Catastrophe Bonds—Regulating a Growing Asset Class

As the severity of natural catastrophes continues to intensify, disaster risk management is becoming increasingly important. In order to expand the capacity of the insurance markets, insurers and reinsurers have utilized alternative risk financing mechanisms such as catastrophe (CAT) bonds. Although the CAT bond market has increased recently, past CAT bond defaults have demonstrated that there are still concerns relating to contract documentation and the collateral structure of the bonds. This article argues that additional regulation that addresses these contracting problems and financial risks would facilitate greater use of CAT bonds. Regulatory change should also include industry‐wide accounting and tax reforms that will further support risk management objectives and the growth of the market. If the CAT bond market continues to experience the growth that was witnessed in the past year and additional regulation is implemented, insurers, reinsurers and governments can benefit from the cost‐effective protection that the instruments may provide in the event of a mega‐catastrophe.     

巨灾风险债券溢价之谜的行为金融学解释

作为一种新型金融工具,巨灾风险债券自发行以来所附带的风险收益就远高于同等级传统债券的收益.尽管均值方差分析方法已证明"溢价之谜"确实存在,但从传统理论角度出发的研究并不能充分解释巨灾风险债券高溢价的成因.本文尝试用行为金融理论分析以获得较合理的解释补充.通过探讨投资者的心理、行为因素在巨灾风险债券溢价之谜中所起的重要作用,得出结论:风险厌恶、固定教育成本、模糊厌恶和羊群效应等行为导致了溢价之谜的出现.这些影响因素的发现不仅是对国际巨灾风险债券市场中的高溢价现象进行解释的重要依据,同时也为我国科学发行巨灾风险债券提供了思路.     

中国市场利率流动性溢酬实证分析

市场利率的流动性溢酬(liquiditypremium),也称为期限溢酬(termpremium),是为了弥补投资者投资于长期证券所承担的额外利率波动风险(Hicks,1942)。这种风险一般随着期限的延长而增加,因此,相应的流动性溢酬也要随着期限的延长而增加。本文在郑振龙、林海(2003)对中国利率期限结构的静态估计的基础之上,通过一个直接的通用模型对中国市场利率的流动性溢酬进行了实证考察和分析,这个模型直接使用总收益率而不是利率的概念,从而就可以避免Nelson(1972)所提出的问题,而且没有对利率的分布做任何假定。同时为了比较分析不同期限的流动性溢酬,这个模型还进行了标准化处理。检验结果表明,中国存在比较明显的流动性溢酬,而且这个流动性溢酬水平随着期限的延长而上升。而且,通过对流动性溢酬随时间变动情况的分析,发现不同期限的流动性溢酬都随时间变动,因此常数流动性溢酬假设就被拒绝。     

Reduced-form Models with Regime Switching: An Empirical Analysis for Corporate Bonds

Empirical evidence shows that there is a close link between regime shifts and business cycle fluctuations. A standard term structure of interest rates, such as the Cox et al. (1985 Econometrica, 53, 385–407; CIR) model, is sharply rejected in the Treasury bond data. Only Markov regime-switching models on the entire yield curve of the Treasury bond data can account for the observed behavior of the yield curve. In this paper, we examine the impact of regime shifts on AAA-rated and BBB-rated corporate bonds through the use of a reduced-form model. The model is estimated by the Efficient Method of Moments (EMM). Our empirical results suggest that regime-switching risk has significant implications for corporate bond prices and hence has a material impact on the entire corporate bond yield curve, providing evidence for the approach of rating through the cycle employed by rating agencies.     

