非系统风险和股票预期收益研究——基于上海证券交易所的股票数据

本文选用2001年至2008年在上海证券交易所上市交易的211支股票的月度数据,对个股的非系统风险和股票预期收益之间的关系进行了实证研究。对于非系统风险的估计,本文采用了直接法,即对个股按照Fama的三因素模型进行回归,回归结果中的残差即为个股所面临的非系统波动率也即非系统风险。在得到个股的非系统波动率之后,本文将个股的公司规模因素、换手率因素、账面市值比因素以及滞后一期的非系统波动率作为自变量,个股的超额收益率作为因变量来研究股票的非系统风险和预期收益之间的关系。实证结果表明个股的非系统风险与预期收益之间是显著为负的关系,即若个股的非系统风险越大,则其预期收益越低。     

国家风险评价指标体系对比研究

西方主流风险评级机构针对国家风险推出了不同的评级排序.本文基于六家评级机构的八个评价体系的指标以及数据,包括政治风险、经济风险、金融风险、信用风险、经济自由、腐败风险等等,从总量风险和要素风险两个角度对评级结果和指标体系进行对比分析.实证结果发现:虽然各个评级机构的指标类型与数据来源各不相同,但是总量风险评级结果存在很强的相关性;国家风险评级指标可以根据不同的受众需求按照风险要素进行分类.本文的研究着眼于更加全面的国家风险评价,深化了对评价指标体系的理解,拓展了对风险类型及其构成的认识.     

上证电子信息行业股票系统的风险分析

资本市场的发展的核心问题是市场的效率。通过股权分置改革，我国的资本市场得到了很好的发展。本文选取上证电子信息行业各公司自上市以来的数据，根据资本资产定价模型，利用普通最小二乘法（OLS），对CAPM模型中的β系数进行拟合，对统计结果做出解释。分别计算出总体和股改前后电子信息股的β系数和R^2数值，发现电子信息行业个股的波动比大盘的波动明显，个股风险偏高；该行业具有较小的系统风险。     

ESG评级对我国商业银行系统性风险的影响研究

基于中国36家上市银行2009～2022年的季度面板数据，利用DCC-SVR-GARCH-CoVaR模型测算系统性风险溢出率，实证分析ESG评级对我国商业银行系统性风险的影响及作用机制。研究发现：ESG评级提高能够显著削弱我国商业银行的系统性风险水平，且ESG评级提高对银行系统性风险水平的削弱作用主要由公司治理（G维度）驱动；地方性银行的ESG评级提高对系统性风险水平的削弱作用更强；ESG评级提高会通过降低银行违约风险发生的概率、减小银行与客户之间的信息不对称程度两种渠道削弱商业银行的系统性风险；经济政策不确定性提升会强化ESG评级提高对银行系统性风险的抑制作用。鉴于此，应充分完善ESG评级体系，将ESG评级纳入商业银行业务战略、内部治理与风险管理体系中，以提高商业银行的风险防控能力。     

大规模高纬度金融资产的系统风险测量——基于动态条件异方差潜在因子模型的视角

从大量的金融资产中提取出的系统风险比基于β系数的单变量方法更为有效,但资产规模的增加会导致"纬数灾难"等问题,难以获得准确估计。本文在将金融资产收益分为公共系统因素和个体特质因素基础上,提出用具有条件异方差形式的动态潜在因子模型(CHDL)估计和预测动态系统因素,用非参数核密度估计系统下跌时的边际期望损失(MES)。本文利用上海证券市场180只样本股进行实证分析,通过IC和Onat检验发现个股和各板块存在显著的系统因子;利用CHDL模型对个股和各板块的系统因子和资产未来收益进行估计和预测,在此基础上计算边际期望损失。Mincer-Zarnowitz回归最优检验法表明,CHDL模型计算的系统风险比常用的市场指数模型具有更高的准确性。     

管理层风险偏好、盈余管理与企业信用评级北大核心

债券市场违约事件频发使企业信用评级受到质疑,作为企业决策主体,管理层的风险偏好是否以及如何影响企业信用评级值得探讨。以2013~2017年有企业信用评级的A股上市公司为样本,采用Ologit和OLS回归模型实证检验管理层风险偏好、盈余管理与企业信用评级之间的关系。实证结果表明:管理层风险偏好与企业信用评级呈显著正向变动关系,表明管理层风险偏好会影响信用评级机构对企业整体信用风险的评估;管理层风险偏好对企业信用评级的影响,部分是通过盈余管理活动来实现的。     

债券信用评级能否反映大客户风险?

