Beyond a bias toward local stocks, investors prefer companies in certain cities over others. This study uses the geographic network of investor-followed stocks from stock watchlists to identify intercity investment preferences in China. We measure the city-pair connectivity by its likelihood of sharing an investor in common whose stock watchlist is highly concentrated in the firms of that city pair. We find that a higher connectivity-weighted aggregate stock demand-to-supply ratio across connected cities is associated with higher stock valuations, higher turnover, better liquidity, and lower cost of equity for firms in the focal city. The effects are robust to controls for geographic proximity and the broad investor base, are stronger among small firms, extend to stock return predictability, and imply excess intercity return comovement. Our results suggest that city connectivity revealed on the stock watchlist helps identify network factors in asset pricing.

Using the unique regulatory setting from the Hong Kong stock market with both shortable and no-short stocks, we document that no-short stocks on average earn significantly higher average returns than shortable stocks. Furthermore, stocks that comove more with the portfolio of no-short stocks than with the portfolio of shortable stocks on average earn higher subsequent abnormal returns. Additions to and deletions from the shorting list only partially contribute to the no-short return premium. To interpret our findings, we provide a theoretical model showing that rational investors’ discounting for the mispricing risk of no-short stocks can lead to the no-short return premium.

Behavioral theories suggest that investor misperceptions and market mispricing will be correlated across firms. We use equity and debt financing to identify common misval- uation across firms. A zero-investment portfolio (UMO, undervalued minus overvalued) built from repurchase and issue firms captures comovement in returns beyond that in some standard multifactor models, and substantially improves the Sharpe ratio of the tangency portfolio. Loadings on UMO incrementally predict the cross-section of returns on both portfolios and individual stocks, even among firms not recently involved in external fi- nancing activities. Further evidence suggests that UMO loadings proxy for the common component of a stock’s misvaluation.

Beyond a bias toward local stocks, investors prefer companies in certain cities over others. This study uses the geographic network of investor-followed stocks from stock watchlists to identify intercity investment preferences in China. We measure the city-pair connectivity by its likelihood of sharing an investor in common whose stock watchlist is highly concentrated in the firms of that city pair. We find that a higher connectivity-weighted aggregate stock demand-to-supply ratio across connected cities is associated with higher stock valuations, higher turnover, better liquidity, and lower cost of equity for firms in the focal city. The effects are robust to controls for geographic proximity and the broad investor base, are stronger among small firms, extend to stock return predictability, and imply excess intercity return comovement. Our results suggest that city connectivity revealed on the stock watchlist helps identify network factors in asset pricing.

We study the effects of a direct high-speed rail (HSR) service between two cities on investors and firms in China’s A-share markets. After an HSR introduction, retail investors make more cross-city web searches and block stock purchases of firms in connected cities. An HSR introduction also leads to less comovement among local stocks and more comovement between stocks in connected cities. Firms located in more central cities in the HSR network enjoy higher firm valuation, lower cost of equity, higher turnover, and better liquidity, in part through the channel of increased investor recognition. The HSR effects on capital market outcomes are more pronounced among small firms and when the connected city-pair distance is below 1,500 km, for which HSR is faster than flying. The findings highlight the importance of in-person interactions in financial markets.

Using text data from Reddit, we construct inter-firm linkages based on shared discussions and common authors on social media. We find that firms linked on social media have similar fundamentals characteristics. The positive predictability of the returns of their Reddit peer stocks on focal stocks’ future returns suggests a sluggish dissemination of information. Our findings show that social media activities capture the collective cognition of the public, effectively reflecting the financial network in an implicit way.

In this paper, using news reports and stock trading data from China, we document that stocks covered by the same media platform tend to comove together and refer to it as media-driven comovement. This finding remains significant both by conducting time series regressions of individual stock returns on co-coverage portfolio returns and by calculating the Pearson correlations among stocks that are co-covered by the same media platform. This is a novel type of comovement since it cannot be fully explained by common factors (e.g., additions to market indices) that lead to comovement but accords well with the investment habitat view. Besides, we find no statistically significant relationship between the frequency of co-coverage and the magnitude of comovement. To better illustrate the economic significance of this media-driven comovement, we construct a trading strategy which earns a monthly return of 115 basis point.

所谓超联动（excess comovement）是指不同资产价格或回报之间的正相关程度超出了基本面经济因素所能解释的范围，其在很大程度上反映了金融市场的非理性成分。超联动效应是金融市场中普遍存在的现象，并由于其对于投资决策和金融监管的重要意义，故一直以来为西方金融学者所重视，相应的研究成果很多。但是在国内，相关的研究却进展缓慢，尚处于萌芽起步阶段。因此，本文欲基于行为金融的视角，从内涵、机理成因、测量方法、实证研究等角度，对当前西方股票市场回报超联动研究成果做一个综述性研究；同时对超联动研究的进一步发展方向及其对国内学者的启示进行了探讨。希望借此能推动该领域研究在国内的进一步发展。