Environmental,social, and governance practices and perceived tail risk

Using the implied volatility smirk on individual equity securities to measure perceived tail risk, we find that better environmental, social and governance (ESG) practices significantly reduce ex-ante expectations of a left-tail event. Our findings are robust to using multiple model specifications and to adjusting for potential endogeneity concerns. We also show that, while practices in each ESG pillar are important in reducing perceived tail risk, the environmental pillar plays the most important role. Our results indicate that investors consider strong ESG practices to be insurance against left-tail events rather than wasteful investment borne out of managers’ own values or self-interest.     

The t copula with multiple parameters of degrees of freedom: bivariate characteristics and application to risk management

The t copula is often used in risk management as it allows for modeling the tail dependence between risks and it is simple to simulate and calibrate. However, the use of a standard t copula is often criticized due to its restriction of having a single parameter for the degrees of freedom (dof) that may limit its capability to model the tail dependence structure in a multivariate case. To overcome this problem, the grouped t copula was proposed recently, where risks are grouped a priori in such a way that each group has a standard t copula with its specific dof parameter. In this paper we propose the use of a generalized grouped t copula, where each group consists of one risk factor only, so that a priori grouping is not required. The copula characteristics in the bivariate case are studied. We explain simulation and calibration procedures, including a simulation study on the finite sample properties of the maximum likelihood estimators and Kendall's tau approximation. This new copula is significantly different from the standard t copula in terms of risk measures such as tail dependence, value at risk and expected shortfall.     

Flexible dependence modeling of operational risk losses and its impact on total capital requirements

Operational risk data, when available, are usually scarce, heavy-tailed and possibly dependent. In this work, we introduce a model that captures such real-world characteristics and explicitly deals with heterogeneous pairwise and tail dependence of losses. By considering flexible families of copulas, we can easily move beyond modeling bivariate dependence among losses and estimate the total risk capital for the seven- and eight-dimensional distributions of event types and business lines. Using real-world data, we then evaluate the impact of realistic dependence modeling on estimating the total regulatory capital, which turns out to be up to 38% smaller than what the standard Basel approach would prescribe.     

The crossroads of ESG and religious screening on firm risk

Using a large and extended global dataset of non-financial firms (4624 listed entities from 2002 to 2018), we provide the first empirical evidence on how ESG and Sharia screenings interact and influence market risks. We link two contrasting literature streams: the risk reduction role that the stakeholder theory attributes to ESG scores, and the opposite effect for Sharia-compliance anticipated by the portfolio and agency theories.We find that when ESG scores are not considered, Sharia certification increases risks. We also prove that engagement in sustainable activities mitigates risks for both Sharia-compliant and conventional firms. More interestingly, we show that Sharia-compliant firms obtain a larger risk-mitigating effect for greater levels of ESG scores. These results are robust to endogeneity and to extensive additional checks.Our findings validate the hypothesized complementarity between ESG and Sharia screenings.     

Forecasting portfolio-Value-at-Risk with nonparametric lower tail dependence estimates

We propose to forecast the Value-at-Risk of bivariate portfolios using copulas which are calibrated on the basis of nonparametric sample estimates of the coefficient of lower tail dependence. We compare our proposed method to a conventional copula-GARCH model where the parameter of a Clayton copula is estimated via Canonical Maximum-Likelihood. The superiority of our proposed model is exemplified by analyzing a data sample of nine different bivariate and one nine-dimensional financial portfolio. A comparison of the out-of-sample forecasting accuracy of both models confirms that our model yields economically significantly better Value-at-Risk forecasts than the competing parametric calibration strategy.     

Nonlinear tail dependence in cryptocurrency-stock market returns: The role of Bitcoin futures

We investigate the median and tail dependence between cryptocurrency and stock market returns of BRICS and Developed countries using a newly developed nonparametric cumulative measure of dependence over the period January 4, 2016 – December 31, 2019 as well as before and after the introduction of Bitcoin futures on December 17, 2017. The new measure is model-free and permits measuring tail risk. The results highlight the leading role of S&P500, Nasdaq and DAX 30 in predicting BRICS and developed countries’ stock market returns. Among BRICS countries, BVSP shows a starring role in predicting stock market returns. BSE 30 is the most predictor of cryptocurrencies, which have a little predictability on stock market returns. Ethereum has the leading role in predicting cryptocurrencies and stock market returns followed by Bitcoin. Tail dependence shows substantial role of S&P500, Nasdaq and BVSP in predicting stock market returns. Subsample analysis show the role of Bitcoin futures in reshaping the mean and tail dependence between cryptocurrency and stock market returns. Our results have important policy implications for portfolio managers, hedge funds and investors.     

