A Generalized Autoregressive Conditional Heteroskedasticity
Model of the Impact of Macroeconomic Factors on Stock Returns: Empirical Evidence from the Nigerian Stock Market.
Most of the literature on the international interactions of stock returns, foreign exchange rate changes and volatility spillovers employ Generalized Autoregressive Conditional Heteroskedasticity
(GARCH) models (Bollerslev, 1986).
Since the OLS does not consider autoregressive conditional heteroskedasticity
, its residual variance is likely to be biased, and hypothesis tests are invalid.
The first- and fourth-order autoregressive conditional heteroskedasticity
tests, however, suggest weak (Mexican peso) to strong (Japanese yen) ARCH effects.
Value at Risk-Exponential Generalized Autoregressive Conditional Heteroskedasticity
(VAR-EGARCH) methodology) to examine the lead-lag relationship between stock and futures markets of France, Germany, and the UK, and confirm that futures markets lead spot markets.
O modelo de volatilidade de series temporais mais importante para estimar variancia condicional e o modelo de processos de heterocedasticidade condicional auto-regressiva generalizada (generalized autoregressive conditional heteroskedasticity
-- Garch) (BOLLERSLEV, 1986; BOLLERSLEV et al.
Autoregressive Conditional Heteroskedasticity
(ARCH) model describes the forecast variance in terms of current observations (Engle, 2004).
In this sense, the present paper suggests the use of autoregressive conditional heteroskedasticity
and stochastic volatility models to predict the volatility used in VaR measures.
1982, Autoregressive Conditional Heteroskedasticity
with Estimates of the Variance of the U.
The Autoregressive Conditional Heteroskedasticity
methodology, presented in Engle takes into account the time-varying nature of the conditional variance.
Engle received the prize for his research on the concept of autoregressive conditional heteroskedasticity
The results of these tests indicate that the residual is normally distributed and there is also no problem of serial correlation and autoregressive conditional heteroskedasticity
Another study by Worthington (2008) adopts the Generalized Autoregressive Conditional Heteroskedasticity
(GARCH) and the GARCH-in-the-mean model based on the Australian stock market.
Fractionally integrated generalized autoregressive conditional heteroskedasticity
, Journal of Econometrics 7 A: 3-30.
Bollerslev's Generalized Autoregressive Conditional Heteroskedasticity
(GARCH) model (1986) is our choice of methodology in the present study.