Forecasting Volatility of Emerging Stock Markets: Liner versus Non-linear GARCH Models
Article Abstract:
In forecasting the volatility of emerging stock markets, the use of the Generalized Auto Regressive Conditional Heteroscedasticity model is more successful even if stock market return series display skewed distributions.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 2000
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Forecasting and Trading Strategies Based on a Price Trend Model
Article Abstract:
Using a price trend model with assumptions, a trading rule based on these forecasts was applied to returns of the Hang Seng Index Futures in Hongkong and found to be satisfactory.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 2000
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Comparison of two non-parametric models for daily traffic forecasting in Hong Kong
Article Abstract:
A study on forecasting of daily vehicular traffic in Hong Kong, using non-parametric regression and Gaussian maximum likelihood models, is discussed.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 2006
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