In The Ascent of Money (2008), the Harvard financial historian Niall Ferguson refers to the Black-Scholes option pricing model 'as a black box' which is beyond comprehension of anyone except the mathematically astute and leaves most investors baffled. In this paper, we develop a heuristic proof of Black-Scholes as an aid to learning, discovery and problem solving. From a deterministic model, the basic structure of Black-Scholes is identified. Thereafter, the generalized form of Black-Scholes is deduced and various underlying components examined with particular emphasis on a conceptual understanding of the symbols N(d1) and N(d2). The methodology relies heavily on intuition and transparency with the more rigorous mathematics relegated to the appendices.
在《货币的崛起》(The Ascent of Money, 2008)一书中，哈佛大学金融历史学家尼尔•弗格森(Niall Ferguson)将布莱克-斯科尔斯期权定价模型称为“一个黑盒子”，除了数学头脑敏锐的人之外，任何人都无法理解它，它让大多数投资者感到困惑。在本文中，我们发展了一种启发式的布莱克-斯科尔斯证明，作为学习、发现和解决问题的辅助。从确定性模型出发，确定了Black-Scholes的基本结构。随后，推导了Black-Scholes的广义形式，并着重对符号N(d1)和N(d2)进行了概念性理解，考察了各种潜在成分。该方法在很大程度上依赖于直觉和透明度，而更严格的数学则被归入附录。
{"title":"Removing the 'Black Box' from the Black-Scholes Option Pricing Model","authors":"E. Maberly, Raylene M. Pierce","doi":"10.2139/ssrn.1978649","DOIUrl":"https://doi.org/10.2139/ssrn.1978649","url":null,"abstract":"In The Ascent of Money (2008), the Harvard financial historian Niall Ferguson refers to the Black-Scholes option pricing model 'as a black box' which is beyond comprehension of anyone except the mathematically astute and leaves most investors baffled. In this paper, we develop a heuristic proof of Black-Scholes as an aid to learning, discovery and problem solving. From a deterministic model, the basic structure of Black-Scholes is identified. Thereafter, the generalized form of Black-Scholes is deduced and various underlying components examined with particular emphasis on a conceptual understanding of the symbols N(d1) and N(d2). The methodology relies heavily on intuition and transparency with the more rigorous mathematics relegated to the appendices.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125904071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Benchmark models for the term structure and dynamic of the interest rate, having the instantaneous rate as the only state variable, were introduced by Vasicek (V) and Cox-Ingersoll-Ross (CIR). Then the measure of a zero-coupon bond price change with respect to any change of the short-term interest rate movement is made by a sensitivity parameter referred as a stochastic duration. Therefore this last notion is theoretically superior to the Macaulay's duration under which the yield-curve is assumed to have made a parallel shift. However, empirical tests on bond immunization performance have not demonstrated any actual superiority of the stochastic duration when compared to the simple classical duration. Consequently in the present paper, we introduce alternative zero-coupon sensitivities with respect to the one-factor shock related to the considered V/CIR model. They lead to a high accuracy level for the approximation of the bond change with respect to the short-term interest rate movement. Our finding allows to get pointwise estimates of a bond hedging error. This is economically more sounding than the standard variance approach. Moreover our result has an implication on stress-testing framework. Indeed we get explicit expressions which enable us to map a view on shocks onto a view on the future bond change. The approach, we introduce here, is suitable for the perspective of hedging or managing a global portfolio or hybrid products.
