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Title: Mutual fund characteristics, fund flows, cash management and performance : a comparative study between the China and US markets
Author: Zhou, You
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2018
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This thesis aims to contribute to the literature on mutual fund markets of China and the US by examining the relative importance of flow determinants, the cash holdings of funds and the performance implications of fund flows. It presents findings from the following three perspectives. By applying Shapley-Owen R-squared decomposition, the first empirical chapter shows that non-risk factors outperform risk factors and risk-adjusted returns in explaining fund flows in both markets. Specifically, investors show more concerns over non-risk factors, including lagged flows, fund size and Morningstar ratings, than risk betas and risk-adjusted alphas in fund selection. In addition, it offers a novel proxy, Smart-to-Dumb Ratio (SDR), which measures the smart money of sophisticated investors. SDR significantly and positively predicts fund performance in the US. The second empirical chapter shows that US fund managers are more influenced by risk factors to determine their cash holdings, while Chinese fund managers are more affected by non-risk factors. Moreover, US fund managers with higher abnormal cash holdings (ACH) are more inclined to tilt their portfolios to lower risk loadings and reduce systematic risk than Chinese fund managers. Furthermore, it shows that abnormal cash holdings attract money inflows in both markets and predict superior fund performance in the US market. The final empirical chapter presents that flow-induced trade (FIT) is significantly and positively associated with stock returns in China, which is consistent with the evidence in the US (Lou, 2012). FIT also significantly and positively predicts short-term fund performance in China. Additionally, it shows that anomaly returns (Stambaugh, Yu and Yuan, 2012) exist and active fund managers may have the ability to exploit stock return anomalies in China.
Supervisor: Cai, Charlie Xiaowu ; Keasey, Kevin Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available