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.
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.
It will be difficult to gain the agreement of all the actors on any proposal for climate change management, if universality and fairness are not considered. In this work, a universal measure of emissions to be applied at the international level is proposed, based on a modification of the Greenhouse Gas Intensity (GHG-I…
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.
Method constructs hedging portfolio for carbon risk but not ESG risk.
problem Hedging carbon risk with ESG risk.
method Triangulated Maximally Filtered Graph and node2vec algorithms.
result Efficient hedging portfolio strategy for carbon risk but not ESG risk.
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.
Study shows ethanol blends and incentives can significantly reduce transportation carbon emissions.
problem Rapid growth in electric vehicles requires complementary strategies to decarbonize transportation.
method Analysis of ethanol blending, regulatory incentives, and economic assessments.
result Ethanol blending, especially E15 and E85, can substantially reduce carbon emissions and provide economic benefits.
Electricity accounts for 25% of global greenhouse gas emissions. Reducing emissions related to electricity consumption requires accurate measurements readily available to consumers, regulators and investors. In this case study, we propose a new real-time consumption-based accounting approach based on flow tracing. This…
Fossil power firms have recently profited more than renewables, but this may be a temporary phenomenon.
problem The profitability gap between renewable and fossil power firms in Europe.
method Machine-learning clustering and Bayesian model averaging.
result Renewable power firms are becoming more profitable, while fossil power firms are becoming less so.
Paper proposes a KGE framework that reduces training time and carbon footprint.
problem Efficient KGE learning with reduced computational cost and environmental impact.
method Full batch learning, Orthogonal Procrustes Analysis, non-negative-sampling training.
result Significant reduction in training time and carbon footprint compared to state-of-the-art approaches.
Study optimizes GCS operations with deep learning and reinforcement learning.
problem Maximizing storage performance in GCS with resource-efficient simulations.
method Introduces MLD model for fast flow prediction and well control optimization, combining deep learning and reinforcement learning.
result Achieves highest NPV while reducing computational resources by over 60%.
Model predicts EU carbon prices using market and political factors.
problem Predict future carbon prices for EU market management.
method Support vector regression with grid search and cross validation.
result Model predicts carbon prices accurately for 2030.
A global agreement on how to reduce and cap human footprint, especially their GHG emissions, is very unlikely in near future. At the same time, bilateral agreements would be inefficient because of their neural and balanced nature. Therefore, unilateral actions would have attracted attention as a practical option. Howev…
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.
Proposes CEP to better represent financial products' carbon impact.
problem Binary 'Green' label inadequately represents financial products' carbon impact.
method Introduces Carbon Equivalence Principle (CEP) for financial products.
result Financial products' carbon impact can be included as a linked term sheet.
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.
Study analyzes carbon footprint of 1,417 ML models on Hugging Face.
problem Scarce knowledge on measuring and reporting carbon footprint of ML models.
method Repository mining study on Hugging Face Hub API.
result Stalled carbon emissions-reporting models, slight decrease in carbon footprint over 2 years.
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.
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.
Paper models transition risk using jump-diffusion model to price credit swaps.
problem Capturing transition risk in financial markets.
method Calibrated jump-diffusion model to CDS term structure, using quantile regression.
result Jump-diffusion model captures transition risk, jumps represent green policies.
AI methods are energy-intensive, but efficiency alone isn't enough for sustainability.
problem AI methods are energy-intensive and contribute to climate change.
method Critically examines the limitations of efficiency in improving environmental sustainability of AI.
result Efficiency alone is insufficient to address the environmental impacts of AI.
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.
Modeling bank portfolio risk under climate transition impacts.
problem Evaluating risk measures for a bank's collateralized loans in a climate transition economy.
method Developed an end-to-end modeling framework using stochastic processes and dynamic macroeconomic variables.
result Derived expressions for risk measures as functions of climate transition parameters.
Model predicts carbon price for green tech adoption.
problem Achieving emission targets with green technology adoption.
method Stationary equilibrium model with endogenous carbon price.
result Carbon price and stationary distribution of firms identified.
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.
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.
Calibrates carbon futures option pricing using high-frequency data.
problem Estimating equity and variance risk premia for carbon futures options.
method Multifactor stochastic volatility framework with jumps, employing indirect inference.
result Provides insights into carbon futures and option dynamics.
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.
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.
Defines SETR to measure carbon transition risk for investors.
problem Difficulty in measuring the magnitude of carbon transition risk for investors.
method Defines Single Event Transition Risk (SETR) and illustrates its use.
result SETR can approximate the magnitude of low-carbon transition risk.
Carbon capture and storage (CCS) can aid decarbonization of the atmosphere to limit further global temperature increases. A framework utilizing unsupervised learning is used to generate a range of subsurface geologic volumes to investigate potential sites for long-term storage of carbon dioxide. Generative adversarial …
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…
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.
China integrates ESG into corporate strategy for sustainable growth.
problem Corporate focus on short-term financial metrics.
method Deep integration of ESG principles into corporate culture and strategy.
result Companies are expected to fulfill social responsibilities and create long-term value.
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 R2 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.
New hybrid model predicts carbon prices using blockchain data.
problem Predicting carbon prices with fluctuation.
method DILATED CNN-LSTM framework with L1/L2 regularization.
result DILATED CNN-LSTM outperforms traditional models.
Greenhouse environment is the key to influence crops production. However, it is difficult for classical control methods to give precise environment setpoints, such as temperature, humidity, light intensity and carbon dioxide concentration for greenhouse because it is uncertain nonlinear system. Therefore, an intelligen…
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.
We explain a persistent cost-of-carry spread in EUA market and suggest ECB policy change.
problem Persistent cost-of-carry spread in EUA market.
method Cointegration analysis of EUA spread with credit spread and risk-free rate.
result Cointegration found between EUA spread, credit spread, and risk-free rate.
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.
Model for multi-period carbon market pricing with allowances.
problem Carbon market pricing with multiple trading periods and compliance times.
method Singular forward-backward stochastic differential equations (SDEs).
result Value function convergence to infinite period model under certain conditions.
Study values and optimizes forestry leases under risk and uncertainty.
problem Valuing and optimizing forestry leases in the presence of catastrophe risk and parameter uncertainty.
method Stochastic bio-economic models, Kalman filter, maximum likelihood estimation, RBSDEs, Monte Carlo simulations.
result Conservative strategy is recommended due to parameter uncertainty.
We constructed physically stable sp2 negatively curved cubic carbon structures which reticulate a Schwarz P-like surface. The method for constructing such crystal structures is based on the notion of the standard realization of abstract crystal lattices. In this paper, we expound on the mathematical method to construct…
We propose a statistical model to understand people's perception of their carbon footprint. Driven by the observation that few people think of CO2 impact in absolute terms, we design a system to probe people's perception from simple pairwise comparisons of the relative carbon footprint of their actions. The formulation…
Study analyzes EU ETS carbon market dynamics, revealing inefficiencies and anomalies.
problem Inefficiencies and anomalies in EU ETS trading and pricing mechanisms.
method Empirical analysis using AR-GARCH model and weighted network analysis.
result Heterogeneous and sometimes counter-intuitive elasticities in price-volume relationships.