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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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219437656874 · Jun 202019922001200920172026
48 results for power utility function

Combines absolute and relative wealth in portfolio optimization with power utility functions.

problem Optimizing portfolios with both absolute and relative wealth considerations.
method Integrates power utility functions for absolute and relative wealth, considering multiple benchmarks.
result Obtains an explicit solution for portfolio optimization combining absolute and relative wealth.

Spectral risk measures (SRMs) are risk measures that take account of user riskaversion, but to date there has been little guidance on the choice of utility function underlying them. This paper addresses this issue by examining alternative approaches based on exponential and power utility functions. A number of problems…

2011-03-29abs ↗pdf ↗

Study examines how liquidity constraints impact optimal retirement decisions.

problem Impact of liquidity constraints on optimal retirement decisions.
method Analytical solution using duality method with different liquidity constraints.
result Sensitivity analysis reveals the effect of liquidity constraints on retirement decisions.

Approximations to utility indifference prices are provided for a contingent claim in the large position size limit. Results are valid for general utility functions on the real line and semi-martingale models. It is shown that as the position size approaches infinity, the utility function's decay rate for large negative…

2012-02-17abs ↗pdf ↗

Paper tackles time inconsistency in portfolio management with stochastic volatility and power utility.

problem Time inconsistency in portfolio management with stochastic volatility and power utility.
method Extended Hamilton Jacobi Bellman (HJB) equation, fixed point iteration, and linear parabolic PDE.
result Subgame perfect strategies are characterized and solved through numerical experiments.

Study optimal strategies for insurer's dividends, investments, and liabilities.

problem Maximize insurer's utility of dividend payments over an infinite horizon.
method Perturbation approach to obtain optimal strategy and value function in closed form.
result Obtained optimal strategy and value function for log and power utility.

We adress the maximization problem of expected utility from terminal wealth. The special feature of this paper is that we consider a financial market where the price process of risky assets can have a default time. Using dynamic programming, we characterize the value function with a backward stochastic differential equ…

2008-11-28abs ↗pdf ↗

Optimal portfolios are formed by combining momentum, size, and volatility characteristics, enhancing utility for all investors.

problem Estimation error in forming optimal portfolios from characteristics.
method Maximizing an in-sample loss function that is more concave than the utility function, linking weights to characteristics.
result Optimal portfolios with significantly higher certainty equivalents than benchmarks for all investors.

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…

2014-05-03abs ↗pdf ↗

We study utility maximization problem for general utility functions using dynamic programming approach. We consider an incomplete financial market model, where the dynamics of asset prices are described by an RdR^d-valued continuous semimartingale. Under some regularity assumptions we derive backward stochastic partial…

2008-06-02abs ↗pdf ↗

In this paper, we solve the time inconsistent portfolio selection problem by using different utility functions with a moving target as our constraint. We solve this problem by finding an equilibrium control under the given definition as our optimal control. We firstly derive a sufficient equilibrium condition for secon…

2014-02-27abs ↗pdf ↗

We consider a Bayesian financial market with one bond and one stock where the aim is to maximize the expected power utility from terminal wealth. The solution of this problem is known, however there are some conjectures in the literature about the long-term behavior of the optimal strategy. In this paper we prove now t…

2017-03-13abs ↗pdf ↗

Develops deep learning methods for solving S-shaped utility maximisation problems.

problem Optimizing portfolios with S-shaped utility and random benchmarks.
method Uses deep learning and duality methods to solve the Hamilton-Jacobi-Bellman equation and adjoint equation.
result Demonstrates the accuracy of deep learning methods for non-concave utility maximisation problems.

We give explicit solutions for utility maximization of terminal wealth problem u(XT)u(X_T) in the presence of Knightian uncertainty in continuous time [0,T][0,T] in a complete market. We assume there is uncertainty on both drift and volatility of the underlying stocks, which induce nonequivalent measures on canonical space o…

2019-09-11abs ↗pdf ↗

This paper considers a utility maximization and optimal asset allocation problem in the presence of a stochastic endowment that cannot be fully hedged through trading in the financial market. After studying continuity properties of the value function for general utility functions, we rely on the dynamic programming app…

2014-06-24abs ↗pdf ↗

Spectral risk measures are attractive risk measures as they allow the user to obtain risk measures that reflect their risk-aversion functions. To date there has been very little guidance on the choice of risk-aversion functions underlying spectral risk measures. This paper addresses this issue by examining two popular …

2011-03-29abs ↗pdf ↗

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.

The paper calculates how fast optimal investment strategies approach CRRA strategies in stochastic factor models.

problem Understanding convergence rates of optimal investment strategies in stochastic factor models.
method Analyzes optimal feedback functions in nonlinear and quadratic term structure models, considering decay of bond prices and power-like utility at high wealth levels.
result Convergence rates of optimal investment strategies to CRRA strategies are determined by bond price decay and power-like utility behavior.

We consider the problem of utility maximization for small traders on incomplete financial markets. As opposed to most of the papers dealing with this subject, the investors' trading strategies we allow underly constraints described by closed, but not necessarily convex, sets. The final wealths obtained by trading under…

2005-08-24abs ↗pdf ↗

Study optimal trading strategies with expert signals in a hidden Gaussian drift market.

problem Optimal trading strategies in a financial market with hidden Gaussian drift and expert signals.
method Transformed power utility maximization problem into full information problem using Kalman filter estimates of the drift.
result Closed-form solutions for value function and optimal trading strategy derived.

In this paper, we propose a new perspective for quantizing a signal and more specifically the channel state information (CSI). The proposed point of view is fully relevant for a receiver which has to send a quantized version of the channel state to the transmitter. Roughly, the key idea is that the receiver sends the r…

2019-04-02abs ↗pdf ↗

Loss-calibrated EP improves Bayesian decision-making by focusing on utility-sensitive posterior approximations.

problem Bayesian decision-making under asymmetric utility functions.
method Loss-calibrated expectation propagation (Loss-EP) that tilts the posterior towards higher utility decisions.
result Loss-EP can capture useful information for decision-making under asymmetric penalties.