We introduce a novel perspective on private information, specifically microstructure-based private information, to unravel how institutional investors predict stock returns. Using tick-by-tick transaction data from the Chinese stock market, we find that in retail-dominated markets, institutional investors positively predict stock returns, consistent with findings from institution-dominated markets. However, in contrast to the traditional view that institutional investors primarily rely on value-based private information, our results indicate that microstructure-based private information contributes almost as much to their predictive power as value-based private information does, with both components jointly accounting for approximately two-thirds of the total predictive power of institutional order flow. This finding reveals that retail investors’ trading activities significantly impact institutional investors, naturally forcing them to balance firm value information with microstructure information, thus profoundly influencing the price discovery process in the stock market.

Using a proprietary database of stock transactions in China, we document significant trading disparities between retail and institutional investors around important macro announcements. These disparities are driven by differences in information positions. We find that before the monthly releases of China’s key monetary aggregates data, institutional investors reduce their stock exposure and shift towards riskier, smaller-cap stocks. In contrast, retail investors increase their stock exposure and avoid riskier stocks. The risk positions of institutional investors are compensated by the pre-announcement premium in smaller stocks. Following the announcements, institutional investors trade in line with news surprises, contributing to price discovery and reinforcing monetary policy transmission into asset prices. Our findings have implications for understanding announcement-related equity premium and for evaluating the general efficiency of stock market in China.

This paper examines whether China’s switch back and forth from fixed to floating exchange rates in 2005 and 2008 changed the contribution to stock price discovery by foreign and domestic investors. During that time, mainland investors could only trade the RMB-denominated A-shares in the domestic Shanghai and Shenzhen markets, while the dual-listed HKD-denominated H-shares were available only to overseas investors. Using intraday data on overlapping trading hours, we find that the switch from a fixed rate to managed floating in July 2005 increased the H-shares’ contribution to price discovery; while the exchange rate regime reversal in July 2008 allowed the domestic stocks to regain their dominance in information shares. These results imply that, in a market subject to restrictions on capital flows, a flexible exchange rate regime increases the propensity of investors to trade foreign-issued stocks to speculate on the RMB exchange rate, which raises overseas investors’ contribution to price discovery.

Using the Boehmer, Jones, Zhang, and Zhang (2021) algorithm, we identify a broad swath of marketable retail investor orders in the U.S. market during the pandemic. The marketable retail trading volumes rapidly rise from $325 billion in 2019 to $852 billion at mid-2020, and stay high for the next two years. The retail order flows positively predict cross-sectional returns over various horizons, and are associated with wider future effective spreads and higher future volatilities, as well as less market participations by high frequency traders and short-sellers. We find supportive evidence for informed and uninformed retail hypotheses.

We study how professional fund managers’ growth expectations affect the actions they take with respect to equity investment and in turn the effects on prices. Using novel data on China’s mutual fund managers’growth expectations, we show that pessimistic managers decrease equity allocations and shift away from more-cyclical stocks. We identify a strong short-run causal effect of growth expectations on stock returns, despite statistically significant delays in price discovery from short-sale constraints. Finally, we find that an earnings-based measure of price informativeness is increasing in fund investment.

This study is the first to examine China’s crude oil options market. Using high-frequency data and three different price discovery measures, we conduct a rigorous analysis and find that after its first 8 months of operation, China’s crude oil options market has already played an important role in price discovery. Factors such as volume, volatility, and speculation can impact its price discovery ability. We also find a unique phenomenon in China’s crude oil derivatives market, namely that speculative activity mainly occurs in the futures market and adds to the price discovery of the futures market rather than to the options

This study examines the price discovery patterns in the three BRICS countries’ stock index futures markets that were launched after 2000 – China, India, and Russia. We detect two structural breaks in these three futures price series and their underlying spot price series, and use them to form subsamples. Employing a Vector Error Correction Model (VECM) and the Hasbrouck (1995) test, we find the price discovery function of stock index futures markets generally improves over time in China and India, but declines in Russia. A closer examination not only confirms the findings of Yang et al. (2012) and Hou and Li (2013) regarding price discovery in China’s stock index markets, but also reveals the inconsistency of futures’ leading role in the price discovery process. Further, we find some evidence of day-of-the-week effects in earlier part of the sample in China, but not in India or Russia. And our GARCH model results show bidirectional volatility spillover between futures and spot in China and India, but only unidirectional in Russia.

We identify both dynamic and long-run relationships between each of the level, slope and curvature factors of the Treasury and corporate bond markets yield curve in China. We aim at determining which market plays a leading role in the discovery of each factor of the yield curve. We obtain three main results. First, we document for the first time the presence of a long-run relationship between the corporate and Treasury bond markets in China both for the level and the slope of their yield curve. Second, such a long-run relationship appears to be stable between the slopes over the full sample 2006-2017, but shows a break for the level factor in 2012. Third, the source market for price discovery varies with the parameters of the yield curve. While the corporate bond market is the source of price discovery for the level factor, this function is fulfilled by the government bond market for the slope parameter. The finding that the Treasury bond market is not fully dominant in level bond-pricing may not come as a surprise. Although China’s corporate bond market has developed rapidly in the past fifteen years, there were few default cases during that period. It is believed investors treat the default risk of corporate bonds as similar to that of Treasury bonds, and benefit from the high corporate spread. Our results for the slope parameter imply that market-oriented reform has progressed enough for the Treasury bond market to already provide a benchmark slope for the yield curve of corporate bonds. When the reform progresses further, we would expect corporate bonds to be priced according to their risk profile which should make the Treasury market lead in price discovery also for the level of the yield curve.

We study the effect of mutual fund allocation on China’s IPO market under the new registration system. The introduction of mutual fund bids significantly increases IPO offer price, resulting in a low initial short-term return and suppressed IPO underpricing. Those newly listed stocks witness lower volatility in the following weeks due to preferential allocation to the mutual fund at the primary market. Further analysis suggests that large investors tend to buy during the first week after IPO and their net purchase strengthens IPO after-market volatility. This new evidence suggests that mutual fund allocation plays a critical role in IPO price discovery and decreases investor lottery trading.

This paper investigates information transmission and price discovery mechanisms in informationally linked and non-synchronous trading markets within the multivariate generalized autoregressive conditional heteroskedasticity framework. Using daily data for copper and soybean contracts from the Chinese futures and spot markets, as well as the London Metal Exchange (LME) and Chicago Board of Trade (CBOT) futures markets, we show that there are asymmetric lead-lag relationships between any two of the three markets. We also find that the volatilities spill over from one market to another for both cases of copper and soybeans. However, the copper and soybean markets exhibit quite different patterns of information transmission. Further, we highlight the remarkable role of the Chinese futures markets in the price formation process, though the LME/CBOT futures markets are the main driving force in price discovery.