The success of behavioral economics has led to a new challenge: many biases offer observationally similar predictions for a targeted financial anomaly. To tame this bias zoo, we combine subjective survey responses with observational data to propose a new approach, one that is robust to question-specific biases introduced through surveys. We illustrate this approach by administering a nationwide survey of Chinese retail investors to elicit their trading motives. In cross-sectional regressions of respondents’ actual turnover on survey-based trading motives, perceived information advantage and gambling preference dominate other motives, though they are not the most prevalent biases based on survey responses.

We develop a model of asset price bubbles based on the communication process between advisors and investors. Advisors are well-intentioned and want to maximize the welfare of their advisees (like a parent treats a child). But only some advisors understand the new technology (the tech-savvies); others do not and can only make a downward-biased recommendation (the old-fogies). While smart investors recognize the heterogeneity in advisors, naive ones mistakenly take whatever is said at face value. Tech-savvies inflate their forecasts to signal that they are not old-fogies, since more accurate information about their type improves the welfare of investors in the future. A bubble arises for a wide range of parameters, and its size is maximized when there is a mix of smart and naive investors in the economy. Our model suggests an alternative source for stock over-valuation in addition to investor overreaction to news and sell-side bias.

We document issuance overpricing of corporate debt securities in China, which is robust across subsamples with different credit ratings, maturities, and issuers. This phenomenon contrasts with underpricing of equity and debt securities in Western countries and reflects China's distinct institutional environment. The average overpricing dropped from 7.44 basis points to 2.41 basis points after the government prohibited underwriters from using rebates in issuances in October 2017. By analyzing overpricing before and after the rebate ban and across different issuers and underwriters, we uncover two channels for underwriters, who compete for future underwriting business, to drive up overpricing: rebates and self-purchases.