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- W4283221344 abstract "The purpose of this study is to investigate the time-varying co-movement between the volatility of gold, exchange rate, and stock market returns in Iran, using weekly data from 27 September 2013 to 3 December 2021. The results of the wavelet-based random forest show that the performance of VAR-DCC-GARCH model is better than that of DCC-GARCH model in predicting financial market volatilities. Furthermore, the results of the VAR-DCC-GARCH model indicate that a positive and relatively high conditional correlation exists in the daily exchange rate and gold-return volatility. The conditional correlation is lower between the exchange rate–stock market returns and the daily gold–stock market returns. In short and long terms, there is no correlation between the exchange rate and the stock market volatilities as well as gold and stock market volatilities, while the correlation between the paired markets exists in the medium term." @default.
- W4283221344 created "2022-06-22" @default.
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- W4283221344 date "2022-06-20" @default.
- W4283221344 modified "2023-09-26" @default.
- W4283221344 title "A Hybrid Model of VAR-DCC-GARCH and Wavelet Analysis for Forecasting Volatility" @default.
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- W4283221344 doi "https://doi.org/10.3390/engproc2022018006" @default.
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