企业债券风险估值与简化式方法

信用风险、利率风险和流动性风险是债券投资者面临的最严峻的风险,对这几种风险的精确估计是债券定价的合理依据和债券投资者有效风险管理的前提.本文介绍一种风险估值的模型--简化式方法,并探讨它在债券定价、信用风险、流动性风险以及违约损失率估计中的应用.     

我国国债利率期限结构实证研究

一、前言 利率是因为出让货币资金在一定时期内的使用权而给货币资金所有者的报酬,它实质上是资金的价格,反映了资金供求关系.利率是金融领域的一个核心概念,它被广泛地应用于固定收益证券的定价以及分析中.利率期限结构是指在相同的风险水平下,不同到期期限的利率与到期期限之间的关系.由于无风险债券没有违约风险,也就没有信用风险溢酬,其价格只与市场利率水平有关,因此从横截面的角度看,利率期限结构可以用一条无风险债券的收益率曲线来表示.     

中国违约风险溢酬研究

违约风险的存在会对公司债券等固定收益证券的定价产生影响。在不存在违约风险的情况下，标的资产的价格直接按照无风险利率进行贴现；在存在违约风险时，必须考虑违约风险。     

中小企业集合债券总体信用风险度量研究

中小企业集合债券总体信用风险既包括系统风险产生的周期性违约风险,又包括相互关联关系导致的传染性违约风险。首先通过对因素模型的改进构建模型Ⅰ,研究集合债券的周期性违约风险;在此基础上引入违约传染建立模型Ⅱ,分析违约传染对违约概率及违约相关性的影响,研究集合债券的总体信用风险。最后基于模型Ⅱ进行算例研究,得出结论：企业间的相互关联关系降低了其1次违约概率,增加了其多次违约概率即违约相关性。     

违约风险与流动性风险对债券利差影响的交互效应

本文基于双向固定效应模型的实证研究结果表明,违约风险、流动性风险和风险交互均会对债券利差产生影响,其中风险交互对债券利差的影响最强,提高了流动性风险与违约风险对债券利差的边际效应。通过分析不同违约风险与流动性风险组合下的风险交互对债券利差的影响差异,发现风险交互效应与违约风险和流动性风险的风险等级不存在必然联系,中（低）风险组合的债券可能存在高风险交互效应,因而在受到负面冲击时可能发生实质性违约。     

固定利率住房抵押贷款违约行为及其定价研究

固定利率住房抵押贷款的信用风险主要是违约风险,基于理性期权的定价模型往往会低估借款人的违约概率.通过分析违约成本及非理性违约因素,可以确定借款人违约时贷款机构收回的现金流,得到固定利率住房抵押贷款定价的期望值模型,并得出模型的求解方法.     

固定收益证券的的综合风险分析及量度简

自金融危机后,投资者青睐固定收益证券以试图规避风险。但固定收益证券在具有稳定的收益的同时,也面临着金融市场中复杂多变的市场风险。本文试图在对固定收益证券的市场风险,包括利率风险、违约风险、流动性风险、再投资风险、通货膨胀风险做出分析和量度的基础上,为投资者提出相关建议。     

应用期权定价理论计算债券久期

根据证券组合的原理,一个有违约倾向的债券的复制组合包括———个无违约风险资产和一个看跌期权的空头。本文应用期权定价的理论和证券组合的原理,对有违约风险的债券中的久期问题进行了研究,并得到了债券久期的数量化计算公式。     

固定收益证券风险分析--以10重钢债为例

本文主要从固定收益证券的各项风险入手,对于债券特征分析中经常涉及到的信用风险、利率风险、流动性风险以及信用评级风险进行了较为全面的阐述。以10重钢债为例,通过KMV模型以及久期计算得到相关的风险量化分析,得到公司债的风险特征。     

公司债的信用风险计量分析

一、引言在现代资本市场中,公司债券与政府债券、股票同为基础性证券,公司债券市场是资本市场的重要组成部分。我国虽然早在1994年的《公司法》就曾列专章对公司债进行了规范,但真正意义上的公司债一直未能问世,市场上存在的主要是“准政府债券”形式的企业债。这些企业债一般是大型国企以经审批的投资项目为基础向国家发改委提出申请,由国务院统一审批发行额度后发行上市,并强制落实担保机制,实际信用级别与其他政府债券大同小异,因此这些企业债并不存在违约风险的问题。2005年修订后的《公司法》第7章以及《证券法》第2章对公司债券进行了详细的规范,尤其是2007年8月14日中国证监会发布的《公司债券发行试点办法》对公司发行债券不再要求强制担保,这标志着中国资本市场将导入真正意义上的公司债券,与此同时也伴随产生了公司债券的违约风险。对投资者而言,固定收益证券市场一般存在着如下几种风险,首先是由于利率变动产生的市场风险,其次还有内部流程不完善或模型错误导致的操作风险和无法及时在市场上出清头寸所产生的流动性风险,最后是由于固定收益证券存在违约可能而产生的信用风险。由于我国已建立了比较成熟的银行间债券市场,同时也有大量政府债券和企业债在证券...     