Semiparametric estimation of multi-asset portfolio tail risk

When correlations between assets turn positive, multi-asset portfolios can become riskier than single assets. This article presents the estimation of tail risk at very high quantiles using a semiparametric estimator which is particularly suitable for portfolios with a large number of assets. The estimator captures simultaneously the information contained in each individual asset return that composes the portfolio, and the interrelation between assets. Noticeably, the accuracy of the estimates does not deteriorate when the number of assets in the portfolio increases. The implementation is as easy for a large number of assets as it is for a small number. We estimate the probability distribution of large losses for the American stock market considering portfolios with ten, fifty and one hundred assets of stocks with different market capitalization. In either case, the approximation for the portfolio tail risk is very accurate. We compare our results with well known benchmark models.     

A new time-varying optimal copula model identifying the dependence across markets

This paper proposes a new time-varying optimal copula (TVOC) model to identify and capture the optimal dependence structure of bivariate time series at every time point. In the TVOC model, half-rotated copulas are constructed to measure the nonlinear and asymmetric negative dependence, and the distribution-free test for independence is introduced to verify the dependent relationship and reduce the computational time. The TVOC model is then employed to research the dependence structure between security and commodity markets. We find evidence that the dependence structures across different markets vary over time and that emergencies are usually the major cause of sudden changes in the dependence structure. We also show that the TVOC model captures the dynamic characteristics of the direction and intensity of the dependence as well as the dynamic characteristics of the types of dependence structure. In particular, the half-rotated copulas can accurately describe the asymmetric negative extreme dependence across different markets.     

ESG,time horizons,risks and stock returns

Investment time horizon is an important part of significance of ESG factors. This research examines the role of ESG factors in returns and risks in short- and medium-term investment periods. It compares (a) the returns and risks of ESG portfolios between before scoring and after scoring, and (b) the returns and risks between ESG portfolios and their peers.The main results suggest that after scoring most short-term ESG portfolios have similar returns, but lower risks than before scoring. The returns of ESG portfolios are similar to those of nonESG portfolios for both short- and medium-term. There are more ESG portfolios, whose risks are different from nonESG portfolios, in the short-term investment than in the medium-term.ESG factors therefore play a greater role in risks than in returns, and in the short-term than in the medium-term. Additionally, the role of ESG factors in risks varies from industry to industry.     

Corporate stakeholders,corporate valuation and ESG

In addition to explicit contracts, corporations issue their stakeholders implicit claims, including fair treatment of employees and the promise of continuing service to customers. Corporate value is created by selling these implicit claims for more than it costs to honour them. Recently, a new class of non-investor stakeholders, related to environmental, social and governance (ESG) issues, has arisen. Although many ESG advocates stress their role in creating shareholder value, they do not explain how this value creation occurs. This paper shows that implicit claims provide a critical link that ties non-investor stakeholders and ESG to shareholder value, both its creation and its possible destruction.     

Secret Recipe of IPO survival: ESG disclosure and performance

While ESG initiation and disclosure may help newly listed companies maintain a social license to operate, mitigate information asymmetry, and attract investor attention, it may impose significant costs on initial public offering (IPO) firms and magnify agency problems. Using a sample of 1102 IPOs issued in the U.S and the ESG data from MSCI between 1999 and 2016, the paper empirically tests the competing hypotheses and examines the influence of ESG disclosure and performance on the survivability of IPOs. We document that (1) voluntary ESG disclosure reduces IPO failure risks and improves long-run performance of IPO; (2) the sooner ESG information is disclosed after the IPO, the greater the likelihood of survival and better long-run performance; and (3) IPOs with better ESG score are less likely to fail, with the impact largely attributable to the company's social and governance performance. Our findings identify new failure risks for IPOs, supply evidence of value-relevance of ESG, and provide practical guidance for managers.     

ESG preferences,risk and return

There are two primary factors that affect expected returns for companies with high ESG (environmental, social and governance) ratings—investor preferences and risk. Although investor preferences for highly rated ESG companies can lower the cost of capital, the flip side of the coin is lower expected returns for investors. Regarding risk, the jury remains out on whether there is an ESG-related risk factor. However, to the extent, ESG is a risk factor it also points towards lower expected returns for investments in highly rated companies. Though ESG investing may have social benefits, higher expected returns for investors are not among them.     

Fund ESG performance and downside risk: Evidence from China

Whether responsible investing reduces portfolio risk remains open to discussion. We study the relationship between ESG performance and downside risk at fund level in the Chinese equity mutual fund market. We find that fund ESG performance is positively associated with fund downside risk during the period between July 2018 and March 2021, and that the positive relationship weakens during the COVID-19 pandemic. We propose three channels through which fund ESG performance could affect fund downside risk: (i) the firm channel in which the risk-mitigation effect of portfolio firms’ good ESG practices could be manifested at fund level, (ii) the diversification channel in which the portfolio concentration of high ESG-rated funds could amplify fund downside risk, and (iii) the flow channel in which funds’ better ESG performance may attract greater investor flows that could reduce fund downside risk. We show evidence that the observed time-varying relationship between fund ESG performance and downside risk is driven by the relative force of the three channels.     

