Online Portfolio Selection of LQ45 Stocks Index with the Adaptive Online Moving Average Method

Irkham Muhammad Fakhri, Deni Saepudin, Aniq Rohmawati

2023

Abstract

An online portfolio is a collection or composition of a fund in financial assets with specific returns held online. Online portfolio selection can increase the chances of getting the right stocks. One way to choose an online portfolio is using the Adaptive Online Moving Average (AOLMA) method. This method predicts stock returns using adaptive decay variables from moving averages so that the predictive rate increases even more. In this paper, portfolio selection using the Adaptive Online Moving Average (AOLMA) method is carried out on the LQ45 stock index dataset from April 2012 to April 2022. The portfolio performance is then compared to the Equal Weight Portfolio (EWP). This portfolio is superior to the equal-weight portfolio in terms of mean return.

Paper Citation

in Harvard Style

Muhammad Fakhri I., Saepudin D. and Rohmawati A. (2023). Online Portfolio Selection of LQ45 Stocks Index with the Adaptive Online Moving Average Method. In Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD; ISBN 978-989-758-678-1, SciTePress, pages 321-327. DOI: 10.5220/0012639200003848

in Bibtex Style

@conference{icaisd23,
author={Irkham Muhammad Fakhri and Deni Saepudin and Aniq Rohmawati},
title={Online Portfolio Selection of LQ45 Stocks Index with the Adaptive Online Moving Average Method},
booktitle={Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD},
year={2023},
pages={321-327},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012639200003848},
isbn={978-989-758-678-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD
TI - Online Portfolio Selection of LQ45 Stocks Index with the Adaptive Online Moving Average Method
SN - 978-989-758-678-1
AU - Muhammad Fakhri I.
AU - Saepudin D.
AU - Rohmawati A.
PY - 2023
SP - 321
EP - 327
DO - 10.5220/0012639200003848
PB - SciTePress