{"title":"Covariance estimation and quasi-likelihood analysis","authors":"Yuta Koike, N. Yoshida","doi":"10.4324/9781315162737-13","DOIUrl":"https://doi.org/10.4324/9781315162737-13","url":null,"abstract":"","PeriodicalId":380412,"journal":{"name":"Financial Mathematics, Volatility and Covariance Modelling","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121160183","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":"Long memory and asymmetry in commodity returns and risk","authors":"S. Cochran, I. Mansur, B. Odusami","doi":"10.4324/9781315162737-2","DOIUrl":"https://doi.org/10.4324/9781315162737-2","url":null,"abstract":"","PeriodicalId":380412,"journal":{"name":"Financial Mathematics, Volatility and Covariance Modelling","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131555538","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":"Do high-frequency-based measures improve conditional covariance forecasts?","authors":"Denisa Banulescu-Radu, E. Dumitrescu","doi":"10.4324/9781315162737-11","DOIUrl":"https://doi.org/10.4324/9781315162737-11","url":null,"abstract":"In this paper we investigate the possible benefits from using ex-post highfrequency based (realized) measures of volatility and correlation in conditional covariance forecasting. For this, we combine the (Robust) Realized GARCH framework with time varying conditional copulas and compare their forecasting abilities with those of multivariate Realized GARCH models and wellestablished competing models from the literature, i.e. the GJR-GARCH copula and the corrected DCC. The one-step-ahead forecasting abilities of the models are assessed in an empirical illustration on three pairs of financial assets by relying on the Model Confidence Set test. Our findings indicate that the proposed specifications relying on realized measures significantly improve the quality of covariance matrix forecasts. JEL Codes: C32, C53, C58","PeriodicalId":380412,"journal":{"name":"Financial Mathematics, Volatility and Covariance Modelling","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116302063","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":"The log-GARCH model via ARMA representations","authors":"Genaro Sucarrat","doi":"10.4324/9781315162737-14","DOIUrl":"https://doi.org/10.4324/9781315162737-14","url":null,"abstract":"The log-GARCH model provides a flexible framework for the modelling of economic uncertainty, financial volatility and other positively valued variables. Its exponential specification ensures fitted volatilities are positive, allows for flexible dynamics, simplifies inference when parameters are equal to zero under the null, and the logtransform makes the model robust to jumps or outliers. An additional advantage is that the model admits ARMA-like representations. This means log-GARCH models can readily be estimated by means of widely available software, and enables a vast range of well-known time-series results and methods. This chapter provides an overview of the log-GARCH model and its ARMA representation(s), and of how estimation can be implemented in practice. After the introduction, we delineate the univariate log-GARCH model with volatility asymmetry (“leverage”), and show how its (nonlinear) ARMA representation is obtained. Next, stationary covariates (“X”) are added, before a first-order specification with asymmetry is illustrated empirically. Then we turn our attention to multivariate log-GARCH-X models. We start by presenting the multivariate specification in its general form, but quickly turn our focus to specifications that can be estimated equation-by-equation – even in the presence of Dynamic Conditional Correlations (DCCs) of unknown form. Next, a multivariate non-stationary log-GARCH-X model is formulated, in which the X-covariates can be both stationary and/or nonstationary. A common critique directed towards the log-GARCH model is that its ARCH terms may not exist in the presence of inliers. An own Section is devoted to how this can be handled in practice. Next, the generalisation of log-GARCH models to logarithmic Multiplicative Error Models (MEMs) is made explicit. Finally, the chapter concludes. JEL Classification: C22, C32, C51, C58","PeriodicalId":380412,"journal":{"name":"Financial Mathematics, Volatility and Covariance Modelling","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131106306","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}
M. Karanasos, Panagiotis Koutroumpis, Zannis Margaronis, Rajat Nath
{"title":"The importance of rollover in commodity returns using PARCH models","authors":"M. Karanasos, Panagiotis Koutroumpis, Zannis Margaronis, Rajat Nath","doi":"10.4324/9781315162737-4","DOIUrl":"https://doi.org/10.4324/9781315162737-4","url":null,"abstract":"","PeriodicalId":380412,"journal":{"name":"Financial Mathematics, Volatility and Covariance Modelling","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131760519","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}
Cristina Amado, Annastiina Silvennoinen, T. Teräsvirta
{"title":"Models with multiplicative decomposition of conditional variances and correlations","authors":"Cristina Amado, Annastiina Silvennoinen, T. Teräsvirta","doi":"10.4324/9781315162737-10","DOIUrl":"https://doi.org/10.4324/9781315162737-10","url":null,"abstract":"Univariate and multivariate GARCH type models with multiplicative decomposition of the variance to short and long run components are surveyed. The latter component can be either deterministic or stochastic. Examples of both types are studied.","PeriodicalId":380412,"journal":{"name":"Financial Mathematics, Volatility and Covariance Modelling","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116286672","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 spot-futures no-arbitrage relations in commodity markets*","authors":"R. Aid, L. Campi, D. Lautier","doi":"10.4324/9781315162737-8","DOIUrl":"https://doi.org/10.4324/9781315162737-8","url":null,"abstract":"In commodity markets the convergence of futures towards spot prices, at the expiration of the contract, is usually justified by no-arbitrage arguments. In this article, we propose an alternative approach that relies on the expected profit maximization problem of an agent, producing and storing a commodity while trading in the associated futures contracts. In this framework, the relation between the spot and the futures prices holds through the well-posedness of the maximization problem. We show that the futures price can still be seen as the risk-neutral expectation of the spot price at maturity and we propose an explicit formula for the forward volatility. Moreover, we provide an heuristic analysis of the optimal solution for the production/storage/trading problem, in a Markovian setting. This approach is particularly interesting in the case of energy commodities, like electricity: this framework indeed remains suitable for commodities characterized by storability constraints, when standard no-arbitrage arguments cannot be safely applied.","PeriodicalId":380412,"journal":{"name":"Financial Mathematics, Volatility and Covariance Modelling","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132456250","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}