Kremena Bachmann

Which Measures Predict Risk Taking in a Multi-Stage Controlled Decision Process?

We assess the ability of different risk profiling measures to predict risk taking along a multi-stage decision process. The latter involves decisions under ambiguity, decisions under risk, decisions after gaining experience and decisions after receiving outcome information on previous decisions. We find that in all decisions risk taking can be predicted by some questions on individuals’ risk tolerance but it is not related to self-reported investment experience. Although simulated experience as part of our study design improves the risk awareness and leads to higher risk taking, it cannot substitute the assessment of risk tolerance and in particular the assessment of individual’s loss aversion. In contrast, self-assessed risk tolerance measures are not suitable for predicting risk taking in any stage of the decision process. Among the socioeconomic characteristics only the gender has some predictive power.

Behavioral finance and investment advice

Behavioural finance studies the psychological factors that influence financial behaviour both on the level of the individual as well as on the level of the market. So far these results have been mainly used to explain the existence of patterns in asset prices and to develop investment strategies that exploit them. While these applications of behavioural finance aim to understand the market, this chapter focuses on the individual investors and asks how to advise behavioural investors helping them make optimal investment decisions.

Is there Swissness in Investment Competence

Based on a large international survey we analyze how German- French- and Italian-speaking Swiss differ in their investment decision behavior and investment competence as compared to their closest neighbors abroad speaking the same language. Although language may be closer to the individual self than the country of residence, we find that there are greater similarities in the decision behavior of Swiss speaking different languages than between Swiss and their linguistically closest neighbors abroad. These similarities hold also for the emotional investment competence and to some extend also for the knowledge-based competence. We conclude that there is Swissness in the decision behavior as well as in the emotional investment competence. The latter is associated with regional differences in the relationship to investment advisors.Based on a large international survey we analyze how German- French- and Italian-speaking Swiss differ in their investment decision behavior and competence as compared to their closest neighbors abroad speaking the same language. Although language may be closer to the individual self than the country of residence, we find that there are greater similarities in the decision behavior of Swiss speaking different languages than between Swiss and their linguistically closest neighbors abroad. These similarities hold also for the investment competence. We conclude that there is Swissness in the decision behavior and in the investment competence, which most likely has cultural origins, as it cannot be explained by demographic and socio-economic similarities between the regional samples.

Earnings Management and Managerial Compensation

This paper studies the earnings management behavior of a manager in a strategic game in which the manager may have incentives to avoid earnings below the analysts’ consensus forecast and the analysts aiming to provide accurate forecasts behave as rational Bayesians. Our analysis reveals the existence of equilibria in which the manager who is compensated with stocks manipulates earnings to meet the consensus forecasts and the earnings manipulation is not detected. When the manager holds stock options, these non-revealing equilibria do not exist. The manager exhausts his reporting discretion as earnings manipulation becomes costless once the price of firm’s shares falls below the exercise price of the options. Our model provides a set of implications for observing opportunistic earnings management in dependence of managerial compensation and investors’ aversion to negative earnings surprises. In addition, the model’s predictions regarding the relationship between earnings management and executive compensation are consistent with empirical observations.