ARTICLE
TITLE

Volatility Estimation and Forecasting During Crisis Periods: A Study Comparing GARCH Models with Semiparametric Additive Models

SUMMARY

In this paper, we compare semiparametric additive models with GARCH models in terms of their capability to estimate and forecast volatility during crisis periods. Our Monte Carlo studies indicate a better performance for GARCH models when their functional forms do not differ from that of the specified Data Generating Process (DGP). However, if they differ from the DGP, the results suggest the superiority of additive models. Additionally, we perform an empirical application in three selected periods of high volatility of IBOVESPA returns series, in which both families of models obtain similar results.

 Articles related

Didit B Nugroho,Bambang Susanto,Saragah R Pratama    

Volatiliy measurement and modeling is an important aspect in many areas of finance. The main purpose of this study is to apply seven APARCH-type models with (1,1) lags to investigate the behavior of exchange rate volatility for the EUR, JPY, and USD sell... see more


Andre Barbosa Oliveira,Pedro L. Valls Pereira    

Petroleum is an important energy commodity, being used in different activities, having a direct or indirect effect on several sectors in the economy. This commodity has unstable prices, as a result of geopolitical shocks as well as market shocks in the p... see more


Saarce Elsye Hatane    

Cocoa plays an important role in generating Indonesian foreign exchange revenues since it is one of Indonesia’s primary commodity exports. Meanwhile, as part of plantation commodity, cocoa’s price also has volatility nature. This study has two aims: to e... see more


Saarce Elsye Hatane    

Agricultural sector plays an important role in Indonesia’s economy; especially for the plantation sub-sector contributing high revenues to Indonesia’sexporting sectors. The primary agricultural commodities in Indonesian export discussed in this study wou... see more


Abdul Khaliq    

This paper investigates the conditional predictability of geopolitical risks (GPR) on the rupiah-dollar exchange rate volatility, using 447 monthly observations spanning January 1985 to March 2022. The paper utilizes asymmetric GARCH (1,1) combined with ... see more