Modelling, Estimation and Visualization of Multivariate Dependence for High-frequency Data
نویسندگان
چکیده
Dependence modelling and estimation is a key issue in the assessment of financial risk. It is common knowledge meanwhile that the multivariate normal model with linear correlation as its natural dependence measure is by no means an ideal model. We suggest a large class of models and a dependence function, which allows us to capture the complete extreme dependence structure of a portfolio. We also present a simple nonparametric estimation procedure of this function. To show our new method at work we apply it to a financial data set of high frequency stock data and estimate the extreme dependence in the data. AMS 2000 Subject Classifications: primary: 62G32, 62H12; secondary: 62E20, 62P05. JEL Classifications: C14, C51.
منابع مشابه
Modelling of Correlated Ordinal Responses, by Using Multivariate Skew Probit with Different Types of Variance Covariance Structures
In this paper, a multivariate fundamental skew probit (MFSP) model is used to model correlated ordinal responses which are constructed from the multivariate fundamental skew normal (MFSN) distribution originate to the greater flexibility of MFSN. To achieve an appropriate VC structure for reaching reliable statistical inferences, many types of variance covariance (VC) structures are considered ...
متن کاملRisk Management in Oil Market: A Comparison between Multivariate GARCH Models and Copula-based Models
H igh price volatility and the risk are the main features of commodity markets. One way to reduce this risk is to apply the hedging policy by future contracts. In this regard, in this paper, we will calculate the optimal hedging ratios for OPEC oil. In this study, besides the multivariate GARCH models, for the first time we use conditional copula models for modelling dependence struc...
متن کاملA Copula-based Quantile Model for Crude oil Return-Volatility Dependence Modelling: Case of Iran Heavy Oil
The main purpose of this study is to investigate the relationship between Iran’s heavy crude oil price returns and volatility dependence using the Copula-based quantile model (CQM). CQM is an efficient tool for analyzing nonlinear time series models as it has no need for initial assumptions. We use monthly data from January 1990 to December 2019. We use the Hadrick-Prescott filter to calculate...
متن کاملIntegrative multivariate distribution models with generalized hyperbolic margins
Multivariate generalized hyperbolic distributions represent an attractive family of distributions (with exponentially decreasing tails) for multivariate data modelling. However, in a limited data environment, robust and fast estimation procedures are rare. In this paper we propose an alternative class of multivariate distributions (with exponentially decreasing tails) belonging to affine-linear...
متن کاملA New High Frequency Grid Impedance Estimation Technique for the Frequency Range of 2 to150 kHz
Grid impedance estimation is used in many power system applications such as grid connected renewable energy systems and power quality analysis of smart grids. The grid impedance estimation techniques based on signal injection uses Ohm’s law for the estimation. In these methods, one or several signal(s) is (are) injected to Point of Common Coupling (PCC). Then the current through and voltage of ...
متن کامل