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142284426568 · Jun 202019922001200920172026
48 results for Systemic utility maximization

Algorithm improves recommendation subset selection in the presence of biases.

problem Maximizing submodular functions for recommendation in the presence of social biases.
method Algorithm for submodular maximization with fairness constraints.
result Algorithm provably outputs subsets with near-optimal utility and proportional representation.

This paper solves robust utility maximization with unknown claim dependencies.

problem Investor optimizes utility in the presence of an intractable contingent claim.
method Quantile optimization approach, transforming dynamic problem into static concave optimization.
result Optimal payoffs depend on ambiguity attitude, market conditions, and claim characteristics.

Paper tackles utility maximization with job-switching and retirement constraints.

problem Maximizing utility with job-switching and retirement constraints.
method Dual-martingale approach and double obstacle problem theory.
result Characterization of optimal job-switching strategy and wealth boundaries.

Optimizes long-term social welfare in recommender systems by matching users to providers.

problem Realistic recommender systems dynamics affect all agents, not just users.
method Formulated as an optimal constrained matching problem, solved using dynamical system equilibrium selection.
result Ensures maximal social welfare with diverse viable providers, improving over myopic matching.

The need for diversification of recommendation lists manifests in a number of recommender systems use cases. However, an increase in diversity may undermine the utility of the recommendations, as relevant items in the list may be replaced by more diverse ones. In this work we propose a novel method for maximizing the u…

2014-11-13abs ↗pdf ↗

This paper tackles robust control of noisy systems with uncertain distributions.

problem Optimal control of sampled-data stochastic systems with multiplicative noise and distributional ambiguity.
method Develops a convex relaxation to handle the ``concave-max'' geometry and derives a probabilistic performance guarantee.
result Derives an explicit, non-asymptotic bound on the duality gap and proves robust viability conditions.

Active inference minimizes expected free energy for optimal behavior.

problem Understanding and optimizing behavior in complex systems.
method Combines Bayesian decision theory, optimal Bayesian design, and the free energy principle.
result Active inference emerges as a unified framework for information-seeking, utility maximization, and goal-directed behavior.

PDBAL targets experiments for probabilistic models to maximize insights.

problem Designing experiments to yield valuable insights efficiently.
method Combines user-specified risk function with probabilistic model to adaptively choose designs.
result PDBAL consistently outperforms standard approaches in simulations and real-world drug screen data.

Study utility maximization with costs, proving convergence and strategies.

problem Utility maximization with proportional transaction costs.
method Extended weak convergence theory and Meyer--Zheng topology.
result Prove convergence of utility maximization problems and optimal trading strategies.

In our previous paper, "A Unified Approach to Systemic Risk Measures via Acceptance Set" (\textit{Mathematical Finance, 2018}), we have introduced a general class of systemic risk measures that allow for random allocations to individual banks before aggregation of their risks. In the present paper, we prove the dual re…

2018-03-27abs ↗pdf ↗

No arbitrage holds if a Pareto solution exists for vector-valued utility maximization.

problem Existence of no arbitrage in markets with transaction costs and multiple assets.
method Prove no arbitrage condition equivalent to Pareto solution for vector-valued utility maximization.
result A consistent price process can be constructed from the Pareto maximizer.

Econometrics is based on the nonempiric notion of utility. Prices, dynamics, and market equilibria are supposed to be derived from utility. Utility is usually treated by economists as a price potential, other times utility rates are treated as Lagrangians. Assumptions of integrability of Lagrangians and dynamics are im…

1999-11-18abs ↗pdf ↗

Study examines insider information's impact on arbitrage and utility maximization in financial portfolios.

problem Analyzing the relationship between insider information and arbitrage in financial portfolio optimization.
method Examines the utility maximization problem under different utility functions (logarithmic and CRRA) with and without no temporary-bankruptcy restriction, considering altered information flow.
result Insider information's value is bounded when arbitrage holds, and it does not always imply arbitrage.

