边界Logistic违约率模型及实证研究

在前人研究基础上对边界Logistic违约率模型展开进一步研究.首先通过抽样分布性质的研究从理论上说明了为什么边界Logistic违约率模型更优越.然后利用中国公司数据展开实证研究,不仅找到了Cramer问题的中国证据,同时还发现边界Logistic违约率模型不仅能够克服Cramer问题、而且对临界值不敏感、同时预测效率也相对较高.     

债务违约风险与期权定价研究

论文分析当已知公司财务信息下的欧式期权定价问题,分别在公司资产服从Merton、Black&Cox和Leland&Toft违约风险模型下,给出了欧式期权的定价公式,并分别讨论了公司资本结构和债务违约边界对欧式期权价格的影响.     

违约暴露集中信用组合的违约损失研究

建立了违约暴露集中信用组合损失估计的递归模型,该模型容易编写计算程序实现.利用该模型,从VaR和经济资本的角度讨论了违约暴露集中对组合损失的影响.发现违约率相同时,对于高信用质量组合,违约暴露集中不会增加组合损失的风险,随着违约暴露集中程度的增加,为组合损失准备的经济资本反而减少;而对一般信用质量组合,违约暴露集中会增加组合损失的风险,随着违约暴露集中程度的增加,经济资本也要增加.对一般信用质量组合,违约暴露越分散,分散得越均匀,组合损失风险就越小,需要的经济资本就越少.     

代理成本与“信用价差之谜”

作为一个内生因素,企业中的代理问题可能会恶化企业的信用风险.通过将代理人与股东之间的最优合约模型嵌入到Leland-Toft内生违约框架中,研究了道德风险这一具体的代理问题对信用风险及信用价差的影响机制.结论表明:企业中的道德风险问题对企业信用风险产生明显影响,并且显著增加信用价差;对于描述道德风险的关键参数,论文建立的模型明确了它们在影响信用价差中起到的作用.由此,论文从代理问题的角度对“信用价差之谜”给出了合理解释.此外,文中也给出了债券价值、股权价值和内生违约边界的显性表达式.     

上市公司信用风险度量模型的实证比较研究

本文首次运用Merton模型和Leland-Toft模型对我国上市公司的信用风险进行了比较实证研究。研究结果表明,Merton模型对上市公司信用风险的预期违约率的计算明显太低。但是,违约距离的计算在一定程度上可以反映出不同公司信用风险存在的差异。而使用Leland-Toft模型计算信用风险的预期违约率较Merton模型有更高的敏感性、有效性。依据大公国际资信评级体系评级的结果,将A股50指数上市公司的信用评级等级,对比Leland-Toft模型计算的预期违约率,不同等级的上市公司,其预期违约率有明显的不同,说明其模型的预测是有效的。并且,也反映出近期预期违约率低而远期则较高的规律性。但是,计算的预期违约率还是偏低,说明Leland-Toft模型在用于目前的上市公司信用风险分析时,尚需调整有关的参数。     

基于信用评分模型的我国商业银行客户违约概率研究

信用风险是商业银行面临的最主要和最复杂的风险。《巴塞尔新资本协议》对信用风险的计量提出了标准法和内部评级法,指出有条件的银行要实施内部评级法,通过对历史数据构建模型测算客户的违约概率。本文结合内部评级法和我国的实际情况,从客户评级的角度,研究了个人客户违约概率和公司客户违约概率。     

信贷资产组合的异质性及其对信用风险损失的影响

本文结合Vasicek模型分析了信贷资产组合的异质性对信用风险损失的影响,并比较了模型中不同参数的异质性对损失的影响效果.分析结果显示,忽略异质性将对风险损失度量带来一定偏差,异质性对信贷组合的损失分布尤其是分布尾部具有较大的影响;较之信贷资产的行业相关性,违约率和违约波动率的异质性对损失分布的影响更为显著.     

上市公司信用债违约风险评估

利用上市公司的债券违约数据,从众多财务指标、公司治理指标、股票市场表现指标中逐步筛选出反映信用风险的指标,并采取经典的判别分析模型、Logistic回归模型、离散时间风险模型,对上市公司信用债违约的概率分别进行建模。最终确定了最适用于中国上市公司的风险评估模型。利用该模型对公司债进行评级,更能反映出公司债的信用风险差异。     

