Investment, Performance, and Flows in Chinese Mutual Funds

Abstract

This thesis comprises three essays investigating the investment, performance, and flows
of Chinese mutual funds. Over the last three decades, China’s economy has undergone
remarkable expansion (Allen et al., 2024), with GDP rising from 444.74 billion USD in
1993 to 17.79 trillion USD in 2023. Accompanying this phenomenal economic growth, China’s
mutual fund industry have also developed significantly, achieving global prominence—at least in
terms of scale. This raises an interesting question: does the behavior of Chinese mutual funds
align with or diverge from our existing understanding of mutual fund behavior in other countries?
Chapter 2 examines the effect of anti-corruption campaign on mutual fund ownership of
company shares, using China’s national anti-corruption campaign launched in late 2012. This
nationwide crackdown on corruption provided staggered exogenous shocks to the extent of
political corruption across all cities of China, particularly in areas where local top-ranking
officials were investigated for corruption. Our findings reveal that mutual funds, as sophisticated
investors, responded to this shock by shifting their share holdings toward firms headquartered in
regions where local top-ranking officials were not investigated during the campaign. This effect
is more pronounced for companies that are more dependent on political connections (non-StateOwned Enterprises (SOEs, hereafter), startups, and large companies) and firms with higher
information asymmetry and weaker monitoring. Furthermore, I find that mutual funds exhibit a
more negative response to firms headquartered in developed regions, suggesting that China’s
unique political-business relations influence mutual fund preferences. This “flight-to-safety”
behavior indicates that corruption investigations deter mutual fund investments, with investors
displaying a preference for firms not under investigation.
Chapter 3 assesses fund managers’ selectivity skills (Jensen, 1968) and factor timing skills
(Treynor and Mazuy, 1966). I distinguish fund good performance due to skill from pure "luck"
by comparing three bootstrap methods (Kosowski et al., 2006; Fama and French, 2010; Harvey
and Liu, 2022). Results show that at least 10.25% (5.17%) of funds generate a positive abnormal
return gross (net) of expenses. This percentage increases to 21.09% (10.16%) for the subsample
of funds with at least 60 consecutive monthly returns. I find strong evidence that, on average,
Chinese mutual fund managers can outperform the benchmark. However, this out-performance
appears to be driven by fund managers’ selectivity skills rather than factor-timing abilities. I find
that Kosowski et al.’s (2006) bootstrap simulation produces narrow confidence intervals, whereas
Fama and French’s (2010) method results in much wider confidence intervals. Harvey and Liu’s
(2022) method yields confidence intervals that fall between the two. Finally, I find evidence that
approximately 20% of Chinese mutual funds outperform the benchmark (net of expenses) due to
skill under either bootstrap method.
Chapter 4 examines the flows into and out of Chinese equity mutual funds. I find fund
investors base their purchase decisions on funds’ prior performance, investing disproportionately
more in past winners. However, they do so asymmetrically, as there is little penalty for funds
i
with disappointing performance. This finding is consistent with evidence from the U.S. mutual
fund industry. Moreover, I find a striking relationship between retail investor flows and fund
performance. Unlike institutional investors, retail investors respond more strongly to raw returns
than to risk-adjusted returns.

Date of Award	30 Sept 2025
Original language	English
Awarding Institution	University of Bristol
Supervisor	Ian Tonks (Supervisor) & Fangming Xu (Supervisor)