Results 11 to 20 of about 229 (64)
A fractionally integrated ECOGARCH process [PDF]
, 2006 In this paper we introduce a fractionally integrated exponential continuous time GARCH(p,d,q) process. It is defined in such a way that it is a continuous time extension of the discrete time FIEGARCH(p,d,q) process.
Czado, Claudia, Haug, Stephan
core +3 more sources
Volatility filtering in estimation of kurtosis (and variance)
Dependence Modeling, 2019 The kurtosis of the distribution of financial returns characterized by high volatility persistence and thick tails is notoriously difficult to estimate precisely.
Anatolyev Stanislav
doaj +1 more source
Estimating the COGARCH(1,1) model - a first go [PDF]
, 2005 We suggest moment estimators for the parameters of a continuous time GARCH(1,1) process based on equally spaced observations. Using the fact that the increments of the COGARCH(1,1) process are ergodic, the resulting estimators are consistent.
Haug, Stephan +3 more
core +2 more sources
Dependence Modeling, 2019 The relationship between the European stock market and the crude oil depends on the significance of the different industries in the European economy. The literature points to a structural change after the 2008 crisis without getting into details of which
Ferreiro Javier Ojea
doaj +1 more source
An exponential continuous time GARCH process [PDF]
, 2006 In this paper we introduce an exponential continuous time GARCH(p,q) process. It is defined in such a way that it is a continuous time extension of the discrete time EGARCH(p,q) process. We investigate stationarity and moment properties of the new model.
Czado, Claudia, Haug, Stephan
core +3 more sources
Copula multivariate GARCH model with constrained Hamiltonian Monte Carlo
Dependence Modeling, 2019 The Copula Multivariate GARCH (CMGARCH) model is based on a dynamic copula function with time-varying parameters. It is particularly suited for modelling dynamic dependence of non-elliptically distributed financial returns series.
Burda Martin, Bélisle Louis
doaj +1 more source
Auto-tail dependence coefficients for stationary solutions of linear stochastic recurrence equations and for GARCH(1,1) [PDF]
, 2010 We examine the auto-dependence structure of strictly stationary solutions of linear stochastic recurrence equations and of strictly stationary GARCH(1, 1) processes from the point of view of ordinary and generalized tail dependence coefficients.
B Basrak +6 more
core +1 more source
Bayesian Model Selection for Beta Autoregressive Processes [PDF]
, 2010 We deal with Bayesian inference for Beta autoregressive processes. We restrict our attention to the class of conditionally linear processes. These processes are particularly suitable for forecasting purposes, but are difficult to estimate due to the ...
Casarin, R., Leisen, F., Valle, L. Dalla
core +2 more sources
Parametric identification of the dynamics of inter-sectoral balance: modelling and forecasting
, 2019 This work is devoted to modelling and identification of the dynamics of the inter-sectoral balance of a macroeconomic system. An approach to the problem of specification and identification of a weakly formalized dynamical system is developed.
Kostylenko, Olena +2 more
core +1 more source
On the threshold hyperbolic GARCH models [PDF]
, 2011 In the financial market, the volatility of financial assets plays a key role in the problem of measuring market risk in many investment decisions. Insights into economic forces that may contribute to or amplify volatility are thus important.
Kwan, W, Li, G, Li, WK
core +1 more source