Approximation methods for multiple period Value at Risk and Expected Shortfall prediction

In this paper, we are interested in predicting multiple period Value at Risk and Expected Shortfall based on the so-called iterating approach. In general, the properties of the conditional distribution of multiple period returns do not follow easily from the one-period data generating process, rendering this a non-trivial task. We outline a framework that forms the basis for setting approximations and study four different approaches. Their performance is evaluated by means of extensive Monte Carlo simulations based on an asymmetric GARCH model, implying conditional skewness and excess kurtosis in the multiple period returns. This simulation-based approach was the best one, closely followed by that of assuming a skewed t-distribution for the multiple period returns. The approach based on a Gram–Charlier expansion was not able to cope with the implied non-normality, while the so-called Root-k approach performed poorly. In addition, we outline how the delta-method may be used to quantify the estimation error in the predictors and in the Monte Carlo study we found that it performed well. In an empirical illustration, we computed 10-day Value at Risk’s and Expected Shortfall for Brent Crude Oil, the EUR/USD exchange rate and the S&P 500 index. The Root-k approach clearly performed the worst and the other approaches performed quite similarly, with the simulation based approach and the one based on the skewed t-distribution somewhat better than the one based on the Gram–Charlier expansion.     

Nonparametric Estimation of Expected Shortfall

The expected shortfall is an increasingly popular risk measurein financial risk management and it possesses the desired sub-additivityproperty, which is lacking for the value at risk (VaR). We considertwo nonparametric expected shortfall estimators for dependentfinancial losses. One is a sample average of excessive losseslarger than a VaR. The other is a kernel smoothed version ofthe first estimator (Scaillet, 2004 Mathematical Finance), hopingthat more accurate estimation can be achieved by smoothing.Our analysis reveals that the extra kernel smoothing does notproduce more accurate estimation of the shortfall. This is differentfrom the estimation of the VaR where smoothing has been shownto produce reduction in both the variance and the mean squareerror of estimation. Therefore, the simpler ES estimator basedon the sample average of excessive losses is attractive forthe shortfall estimation.     

A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances

Cross-sectional spatial models frequently contain a spatial lag of the dependent variable as a regressor or a disturbance term that is spatially autoregressive. In this article we describe a computationally simple procedure for estimating cross-sectional models that contain both of these characteristics. We also give formal large-sample results.     

Structural Changes in Expected Stock Returns Relationships: Evidence from ASE

Abstract:  This paper suggests a recursive application of Fama and MacBeth's (1973) testing procedure to assess the significance of macroeconomic factors and firm-specific effects priced in explaining the cross-sectional variation of expected stock returns over time. The paper applies the suggested testing procedure to investigate the source of risks of the Athens Stock Exchange (ASE). Among the variables examined, it finds out that the changes in the short term interest rates and firm size can explain a significant proportion of the variation of the ASE individual returns. The paper argues that the significance of interest rate changes can be associated with monetary policy changes introduced by the Greek authorities after the mid-nineties. These changes were focused on targeting interest rates, instead of monetary aggregates.     

Estimating Systematic Risk Using Time Varying Distributions

This article proposes a dynamic vector GARCH model for the estimation of time-varying betas. The model allows the conditional variances and the conditional covariance between individual portfolio returns and market portfolio returns to respond asymmetrically to past innovations depending on their sign. Covariances tend to be higher during market declines. There is substantial time variation in betas but the evidence on beta asymmetry is mixed. Specifically, in 50% of the cases betas are higher during market declines and for the remaining 50% the opposite is true. A time series analysis of estimated time varying betas reveals that they follow stationary mean-reverting processes. The average degree of persistence is approximately four days. It is also found that the static market model overstates non-market or, unsystematic risk by more than 10%. On the basis of an array of diagnostics it is confirmed that the vector GARCH model provides a richer framework for the analysis of the dynamics of systematic risk.     

A Value at Risk Approach to Background Risk

This paper studies the effects of an uninsurable background risk (BR) on the demand for insurance (proportional and with deductible). We study both the case of BR uncorrelated with the insurable one and the perfectly correlated one, in a Gaussian world. In order to perform our study, we exploit the new risk measure known as Value at Risk (VaR) and consider insurance contracts which are Mean-VaR efficient. We obtain results which depend on the parameters (moments) of both risks and on the magnitude of loadings charged by the insurance company, instead of depending on the risk attitudes of the insured, such as risk aversion and prudence.We demonstrate that, if loadings are not too high, the demand for insurance increases with positively correlated BR; it decreases with BR negatively correlated if the latter is less risky than the insurable one (in this case it can even go to zero, if loadings are too high); it goes to zero with BR which is negatively correlated and more risky than the insurable one.     

