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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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10203040 · Dec 202519922001200920172026
48 results for green finance

New eco-systemic prudential policies aim to finance green companies, reducing systemic financial risk.

problem Insufficient financing for green companies despite available savings and monetary management.
method Reorient corporate accounting towards socio-environmental solvency, facilitating access with public guarantees.
result Green financing increases, reducing systemic financial risk and promoting less leveraged investments.

In this note we review the basic mathematical ideas used in finance in the language of modern physics. We focus on discrete time formalism, derive path integral and Green's function formulas for pricing. We also discuss various risk mitigation methods.

2020-01-26abs ↗pdf ↗

A new approach for green investing in Indian markets considers environmental factors.

problem Identifying and managing climate risk in sustainable investing.
method Combining ESG ratings with modern portfolio theory and scenario analysis.
result The green portfolio performs better than market returns, highlighting the importance of climate risk.

AI helps assess nature-related financial risks for financial institutions.

problem Challenges in evaluating nature-related risks due to large data volume and complexity.
method Uses AI to address data gaps, uncertainty, and complex systems.
result Potential AI solutions for two use cases: beef supply and water utility.

The paper explores how innovative financing solutions boost Moroccan businesses' performance.

problem Market volatility, ecological transitions, and technological change pose challenges to business sustainability.
method Examines innovative financing solutions like venture capital, green finance, crowdfunding, and blockchain.
result Embracing innovative financial strategies can transform business challenges into opportunities.

This study finds ESG rating disagreement reduces corporate productivity, especially in certain types of firms.

problem The impact of ESG rating disagreement on corporate productivity.
method Analysis of A-share listed companies data from 2015 to 2022 using XGBoost regression and SHAP.
result ESG rating disagreement reduces corporate productivity, especially in certain types of firms.

Formula for Hadamard coefficients from Green's operators on spacetimes.

problem Calculating Hadamard coefficients from Green's operators on spacetimes.
method Developed formulas for diagonal values and integrals over the diagonal of Hadamard coefficients.
result Formulated analogues of Hadamard expansions and resolvents for Green's operators.

Green stocks show less factor exposure heterogeneity compared to brown stocks.

problem Exploring differences in factor exposure between green and brown stocks.
method Examined S&P 500 firms grouped by greenhouse gas emissions, analyzing factor exposure over 2014-2020.
result Green stocks have less factor exposure heterogeneity than brown stocks, except for the value factor.

Green functions on stationary varifolds established with inequalities and convergence results.

problem Establishing Green functions on stationary varifolds with inequalities and convergence.
method Extending Grüter and Widman's method, constructing Green functions, using local Harnack inequality.
result Green functions converge for sequences of stationary varifolds converging with multiplicity one.

The paper derives expansions for Green's operators and resolvents using Hadamard methods.

problem Analyzing normally hyperbolic operators and their Green's functions.
method Hadamard expansions for powers of Green's operators and resolvents.
result Derives expansions involving Hadamard coefficients for advanced/retarded Green's operators.

The paper discusses methods to compute Green's function on algebraic surfaces using Schottky uniformization.

problem Computing Green's function on algebraic surfaces using Schottky uniformization.
method Investigates convergence of deformations of a formula related to Green's function.
result Provides insights into the geometric interpretation of the formula for Green's function.

A regression algorithm uses Green's function and covariance matrix for predictive distributions.

problem Regression and uncertainty quantification for machine learning.
method Green's function theory, Bayesian approach, covariance matrix of normalized Green's function.
result The covariance matrix provides predictive distributions with mean and confidence intervals.

On compact surfaces, a Green-Wasserstein inequality cannot be improved without the sqrt(log n) factor.

problem Can the Green-Wasserstein inequality be improved without the sqrt(log n) factor?
method Contradiction proof using second-moment estimates and semi-discrete random matching asymptotics.
result It is impossible to remove the sqrt(log n) factor in the inequality on any compact connected surface.

We study several quantities associated to the Green's function of a multiply connected domain in the complex plane. Among them are some intrinsic properties such as geodesics, curvature, and L2L^2-cohomology of the capacity metric and critical points of the Green's function. The principal idea used is an affine scaling…

2016-05-14abs ↗pdf ↗

The paper analyzes risk spillovers between AI ETFs, AI tokens, and green markets.

problem Risk spillovers among AI ETFs, AI tokens, and green markets.
method R2 decomposition method
result AI ETFs and clean energy act as risk transmitters, while AI tokens and green assets act as receivers.

