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arXiv research

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.

168,657 papers · 148 categories

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15304459 · Jun 202019922001200920172026
48 results for incomplete preferences

Researchers develop multi-utility representations for incomplete preferences linked to risk measures.

problem Handling incomplete preferences induced by set-valued risk measures.
method Established dual representations of set-valued risk measures to create parsimonious and well-behaved multi-utility representations.
result Unified dual representations of set-valued risk measures, linking them to scalar risk measures.

Paper extends RUMs with features to handle incomplete preferences and proves identifiability.

problem Learning preferences from incomplete and possibly noisy data.
method Generalized Mixture of Random Utility Models with features, proving identifiability and consistency of MLE.
result Proves consistency of Maximum Likelihood Estimation (MLE) for PL with features under certain conditions.

This paper solves optimal consumption-investment problems with time-varying preferences.

problem Optimal consumption-investment problems under time-varying incomplete preferences.
method Develops a martingale-type solution in a topological vector space, using stochastic processes and scalarization methods.
result Optimal investment policies are set-valued, with selectors decomposed into four components.

Given an incomplete ratings data over a set of users and items, the preference completion problem aims to estimate a personalized total preference order over a subset of the items. In practical settings, a ranked list of top-kk items from the estimated preference order is recommended to the end user in the decreasing …

2019-03-17abs ↗pdf ↗

Introduces RPU to explain randomization preference in dynamic settings.

problem Explains preference for randomization in dynamic investment problems.
method Introduces recursive perturbed utility (RPU) to incorporate randomization preference.
result Proves RPU-optimal portfolio policy is Gaussian and can be expressed in closed form.

We study existence and uniqueness of continuous-time stochastic Radner equilibria in an incomplete market model among a group of agents whose preference is characterized by cash invariant time-consistent monetary utilities. An assumption of "smallness" type is shown to be sufficient for existence and uniqueness. In par…

2015-05-27abs ↗pdf ↗

The paper analyzes investment and consumption strategies under uncertain market conditions.

problem Investment and consumption under drift and volatility uncertainties.
method Randomization approach to construct robust preferences and strategies.
result Developed optimal and robust investment and consumption strategies remain valid in the physical market.

The paper solves portfolio selection for complex preferences in continuous time.

problem Dynamic portfolio selection for nonlinear preferences with time inconsistency.
method Stochastic maximum principle and verification theorems for equilibrium strategies.
result Equilibrium strategies derived in closed form for CRRA and CARA preferences.

Study optimal consumption and investment for investors with Epstein-Zin preferences.

problem Optimal consumption and investment for investors with Epstein-Zin preferences in an incomplete market.
method Variational characterisation and direct method to prove existence of optimal policies.
result Existence and uniqueness of optimal consumption and investment policies.

The paper refutes standard asset pricing models and introduces new theories.

problem Inaccuracies in standard asset pricing models.
method Introduces new theories and empirical tests to explain asset pricing anomalies.
result New theories explain why standard models are inaccurate and provide insights.

New method accounts for hidden context in preference learning for RLHF models.

problem Incomplete data with hidden context affects RLHF model outcomes.
method Distributional Preference Learning (DPL) methods estimate hidden context distributions.
result DPL methods reduce RLHF vulnerabilities by accounting for hidden context.

A new method improves recommendation accuracy by learning from multiple networks and time-dependent user preferences.

problem Incomplete user profiles and dynamic user preferences degrade recommender quality.
method A cross-network time-aware recommender that learns from multiple source networks and develops current user models.
result The proposed solution achieves superior performance in accuracy, novelty, and diversity.

Study dynamic asset allocation in incomplete markets using game theory and nonlocal BSDEs.

problem Dynamic mean-variance asset allocation in general incomplete markets with non-exponential discounting.
method Game-theoretic approach, decomposition into myopic and hedging strategies, nonlocal BSDEs, fixed-point theorem.
result Well-posedness of solutions to BSDEs, existence of equilibrium control policy.