内生性回收率与信用风险度量研究

在信用风险模型中,外生性回收率的设定会忽略回收率对损失分布尾部的影响,而且会导致潜在的模型风险。本文将因子扩散过程引入结构信用风险模型,获得了回收率和违约概率之间的内在关系,利用Monte Carlo模拟方法数值分析了预期回收率对违约概率和资产价值波动率的依赖性,结果表明预期回收率与违约率之间具有很强的负相关关系,而且这种相关关系会受到债务人资产价值波动率的正向影响。在内生性回收率下,推导了信用损失的概率分布,计算了信用风险的Credit-VaR和ETF指标。最后利用市场数据检验了内生回收率信用风险模型的有效性,结果表明该模型可以很好的描述历史违约率和回收率的变化过程。     

考虑违约追偿和损失补偿的多中心集配网络联盟优化问题

针对多中心集配网络优化研究在网络联盟构建和机制设计方面存在的不足，研究考虑违约追偿和损失补偿的多中心集配网络联盟优化策略。首先，提出基于履约成员重要度的最小费用剩余节约方法，研究了履约成员应得利润问题，进而分别建立履约成员损失补偿和违约成员违约成本分摊模型，对履约成员应得补偿和违约成员违约成本进行了量化研究。其次，考虑违约行为导致的客户服务关系变化特征，构建了最小化网络运营总成本、车辆使用数以及服务等待时间的多目标优化模型。然后，提出了基于K-means多维聚类算法的CW-NSGA-Ⅲ混合启发式算法求解模型，该算法结合CW节约算法提高了初始可行解质量，应用精英保留策略增强了混合算法搜索性能，并引入基于路径偏移惩罚的边界交叉聚合方法改进了非支配解的选择机制，保证非支配解集的多样性，同时提高了其收敛速度，与MOGA、MOHSA和MOPSO算法进行对比分析，验证了算法的有效性。最后，结合实例对提出的模型和算法进行验证，并对不同违约成员数量和客户退出方式下的多中心集配网络优化结果进行了对比分析。结果表明，该方法能够量化违约成员违约成本，保障履约成员应得利润，完善联盟成员合作机制，并优化违约行为...     

Trade credit: the interaction of financing,marketing, operations,and risk behavior

This paper builds an inter-organizational Stackelberg game model of trade credit. The incentive-compatible decision on credit term is made endogenously and in coordination to ensure Pareto optimality for both the supplier and the retailer. Our model factors in financing, marketing, operations, default risk, and risk attitude coherently, treating trade credit as their intersectional nexus. We introduce the uncertainty due to the possible default of the retailer on the accounts payable into our model. The in-kind nature of trade credit is in line with the two-stage lottery method employed in this paper to capture the consequences of default on trade credit effectively. We find that financing capacity encourages the supplier to extend the credit term: a larger market demand rate prompts the supplier to extend a longer credit term, but a higher holding cost for the retailer shortens the length of the credit term received. More risk-averse suppliers tend to grant shorter term, but the impact of risk attitude is insignificant. Empirically, we find evidence supporting our main theoretical predictions by employing a panel sample of manufacturing companies covering 1998–2007 from the COMPUSTAT database.     

SOVEREIGN DEBT RESTRUCTURINGS: PREEMPTIVE OR POST‐DEFAULT

Sovereign debt restructurings can be implemented preemptively—prior to a payment default. We code a comprehensive new data set and find that preemptive restructurings (i) are frequent (38% of all deals 1978–2010), (ii) have lower haircuts, (iii) are quicker to negotiate, and (iv) see lower output losses. To rationalize these stylized facts, we build a quantitative sovereign debt model that incorporates preemptive and post‐default renegotiations. The model improves the fit with the data and explains the sovereign's optimal choice: preemptive restructurings occur when default risk is high ex ante, while defaults occur after unexpected bad shocks. Empirical evidence supports these predictions.     

External audit and bankruptcy prediction

In this paper, we investigate the relationship between external auditor characteristics and the likelihood of bankruptcy. We use a sample of US public companies to analyse whether auditor attributes are associated with default. We also test whether the inclusion of such attributes in bankruptcy prediction models improves their predictive ability. We find that firms audited by industry-expert auditors, large audit firms and long-tenured auditors are less likely to default. Firms with higher audit fees are more likely to default. Our results also show that the inclusion of auditor attributes significantly increases the predictive ability of bankruptcy prediction models. This paper contributes to the literature about auditing and bankruptcy prediction. Our results suggest that the auditor attributes can provide predictive signals concerning a default risk and that an external audit can play a relevant role in early warnings of financial distress. Our study also suggests that bankruptcy prediction models can become more effective if they are complemented with audit data. Our results are of interest to market participants, auditors, regulating authorities, banks and other financial institutions that are interested in credit risk assessment.     

