https://doi.org/10.1140/epjs/s11734-025-01639-3
Regular Article
Recurrent fractal interpolation for data with generalized tempered stable noise: an application to NIFTY data
1
Department of Mathematics-School of Advanced Sciences, Vellore Institute of Technology Chennai, 600127, Chennai, Tamil Nadu, India
2
Department of Mathematics, Indian Institute of Technology Madras, 600036, Chennai, Tamil Nadu, India
Received:
15
March
2025
Accepted:
15
April
2025
Published online:
1
May
2025
This study proposes a fractal interpolation approach to address the issue of missing or unknown values in data with generalized tempered stable noise. The recurrent fractal interpolation method is utilized to estimate intermediate missing or unknown values, and the probability distribution of the constructed linear recurrent fractal interpolation function is derived to analyze the uncertainty around the estimated values. A comprehensive simulation study is conducted to demonstrate the effectiveness of the proposed technique. Moreover, this technique is applied to weekly data from NIFTY, a benchmark index of the National Stock Exchange of India, to demonstrate its practical utility.
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© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
