Horizon and Regime Dependent Performance of GARCH Type Models: Evidence from Volatility Forecasting in a Frontier Market

This study examined the comparative performance of GARCH family models including GARCH, EGARCH, GJR GARCH, APARCH, and FIGARCH within a horizon and regime aware framework to assess forecasting accuracy. Using daily prices of equity and foreign exchange markets in Kenya covering 1997–2024, volatility was modelled and validated through Value at Risk and Expected Shortfall back tests to establish economic relevance. The results reveal strong horizon and regime dependence: EGARCH performs well in capturing short run volatility in the equity market and turbulent foreign exchange re-gimes, while FIGARCH dominates in calm equity markets and at medium term horizons. Risk validation confirms that FIGARCH delivers reliable tail risk forecasts for equities, whereas EGARCH excels in turbulent foreign exchange markets. Unlike prior comparative studies that focus on efficient markets with stable volatility structures, this study applied GARCH family models to a frontier market, comparing forecasting accuracy across vary-ing horizons and regimes. The study advanced beyond best fit evaluations by linking forecasting performance to horizon length, asset type, and regime shifts, thereby contrib-uting new evidence on modelling volatility in African frontier markets and offering in-sights relevant for regulators, institutional investors, and policymakers concerned with financial stability.