Climate Finance & Risk 2024 

Zili Yang is Professor of Economics at the State University of New York at Binghamton. He received Ph.D. in economics from Yale University in 1993. He has collaborated with Professor William Nordhaus, winner of the 2018 Nobel Prize for Economics, on the development of the RICE model. He is the author of Strategic Bargaining and Cooperation in Greenhouse Gas Mitigations (The MIT Press, 2008) and The Environment and Externality: Theory, Algorithms, and Applications (Cambridge University Press, 2021).

Constructing the Stable Climate Coalitions Based on the Lindahl Principle * --- The Findings from the RICE2020 Model The stability of a coalition is a crucial concern in the studies of international environmental agreements (IEA) and climate negotiations where externalities are present. In this paper, we demonstrate that the coalitions based on the Lindahl principle possess the best incentive properties and the fairest cost-sharing structure. Therefore, they are the most stable coalitions among all alternatives. Through exhaustive simulations in the 12-region RICE2020 model, we show that the coalitions built with the Lindahl principle are far superior to those with the utilitarian principle on which the literature has focused. The sophisticated algorithms to implement the Lindahl principle in the RICE model pave the way for the broad application of the Lindahl equilibrium concept in environmental problems. Finally, this paper also connects the stability of IEAs with climate negotiation in the real world.

Keywords: The Lindahl equilibrium, international environmental agreement (IEA), integrated assessment model (IAM), stable coalitions

* The author thanks the financial support of China’s National Key R&D Program (No. 2016YFA0602603) and the Whitney and Betty MacMillan Center for International and Area Studies at Yale.

Yongyang Cai, Professor in Detment of Agricultural, Environmental and Development Economics at The Ohio State University. His research focuses on dynamic and stochastic integration of climate and the economy; integration of regional food, energy, water systems, and economy; and computational methods in economics. He has published peer-reviewed papers in leading academic journals, including Journal of Political Economy, Journal of the European Economic Association, Quantitative Economics, Journal of the Association of Environmental and Resource Economists, Journal of Environmental Economics and Management, Nature Climate Change, Proceedings of the National Academy of Sciences, and Operations Research. He is a co-investigator on several research projects funded by the National ScieAnce Foundation and USDA. He currently serves as an Associate Editor at Climatic Change, and an editorial board member at Computational Economics. Prior to joining OSU, Cai was a Senior Research Scientist at the Becker Friedman Institute and the Center for Robust Decision Making on Climate and Energy Policy of the University of Chicago, as well as a Visiting Fellow at the Hoover Institution of Stanford University. In 2021, he received the Erik Kempe Award in environmental and resource economics.

Dynamics of Global Emission Permit Prices and Regional Social Cost of Carbon under Noncooperation We build a dynamic multi-region model of climate and economy with emission permit trading among 12 aggregated regions in the world. We solve for the dynamic Nash equilibrium under noncooperation, wherein each region adheres to the emission cap constraints following commitments that were first outlined in the 2015 Paris Agreement and updated in subsequent years. Our model shows that the emission permit price reaches $811 per ton of carbon by 2050. We demonstrate that a regional carbon tax is complementary to the global cap-and-trade system, and the optimal regional carbon tax is equal to the difference between the regional marginal abatement cost and the permit price. 

Dr Richard Matear is a senior climate scientist in the Climate Intelligence program of CSIRO Environment.  Richard has 30 years of experience investigating how rising greenhouse gases impact our climate.   His research utilises models and observations to understand the mechanisms driving climate variability and change and its implications for our future climate.  Richard currently leads CSIRO's future climate and hazard activity in the Australia Climate Service. In this role, he is working to ensure our climate intelligence is used to inform Australia's first National Climate Risk Assessment and helps guide Australia’s Climate Adaptation Plans.  Richard is also involved in efforts to demonstrate ocean-based negative emission technologies to remove carbon dioxide from the atmosphere and mitigate climate change. 

Future Climate Change and role of negative emissions technologies in reducing the Loss and Damages of Anthropogenic Climate Change

Over the last decade, the world has experienced frequent extreme climate events that have devastated people, communities, the economy, and the environment (e.g., the Australian Black Summer of 2019-20). The impacts of anthropogenic climate change are already being felt, and extreme climate events are projected to increase unless much more action is taken to limit warming.

The Paris Agreement (2015) and recent IPCC Reports on the impacts of global warming set international aspirations to limit global warming to “well below 2 °C above pre-industrial levels” and to pursue efforts to limit the temperature increase to 1.5 °C. Limiting warming requires rapidly reducing CO2 emissions. However, achieving the Paris Agreement goals by reducing greenhouse gas emissions alone is virtually impossible. Modelling scenarios to keep global warming within the limits of the Paris Agreement requires the large-scale deployment of negative emission technologies (NETs) to achieve a net zero level of CO2 emissions.  

Many potential approaches exist for removing CO2 from the atmosphere, with a current focus on land-based methods. However, meeting the Paris Agreement goals with land-based NETs alone will be extremely difficult because land-based NETs have side effects, sustainability-related trade-offs (e.g., competition for land use, accelerated loss of biodiversity), limited potentials, and issues of carbon storage permanence. In contrast, the ocean covers over 70 % of the Earth’s surface, contains many times more carbon than the atmosphere and terrestrial biosphere, and will be the predominant long-term sink for anthropogenic CO2. These factors suggest that ocean-based NETs should be critical in transitioning to net zero.  