{"title":"Interest Rate Sensitivities Under the Vasicek and Cox-Ingersoll-Ross Models","authors":"Y. Rakotondratsimba","doi":"10.2139/ssrn.1977902","DOIUrl":"https://doi.org/10.2139/ssrn.1977902","url":null,"abstract":"Benchmark models for the term structure and dynamic of the interest rate, having the instantaneous rate as the only state variable, were introduced by Vasicek (V) and Cox-Ingersoll-Ross (CIR). Then the measure of a zero-coupon bond price change with respect to any change of the short-term interest rate movement is made by a sensitivity parameter referred as a stochastic duration. Therefore this last notion is theoretically superior to the Macaulay's duration under which the yield-curve is assumed to have made a parallel shift. However, empirical tests on bond immunization performance have not demonstrated any actual superiority of the stochastic duration when compared to the simple classical duration. Consequently in the present paper, we introduce alternative zero-coupon sensitivities with respect to the one-factor shock related to the considered V/CIR model. They lead to a high accuracy level for the approximation of the bond change with respect to the short-term interest rate movement. Our finding allows to get pointwise estimates of a bond hedging error. This is economically more sounding than the standard variance approach. Moreover our result has an implication on stress-testing framework. Indeed we get explicit expressions which enable us to map a view on shocks onto a view on the future bond change. The approach, we introduce here, is suitable for the perspective of hedging or managing a global portfolio or hybrid products.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123785711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we investigate the efficiency of the day-ahead market for electricity at the EPEX, the largest central European market for electricity. To analyze whether generating companies use their market power to influence prices, we used a conjectural variations approach for the years 2007-2010 on a yearly basis as well as a direct approach for estimating marginal costs for the year 2010. The results of both approaches show no indication for systematic abuse of market power by the suppliers of electricity on the EPEX day-ahead spot market for the analyzed period of time. Conducting the same analysis for high load hours, which are generally considered to be the most prone to market manipulation, yielded similar results suggesting that the results are robust. For our analysis, we considered hourly price and demand data and consequently obtained a high level of statistical significance in our models.
{"title":"On the Efficiency of the EPEX Day-Ahead Spot Market","authors":"D. Wozabal, C. Graf","doi":"10.2139/ssrn.1973554","DOIUrl":"https://doi.org/10.2139/ssrn.1973554","url":null,"abstract":"In this paper we investigate the efficiency of the day-ahead market for electricity at the EPEX, the largest central European market for electricity. To analyze whether generating companies use their market power to influence prices, we used a conjectural variations approach for the years 2007-2010 on a yearly basis as well as a direct approach for estimating marginal costs for the year 2010. The results of both approaches show no indication for systematic abuse of market power by the suppliers of electricity on the EPEX day-ahead spot market for the analyzed period of time. Conducting the same analysis for high load hours, which are generally considered to be the most prone to market manipulation, yielded similar results suggesting that the results are robust. For our analysis, we considered hourly price and demand data and consequently obtained a high level of statistical significance in our models.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124619570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Economic time-series are susceptible to infrequent but severe structural breaks that stem from banking crises, changes in government policy or shifts in consumer con fidence. We present an affine, arbitrage-free, regime-switching dynamic Nelson-Siegel model of the term structure that identifies structural breaks. We develop the model in continuous time and present a class of general affine hidden Markov models of the term structure. We highlight the assumptions that are necessary to reach tractable versions in this class such as the Dai, Singleton and Yang (2007) model and the arbitrage-free regime-switching Nelson and Siegel model. We estimate an arbitrage-free hidden Markov Nelson Siegel model on historical yield curve data via a multi-regime approximate Kalman filter. We contrast the model to single-regime alternatives and conclude that our model performs better in-sample. Using likelihood ratio tests, we show that regimes are driven by long term means, mean reversions, measurement and transition covariance matrices. The regimes conform to periods of expansionary and restrictive monetary policy, but do not coincide exactly with recessions. Our regimes capture the NBER recession dates, but persist long after the recessions have ended.
