{"title":"Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach","authors":"Marc Hallin , Carlos Trucíos","doi":"10.1016/j.ecosta.2021.04.006","DOIUrl":"https://doi.org/10.1016/j.ecosta.2021.04.006","url":null,"abstract":"<div><p><span><span>Beyond their importance from the regulatory policy point of view, Value-at-Risk (VaR) and Expected Shortfall (ES) play an important role in risk management, portfolio allocation, capital level requirements, trading systems, and hedging strategies. However, due to the </span>curse of dimensionality<span>, their accurate estimation and forecast in large portfolios is quite a challenge. To tackle this problem, two procedures are proposed. The first one is based on a filtered historical simulation method in which high-dimensional conditional covariance matrices are estimated via a general </span></span>dynamic factor<span> model with infinite-dimensional factor space and conditionally heteroscedastic factors; the other one is based on a residual-based bootstrap scheme. The two procedures are applied to a panel with concentration ratio close to one. Backtesting and scoring results indicate that both VaR and ES are accurately estimated under both methods, which both outperform the existing alternatives.</span></p></div>","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"27 ","pages":"Pages 1-15"},"PeriodicalIF":1.9,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.ecosta.2021.04.006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50178655","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}
{"title":"Empirical Bayes Model Averaging with Influential Observations: Tuning Zellner’s g Prior for Predictive Robustness","authors":"Christopher M. Hans, Mario Peruggia, Junyan Wang","doi":"10.1016/j.ecosta.2021.12.003","DOIUrl":"https://doi.org/10.1016/j.ecosta.2021.12.003","url":null,"abstract":"<div><p><span><span>The behavior of Bayesian model averaging (BMA) for the normal linear regression model in the presence of influential observations that contribute to model misfit is investigated. Remedies to attenuate the potential negative impacts of such observations on inference and prediction are proposed. The methodology is motivated by the view that well-behaved residuals and good </span>predictive performance often go hand-in-hand. Focus is placed on regression models that use variants on Zellner's </span><span><math><mi>g</mi></math></span> prior. Studying the impact of various forms of model misfit on BMA predictions in simple situations points to prescriptive guidelines for “tuning” Zellner's <span><math><mi>g</mi></math></span> prior to obtain optimal predictions. The tuning of the prior distribution is obtained by considering theoretical properties that should be enjoyed by the optimal fits of the various models in the BMA ensemble. The methodology can be thought of as an “empirical Bayes” approach to modeling, as the data help to inform the specification of the prior in an attempt to attenuate the negative impact of influential cases.</p></div>","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"27 ","pages":"Pages 102-119"},"PeriodicalIF":1.9,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50178662","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}
Antonio Canale , Antonio Lijoi , Bernardo Nipoti , Igor Prünster
{"title":"Inner spike and slab Bayesian nonparametric models","authors":"Antonio Canale , Antonio Lijoi , Bernardo Nipoti , Igor Prünster","doi":"10.1016/j.ecosta.2021.10.017","DOIUrl":"https://doi.org/10.1016/j.ecosta.2021.10.017","url":null,"abstract":"<div><p><span><span>Discrete Bayesian<span> nonparametric models whose expectation is a convex </span></span>linear combination of a point mass at some point of the support and a diffuse probability distribution allow to incorporate strong prior information, while still being extremely flexible. Recent contributions in the statistical literature have successfully implemented such a modelling strategy in a variety of applications, including density estimation, nonparametric regression and model-based clustering. A thorough study is presented on a large class of nonparametric models, named </span><span><em>inner spike and slab </em><em>hNRMI</em><em> models</em></span><span><span> and obtained by considering homogeneous normalized random measures with independent increments (hNRMI) with base measure given by a convex linear combination of a point mass and a diffuse probability distribution. In turn, the distributional properties of these models are investigated, with focus on: i) the exchangeable partition probability function they induce, ii) the distribution of the number of distinct values in an exchangeable sample, iii) the </span>posterior predictive distribution, and iv) the distribution of the number of elements that coincide with the only point of the support with positive probability. These theoretical findings represent the main building block for an actual implementation of Bayesian inner spike and slab hNRMI models by means of a generalized Pólya urn scheme.</span></p></div>","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"27 ","pages":"Pages 120-135"},"PeriodicalIF":1.9,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50178661","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}
{"title":"Fluctuation-type monitoring test for explosive behavior","authors":"Eiji Kurozumi","doi":"10.1016/j.ecosta.2023.06.007","DOIUrl":"https://doi.org/10.1016/j.ecosta.2023.06.007","url":null,"abstract":"","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"70 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83908081","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}
{"title":"Mean group instrumental variable estimation of time-varying large heterogeneous panels with endogenous regressors","authors":"Yu Bai, Massimiliano Marcellino, G. Kapetanios","doi":"10.1016/j.ecosta.2023.06.004","DOIUrl":"https://doi.org/10.1016/j.ecosta.2023.06.004","url":null,"abstract":"","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"8 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85391343","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}
{"title":"On the distribution-freeness of a test of angular symmetry based on halfspace depth","authors":"A. Dürre, D. Paindaveine","doi":"10.1016/j.ecosta.2023.06.003","DOIUrl":"https://doi.org/10.1016/j.ecosta.2023.06.003","url":null,"abstract":"","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"36 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73684408","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}
{"title":"Normality testing after outlier removal","authors":"Vanessa Berenguer-Rico, Bent Nielsen","doi":"10.1016/j.ecosta.2023.06.001","DOIUrl":"https://doi.org/10.1016/j.ecosta.2023.06.001","url":null,"abstract":"","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"26 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75616568","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}
{"title":"Robust logistic regression for ordered and unordered responses","authors":"M. Iannario, Anna Clara Monti","doi":"10.1016/j.ecosta.2023.05.004","DOIUrl":"https://doi.org/10.1016/j.ecosta.2023.05.004","url":null,"abstract":"","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"17 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89371091","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}
{"title":"Robust Fixed-b Inference in the Presence of Time-Varying Volatility","authors":"M. Demetrescu, C. Hanck, Robinson Kruse-Becher","doi":"10.1016/j.ecosta.2023.05.003","DOIUrl":"https://doi.org/10.1016/j.ecosta.2023.05.003","url":null,"abstract":"","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"15 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88515536","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}