Structural Models of Corporate Bond Pricing: An Empirical Analysis

This article empirically tests five structural models of corporatebond pricing: those of Merton (1974), Geske (1977), Longstaffand Schwartz (1995), Leland and Toft (1996), and Collin-Dufresneand Goldstein (2001). We implement the models using a sampleof 182 bond prices from firms with simple capital structuresduring the period 1986–1997. The conventional wisdom isthat structural models do not generate spreads as high as thoseseen in the bond market, and true to expectations, we find thatthe predicted spreads in our implementation of the Merton modelare too low. However, most of the other structural models predictspreads that are too high on average. Nevertheless, accuracyis a problem, as the newer models tend to severely overstatethe credit risk of firms with high leverage or volatility andyet suffer from a spread underprediction problem with saferbonds. The Leland and Toft model is an exception in that itoverpredicts spreads on most bonds, particularly those withhigh coupons. More accurate structural models must avoid featuresthat increase the credit risk on the riskier bonds while scarcelyaffecting the spreads of the safest bonds.     

Libor Market Models versus Swap Market Models for Pricing Interest Rate Derivatives: An Empirical Analysis

We empirically compare Libor and Swap Market Models for the pricing of interest rate derivatives, using panel data on prices of US caplets and swaptions. A Libor Market Model can directly be calibrated to observed prices of caplets, whereas a Swap Market Model is calibrated to a certain set of swaption prices. For both models we analyze how well they price caplets and swaptions that were not used for calibration. We show that the Libor Market Model in general leads to better prediction of derivative prices that were not used for calibration than the Swap Market Model. Also, we find that Market Models with a declining volatility function give much better pricing results than a specification with a constant volatility function. Finally, we find that models that are chosen to exactly match certain derivative prices are overfitted; more parsimonious models lead to better predictions for derivative prices that were not used for calibration.     

An Empirical Analysis of Exchange Ratio Determination Models for Merger: A Note

This paper examines the empirical validity of two exchange ratio determination models for merger, the Larson and Gonedes (LG) PE model and the Yagil dividend growth model. These two models formulate exchange ratios as a function of a different factor: expected post-merger price-earnings multiple and expected post-merger dividend growth, respectively. While the LG model has been tested in previous studies, the Yagil model has yet been subject to empirical testing. This paper finds empirical support for the LG model but finds weak support for the Yagil model. In particular, the results show that the number of stock mergers that result in wealth gains for both acquiring and target firms and hence conform to the rationality assumption of each model is substantially greater for the LG model than for the Yagil model. Regression analysis provides confirmatory evidence on the empirical validity of the LG model that PE-related variables play a more significant role in explaining the actual exchange ratios than growth-related variables.     

Libor Market Models versus Swap Market Models for Pricing Interest Rate Derivatives: An Empirical Analysis

We empirically compare Libor and Swap Market Models for thepricing of interest rate derivatives, using panel data on pricesof US caplets and swaptions. A Libor Market Model can directlybe calibrated to observed prices of caplets, whereas a SwapMarket Model is calibrated to a certain set of swaption prices.For both models we analyze how well they price caplets and swaptionsthat were not used for calibration. We show that the Libor MarketModel in general leads to better prediction of derivative pricesthat were not used for calibration than the Swap Market Model.Also, we find that Market Models with a declining volatilityfunction give much better pricing results than a specificationwith a constant volatility function. Finally, we find that modelsthat arechosen to exactly match certain derivative prices areoverfitted; more parsimonious models lead to better predictionsfor derivative prices that were not used for calibration. JELClassification: G12, G13, E43.     

An Empirical Analysis of Exchange Ratio Determination Models for Merger: A Note

This paper examines the empirical validity of two exchange ratio determination models for merger, the Larson and Gonedes (LG) PE model and the Yagil dividend growth model. These two models formulate exchange ratios as a function of a different factor: expected post-merger price-earnings multiple and expected post-merger dividend growth, respectively. While the LG model has been tested in previous studies, the Yagil model has yet been subject to empirical testing. This paper finds empirical support for the LG model but finds weak support for the Yagil model. In particular, the results show that the number of stock mergers that result in wealth gains for both acquiring and target firms and hence conform to the rationality assumption of each model is substantially greater for the LG model than for the Yagil model. Regression analysis provides confirmatory evidence on the empirical validity of the LG model that PE-related variables play a more significant role in explaining the actual exchange ratios than growth-related variables.     