监测系统性金融风险——中国金融市场压力指数构建和状态识别

对系统性金融风险进行识别和评估,日益成为各国中央银行的核心关切。囿于数据频率,基于金融机构经营稳健性评估的金融系统性风险监测存在一定的滞后性,不利于中央银行及时进行风险应对,利用金融市场交易数据进行风险监测可极大程度克服滞后性问题。本文根据中国金融市场特点,选取债券市场、股票市场、货币市场和外汇市场17个有代表性的指标,运用经验累积分布函数法分别构造了各子市场的压力指数,以各子市场之间时变的相关关系刻画系统性金融风险的跨市场传染特征,合成金融市场压力指数,并通过建立马尔可夫区制转换模型,对金融市场压力状态进行识别。金融市场压力指数能有效反映样本域内的压力事件,并兼具稳健性、能逐日监测等优点,为监测评估系统性金融风险、选择政策实施窗口和评估政策实施效果等提供了有力工具。     

Binary interest rate sensitivities of emerging market corporate bonds

We develop a framework to assess interest rate sensitivities of emerging market corporate debt. Our analysis, based on yield indexes, is applied to investment grade and high yield portfolios. We reach beyond correlation-based analyses of interest rate sensitivity and keep our scope centered at capital gains of emerging market corporates and U.S. government bonds portfolios. Our empirical analysis spans over the period 2002–2015. We address interest rate sensitivity of assets during the ignition, apogee, and the aftermath of the global financial crisis. Based on historical data series, we evidence that the emerging market corporate bonds exhibit two different regimes of sensitivity to interest rate changes. We observe switching from a positive sensitivity under the normal market conditions to a negative one during distressed phases of business cycles and provide economical explanations of such phenomena. We show that emerging market corporate bonds, which on average could appear rather insensitive to the interest rate risk, in fact, present binary interest rate sensitivities. This research sheds light on how financial institutions may approach interest rate risk management including the downside risk hedge. Our findings allow banks and financial institutions to optimize economic capital under Basel III regulatory capital rules.     

压力测试及其在中美两国中的应用

在全球金融危机之中,传统的风险评估和预警机制没有发挥预期作用,压力测试作为一个重要评估工具,逐渐被各界重视。巴塞尔银行监管委员会于2009年5月发布了《压力测试实践和监管稳健原则》,针对压力测试在各个金融机构中的运用有了具体的指导思想,而同年美国为应对次贷危机在19家银行间开展的压力测试也是一次具有较大影响力的尝试。另一方面,在中国房地产市场面临调整的情况下,作为一种新型的风险检验方法,2010年中国银监会针对银行房地产信贷开展的大规模压力测试,其结果则有待实践检验。     

Testing macroprudential stress tests: The risk of regulatory risk weights

We compare the capital shortfall measured by regulatory stress tests, to that of a benchmark methodology — the “V-Lab stress test” — that employs only publicly available market data. We find that when capital shortfalls are measured relative to risk-weighted assets, the ranking of financial institutions is not well correlated to the ranking of the V-Lab stress test, whereas rank correlations increase when required capitalization is a function of total assets. We show that the risk measures used in risk-weighted assets are cross-sectionally uncorrelated with market measures of risk, as they do not account for the “risk that risk will change.” Furthermore, the banks that appeared to be best capitalized relative to risk-weighted assets were no better than the rest when the European economy deteriorated into the sovereign debt crisis in 2011.     

The disciplining effect of supervisory scrutiny in the EU-wide stress test

Relying on confidential supervisory data related to the 2016 EU-wide stress test, this paper presents novel empirical evidence that supervisory scrutiny associated to stress testing has a disciplining effect on bank risk. We find that banks that participated in the 2016 EU-wide stress test subsequently reduced their credit risk relative to banks that were not part of this exercise. Relying on new metrics for supervisory scrutiny that measure the quantity, potential impact, and duration of interactions between banks and supervisors during the stress test, we find that the disciplining effect is stronger for banks subject to more intrusive supervisory scrutiny during the exercise. We also find that a strong risk management culture is a prerequisite for the supervisory scrutiny to be effective. Finally, we show that a similar disciplining effect is not exerted neither by higher capital charges nor by more transparency and related market discipline induced by the stress test.     