This presentation will start by motivating the need for action by reviewing the future trajectory of greenhouse gas emissions, our recent climate, and the near and long-term impacts of global as seen through sea level rise.  Then, I will discuss ocean-based NETS as a potential solution to mitigate future climate change.  The presentation hopes to stimulate discussion and collaboration around assessing the costs of climate change and quantifying the benefits of climate change action. Motivating and accelerating the deployment of NETs requires studies showing the benefit of their use will exceed their deployment costs. 

Jun’ya TAKAKURA received his Ph.D. (Doctor of Design) from Kyushu University, Fukuoka, Japan, in 2015. Since 2016, he has been working at the National Institute for Environmental Studies, where he is engaged in research on the assessment of climate change impacts. He is also a member of the AIM (Asia-Pacific Integrated Model) team.

Estimating global-scale economic impact of climate change: overview of statistical and structural models Climate change can cause various impacts on society including economic impacts. To quantify the economic impact of climate, various methods and models are used. Broadly speaking, these models can be divided into statistical models and structural models. Statistical models are based on statistical regression analysis using observed economic outcomes and climate, but do not explicitly model the underlying processes. On the other hand, structural models incorporate bio-physical and economic processes explicitly. In this presentation, I will introduce the overview of these methos, model characteristics, and recent research results.

Pavel Shevchenko is a Professor in the Department of Actuarial Studies and Business Analytics and Director of the Centre for Risk Analytics at Macquarie Business School. Prior to joining Macquarie University in August 2016, he worked at CSIRO Australia (1999-2016) holding the position of a Senior Principal Research Scientist (2012-2016). Since 1999, Prof Shevchenko has worked in the area of risk analytics, leading research and industry commercial projects on: modelling of operational and credit risks; longevity and mortality, retirement products; option pricing; insurance; modelling commodities and foreign exchange; and the development of relevant numerical methods and software.  

Solving stochastic dynamic integrated climate-economy models using Least Squares Monte Carlo 

Stochastic versions of recursive integrated climate-economy assessment models are essential for studying and quantifying policy decisions under uncertainty. However, as the number of stochastic shocks increases, solving these models as dynamic programming problems using deterministic grid methods becomes computationally infeasible, and simulation-based methods are needed. The least-squares Monte Carlo (LSMC) method has become popular for solving optimal stochastic control problems in quantitative finance. In this paper, we extend the application of the LSMC method to stochastic climate-economy models. We exemplify this approach using a stochastic version of the DICE model with all five main uncertainties discussed in the literature. To address the complexity and high dimensionality of these models, we incorporate deep neural network approximations in place of standard regression techniques within the LSMC framework. Our results demonstrate that the deep LSMC method can be used to efficiently derive optimal policies for climate-economy models in the presence of uncertainty.

TOMOKO MATSUI (Senior Member, IEEE) received the Ph.D. degree in computer science from the Tokyo Institute of Technology, Tokyo, Japan, in 1997. From 1988 to 2002, she was a Researcher in several NTT laboratories, focusing on speaker and speech recognition. From 1998 to 2002, she was a Senior Researcher with the Spoken Language Translation Research Laboratory, ATR, Kyoto, focusing on speech recognition. In 2001, she was an Invited Researcher with the Acoustic and Speech Research Department, Bell Laboratories, Murray Hill, NJ, USA, working on identifying effective confidence measures for verifying speech recognition results. She is currently a Professor with The Institute of Statistical Mathematics, Tokyo, working on statistical spatial–temporal modeling for various applications, including speech and image recognition. She received the Best Paper Award from the Institute of Electronics, Information, and Communication Engineers of Japan, in 1993.

DICE climate-economy predictions under the shared socioeconomic pathways and representative mitigation strategies Our study revisits the social cost of carbon using the DICE (Dynamic Integrated Climate-Economy) framework, calibrated with Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). We incorporate data from multiple integrated climate-economy models such as AIM, GCAM, IMAGE, and WITCH-GLOBIOM, optimized for future projections of temperature, carbon concentrations, GDP, and population. The projections extend beyond 2100, applying a log-linear regression to estimate time trends from the SSP database. This method helps us address challenges of complex data and rare event scenarios in climate risk modeling. The findings underscore the importance of nuanced economic assumptions in assessing long-term environmental impacts, reinforcing the role of integrated approaches in enhancing our understanding of climate risks.

DAISUKE MURAKAMI received his Ph.D. degree in engineering from University of Tsukuba in 2014. From 2014 to 2017, he worked at the National Institute for Environmental Studies, Japan as a research associate. Since 2017, he is working at the Department of Statistical Data Science, in the Institute of Statistical Mathematics, Japan, as an assistant professor, and as an associate professor since 2023. His research interests include spatial and spatiotemporal statistics, quantitative geography, urban and environmental analysis.

Estimating building-level shared socioeconomic pathways (SSPs) through statistical downscaling: A case study in Japan. It is an urgent task for cities worldwide to achieve sustainable development. Shared socio-economic pathways (SSPs) need to be considered in order to design urban policies taking into account possible future socio-economic development. However, SSP scenario data are originally provided by countries, which are too coarse to be used for urban policy making. Although SSPs have been downscaled (e.g. to 1/12 degree grids), the spatial resolution is still insufficient. To address this problem, this study downscales national-level SSPs to the level of individual buildings in Japan. A statistical model incorporating spatial dependence, covariates and an urban growth is developed and used for the downscaling. Based on the downscaling result, the potential and challenges of the building level SSPs are discussed. 