系统性风险转移、金融危机与公允价值披露

金融创新过程中系统性风险的转移突破了证券投资中收益与风险的传统对应关系,使衍生工具成为一种能有效规避系统性风险的投资载体。公允价值按市值计价的会计处理方法存在着一定的不足,即反映收益的同时忽视了对风险的应有监督;而同时披露收益的相关性和风险的相关性这两方面的信息是提升公允价值信息决策有用性的重要一环。这就需要从披露的视角研究公允价值的具体应用,探讨公允价值披露的改进。     

Decision making with Expected Shortfall and spectral risk measures: The problem of comparative risk aversion

We analyze spectral risk measures with respect to comparative risk aversion following Arrow (1965) and Pratt (1964) for deterministic wealth, and Ross (1981) for stochastic wealth. We argue that the Arrow–Pratt-concept per se well matches with economic intuition in standard financial decision problems, such as willingness to pay for insurance and simple portfolio problems. Different from the literature, we find that the widely-applied spectral Arrow–Pratt-measure is not a consistent measure of Arrow–Pratt-risk aversion. Instead, the difference between the antiderivatives of the corresponding risk spectra is valid. Within the framework of Ross, we show that the popular subclasses of Expected Shortfall, and exponential and power spectral risk measures cannot be completely ordered with respect to Ross-risk aversion. Thus, for all these subclasses, the concept of Ross-risk aversion is not generally compatible with Arrow–Pratt-risk aversion, but induces counter-intuitive comparative statics of its own. Compatibility can be achieved if asset returns are jointly normally distributed. The general lesson is that these restrictions have to be considered before spectral risk measures can be applied for the purpose of optimal decision making and regulatory issues.     

Estimating the Equity Risk Premium Using Accounting Fundamentals

This study uses recent developments in the theoretical modelling of the links between unrecorded accounting goodwill, accounting profitability and the cost of equity, together with Capital Asset Pricing Model (CAPM) betas, to estimate the ex-ante equity risk premium in the UK. The results suggest that, over our sample period from 1968 to 1995, the premium has been in the region of 5%. Our estimate lends support to the view that the ex-ante equity risk premium is substantially less than the historical average of the excess of equity returns over the risk-free rate, and is similar to the rates applied recently by UK competition regulators.     

金融创新风险的分类及其形成

本文通过对金融创新和金融风险的分析,讨论了金融创新风险的一般概念.然后,根据金融创新风险产生的原因以及对金融体系的不同影响进行分类,划分为金融创新自身活动及产品风险、金融创新市场风险、金融创新机构风险、金融创新货币政策及监管风险、金融创新系统化及国际化风险等,并对每一种风险的形成进行分析和阐述.     

金融创新风险的分类及其形成

本文通过对金融创新和金融风险的分析,讨论了金融创新风险的一般概念。然后,根据金融创新风险产生的原因以及对金融体系的不同影响进行分类,划分为金融创新自身活动及产品风险、金融创新市场风险、金融创新机构风险、金融创新货币政策及监管风险、金融创新系统化及国际化风险等,并对每一种风险的形成进行分析和阐述。     

Expected Returns and Idiosyncratic Risk: Industry-Level Evidence from Russia

We explore a relation between expected returns and idiosyncratic risk in Russia. Investors in the Russian stock market cannot fully diversify their portfolios due to transaction costs, information gathering and processing costs, and shortcomings in investor protection. This implies that investors demand a premium for idiosyncratic risk. We estimate the price of idiosyncratic risk using MIDAS regressions and a cross section of Russian industry portfolios. We find that idiosyncratic risk is economically significant and commands a negative (positive) premium, on average, of 10.0% (8.0) per year before (after) the global financial crisis in 2008. The results remain unaffected after controlling for global pricing factors and return reversal.     

金融工具的风险计量、分类体系与公允价值

金融工具会计准则过于复杂的原因之一在于金融工具本身具有丰富的风险内涵.现行金融工具会计体系是一种基于分类基础上的混合计量基础或计量属性体系,公允价值单维计量模式比现行的混和计量模式更简易,公允价值单维计量体系将是金融工具会计准则的长期目标.本研究表明,公允价值在应用层面并不会增加金融工具计量的复杂性,同时也契合全面风险...     

