Forecasting stock market volatility using (non‐linear) Garch models
نویسندگان
چکیده
منابع مشابه
Forecasting Stock Market Volatility Using (Non-Linear) Garch Models
In this papeT we study the performance of the GARCH model and two of its non-linear modifications to forecast weekly stock market volatility. The models are the Quadratic GARCH (Engle and Ng. 1993) and the Glosten. Jagannathan and Runkle (1992) models which have been proposed to describe, for example, the often observed negative skewness in stock market indices. We find that the QGARCH model is...
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This paper investigates the nature of volatility characteristics of stock returns in the Bangladesh stock markets employing daily all share price index return data of Dhaka Stock Exchange (DSE) and Chittagong Stock Exchange (CSE) from 02 January 1993 to 27 January 2013 and 01 January 2004 to 20 August 2015 respectively. Furthermore, the study explores the adequate volatility model for the stoc...
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The discrete time ARCH/GARCH model of Engle and Bollarslev has been enormously influential and successful in the modelling of financial data. Recently, Klüppelberg, Lindner, andMaller (2004) introduced the so-called “COGARCH”model as a continuoustime analogue to the GARCH model. Many aspects of the COGARCH have been investigated, including various of its theoretical properties, its relations to...
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ژورنال
عنوان ژورنال: Journal of Forecasting
سال: 1996
ISSN: 0277-6693,1099-131X
DOI: 10.1002/(sici)1099-131x(199604)15:3<229::aid-for620>3.3.co;2-v