Research
On-device research index

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

Trend · papers per month

4387130173 · Jun 202019922001200920172026
48 results for industrial carbon reduction

Study finds environmental liability insurance reduces industrial carbon emissions.

problem Reduction of industrial carbon emissions.
method Two-way fixed effect model using provincial (city) level panel data from 2010 to 2020.
result Environmental liability insurance reduces industrial carbon emissions at both direct and indirect levels, with varying effects.

Optimizes gradual reduction of excess carbon emissions to net-zero.

problem Achieving net-zero carbon emissions through gradual reduction of excess emissions.
method Stochastic control approach to identify optimal emission strategy under constraints.
result Identifies the emission strategy that maximizes future profit from excess emissions.

This paper analyzes energy and carbon footprints in distributed and federated learning.

problem High energy costs and carbon emissions in centralized AI methods.
method A novel framework quantifying energy and carbon footprints in vanilla and consensus-based FL methods.
result Optimal bounds and operational points for green FL designs and sustainability assessment.

Climate change is widely expected to increase weather related damage and the insurance claims that result from it. This will increase insurance premiums, in a way that is independent of a customer's contribution to the causes of climate change. Insurance provides a financial mechanism that mitigates some of the consequ…

2015-09-03abs ↗pdf ↗

Study improves carbon price forecasting using quantile regression and feature selection.

problem Accurately predicting carbon prices influenced by geopolitical, social, and economic factors.
method Collect and analyze various influencing factors, select significant features, and use Sparse Quantile Group Lasso and Adaptive Sparse Quantile Group Lasso for robust predictions.
result Proposed methods outperform existing ones and provide a complete profile of future carbon prices.

A model optimizes carbon emission reduction and allowance purchasing for companies.

problem Optimizing carbon emissions and allowance purchasing for companies.
method Established an optimal control model involving two stochastic processes with two control variables, converted into an HJB equation, proved existence and uniqueness of solution.
result Proved the existence and uniqueness of the solution to the HJB equation.

Investigates optimal PPI strategies to reduce carbon emissions while managing financial risk.

problem Optimizing portfolio insurance strategies to mitigate carbon emissions.
method Modelled risky assets using stochastic factor model with partial information, solved optimization problem using CRRA utility function.
result Optimal carbon penalized PPI strategies reduce carbon emissions without sacrificing financial performance.

PIML enhances machine learning for subsurface energy systems.

problem Lack of interpretability and domain-specific knowledge in machine learning models.
method Integrates physics principles into data-driven models using deep learning.
result PIML improves model generalization and adherence to physical laws.

Study analyzes impacts of COVID-19 on French forestry sector, finds mixed results in supply chain.

problem Impact of COVID-19 on forestry sector supply chain and future opportunities.
method Integrated methodology combining Material Flow Analysis and Wood Product Model.
result Significant disruptions and shifts in wood production, highlighting resilience and vulnerabilities.

Study finds cherry-picking load shaping strategies outperforms others in reducing grid CO2 emissions.

problem Lack of detailed counterfactual data makes it hard to assess load shaping strategies' effectiveness.
method Calibrated granular ERCOT simulations for counterfactual analysis of load shaping strategies.
result LMP-based load shaping outperforms other strategies in reducing grid CO2 emissions.

This work models GHG offset credit markets to find optimal strategies for market participants.

problem Optimizing GHG offset credit markets to reduce emissions and penalize excess emissions.
method Characterized optimal behavior in single-player and two-player GHG offset credit markets using optimal stopping and control problems, and mixed-Nash equilibria.
result Market participants benefit from optimal OC trading and generation, highlighting the importance of acting optimally.

Optimal dynamic allocation of carbon allowances reduces emissions efficiently.

problem Reducing carbon emissions from firms over time with dynamic allocation and trading.
method Variational approach to solve the Stackelberg game between regulator and firms.
result Optimal policies lead to constant abatement effort and allowance price, outperforming static allocations.

The study designs a green investment fund and a hedging strategy for insurance policies linked to it.

problem Hedging unit-linked life insurance policies with an environmentally sensitive investment fund.
method Developed a carbon-intensity-driven portfolio selection rule and a quadratic hedging approach.
result The hedging strategy minimizes the variance of hedging costs, as demonstrated through numerical analysis.

The study assesses carbon risk in investment portfolios and proposes new management strategies.

problem The impact of carbon risk on stock pricing and portfolio construction.
method Developed a BMG risk factor and estimated time-varying carbon beta using a multi-factor model.
result Carbon risk can be incorporated into portfolio construction to reduce unrewarded financial risks.

This paper introduces a new market-based carbon risk measure for portfolio optimization.

problem The challenge of measuring and managing carbon risk in investment portfolios.
method Develops a market-based carbon risk measure and applies it to minimum variance portfolio construction.
result Market-based carbon risk measures can complement fundamental-based approaches in portfolio optimization.

