LONG-TERM VOLATILITY DYNAMICS OF THE GERMAN STOCK MARKET: INSIGHTS FROM TWO DECADES OF DAILY RETURNS

Shahil Raza, Aman Shreevastava, Bharat Kumar Meher, Birau Ramona, Popescu Virgil, Roshan Kumar Yadav and Lupu (filip) Gabriela Ana Maria
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Shahil Raza: DEPARTMENT OF COMMERCE, ALIGARH MUSLIM UNIVERSITY, ALIGARH, UTTAR PRADESH 202001, INDIA
Aman Shreevastava: P.G. DEPARTMENT OF COMMERCE AND MANAGEMENT, PURNEA UNIVERSITY, PURNEA, BIHAR, INDIA-854301
Bharat Kumar Meher: P.G. DEPARTMENT OF COMMERCE AND MANAGEMENT, PURNEA UNIVERSITY, PURNEA, BIHAR, INDIA-854301
Birau Ramona: UNIVERSITY OF CRAIOVA, EUGENIU CARADA DOCTORAL SCHOOL OF ECONOMIC SCIENCES, CRAIOVA, ROMANIA & CONSTANTIN BRANCUSI UNIVERSITY OF TARGU JIU, FACULTY OF ECONOMIC SCIENCE, TG- JIU, ROMANIA
Popescu Virgil: FACULTY OF ECONOMICS AND BUSINESS ADMINISTRATION, UNIVERSITY OF CRAIOVA, CRAIOVA, ROMANIA
Roshan Kumar Yadav: P.G. DEPARTMENT OF COMMERCE AND MANAGEMENT, PURNEA UNIVERSITY, PURNEA, BIHAR, INDIA-854301
Lupu (filip) Gabriela Ana Maria: UNIVERSITY OF CRAIOVA, EUGENIU CARADA DOCTORAL SCHOOL OF ECONOMIC SCIENCES, CRAIOVA, ROMANIA

Annals - Economy Series, 2026, vol. 2, 96-105

Abstract: This study provides an empirical analysis of the volatility dynamics of the Deutscher Aktienindex (DAX) stock index over a 20-year period based on daily observations, specifically from January 2, 2006, to March 20, 2026. Utilizing a dataset of 5,140 daily return points, the research explores the time-varying nature of market risk and the presence of volatility clustering. The primary objective is to identify a robust econometric framework capable of capturing the asymmetric response of volatility to market shocks, commonly known as the leverage effect. To achieve this, the study evaluates several GARCH-family models specifications, including GARCH, EGARCH, GJRGARCH, and APARCH models, paired with various error distributions such as Normal, Student-t, GED, and Skewed-t. Initial testing confirms that the return series is stationary, non-normally distributed, and characterized by significant "fat tails". Based on the lowest Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), the GJR-GARCH model with a Skewed-t distribution is identified as the most suitable model for the DAX index. The results demonstrate high volatility persistence and provide strong evidence of the leverage effect, where negative market shocks impact volatility more significantly than positive ones. Diagnostic checks, including the Ljung-Box test, confirm that the model successfully captures the underlying volatility structure. These findings offer valuable insights for investors and policymakers regarding risk assessment and strategic decision-making in the German equity market.

Keywords: DAX Index; GJR-GARCH model; Volatility Clustering; Leverage Effect; Skewed-t Distribution; Market Risk (search for similar items in EconPapers)
Date: 2026
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