全球風(fēng)險(xiǎn)管理專業(yè)人士協(xié)會(huì)(GARP)致力于為風(fēng)險(xiǎn)管理?xiàng)l線上的各級(jí)人員，包括各大金融機(jī)構(gòu)的風(fēng)險(xiǎn)從業(yè)者和監(jiān)管機(jī)構(gòu)人員提供風(fēng)險(xiǎn)教育和最新行業(yè)資訊。金程網(wǎng)校將持續(xù)轉(zhuǎn)載“GARP Risk Intelligence”系列文章，介紹科技、企業(yè)文化與治理、能源等領(lǐng)域?qū)Σ僮黠L(fēng)險(xiǎn)、信用風(fēng)險(xiǎn)、市場(chǎng)風(fēng)險(xiǎn)和資產(chǎn)負(fù)債管理的影響。讓我們一起全面認(rèn)識(shí)風(fēng)險(xiǎn)，防范風(fēng)險(xiǎn)，化解風(fēng)險(xiǎn)。

　　全球金融危機(jī)過(guò)去已經(jīng)有十多年。監(jiān)管機(jī)構(gòu)和央行行長(zhǎng)們相信一個(gè)更強(qiáng)大、資本更充足的銀行體系能夠更好地抵御另一次重大的系統(tǒng)性沖擊。但是，我們?nèi)匀蝗鄙倌鼙蛔C實(shí)有效的系統(tǒng)性風(fēng)險(xiǎn)衡量指標(biāo)，更不用說(shuō)能夠超越市場(chǎng)噪音和波動(dòng)性的預(yù)測(cè)工具了。

　　去年美國(guó)聯(lián)邦儲(chǔ)備委員會(huì)網(wǎng)站上發(fā)表了一篇論文《銀行控股與系統(tǒng)風(fēng)險(xiǎn)》提出了一種能夠監(jiān)控銀行業(yè)系統(tǒng)風(fēng)險(xiǎn)獨(dú)特而有效的方法。它還可用于跟蹤金融領(lǐng)域的復(fù)雜變化和風(fēng)險(xiǎn)，如共同基金、房地產(chǎn)投資信托(REITs)和交易商-經(jīng)紀(jì)商股份。

　　該方法基于一種新型“統(tǒng)計(jì)模型和評(píng)估框架 (statistical model and estimation framework)”，監(jiān)管機(jī)構(gòu)可以使用該模型框架“分析資產(chǎn)持有情況，更好地評(píng)估銀行內(nèi)的集中性風(fēng)險(xiǎn)，而無(wú)需直接檢查銀行資產(chǎn)負(fù)債表。此外，銀行投資組合的相似性能夠提供它們之間相互關(guān)聯(lián)性的信息，這是衡量風(fēng)險(xiǎn)傳播可能性的一個(gè)重要指標(biāo)。”

　　這篇文章的作者包括Celso Brunetti，美國(guó)聯(lián)邦儲(chǔ)備委員會(huì)研究和統(tǒng)計(jì)司系統(tǒng)金融機(jī)構(gòu)和市場(chǎng)部門主管;Jeffrey H. Harris，美國(guó)大學(xué)(American University)科歌德商學(xué)院Gary D. Cohn Goldman Sachs金融學(xué)主席; Shawn Mankad，康奈爾大學(xué)約翰遜研究生院運(yùn)營(yíng)、科技和信息管理助理教授。作者們計(jì)劃改進(jìn)并將最初的研究和驗(yàn)證進(jìn)行延伸，他們將在今年夏天發(fā)布更新版論文。

　　“我們目前在金融領(lǐng)域?qū)嵤┑脑S多法規(guī)其實(shí)不適用于現(xiàn)實(shí)世界的許多風(fēng)險(xiǎn)，”美國(guó)大學(xué)的Harris教授說(shuō)，他從2017年9月到2018年5月?lián)蚊绹?guó)證券交易委員會(huì)首席經(jīng)濟(jì)學(xué)家，及經(jīng)濟(jì)和風(fēng)險(xiǎn)分析部(DERA)主任。

　　“如果我們能夠?qū)鹑跈C(jī)構(gòu)及其所承擔(dān)的義務(wù)或交易對(duì)手義務(wù)有所了解，”Harris教授補(bǔ)充說(shuō)，“我們的模型框架就會(huì)更好。”他們發(fā)表的論文對(duì)現(xiàn)有的多個(gè)風(fēng)險(xiǎn)管理維度進(jìn)行了補(bǔ)充。

　　1. 過(guò)去的系統(tǒng)性風(fēng)險(xiǎn)研究嘗試

　　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. 新的統(tǒng)計(jì)手段關(guān)注資產(chǎn)集中性風(fēng)險(xiǎn)

　　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. 更及時(shí)、更有預(yù)見(jiàn)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. 貝葉斯框架

　　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.杠桿和壓力測(cè)試

　　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.新方法的強(qiáng)化和補(bǔ)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.

　　風(fēng)險(xiǎn)管理是一門技術(shù)學(xué)科，所以來(lái)面試風(fēng)險(xiǎn)管理的畢業(yè)生們通常有強(qiáng)大的數(shù)學(xué)技能，以及對(duì)金融模型的充分理解。他們必須把這些能力應(yīng)用到真實(shí)的案例中，因此銀行也喜歡尋找這些能夠解決問(wèn)題的能力的人。

　　目前在中國(guó)，很多人對(duì)金融風(fēng)險(xiǎn)管理不夠了解，以至于不少擁有這樣的能力的人錯(cuò)失良機(jī)，與最適合自己的工作擦肩而過(guò)。不過(guò)FRM金融風(fēng)險(xiǎn)管理師考試還是給了廣大學(xué)生一個(gè)好的平臺(tái)——大學(xué)生即可報(bào)名考試，大家在學(xué)習(xí)的過(guò)程中不光豐富了金融風(fēng)險(xiǎn)管理的知識(shí)，也能夠在未來(lái)就業(yè)中拓寬自己的職業(yè)道路。很多數(shù)學(xué)、統(tǒng)計(jì)、財(cái)務(wù)等專業(yè)的同學(xué)也加入到FRM的考試大軍中來(lái)。

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