{"title":"Term Structure Modeling with Structural Breaks: A Simple Arbitrage-Free Approach","authors":"Wachi Bandara, Richard Munclinger","doi":"10.2139/ssrn.1974033","DOIUrl":"https://doi.org/10.2139/ssrn.1974033","url":null,"abstract":"Economic time-series are susceptible to infrequent but severe structural breaks that stem from banking crises, changes in government policy or shifts in consumer con fidence. We present an affine, arbitrage-free, regime-switching dynamic Nelson-Siegel model of the term structure that identifies structural breaks. We develop the model in continuous time and present a class of general affine hidden Markov models of the term structure. We highlight the assumptions that are necessary to reach tractable versions in this class such as the Dai, Singleton and Yang (2007) model and the arbitrage-free regime-switching Nelson and Siegel model. We estimate an arbitrage-free hidden Markov Nelson Siegel model on historical yield curve data via a multi-regime approximate Kalman filter. We contrast the model to single-regime alternatives and conclude that our model performs better in-sample. Using likelihood ratio tests, we show that regimes are driven by long term means, mean reversions, measurement and transition covariance matrices. The regimes conform to periods of expansionary and restrictive monetary policy, but do not coincide exactly with recessions. Our regimes capture the NBER recession dates, but persist long after the recessions have ended.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125661305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we study the implications for hedging Bermudan swaptions of the choice of the instantaneous volatility for the driving Markov process of the one-dimensional swap Markov-functional model. We find that there is a strong evidence in favor of what we term "parametrization by time" as opposed to "parametrization by expiry". We further propose a new parametrization by time for the driving process which takes as inputs into the model the market correlations of relevant swap rates. We show that the new driving process enables a very effective vega-delta hedge with a much more stable gamma profile for the hedging portfolio compared with the existing ones.
{"title":"Implications for Hedging of the Choice of Driving Process for One-Factor Markov-Functional Models","authors":"J. Kennedy, Duy Pham","doi":"10.2139/ssrn.1972932","DOIUrl":"https://doi.org/10.2139/ssrn.1972932","url":null,"abstract":"In this paper, we study the implications for hedging Bermudan swaptions of the choice of the instantaneous volatility for the driving Markov process of the one-dimensional swap Markov-functional model. We find that there is a strong evidence in favor of what we term \"parametrization by time\" as opposed to \"parametrization by expiry\". We further propose a new parametrization by time for the driving process which takes as inputs into the model the market correlations of relevant swap rates. We show that the new driving process enables a very effective vega-delta hedge with a much more stable gamma profile for the hedging portfolio compared with the existing ones.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132143911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper introduces a multivariate pure-jump Levy process which allows for skewness and excess kurtosis of single asset returns and for asymptotic tail dependence in the multivariate setting. It is termed Variance Compound Gamma (VCG). The novelty of my approach is that, by applying a two-stage stochastic time change to Brownian motions, I derive a hierarchical structure with different properties of inter- and intra-sector dependence. I investigate the properties of the implied static copula families and come to the conclusion that they are ordered with respect to their parameters and that the lower-tail dependence of the intra-sector copula is increasing in the absolute values of skewness parameters. Furthermore, I show that the joint characteristic function of the VCG asset returns can be explicitly given as a nested Archimedean copula of their marginal characteristic functions. Applied to credit portfolio modelling, the framework introduced results in a more conservative tail risk assessment than a Gaussian framework with the same linear correlation structure, as I show in a simulation study. To foster the simulation efficiency, I provide an Importance Sampling algorithm for the VCG portfolio setting.
{"title":"A Hierarchical Model of Tail-Dependent Asset Returns","authors":"Natalia Tente","doi":"10.2139/ssrn.1973040","DOIUrl":"https://doi.org/10.2139/ssrn.1973040","url":null,"abstract":"This paper introduces a multivariate pure-jump Levy process which allows for skewness and excess kurtosis of single asset returns and for asymptotic tail dependence in the multivariate setting. It is termed Variance Compound Gamma (VCG). The novelty of my approach is that, by applying a two-stage stochastic time change to Brownian motions, I derive a hierarchical structure with different properties of inter- and intra-sector dependence. I investigate the properties of the implied static copula families and come to the conclusion that they are ordered with respect to their parameters and that the lower-tail dependence of the intra-sector copula is increasing in the absolute values of skewness parameters. Furthermore, I show that the joint characteristic function of the VCG asset returns can be explicitly given as a nested Archimedean copula of their marginal characteristic functions. Applied to credit portfolio modelling, the framework introduced results in a more conservative tail risk assessment than a Gaussian framework with the same linear correlation structure, as I show in a simulation study. To foster the simulation efficiency, I provide an Importance Sampling algorithm for the VCG portfolio setting.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124441426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper develops a DSGE model which explains variation in the nominal and real term structure along with inflation surveys and four macro variables in the UK economy. The model is estimated based on a third-order approximation to allow for time-varying term premia. We find a fall in nominal term premia during the 1990s which mainly is due to lower inflation risk premia. A structural decomposition further shows that this fall is driven by negative preference shocks, lower fixed production costs, and positive investment shocks.
