Investors' horizon and stock prices
Massachusetts Institute of Technology. Dept. of Economics.
George-Marios Angeletos and Guido Lorenzoni.
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This dissertation consists of three essays on the relation between investors' trading horizon and stock prices. The first chapter explores the theoretical relation between the horizon of traders and the negative externality generated by their activity on the information revealed by stock prices. The last two chapters focus on the empirical relation between institutional investors trading frequency and stock prices behaviour. The first chapter examines how short term trading impacts the aggregation of information in financial markets. I develop a model where short-term traders, in an attempt to learn about the average beliefs of future market participants, make the price relatively more noisy. This typically introduces a negative informational externality on long-term investors. I show that (i) as the horizon of the informed traders decreases, the price becomes relatively less precise; (ii) an inflow of informed traders in the market can decrease the informativeness of the price when the traders have a relatively short horizon or the market is expected to be thin in the future; (iii) finally, as rational informed short-term traders have access to an extra source of information about the future price, they end up creating more noise and a decrease in the informativeness of the price might result. Thus, paradoxically, more informed trading could lead to a less informative price. Among scholars, practitioners and policy makers, investor short-termism and high frequency trading have been associated with excess volatility in financial markets and with a disconnect between asset prices and fundamentals. Motivated by this observation, in Chapter 2 I construct a novel measure of the intrinsic frequency of trading for each of the large US institutional investors (13-F institutions) using Thomson-Reuters Institutional Holdings quarterly data for the period 1980-2005. This measure controls for the market and portfolio characteristics and identifies an investor-specific fixed effect in the frequency of trading. I then study how the composition of these fixed effects impacts stock price behavior through their forecasting role in explaining the return and the return on equity (cash flow of a company) in the short run as well as the long run. I show that (i) the securities in which investors exhibit higher intrinsic trading frequency exhibit higher volatility, but (ii) this volatility is mainly driven by the cashflow component of the security prices. Further, (iii) the prices of the securities held by investors with a higher intrinsic trading frequency do not forecast the long-run return as opposed to the securities held by investors with a lower intrinsic trading frequency. As such, the prices mainly respond to the long-run return on equity. Overall, the results challenge the view that higher frequency of trading-a commonly used proxy for investor short-termnism-causes a disconnect between asset prices and fundamentals. Finally, in Chapter 3 (co-auhtored with Fernando Duarte) we show a novel relation between the institutional investors' intrinsic trading frequency-a commonly used proxy for the investors's investment horizon- and the cross-section of stock returns. We show that the 20$ of stocks with the lowest trading frequency earn mean returns that are 6 percentage points per year higher than the 20% of stocks that have the highest trading frequency. The magnitude and predictability of these returns persist or even increase when risk-adjusted by common indicators of systematic risks such as the Fama-French, liquidity or momentum factors. Our results show that the characteristics of stockholders affect expected returns of the very securities they hold, supporting the view that heterogeneity among investors is an important dimension of asset prices.
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 140-150).
DepartmentMassachusetts Institute of Technology. Dept. of Economics.
Massachusetts Institute of Technology