Proposes a Carbon Equivalence Principle for financial products to align incentives and drive sustainability.

problem Align financial market incentives with carbon emissions to limit global warming.
method Introduces a Carbon Equivalence Principle requiring financial products to describe equivalent carbon flows alongside cash flows.
result Transparency of carbon flows in financial products can align incentives and reduce future costs, necessitating project re-structuring and financial net-zero designs.

This study analyzes how carbon pricing affects credit risk measures in a portfolio.

problem Impact of carbon pricing on credit risk measures in a portfolio.
method Adapted stochastic multisectoral model to account for GHG emissions costs and carbon prices.
result Carbon pricing distorts firm value distributions, increases banking fees, and reduces profitability.

Paper analyzes how present-bias affects carbon emissions and proposes a method to mitigate it.

problem Present-bias impacts carbon emission patterns towards a net zero target.
method Stochastic control techniques adapted from insurance risk theory.
result Higher present-bias leads to excess emissions, and carbon taxes can reduce emissions but beyond a certain point have diminishing returns.

Deep learning calibrates CO2 storage formations from seismic and well data.

problem Uncertainty in CO2 storage formation properties.
method Two deep learning models for well and seismic data, integrated into MCMC history matching.
result Significant uncertainty reduction in key parameters and accurate CO2 plume predictions.

Study finds carbon emissions affect stock value, but not bought emissions.

problem Determining if carbon emissions impact stock value and whether this is due to direct or indirect emissions.
method Fixed-effects analysis with propensity score weighting to control for selection bias.
result Firms with higher Scope 1 emissions have a statistically significant positive carbon premium, but Scope 2 emissions do not.

Carbontracker tracks and predicts training DL models' carbon footprint.

problem Exponential growth in energy consumption for training deep learning models.
method Carbontracker tool for tracking and predicting energy and carbon footprint.
result Promotes responsible computing and encourages energy-efficient deep learning.

A successful response to climate change needs vast investments in low-carbon research, energy, and sustainable development. Governments can drive research, provide environmental regulation, and accelerate global development, but the necessary low-carbon investments of 2-3% GDP have yet to materialise. A new strategy to…

2018-07-09abs ↗pdf ↗

Optimizes renewable energy mix to meet carbon-free targets at lowest cost.

problem Minimizing annual procurement costs while achieving specified carbon-free hourly performance.
method Probabilistic framework with simulation scenarios and probability constraints. Fixed set of renewable generators and load customer.
result Demonstrated that certain renewable energy portfolios can meet carbon-free targets at lower costs compared to others.

Study assesses climate risks on supply chains and financial systems using detailed firm emissions data.

problem Lack of firm-level CO2 emissions data hinders assessment of transition risks from carbon pricing.
method Used detailed Hungarian firm emissions data and a simple economic ABM model to simulate carbon pricing impacts.
result 45% of companies are directly exposed to carbon pricing, leading to significant economic and financial losses.

A new model selects low-carbon mutual funds considering ESG criteria, risk, and investor preferences.

problem Aligning financial investments with a low-carbon economy.
method Tri-criterion portfolio selection model using a preference-based multi-objective genetic algorithm (ev-MOGA).
result The model successfully incorporates carbon risk exposure and loss-adverse attitudes into portfolio construction.

The paper examines spillovers between agriculture, crude oil, carbon, and climate markets.

problem Understanding dynamic spillovers between agriculture, crude oil, carbon emission, and climate markets.
method A novel R2R^2 decomposed connectedness approach.
result Overall spillovers are mainly contemporaneous, not lagged; climate change significantly impacts others; agricultural markets have heterogeneous effects; corn is a major risk contributor.

We report the results of fifteen sets of portfolio selection simulations using stocks in the ASX200 index for the period May 2000 to December 2013. We investigated five portfolio selection methods, randomly and from within industrial groups, and three based on neighbor-Net phylogenetic networks. We report that using ra…

2016-03-08abs ↗pdf ↗

A new framework uses an Incremental Transformer to design geopolymer mixtures efficiently.

problem Designing geopolymer mixtures with limited data and physical constraints.
method Topology-aware surrogate framework guided by Incremental Transformer.
result The design space is redundant, with fewer effective mixture regimes.

Study models risks for low-carbon economy in Balkan countries, focusing on shadow economy and populism.

problem Risks and uncertainties in establishing a low-carbon economy in Balkan countries with transition economies.
method Transdisciplinary approach combining economic policy, public opinion, and climate change models.
result Identifies shadow economy and populism as key risk factors for low-carbon economy implementation.

This research uses reinforcement learning to find optimal emission offsets in greenhouse gas markets.

problem Finding optimal emission offsets in greenhouse gas markets to control excess emissions.
method Utilized reinforcement learning, specifically Nash-DQN, to estimate market Nash equilibria.
result Emitting firms can achieve significant financial savings by abiding by the Nash equilibria found in the market.