Sensitivity analysis applied to tilting methodologies

Tom Chan, Julien Riposo (), E. G. Klepfish and Andreas Schroeder
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Tom Chan: Senior Research Analyst, Research and Analytics, LSEG
Julien Riposo: Digital Assets Quantitative Research, LSEG
E. G. Klepfish: Manager, Research - Index Research & Design, EMEA, LSEG
Andreas Schroeder: Head of EMEA Index Research & Design, LSEG

Journal of Asset Management, 2025, vol. 26, issue 2, No 5, 186-215

Abstract: Abstract This paper addresses the challenge of constructing factor portfolios that accurately reflect asset characteristics while remaining robust to noise. We examine the variation of the portfolio weights produced on noisy versions of the original signal while targeting a fixed unit of signal exposure. It is proposed a framework to evaluate how well portfolio strategies handle noise by analyzing how portfolio weights vary with noisy versions of the original signal, while maintaining a consistent level of signal exposure. Assuming normal distribution for signal and noise, we analytically derive the distribution of portfolio weight deviations. These findings are supported by simulations using more realistic skewed, fat-tailed, and correlated signals. The framework is then applied to various common portfolio strategies and factors.

Keywords: Indexing; Tilting; Factor; Sensitivity; Probability (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1057/s41260-024-00388-7

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