Showing 1 - 6 of 6
This paper presents a 2-regime SETAR model with different long-memory processes in both regimes. We briefly present the memory properties of this model and propose an estimation method. Such a process is applied to the absolute and squared returns of five stock indices. A comparison with simple...
Persistent link: https://www.econbiz.de/10010750892
This paper focuses on the use of dynamical chaotic systems in Economics and Finance. In these fields, researchers employ different methods from those taken by mathematicians and physicists. We discuss this point. Then, we present statistical tools and problems which are innovative and can be...
Persistent link: https://www.econbiz.de/10010738625
We propose a novel methodology for forecasting chaotic systems which is based on exploiting the information conveyed by the local Lyapunov ex- ponent of a system. We show how our methodology can improve forecast- ing within the attractor and illustrate our results on the Lorenz system.
Persistent link: https://www.econbiz.de/10010603652
This paper presents a 2-regime SETAR model with a long-memory process in the first regime and a short-memory process in the second regime. We briefly introduce the properties of this model and methods for locating the threshold parameter are proposed. Such a process is applied to stock indices...
Persistent link: https://www.econbiz.de/10008790799
The paper focuses on the conditions of the use of the nearest neighbors method analysing the impact of the Euclidean distance and in sample predictions, the choice of the neighbors, the number of neighbors and the distance between the neighbors.
Persistent link: https://www.econbiz.de/10008792374
This paper presents a 2-regime SETAR model with different longmemory processes in both regimes. We briefly present the memory properties of this model and propose an estimation method. Such a process is applied to the absolute and squared returns of five stock indices. A comparison with simple...
Persistent link: https://www.econbiz.de/10008794815