Analysis of ruin measures for the classical compound Poisson risk model with dependence

In this paper, we consider an extension to the classical compound Poisson risk model. Historically, it has been assumed that the claim amounts and claim inter-arrival times are independent. In this contribution, a dependence structure between the claim amount and the interclaim time is introduced through a Farlie–Gumbel–Morgenstern copula. In this framework, we derive the integro-differential equation and the Laplace transform (LT) of the Gerber–Shiu discounted penalty function. An explicit expression for the LT of the discounted value of a general function of the deficit at ruin is obtained for claim amounts having an exponential distribution.     

尾部风险研究进展与评述

由于部分业务、部门或市场的尾部风险溢出不仅会引发金融体系的“多米诺骨牌”效应,而且会对实体经济产生巨大负外部性,因此尾部风险事件极易引起金融市场震荡。鉴于此,识别与监测尾部风险是有效防控系统性金融风险爆发与传染的起点。本文首先以全球金融危机为节点,根据文献厘清尾部风险测度指标在危机前后的脉络。其次,介绍与尾部风险传染密切相关的尾部风险相依、金融关联网络的相关研究进展,在此基础上对尾部风险溢出强度及溢出方向展开讨论。再次,本文归纳了引发尾部风险溢出的宏观、中观和微观层面的影响因素以及尾部风险管理的路径选择。最后,对当前及未来尾部风险相关研究进行评述与展望。据此,力求为我国进一步提高防范化解金融风险能力、统筹推进疫情防控和经济社会发展、促进国民经济稳健运行和良性循环提供借鉴。     

ESG投资能够促进银行创造流动性吗?——兼论经济政策不确定性的调节效应

当前在我国致力于实现“碳达峰、碳中和”目标的大背景下,银行能否通过ESG投资促进流动性创造,进而推动高质量发展具有重大战略意义。本文利用2009年第一季度至2020年第二季度中国36家上市银行的面板数据,实证分析ESG投资对银行流动性创造的影响,并将其置于经济政策不确定性条件下予以讨论。研究发现:第一,ESG投资整体上促进流动性创造,表现为对资产端和负债端流动性创造的促进作用,以及对表外流动性创造的抑制作用。从ESG投资结构看,环境保护投资和社会责任投资均抑制流动性创造,而公司治理投资则促进流动性创造。异质性分析表明,地方性银行和资本短缺银行的ESG投资对流动性创造具有更强的促进作用。第二,中介机制分析发现,ESG投资主要通过“盈利”和“风险”渠道促进流动性创造。第三,在经济政策不确定性上升时期,ESG投资对流动性创造的促进作用更加显著。从ESG投资分项看,经济政策不确定性会增强环境保护投资和社会责任投资对流动性创造的抑制作用,以及公司治理投资对流动性创造的促进作用。本文结论为充分发挥ESG投资作用并以此推动高质量发展提供了政策启示。     

Dynamic Modeling of Tail Risk: Applications to China, Hong Kong and Other Asian Markets

In this paper, we study the extreme dependence between the markets in Hong Kong, Shanghai, Shenzhen, Taiwan and Singapore. The tail dependence coefficient (TDC), which measures how likely financial returns move together in extreme market conditions, is modeled dynamically using the Multivariate Generalized Autoregressive Conditional Heteroscedasticity model with the time-varying correlation matrix of Tse and Tsui (Journal of Business & Economic Statistics, 20(3):351–363, 2002). The time paths of the TDC indicate that Hong Kong stocks had the highest extreme dependence during the Asian financial crisis and their TDCs have followed an increasing trend since 2006. The results in this paper also show that the TDC pattern of Singapore with the other markets is very similar to the TDC pattern of Hong Kong with the other markets. An increasing trend in the extreme dependence between Shanghai A Share Index and Shanghai B Share Index and between the Hang Seng Index and the Hong Kong China Enterprise Index is observed from 2002 to 2007. A substantial rise in the TDC between Shenzhen A Share Index and Shenzhen B Share Index was recorded after the China market reforms in 2005. Our TDC modeling with Asian market data provides evidence that Asian markets are becoming integrated and their extreme co-movements during financial turmoil are becoming stronger.     

Modelling the nonlinear relationship between oil prices,stock markets,and exchange rates in oil-exporting and oil-importing countries

This article investigates the multivariate dependence between oil prices, equity markets, and exchange rates in certain oil-importing and oil-exporting countries by applying the vine copulas approach which offers a greater flexibility and permits the modelling of complex dependency patterns for high-dimensional distributions. Our results show that the dependence between oil and exchange rates is significantly negative during different periods of analysis, except for the British Pound and Japanese Yen exchange rates. This result indicates that oil may serve as a weak hedge against exchanges rates.     

Multivariate models for operational risk

Böcker and Klüppelberg [Risk Mag., 2005, December, 90–93] presented a simple approximation of OpVaR of a single operational risk cell. The present paper derives approximations of similar quality and simplicity for the multivariate problem. Our approach is based on the modelling of the dependence structure of different cells via the new concept of a Lévy copula.