Statistics & Risk Modeling最新文献_第6页

Series expansions for convolutions of Pareto distributions 帕累托分布卷积的级数展开

IF 1.5

Statistics & Risk Modeling Pub Date : 2015-04-01 DOI: 10.1515/strm-2014-1168

Q. Nguyen, C. Robert

引用次数: 3

Leveraging the network: A stress-test framework based on DebtRank 利用网络:基于DebtRank的压力测试框架

IF 1.5

Statistics & Risk Modeling Pub Date : 2015-03-02 DOI: 10.1515/strm-2015-0005

S. Battiston, G. Caldarelli, M. d’Errico, S. Gurciullo

{"title":"Leveraging the network: A stress-test framework based on DebtRank","authors":"S. Battiston, G. Caldarelli, M. d’Errico, S. Gurciullo","doi":"10.1515/strm-2015-0005","DOIUrl":"https://doi.org/10.1515/strm-2015-0005","url":null,"abstract":"Abstract We develop a novel stress-test framework to monitor systemic risk in financial systems. The modular structure of the framework allows to accommodate for a variety of shock scenarios, methods to estimate interbank exposures and mechanisms of distress propagation. The main features are as follows. First, the framework allows to estimate and disentangle not only first-round effects (i.e. shock on external assets) and second-round effects (i.e. distress induced in the interbank network), but also third-round effects induced by possible fire sales. Second, it allows to monitor at the same time the impact of shocks on individual or groups of financial institutions as well as their vulnerability to shocks on counterparties or certain asset classes. Third, it includes estimates for loss distributions, thus combining network effects with familiar risk measures such as VaR and CVaR. Fourth, in order to perform robustness analyses and cope with incomplete data, the framework features a module for the generation of sets of networks of interbank exposures that are coherent with the total lending and borrowing of each bank. As an illustration, we carry out a stress-test exercise on a dataset of listed European banks over the years 2008–2013. We find that second-round and third-round effects dominate first-round effects, therefore suggesting that most current stress-test frameworks might lead to a severe underestimation of systemic risk.","PeriodicalId":44159,"journal":{"name":"Statistics & Risk Modeling","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/strm-2015-0005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67313495","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: 96

Change detection in the Cox–Ingersoll–Ross model Cox-Ingersoll-Ross模型中的变化检测

IF 1.5

Statistics & Risk Modeling Pub Date : 2015-02-25 DOI: 10.1515/strm-2015-0008

G. Pap, Tamás T. Szabó

引用次数: 2

Analyzing model robustness via a distortion of the stochastic root: A Dirichlet prior approach 利用随机根的失真分析模型的稳健性:狄利克雷先验方法

IF 1.5

Statistics & Risk Modeling Pub Date : 2015-01-01 DOI: 10.1515/strm-2015-0009

Jan-Frederik Mai, Steffen Schenk, M. Scherer

{"title":"Analyzing model robustness via a distortion of the stochastic root: A Dirichlet prior approach","authors":"Jan-Frederik Mai, Steffen Schenk, M. Scherer","doi":"10.1515/strm-2015-0009","DOIUrl":"https://doi.org/10.1515/strm-2015-0009","url":null,"abstract":"Abstract It is standard in quantitative risk management to model a random vector 𝐗:={X t k } k=1,...,d ${mathbf {X}:=lbrace X_{t_k}rbrace _{k=1,ldots ,d}}$ of consecutive log-returns to ultimately analyze the probability law of the accumulated return X t 1 +⋯+X t d ${X_{t_1}+cdots +X_{t_d}}$ . By the Markov regression representation (see [25]), any stochastic model for 𝐗${mathbf {X}}$ can be represented as X t k =f k (X t 1 ,...,X t k-1 ,U k )${X_{t_k}=f_k(X_{t_1},ldots ,X_{t_{k-1}},U_k)}$ , k=1,...,d${k=1,ldots ,d}$ , yielding a decomposition into a vector 𝐔:={U k } k=1,...,d ${mathbf {U}:=lbrace U_{k}rbrace _{k=1,ldots ,d}}$ of i.i.d. random variables accounting for the randomness in the model, and a function f:={f k } k=1,...,d ${f:=lbrace f_krbrace _{k=1,ldots ,d}}$ representing the economic reasoning behind. For most models, f is known explicitly and Uk may be interpreted as an exogenous risk factor affecting the return Xtk in time step k. While existing literature addresses model uncertainty by manipulating the function f, we introduce a new philosophy by distorting the source of randomness 𝐔${mathbf {U}}$ and interpret this as an analysis of the model's robustness. We impose consistency conditions for a reasonable distortion and present a suitable probability law and a stochastic representation for 𝐔${mathbf {U}}$ based on a Dirichlet prior. The resulting framework has one parameter c∈[0,∞]${cin [0,infty ]}$ tuning the severity of the imposed distortion. The universal nature of the methodology is illustrated by means of a case study comparing the effect of the distortion to different models for 𝐗${mathbf {X}}$ . As a mathematical byproduct, the consistency conditions of the suggested distortion function reveal interesting insights into the dependence structure between samples from a Dirichlet prior.","PeriodicalId":44159,"journal":{"name":"Statistics & Risk Modeling","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/strm-2015-0009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67313574","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