Christina Nikitopoulos is an Associate Professor at the UTS Business School with expertise in energy finance, sustainable finance, renewable energy, and commodity markets. Christina’s projects in sustainable finance address the challenges of fossil fuel divesting, green bonds screening and the effects of climate transition risk on sovereign bond markets. This research analyses dynamic portfolio construction strategies accounting for the demographic attributes of investors, such as performance tracking, risk tolerance, and management structure, as well as, divestment schedules and re-investing, to inform of optimal carbon reduction practices in equity and bond portfolios. Her research also quantifies the significance of climate transition risk factors as determinants of sovereign bond markets. Christina also leads several projects addressing energy transition and the impact of renewable energy generation on electricity price dynamics in Australia. These studies offer insights and recommendations of practical relevance to policymakers, energy providers, and consumers and inform debates regarding system’s security and reliability and optimal courses of action to facilitate energy transition. Christina has been awarded two Australian Research Council grants and many internal and industry research grants, including the UTS Strategic Research Accelerator Program 2024. Christina publishes in leading finance journals including the Journal of Banking & Finance, Energy Economics, Quantitative Finance, Journal of Commodity Markets and Energy Policy.  She is a member of the Commodity and Energy Markets Association (CEMA), the Academic Female Finance Committee (AFFECT), the International Association of Energy Economics (IAEE), Financial Research Network (FIRN), and the Australian Accounting & Finance Association of Australia and New Zealand (AFAANZ).

Anatomy of Municipal Green Bond Yield Spreads Exploring the attributes of the rapidly evolving green bond market is pivotal in determining effective capital allocation to enable climate risk mitigation. We propose a novel approach to compute green bond spreads based on yields to maturity and their term structure, and we analyse the key attributes influencing the magnitude and sign of these spreads as well as their consistency over time. Based on California’s green municipal bond market, we find that these two types of green bond spreads are on average positive, but reach negative territories after 2022. Using the Bayesian Association rule learning technique, we find that positive spreads in both sign and magnitude have consistently been associated with structuring attributes like tax status, pricing strategy, and maturity, while negative spread dynamics are more likely to be associated with a more complex interaction of structuring attributes, including spread and yield on issuance, and callability. When the spread embeds information from the yield term structure, the structuring attributes of significance include duration, maturity, and callability. Sector-specific differences in credit ratings, issue sizes, and use of proceeds have been identified that can inform green bond portfolio screening, selection and diversification strategies. The distinctive attributes of the two types of spread also highlight the dynamic and heterogeneous nature of green bond spreads and offer practical insights regarding green bond screening to inform investment and policy decisions for sustainable portfolio management. 

Kylie-Anne Richards is an academic at the University of Technology Sydney with research and teaching interests in sustainable finance, green finance, statistics, econometrics, and high-frequency finance. Kylie-Anne develops and lectures the Sustainable Finance subjects offered in the Master of Finance, MBA, Executive MBA, Master of Financial Planning, and Microcredential suites.

Dr. Richards is an accomplished academic and an internationally recognized scholar. Her work appears in top-tier academic journals, including 'Energy Economics,' 'Annals of Actuarial Science,' 'Global Finance Journal ', 'International Journal of Financial Engineering,' 'Statistical Inference for Stochastic Processes.', etc. She has presented her research at conferences and workshops globally. Dr. Richards has also received numerous research grants in recognition of her expertise.

Dr. Richards has been featured in various media outlets for her expertise in sustainable finance. She has been interviewed for articles and podcasts on topics such as climate change transition risk, the use of AI in fixed-income analysis, diversity and inclusion, etc. Dr. Richards has been featured in media outlets such as KangaNews, InvestorDaily, UTS News Business and Law, Bloomberg Green, FS Sustainability, and The Conversation. She also makes regular appearances on AusBiz, a live and on-demand platform, discussing topics such as fixed-income markets, economics, and sustainability.

Dr. Richards holds a full-time position as Director at the Future Fund. Previously, she served as the Deputy Chief Investment Officer and Board Member of Fortlake Asset Management since its inception. Dr. Richards has extensive domestic and overseas industry experience, having worked at Macquarie Group in Hong Kong as Head of Financial Engineering for the Asia Pacific. Subsequently, she was Head of Indexation and Quantitative Trading Research at CLSA in Sydney. She was also the Co-founder and Portfolio Manager at QTR Capital, a proprietary trading business active in developed markets globally.

Dr. Richards holds a PhD from the School of Mathematics and Statistics at the University of New South Wales (UNSW). She also holds a Master of Finance (Financial Engineering) from the University of Hong Kong and a Bachelor of Science (Mathematics and Statistics) and a Bachelor of Commerce (Finance) from the University of Melbourne. During her PhD studies, Dr. Richards was the recipient of the QRSLab Boronia Managed Funds PhD Scholarship in 2011 in recognition of her academic achievements.

