نتایج جستجو برای: result of diebold

تعداد نتایج: 21169171  

Journal: :Fulbright review of economics and policy 2023

Purpose This study aims to examine the ability of clean energy stocks provide cover for investors against market risks related climate change and disturbances in oil market. Design/methodology/approach The adopts feasible quasi generalized least squares technique estimate a predictive model based on Westerlund Narayan’s (2015) approach evaluating hedging effectiveness stocks. out-of-sample fore...

Journal: : 2021

The aim of the study is to analyze shock and volatility spillover between BIST Finance, Industry, Technology, Tourism, Transportation, Food, Retail-Trade sectors. In this direction, daily data obtained January 5, 2010, December 4, 2020, were analyzed using a new method named TVP-VAR Diebold Yılmaz Spillover Index developed by Antonakakis et al. (2019). Our results indicate that industrial finan...

2002
Jonathan Ohn Larry W. Taylor Adrian Pagan Larry Taylor

We discuss several tests for duration dependence, and establish a few theoretical relationships among the tests that we examine. Some of our test statistics are new to the econometrics literature, and we make an important distinction between the discrete and continuous time frameworks. We then test for duration dependence in business and stock-market cycles, and compare our results for business...

Journal: :Journal of African Studies and Development 2022

This study examines the level of linkage between Nigeria and some selected African countries on one hand linkages economic growth, inflation, unemployment other hand, in these economies. The covers period 2000 2019. aims to first measure distance using approach proposed by Mazurek. Second, degree spillovers was characterized countries, a VAR-based spillover index method Diebold Yilmaz. main fin...

2010
Nicolas CHAPADOS Christian DORION

We provide a formulation of stochastic volatility based on Gaussian processes, a flexible framework for Bayesian nonlinear regression. The advantage of using Gaussian processes in this context is to place volatility forecastingwithin a regression framework; this allows a large number of explanatory variables to be used for forecasting, a task difficult with standard volatility-forecasting formu...

1998
Raymond P. Jefferis

Futurologists continue to tell us (Naisbit 1982, Diebold 1984, Porter 1985, Skinner 1985, Toffler 1990) that we are entering an information age, in which intellectual property and the ability to translate it into flexible productive systems will be the principal competitive advantage available to corporations. Exploiting information systems for this purpose in the pharmaceutical industry is a d...

2002
Andrea Carriero

In this paper we propose a strategy for forecasting the term structure of interest rates which may produce significant gains in predictive accuracy. The key idea is to use the restrictions implied by Affine Term Structure Models (ATSM) on a vector autoregression (VAR) as prior information rather than imposing them dogmatically. This allows to account for possible model misspecification. We appl...

Journal: :Int. Arab J. Inf. Technol. 2015
Meng Han Zhihai Wang Jidong Yuan

Previous mining algorithms on high dimensional datasets, such as biological dataset, create very large patterns sets as a result which includes small and discontinuous sequential patterns. These patterns do not bear any useful information for usage. Mining sequential patterns in such sequences need to consider different forms of patterns, such as contiguous patterns, local patterns which appear...

Alireza Abadi Davood Soroosh Elahe Fahimi Seyyed Mahdi Mirhamidi

Compartment syndrome is a rare vascular disorder and an orthopedic emergency caused by high intramuscular pressure following bone fractures and some other etiologies. It mostly involves extremities, but can affect other parts of the body. The syndrome is diagnosed based on extensively varying signs and symptoms including feeling pain, pallor, pulselessness, and some other signs among patients. ...

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