Results 91 to 100 of about 3,916 (205)
Modeling and forecasting the volatility of Brazilian asset returns [PDF]
The goal of this paper is twofold. First, using five of the most actively traded stocks in the Brazilian financial market, this paper shows that the normality assumption commonly used in the risk management area to describe the distributions of returns ...
Leonardo Souza +3 more
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A Hybrid Fuzzy GJR-GARCH Modeling Approach for Stock Market Volatility Forecasting
, 2013 Forecasting stock market returns volatility is a challenging task that has attracted the attention of market practitioners, regulators and academics in recent years. This paper proposes a Fuzzy GJR-GARCH model to forecast the volatility of S&P 500 and Ibovespa indexes.
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Estimated Value-at-Risk Using the ARIMA-GJR-GARCH Model on BBNI Stock
Operations Research: International Conference SeriesStocks are investment instruments that are much in demand by investors as a basis in financial storage. Return and risk are the most important things in investing. Return is a complete summary of investment and the return series is easier to handle than the price series. The movement of risk of loss is obtained from stock investments with profits.
Rizki Apriva Hidayana +2 more
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Quantitative Finance and Economics, 2019 Este estudio emplea varios métodos para simular y construir la cartera a partir de índices bursátiles de los seis mercados de la Asociación de Naciones del Sudeste Asiático (ASEAN) durante el período comprendido entre enero de 2001 y diciembre de 2017, a saber, Cópulas variables en el tiempo; Glosten, Jagannathan y Runkle (GJR); heterocedasticidad ...
Sang Phu Nguyen, Toan Luu Duc Huynh
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A Skewed GARCH-in-Mean Model: An Application to U.S. Stock Returns [PDF]
In this paper we consider a GARCH-in-Mean (GARCH-M) model based on the so-called z distribution. This distribution is capable of modeling moderate skewness and kurtosis typically encountered in financial return series, and the need to allow for skewness ...
Markku Lanne, Pentti Saikkonen
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Estimating and Forecasting Volatility of Financial Time Series in Pakistan with GARCH-type Models
Lahore Journal of EconomicsIn this paper we compare the performance of different GARCH models such as GARCH, EGARCH, GJR and APARCH models, to characterize and forecast financial time series volatility in Pakistan.
G.R. Pasha, Tahira Qasim, Muhammad Aslam
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Exchange Rate Exposure of Sectoral Returns and Volatilities: Evidence from Japanese Industrial Sectors [PDF]
Most studies of exchange rate exposure of stock returns do not address three relevant aspects simultaneously. They are, namely: sensitivity of stock returns to exchange rate changes; sensitivity of volatility of stock returns to volatility of changes in ...
Albert K. Tsui, Prabhath Jayasinghe
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Modelo Híbrido GJR-GARCH Nebuloso para a Previsão da Volatilidade em Mercados de Ações
Brazilian Review of Finance, 2012 A previsão da volatilidade dos retornos de ativos financeiros é uma abordagem desafiadora e tem atraído a atenção de participantes do mercado, reguladores e acadêmicos nos anos recentes. Este artigo propõe um modelo GJR-GARCH nebuloso para a previsão da volatilidade dos índices S&P 500 e Ibovespa.
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Forecasting the time-varying beta of UK firms: GARCH models vs Kalman filter method
, 2007 This paper forecast the weekly time-varying beta of 20 UK firms by means of four different GARCH models and the Kalman filter method. The four GARCH models applied are the bivariate GARCH, BEKK GARCH, GARCH-GJR and the GARCH-X model.
Choudhry, Taufiq, Wu, Hao
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Volatility Transmission acros the Term Structure of Swap Markets: International Evidence [PDF]
We characterize the behavior of volatility across the term structure of interest rate swaps in three currencies (Deutsche mark, Japanese yen and US Dollar)Interest rate swaps, Term structure of interest rates, Autoregressive conditional heteroscedstic ...
Alfonso Novales, Pilar Abad
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