Chasing stock market returns: mutual funds extrapolative flow, performance and asset pricing implications

Survey evidence shows that investor expectations on future market realizations are highly correlated with in ows into mutual funds and tend to extrapolate information from past returns. This work investigates cyclical determinants of net aggregate fund ows in Emerging Markets, it measures the profitability of market-timing strategies of Italian investors in equity mutual funds and provides first insights about the effects of these strategies on asset prices. Chapter 2 investigates how cyclical variables drive net aggregate fund ows towards Emerging Markets (EMs). Through the aggregation of net ows of all open-end dedicated funds, the analysis finds that ows in equity and fixed income are driven by recent past performance in both developed and emerging economies. Further analysis confirms that much of the evidence comes from US and EU larger mutual funds. A structural VAR shows that ows become more responsive through time to market uncertainty and rates. In particular, after the Great Recession ows exhibit a lower reaction to the S&P index, becoming more responsive to market volatility and to US interest rates. Furthermore the US consumer sentiment index has a key role in the explanation of fund ows and it increased through time with an effect that is more sluggish and persistent with respect to other cyclical determinants. Chapter 3 shows that simple buy-and-hold strategies beat the market-timing strategies effectively used by Italian investors in equity mutual funds. Therefore, investors should re- consider their investment behavior and choose cheaper, in terms of fees, and simpler, passive strategies. The analysis estimates returns from market-timing strategies using aggregate data on a large sample of equity mutual funds' net ows and considers funds investing either in Europe and the Euro Area, or the US, or Emerging Markets. In all cases, buy-and-hold wins with extra returns that go from 0.24% per quarter (Europe and Euro Area) to 0.87% per quarter (US market). Differences in the performance of the two strategies are not explained by differences in risk and risk exposure. Chapter 4 presents future research developing a discrete asset pricing model with het-erogeneous agents. Some of them, called chasers, develop their demand of the risky asset relying on extrapolative subjective beliefs, in equilibrium this has effects on the asset price.