Prognozowanie stanu turbulencji dla instrumentu finansowego w perspektywie dziennej na podstawie modeli dla binarnej zmiennej zależnej
One-day prediction of state of turbulence for financial instrument based on models for binary dependent variable
Author(s): Marcin ChlebusSubject(s): Economy, Financial Markets
Published by: Uniwersytet Warszawski - Wydział Nauk Ekonomicznych
Keywords: forecasting; state of turbulence; state switching models; binary dependent variable models (LOGIT; PROBIT; CLOGLOG); market risk
Summary/Abstract: This paper proposes an approach to predict states (states of tranquillity and turbulence) for a financial instrument in a one-day horizon. The prediction is made using 3 different models for a binary variable (LOGIT, PROBIT, CLOGLOG), 4 definitions of a dependent variable (1%, 5%, 10%, 20% of worst realization of returns), 3 sets of independent variables (untransformed data, PCA analysis and factor analysis). Additionally an optimal cut-off point analysis is performed. The evaluation of the models was based on the LR test, Hosmer-Lemeshow test, GINI coefficient analysis and KROC criterion based on the ROC curve.Nine combinations of assumptions have been chosen as appropriate (any model for a binary variable, the dependent variable defined as 1%, 5% or 10% of worst realization of returns, untransformed data, 1%, 5% or 10% cut-off point respectively). Models built on these assumptions meet all the formal requirements and have a high predictive and discriminant ability.
Journal: Ekonomia. Rynek, Gospodarka, Społeczeństwo
- Issue Year: 2014
- Issue No: 37
- Page Range: 127-148
- Page Count: 22
- Language: Polish