We document a unique determinant of financial systemic risks in China, share pledge financing (SPF) network, by studying all listed Chinese financial institutions that provide SPF business. As one of the most popular refinancing tools in China, SPF formulates a network among financial institutions with common collaterals. We propose a centrality measure to quantify such network effects, and document that banks are more important than securities in the SPF network before 2018, but this pattern has reversed afterwards. SPF network effects, rather than SPF margin closeout risks, significantly increase systemic risks of China's financial institutions, by increasing both individual risks of financial institutions and connectedness among them. Such an impact of the SPF network on systemic risks is more pronounced in OTC markets than in exchanges. The SPF network affects systemic risks in more extreme cases, while SPF margin closeout risks affect systemic risks in more moderate cases.

This study shows that weather-based indicators of mood impact perceptions of mispricing and trading decisions of institutional investors. Using survey and disaggregated trade data, we show that relatively cloudier days increase perceived overpricing in individual stocks and the Dow Jones Industrial Index and increase selling propensities of institutions. We introduce stock-level measures of investor mood; investor optimism positively impacts stock returns among stocks with higher arbitrage costs, and stocks experiencing similar investor mood exhibit return comovement. These findings complement existing studies on how weather impacts stock index returns and identify another channel through which it can manifest.

Motivated by recent evidence of informed trading by individual investors (Kaniel et al., 2012, Kelley and Tetlock, 2013, Wang and Zhang, 2015), we posit that individual investor trading enhances firm performance. Consistent with the conjecture, we find that individual investor trading positively impacts firm value. The results are robust to inclusion of year, industry and firm fixed effects, alternative model specifications, a control for endogeneity, Granger causality test, matched sample analysis and subsample analyses. The positive effect of individual investor trading on firm value is stronger for firms with higher information production and stocks with higher spread, consistent with the information and spread channel mechanism. Our results suggest that trading by individual investors enhances firm value by improving stock price informativeness and reducing spread.

This paper examines the role of institutional trading during the option backdating scandal of 2006–2007. Unlike their inability to anticipate other corporate events, institutional investors as a group display negative abnormal trading imbalances (i.e., buy minus sell volumes) in anticipation of firm-specific backdating exposures. Consistent with informed trading, the underlying trades earn positive abnormal short- and long-term profits. Moreover, the negative abnormal imbalances are larger in magnitude when backdating is likely a more severe issue. Local institutions, in particular, display negative trading imbalances earlier in event-time and earn consistently higher trading profits than non-local institutions. Although we find some evidence of over-reaction following the arrival of information about the backdating scandal, these patterns are short-lived and exclusively due to the activity of non-local institutions. Overall, institutional investors behave as informed investors, particularly in local stocks, during this prolonged period of heightened uncertainty about corporate reporting and governance practices.

An investor receives utility bursts from realizing gains and losses at the individual stock level and dynamically allocates his mental budget between risky and risk‐free assets at the trading account level. Using savings, he reduces his stockholdings and is more willing to realize losses. Using leverage, he increases his stockholdings beyond his mental budget and is more reluctant to realize losses. While leverage strengthens the disposition effect, introducing leverage constraints mitigates it. Our model predicts that investors with stocks in deep losses sell them either immediately or after stocks rebound a little.

This paper examines the relation between portfolio concentration and investment performance in corporate bond mutual funds. Using detailed holdings data, we construct portfolio concentration measures at the firm, industry, and credit rating levels. We find that portfolio concentration is significantly positively related to expected abnormal returns of corporate bond funds, and this relation is mainly driven by investment-grade funds. High-yield funds, however, do not exhibit such a relation, possibly due to the erosion of the value of portfolio concentration by liquidity costs. In support of this conjecture, we document that the concentration-performance relation is less pronounced among funds with higher sensitivities to market-wide illiquidity innovations and during periods of bond market illiquidity shocks and fund-level net money outflows. Finally, we show that more concentrated funds demonstrate stronger performance persistence, and investors appear to consider portfolio concentration in making investment decisions.

This study shows that weather-based indicators of mood impact perceptions of mispricing and trading decisions of institutional investors. Using survey and disaggregated trade data, we show that relatively cloudier days increase perceived overpricing in individual stocks and the Dow Jones Industrial Index and increase selling propensities of institutions. We introduce stock-level measures of investor mood; investor optimism positively impacts stock returns among stocks with higher arbitrage costs, and stocks experiencing similar investor mood exhibit return comovement. These findings complement existing studies on how weather impacts stock index returns and identify another channel through which it can manifest.

This study examines whether state-level economic conditions affect the liquidity of local firms. We find that liquidity levels of local stocks are higher (lower) when the local economy has performed well (poorly). This relation is stronger when local financing constraints are more binding, the local information environment is more opaque, and local institutional ownership levels and trading intensity are higher. Overall the evidence supports the notion that the geographical segmentation of U.S. capital markets generates predictable patterns in local liquidity.

Using data from 2002 to 2013, we show that algorithmic trading has a positive impact on firm value. Most of this positive impact flows through the channels of stock liquidity, idiosyncratic volatility, and idiosyncratic skewness, but algorithmic trading also has a large economic effect outside those channels. We use the advent of auto quotation on the New York Stock Exchange as an exogenous shock to algorithmic trading to rule out reverse causality. The positive effects of algorithmic trading on firm value are stronger for larger firms and in the post-2007 period when algorithmic trading intensity is higher.