A copula-based hierarchical hybrid loss distribution 一种基于copula的分层混合损失分布

IF 1.5

Statistics & Risk Modeling Pub Date : 2015-01-01 DOI: 10.1515/strm-2012-1128

E. Bernardi, S. Romagnoli

引用次数: 0

Implied basket correlation dynamics 隐含篮子相关动力学

IF 1.5

Statistics & Risk Modeling Pub Date : 2014-11-20 DOI: 10.1515/strm-2014-1176

W. Härdle, Elena Silyakova

引用次数: 11

Exact and approximate hidden Markov chain filters based on discrete observations 基于离散观测的精确和近似隐马尔可夫链滤波器

IF 1.5

Statistics & Risk Modeling Pub Date : 2014-11-04 DOI: 10.1515/strm-2015-0004

N. Bäuerle, Igor Gilitschenski, U. Hanebeck

引用次数: 1

Verification of internal risk measure estimates 内部风险度量评估的验证

IF 1.5

Statistics & Risk Modeling Pub Date : 2014-10-16 DOI: 10.1515/strm-2015-0007

Mark H. A. Davis

{"title":"Verification of internal risk measure estimates","authors":"Mark H. A. Davis","doi":"10.1515/strm-2015-0007","DOIUrl":"https://doi.org/10.1515/strm-2015-0007","url":null,"abstract":"Abstract This paper concerns sequential computation of risk measures for financial data and asks how, given a risk measurement procedure, we can tell whether the answers it produces are ‘correct’. We draw the distinction between ‘external’ and ‘internal’ risk measures and concentrate on the latter, where we observe data in real time, make predictions and observe outcomes. It is argued that evaluation of such procedures is best addressed from the point of view of probability forecasting or Dawid’s theory of ‘prequential statistics’ [12]. We introduce a concept of ‘calibration’ of a risk measure in a dynamic setting, following the precepts of Dawid’s weak and strong prequential principles, and examine its application to quantile forecasting (VaR – value at risk) and to mean estimation (applicable to CVaR – expected shortfall). The relationship between these ideas and ‘elicitability’ [24] is examined. We show in particular that VaR has special properties not shared by any other risk measure. Turning to CVaR we argue that its main deficiency is the unquantifiable tail dependence of estimators. In a final section we show that a simple data-driven feedback algorithm can produce VaR estimates on financial data that easily pass both the consistency test and a further newly-introduced statistical test for independence of a binary sequence.","PeriodicalId":44159,"journal":{"name":"Statistics & Risk Modeling","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/strm-2015-0007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67313888","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: 41

Prediction of regionalized car insurance risks based on control variates 基于控制变量的区域化车险风险预测

IF 1.5

Statistics & Risk Modeling Pub Date : 2014-06-28 DOI: 10.1515/strm-2013-1148

M. Christiansen, C. Hirsch, V. Schmidt

引用次数: 0

Stochastic orderings with respect to a capacity and an application to a financial optimization problem 容量的随机排序及其在财务优化问题中的应用

IF 1.5

Statistics & Risk Modeling Pub Date : 2014-06-28 DOI: 10.1515/strm-2013-1151

Miryana Grigorova

引用次数: 10