Forecasting expected shortfall: Should we use a multivariate model for stock market factors?

Is univariate or multivariate modeling more effective when forecasting the market risk of stock portfolios? We examine this question in the context of forecasting the one-week-ahead expected shortfall of a stock portfolio based on its exposure to the Fama–French and momentum factors. Applying extensive tests and comparisons, we find that in most cases there are no statistically significant differences between the forecasting accuracy of the two approaches. This result suggests that univariate models, which are more parsimonious and simpler to implement than multivariate factor-based models, can be used to forecast the downside risk of equity portfolios without losses in precision.     

当代中国文化中科学精神的缺失与重构

科学精神在当代中国文化中的缺失现象比较严重，而科学精神在先进文化中又起看非常重要的作用，因此，我们必须重建科学精神，使相信科学、崇尚科学的意识深深地扎根生长，成为我们时代的精神。     

Agricultural Financial Risks Resulting from Extreme Events

Decision‐makers in the agricultural sector operate in a volatile and risky environment. The statistical assessment of agricultural commodity prices is necessary to deduce the stylised facts of agricultural markets and guide the action of market participants. This article examines the kurtosis values of 60 agricultural commodities and presents evidence that the distributions of their returns are fat‐tailed. We use power‐law distributions to model the tail returns and the possible time‐varying extreme event risks in commodity markets. Our results suggest that the usefulness of the value at risk and expected shortfall as risk management tools is questionable.     

EFFICIENT HEDGING OF EUROPEAN OPTIONS WITH ROBUST CONVEX LOSS FUNCTIONALS: A DUAL‐REPRESENTATION FORMULA

Motivated by numerical representations of robust utility functionals, due to Maccheroni et al., we study the problem of partially hedging a European option H when a hedging strategy is selected through a robust convex loss functional L(·) involving a penalization term γ(·) and a class of absolutely continuous probability measures . We present three results. An optimization problem is defined in a space of stochastic integrals with value function EH(·) . Extending the method of Föllmer and Leukerte, it is shown how to construct an optimal strategy. The optimization problem EH(·) as criterion to select a hedge, is of a “minimax” type. In the second, and main result of this paper, a dual‐representation formula for this value is presented, which is of a “maxmax” type. This leads us to a dual optimization problem. In the third result of this paper, we apply some key arguments in the robust convex‐duality theory developed by Schied to construct optimal solutions to the dual problem, if the loss functional L(·) has an associated convex risk measure ρ^L(·) which is continuous from below, and if the European option H is essentially bounded.     

Extreme spectral risk measures: An application to futures clearinghouse margin requirements

This paper applies the extreme-value (EV) generalised pareto distribution to the extreme tails of the return distributions for the S&P500, FT100, DAX, Hang Seng, and Nikkei225 futures contracts. It then uses tail estimators from these contracts to estimate spectral risk measures, which are coherent risk measures that reflect a user’s risk-aversion function. It compares these to VaR and expected shortfall (ES) risk measures, and compares the precision of their estimators. It also discusses the usefulness of these risk measures in the context of clearinghouses setting initial margin requirements, and compares these to the SPAN measures typically used.     

基于边际分析法的可修复备件最优库存研究

分析了可用度和短缺数效能指标之间的关系,用短缺数代替可用度求最优库存。以备件保障经费为约束条件、短缺数最大为目标函数,建立了单基地最优库存模型。用边际分析法求解,并将库存模型应用于实例,计算工具是Matlab。进行了数值实验和理论分析,结果证明该模型的优化效果和实用性很好。     

沪深股市风险度量中半参数ES模型的实证检验

目前度量预期不足(Expected Shortfall, ES)的风险技术大多基于参数模型,其建模过程避免不了对收益的分布类型做出假定,但这些分布往往与现实相悖。为此,介绍两种重要半参数模型,即CARE模型和CARES模型,并应用我国2007-2016年上证综合指数与深证成分指数的相关数据评估模型优劣。结果表明：CARES模型与CARE模型在度量我国股市风险中都具有较好的效果,但两者比较,CARES模型明显优于CARE模型。因此,CARES模型能作为我国股市风险度量工具中的一个重要补充。     

A novel downside beta and expected stock returns

A number of studies have found that the cross-section of stock returns reflects a risk premium for bearing downside beta; however, existing measures of downside beta have poor power for predicting returns. This paper proposes a novel measure of downside beta, the ES-implied beta, to improve the prediction of the cross-section of asset returns. The ES-implied beta explains stock returns over the same period as well as the widely used downside beta, but improves the prediction for future returns due to its high persistence. In the empirical analysis, the widely used downside beta shows a weak relation with future expected returns, but the ES-implied beta implies a statistically and economically significant risk premium of 0.6% per month and explains 0.6% of the variation in the cross-sectional returns. The effect cannot be explained by traditional cross-sectional effects and is different from the CAPM beta, the downside beta in Ang et al. (2006), coskewness, and cokurtosis.     

Systemic risk and bank consolidation: International evidence

This paper analyzes the systemic risk effects of bank mergers to test the “concentration-fragility” hypothesis. We use the marginal expected shortfall as well as the lower tail dependence between a bank’s stock returns and a relevant bank sector index to capture the merger-related change in an acquirer’s contribution to systemic risk. In our empirical analysis of a dataset of international domestic and cross-border mergers, we find clear evidence for a significant increase in the merging banks’, the combined banks’ as well as their competitors’ contribution to systemic risk following mergers, thus confirming the “concentration-fragility” hypothesis.     

Update rules for convex risk measures

In the first part of the paper we investigate the properties that describe the intertemporal structure of dynamic convex risk measures. The usual backward approach to dynamic risk assessment leads to strong and weak versions of time consistency. As an alternative, we introduce a forward approach of consecutivity. In the second part we discuss the problem of how to update a convex risk measure when new information arrives. We analyse to what extent the above properties are appropriate update criteria.