The paper examines utility maximization in markets with hidden Gaussian drift, finding restrictions on model parameters.

problem Utility maximization problems in markets with hidden Gaussian drift mean-reverting processes.
method Derives sufficient conditions for bounded maximum expected utility of terminal wealth for models with full and partial information.
result Restrictions on model parameters for bounded maximum expected utility.

New method for fair resource allocation in AI-aware networks with unknown utility functions.

problem Fair resource allocation in AI-aware communication networks with unknown utility functions.
method Distributed, data-driven bilevel optimization approach to learn surrogate utility functions.
result The proposed algorithm learns from data to autotune surrogate utility functions for unknown utility functions.

Study on robust utility maximization with nonconcave utility functions under projective determinacy.

problem Investor's optimal investment strategy under model ambiguity and nonconcave utility.
method Projective functions of the path and sets of priors, upper-semicontinuous utility.
result Existence of optimal investment strategy under PD.

The paper solves a portfolio selection problem in incomplete markets by balancing utility and risk.

problem Time-inconsistent portfolio selection in incomplete markets.
method Characterizes equilibrium via a coupled quadratic BSDE system, introduces approximate equilibrium for general cases.
result Established existence theory for equilibrium strategies in special and general cases.

Stability of the utility maximization problem with random endowment and indifference prices is studied for a sequence of financial markets in an incomplete Brownian setting. Our novelty lies in the nonequivalence of markets, in which the volatility of asset prices (as well as the drift) varies. Degeneracies arise from …

2014-10-03abs ↗pdf ↗

The effectiveness of utility-maximization techniques for portfolio management relies on our ability to estimate correctly the parameters of the dynamics of the underlying financial assets. In the setting of complete or incomplete financial markets, we investigate whether small perturbations of the market coefficient pr…

2007-06-04abs ↗pdf ↗

New framework for fair online allocation in continuous time with deadlines.

problem Fair allocation under deadlines in continuous-time online learning.
method Continuous-time utility maximization, dual ascent optimization for time averages.
result Achieves ildeO(B1/2) ilde{O}(B^{-1/2}) regret bound in the absence of statistical knowledge.

A note on utility maximization with costs, proving trading strategies.

problem Utility maximization with proportional transaction costs and stability of optimal portfolios.
method Proof of a limit theorem using a dual approach.
result Established a uniqueness result for optimal trading strategies.

New algorithm tackles unknown utility network resource allocation.

problem Maximizing network utility with unknown agent utilities.
method Modeling as a bandit problem, proposing algorithms for resource allocation.
result Proposed algorithms are optimal when all agents have the same utility.

In the large financial market, which is described by a model with countably many traded assets, we formulate the problem of the expected utility maximization. Assuming that the preferences of an economic agent are modeled with a stochastic utility and that the consumption occurs according to a stochastic clock, we obta…

2014-03-24abs ↗pdf ↗

Bayesian decision theory outlines a rigorous framework for making optimal decisions based on maximizing expected utility over a model posterior. However, practitioners often do not have access to the full posterior and resort to approximate inference strategies. In such cases, taking the eventual decision-making task i…

2019-02-02abs ↗pdf ↗

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…

2017-12-20abs ↗pdf ↗

Closed-form optimal portfolios for exponential utility in small/large markets.

problem Optimal portfolios maximizing exponential utility in small/large financial markets.
method Closed-form expressions for optimal portfolios in small markets, convergence to large market optimal utility, numerical procedure for general utility functions.
result Optimal utility in large markets converges to optimal utility in small markets, requiring infinite diversification.

Study utility maximization with delayed information in continuous time Gaussian markets.

problem Maximizing utility with delayed information in continuous time Gaussian markets.
method Purely probabilistic approach based on Radon-Nikodym derivatives of Gaussian measures.
result Solution for optimal control and value in a specific Gaussian framework.