The paper challenges the assumption of a unique global time in financial markets, highlighting market incompleteness.

problem The assumption of a unique global time in financial markets is challenged.
method The paper contrasts event-time, renewal, point-process, and order-flow descriptions of financial markets.
result Non-uniqueness of time leads to a more foundational form of market incompleteness.

Study forward investment performance in semimartingale markets with stochastic factors.

problem Investigate forward investment performance in incomplete semimartingale markets with power risk preferences and stochastic integrated factors.
method Develop necessary and sufficient conditions for FIPP existence, use integral representations, and solve ill-posed HJB equations.
result Explicit constructions for time-monotone FIPPs in semimartingale models, generalizing from Brownian to semimartingale markets.

Study optimal control strategy for hedge funds managers with PSAHARA utility family.

problem Optimizing risk and reward in incomplete markets with non-monotone risk aversion and convex compensation.
method Introduced PSAHARA utility family to model non-monotone risk aversion and convex compensation. Proved concavification techniques for non-concave utility functions. Derived explicit optimal control strategy.
result PSAHARA utility induces risk-taking behavior even with convex compensation, leading to high returns and volatility.

This paper studies the problem of optimal investment with CRRA (constant, relative risk aversion) preferences, subject to dynamic risk constraints on trading strategies. The market model considered is continuous in time and incomplete. the prices of financial assets are modeled by Itô processes. The dynamic risk constr…

2011-06-09abs ↗pdf ↗

Study on hedging and valuation of basis risk in incomplete markets with partial information.

problem Hedging and valuation of European and American claims in an incomplete market with correlated assets and partial information.
method Stochastic control and partial information scenario, forward indifference valuation, dual representation, PDE approach.
result Derivation of optimal hedging strategy and forward indifference price representation for claims.

In this paper, we propose an equilibrium pricing model in a dynamic multi-period stochastic framework with uncertain income streams. In an incomplete market, there exist two traded risky assets (e.g. stock/commodity and weather derivative) and a non-traded underlying (e.g. temperature). The risk preferences are of expo…

2012-05-28abs ↗pdf ↗

This paper considers the optimal portfolio selection problem in a dynamic multi-period stochastic framework with regime switching. The risk preferences are of exponential (CARA) type with an absolute coefficient of risk aversion which changes with the regime. The market model is incomplete and there are two risky asset…

2011-02-24abs ↗pdf ↗

This paper formulates a model of utility for a continuous time framework that captures the decision-maker's concern with ambiguity about both volatility and drift. Corresponding extensions of some basic results in asset pricing theory are presented. First, we derive arbitrage-free pricing rules based on hedging argumen…

2013-01-20abs ↗pdf ↗

We consider thin incomplete financial markets, where traders with heterogeneous preferences and risk exposures have motive to behave strategically regarding the demand schedules they submit, thereby impacting prices and allocations. We argue that traders relatively more exposed to market risk tend to submit more elasti…

2017-07-17abs ↗pdf ↗

New method clusters strong and weak views effectively, improving performance by up to 40%.

problem Clustering incomplete multi-view data with unbalanced incompleteness.
method View evolution scheme and weighted multi-view subspace clustering.
result Improves clustering performance by up to 40% on three metrics.

Investor optimizes wealth in a market with non-traded endowment, deriving expansions up to second order.

problem Optimizing wealth in an incomplete financial market with a non-traded endowment.
method Duality techniques and Kunita-Watanabe projections for deriving expansions up to second order.
result Derives expansions of the primal value function and optimal wealth process up to second order with respect to the non-traded endowment units.

This paper solves the consumption-investment problem under Epstein-Zin preferences on a random horizon. In an incomplete market, we take the random horizon to be a stopping time adapted to the market filtration, generated by all observable, but not necessarily tradable, state processes. Contrary to prior studies, we do…

2019-03-21abs ↗pdf ↗

Develops GNNs for incomplete graphs, improving learning from missing node attributes.

problem Learning from incomplete graphs with missing node attributes.
method Introduces PaGNNs with novel partial aggregation functions for incomplete graph data.
result Demonstrates effectiveness and efficiency of PaGNNs on various datasets.