GARP分享丨新统计手段或能为系统性风险监测提供新思路
行业资讯 | 2019-03-20
全球风险管理专业人士协会（GARP）致力于为风险管理条线上的各级人员，包括各大金融机构的风险从业者和监管机构人员提供风险教育和最新行业资讯。金程网校将持续转载“GARP Risk Intelligence”系列文章，介绍科技、企业文化与治理、能源等领域对操作风险、信用风险、市场风险和资产负债管理的影响。让我们一起全面认识风险，防范风险，化解风险。
全球金融危机过去已经有十多年。监管机构和央行行长们相信一个更强大、资本更充足的银行体系能够更好地抵御另一次重大的系统性冲击。但是，我们仍然缺少能被证实有效的系统性风险衡量指标，更不用说能够超越市场噪音和波动性的预测工具了。
去年美国联邦储备委员会网站上发表了一篇论文《银行控股与系统风险》提出了一种能够监控银行业系统风险独特而有效的方法。它还可用于跟踪金融领域的复杂变化和风险，如共同基金、房地产投资信托（REITs）和交易商-经纪商股份。
该方法基于一种新型“统计模型和评估框架 （statistical model and estimation framework）”，监管机构可以使用该模型框架“分析资产持有情况，更好地评估银行内的集中性风险，而无需直接检查银行资产负债表。此外，银行投资组合的相似性能够提供它们之间相互关联性的信息，这是衡量风险传播可能性的一个重要指标。”
这篇文章的作者包括Celso Brunetti，美国联邦储备委员会研究和统计司系统金融机构和市场部门主管；Jeffrey H. Harris，美国大学（American University）科歌德商学院Gary D. Cohn Goldman Sachs金融学主席； Shawn Mankad，康奈尔大学约翰逊研究生院运营、科技和信息管理助理教授。作者们计划改进并将最初的研究和验证进行延伸，他们将在今年夏天发布更新版论文。》》更多FRM证书相关问题点我咨询
“我们目前在金融领域实施的许多法规其实不适用于现实世界的许多风险，”美国大学的Harris教授说，他从2017年9月到2018年5月担任美国证券交易委员会首席经济学家，及经济和风险分析部（DERA）主任。
“如果我们能够对金融机构及其所承担的义务或交易对手义务有所了解，”Harris教授补充说，“我们的模型框架就会更好。”他们发表的论文对现有的多个风险管理维度进行了补充。
他们发表的论文对现有的多个风险管理维度进行了补充。
1. 过去的系统性风险研究尝试
Academics and official and government bodies such as the Financial Stability Board, the SEC's DERA and U.S. Treasury Office of Financial Research （OFR） have been hard at work on systemic risk indicators and tools. Pre-existing literature on the subject was compiled in a January 2012 paper, the first in the OFR's working paper series, by Massachusetts Institute of Technology professor Andrew Lo and three co-authors. A Financial Stress Index and Financial System Vulnerabilities Monitor tools are among the monitoring tools subsequently developed and maintained by the OFR.
Still, in a March 2018 video interview accompanying Lo's designation as the Global Association of Risk Professionals' Risk Manager of the Year, the MIT Sloan School of Management professor invoked the adage, “you can't manage what you can't measure.”
“We can measure inflation, GDP, all sorts of variables involving economic growth and various aspects of our economy,” Lo said. “But the one thing we don't have yet, 10 years after the financial crisis, is, ‘what is the current level of systemic risk?’”
2. 新的统计手段关注资产集中性风险
Brunetti, Harris and Mankad propose a new statistical method estimating the portfolio concentration or stock returns on balance sheet within each bank, along with an estimate of the common asset holdings across all banks. The former provides a measure of each bank's asset diversification; the latter, an indication the overall banking system's susceptibility to shocks.
It relies on an analysis of daily inter-bank trades and stock returns for individual banks and across all banks, culled from the e-MID European interbank deposit market, and publicly available stock return data, culled from annual reports and other, more current sources.
What's new about this approach, Harris explains, is that it focuses on the asset side of the balance sheet and identifies the concentration risk within each bank – the degree of concentration in one or a few assets. Other approaches tend to focus on the liability side or on capital adequacy, which is what the MES （marginal expected shortfall） and SRISK systemic risk monitoring approaches tend to do.
