“投资人付费”vs.“发行人付费”:谁的信用评级质量更高？

本文选择2011-2015年被中债资信覆盖的发债A股上市公司作为主要研究对象,比较了“投资人付费”与“发行人付费”模式下的评级质量高低。研究发现:(1)与“发行人付费”评级相比,采用“投资人付费”模式的中债资信所作评级显著更低。(2)与“发行人付费”评级相比,当采用“投资人付费”模式的中债资信所作评级越低时,发行人未来盈利能力越差、预期违约风险越高,投资者要求的风险补偿也越高,这表明“投资人付费”模式下的信用评级质量更高。(3)“发行人付费”模式的评级结果可以在一定程度上反映公司的内部私有信息,但由于同时存在独立性缺失问题,“发行人付费”模式的信用评级质量仍然不如“投资人付费”模式的信用评级质量,这说明独立性对于评级机构尤其重要。     

影响信用评级市场发展与评级产品应用的几个问题

我国信用评级市场发展和评级产品应用受制于法律法规不完善、评级管理不统一、评级需求失衡、制度机制不协调等因素。应加快信用评级市场管理的法制建设,明确信用评级市场的地位与作用,理顺监管体制和管理机制,加强对信用评级产品应用的政策扶持,提高信用评级市场自我发展能力。     

评级膨胀、双评级规范的网络效应与美国信用评级霸权

与通货膨胀一样,评级膨胀具有持久的、螺旋上升的和影响深远的危害性。信用评级在本质上只是一个相对风险措施,典型的信用评级并不能完全反映宏观经济周期。对国家和投资者来说,信用评级所导致的风险与威胁主要来自于＂信用评级膨胀＂。而究其根本,评级膨胀的大规模泛滥最终得益于美国两大评级机构的双评级规范霸权,以及由美国评级机构所垄断的国际评级网络。由于存在激励促使他们逃避基于评级的监管,因此道德风险在所难免,并一定会催生评级膨胀。因此,评级膨胀只是表象和媒介,双评级规范和网络效应才是美国评级霸权的最终顶点。     

Market structure and rating strategies in credit rating markets – A dynamic model with matching of heterogeneous bond issuers and rating agencies

This paper investigates the impact of rating agencies in a market with asymmetric information. In particular, the role of credit rating agencies as an intermediary between investors and bond issuers is discussed. We model this setting in a dynamic framework in which both rating agencies and bond issuers are of heterogeneous quality. Rating agencies can apply costly research technology to reveal the fundamental nature of bond issuers and engage in rating smoothing. We show that rating smoothing can compensate for low research quality, even though it is accompanied by a quality deterioration in the rating market and market clustering. Moreover, low-quality bond issuers have a general tendency to match with low-quality rating agencies. If investors place a strong emphasis on the reputation of rating agencies, rating markets also tend to be strongly clustered.     

The Nature and Persistence of Initial Public Offering Aftermarket Returns Predictability

This paper examines the predictability of monthly aftermarket returns of initial public offerings during the first six years of trading. Predictability is tested under the null hypothesis of random walk using a Markov chain analysis. The evidence shows that excess returns of IPOs (adjusted for the return on the equally weighted NASDAQ index) demonstrate non-random walk behavior through the first five years of trading and random walk behavior in the sixth year. This is accompanied by predictability of monthly excess returns conditioned on the two previous months' excess returns. A trading strategy is offered to capitalize on the predictability patterns. Implementing the trading strategy is not possible due to institutional barriers, providing additional explanation for why IPOs do not reach their intrinsic values for extended periods of time.     

Valuation of quanto options in a Markovian regime-switching market: A Markov-modulated Gaussian HJM model

We consider the valuation of European quanto call options in an incomplete market where the domestic and foreign forward interest rates are allowed to exhibit regime shifts under the Heath–Jarrow–Morton (HJM) framework, and the foreign price dynamics is exogenously driven by a regime switching jump-diffusion model with Markov-modulated Poisson processes. We derive closed-form solutions for four different types of quanto call options, which include: options struck in a foreign currency, a foreign equity call struck in domestic currency, a foreign equity call option with a guaranteed exchange rate, and an equity-linked foreign exchange-rate call.     

Regulations for the Eighth International Congress of Actuaries

Abstract

The present paper proposes and investigates a procedure for numerical evaluation of the transition probabilities for a time-inhomogeneous Markov process when the intensities are known (estimated). The procedure is based on Taylor-expansion of the transition probabilities linked with the Chapman-Kolmogorov equations.     

Information stages in efficient markets

Market efficiency, in its strong form, asserts that asset prices fully reflect all available information. The classical event study methodology attempts to make explicit this link by assuming rigid and universal pre-event, event, and post-event periods. As an alternative, our framework captures the progressive diffusion of information around events as well as the overlapping impacts of separate events. We also illustrate that our approach captures mean-reversion of expected returns and increased volatility around announcement dates. These features reflect latent regime switches and are associated with semi-strong market efficiency.     

普惠金融与移动支付使用意愿影响因素-—以重庆为例

我国普惠金融发展面临的最大难题是如何满足低收入群体、农村及偏远地区居民对金融服务的需求,移动支付的发展为应对这一难题提供了解决途径。本文对334份有效样本数据进行实证研究,在技术接受模型的基础上,引入感知理论,同时增加了趣味性、外部影响、个人创新性等影响因素,最终构建影响研究对象使用移动支付意愿的理论模型。本文通过建立马尔科夫链,揭示研究对象使用移动支付意愿的总体情况,进行逐步回归分析得出影响移动支付使用意愿的主要因素,最后综合数据分析的结果,提出对策建议。     

Counterparty Risk for Credit Default Swaps: Markov Chain Interacting Intensities Model with Stochastic Intensity

We analyze the counterparty risk for credit default swaps using the Markov chain model of portfolio credit risk of multiple obligors with interacting default intensity processes. The default correlation between the protection seller and underlying entity is modeled by an increment in default intensity upon the occurrence of an external shock event. The arrival of the shock event is a Cox process whose stochastic intensity is assumed to follow an affine diffusion process with jumps. We examine how the correlated default risks between the protection seller and the underlying entity may affect the credit default premium in a credit default swap.     

Structural Changes in Volatility of Foreign Exchange Rates after theAsian Financial Crisis

Regime-shift models of daily returns are estimated for the foreign exchange rates of the Asian currencies that suffered from drastic devaluation during the Asian financial crisis in 1997, and the change points are detectedfor their volatility structures. Furthermore, how the persistence in the volatility of their exchange rates changed after the crisis is examined.     

A link between complete models with stochastic volatility and ARCH models

In this paper, we propose a heteroskedastic model in discrete time which converges, when the sampling interval goes to zero, towards the complete model with stochastic volatility in continuous time described in Hobson and Rogers (1998). Then, we study its stationarity and moment properties. In particular, we exhibit a specific model which shares many properties with the GARCH(1,1) model, establishing a clear link between the two approaches. We also prove the consistency of the pseudo conditional likelihood maximum estimates for this specific model.Received: December 2002Mathematics Subject Classification: 90A09, 60J60, 62M05JEL Classification: C32This work was supported in part by Dynstoch European network. Thanks to David Hobson for introducing me to these models, and to Valentine Genon-Catalot for numerous and very fruitful discussion on this work. The author is also grateful to Uwe Kuchler for various helpful suggestions, and to two referees and an associate editor for their comments and suggestions.