{"title":"An Estimated DSGE Model: Explaining Variation in Term Premia","authors":"Martin M. Andreasen","doi":"10.2139/ssrn.1972911","DOIUrl":"https://doi.org/10.2139/ssrn.1972911","url":null,"abstract":"This paper develops a DSGE model which explains variation in the nominal and real term structure along with inflation surveys and four macro variables in the UK economy. The model is estimated based on a third-order approximation to allow for time-varying term premia. We find a fall in nominal term premia during the 1990s which mainly is due to lower inflation risk premia. A structural decomposition further shows that this fall is driven by negative preference shocks, lower fixed production costs, and positive investment shocks.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128801225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose a probability-integral-transformation-based estimator of multivariate densities. Given a sample of random vectors, we first transform the data into their corresponding marginal distributions. We then estimate the density of the transformed data via the exponential series estimator. The density of the original data is constructed as the product of the density of the transformed data and marginal densities of the original data. This construction coincides with the copula decomposition of multivariate densities. We decompose the Kullback-Leibler Information Criterion (KLIC) between the true and estimated densities into the KLIC of the marginal densities and that between the true copula density and a variant of the estimated copula density. This result is of independent interest in itself, and facilitates our asymptotic analysis. We derive the large sample properties of the proposed estimator, and further propose a hierarchical model specification method guided by stepwise preliminary subset selections. Monte Carlo simulations demonstrate the superior performance of the proposed method. We employ the proposed method to explore the joint distribution of four major stock markets and some conditional distributions of interest. The estimated copula density function, a by-product of our estimation, provides useful insight into the conditional dependence structure between the US and UK markets, and suggests a certain resilience against financial contagions originated from the Asian market.
提出了一种基于概率积分变换的多元密度估计方法。给定一个随机向量样本，我们首先将数据转换为相应的边际分布。然后，我们通过指数级数估计器估计变换后数据的密度。原始数据的密度被构造为转换后数据的密度与原始数据的边缘密度的乘积。这种构造与多元密度的copula分解相一致。我们将真密度和估计密度之间的kullbackleibler信息准则(KLIC)分解为边缘密度的KLIC和真联结密度与估计联结密度的一个变体之间的KLIC。这个结果本身是独立的，有利于我们的渐近分析。我们推导了所提估计量的大样本性质，并进一步提出了一种基于逐步初步子集选择的分层模型规范方法。蒙特卡罗仿真验证了该方法的优越性。我们利用所提出的方法来探讨四大股票市场的联合分布和一些有条件的兴趣分布。估算出的联结密度函数(copula density function)是我们估算的副产品，它为了解美国和英国市场之间的条件依赖结构提供了有用的见解，并表明它们对源自亚洲市场的金融传染具有一定的抵御能力。
{"title":"A Transformation-Based Nonparametric Estimator of Multivariate Densities with an Application to Global Financial Markets","authors":"Meng-Shiuh Chang, Ximing Wu","doi":"10.2139/ssrn.1969208","DOIUrl":"https://doi.org/10.2139/ssrn.1969208","url":null,"abstract":"We propose a probability-integral-transformation-based estimator of multivariate densities. Given a sample of random vectors, we first transform the data into their corresponding marginal distributions. We then estimate the density of the transformed data via the exponential series estimator. The density of the original data is constructed as the product of the density of the transformed data and marginal densities of the original data. This construction coincides with the copula decomposition of multivariate densities. We decompose the Kullback-Leibler Information Criterion (KLIC) between the true and estimated densities into the KLIC of the marginal densities and that between the true copula density and a variant of the estimated copula density. This result is of independent interest in itself, and facilitates our asymptotic analysis. We derive the large sample properties of the proposed estimator, and further propose a hierarchical model specification method guided by stepwise preliminary subset selections. Monte Carlo simulations demonstrate the superior performance of the proposed method. We employ the proposed method to explore the joint distribution of four major stock markets and some conditional distributions of interest. The estimated copula density function, a by-product of our estimation, provides useful insight into the conditional dependence structure between the US and UK markets, and suggests a certain resilience against financial contagions originated from the Asian market.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125708401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The vast of literature concerning the reaction to macroeconomic announcements focus on American releases and their impact on returns and volatility. We are interested if the news from the German and the Polish economy are significant for the stock exchanges in these two countries. Using high-frequency 5-minute returns from 2009-2010 we show that the periodical patterns of the German and the Polish main indices is very similar and their reaction to the macroeconomic announcements too. In both cases the domestic and neighbor-country announcements are much less important comparing to American releases.
