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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.

169,051 papers · 148 categories

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126253379505 · Jun 202019922001200920182026
48 results for subsidy effects

A new ride-hailing subsidy system uses deep causal networks to estimate consumer elasticity.

problem Estimating consumer elasticity with subsidies in ride-hailing industry.
method Introduces a consumer subsidizing system using deep causal networks to address confounding effects.
result Effective in estimating the uplift effect of subsidies without confounding.

Study evaluates UK CDC schemes, finding intergenerational cross-subsidies in flat-accrual schemes and dynamic-accrual schemes can reduce but not eliminate them.

problem Intergenerational cross-subsidies in UK CDC schemes, particularly in flat-accrual schemes.
method Comparison of flat-accrual and dynamic-accrual CDC schemes, analysis of performance and level of cross-subsidies.
result Dynamic-accrual schemes can reduce but not eliminate intergenerational cross-subsidies, while flat-accrual schemes often have significant cross-subsidies.

Subsidized insurance reduces poverty by providing social benefits and lowering government costs.

problem Reducing poverty through effective social protection mechanisms.
method Modeling household capital dynamics under four insurance frameworks (uninsured, insured, insured with subsidies, insured with flexible premiums) to assess poverty reduction and governmental costs.
result Subsidized insurance schemes provide maximum social benefits while reducing governmental costs, effectively reducing poverty.

Privacy subsidy found in market trading with noisy direction signals.

problem Analyzing welfare and bid-ask spread in a market with privacy mechanisms.
method Closed-form derivation of bid-ask spread and welfare under flip-noise direction observation.
result Privacy subsidy of μηΔμηΔ from liquidity pool to traders, robust across models.

Continuous-time Kyle model shows privacy subsidy from noise-perturbed order flow.

problem Quantifying break-even fees for committed-AMM exchanges under privacy-aggregated information.
method Extended Nakamura's (2026) single-period result to continuous-time, observing order flow perturbed by Brownian noise.
result Cumulative privacy subsidy is identified as equivalent to Loss-Versus-Rebalancing in price observation gap.

The paper examines how social inequality affects algorithmic classification outcomes.

problem Social inequality impacts algorithmic classification outcomes.
method Adapting models of strategic manipulation to account for social inequality and subsidy effects.
result Subsidizing disadvantaged groups can paradoxically harm both groups and the learner.

Privacy-preserving crypto exchanges adjust prices based on Gaussian noise.

problem Ensuring fair pricing in privacy-preserving cryptocurrency exchanges.
method Derive Kyle equilibrium with Gaussian noise perturbation, rescaling price-impact and strategy factors.
result Identify a privacy subsidy as a transfer from LP pool to traders, invariant to noise.

COF algorithm minimizes cost in multi-armed bandits with known costs and reward constraints.

problem Minimizing cost while meeting a minimum reward requirement in uncertain environments.
method COF algorithm that intelligently combines samples from all arms to gauge feasibility and minimize cost.
result COF achieves instance-dependent upper bounds on cumulative cost and quality regret.

The paper analyzes MENA region's energy consumption and policy needs for renewable energy.

problem High dependency on oil and low renewable energy penetration in MENA region.
method Analysis of World Bank datasets and policy portfolio in MENA countries.
result MENA region has high potential for solar energy but faces challenges in decoupling economic growth from energy consumption.

The paper explores fairness, welfare, and equity in personalized pricing across various applications.

problem Interplay of fairness, welfare, and equity in personalized pricing based on customer features.
method Comprehensive literature review and observational metrics without underlying valuation distribution assumptions.
result Personalized pricing can expand access, improve welfare, and increase revenue or budget utilization.

The study uses a multi-armed bandit model to analyze and mitigate hiring discrimination.

problem Hiring discrimination due to insufficient data on worker skill and characteristics.
method Multi-armed bandit model to simulate firms' learning process and policy solutions.
result Temporary affirmative actions effectively alleviate discrimination caused by data insufficiency.

A government has to finance a risk for its population. It shares the charges among the population with a fixed scale based on economic criteria. Various organisms have to collect and to redistribute fairly the subsidies. Under these conditions, when the size of the organisms is varied, the distribution's laws of the cr…

2014-01-13abs ↗pdf ↗

Tax systems ensure sustainable economic development by adjusting production technologies and gross output volumes.

problem Ensuring sustainable economic development through optimal tax systems.
method Explicit formulas and mathematical proofs for tax systems based on production technologies and gross output volumes.
result The vector of gross output must belong to the interior of the cone formed by the columns of the total cost matrix under perfect taxation systems.