Shades of green: Unveiling the impact of municipal green bonds on the environment  Green bonds, which finance environmentally beneficial projects and sustainable development goals, are distinguished from traditional bonds by their focus on the use of proceeds. However, investors often face challenges in evaluating the carbon reduction potential of these bonds due to the lack of standardized environmental impact reporting. To address this, our research introduces a novel methodology that combines kernel Principal Component Analysis (kPCA) and Canonical Correlation Analysis (CCA) to detect spatial–temporal cross-correlations in multivariate datasets, effectively managing the comparability of variables and the treatment of both categorical and numerical data. Applying this approach to financial and environmental data from green bonds issued by municipal agencies in nine California counties, along with pollution and climate data, we found a significant correlation between green bond issuance and pollution reduction efforts, underscoring the tangible impact these financial instruments have on reducing pollution in the region. However, the study also revealed that detecting spatial–temporal relationships between green bond proceeds and positive climate change effects was inconclusive, likely due to the longer time frame required for climate impacts to become statistically measurable. Given that green bonds are a relatively new financial instrument, with substantial market growth occurring only in the last decade, the ability to detect climate benefits may take longer to manifest, suggesting that further research and extended observation periods are needed to fully understand the long-term environmental impact of green bond initiatives.  

Suthee Visitwarakorn works as a Senior Vice President of Risk Management Department at Bank for Agriculture and Agricultural Cooperatives, which is a Banking company with an estimated 18.4 K employees; and founded in 1966. He is part of the Office Operations team within the Risk Management Department and their management level is Director. 

Dr.Witsanu Attavanich is an associate professor of Economics Department at the Faculty of Economics, Kasetsart University. He received his B.Sc. in Economics at Kasetsart University with the first-class honors and awarded gold medal. He received his MA in Economics at Thammasat University and Ph.D. in the field of environmental and resource economics at Texas A&M University (USA) in 2011. He pursued his postdoctoral training at Rutgers University (USA) and served as a visiting research fellow of Summer Research Institute, Harris Manchester College, University of Oxford (UK). His recent research efforts have largely involved policy analysis (mainly in climate change, agriculture, land use, transportation, development, strategic planning, energy and environment). He teaches courses in microeconomic theory, econometrics for public program and policy evaluation, energy economics, managerial economics, and environmental economics. He received an outstanding award for research & innovation in the field of social science and humanities from Kasetsart University in 2014 & 2017; the 2017 rising star academic award from the Alumni Association of Economics & Business Administration, Kasetsart University; and the 2019 Puey Ungphakorn Award for the ฺBest Young Thai Economist who has outstanding academic performance. His recent contributed report won the 2016 Abraham Lincoln Honor Award for Increasing Global Food Security from the U.S. Department of Agriculture. He serves as associate deputy editor of Climatic Change and associate editors of Kasetsart Journal of Social Sciences and Applied Economics Journal .

Impact of Physical and Transition Risks from Climate Change on Thai Agri-Food Sector Agri-food sector has played a crucial role in Thailand. Not only it is major sources of food and employment, it is also a major source of export revenue and ensures the achievement of several sustainable development goals. This presentation will show that climate change was adversely affected the Thai economy and its agri-food sector. Moreover, the presentation will show how the Thai agri-food sector will be affected by future physical and transition risks from climate change. Several policy recommendations will be purposed to address the future impact of climate change on Thai agri-food sector.

Sandy Trust leads the UK’s Institute and Faculty of Actuaries (IFOA) research paper collaborations with Earth System scientists on climate change and sustainability topics; recent papers include The Emperor’s New Climate Scenarios and Climate Scorpion – the sting is in the tail. Sandy sits on IFOA Council and is past Chair of the IFOA’s Sustainability Board.
 
He works in financial services with large investors – pension schemes, asset managers, and insurance companies with typically several hundred billion dollars of assets under management – to develop and implement their approaches to sustainability – allowing them to protect value, comply with regulation, and compete in this fast-moving area.
 
He is currently Head of Organizational Risk at M&G plc, a FTSE100 investment firm, where he is the risk lead on sustainability. Previously he helped a Big 4 firm build their consulting capability in this space. 

Climate Scorpion: The Sting is in the Tail - Introducing Planetary Insolvency The IFoA report ‘Climate Scorpion’ shares the latest IFoA research collaboration with climate scientists. It explores the potential for extreme climate risks, their knock-on social effects, and actions we can take to manage them.

In this session, we explore how the actuarial approach towards ruinous risks can be applied to climate change. We explore the key findings from the paper, namely:

• the rate of global warming accelerated in 2023: there is early indication this is not temporary

• life in the tail: increased warming is now driving more severe impacts across the planet

• an overshoot of the 1.5°C temperature threshold is likely

• the sting in the tail of the Earth’s climate sensitivity

• warming above 1.5°C is dangerous, increasing the risk of triggering multiple climate tipping points

Dr Nicola Ranger is Director of the Global Finance and Economy Group of the Environmental Change Institute at the University of Oxford and a Senior Research Fellow. She also directs the Oxford Martin Systemic Resilience Initiative, the UK Integrating Finance and Biodiversity Programme and the Resilient Planet Finance Lab. Nicola brings 20 years' expertise in risk, analytics, economics, finance and fiscal policy as a practitioner and researcher across industry, government, IFIs and academia. She works with governments, Central Banks, regulators, financial institutions and international organisations to help align policy and finance with resilience and sustainability goals. She has formerly held senior positions at the World Bank, HM Treasury/Cabinet Office, the UK Department for International Development, the Foreign Commonwealth and Development Office and the London School of Economics and Political Science and is a member of several high-level expert groups, including the European Commission’s HLEG on Sustainable Investment in LMICs and the UK’s Green Taxonomy Advisory Group (GTAG). 

