A Collection on the Versatility and Predictive Power of Survey Expectations Data

This collection of papers analyzes the versatility and predictive power of survey expectations data in asset pricing and macroeconomic forecasting. The first paper, Using Sentiment Surveys to Predict GDP Growth and Stock Returns sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I demonstrate that surveys have significant predictive power for both GDP growth and excess stock returns, and that the results are robust to the inclusion of information pertaining to the macroeconomic environment and momentum. The findings reject the conventional wisdom that the effect of sentiment is apparent exclusively in small-capitalization stocks. The second paper, Sexonomics: Gender, Wealth, and Expectations in Financial Markets , examines the role of gender and wealth in expectations formation and shows that different gender and wealth cohorts have different relative abilities to predict inflation, interest rates, unemployment, income, stock prices, and the housing market. The results cast doubt on the Rational Expectations Hypothesis, complement recent findings in the emerging field of neuroeconomics, and have implications for investor education, understanding asset bubbles, policy makers, financial services marketing, investment management, portfolio allocation, and economic forecasting. The third paper, An Inflation Expectations Horserace, examines the use of high-frequency versus low-frequency inflation expectations data. I present a collection of 37 different measures of inflation expectations, including many previously unexploited monthly and real-time measures of inflation expectations. These higher frequency measures tend to outperform the standard low frequency survey measures in tests of accuracy, predictive power, and rationality, indicating that there are benefits to using higher frequency measures of inflation expectations. Out of sample forecasts confirm the findings