Analisis Kinerja Portofolio Saham Optimal pada Indeks LQ45 dengan Pendekatan Metode Sparse for High Dimensional Index Tracking dan Sparse Mean Reverting

Pricila, Verencia (2023) Analisis Kinerja Portofolio Saham Optimal pada Indeks LQ45 dengan Pendekatan Metode Sparse for High Dimensional Index Tracking dan Sparse Mean Reverting. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Investasi dianggap penting dalam merealisasikan manajemen keuangan yang baik karena bisa memberikan keamanan finansial di masa kini dan masa depan, bahkan sebagai jalan untuk memperoleh passive income dan meningkatkan kekayaan secara sekaligus. Dalam praktiknya, investasi kerap dikaitkan dengan berbagai macam alternatif baik real asset ataupun dalam financial asset. Produk investasi seperti saham mampu memberikan pengembalian yang substansial tetapi selalu berbanding lurus atau diimbangi oleh risiko yang cukup besar. Pada banyak situasi investasi, beberapa efisiensi digunakan untuk optimalisasi kekayaan. Optimasi dilakukan untuk mengurangi risiko karena adanya diversifikasi yang terbentuk berdasarkan preferensi sehingga portofolio yang dihasilkan. Pada penelitian ini, dilakukan pembentukkan portofolio berdasarkan metode Sparse for High Dimensional Index Tracking (HDIT) dan Sparse Mean Reverting (MR) berdasarkan preferensi saham indeks LQ45 untuk mengacu pada kinerja IHSG untuk kemudian dibandingkan risiko dan kinerjanya. Melalui kedua metode tersebut, didapatkan 18 saham sebagai penyusun portofolio HDIT dan 25 saham penyusun portofolio MR. Berdasarkan besar risiko melalui ukuran Value at Risk (VaR) dan Conditional Value at Risk (CVaR), didapatkan portofolio HDIT memiliki ukuran Risiko lebih rendah dibandingkan portofolio MR atau tepatnya sebesar -2,0137% dan -2,8631% dibandingkan -2,2954% dan -3,3665%. Disamping itu, diperoleh rata-rata return portofolio HDIT lebih tinggi 0,0033% dibandingkan rata-rata return MR, tepatnya 0,0859% untuk portofolio HDIT dan 0,0826% untuk portofolio MR. Sedangkan untuk kinerja portofolio secara indeks Sharpe, Treynor dan Jensen, juga dihasilkan portofolio HDIT lebih baik dibandingkan portofolio MR karena memiliki nilai yang lebih tinggi.
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Investment is considered necessary in realizing good financial management because it can provide financial security in the present and the future, even as a way to earn passive income and increase wealth all at once. In practice, investment is often associated with various alternatives, both real assets and financial assets. Investment products such as stocks can provide substantial returns but are always directly proportional or offset by considerable risk. In many investment situations, several efficiencies are used for wealth optimization. Optimization is carried out to reduce risk due to diversification which is formed based on preferences so that the resulting portfolio. In this study, portfolio formation was carried out based on the Sparse for High Dimensional Index Tracking (HDIT) and Sparse Mean Reverting (MR) methods based on LQ45 index stock preference to refer to the performance of the JCI to compare the risk and performance. Through these two methods, 18 stocks made up the HDIT portfolio, and 25 stocks made up the MR portfolio. Based on the size of the risk through Value at Risk (VaR) and Conditional Value at Risk (CVaR) measures, it is found that the HDIT portfolio has a lower risk measure than the MR portfolio or, to be precise -2.0137% and -2.8631% compared to -2.2954 % and -3.3665%. In addition, the average HDIT portfolio return was 0.0033% higher than the MR average return, to be exact 0.0859% for the HDIT portfolio and 0.0826% for the MR portfolio. zivolaoAs for the performance of the portfolio in terms of the Sharpe, Treynor, and Jensen index, the HDIT portfolio is also better than the MR portfolio because it has a higher value.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Investment, Portfolio Optimization, Sparse for High Dimensional Index Tracking, Sparse Mean Reverting, Stocks Investasi, Optimasi Portofolio, Saham, Sparse for High Dimensional Index Tracking, Sparse Mean Reverting
Subjects:	Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry)
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Actuaria > 94203-(S1) Undergraduate Thesis
Depositing User:	Verencia Pricila
Date Deposited:	19 Jan 2023 07:01
Last Modified:	19 Jan 2023 07:01
URI:	http://repository.its.ac.id/id/eprint/95491

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