A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Theory integrates loss aversion into expected utility for monetary returns.
GBC methods compute expected utility without needing the model's density.
The expected utility operators introduced in a previous paper, offer a framework for a general risk aversion theory, in which risk is modelled by a fuzzy number . In this paper we formulate a coinsurance problem in the possibilistic setting defined by an expected utility operator . Some properties of the optimal …
Study examines how risk tolerance impacts long-term investment returns.
Active inference minimizes expected free energy for optimal behavior.
Study optimal investment and consumption in incomplete markets with nonlinear expectations.
Investigates conditions for risk or utility functionals to be sensitive to large losses.
The paper confirms a conjecture about optimal expected utility in markets with insider information.
This paper discusses the sensitivity of the long-term expected utility of optimal portfolios for an investor with constant relative risk aversion. Under an incomplete market given by a factor model, we consider the utility maximization problem with long-time horizon. The main purpose is to find the long-term sensitivit…
We demonstrate a limitation of discounted expected utility, a standard approach for representing the preference to risk when future cost is discounted. Specifically, we provide an example of the preference of a decision maker that appears to be rational but cannot be represented with any discounted expected utility. A …
Loss-calibrated EP improves Bayesian decision-making by focusing on utility-sensitive posterior approximations.
Optimal portfolios are found for a wide range of utility functions under hyperbolic returns.
Gambles are random variables that model possible changes in monetary wealth. Classic decision theory transforms money into utility through a utility function and defines the value of a gamble as the expectation value of utility changes. Utility functions aim to capture individual psychological characteristics, but thei…
Study finds cheapest possible payoff under ambiguity, linking to maxmin expected utility.
Possibilistic risk theory starts from the hypothesis that risk is modelled by fuzzy numbers. In particular, in a possibilistic portfolio choice problem, the return of a risky asset will be a fuzzy number. The expected utility operators have been introduced in a previous paper to build an abstract theory of possibilisti…
We examine Kreps' (2019) conjecture that optimal expected utility in the classic Black--Scholes--Merton (BSM) economy is the limit of optimal expected utility for a sequence of discrete-time economies that "approach" the BSM economy in a natural sense: The th discrete-time economy is generated by a scaled -step r…
A classical portfolio theory deals with finding the optimal proportion in which an agent invests a wealth in a risk-free asset and a probabilistic risky asset. Formulating and solving the problem depend on how the risk is represented and how, combined with the utility function defines a notion of expected utility. In t…
We provide an economic interpretation of the practice consisting in incorporating risk measures as constraints in a classic expected return maximization problem. For what we call the infimum of expectations class of risk measures, we show that if the decision maker (DM) maximizes the expectation of a random return unde…
Optimizes portfolios with utility theory, diversification, and leverage.
We consider an infinite dimensional optimization problem motivated by mathematical economics. Within the celebrated "Arbitrage Pricing Model", we use probabilistic and functional analytic techniques to show the existence of optimal strategies for investors who maximize their expected utility.
This paper discusses an alternative explanation for the empirical findings contradicting the positive relationship between risk (variance) and reward (expected return). We show that these contradicting results might be due to the false definition of risk-perception, which we correct by introducing Expected Downside Ris…
Proves weak convergence equals mean convergence in GGC.
Study examines insurance demand under ambiguity aversion.
Diversification represents the idea of choosing variety over uniformity. Within the theory of choice, desirability of diversification is axiomatized as preference for a convex combination of choices that are equivalently ranked. This corresponds to the notion of risk aversion when one assumes the von-Neumann-Morgenster…
The paper tackles optimal policy learning with asymmetric counterfactual utilities in healthcare decisions.
The paper resolves a counterexample showing convergence of expected utility in binomial models.
We consider market players with tail-risk-seeking behaviour as exemplified by the S-shaped utility introduced by Kahneman and Tversky. We argue that risk measures such as value at risk (VaR) and expected shortfall (ES) are ineffective in constraining such players. We show that, in many standard market models, product d…
In this paper we study a robust expected utility maximization problem with random endowment in discrete time. We give conditions under which an optimal strategy exists and derive a dual representation for the optimal utility. Our approach is based on a general representation result for monotone convex functionals, a fu…
Motivated by the AIG bailout case in the financial crisis of 2007-2008, we consider an insurer who wants to maximize the expected utility of the terminal wealth by selecting optimal investment and risk control strategies. The insurer's risk process is modelled by a jump-diffusion process and is negatively correlated wi…
A new method extends Bayesian optimization to more models and utilities.
Optimal financial strategies minimize risk under uncertain models.
Expands Bayesian experiment design framework to account for model discrepancies.
Study optimizes insurance investment to maximize utility across all capital levels.
A new, computationally friendly formula for a class of risk-averse preferences.
Investor finds a fair outcome in complex financial markets.
Study preferences over uncertain time payments, finds growth-optimality better than expected utility theory.
Investment and consumption strategy optimized under uncertain conditions.
Paper formalizes Simon's satisficing through FFSD, proving its equivalence to expected utility theory.
We develop a general theory of convex duality for certain singular control problems, taking the abstract results by Kramkov and Schachermayer (1999) for optimal expected utility from nonnegative random variables to the level of optimal expected utility from increasing, adapted controls. The main contributions are the f…
We study the dynamic indifference pricing with ambiguity preferences. For this, we introduce the dynamic expected utility with ambiguity via the nonlinear expectation--G-expectation, introduced by Peng (2007). We also study the risk aversion and certainty equivalent for the agents with ambiguity. We obtain the dynamic …
Assuming that agents' preferences satisfy first-order stochastic dominance, we show how the Expected Utility paradigm can rationalize all optimal investment choices: the optimal investment strategy in any behavioral law-invariant (state-independent) setting corresponds to the optimum for an expected utility maximizer w…
Bayesian Parametric Portfolio Policies corrects overestimation of utility and risk in traditional PPP.
Experimentally, it has been observed that humans and animals often make decisions that do not maximize their expected utility, but rather choose outcomes randomly, with probability proportional to expected utility. Probability matching, as this strategy is called, is equivalent to maximum entropy reinforcement learning…
In this paper we will provide a representation of the penalty term of general dynamic concave utilities (hence of dynamic convex risk measures) by applying the theory of g-expectations.
Formalizes vNM utility theorem using Lean 4, proving existence and uniqueness.
We consider the problem of maximizing expected utility from terminal wealth in models with stochastic factors. Using martingale methods and a conditioning argument, we determine the optimal strategy for power utility under the assumption that the increments of the asset price are independent conditionally on the factor…
Proposes a new VIX futures trading strategy based on term structure modeling.
Examines optimal risk sharing with realistic risk attitudes, finding risk seeking in certain subdomains.