Diversifiable and Non-diversifiable Risk and the Advanced Choice under Ambiguous or Uncertain Conditions

The objective of this paper is to revisit the concepts of diversifiable and non-diversifiable risk, expound the portfolio risk in two ways: mathematically first, and with practical examples, second It also explains lending and borrowing at the risk-free rate of return, in addition to juxtaposing the diversification method to measure the unsystematic risk against utilizing Beta to measure the systematic risk. Furthermore, it briefly examines the mathematical simulation and sensitivity analysis, and mathematically delineates the technique for choices under risk, ambiguity, and uncertainty. The practical implication of this conceptual paper is to offer a further clarification of theoretical terms, especially those which might be interchangeable in financial and economic literature, and further show, by examples, the terms’ applicability.

Diversifiable and Non-diversifiable Risk and the Advanced Choice under Ambiguous or Uncertain Conditions

The objective of this paper is to revisit the concepts of diversifiable and non-diversifiable risk, expound the portfolio risk in two ways: mathematically first, and with practical examples, second It also explains lending and borrowing at the risk-free rate of return, in addition to juxtaposing the diversification method to measure the unsystematic risk against utilizing Beta to measure the systematic risk. Furthermore, it briefly examines the mathematical simulation and sensitivity analysis, and mathematically delineates the technique for choices under risk, ambiguity, and uncertainty. The practical implication of this conceptual paper is to offer a further clarification of theoretical terms, especially those which might be interchangeable in financial and economic literature, and further show, by examples, the terms’ applicability.

By chance or by choice? Biased attribution of others’ outcomes when social preferences matter

Decision makers in positions of power often make unobserved choices under risk and uncertainty. In many cases, they face a trade-off between maximizing their own payoff and those of other individuals. What inferences are made in such instances about their choices when only outcomes are observable? We conduct two experiments that investigate whether outcomes are attributed to luck or choices. Decision makers choose between two investment options, where the more costly option has a higher chance of delivering a good outcome (that is, a higher payoff) for the group. We show that attribution biases exist in the evaluation of good outcomes. On average, good outcomes of decision makers are attributed more to luck as compared to bad outcomes. This asymmetry implies that decision makers get too little credit for their successes. The biases are exhibited by those individuals who make or would make the less prosocial choice for the group as decision makers, suggesting that a consensus effect may be shaping both the belief formation and updating processes.

Decision Theory under Uncertainty Mean-Variance Approach

In this paper, we mainly consider the theory and analysis of Decision under uncertainty which is making the foundations of all finance and portfolio theories. Decision makers face choices among a number of risky alternatives which is represented by lotteries. This paper develops alternative theories for choices under risk which expected utility theory which is derived from reasonable axioms about rational behavior in risky environment. An alternative theory of choice is developed, in which value is assigned to gains and losses rather than to final assets. All risky alternatives can be summarized by two numbers – mean u and variance called Mean-Variance Theory (MVT). This implies that typical mean-variance utility function v which is increasing in and decreasing in.The results show that, investors have different mean variance utility functions but the main results regarding optimal portfolio of risky assets do not depend on the specific utility functions of investors.

Salience and Skewness Preferences

Whether people seek or avoid risks on gambling, insurance, asset, or labor markets crucially depends on the skewness of the underlying probability distribution. In fact, people typically seek positively skewed risks and avoid negatively skewed risks. We show that salience theory of choice under risk can explain this preference for positive skewness, because unlikely, but outstanding payoffs attract attention. In contrast to alternative models, however, salience theory predicts that choices under risk not only depend on the absolute skewness of the available options, but also on how skewed these options appear to be relative to each other. We exploit this fact to derive novel, experimentally testable predictions that are unique to the salience model and that we find support for in two laboratory experiments. We thereby argue that skewness preferences—typically attributed to cumulative prospect theory—are more naturally accommodated by salience theory.

Prospect Theory and sentiment-driven fluctuations

In this paper we aim to present a novel channel through which the volatility of the monetary/financial sector affects the instability of the real macroeconomic variables originated by self-fulfilling market sentiments. To this aim, we insert some elements of Prospect Theory in the preferences of agents living in an overlapping generations economy where consumers’ heterogeneity and firms’ imperfect information on the level of aggregate demand allow market sentiments to affect the equilibrium path of the economy under rational expectations. In this environment, greater heterogeneity in the household’s narrow framing parameter and in the degree of competition in goods markets favor the emergence of self-fulfilling equilibria by exacerbating the coordination problem generated by a pair-wise matching process taking place in the labor market. Furthermore, the more dispersed are agents’ deviations from standard rationality the higher is the volatility of the economy due to sentiment fluctuations. Finally, a higher volatility of the money/financial market, by increasing the effect of Prospect Theory on households’ choices under risk, increases the noise of the signal upon which firms make their hiring decisions; this, in its turn, generates greater variability in market sentiments and hence in real economic activity.