Abstract : There is an increasing awareness of the urgency required to combat climate change and environmental pollution from central governments, researchers, and the industry around the world. Over 130 countries have committed to carbon neutrality targets in various forms, representing approximately 80% of the world population and 90% of the world’s GDP. This shift in public attention is particularly relevant to our economic and financial systems in several aspects. This minisymposium discusses how to model and measure climate risks, their implications for corporate decisions, credit risks, and supply chain risks, how to green investing, and how to regulate the climate emissions market. Overall, these progresses allow researchers, regulators, and other stakeholders to improve their insights into the climate transitional risk to the economy, which will enable society to design policies and strategies to help allocate resources for carbon-neutral goals.
[01677] Optimal ecological transition path of a credit portfolio distribution, based on Multidate Monge-Kantorovich formulation
Format : Talk at Waseda University
Author(s) :
Emmanuel Gobet (Ecole Polytechnique)
Clara Lage (Ecole polytechnique and Univ. Lyon1)
Abstract : Accounting for climate transition risks is one of the most important challenges in the transition to a low-carbon economy. Banks are encouraged to align their investment portfolios to CO2 trajectories fixed by international agreements, showing the necessity of a quantitative methodology to implement it. We propose a mathematical formulation for this problem and a multistage optimization criterion for a transition between the current bank portfolio and a target one. The optimization problem combines the Monge-Kantorovich formulation of optimal transport, for which the cost is defined according to the financial context, and a credit risk measure. We show that the problem is well-posed, and can be embedded into a saddle-point problem for which Primal-Dual algorithms can be used. We design a numerical scheme that is able to solve the problem in available time, with nice scalability properties according to the number of decision times; its numerical convergence is analysed. Last we test the model using real financial data, illustrating that the optimal portfolio alignment may differ from the naive interpolation between the initial portfolio and the target.
[01674] Optimal Dynamic Contracts and Environmental Pollution
Format : Talk at Waseda University
Author(s) :
Jerome Detemple (Boston University)
Hao Xing (Boston University)
Abstract : We examine optimal dynamic contracts when production generates harmful pollution. We derive optimal consumption, effort and environmental investment of the agent and solve for the optimal contract offered by the principal. We then solve for a stationary pollution equilibrium in an economy with a continuum of
polluting firms. The optimal contract rewards for financial performance and self-pollution mitigation. We study the impact of model parameters on contractual structure, managerial decisions, and the stationary pollution distribution.
[05305] Optimal Impact Portfolios with General Dependence and Marginals
Format : Talk at Waseda University
Author(s) :
Andrew Lo (MIT)
Lan Wu (Peking University)
Ruixun Zhang (Peking University)
Chaoyi Zhao (Peking University)
Abstract : Impact investing typically involves ranking and selecting assets based on a non-financial impact factor, such as the environmental, social, and governance (ESG) score and the prospect of developing a disease-curing drug. We develop a framework for constructing optimal impact portfolios and quantifying their financial performances. Under general bivariate distributions of the impact factor and residual returns from a multi-factor asset-pricing model, the construction and performance of optimal impact portfolios depend critically on the dependence structure (copula) between the two. We derive a general representation theorem to characterize the distribution of induced order statistics (returns of impact-ranked assets), which allows us to explicitly and efficiently compute the optimal portfolio weights under any copula. The optimal weights depend on the tail characteristics of the copula, as well as whether the marginal distribution of residual returns is skewed or heavy-tailed. Our framework requires the estimation of only a constant number of parameters as the number of assets grows, providing a more regularized and robust approach compared to traditional Markowitz portfolios.
[01612] Bridging Shared Socioeconomic Pathways of GHG Emission and Credit Risk
Format : Talk at Waseda University
Author(s) :
Florian Bourgey (Bloomberg L.P.)
Abstract : We investigate the impact of transition risk on a firm’s low-carbon production. As the world is facing global climate change, the Intergovernmental Panel on Climate Change has set the idealized carbon-neutral scenario around 2050. In the meantime, many carbon reduction scenarios, known as Shared Socioeconomic Pathways (SSPs) have been proposed in the literature for different production sectors in a more comprehensive socio-economic context. We consider, on the one hand, a firm that aims to optimize its emission level under the double objectives of maximizing its production profit and respecting the emission mitigation scenarios. Solving the penalized optimization problem provides the optimal emission according to a given SSP benchmark. On the other hand, such transitions affect the firm’s credit risk. We model the default time by using the structural default approach. We are particularly concerned with how, by following different SSPs scenarios, the adopted strategies may influence the firm’s default probability. We then show how to incorporate physical risk and extend the previous framework to a large-sized portfolio.
Abstract : We introduce investors with preferences for green assets to a general equilibrium setting in which they also prefer consuming green goods. Their preference for green goods induces consumption premia on expected returns, which counterbalance the green premium stemming from their preferences for green assets. Because they provide a hedge when green goods become expensive, brown assets command lower consumption premia, while green investors allocate a larger share of their portfolios towards them. Empirically, the green-minus-brown consumption premia differential reached 30-40 basis points annually, and contributes to explaining the limited impact of green investing on the cost of capital of polluting firms.
[01683] On some initial climate change impact models in actuarial science
Format : Online Talk on Zoom
Author(s) :
Stephane Loisel (ISFA, Universite Lyon 1)
Abstract : In this talk, we start by presenting the main sources of uncertainty about the impact of climate change in the insurance industry, and the approaches proposed to model them. We then focus on the impact of physical risk on biometric risks for life insurance and on claims frequency risk in non-life insurance and present work in progress on these two topics.
[05370] Optimal carbon tax in the Golosov et al. 2014 DGSE central planning model
Format : Online Talk on Zoom
Author(s) :
Stéphane Crépey (Université Paris Cité / LPSM)
Dounia Essaket (Université Paris Cité / LPSM)
Florian Bourgey (Bloomberg L.P.)
Noufel Frokha (Université Paris 1)
Gauthier Vermandel (Ecole Poytechnique)
Abstract : We provide a full analytical solution to the Golosov et al. 2014 optimal control formulation of the carbon tax problem in a DGSE central planning setup. Whereas the original paper was only solving the problem in terms of first order necessary conditions, we derive the value function itself. This gives a direct access to the carbon tax as the derivative of the value function with respect to the Lagrangian parameter associated with the labor constraint.
[01585] Using NLP to Analyze Corporate Communication
Format : Online Talk on Zoom
Author(s) :
Markus Leippold (University of Zurich)
Abstract : Corporate climate disclosures are considered an essential prerequisite to managing climate-related financial risks. At the same time, current disclosures are imprecise, inaccurate, and greenwashing-prone. We introduce a deep learning approach to enable comprehensive climate disclosure analyses by fine-tuning the climateBert model. From 14,584 annual reports of the MSCI World index firms from 2010 to 2020, we extract the amount of cheap talk, defined as the share of precise versus imprecise climate commitments. We then test various hypotheses by linking three different climate initiatives, namely the Task Force on Climate-Related Financial Disclosure, the Science-Based Targets Initiative, and the Climate Action 100+, to the economic channels of signaling, credibility, and active engagement. In particular, we ask whether these initiatives decrease cheap talk by disciplining companies in how they define and disclose actionable climate commitments in their annual reports.