3. 更及时、更有预见性的新手段
Harris and his co-authors, in their paper, describe the asset-based approach as “more timely” and “a robust forecasting tool.”
They say that their testing indicates that the standard deviation and skewness of their measures generally lead, or are more predictive than, data published by the European Central Bank – the Composite Systemic Risk Index, the Simultaneous Default Probability and Sovereign Composite Systemic Risk Index, as well as EU macroeconomic indicators such as the Consumer Confidence Index （CCI） and Purchasing Managers' Index （PMI）。
Harris says that risk insights can be produced with greater frequency than with quarterly or annual bank earnings statements.
4. 贝叶斯框架
As described in the paper, the approach involves eight categories of bank data – cash, commercial loans, intangible assets, interbank assets, residential loans, investments, other holdings and remainder holdings.
A “novel Bayesian estimation framework” utilizes the two sets of data: stock returns and interbank lending data. This allows for the creation of a concentration index, which captures the degree of diversification of each bank's portfolio, and a similarity index, which captures how similar portfolio holdings are across banks.
Finally, the authors have tested and validated their approach from both a statistical perspective through various simulation exercises, and from an accounting perspective.
Charles Kane, a senior lecturer at MIT Sloan, says that new approaches for monitoring systemic risk are welcome. Sam Malone, director of research at Moody's Analytics （not the credit rating business of Moody's Investors Service）， says, “This new approach is a good idea because it allows for greater frequency in systemic risk measurement.” He also applauds the use of bank stock returns as a data input, something that Moody's employs in its own Systemic Risk Monitor tool, and the triangulation of this information with interbank trading data.
5.政策不足
In a forthcoming American Economic Review article, “Macroprudential Policy: What We've Learned, Don't Know and Need to Do,” Kristin J. Forbes, Jerome and Dorothy Lemelson professor of management at the MIT Sloan School, considers whether policymakers have done enough to prevent the next crisis.
“There are key issues around macroprudential policy about which we do not have sufficient understanding, such as on the new risks generated from the leakages and spillovers, on how to calibrate the different regulations （especially given political incentives）， and on the potential risks to financial stability outside the mandates for most macroprudential authorities,” Forbes writes.
MIT's Kane says that no single approach is adequate to this complex task, and we still need to measure the sustainability, credit ratios and liability side of the banks' balance sheets and regulatory policies to realize the overall risk.
The Brunetti-Harris-Mankad framework is “not a silver bullet,” Kane says, noting that it is more focused on commercial banking as opposed to investment banking, where sophisticated, hard-to-measure derivative instruments can be a source of extreme risk.
6.杠杆和压力测试
Malone of Moody's Analytics says one limitation of the asset-based approach – in its initial iteration and testing – is that it does not look closely at leveraged loan activity in the U.S. and the way in which “as an asset class, we have seen a suboptimal amount of crowding,” a trend of concern to systemic risk watchers.
He believes that any thorough effort to monitor for systemic risk would require the inclusion of systemic risk metrics with U.S. CCAR regulatory stress tests. “It is curious that we haven't seen that,” Malone says.
7.新方法的强化和补充
Harris and colleagues acknowledge their approach's limitations, which they intend to address in future testing and iterations. The initial testing was limited to an analysis of 40 to 60 European banks. Future tests will include larger quantities of data specific to the U.S. banking system.
“Integrating data from myriad products across various regulated and unregulated markets remains a significant challenge,” Harris says, adding that this new method provides a practical means for assessing complex financial institutions that trade hundreds of financial products in markets around the world.
Facilitating more frequent monitoring in complex and dynamic financial environments is an important breakthrough, he says. He calls the tool “an important building block for regulators, the banks and for others” who remain concerned about systemic risk.
风险管理是一门技术学科，所以来面试风险管理的毕业生们通常有强大的数学技能，以及对金融模型的充分理解。他们必须把这些能力应用到真实的案例中，因此银行也喜欢寻找这些能够解决问题的能力的人。
目前在中国，很多人对金融风险管理不够了解，以至于不少拥有这样的能力的人错失良机，与最适合自己的工作擦肩而过。不过FRM金融风险管理师考试还是给了广大学生一个好的平台——大学生即可报名考试，大家在学习的过程中不光丰富了金融风险管理的知识，也能够在未来就业中拓宽自己的职业道路。很多数学、统计、财务等专业的同学也加入到FRM的考试大军中来。
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