Kosowski, Timmermann, Wermers, and White (2006) find that certain growth-oriented fund managers have substantial skill but do not stipulate the particular skills that they possess. I use novel style timing models to examine in detail the timing skills of 3,181 US equity mutual funds classified as having a growth investment objective by Standard & Poor’s, over the period from 1993 to 2006. To control for idiosyncratic variation in mutual fund returns, the bootstrap method of Kosowski et al. is used to analyze the significance of alpha and timing coefficient estimates. To exclude the possibility that the observed timing ability is due to good luck, synthetic funds are examined as in Busse (1999). The results indicate that growth-oriented fund managers who earn abnormal returns demonstrate substantial growth timing skill, i.e. successful timing activity across the value/growth continuum. This observed growth timing ability accounts for at least 45% of abnormal returns and is persistent; the top 10% of funds which demonstrate growth timing ability in the past three years also demonstrate the best growth timing ability in the following year. Successful growth timing is confined to those managers who invest primarily in growth stocks. However, there is little evidence of successful market timing (i.e. forecasting future market states and weighting equity exposure accordingly), size timing (i.e. adjusting exposure between small and large capitalization stocks) or momentum timing (i.e. switching between momentum investing and contrarian investing strategies). The models employed clearly distinguish between growth timing and market timing skills, thereby avoiding a common misidentification problem.

Hedge fund managers are characterised as either market timers or asset pickers . Their superior performance can be attributed to either timing skill, selection ability or a combination of both. In the existing literature, average hedge fund performance across the entire time span under investigation is usually investigated and measured, and hence, potentially certain subtle but important features exhibited in different time periods can be averaged out in the analysis. This thesis investigates the structural breaks in the selection ability and timing skill of hedge fund managers. This research issue is of particular importance when the hedge fund performance before, during and after the recent financial crisis is compared and contrasted. This thesis conducts a structural break analysis of hedge fund managers performance in relation to market-wide liquidity and liquidity commonality in the foreign exchange (FX) market. Liquidity commonality captures the co-movement of individual asset liquidities. The measure adopted in the existing literature has several limitations. This thesis proposes a new measure, termed the Beta Index, which is derived from the time-varying exposure of individual liquidities to market liquidity movements. It is shown that the developed Beta Index is more able to identify the level of liquidity commonality in the FX market. It is also more flexible in measuring commonality with different data sampling frequency. The obtained empirical results have some practical implications. They show that the selection skill and timing ability of hedge fund managers are subject to regime switches. Under severe market conditions, most hedge fund managers possess the skill to time FX market-wide liquidity and are able to reduce losses from the FX market by reducing their funds FX exposure prior to the FX market-wide liquidity deteriorations. In the meantime, most hedge fund managers are able to deliver excess returns from time to time due to their selection ability. However, when sudden shocks of crisis occur, they fail to forecast the unexpected behaviour in the price of individual assets underlying the funds and display unsuccessful selection ability. In addition, the results suggest that many hedge funds are exposed to the FX liquidity commonality risk which impairs hedging strategies and diversification performance.

I study various aspects of mutual funds in my thesis. These are divided over four chapters. The first chapter is an introduction to the thesis and sets out an executive summary of my research. The second to fourth chapters each deal with a new concept. The second chapter shows that the sensitivity of an investor's reaction to a mutual fund's recent performance increases with the fund's historical performance. Put differently, bad (good) performance combined with a good-history for a fund results in a greater fraction of capital outflows (inflows) relative to a fund with a poor past history. The evidence is puzzling as we would expect investors to stick with a fund having a good-history, even after a single bad performance. I solve this problem using a model with investors of differing attentiveness. In equilibrium, fund owner's attentiveness increases the historical record of a fund. With this mechanism, the model can explain the higher sensitivity of outflows for higher reputation funds. The chapter is important in that it shows that return-chasing behavior is not ubiquitous. It also provides a clear evidence where the market is slow to incorporate the new information into decision making. The third chapter studies the managerial side of the mutual funds industry regarding the risk-taking behavior of the mutual funds. Mutual fund managers are compared against a benchmark or with the peers. The employment, as well as investor's capital flows, depends on how the manager fares in the competition. I present new evidence in the chapter that the exposure of a manager to these risks is heterogeneous, and manager's historical performance governs it. The evidence implies that the risk-appetite and behavior of a manager depends on his historical performance. I find strong support in the data for this hypothesis. I show that funds with poor historical performance do not boost the portfolio risk to catch up with the peers if they are lagging at the interim date. In general, the risk appetite of the poor-history manager is less driven by their interim performance. But the good-history managers respond to their midyear position and more so during the bull years. The evidence on risk-shifting is consistent with the evidence on how each incentive behaves for good and poor history managers over bull and bear phases. The fourth chapter shows that capital movement in and out of a mutual fund is more sensitive to fund performance during periods of high market volatility. I explain this result using a model where the manager has picking as well as timing skill. A volatile market presents an opportunity to generate timing value and to that extent produces speedy learning about managerial timing ability. Persistence in volatility boosts the sensitivity of flows to performance during such times. Given the counter-cyclical nature of market volatility, the model predicts that the flow sensitivity is higher during the recessions. Data supports the model prediction. The chapter provides a clear example when the trade volume (here capital flows) is linked positively with the volatility. Usually, literature has shown how the volatile periods slows the learning and hence trade volumes too. But my model indicates that there could be substantial learning going on during volatile times about critical economics parameters, mainly because those parameters are revealed only during volatile times.