The Effects of Regulated Premium Subsidies on Insurance Costs: An Empirical Analysis of Automobile Insurance

State regulation of rates is sometimes used as a means to make automobile insurance more affordable to consumers by restricting insurer profits and pricing practices. Incentive distortions arising from this type of rate regulation might lead to higher accident rates and higher insurance loss costs. Annual state‐level panel data for the time period 1980–1998 are used to investigate these effects, using empirical methods that recognize the endogenous determination of states’ regulatory choices. Results suggest that rate regulation that systematically suppresses (some or all) drivers’ insurance premiums is associated with significantly higher average loss costs and higher insurance claim frequency.     

Recent Research Developments Affecting Nonlife Insurance—The CAS Risk Premium Project 2014 Update

This article discusses the main results of the Casualty Actuarial Society Risk Premium Project 2014 update. It reviews the recent research developments in the process of nonlife risk assessment. Of special note, systemic risk continuously attracts a great deal of attention. In the past year, reinsurance studies have increased significantly, driven by progress in optimal reinsurance design and reinsurance asymmetric information. Both topics show the academic reflection of financial crisis in the field of risk and insurance. The evaluation of reserves and the methods mitigating asymmetric information have also received a great deal of attention.     

An Empirical Comparison of Option‐Pricing Models in Hedging Exotic Options

This paper examines the empirical performance of various option‐pricing models in hedging exotic options, such as barrier options and compound options. A practical and relevant testing approach is adopted to capture the essence of model risk in option pricing and hedging. Our results indicate that the exotic feature of the option under consideration has a great impact on the relative performance of different option‐pricing models. In addition, for any given model, the more “exotic” the option, the poorer the hedging effectiveness.     

An Empirical Comparison of Convertible Bond Valuation Models

This paper empirically compares three convertible bond valuation models. We use an innovative approach where all model parameters are estimated by the Marquardt algorithm using a subsample of convertible bond prices. The model parameters are then used for out-of-sample forecasts of convertible bond prices. The mean absolute deviation is 1.86% for the Ayache-Forsyth-Vetzal model, 1.94% for the Tsiveriotis-Fernandes model, and 3.73% for the Brennan-Schwartz model. For this and other measures of fit, the Ayache-Forsyth-Vetzal and Tsiveriotis-Fernandes models outperform the Brennan-Schwartz model.     

通货膨胀率对保费收入的非对称影响——基于1982-2010年广西统计数据的实证

基于广西保险市场1982-2010年统计数据的实证分析表明,保费收入对于物价波动的反应是非对称的。温和的通货膨胀能够促进保险业务的发展,而奔腾的通货膨胀则起到阻碍的作用。而且与温和的通货膨胀相比较,市场需求对奔腾的通货膨胀的反应更加强烈。在目前温和的通货膨胀情况下,首先保险业需要抓住扩大内需的有利时机,积极创新通货膨胀指数化的保险产品;其次,政府要加强通货膨胀管理,防止奔腾的通货膨胀。     

An Empirical Investigation of Alternative Contingent Claims Models for Pricing Residential Mortgages

Researchers have employed option pricing techniques to analyze mortgage financing and valuation. Alternative models (one-, two-, and three-variable models) employing different variables (short- and long-term interest rates and building value) have been designed to price mortgage securities. No prior research has addressed the question of whether the pricing accuracy of these contingent claims models improves as states increase or whether contingent claims models' valuation abilities generate reasonable estimates of primary mortgage market prices. The articles investigates the relative efficiency of each of these alternative mortgage valuation models in predicting primary market mortgage values. Our results show that a two-variable model (short rate and building value) is the most efficient. Valuation results indicate a positive pricing spread between the primary market and the theoretically estimated value.     

An Empirical Comparison of Forward-Rate and Spot-Rate Models for Valuing Interest-Rate Options

Our main goal is to investigate the question of which interest-rate options valuation models are better suited to support the management of interest-rate risk. We use the German market to test seven spot-rate and forward-rate models with one and two factors for interest-rate warrants for the period from 1990 to 1993. We identify a one-factor forward-rate model and two spot-rate models with two factors that are not significantly outperformed by any of the other four models. Further rankings are possible if additional criteria are applied.