Mandatory Disclosure,Voluntary Disclosure,and Stock Market Liquidity: Evidence from the EU Bank Stress Tests

We use the EU stress tests and the Eurozone sovereign debt crisis to study the consequences of supervisory disclosure of banks’ sovereign risk exposures. We test the idea that a mandatory one‐time disclosure induces an increase in voluntary disclosures about sovereign risk in the following periods and, through the shift in the voluntary disclosure equilibrium, increases the liquidity of banks’ shares. First, we find that the timing and content of different mandatory disclosure events helps explain the levels of stress‐test banks’ voluntary disclosures about sovereign risk. Second, although the bid‐ask spreads of stress test participants generally increased after the mandatory stress test in 2011, our results suggest that the decrease in market liquidity is entirely attributable to those stress‐test participants that did not commit to voluntarily maintaining the disclosures of sovereign risk exposure.     

Using Technology to Encourage Critical Thinking and Optimal Decision Making in Risk Management Education

This article draws a link between the risk management failures in the financial services industry and the educational philosophy and teaching constraints at business schools. An innovative application of prediction market technology within business education is proposed as a method that can be used to encourage students to think about risk in an open and flexible way. This article explains how prediction markets also provide students with the necessary experience to critically evaluate and stress‐test quantitative risk modeling techniques later in their academic and professional careers.     

Evaluating the Risks of Modeling Assumptions Used in Risk Measurement

Over the past few years, risk measurement has become an important, high-profile responsibility for most firms in the financial services industry. With advances in academic theory and in technology, financial risk modeling has grown increasingly sophisticated. Most firms rely on a number of models to analyze their market risks (for example, sensitivity to changes in interest rates, exchange rates, commodity prices, and so on) for asset/liability management. But it is critical to recognize that even the most sophisticated models must make assumptions about key parameters that affect the results of the analysis. This so-called “model risk” reflects the fact that in the real world risk factors are unstable and the historical data upon which many modeling inputs are based can change. This paper discusses model risk, gives specific examples of how model risk can affect fixed-income portfolio valuation, and explains why risk measurement should involve stress testing of key modeling assumptions. If the results of a valuation or asset/liability analysis change dramatically given a small change in a modeling assumption, management may wish to reduce the firm’s exposure to that risk factor, as absolute certainty in financial modeling is an unobtainable goal.     

商业银行市场风险压力测试研究

2007年起始的全球金融危机暴露了银行业对压力时期的市场风险预测失灵。危机后,西方国家通过压力测试来评估银行的资本充足状况。这一举措起到了恢复市场信心的作用。因为影响市场的风险因素众多,所以市场风险压力测试有别于其他风险类别的压力测试。虽然市场风险压力测试在学术领域、监管层面和实际应用中都得到了一定程度的研究与发展,然而当前压力测试方法还存在诸多不足,如不能提供压力情景可能性分析、无法涵盖模型外风险因素的测度、受限于产品定价模型的假设等。因此,在未来发展中应更加关注压力测试结果在银行的运用,及充分考虑尚未被普遍纳入压力情景的隐性风险因素。     

Dark Markets,by Darrell Duffie

This paper develops a method for selecting and analysing stress scenarios for financial risk assessment, with particular emphasis on identifying sensible combinations of stresses to multiple factors. We focus primarily on reverse stress testing – finding the most likely scenarios leading to losses exceeding a given threshold. We approach this problem using a nonparametric empirical likelihood estimator of the conditional mean of the underlying market factors given large losses. We then scale confidence regions for the conditional mean by a coefficient that depends on the tails of the market factors to estimate the most likely loss scenarios. We provide rigorous justification for the confidence regions and the scaling procedure when the joint distribution of the market factors and portfolio loss is elliptically contoured. We explicitly characterize the impact of the heaviness of the tails of the distribution, contrasting a broad spectrum of cases including exponential tails and regularly varying tails. The key to this analysis lies in the asymptotics of the conditional variances and covariances in extremes. These results also lead to asymptotics for marginal expected shortfall and the corresponding variance, conditional on a market stress; we combine these results with empirical likelihood significance tests of systemic risk rankings based on marginal expected shortfall in stress scenarios.