{"title":"Macroeconomic News Effects on the Stock Markets","authors":"Barbara Będowska-Sójka","doi":"10.2139/ssrn.2019995","DOIUrl":"https://doi.org/10.2139/ssrn.2019995","url":null,"abstract":"The vast of literature concerning the reaction to macroeconomic announcements focus on American releases and their impact on returns and volatility. We are interested if the news from the German and the Polish economy are significant for the stock exchanges in these two countries. Using high-frequency 5-minute returns from 2009-2010 we show that the periodical patterns of the German and the Polish main indices is very similar and their reaction to the macroeconomic announcements too. In both cases the domestic and neighbor-country announcements are much less important comparing to American releases.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115551309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Powell, D. Allen, A. Kramadibrata, Abhay K. Singh
Using quantile regression, this article examines default risk of emerging and speculative companies in Australia and the United States as compared to established investment entities. We use two datasets for each of the two countries, one speculative and one established. In the US we compare companies from the S&P 500 to those on the Speculative Grade Liquidity Ratings list (Moody's Investor Services, 2010). For Australia, we compare entities from the S&P/ASX 200 to those on the S&P/ASX Emerging Companies Index (EMCOX). We also divide the datasets into GFC and Pre-GFC periods to examine default risk over different economic circumstances. Quantile Regression splits the data into parts or quantiles, thus allowing default risk to be examined at different risk levels. This is especially useful in measuring extreme risk quantiles, when corporate failures are most likely. We apply Monte Carlo simulation to asset returns to calculate Distance to Default using a Merton structural credit model approach. In both countries, the analysis finds substantially higher default risk for speculative as compared to established companies. The spread between speculative company and established company default risk is found to remain constant in Australia through different economic circumstances, but to increase in the US during the GFC as compared to pre-GFC. These findings are important to lenders in understanding, and providing for, default risk for companies of different grades through varying economic cycles.Classification-JEL:
{"title":"A Quantile Analysis of Default Risk for Speculative and Emerging Companies","authors":"R. Powell, D. Allen, A. Kramadibrata, Abhay K. Singh","doi":"10.2139/ssrn.1967310","DOIUrl":"https://doi.org/10.2139/ssrn.1967310","url":null,"abstract":"Using quantile regression, this article examines default risk of emerging and speculative companies in Australia and the United States as compared to established investment entities. We use two datasets for each of the two countries, one speculative and one established. In the US we compare companies from the S&P 500 to those on the Speculative Grade Liquidity Ratings list (Moody's Investor Services, 2010). For Australia, we compare entities from the S&P/ASX 200 to those on the S&P/ASX Emerging Companies Index (EMCOX). We also divide the datasets into GFC and Pre-GFC periods to examine default risk over different economic circumstances. Quantile Regression splits the data into parts or quantiles, thus allowing default risk to be examined at different risk levels. This is especially useful in measuring extreme risk quantiles, when corporate failures are most likely. We apply Monte Carlo simulation to asset returns to calculate Distance to Default using a Merton structural credit model approach. In both countries, the analysis finds substantially higher default risk for speculative as compared to established companies. The spread between speculative company and established company default risk is found to remain constant in Australia through different economic circumstances, but to increase in the US during the GFC as compared to pre-GFC. These findings are important to lenders in understanding, and providing for, default risk for companies of different grades through varying economic cycles.Classification-JEL:","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132904140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：