Volatile market condition and investor clientele effects on mutual fund flow performance relationship

Jun Xiao, Mingsheng Li, Jing Shi

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

We analyze mutual fund flow–performance relationship using a novel sample of Chinese mutual funds that trade in a volatile market environment. Consistent with existing literature, we find that the net flow to a fund is positively related to past fund performance. However, the positive flow–performance relationship weakens when the stock market is divided into high and low volatile periods or when funds are divided into good and poor performers. Contrary to previous studies using samples in the U.S. and other countries, our results do not exhibit an asymmetric flow–performance relationship, nor do we find any significant Morningstar rating effect or smart money effect. Furthermore, we find that the overall stock market performance is the primary driving force of flow–performance relationship and the positive relationship is more pronounced in bull markets. Consistent with Thaler and Johnson's (1990) house money effect and the overconfidence hypothesis proposed by Gervais and Odean (2001), this suggests that Chinese mutual fund investors are vulnerable to market conditions. The overall results imply that market conditions and investor clientele differences play an important role in fund investments and flow–performance relationships.
Original languageEnglish
Pages (from-to)310-334
Number of pages25
JournalPacific-Basin finance journal
Volume29
DOIs
Publication statusPublished - Sep 2014
Externally publishedYes

Keywords

  • Chinese mutual funds
  • flow–performance relationship
  • asymmetric relationship
  • disposition effect
  • house money effect
  • star effect
  • cognitive dissonance
  • attribution bias
  • overconfidence
  • smart money effect
  • investor clientele

Fingerprint Dive into the research topics of 'Volatile market condition and investor clientele effects on mutual fund flow performance relationship'. Together they form a unique fingerprint.

Cite this