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Volatility forecasting of exchange rate by quantile regression

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  • Huang, Alex YiHou
  • Peng, Sheng-Pen
  • Li, Fangjhy
  • Ke, Ching-Jie
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    Abstract

    Exchange rates are known to have irregular return patterns; not only their return volatilities but the distribution functions themselves vary with time. Quantile regression allows one to predict the volatility of time series without assuming an explicit form for the underlying distribution. This study presents an approach to exchange rate volatility forecasting by quantile regression utilizing a uniformly spaced series of estimated quantiles. Based on empirical evidence of nine exchange rate series, using 19Â years of daily data, the adopted approach generally produces more reliable volatility forecasts than other key methods.

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    Bibliographic Info

    Article provided by Elsevier in its journal International Review of Economics & Finance.

    Volume (Year): 20 (2011)
    Issue (Month): 4 (October)
    Pages: 591-606

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    Handle: RePEc:eee:reveco:v:20:y:2011:i:4:p:591-606

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    Web page: http://www.elsevier.com/locate/inca/620165

    Related research

    Keywords: Exchange rate Volatility Quantile regression;

    References

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    Cited by:
    1. Mauricio Lopera Castaño & Ramón Javier Mesa Callejas & Sergio Iván Restrepo Ochoa & Charle Augusto Londoño Henao, 2013. "Modelando el esquema de intervenciones del tipo de cambio para Colombia. una aplicación empírica de la técnica de regresión del cuantil bajo redes neu," REVISTA CUADERNOS DE ECONOMÍA, UN - RCE - CID.

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