大客户具有较强的议价能力,客户集中度风险是企业风险管理的重要内容.以往的研究主要集中于客户集中度过高对股票市场的影响,较少关注债券市场中评级机构对发行人大客户风险的甄别能力.本文以2007～2019年发行公司债为样本,检验了债券信用评级对客户集中度风险的揭示程度.实证研究发现:客户集中度越高,信用评级机构的评级等级越低,并带来了更高的信用利差;相比发行人付费评级,投资人付费的独立评级对高客户集中度公司的评级水平相对更低,对大客户风险的甄别效果更好.进一步研究发现,两类评级模式对大客户风险甄别效果的差异在应收账款周转更慢、盈余管理程度更高的企业中表现得更明显;两类评级模式对于国有企业大客户风险的甄别效果均较弱.本文的研究结果表明,债券信用评级市场基本能反映大客户风险,但发行人付费评级模式下对大客户风险还存在一定的虚高评级,应鼓励投资人付费信用评级的发展,促进信用评级体系的有序竞争.     

企业信用风险度量模型的框架设计

企业信用风险一般是指企业在其外部债务到期时无力偿还，从而使企业自身面临着破产清算的困境，并使债权人遭受损失的可能性。目前，我国企业信用缺失严重，如何科学有效地度量信用风险，以更好地防范和控制风险的恶化已成为理论界和实务界研究的主要课题。本正是在分析了国内外信用度量方法的基础上，针对我国的实际情况，设计了一个“以商业化运作的数据平台为支持，以商业银行为主体，各类征信公司和评级机构为辅助的企业信用风险的综合度量模型”的基本框架。     

大数据背景下企业审计风险成因及其应对措施探讨

随着大数据技术在企业界的广泛应用，企业的财务数据形式和审计方式也发生了很大变化，传统的审计风险模型已经不再适合当前大数据环境下的企业审计风险评估。本文旨在大数据背景下探索优化传统审计风险模型，通过分析审计风险的具体成因，提出了应对措施，以供参考借鉴。     

基于风险视角的ESG评级价值相关性再思考

投资者对可持续发展的关注推动了ESG评级的快速发展。ESG评级能否提供价值相关的信息成为研究热点,但结论并不一致。基于实践中更为普遍的ESG负面筛选策略,本文创新性地从风险角度检验ESG风险评级与投资价值之间的关系,以重新审视ESG评级的价值相关性。具体地,本文借助评价ESG风险暴露程度的RepRisk评级数据,验证ESG风险评级对公司股票回报率与波动性的影响,并进一步对比分析ESG正面评级的价值相关性。研究发现,ESG风险越高的公司,其股票回报率越低,股价波动性越大,但ESG正面评级的价值相关性并不稳定。在此基础上,本文提出我国ESG信息披露与ESG投资未来发展的建议。     

The multi-state latent factor intensity model for credit rating transitions

A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic factors. The model has a generalized semi-Markov structure designed to accommodate many of the stylized facts of credit rating migrations. Parameter estimation is based on Monte Carlo maximum likelihood methods for which the details are discussed in this paper. A simulation experiment is carried out to show the effectiveness of the estimation procedure. An empirical application is presented for transitions in a 7 grade rating system. The model includes a common dynamic component that can be interpreted as the credit cycle. Asymmetric effects of this cycle across rating grades and additional semi-Markov dynamics are found to be statistically significant. Finally, we investigate whether the common factor model suffices to capture systematic risk in rating transition data by introducing multiple factors in the model.     

A model for risk classification of banks

This paper deals with designing a bank risk classification scheme based on readily available performance data. This risk rating is referred to as ‘Risk rating’. Due to non-availability of data on CAMEL rating (C rating), R risk rating has potential for studying risk-based premiums insurance policy and for determining optimal frequencies for variable frequency on-site examination policy. A composite non-performance measure is developed to estimate probability of failure of a bank based on performance data available in bank call reports by fitting a Logit curve and estimating its parameters using maximum likelihood method. Division of banks into healthy and watchful types is based on critical dividing value of probability of failure.     

