FORECASTING REALIZED VOLATILITY WITH LINEAR AND NONLINEAR UNIVARIATE MODELS

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Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/69894

標題:	FORECASTING REALIZED VOLATILITY WITH LINEAR AND NONLINEAR UNIVARIATE MODELS
作者:	McAleer, M. Medeiros, M.C.
關鍵字:	Bagging;Financial econometrics;Neural networks;Nonlinear models;Realized volatility;Volatility forecasting;neural-network models;time-series;stochastic volatility;market;microstructure;feedforward networks;long-memory;inflation;return;noise;variance
Project:	Journal of Economic Surveys
期刊/報告no：:	Journal of Economic Surveys, Volume 25, Issue 1, Page(s) 6-18.
摘要:	In this paper, we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S&P 500 and FTSE 100 futures. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is computed from high-frequency intraday returns. We also consider a simple algorithm based on bagging (bootstrap aggregation) in order to specify the models analysed in this paper.
URI:	http://hdl.handle.net/11455/69894
ISSN:	0950-0804
DOI:	10.1111/j.1467-6419.2010.00640.x
Appears in Collections:	期刊論文

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