We study how monetary policy in China influences banks’ shadow banking activities. We develop and estimate the endogenously switching monetary policy rule that is based on institutional facts and at the same time tractable in the spirit of Taylor (1993). This development, along with two newly constructed micro banking datasets, enables
us to establish the following empirical evidence. Contractionary monetary policy during 2009–2015 caused shadow banking loans to rise rapidly, offsetting the expected decline of traditional bank loans and hampering the effectiveness of monetary policy on total
bank credit. We advance a theoretical explanation of our empirical findings.
We contend that mutual fund performance cannot be properly measured using the alpha from standard asset pricing models if passive portfolios have nonzero alphas. We show how controlling for the passive component of alpha produces an alternative measure of managerial skill that we call “active alpha.” Active alpha is persistent and associated with superior portfolio performance. Therefore, it would be sensible for sophisticated investors to reward managers with high active alpha. In addition to allocating their money based on standard alpha, we find that a subset of investors allocate their assets to funds with high active alpha performance.
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.
Work in Progress
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.