中国上证综合与恒生指数的风险度评估

针对中国上证综合与香港恒生指数的风险度问题，提出从风险波动的深度、广度、持久度三个方面分别进行评估，其中测量波动深度采用了VAR指标，测量波动的广度采用了极差R指标，测量风险存在的持久度采用了Hurst指数指标，综合这三方面的因素运用风险度评价指数r来评价指数的风险。选择2000年1月3日至2009年9月1日的中国上证综合与香港恒生的日收益率研究对象进行分析，结果发现：上证指数波动的深度、持久性要比恒生指数大，而波动的宽度要比恒生指数小。在本文研究期间内，上证指数的风险评价指数要比恒生指数小，这在一定程度上说明上证指数的风险度要比恒生指数小。     

中小企业板运输仓储上市企业的财务风险评价

选取了深市中小企业板上市的13家运输仓储企业的2019年年度财务数据,采用主成分分析的方法对样本公司的财务风险进行了评价。研究结果表明:样本公司的财务风险整体较高,且不同样本公司间的财务风险差异较大;各样本公司在偿债能力、营运能力、盈利能力与发展能力四个方面均有所不同,且差异比较明显;财务风险等级为“低风险”的公司有3家,“一般风险”的公司有1家,“较高风险”的公司有8家,“高风险”的公司有1家。最后,基于上述研究结果,对上市公司的财务管理提出了相关建议。     

Fiscal Rules and Financial Systems: Complements or Substitutes?

We study the effect of fiscal rules on a country's credit rating and their interaction with financial development. We build a rich set of panel data, which includes a novel index for the strength of fiscal rules. We find a positive and significant effect of fiscal rules on sovereign ratings. We also find that this effect is attenuated in economies with a more developed domestic financial system. Therefore, financial markets act as a substitute for fiscal rules in lowering the default risk assessed by credit rating agencies. This substitution effect between fiscal rules and financial development is mostly triggered through the monitoring and enforcement dimension of fiscal rules.     

An Empirical Assessment of Country Risk Ratings and Associated Models

Abstract.  Country risk has become a topic of major concern for the international financial community over the last two decades. The importance of country ratings is underscored by the existence of several major country risk rating agencies, namely the Economist Intelligence Unit, Euromoney, Institutional Investor, International Country Risk Guide, Moody's, Political Risk Services, and Standard and Poor's. These risk rating agencies employ different methods to determine country risk ratings, combining a range of qualitative and quantitative information regarding alternative measures of economic, financial and political risk into associated composite risk ratings. However, the accuracy of any risk rating agency with regard to any or all of these measures is open to question. For this reason, it is necessary to review the literature relating to empirical country risk models according to established statistical and econometric criteria used in estimation, evaluation and forecasting. Such an evaluation permits a critical assessment of the relevance and practicality of the country risk literature. The paper also provides an international comparison of risk ratings for twelve countries from six geographic regions. These ratings are compiled by the International Country Risk Guide, which is the only rating agency to provide detailed and consistent monthly data over an extended period for a large number of countries. The time series data permit a comparative assessment of the international country risk ratings, and highlight the importance of economic, financial and political risk ratings as components of a composite risk rating.     

A coupled Markov chain approach to credit risk modeling

We propose a Markov chain model for credit rating changes. We do not use any distributional assumptions on the asset values of the rated companies but directly model the rating transitions process. The parameters of the model are estimated by a maximum likelihood approach using historical rating transitions and heuristic global optimization techniques.We benchmark the model against a GLMM model in the context of bond portfolio risk management. The proposed model yields stronger dependencies and higher risks than the GLMM model. As a result, the risk optimal portfolios are more conservative than the decisions resulting from the benchmark model.     

基于港口供应链的风险预警与实证探究

首先分析了供应链风险预警和港口供应链问题,并以SCOR模型为基础结合统计实证构建了港口供应链的风险预警指标体系,并基于Hallikas的供应链风险双因素框架建立了双因素评估模型,最后就青岛港前港公司矿石供应链进行了实证检验,得出其供应链风险等级状况。     

Two new mean–variance enhanced index tracking models based on uncertainty theory

The enhanced index tracking (EIT) problem is concerned with selecting a tracking portfolio that achieves an excess return over a given benchmark with a minimum tracking error. This paper explores the EIT problem by providing two new mean–variance EIT models based on uncertainty theory where stock returns are treated as uncertain variables instead of random variables and stock return distributions are estimated by experts instead of from historical data. First, this paper formulates an uncertain enhanced index tracking (UEIT) model and analyzes the characteristic of the UEIT frontier. Then to reduce the tracking portfolio’s risk, this paper adds a risk index (RI) constraint to the UEIT model and proposes a UEIT-RI model. Next, by comparing the UEIT and UEIT-RI models this paper gives the advantages of the two models. Investors can choose the model according to their preferences. Finally, this paper conducts numerical examples to illustrate the application of the two models and the analysis results.     

信用评级在估计债券信用风险损失中的应用

债券信用评级有效地揭示了债券的相对信用风险,为债券投资者提供了重要的投资决策参考。在计算债券信用风险损失中,可以充分利用评级公司公布的数据来具体的计算出各债券的信用风险值,本文给出这种方法和例子。