It is a well-known fact that actively managed mutual funds on average underperform the passive benchmarks. In this paper, I use the stochastic dominance test proposed by Linton, Maasoumi, and Whang (2005) to shed new light on mutual fund performance on average and across styles. This test evaluates mutual fund performance using a non-parametric framework that 1) imposes a minimal set of conditions on preferences; and 2) analyzes the entire return distribution for each mutual fund group. I find little evidence that actively managed mutual funds on average underperform the passive benchmark, suggesting that mutual fund performance results are highly sensitive to investor preference assumptions. Exploring the returns for different styles of mutual funds, I find that aggressive mutual funds underperform the market for risk-averse investors, whereas both growth & income and income funds outperform the market for prudent investors. Furthermore, I find that mutual fund portfolios formed by the stochastic dominance approach provide superior future performance.
We argue that the rise in China’s shadow banking was inextricably linked to potential balance-sheet risks in the banking system. We substantiate this argument with three didactic findings: (1) commercial banks in general were prone to engage in channeling risky entrusted loans; (2) shadow banking through entrusted lending masked small banks’ exposure to balance-sheet risks; and (3) two well-intended regulations and institutional asymmetry between large and small banks combined to give small banks an incentive to exploit regulatory arbitrage by bringing off-balance-sheet risks into the balance sheet. We reveal these findings by constructing a comprehensive transaction-based loan dataset, providing robust empirical evidence, and developing a theoretical framework to explain the linkages between monetary policy, shadow banking, and traditional banking (the banking system) in China.
Work in Progress
Beta Anomaly and Mutual Fund Performance, with Jeong Ho (John) Kim
Entropy and Exchange Rates Forecasting in Emerging Markets
I tackle the Meese-Rogoff (exchange rate disconnect) puzzle using non-parametric forecasting models. In particular, I assess the performance of a set of linear and non-parametric forecasting models for the exchange rate using general entropy measures. I find that, in contrast to the popular linear Taylor rule-based models of exchange rate, non-parametric models significantly improve both in-sample fit and out-of-sample forecasting for the peso-dollar exchange rate. Moreover, the non-parametric Taylor rule-based exchange rate model consistently outperforms the random walk model in-sample and out-of-sample. These results show that economic variables indeed do contain information useful for forecasting exchange rate movements if the model is properly specified.
Federal Open Market Committee Meetings and Mutual Fund Performance
I uncover the finding that mutual fund returns on Federal Open Market Committee (FOMC) dates are significantly higher than non-FOMC days. Examining mutual fund daily returns from 1998 to 2005, I find that these FOMC mutual fund returns have accounted for sizable fractions of total mutual fund returns. Stochastic dominance test results show that investors with increasing utility function will prefer mutual fund returns on FOMC days to those on non-FOMC days. I also examine whether mutual funds outperform the S&P 500 on FOMC days and whether certain styles of mutual funds perform better on FOMC days. Even though the S&P 500 also experiences higher returns on FOMC days, I find that risk-averse investors will prefer the average returns of mutual funds with growth investment objectives to the returns of the S&P 500 on FOMC days.