Two-sided exponential–geometric distribution: inference and volatility modeling

Emrah Altun ()
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Emrah Altun: Bartin University

Computational Statistics, 2019, vol. 34, issue 3, No 13, 1215-1245

Abstract: Abstract In this paper, two-sided exponential–geometric (TSEG) distribution is proposed and its statistical properties are studied comprehensively. The proposed distribution is applied to the GJR-GARCH model to introduce a new conditional model in forecasting Value-at-Risk (VaR). Nikkei-225 and BIST-100 indexes are analyzed to demonstrate the VaR forecasting performance of GJR-GARCH-TSEG model against the GJR-GARCH models defined under normal, Student-t, skew-T and generalized error innovation distributions. The backtesting methodology is used to evaluate the out-of-sample performance of VaR models. Empirical findings show that GJR-GARCH-TSEG model produces more accurate VaR forecasts than other competitive models.

Keywords: GARCH; GJR-GARCH; Exponential–geometric distribution; Value-at-risk; Volatility (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s00180-019-00873-3

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