Dataset and Application for a Hybrid HRP–MEREC–WEDBA Portfolio Optimization Model

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Authors: Ali Katrancı
Cited by: 0

Abstract

The firm-level daily stock closing prices in this dataset are utilized in the empirical implementation of a hybrid portfolio optimization framework that incorporates MEthod based on the Removal Effects of Criteria (MEREC), Weighted Euclidean Distance Based Approximation (WEDBA), and Hierarchical Risk Parity (HRP) techniques. The dataset contains the raw data as well as the implementation phases and computational processes of the MEREC and WEDBA algorithms used in the portfolio optimization process. In order to facilitate replication, validation, and additional research in portfolio optimization and multi-criteria decision-making applications, the data were gathered and preprocessed for portfolio construction and performance analysis.

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
3 January 2026
Document type
Dataset