Author: Robert O'NeillPublisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Essays on Forecasting the Multivariate Variance-covariance Matrix
Author: Robert O'NeillEssays on Forecasting the Multivariate Variance-covariance Matrix
Author: Robert O'NeillVolatility and Time Series Econometrics:Essays in Honor of Robert Engle
Author: Tim BollerslevPublisher: OUP Oxford
ISBN: 0199549494
Category : Business & Economics
Languages : en
Pages : 432
Book Description
Robert Engle received the Nobel Prize for Economics in 2003 for his work in time series econometrics. This book contains 16 original research contributions by some the leading academic researchers in the fields of time series econometrics, forecasting, volatility modelling, financial econometrics and urban economics, along with historical perspectives related to field of time series econometrics more generally.Engle's Nobel Prize citation focuses on his path-breaking work on autoregressive conditional heteroskedasticity (ARCH) and the profound effect that this work has had on the field of financial econometrics. Several of the chapters focus on conditional heteroskedasticity, and develop the ideas of Engle's Nobel Prize winning work. Engle's work has had its most profound effect on the modelling of financial variables and several of the chapters use newly developed time series methods to study thebehavior of financial variables. Each of the 16 chapters may be read in isolation, but they all importantly build on and relate to the seminal work by Nobel Laureate Robert F. Engle.
Multivariate Analysis--III
Author: Paruchuri R. KrishnaiahPublisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 438
Book Description
Time series and stochastic processes; Distribution theory and inference; Characteristic functions and characterizations; Design and analysis of experiments; Classification, modelling, and reliability.
A Test of Covariance Matrix Forecasting Methods
Author: Valeriy ZakamulinPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Providing a more accurate covariance matrix forecast can substantially improve the performance of optimized portfolios. Using out-of-sample tests, in this paper, we evaluate alternative covariance matrix forecasting methods by looking at (1) their forecast accuracy, (2) their ability to track the volatility of the minimum-variance portfolio, and (3) their ability to keep the volatility of the minimum-variance portfolio at a target level. We find large differences between the methods. Our results suggest that shrinkage of the sample covariance matrix improves neither the forecast accuracy nor the performance of minimum-variance portfolios. In contrast, switching from the sample covariance matrix forecast to a multivariate GARCH forecast reduces forecasting error and portfolio tracking error by at least half. Our findings also reveal that the exponentially weighted covariance matrix forecast performs only slightly worse than the multivariate GARCH forecast.
A General Model for Multivariate Analysis
Author: Jeremy D. FinnPublisher: Holt McDougal
ISBN:
Category : Mathematics
Languages : en
Pages : 616
Book Description
Step-down Procedure in Multivariate Analysis
Author: J. RoyPublisher:
ISBN:
Category : Analysis of variance
Languages : en
Pages : 40
Book Description
Analyzing Multivariate Data
Author: Norman CliffPublisher:
ISBN:
Category : Multivariate analysis
Languages : en
Pages : 536
Book Description
Forecasting the Variance
Author: Moritz HeidenThe Foundations of Multivariate Analysis
Author: Kei TakeuchiPublisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 478
Book Description
Essentials of linear algebra; Fundamental concepts of multivariate analysis; Regression analysis; Analyses of variance and covariance; Principal component analysis; Canonical correlation analysis and discriminant analysis; Factor analysis; Analysis of categorical data; Theory of distance and its application to classification problems; Analysis of covariance structures.