Do More Economists Hold Stocks?

A unique data set enables us to test the hypothesis that more economists than otherwise identical investors hold stocks due to informational advantages. We confirm that economists have a significantly higher probability of participating in the stock market than investors with any other education, even when controlling for several background characteristics. We make use of a large register-based panel data set containing detailed information on the educational attainments and various financial and socioeconomic variables. We model the stock market participation decision by the probit model. The results are shown to be highly robust to various assumptions, including unobserved individual heterogeneityInvestor education; Portfolio choice; Stock market participation

Higher-order beliefs among professional stock market forecasters : some first empirical tests

A sizeable literature reports that financial market analysts and forecasters herd for reputational reasons. Using new data from a large survey of professional forecasters' expectations about stock market movements, we find strong evidence that the expected average of all forecasters' forecasts (the expected consensus forecast) influences an individual forecaster's own forecast. This looks like herding. In our survey, forecasters do not herd for reputational reasons, however. Instead of herding, we suggest that forecasters form higher-order expectations in the spirit of Keynes (1936). We find that young forecasters and portfolio managers, who in previous studies have been reported to be those who in particular herd, rely more on the expected consensus forecasts than other forecasters. Given that forecasters have no incentive to herd in our study, we conclude that our results indicate that the incorporation of the expected consensus forecast into individual forecasts is most likely due to higher-order expectations

Higher-order beliefs among professional stock market forecasters: some first empirical tests

A sizeable literature reports that financial market analysts and forecasters herd for reputational reasons. Using new data from a large survey of professional forecasters' expectations about stock market movements, we find strong evidence that the expected average of all forecasters' forecasts (the expected consensus forecast) influences an individual forecaster's own forecast. This looks like herding. In our survey, forecasters do not herd for reputational reasons, however. Instead of herding, we suggest that forecasters form higher-order expectations in the spirit of Keynes (1936). We find that young forecasters and portfolio managers, who in previous studies have been reported to be those who in particular herd, rely more on the expected consensus forecasts than other forecasters. Given that forecasters have no incentive to herd in our study, we conclude that our results indicate that the incorporation of the expected consensus forecast into individual forecasts is most likely due to higher-order expectations. --Higher-order expectations,stock market forecasts,forecaster heterogeneity

Construction and information content of an investor-cost based rating of Danish mutual funds

We develop a new rating of mutual funds: the atpRating. The atpRating assigns crowns to each individual mutual fund based upon the costs an investor pays when investing in the fund in relation to what it would cost to invest in the fund’s peers. Within each investment category, the rating assigns five crowns to funds with the lowest costs and one crown to funds with the highest costs. We investigate the ability of the atpRating to predict the future performance of a fund. We find that an investor who has invested in the funds with the lowest costs within an investment category would have obtained an annual risk-adjusted excess return that is approximately 3-4 percentage points higher per annum than if the funds with the highest costs had been invested in. We compare the atpRating with the Morningstar Rating. We show that one reason why the atpRating and the Morningstar Rating contain different information is that the returns Morningstar uses as inputs when rating funds are highly volatile whereas the costs the atpRating uses as inputs when rating funds are highly persistent. In other words, a fund that has low costs one year will most likely also have low costs the following year, whereas the return of a fund in a certain year generally contains only little information about the future return that the fund will generate. Finally, we have information on the investments in different mutual funds made by a small subgroup of investors known to have been exposed to both the atpRating and the Morningstar Rating, i.e. information is provided on how investors use the two ratings. We find that investors have a clear preference for high-rated funds

Dividend Predictability Around the World

We show that dividend-growth predictability by the dividend yield is the rule rather than the exception in global equity markets. Dividend predictability is weaker, however, in large and developed markets where dividends are smoothed more, the typical firm is large, and volatility is lower. Our findings suggest that the apparent lack of dividend predictability in the United States does not uniformly extend to other countries. Rather, cross-country patterns in dividend predictability are driven by differences in firm characteristics and the extent to which dividends are smoothe

Capital market integration and consumption risk sharing over the long run

We empirically investigate time variation in capital market integration and consumption risk sharing using data for 16 countries from 1875 to 2012. We show that there has been considerable variation over time in the degrees of capital market integration and consumption risk sharing and that higher capital market integration forecasts more consumption risk sharing in the future. This finding is robust to controlling for trade openness and exchange rate volatility as alternative drivers of risk sharing. Finally, we calculate the welfare costs of imperfect consumption risk sharing and find that these costs vary over time, line up with variation in risk sharing, and are quite substantial during periods of low risk sharing

Forecasting the equity risk premium: The role of technical indicators

Forecasting the Equity Risk Premium: The Role of Technical Indicators Abstract Do existing equity risk premium forecasts ignore useful information, such as technical indicators? Although academics have extensively used macroeconomic variables to forecast the U.S. equity risk premium, they have paid relatively little attention to the technical stock market indicators widely employed by practitioners. Our paper fills this gap by studying the forecasting ability of technical indicators relative to popular macroeconomic variables. We find that technical indicators display statistically and economically significant out-of-sample forecasting power and generate substantial utility gains; moreover, technical indicators tend to detect the typical decline in the equity risk premium near cyclical peaks, while macroeconomic variables more readily pick up the typical rise near cyclical troughs. In line with this cyclical behavior, utilizing information from both technical indicators and macroeconomic variables substantially increases out-of-sample forecasting performance relative to either alone. JEL classification: C53, C58, E32, G11, G12, G1