Integrating climate risks into financial decision making: new applications of catastrophe risk modelling Within the insurance industry, catastrophe risk models have long been a chosen tool for assessing and managing the financial risks of climate shocks. Yet, these models are rarely used outside of the sector, despite the increased focus on climate risk management amongst Central Banks, asset owners, banks and others. We will demonstrate the application of catastrophe risk models in climate finance applications, in stress testing by banks, sovereign bonds, debt sustainability analysis and climate adaptation. We will show how such approaches can be used to assess emerging risks, including compound risks and nature-related risks. These applications demonstrate the importance of a stochastic representation of climate shocks within financial decision making, both for risk management and to support the mobilisation of finance for adaptation.

Neil Tagoe is a pension Actuary by training with much experience in the valuation and design of Social Security pension schemes, private pension schemes and has over the course of his career built experience in developing performance indicators for health insurance schemes in Ghana. As a Social Protection expert, he served as a Technical Advisor for ILO Social Protection Programme and Board member of the Ghana-Luxemburg Social Trust for over 15 years.

He is a Certified Financial Analyst, Fellow of Actuarial Society of Ghana (FASG) and Institute of Management Specialist, UK (FIMS). Neil is the President of the Actuarial Society of Ghana (ASG) and the Vice Chair, Africa Task Force of the International Actuarial Association (IAA).

Rade Musulin is a Principal at Finity Consulting in Sydney, Australia, where he leads the Climate Risk practice. Previously he served as the Chief Executive Officer of FBAlliance Insurance, Chief Operating Officer of Aon Benfield Analytics Asia Pacific, and Vice President Operations, Public Affairs, and Reinsurance for the Florida Farm Bureau Insurance Companies.

Rade serves as Vice-Chair of the International Actuarial Association’s Resource and Environmental Working Group and was Vice President – Casualty for the American Academy of Actuaries from 2016 – 2018. He has a long history of volunteer service, including roles with the Actuaries Institute of Australia, American Academy of Actuaries, Casualty Actuarial Society, and International Actuarial Association. He is a past Chair of the Board of the Florida Insurance Council and of the Advisory Council of the Florida Hurricane Catastrophe Fund.

His main areas of interest include how changing population demographics affect catastrophe exposure, climate change adaptation, applications of catastrophe models for disaster planning in developing countries, building code development, and community resilience. Rade has maintained close ties with academic institutions, including being a lecturer for undergraduate classes in actuarial science, risk management, and political science.

The role of workforce modelling in planning for decarbonization Fossil fuels have underpinned industrialization and rising prosperity for over two centuries, with workforces in modern economies trained and developed either directly or indirectly to participate in activities enabled by fossil fuels. The growing adverse consequences of GHG emissions have forced many countries to fast track environmentally sustainable policies. An often-overlooked aspect of implementing such policies and minimizing the disruption of transition is understanding the way the workforce will need to change. Decarbonization, combined with robotics and AI, will place significant strains on workers and their communities. Millions of people will need to switch occupations, upgrade skills, and possibly relocate. All of this is complicated by other demographic trends, specifically lower birth rates and ageing populations. Governments will need to plan for workforce transition, including education, retraining, and creating new infrastructure if relocation is required. As potential Imbalances in supply and demand for labor will impact costs, employers and investors will need to understand the dynamics of workforce supply and demand to make investment decisions and manage operational risk.

In this session our speaker will present research on both direct and indirect impacts on Australia’s workforce from these trends. Key variables include whether jobs are manual or cognitive, how routine they are, and what skills will be required at the industry level. The role of the education system (both vocational and university) to build the supply of workers to meet the demand will be considered. The speaker will also discuss ways to model the future workforce to assist in identifying obstacles and opportunities for an orderly transition to a low carbon economy.

Stefan Trück is a Professor of Business Analytics and Director of the Transforming Energy Markets Research Centre at Macquarie University. Previously, he has held positions at Queensland University of Technology and Karlsruhe Institute of Technology in Germany where he received a PhD in Business Engineering. Stefan’s research interests focus on risk management, financial econometrics and business analytics. His is a world leading expert in the area of electricity markets and energy finance, while his research also comprises the areas of and commodity markets, credit risk, systemic risk, emissions trading, climate change economics and international financial markets. He has published in many high impact journals. He has also worked in various consulting projects in the area of energy and financial risk for organisations such as Deutsche Bank, Deutsche Bundesbank, Australian Energy Market Commission, Saudi Electricity and Co-Generation Regulatory Authority, Maybank, CRC Limited, just to name a few. He also has received various research grants, including two Discovery Grants from the Australian Research Council (ARC) plus an ARC Future Fellowship, one of the most prestigious awards for mid-career researchers in Australia. 

