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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.

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24487296 · May 202619922001200920172026
48 results for surplus description length

New methods evaluate data representations by complexity of low-loss predictor learning.

problem Evaluating quality of data representations for downstream tasks.
method Surplus Description Length (SDL) and ε Sample Complexity (εSC) methods.
result Methods measure the information needed to approximate optimal predictor up to specified tolerance.

We use the theory of coherent measures to look at the problem of surplus sharing in an insurance business. The surplus share of an insured is calculated by the surplus premium in the contract. The theory of coherent risk measures and the resulting capital allocation gives a way to divide the surplus between the insured…

2018-10-28abs ↗pdf ↗

Optimizes capital structure for life insurance companies with surplus participation.

problem Determining the optimal participation rate in life insurance contracts.
method Adapted Leland's dynamic capital structure model to life insurance context.
result Optimal participation rate is highly sensitive to contract duration and tax rate.

The study examines how different interpolation methods affect the decomposition of life insurance surplus.

problem The impact of different interpolation methods on the decomposition of life insurance surplus.
method The study uses the IASU decomposition method to analyze the effects of different interpolation methods (Lee-Carter and linear) on the surplus decomposition.
result Lee-Carter and linear interpolation yield almost identical decompositions, while constant approximations result in different decompositions.

Optimal dividend payout strategy found for Brownian risk model with ratcheting constraint.

problem Optimal dividend payout from a surplus process governed by Brownian motion with drift under ratcheting constraint.
method Solved a two-dimensional optimal control problem using viscosity solutions of Hamilton-Jacobi-Bellman equations.
result Threshold and curve strategies identified as optimal for different dividend rate sets.

Study shows LLC correlates with neural network compressibility.

problem Evaluating limits of neural network compression.
method Extended minimum description length principle using singular learning theory.
result Complexity estimates based on LLC are linearly correlated with compressibility.

The theory of acceptance sets and their associated risk measures plays a key role in the design of capital adequacy tests. The objective of this paper is to investigate, in the context of bounded financial positions, the class of surplus-invariant acceptance sets. These are characterized by the fact that acceptability …

2014-01-14abs ↗pdf ↗

This paper presents a systematic study of the notion of surplus invariance, which plays a natural and important role in the theory of risk measures and capital requirements. So far, this notion has been investigated in the setting of some special spaces of random variables. In this paper we develop a theory of surplus …

2017-07-16abs ↗pdf ↗

The study quantifies the information needed for causal queries at different levels of Pearl's hierarchy.

problem How much additional information is needed for interventional and counterfactual queries compared to observational queries?
method Formalized via query-class description length, using Kolmogorov complexity of answer oracles induced by SCMs.
result Binary acyclic SCMs show a quadratic gap between observational and interventional descriptions, and a logarithmic gap between interventional and counterfactual descriptions.

The paper analyzes insurance risk with Parisian ruin and capital injection.

problem Analyzing insurance risk with Parisian ruin and capital injection.
method Using fluctuation and excursion theory of spectrally negative Levy processes.
result Distributional identities and ruin probabilities are derived.

New method improves bivariate causal discovery by accurately estimating cause variable complexity.

problem Improper estimation of cause variable complexity in current MDL-based methods.
method Rate-distortion MDL (RDMDL) using information dimension for cause variable complexity estimation.
result RDMDL achieves competitive performance on Tübingen dataset.

We study a singular stochastic control problem faced by the owner of an insurance company that dynamically pays dividends and raises capital in the presence of the restriction that the surplus process must be above a given dividend payout barrier in order for dividend payments to be allowed. Bankruptcy occurs if the su…

2019-02-17abs ↗pdf ↗

New method estimates consumer surplus from randomized pricing data.

problem Estimating consumer surplus from observational data, especially in AI-driven pricing.
method Cumulative Propensity Weights (CPW) and Augmented CPW (ACPW) estimators.
result Validated methods for estimating consumer surplus from randomized pricing data.

