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Journal of Finance and Accounting. 2013, 1(2), 48-53
DOI: 10.12691/jfa-1-2-2
Open AccessArticle

Does Anyone Need a GARCH(1,1)?

Erhard Reschenhofer1,

1Department of Statistics and Operations Research, University of Vienna, Vienna, Austria

Pub. Date: June 20, 2013

Cite this paper:
Erhard Reschenhofer. Does Anyone Need a GARCH(1,1)?. Journal of Finance and Accounting. 2013; 1(2):48-53. doi: 10.12691/jfa-1-2-2


Hansen and Lunde [16] posed the question "Does anything beat a GARCH(1,1)?" and compared a large number of parametric volatility models in an extensive empirical study. They found that no other model provides significantly better forecasts than the GARCH(1,1) model. In contrast, this paper arrives at the conclusion that simple robust estimators such as weighted medians of past (squared) returns outperform the GARCH(1,1) model both in-sample as well as out-of-sample. This conclusion is based on theoretical arguments as well as on empirical evidence.

conditional heteroskedasticity volatility weighted medians intraday range Brownian motion

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