A theoretical model of social norms and behavioral martingales in stock markets
Fei Qiu et al.
What the paper says
This paper investigates the nominal share price anchor, a phenomenon documented in the US stock market (1933–2007) where average nominal share prices exhibited remarkable stability. We develop a social norm formation model that explicitly incorporates the interplay between private market participants and government influence in shaping collective pricing behavior. This framework, grounded in rational expectations augmented by social norms, implies a self-reinforcing stability in nominal prices arising from a dynamic interplay between adherence to norms and potential deviations. We further introduce the concept of a “behavioral martingale” to capture the observed price dynamics. To empirically test the implications of our theoretical model, we extend the analysis to the Chinese stock market (1993–2022), a distinct economic context characterized by government-influenced financial markets. We demonstrate a similar nominal price anchoring phenomenon in China, despite divergent social, economic, and historical contexts compared to the US. We also conduct a comparative analysis using US market data covering the identical timeframe. This comparison indicates that the US market exhibited less nominal price stability during these specific years, suggesting the anchoring effect observed in China was comparatively stronger. Our findings offer insights into market efficiency, investor decision-making, and the potential impact of regulatory policy across diverse economic environments. The theoretical model and supporting empirical evidence highlight the role of social norms in shaping financial market outcomes, even in the presence of government intervention and divergent institutional frameworks.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.