Econometrics: Applied Econometric Modeling in Financial Economics eJournal最新文献_第8页

Term Structure Modeling with Structural Breaks: A Simple Arbitrage-Free Approach 具有结构断裂的期限结构建模:一种简单的无套利方法

Econometrics: Applied Econometric Modeling in Financial Economics eJournal Pub Date : 2011-12-17 DOI: 10.2139/ssrn.1974033

Wachi Bandara, Richard Munclinger

{"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}

引用次数: 2

An Estimated DSGE Model: Explaining Variation in Term Premia 一个估计的DSGE模型:解释定期保费的变化

Econometrics: Applied Econometric Modeling in Financial Economics eJournal Pub Date : 2011-12-14 DOI: 10.2139/ssrn.1972911

Martin M. Andreasen

引用次数: 2

A Transformation-Based Nonparametric Estimator of Multivariate Densities with an Application to Global Financial Markets 基于变换的多元密度非参数估计及其在全球金融市场中的应用

Econometrics: Applied Econometric Modeling in Financial Economics eJournal Pub Date : 2011-12-07 DOI: 10.2139/ssrn.1969208

Meng-Shiuh Chang, Ximing Wu

{"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}

引用次数: 0

Macroeconomic News Effects on the Stock Markets 宏观经济新闻对股市的影响

Econometrics: Applied Econometric Modeling in Financial Economics eJournal Pub Date : 2011-12-01 DOI: 10.2139/ssrn.2019995

Barbara Będowska-Sójka

引用次数: 0

A Quantile Analysis of Default Risk for Speculative and Emerging Companies 投机和新兴公司违约风险的分位数分析

Econometrics: Applied Econometric Modeling in Financial Economics eJournal Pub Date : 2011-12-01 DOI: 10.2139/ssrn.1967310

R. Powell, D. Allen, A. Kramadibrata, Abhay K. Singh

{"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}

引用次数: 3

Multistate Asymmetric ACD Model: An Application to Order Dynamics in the EUR/PLN Spot Market 多态非对称ACD模型:在欧元/PLN现货市场订单动力学中的应用

Econometrics: Applied Econometric Modeling in Financial Economics eJournal Pub Date : 2011-12-01 DOI: 10.2139/ssrn.1986778

K. Bień-Barkowska

引用次数: 0

Asymptotic Expansions of the Lognormal Implied Volatility: A Model Free Approach 对数正态隐含波动率的渐近展开式:无模型方法

Econometrics: Applied Econometric Modeling in Financial Economics eJournal Pub Date : 2011-11-29 DOI: 10.2139/ssrn.1965977

C. Grunspan

引用次数: 10

Comparing Australian and US Corporate Default Risk Using Quantile Regression 用分位数回归比较澳大利亚和美国企业违约风险

Econometrics: Applied Econometric Modeling in Financial Economics eJournal Pub Date : 2011-11-27 DOI: 10.2139/ssrn.1965284

D. Allen, A. Kramadibrata, R. Powell, Abhay K. Singh

{"title":"Comparing Australian and US Corporate Default Risk Using Quantile Regression","authors":"D. Allen, A. Kramadibrata, R. Powell, Abhay K. Singh","doi":"10.2139/ssrn.1965284","DOIUrl":"https://doi.org/10.2139/ssrn.1965284","url":null,"abstract":"The severe bank stresses of the Global Financial Crisis (GFC) have underlined the importance of understanding and measuring extreme credit risk. The Australian economy is widely considered to have fared much better than the US and most other major world economies. This paper applies quantile regression and Monte Carlo simulation to the Merton structural credit model to investigate the impact of extreme asset value fluctuations on default probabilities of Australian companies in comparison to the USA. Quantile regression allows modelling of the extreme quantiles of a distribution which allows measurement of capital and PDs at the most extreme points of an economic downturn, when companies are most likely to fail. Daily asset value fluctuations of over 600 Australian and US investment and speculative entities are examined over a ten year period spanning pre-GFC and GFC. The events of the GFC also showed how the capital of global banks was eroded as defaults increased. This paper therefore also examines the impact of these fluctuating default probabilities on the capital adequacy of Australian and US banks. The paper finds highly significant variances in default probabilities and capital between quantiles in both Australia and the US, and shows how these variances can assist banks and regulators in calculating capital buffers to sustain banks through volatile times.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130387747","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}

引用次数: 6

Evidence on Changes in Time Varying Volatility Around Bonus and Rights Issue Announcements 关于奖金和配股公告时变波动率变化的证据

Econometrics: Applied Econometric Modeling in Financial Economics eJournal Pub Date : 2011-11-20 DOI: 10.1108/17468801311307000

Madhuri Malhotra, M. Thenmozhi, G. ArunKumar

引用次数: 8

Are Capital Markets Inefficient on a Macro Level? 资本市场在宏观层面上是低效的吗?

Econometrics: Applied Econometric Modeling in Financial Economics eJournal Pub Date : 2011-11-15 DOI: 10.2139/ssrn.1959798

Jan Bernhard, Michael Verhofen

{"title":"Are Capital Markets Inefficient on a Macro Level?","authors":"Jan Bernhard, Michael Verhofen","doi":"10.2139/ssrn.1959798","DOIUrl":"https://doi.org/10.2139/ssrn.1959798","url":null,"abstract":"Samuelson’s dictum (1998) states that capital markets are “macro inefficient”. If this conjecture is true, returns should be partially predictable across different asset classes. We test for the predictability of returns on an asset class level by exploiting the advantageous features of the parametric portfolio policy approach proposed by Brandt, Santa-Clara and Valkanov (2009). We apply the parametric portfolio policy framework in a multi asset investment universe and perform a number of robustness checks such as varying the degree of risk aversion, conducting out-of-sample analyses and including transaction costs. Our results demonstrate that the parametric portfolio policy approach generates positive excess returns after costs in an out-of-sample setting by parameterizing the asset weights as a function of the assets’ value and momentum characteristics. The optimal strategy is a combination of value and momentum investing and depends on the risk aversion of investors. Risk-averse investors benefit from focusing on value investing, while our results advise risk-seeking investors to favor momentum investing. Overall, our analysis indicates that capital markets are inefficient on a macro level.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"596 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121977873","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}

引用次数: 1