Study finds actuarial unfairness in China's pension system, proposing income-dependent annuitization rules.

problem Actuarial fairness in China's NDC pension system when mortality differs across income groups.
method Developed a mortality-differentiated Lee-Carter framework with group-specific baseline mortality schedules and a common period effect, estimated using national and subgroup data.
result Substantial actuarial unfairness in the current age-only divisor, with a reverse transfer from poorer to richer retirees.

AI-driven tax policies improve economic equality and productivity.

problem Lack of appropriate economic data and limited opportunity to experiment.
method Two-level deep reinforcement learning approach to learn dynamic tax policies from observational data.
result AI-driven tax policies improve the trade-off between equality and productivity by 16%.

This paper improves bond market making by adjusting hit-ratios for client flow quality.

problem Economic misleading of raw hit-ratios in corporate bond market making.
method Stochastic-control framework with residual-quality-adjusted hit-ratio.
result Optimal quotes decompose into various components, improving service/economics frontier.

Various types of structures that enable a group of individuals to pool their mortality risk have been proposed in the literature. Collectively, the structures are called pooled annuity funds. Since the pooled annuity funds propose different methods of pooling mortality risk, we investigate the connections between them …

2013-11-20abs ↗pdf ↗

Many real-world systems can be studied in terms of pattern recognition tasks, so that proper use (and understanding) of machine learning methods in practical applications becomes essential. While a myriad of classification methods have been proposed, there is no consensus on which methods are more suitable for a given …

2016-12-26abs ↗pdf ↗

The leverage effect weakly impacts return distributions, especially for small firms.

problem The leverage effect's impact on return distributions is inconsistent and puzzling.
method Analyzed the determinants of return distributions and proposed an indirect method to measure the interaction effect.
result The interaction effect between leverage and mean-reversion is weak and impacts return distributions mainly for small firms.

The Kalinin effectivity is studied and applied to compactifications and Hilbert squares.

problem Understanding Kalinin effectivity in compactifications and its applications.
method Definition, construction methods, and analysis of Kalinin effectivity in various compactifications.
result Wonderful compactifications of hyperplane arrangements and configuration spaces are Kalinin effective.

New method estimates treatment effects in network data, accounting for spillover effects.

problem Treatment effect estimation in networks with spillover effects.
method Augmented inverse probability weighting (AIPW) with cross-fitting and machine learning.
result Semiparametric treatment effect estimator converges at parametric rate and follows Gaussian distribution.

The paper clarifies the distinction between CATE and ITE under ignorability assumptions.

problem Confusion between CATE and ITE hinders personalized effect estimation.
method Clarifies the distinction between CATE and ITE under ignorability assumptions.
result CATE and ITE are not necessarily the same under ignorability assumptions.

GADGET framework decomposes global feature effects using recursive partitioning.

problem Misleading global feature effects when feature interactions are present.
method Generalized additive decomposition of global effects (GADGET) based on recursive partitioning.
result Minimizes interaction-related heterogeneity of local feature effects.

A new method purifies interaction effects in models to improve interpretability.

problem Interaction effects can be misinterpreted as separate main effects, complicating model interpretation.
method Proposes pure interaction effects and a Functional ANOVA decomposition algorithm to identify and isolate interaction effects.
result Identifies and separates interaction effects from main effects, showing large disparities in model interpretation.

A new method estimates treatment effects in mixed groups, improving accuracy.

problem Estimating treatment effects in mixed groups with heterogeneous responses.
method PCM (pre-cluster and merge) approach for nonparametric estimation.
result Asymptotic consistency and significant improvement in accuracy over existing methods.

Study estimates heterogeneous principal causal effects with binary treatments and intermediate variables.

problem Estimating subgroup effects within strata defined by potential values of an intermediate variable.
method Proposes a framework for estimating and forming confidence intervals for heterogeneous principal causal effects under principal ignorability assumption. Develops several estimators with varying robustness properties.
result Established large-sample theory and analyzed bias contributions of each approach.

Study develops method for estimating causal effects in continuous variables.

problem Lack of methods for estimating causal effects in continuous variables.
method Develops a method independent of data generating models for continuous variable interventions.
result Preserves identifiability of data and applies to any generating models.

ICA accurately estimates treatment effects even with confounders.

problem Estimating treatment effects in the presence of confounding variables.
method Uses Independent Component Analysis (ICA) to identify latent sources and estimate mixing coefficients.
result Linear ICA can consistently estimate multiple treatment effects, even with Gaussian confounders, and is more sample-efficient than Orthogonal Machine Learning (OML).

Method improves treatment effect estimation in randomized experiments.

problem Estimating distributional treatment effects in randomized experiments.
method Distributional regression framework with machine learning for variance reduction.
result The proposed method reduces variance of distributional treatment effect estimators.