Robust Parameter Estimation for Financial Data Simulation

David Lee

MPRA Paper from University Library of Munich, Germany

Abstract: Financial market data are known to be far from normal and replete with outliers, i.e., “dirty” data that contain errors. Data errors introduce extreme or aberrant data points that can significantly distort parameter estimation results. This paper proposes a robust estimation approach to achieve stable and accurate results. The robust estimation approach is particularly applicable for financial data that often features the three situations we are protecting against: occasional rogue values (outliers), small errors and underlying non-normality.

Keywords: robust parameter estimation; financial market data; market data simulation; risk factor. (search for similar items in EconPapers)
JEL-codes: C13 C15 C53 C63 G17 (search for similar items in EconPapers)
Date: 2025-08
New Economics Papers: this item is included in nep-cmp, nep-ecm and nep-mac
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:125703

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