Default and Punishment in General Equilibrium1

We extend the standard model of general equilibrium with incomplete markets to allow for default and punishment by thinking of assets as pools. The equilibrating variables include expected delivery rates, along with the usual prices of assets and commodities. By reinterpreting the variables, our model encompasses a broad range of adverse selection and signalling phenomena in a perfectly competitive, general equilibrium framework. Perfect competition eliminates the need for lenders to compute how the size of their loan or the price they quote might affect default rates. It also makes for a simple equilibrium refinement, which we propose in order to rule out irrational pessimism about deliveries of untraded assets. We show that refined equilibrium always exists in our model, and that default, in conjunction with refinement, opens the door to a theory of endogenous assets. The market chooses the promises, default penalties, and quantity constraints of actively traded assets.     

基于Copula风险中性校准的违约相关性研究

违约率的估计是IRB法的核心要素之一,违约相关性是违约概率研究和估计的不可忽略的重要因素,目前的研究大多通过资产相关替代研究违约相关。风险中性可降低模型风险带来的估计误差。本文针对CDS's特征构建了风险中性违约相关估算的Copula模型,并提出了Copula选择方法且进行了实例分析,发现8自由度学生t-Copula是最优的。     

A Quantitative Theory of Unsecured Consumer Credit with Risk of Default

We study, theoretically and quantitatively, the general equilibrium of an economy in which households smooth consumption by means of both a riskless asset and unsecured loans with the option to default. The default option resembles a bankruptcy filing under Chapter 7 of the U.S. Bankruptcy Code. Competitive financial intermediaries offer a menu of loan sizes and interest rates wherein each loan makes zero profits. We prove the existence of a steady‐state equilibrium and characterize the circumstances under which a household defaults on its loans. We show that our model accounts for the main statistics regarding bankruptcy and unsecured credit while matching key macroeconomic aggregates, and the earnings and wealth distributions. We use this model to address the implications of a recent policy change that introduces a form of “means testing” for households contemplating a Chapter 7 bankruptcy filing. We find that this policy change yields large welfare gains.     

Taxes and the choice between risky and risk-free debt: on the neutrality of credit default taxation

Shareholders can decide if their corporation issues risky or risk-free debt. We identify tax systems in which the choice between risky and risk-free debt is not distorted by taxes. These credit default neutral tax systems make it possible to make capital structure decisions and firm valuations neglecting credit default risk, even after taxes. Thus credit default neutrality is a characteristic of a tax system that helps to reduce planning costs. Moreover, credit default neutrality is a necessary condition for financial neutrality of taxation. We find one class of credit default neutral taxes that preserves and another class that modifies the expected tax distribution between creditors and debtor firm. Finally, we show the influence of personal taxation on credit default neutrality.

Solving the Feldstein–Horioka Puzzle With Financial Frictions

Unlike the prediction of a frictionless open economy model, long‐term average savings and investment rates are highly correlated across countries—a puzzle first identified by Feldstein and Horioka (1980). We quantitatively investigate the impact of two types of financial frictions on this correlation. One is limited enforcement, where contracts are enforced by the threat of default penalties. The other is limited spanning, where the only asset available is noncontingent bonds. We find that the calibrated model with both frictions produces a savings–investment correlation and a volume of capital flows close to the data. To solve the puzzle, the limited enforcement friction needs low default penalties under which capital flows are much lower than those in the data, and the limited spanning friction needs to exogenously restrict capital flows to the observed level. When combined, the two frictions interact to endogenously restrict capital flows and thereby solve the Feldstein–Horioka puzzle.     

Myopic Analysis for Multi‐Echelon Inventory Systems with Batch Ordering and Nonstationary/Time‐Correlated Demands

We provide an exact myopic analysis for an N‐stage serial inventory system with batch ordering, linear ordering costs, and nonstationary demands under a finite planning horizon. We characterize the optimality conditions of the myopic nested batching newsvendor (NBN) policy and the myopic independent batching newsvendor (IBN) policy, which is a single‐stage approximation. We show that echelon reorder levels under the NBN policy are upper bounds of the counterparts under both the optimal policy and the IBN policy. In particular, we find that the IBN policy has bounded deviations from the optimal policy. We further extend our results to systems with martingale model of forecast evolution (MMFE) and advance demand information. Moreover, we provide a recursive computing procedure and optimality conditions for both heuristics which dramatically reduces computational complexity. We also find that the NBN problem under the MMFE faced by one stage has one more dimension for the forecast demand than the one faced by its downstream stage and that the NBN policy is optimal for systems with advance demand information and stationary problem data. Numerical studies demonstrate that the IBN policy outperforms on average the NBN policy over all tested instances when their optimality conditions are violated.