The risk and economic cost of wind droughts in wholesale electricity markets This study provides a comprehensive analysis of the dynamics of wind output within the Australian National Electricity Market (NEM) and its implications for system reliability and price behaviour. As Australia accelerates its transition towards renewable energy sources, wind power has emerged as a key component of the energy mix. However, due to the intermittent nature of wind and solar, the rapid deployment of renewable generation also poses significant challenges for maintaining a reliable electricity supply. The study applies advanced econometric techniques to examine the temporal and spatial patterns of wind output across different regions of the NEM. Using historical data, we examine how the increased growth of wind capacity over the past 10 years has changed the statistical profile of cumulative generation output from wind and impacted spot electricity prices. In particular, we are interested in examining the risk of low generation output from wind as well as whether adding additional wind capacity has helped to stabilize the output from wind generation relative to the installed capacity. To answer these questions, we propose the use of a so-called aggregated capacity factor from wind generation and analyze the dynamics of this factor and related variables. Our analysis addresses the intermittency of wind power, shedding light on the fluctuations in wind output and their impact on wholesale prices in the NEM. Overall, our study contributes to a deeper understanding of the complexities associated with wind power integration in the NEM, offering valuable insights for policymakers, grid operators, and energy market participants with regards to system reliability and spot electricity prices.

Jiro Akahori is a Professor of Department of Mathematical Sciences, Ritsumeikan University. 

• E-mail: akahori@se.ritsumei.ac.jp

• Born on June 10, 1967, Male, Japanese

• Ph. D in Mathematical Sciences, University of Tokyo, March 1997

• Lecturer (1998–2000), Associate Professor (2000–2008), Professor since

• April 2008, at Department of Mathematical Sciences, Ritsumeikan University

• Director of Research Center for Finance, Ritsumeikan University since 2008

• Vice President of Japanese Association of Financial Econometrics & Engineering since 2012 

• Editor-in-Chief of Asia Pacific Financial Markets since 2006, (The official journal of Japanese Association of Financial Econometrics & Engineering, published from Springer)

Research interests: Probability Theory and Mathematical Finance.

Selected Publications:

1. “An efficient weak Euler-Maruyama type approximation scheme of very high dimensional SDEs by orthogonal random variables” (with Masahiro Kinuya, Takashi Sawai, Tomooki Yuasa), Mathematics and Computers in Simulation, 2021, 187,540-565

2. “A Discrete-Time Clark-Ocone Formula and its Application to an Error Analysis”, (with Takafumi Amaba, Kaori Okuma), Journal of Theoretical Probability September 2017, Volume 30, Issue 3, pp 932–960 

3. “A Heat Kernel Approach to Interest Rate Models”, (with Yuji Hishida, Josef Teichmann and Takahiro Tsuchiya) Japan Journal of Industrial and Applied Mathematics  31/ 2, 419-439, (2014) 

4. “Tau functions of KP solitons realized in Wiener space”, (with Hidemi Aihara, Jiro Akahori, Hiroko Fujii, Yasuhumi Nitta) Bulletin of the London Mathematical Society,  45/ 6, 1301-1309 (2013) 

5. Noises, stochastic flows, and E0-semigroups”, (with Masaki Izumi and Shinzo Watanabe), Sˆugaku 59-3, 243–263, (2007).

Environmental macro-finance in continuous-time I will discuss how continuous-time finance can/should be combined with macro- and environmental- economics. I will also discuss "quantitative" issues, numerical analysis together with statistical estimation for continuous-time models. 

Prof. Gareth W. Peters is the ‘Janet and Ian Duncan Endowed Chair Professor in Actuarial Science’ and 'Chair Professor in Statistics for Risk and Insurance' in the Department of Applied Probability and Statistics in University of California Santa Barbara.

Previously, Prof. Peters was the Chair Professor for Statistics in Risk and Insurance in the Department of Actuarial Mathematics and Statistics, in Heriot-Watt University in Edinburgh. Where he was also the Director of the Scottish Financial Risk Academy (SFRA).

Previously he held tenured positions in the Department of Statistical Sciences, University College London, UK and the Department of Mathematics and Statistics in University of New South Wales, Sydney, Australia.

Prof. Peters holds or held the following professional elected positions:

• Member of London Mathematical Society - 2016+

• Fellow and Member of Institute of Operational Risk (FIOR) - 2016+

• Fellow of Royal Statistical Society (FRSS) and Chartered Statistician (CStat -RSS) - 2018+ & (Adv DSP-RSS) - 2024+

• Member of Edinburgh Mathematical Society - 2018+

• Fellow of Institute of Mathematics and Applications (FIMA) and Chartered Mathematician (CMath- FIMA) - 2020+

• Specialist Institute of Risk Management (SIRM) - 2020+

• Member of International Statistical Institute - 2021+

• Associate Editor Annals of Actuarial Science Journal - 2021+

• Elected Member of International Statistical Institute ISI - 2021+

• Appointed Member of Green Finance Working Party - IFoA - 2021+

• Appointed Member of GI-Machine Learning in Reserving Working Party - IFoA - 2021+

• Elected Member Sigma Xi 2023+ - Scientific Research Honor Society

• Invited Specialist External Reviewer of the Institute of Statistical Mathematics (ISM), National Statistics Institute of Japan, inTokyo - 2022-2023

• Member of International Society of Bayesian Analysis - 2011-2016

• Elected Member Young Academy of Science - Royal Society of Edinburgh (YAS-RSE) - 2017-2021

• American Risk and Insurance Association (ARIA) Member - 2021-2023

Prof. Peters was also the Nachdiploma Lecturer in Machine Learning for Risk and Insurance at ETH Zurich in the Risk Laboratory.

