Sonia Jimenez-Garces

Information Precision, Noise, and the Cross-Section of Stock Returns

We derive a cross-sectional asset pricing measure from a noisy multi-asset rational expectations equilibrium model. The measure is based on the time-series covariance of an asset’s returns and security prices. Empirically, stocks with a measure one standard deviation above and below the average have returns that dier by 0.36% the following month (4.44% per annum) which is statistically signicant at the 1%-level. Results remain signicant after including variables such as stock market capitalization, book-to-market ratio, and the probability of information-based trading. Our measure can be understood as a proxy for information risk and/or supply uncertainty. We show the two explanations are theoretically intertwined.

Exploiting Industry Momentum with Sector Funds: The Case of the European Market

Academics and practitioners show a tremendous interest in the trending behavior of stock prices. A wide empirical literature establishes that common stocks exhibiting high returns on a period of 3–12 months (past winners) will overperform on subsequent periods. Moreover, past losers continue to be losers on future periods. This phenomenon, called momentum, represents one of the most important challenges for the concept of market efficiency. In practice, financial planners argue that momentum is one of the most effective investment vehicles.