Forecasting and backtesting of market risks in emerging markets

Dean Fantazzini

Emerging markets often go through periods of financial turbulence and the estimation of market risk measures may be problematic. Online search queries and implied volatility may (or may not) improve the model estimates. In these situations a step-by-step analysis with R and Russian market data is provided. Four classes of models are considered (GARCH, HAR, ARFIMA, and realized-GARCH), and a detailed forecasting and backtesting investigation is performed.

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Year of publication:	2021
Authors:	Fantazzini, Dean
Published in:	Risk assessment and financial regulation in emerging markets' banking : trends and prospects. - Cham, Switzerland : Springer, ISBN 978-3-030-69747-1. - 2021, p. 199-223
Subject:	ARFIMA \| Forecasting \| GARCH \| Google trends \| HAR \| Implied volatility \| Realized volatility \| Realized-GARCH \| Value-at-risk \| ARCH-Modell \| ARCH model \| Volatilität \| Volatility \| Prognoseverfahren \| Forecasting model \| Risikomaß \| Risk measure \| Schwellenländer \| Emerging economies \| Zeitreihenanalyse \| Time series analysis \| Marktrisiko \| Market risk \| ARMA-Modell \| ARMA model

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Type of publication:	Article
Type of publication (narrower categories):	Aufsatz im Buch ; Book section
Language:	English
Other identifiers:	10.1007/978-3-030-69748-8_9 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012591721