Results 31 to 40 of about 244 (54)

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

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

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, Rodrigues, Helena Sofia, Torres, Delfim F. M.   +2 more
core   +1 more source

MONTE CARLO AND NUMERICAL METHODS TO SOLVE THE TIME SERIES MODEL

Analele Universitatii Bucuresti. Informatica
In this paper we will solve the nonlinear system of equations in the parameters of the time series model by Monte Carlo methods and by numerical methods.
Daniel Ciuiu
semanticscholar   +1 more source

A Continuous Time GARCH Process of Higher Order [PDF]

, 2005
A continuous time GARCH model of order (p,q) is introduced, which is driven by a single Lévy process. It extends many of the features of discrete time GARCH(p,q) processes to a continuous time setting.
Brockwell, Peter J., Chadraa, Erdenebaatar, Lindner, Alexander M.   +2 more
core   +2 more sources

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

A Bayesian Networks Approach to Operational Risk

, 2010
A system for Operational Risk management based on the computational paradigm of Bayesian Networks is presented. The algorithm allows the construction of a Bayesian Network targeted for each bank using only internal loss data, and takes into account in a ...
Aquaro, V., Bardoscia, M., Bellotti, R., Consiglio, A., De Carlo, F., Ferri, G.   +5 more
core   +1 more source

Asymptotics of Asynchronicity [PDF]

, 2011
In this article we focus on estimating the quadratic covariation of continuous semimartingales from discrete observations that take place at asynchronous observation times.
Bibinger, Markus
core   +4 more sources

Wavelet-Based Prediction for Governance, Diversification and Value Creation Variables [PDF]

, 2010
We study the possibility of completing data bases of a sample of governance, diversification and value creation variables by providing a well adapted method to reconstruct the missing parts in order to obtain a complete sample to be applied for testing ...
Hallara, Slah-Eddine, Kahloul, Ines, Mabrouk, Anouar Ben   +2 more
core  

Cross sectional efficient estimation of stochastic volatility short rate models [PDF]

, 2001
We consider the problem of estimation of term structure of interest rates. Filtering theory approach is very natural here with the underlying setup being non-linear and non-Gaussian. Earlier works make use of Extended Kalman Filter (EKF).
Danilov, D., Mandal, P.K.
core   +4 more sources