Prof. Peters has made in excess of 150 international invited presentations, speaker engagements including numerous key note presentation s. He has delivered numerous professional training courses to c- suite executive level industry professionals as well as numerous central banks.

Prof. Peters has published in excess of 200 peer reviewed articles on risk and insurance modelling, 2 research text books on Operational Risk and Insurance as well as being the editor and contributor to 3 edited text books on spatial statistics and Monte Carlo methods.

He currently holds positions as:

• Honorary Prof. of Statistics at University College London, 2018+

• Affiliated Prof. of Statistics in University of New South Wales Australia 2015+

• Affiliate Member of Systemic Risk Center, London School of Economics 2014+

• Affiliate Member of Oxford Mann Institute, Oxford University (OMI) 2013+

• Honorary Prof. of Statistics in University of Sydney Australia 2018+

• Honorary Prof. of Statistics in Maquarie University, Australia 2018+

• Visiting Prof. in Institute of Statistical Mathematics, Tokyo, Japan 2009 -2023+ 

He previously held positions as:

• 2018-2021 Academic Director of Scottish Financial Risk Academy. Scottish Fi nancial Risk Academy

• 2017-2019 Group leader of Sound Practice Guidance Series in Operatio nal Risk practice Institute of Operational Risk.

• 2011-2021 Co-founder of Quantitative Risk Solution Laboratory, Heriot-Watt University, Edinburgh (previously University College London 2011 -2018).

• 2018-2020 Selected Member of Bond Review Working Party (Know ledge Exchange Sub-Group) UK Mathematical Sciences.

• 2015-2017 Affiliated Prof. Institution of Theoretical and Applied Geo physics , Peking University, Beijing, China.

• 2010-2017 Adjunct Scientist: Mathematics, Informatics and Statistics group in Commonwealt h Scientific and Industrial Research Organization.

• 2012-2017 Principle Investigator in Center for Computational Statistics and Machine Learning, University College London.

• 2014-2017 Associate Lecturer of Department of Statistics , University of New South Wales (UNSW).

• 2017-2018 Invited Nachdiploma Professor of ETH Department of Mathemat ics Jointly with Swiss Finance Institute.

webpage: https://www.qrslab.com/

Abstract: In this talk, we assess the benefits of coordination and partnerships between governments and private insurers and provide further evidence for microinsurance products as powerful and cost-effective tools for achieving poverty reduction. To explore these ideas, we model the capital of a household from a ruin-theoretic perspective to measure the impact of microinsurance on poverty dynamics and the governmental cost of social protection. We analyze the model under four frameworks: uninsured, insured (without subsidies), insured with subsidized constant premiums, and insured with subsidized flexible premiums. Although insurance alone (without subsidies) may not be sufficient to reduce the likelihood of falling into the area of poverty for specific groups of households, because premium payments constrain their capital growth, our analysis suggests that subsidized schemes can provide maximum social benefits while reducing governmental costs.

Short bio: Sooie-Hoe Loke is an Associate Professor and the Assistant Chair of the Mathematics Department at Central Washington University. He obtained his doctoral degree from Oregon State University and completed postdoctoral work at the University of Waterloo. He is an Associate Editor of Variance and his recent actuarial research interests are inclusive insurance and value-based healthcare.

Andrea Macrina is Professor of Mathematics and the Director of the Financial Mathematics MSc Programme in the Department of Mathematics, University College London. Dr Macrina is Adjunct Professor at the University of Cape Town in the African Institute of Financial Markets and Risk Management where in 2014 he co-founded the Financial Mathematics Team Challenge (FMTC). He is a recipient of the Fields Research Fellowship awarded by The Fields Institute for Research in Mathematical Sciences. 

Prof. Macrina held a Senior Lectureship followed by a Readership in the Department of Mathematics, University College London, an Adjunct Professorship at the Department of Actuarial Science of the University of Cape Town, a Lectureship in Financial Mathematics in the Department of Mathematics, King's College London, a one-year Visiting Research Associate Professorship in the Institute of Economic Research, Kyoto University, and a six-month Research Fellowship at ETH Zurich. Read more about him.

Eric Ofosu-hene is a Senior Lecturer in Accounting and Finance at Leicester Castle Business School, De Montfort University (UK). He Chairs the Sustainability - Demography Mortality and Morbidity Working Party of the Institute and Faculty of Actuaries (UK), where he leads and drives research strategy on the impact of climate change on mortality and morbidity. He has consulted for several organisations in both the public and private sectors drawing on Enterprise Risk Management and Pensions Management expertise. His research work is at the intersection of actuarial science, finance and climate change and has published in leading journals including Energy Economics, Annals of Actuarial Science and others. Eric holds a PhD in Actuarial Science from University of Kent, a double Master of Science degrees with distinction in Actuarial Management and Actuarial Science from Heriot-Watt University and is a Qualified Accountant with the Association of Chartered Certified Accountants (UK). 

Modelling the impact of environmental variables and deprivation scores on excess heat mortality in the UK: A Spatio-temporal analysis and policy stress test design.

