气候风险 (CRISK) 分析为全球金融公司提供与气候相关的风险措施。这些衡量标准会定期更新， 并且可以绘制历史估值以查看各个公司的业绩变化。
继Jung等人（2022年）后，气候压力测试程序包括三个步骤。 第一步是通过使用搁浅资产（SA）投资组合回报作为过渡风险的代理度量来衡量气候风险因子。 搁浅资产组合由利特曼研发，由能源ETF（XLE）30%多头头寸，煤炭ETF（KOL）70%多头头寸和市场空头头寸组成。 我们以MSCI全国世界指数（ACWI）作为市场。SA投资组合的表现不佳可以被解释为过渡风险的上升。
第二步是利用DCB模型估计金融机构的时变气候测试值。我们用以下两个因子来模拟银行i的股票回报率：
$$r_{it}=\beta _{it}^{Mkt}MKT_{i}+\beta _{it}^{Climate}CF_{t}+\varepsilon _{it}$$其中\(r_{it}\)是\(i\)银行的股票回报，\(MKT\)是市场回报，\(CF\)是气候风险因子，来自前一步的计算。 第一个因子\(\beta _{it}^{Mkt}\)的加载称为市场\(\beta\)，第二个因子\(\beta _{it}^{Climate}\)的加载称为气候\(\beta\)。根据恩格尔的动态条件\(\beta\)型进行动态估计。
第三步是计算气候风险。这一步扩展了Acharya等人（2011）、Acharya等人（2012）、 布朗利斯和恩格尔（2017）的SRISK方法。CRISK定义为气候压力条件下的预期资本短缺，计算方法为：
$$CRISK_{it}=kD_{it}-(1-k)W_{it}(1-LRMES_{it})$$\(D\)表示银行的债务账面价值，\(W\)表示银行的市值，\(LRMES\)表示长期边际预期短缺，即当搁浅资产投资组合在6个月内显著下降时， 公司股权的预期部分损失。计算方法为：
$$LRMES=1-exp(\beta ^{Climate}log(1-\theta))$$其中，\(\theta\)为气候压力水平，其默认值为50%。\(k\)是作为资产份额的审慎资本水平。
Climate Risk (CRISK) Analysis presents climate-related risk measures for global financial firms. These measures are updated on a regular basis and the historical estimates can be plotted to see the changing performance of individual firms.
Following Jung et al. (2022), the climate stress testing procedure involves three steps. The first step is to measure the climate risk factor by using the stranded asset (SA) portfolio return as a proxy measure for transition risk. The stranded asset portfolio is developed by Litterman and composed of 30% long position in the energy ETF (XLE), 70% long position in the coal ETF (KOL), and a short position in the market. We use MSCI all-country world index (ACWI) as the market. An underperformance of SA portfolio can be interpreted as a rise in transition risk.
The second step is to estimate the time-varying climate betas of financial institutions using the DCB model. We model bank i’s stock return with two factors as:
$$r_{it}=\beta _{it}^{Mkt}MKT_{i}+\beta _{it}^{Climate}CF_{t}+\varepsilon _{it}$$where \(r_{it}\) is the stock return of bank \(i\), \(MKT\) is the market return, and \(CF\) is the climate risk factor, measured from the previous step. The loading on the first factor, \(\beta _{it}^{Mkt}\), is called market beta and the loading on the second factor, \(\beta _{it}^{Climate}\), is called climate beta. The betas are estimated dynamically, following the Dynamic Conditional Beta model of Engle.
The third step is to compute CRISK. This step extends the SRISK methodology of Acharya et al. (2011), Acharya et al. (2012), and Brownlees and Engle (2017). The CRISK is defined as the expected capital shortfall conditional on the climate stress, and is calculated as:
$$CRISK_{it}=kD_{it}-(1-k)W_{it}(1-LRMES_{it})$$\(D\) denotes the bank’s book value of debt, \(W\) denotes the market capitalization of the bank, and \(LRMES\) denotes the Long-Run Marginal Expected Shortfall, which is the expected fractional loss of the firm equity when the SA portfolio declines significantly in a six-month period. It is calculated as:
$$LRMES=1-exp(\beta ^{Climate}log(1-\theta))$$where \(\theta\) is the climate stress level and its default value is 50%. \(k\) is a prudential level of capital as a share of assets.