基于风险价值法和压力测试法的企业风险管理方法研究

本文提出风险价值法和压力测试法的企业风险管理方法,克服了传统方法只给出风险相对严重程度的不足。建立风险量化评估、预警和控制体系,采用优化组合方法,实施一体化风险管理,规避重大风险事件的发生。     

The Effect of Shortfall as a Risk Measure for Portfolios with Hedge Funds

Abstract:  Current research suggests that the large downside risk in hedge fund returns disqualifies the variance as an appropriate risk measure. For example, one can easily construct portfolios with nonlinear pay-offs that have both a high Sharpe ratio and a high downside risk. This paper examines the consequences of shortfall-based risk measures in the context of portfolio optimization. In contrast to popular belief, we show that negative skewness for optimal mean-shortfall portfolios can be much greater than for mean-variance portfolios. Using empirical hedge fund return data we show that the optimal mean-shortfall portfolio substantially reduces the probability of small shortfalls at the expense of an increased extreme crash probability. We explain this by proving analytically under what conditions short-put payoffs are optimal for a mean-shortfall investor. Finally, we show that quadratic shortfall or semivariance is less prone to these problems. This suggests that the precise choice of the downside risk measure is highly relevant for optimal portfolio construction under loss averse preferences.     

金融创新、金融风险与中国金融监管模式

金融创新对宏观政策的制定、金融市场运行、商业银行透明度均有影响,它能够管理和控制金融风险,也能增大金融风险,还将对金融稳定性产生很大的负面影响。中国的金融监管应建立健全银行、证券、保险监管机构间以及与宏观调控部门的协调机制,通过中国金融监督管理委员会与国际性金融监管组织的合作,积极参与国际金融监管准则的制定,借鉴国外金融监管经验,不断提高金融监管的专业化水平。     

Delayed Expected Loss Recognition and the Risk Profile of Banks

This paper investigates the extent to which delayed expected loan loss recognition (DELR) is associated with greater vulnerability of banks to three distinct dimensions of risk: (1) stock market liquidity risk, (2) downside tail risk of individual banks, and (3) codependence of downside tail risk among banks. We hypothesize that DELR increases vulnerability to downside risk by creating expected loss overhangs that threaten future capital adequacy and by degrading bank transparency, which increases financing frictions and opportunities for risk‐shifting. We find that DELR is associated with higher correlations between bank‐level illiquidity and both aggregate banking sector illiquidity and market returns (i.e., higher liquidity risks) during recessions, suggesting that high DELR banks as a group may simultaneously face elevated financing frictions and enhanced opportunities for risk‐shifting behavior in crisis periods. With respect to downside risk, we find that during recessions DELR is associated with significantly higher risk of individual banks suffering severe drops in their equity values, where this association is magnified for banks with low capital levels. Consistent with increased systemic risk, we find that DELR is associated with significantly higher codependence between downside risk of individual banks and downside risk of the banking sector. We theorize that downside risk vulnerability at the individual bank level can translate into systemic risk by virtue of DELR creating a common source of risk vulnerability across high DELR banks simultaneously, which leads to risk codependence among banks and systemic effects from banks acting as part of a herd.     

金融服务外包的风险控制及其监管研究

金融服务外包是金融领域的新兴业务,从国际范围看,金融服务外包行业正处于行业生命周期的高速成长期,尤其是近年来发展迅猛;目前我国金融业务外包已经开始起步并呈现不断发展的趋势。金融服务外包有利于强化金融机构的核心竞争力、规避经营风险和降低经营成本;但也会带来外包失败、成本增加、收益分配的不确定性、战略泄漏等风险。金融机构自身要加强内部控制防范风险,金融监管部门也应加强监管,要合理限定金融服务外包的范围、规范监管机构的权限与监管程序、规范金融机构选择外包商的基本程序和机制、要求金融机构和外包商建立应急机制,并适度从严监管跨国金融服务外包。     

金融服务外包的风险控制及其监管研究

金融服务外包是金融领域的新兴业务，从国际范围看，金融服务外包行业正处于行业生命周期的高速成长期，尤其是近年来发展迅猛；目前我国金融业务外包已经开始起步并呈现不断发展的趋势。金融服务外包有利于强化金融机构的核心竞争力、规避经营风险和降低经营成本；但也会带来外包失败、成本增加、收益分配的不确定性、战略泄漏等风险。金融机构自身要加强内部控制防范风险，金融监管部门也应加强监管，要合理限定金融服务外包的范围、规范监管机构的权限与监管程序、规范金融机构选择外包商的基本程序和机制、要求金融机构和外包商建立应急机制，并适度从严监管跨国金融服务外包。