Prospect Theory

The Interplay between Utility and Risk in Portfolio Selection ArXiv ID: 2509.10351 “View on arXiv” Authors: Leonardo Baggiani, Martin Herdegen, Nazem Khan Abstract We revisit the problem of portfolio selection, where an investor maximizes utility subject to a risk constraint. Our framework is very general and accommodates a wide range of utility and risk functionals, including non-concave utilities such as S-shaped utilities from prospect theory and non-convex risk measures such as Value at Risk. Our main contribution is a novel and complete characterization of well-posedness for utility-risk portfolio selection in one period that takes the interplay between the utility and the risk objectives fully into account. We show that under mild regularity conditions the minimal necessary and sufficient condition for well-posedness is given by a very simple either-or criterion: either the utility functional or the risk functional need to satisfy the axiom of sensitivity to large losses. This allows to easily describe well-posedness or ill-posedness for many utility-risk pairs, which we illustrate by a large number of examples. In the special case of expected utility maximization without a risk constraint (but including non-concave utilities), we show that well-posedness is fully characterised by the asymptotic loss-gain ratio, a simple and interpretable quantity that describes the investor’s asymptotic relative weighting of large losses versus large gains. ...

A new behavioral model for portfolio selection using the Half-Full/Half-Empty approach ArXiv ID: 2312.10749 “View on arXiv” Authors: Unknown Abstract We focus on a behavioral model, that has been recently proposed in the literature, whose rational can be traced back to the Half-Full/Half-Empty glass metaphor. More precisely, we generalize the Half-Full/Half-Empty approach to the context of positive and negative lotteries and give financial and behavioral interpretations of the Half-Full/Half-Empty parameters. We develop a portfolio selection model based on the Half-Full/Half-Empty strategy, resulting in a nonconvex optimization problem, which, nonetheless, is proven to be equivalent to an alternative Mixed-Integer Linear Programming formulation. By means of the ensuing empirical analysis, based on three real-world datasets, the Half-Full/Half-Empty model is shown to be very versatile by appropriately varying its parameters, and to provide portfolios displaying promising performances in terms of risk and profitability, compared with Prospect Theory, risk minimization approaches and Equally-Weighted portfolios. ...

Behavioral Economics ArXiv ID: ssrn-245828 “View on arXiv” Authors: Unknown Abstract Behavioral Economics is the combination of psychology and economics that investigates what happens in markets in which some of the agents display human limitati Keywords: Behavioral Economics, Prospect Theory, Cognitive Biases, Heuristics, General (Economics) Complexity vs Empirical Score Math Complexity: 3.0/10 Empirical Rigor: 2.0/10 Quadrant: Philosophers Why: The paper is a theoretical and conceptual survey of behavioral economics, focusing on high-level ideas like bounded rationality and limits of arbitrage with minimal mathematical formalism or empirical data. It lacks backtests, datasets, or implementation details, positioning it as a philosophical/theoretical discussion rather than a quantitative trading strategy. flowchart TD A["Research Goal:<br>Understand deviations from<br>rational economic models"] --> B{"Methodology"} B --> C["Theoretical Modeling<br>e.g., Prospect Theory"] B --> D["Experimental Design<br>Labs & Field Studies"] C --> E["Data Inputs:<br>Psychological Heuristics &<br>Bias Observations"] D --> E E --> F["Computational Processes:<br>Agent-Based Simulation<br>& Probability Weighting"] F --> G{"Key Findings/Outcomes"} G --> H["Prospect Theory<br>Loss Aversion & Reference Dependence"] G --> I["Identified Cognitive Biases<br>e.g., Anchoring, Framing"] G --> J["Policy Implications<br>Nudges & Market Regulation"]

Behavioral Economics ArXiv ID: ssrn-245733 “View on arXiv” Authors: Unknown Abstract Behavioral Economics is the combination of psychology and economics that investigates what happens in markets in which some of the agents display human limitati Keywords: Behavioral Economics, Prospect Theory, Cognitive Biases, Heuristics, General (Economics) Complexity vs Empirical Score Math Complexity: 4.0/10 Empirical Rigor: 6.0/10 Quadrant: Street Traders Why: The paper involves established financial models and deterministic thresholds but lacks statistical backtesting or empirical datasets. The focus is on practical application and optimization within existing frameworks, fitting the Street Trader profile. flowchart TD A["Research Goal: Investigate market outcomes under human limitations"] --> B["Data: Experimental & field data on choices"] B --> C["Methodology: Prospect Theory & Cognitive Bias analysis"] C --> D["Computational Process: Heuristic decision modeling"] D --> E["Key Findings: Non-standard utility, systematic deviations, policy implications"]