Green functions for GJMS operators on spheres derived, linking geometry and rigidity.

problem Deriving Green functions for GJMS operators on spheres.
method Explicit representation formulae derived using Gegenbauer polynomials.
result Spheres uniquely characterized by their Green functions, with strong rigidity theorems for n=3,4,5n=3,4,5.

Survey on rigidity and almost rigidity of Green functions in non-negative Ricci curvature spaces.

problem Rigidity and almost rigidity of Green functions in non-negative Ricci curvature spaces.
method Survey and observation on Cheeger-Yau inequality on RCD spaces.
result Observations on the Cheeger-Yau inequality and its applications.

Study asymptotics of Poisson kernel and Green's functions for fractional conformal Laplacian.

problem Asymptotics of Poisson kernel and Green's functions for fractional conformal Laplacian.
method Sharp expansions derived for the Poisson kernel and Green's functions near singularities.
result Sharp expansions of the Green's functions solve the first part of Kim-Musso-Wei's conjecture.

Discrete Green's functions are the inverses or pseudo-inverses of combinatorial Laplacians. We present compact formulas for discrete Green's functions, in terms of the eigensystems of corresponding Laplacians, for products of regular graphs with or without boundary. Explicit formulas are derived for the cycle, torus, a…

2003-09-04abs ↗pdf ↗

Proves Green function rigidity for specific operators and obtains new ADM mass formula.

problem Proving Green function rigidity for specific operators and obtaining new ADM mass formula.
method Positive mass theorem and positive energy theorem for Paneitz operator.
result Obtained new formula for the ADM mass of asymptotically flat hypersurfaces.

Central limit theorem for Green metrics on hyperbolic groups.

problem Proving a central limit theorem for Green metrics on hyperbolic groups.
method Proving a central limit theorem for Green metrics on hyperbolic groups using probability measures and ordering elements.
result Proved a central limit theorem for Green metrics on hyperbolic groups.

In this article we study the role of the Green function for the Laplacian in a compact Riemannian manifold as a tool for obtaining well-distributed points. In particular, we prove that a sequence of minimizers for the Green energy is asymptotically uniformly distributed. We pay special attention to the case of locally …

2017-02-02abs ↗pdf ↗

Low redispatch prices boost green hydrogen production cost, encouraging electrolyzer siting.

problem Uncertainty in redispatch power availability and its impact on green hydrogen production cost.
method Historic redispatch time series analysis and power purchase scenarios evaluation.
result Low price levels can lead to notable production cost reductions, incentivizing electrolyzer siting.

The study establishes inequalities for functions on manifolds using Green function estimates.

problem Developing inequalities for functions on manifolds.
method Used integral representations and uniform estimates for Green functions.
result Proved LpL^p Sobolev-type and Poincaré-type inequalities for functions on real and complex manifolds.

GF-Net learns Green's functions for linear reaction-diffusion equations.

problem Learning Green's functions for linear reaction-diffusion equations on arbitrary domains.
method GF-Net, a neural network, learns Green's functions in an unsupervised manner using physics-informed approach and symmetry.
result GF-Net efficiently solves linear reaction-diffusion equations under various boundary conditions and sources.

Investment managers face harder choices in green stocks due to reduced performance variability.

problem Difficulty in deploying talent in green stocks due to reduced performance variability.
method Analysis of S&P 500 firms' greenhouse gas emission levels and peer performance ratios.
result Performance variability has decreased in green stocks, making it harder for managers to choose.

The paper proposes a method to monitor deep learning predictions for retraining, reducing costs.

problem Reducing computational costs in deep learning by detecting when predictions are no longer valid.
method Sequential monitoring of network predictions based on projected second moments monitoring.
result The proposed method can drastically reduce computational costs in deep learning.

Gradient descent with error feedback performs better than vanilla when features are rare.

problem Improving communication complexity in distributed optimization with rare features.
method Gradient descent with greedy sparsification and error feedback for rare features.
result Communication complexity improves as features become more rare, potentially better than vanilla GD.