As climate change intensifies, the occurrence and severity of heatwaves are projected to increase, posing significant public health risks, particularly excess heat mortality. This study aims to model the impact of key environmental variables—on excess heat mortality across England and Wales, with a specific focus on how deprivation scores explain the variation in mortality rates in a spatio-temporal context. Utilizing high-resolution environmental and socio-economic data across multiple spatial and temporal scales, we develop joint models to capture the interaction between environmental stressors and socio-economic disparities. Air pollution, temperature extremes, humidity, precipitation and land use variables are integrated to assess their combined effect on excess-heat mortality, while deprivation scores provide critical insights into community vulnerability. The study employs advanced spatial statistics and machine learning techniques to identify high-risk regions and populations and to quantify the direct and indirect effects of these variables on excess heat mortality outcomes.

To inform targeted and effective policy interventions, we design a series of stress tests that simulate various climate scenarios, socio-economic shifts, and mitigation strategies. These stress tests provide a framework for policymakers to understand potential future challenges and to develop adaptive measures that can mitigate the adverse effects of heatwaves. This research provides evidence-based insights into the multi-dimensional factors influencing heat mortality, highlighting the critical role of environmental and socio-economic variables in shaping public health responses to climate change. The findings underline the necessity of integrating environmental management, urban planning, and socio-economic policies to reduce heat-related mortality and promote equitable health outcomes.

Yuthana Sethapramote is an Associate Professor of Economics and the Director of the Master’s program in Financial Economics at the School of Development Economics, National Institute of Development Administration (NIDA), located in Bangkok, Thailand. He joined NIDA in 2005 after completing his doctoral degree in Economics from the University of Warwick. Yuthana Sethapramote's research focuses on financial econometrics, with publications in international journals on topics such as macroeconomic and financial linkages in Asia, risk spillovers in financial markets, and the effects of monetary policy. He has also collaborated on industry projects, evaluating the economic impacts of infrastructure development and developing macroeconomic models for commercial banks.

Climate Risk and Financial Stability: A Systemic Risk Perspective from Thailand

This paper explores the impact of climate risk on systemic risk within Thailand's banking sector. To assess transition risk, we apply the Fama-French multi-factor asset pricing models to quantify the effects of climate change on financial markets. We calculate the risk premium of brown industries relative to green industries using a long-short portfolio (Brown minus Green – BMG). The Standardized Precipitation Evapotranspiration Index (SPEI) is employed as a proxy for physical risk. Systemic risk at the bank level is measured using conditional value-at-risk (CoVaR), based on trading data from the Stock Exchange of Thailand. We conduct panel regressions to quantify the effects of climate risk on systemic risk, with Fama-French (2015) risk factors and macroeconomic variables included as control variables.

Empirical results show that the BMG factor significantly impacts systemic risk in Thai banks, underscoring the role of transition risk in exacerbating systemic risk within the banking sector. Regarding physical risk, bank portfolios are particularly sensitive to flood risk. These findings provide valuable insights for regulators in Thailand to monitor financial stability using both transition and physical risk indicators. Furthermore, commercial banks can leverage these indicators to conduct stress tests and manage risk more effectively.

Pasin Marupanthorn currently serves as the Vice President at the Thai Quantitative Analyst and Financial Engineer Association (TQF), where he also holds the position of a quantitative researcher. He graduated with a Bachelor’s degree in Applied Mathematics with Physics, earning second-class honors from Thammasat University. He furthered his studies at Thammasat University, obtaining a Master’s degree in Mathematics. Pasin later pursued a second Master’s degree in Mathematical Modelling at the University of Birmingham, where he graduated with distinction.

He completed his Ph.D. in Actuarial Mathematics at Heriot-Watt University under the supervision of Chair Professor Gareth W. Peters and Dr. Eric Ofosu Hene. During his Ph.D. studies, Pasin was actively involved in the Quantitative Risk Solution Laboratory (QRSL), contributing to advanced research in quantitative finance. Additionally, he earned a Master’s degree in Financial Engineering from WorldQuant University, further broadening his expertise in financial mathematics.

Pasin is certified by the CQF Institute, having successfully completed the qualifications necessary for a career in quantitative finance. Prior to his studies in the UK, he worked as a lecturer at RMUTSB for three years. Upon returning to Thailand after completing his Ph.D., he joined TQF as a quantitative researcher and continues to contribute to academia as a university lecturer.

His portfolio and additional details can be found on my personal website: https://quantfilab.github.io/pmarupanthorn/

Evaluating the Impact of ESG Sustainability Factors on US Index Returns This study evaluates the impact of ESG (Environmental, Social, and Governance) sustainability factors on U.S. equity indices using various factor models. The analysis focuses on Morningstar's U.S. market and sustainability indices from 2013 to 2022, excluding the COVID-19 period. The study employs three types of models: a standard factor model, a time series factor model, and a functional factor model. The standard factor model assesses the instantaneous effect of ESG factors on index returns, revealing that sustainability indices effectively mitigate ESG-related risks, while traditional U.S. indices are more sensitive to these factors. The time series factor model investigates the time-lagging effects of ESG factors, showing that sustainability indices exhibit a stronger correlation with ESG factors over time, especially in the short term. Finally, the functional factor model explores the dynamic and cumulative effects of ESG factors, highlighting their significant impact on sustainability indices compared to traditional indices.