Market Based Climate Stress Tests

基于市场的气候压力测试

• 批准号: 2218455
• 负责人: Robert Engle
• 金额: $ 29.51万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2218455&HistoricalAwards=false
• 关键词: Market; Based; Climate; Stress; Tests

A changing climate will also create changes in the risks and opportunities faced by investors. If banks are exposed to the risks of climate change, then these risks could potentially affect how financial markets function. This project will evaluate the exposure of banks and other financial institutions to climate change risks. After these methods are carefully tested for accuracy and reliability, the results will be updated weekly and posted freely on the internet for regulators, investors and policy makers to see. These estimates will help regulators assess financial system resilience in the event of climate related shocks. This project takes a completely new approach to stress testing for climate change. It focusses on prices of assets such as bank loans, rather than actual damages. Such bank stress tests can show exposure to climate change from damages that will not occur for more than twenty years but which could bankrupt a bank over a short period of time since asset prices can fall today in response to bad news about the distant future. These exposure measures are essentially a way to see how resilient banks are to climate related risks by examining the correlation between its stock return and climate risk factors. In fact, this observation leads to the measurement of the “greenness” of any investment by looking at the correlation between its return and a suite of climate risk factors. This project will apply state of the art statistical procedures to measure the exposure of financial institutions to climate risks. The procedure first formulates a portfolio of investment assets that reflects the risks of climate change. If climate change becomes more severe, this portfolio will fall in value. Several candidates for this portfolio are based on transition risks or physical risks or other versions of climate risk. To assess the exposure of banks, the change in a bank’s stock market valuation is regressed on the climate risk portfolios to see how important they are in determining the change in value of the bank. This regression allows the coefficients to change following the Dynamic Conditional Beta (DCB) framework as in Engle (2016). To be certain that this accurately measures the exposure, the project will a) develop the econometrics to estimate the confidence intervals in the dynamic conditional beta model, b) develop additional climate risk measures using climate efficient factor mimicking portfolios of publicly available funds marketed as sustainable, c) determine which portfolio is the best measure of transition risk, d) consider other risk factors for financial institutions, e) incorporate granular supervisory data to determine the extent to which market measures reflect actual bank holdings, f) compare the exposure rankings from the VRI model and from supervisory measures which mostly reflect NGFS methodology. A key feature of this research involves the use of confidential supervisory data from central banks in different parts of the world. Together these unique data sources will help to corroborate and improve the estimates from the econometrics. Comparison of the findings with those from supervisors can be carried out simply by rank correlations. However more interesting comparisons may involve understanding where there are differences. For example, using one set of exposures to predict another and including characteristics data will show where the differences are most important.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

气候的变化也将改变投资者面临的风险和机会。如果银行面临气候变化的风险，那么这些风险可能会影响金融市场的运作。 该项目将评估银行和其他金融机构面临的气候变化风险。在对这些方法的准确性和可靠性进行仔细测试后，结果将每周更新，并免费发布在互联网上，供监管机构、投资者和政策制定者查看。这些估计将有助于监管机构评估金融体系在气候相关冲击下的弹性。该项目采用了一种全新的方法来进行气候变化的压力测试。它关注的是银行贷款等资产的价格，而不是实际损失。这样的银行压力测试可以显示气候变化对20年内不会发生的损失的影响，但这可能会在短时间内使银行破产，因为资产价格可能会在今天下跌，以应对遥远未来的坏消息。这些风险敞口指标基本上是一种通过检查其股票回报与气候风险因素之间的相关性来了解银行对气候相关风险的弹性的方法。事实上，这一观察结果导致通过观察其回报与一系列气候风险因素之间的相关性来衡量任何投资的“绿色”。 该项目将采用最先进的统计程序来衡量金融机构对气候风险的暴露程度。该程序首先制定反映气候变化风险的投资资产组合。如果气候变化变得更加严重，这个投资组合的价值将下降。 该投资组合的几个候选者基于过渡风险或物理风险或其他版本的气候风险。为了评估银行的风险敞口，将银行股票市场估值的变化回归到气候风险投资组合中，以了解它们在决定银行价值变化方面的重要性。这种回归允许系数按照Engle（2016）中的动态条件Beta（DCB）框架变化。为了确保这一方法能够准确地衡量风险，该项目将：a）发展计量经济学，以估计动态条件贝塔模型中的置信区间; B）利用气候效率因子，模仿作为可持续发展的上市基金的投资组合，制定额外的气候风险衡量标准; c）确定哪种投资组合是衡量转型风险的最佳方法; d）考虑金融机构的其他风险因素，e）纳入精细监管数据，以确定市场指标反映银行实际持有量的程度，f）比较VRI模型和主要反映NGFS方法的监管指标的风险敞口排名。 这项研究的一个主要特点是使用世界各地中央银行的机密监督数据。这些独特的数据来源将有助于证实和改进计量经济学的估计。比较的结果与那些从主管可以进行简单的等级相关性。然而，更有趣的比较可能涉及了解哪里有差异。例如，使用一组暴露来预测另一组暴露，并包括特征数据，将显示差异最重要的地方。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。