This paper investigates how foreign institutional investors, specifically Qualified Foreign Institutional Investors (QFIIs), influence the investment strategies of Chinese mutual fund management companies (FMCs) in which they hold shares. By analysing panel data from 1,766 mutual funds managed by 44 foreign-invested FMCs in China between 2005 and 2021, we explore whether QFII-invested FMCs (Q-FMCs) learn more from their domestic counterparts (D-FMCs) than other foreign-invested FMCs (NQ-FMCs). Our findings show that Q-FMC-managed mutual funds exhibit portfolio allocations more closely aligned with local DFMCs than those managed by NQ-FMCs. This imitation is particularly pronounced when selecting new stocks, enhancing portfolio performance, but not when rebalancing existing positions. Additionally, Q-FMCs trade more actively than NQ-FMCs. Robustness checks confirm these results across various ownership structures, fund characteristics, market conditions, and regulatory changes. These findings highlight the dual role of QFIIs as both investors and learners in China’s evolving financial landscape, offering insights into how foreign capital integrates into emerging mutual fund markets, informing regulatory policy aimed at fostering cross-border financial development.

We hypothesize and test an inverse relationship between liquidity and price volatility derived from microstructure theory. Two important facets of liquidity trading are examined: thickness and noisiness. As represented by expected volume (thickness) and realized average commission cost per share (noisiness) of NYSE equity trading, both facets are found negatively associated with ex post and ex ante price volatilities of the NYSE stock portfolios and the NYSE composite index futures. Furthermore, the inverse association between volatility and noisiness is amplified in times of market crisis. The overall results demonstrate that volatility increases as noise trading declines. All findings retain statistical significance and materiality after controlling for a number of specifications. This inverse liquidity-volatility relationship reflects a microstructure interpretation of the liquidity risk premium documented in the asset pricing literature.