Optimal reinsurance when Value at Risk and expected surplus is balanced through their ratio is studied, and it is demonstrated how results for risk-adjusted surplus can be utilized. Simplifications for large portfolios are derived, and this large-portfolio study suggests a new condition on the reinsurance pricing regim…

2019-12-09abs ↗pdf ↗

We study an optimal investment control problem for an insurance company. The surplus process follows the Cramer-Lundberg process with perturbation of a Brownian motion. The company can invest its surplus into a risk free asset and a Black-Scholes risky asset. The optimization objective is to minimize the probability of…

2015-02-08abs ↗pdf ↗

Critical trajectories in a sphere are found for a specific bending functional.

problem Finding closed trajectories in a sphere for a specific bending functional.
method Existence of infinitely many closed trajectories shown for a given Lagrange multiplier.
result Existence of closed trajectories dependent on a pair of relatively prime natural numbers.

Study shows Bitcoin mining with surplus electricity can boost KEPCO's financial stability.

problem Improving energy resource efficiency and reducing KEPCO's debt.
method Utilized surplus electricity for Bitcoin mining using Antminer S21 XP Hyd, analyzed with Random Forest Regressor and Long Short-Term Memory models.
result Bitcoin mining with surplus electricity generates economic revenue, minimizes energy loss, and resolves payment issues for KEPCO.

We consider an insurance company whose surplus is represented by the classical Cramer-Lundberg process. The company can invest its surplus in a risk free asset and in a risky asset, governed by the Black-Scholes equation. There is a constraint that the insurance company can only invest in the risky asset at a limited l…

2011-12-17abs ↗pdf ↗

This paper solves an optimal dividend payout problem with ratcheting constraints using a novel method.

problem Optimal dividend payout under ratcheting constraints for a Brownian motion surplus process.
method Novel partial differential equation method to solve the Hamilton-Jacobi-Bellman (HJB) equation.
result Existence and uniqueness of solution in stronger functional spaces, strict monotonicity, boundedness, and CC^\infty-smoothness of the free boundary.

DL/FBF improves GPSR solutions by selecting compact, generalising expressions.

problem Overfitting and structural bloat in symbolic regression with genetic programming.
method Description length (DL) and fractional Bayes factor (FBF) criteria for selecting compact, generalising expressions.
result DL/FBF post-selection improves test performance compared to AIC/BIC baseline.

Efficiently estimates SAGE values using causal structure learning.

problem Computational infeasibility of exact SAGE calculations.
method Uses causal structure learning to identify conditional independencies and accelerate SAGE approximation.
result Empirically demonstrates efficient and accurate estimation of SAGE values.

Study improves neural network performance in sequential learning for image classification.

problem Improving neural network performance in sequential learning for image classification.
method Evaluation of approaches for computing prequential description lengths, proposing forward-calibration and replay-streams.
result Improved description lengths for image classification datasets, outperforming previous results.

CDL index improves clustering validation for non-convex data.

problem Selecting clustering algorithms and hyperparameters without labeled data.
method CDL uses compactness, centers, and covariances to compute a probabilistic description length bound.
result CDL outperforms conventional CVIs on synthetic and image benchmarks.

Paper explores how risk-averse individuals' willingness to pay for insurance varies with risk probability.

problem Understanding how risk-averse individuals' willingness to pay for insurance varies with risk probability.
method Analyzes willingness to pay (WTP) for partial risk reduction within the dual theory of decision.
result In dual theory, reducing the probability of risk and providing insurance can be complementary if the surplus increases with risk reduction.

Paper analyzes robust strategies in a pension plan game with ambiguous financial markets.

problem Analyzing robust strategies in a defined benefit pension plan game with ambiguous financial markets.
method Formulated and solved two robust non-zero-sum games using stochastic dynamic programming.
result Explicit forms and optimality of the solutions are shown for the firm and union.