Analisis Survival Saham Pada Indeks IDX30 Menggunakan Regresi Cox Time Dependent Covariates

Arianthi, Putu Manik Sesa (2025) Analisis Survival Saham Pada Indeks IDX30 Menggunakan Regresi Cox Time Dependent Covariates. Diploma thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Ketidakstabilan ekonomi global termasuk pasar modal terjadi karena berbagai faktor seperti kebijakan moneter, pandemi, dan isu geopolitik. Hal ini dapat memengaruhi keputusan investor dalam berinvestasi, tercermin dari penurunan Indeks Harga Saham Gabungan (IHSG) sebesar -1,48% saat terjadi isu geopolitik yaitu invasi Rusia-Ukraina pada tahun 2022. Selain IHSG, kinerja pasar modal juga dapat diukur melalui indeks IDX30. Namun, komposisi saham IDX30 terus berubah akibat evaluasi mayor oleh BEI. Hal ini menyebabkan waktu bertahan setiap saham dalam IDX30 bervariasi tergantung pada likuiditas, kapitalisasi pasar, dan fundamental perusahaan yang dapat dilihat dari rasio keuangan. Untuk memfokuskan pengambilan keputusan dan strategi investasi jangka panjang, maka perlu dilakukan analisis guna mengetahui risiko dari rasio keuangan yang berpengaruh signifikan terhadap ketahanan suatu saham di IDX30, sehingga dapat dilakukan pengukuran peluang sebuah saham bertahan pada IDX30 dalam jangka waktu tertentu. Metode yang dapat digunakan adalah analisis survival dengan model Cox Proportional Hazard (CPH). Kelebihan dari model CPH yaitu tidak memiliki bentuk distribusi spesifik pada baseline hazard, sehingga model dapat menyesuaikan berbagai pola risiko yang mungkin ada pada data. Selain itu, model dapat dimodifikasi dengan mempertimbangkan variabel prediktor yang berubah seiring berjalannya waktu (time dependent covariate). Hasil analisis menunjukkan bahwa variabel ROE dan jenis sektor berpengaruh terhadap lama waktu bertahan saham di IDX30. Selain itu, peningkatan ROE dapat menurunkan risiko saham untuk keluar dari IDX30 dan seluruh sektor memiliki risiko lebih tinggi untuk keluar dari IDX30 dibandingkan sektor barang baku.
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Global economic instability, including in the capital markets, arises from various factors such as monetary policy, pandemics, and geopolitical issues. This can affect investor decisions, as reflected by a 1.48% decline in the Jakarta Composite Index (JCI) during geopolitical tensions like the Russia-Ukraine invasion. In addition to the JCI, the performance of the capital market can also be measured through the IDX30 index. However, the composition of IDX30 stocks continuously changes due to major evaluations by the Indonesia Stock Exchange (IDX). This leads to varying durations of each stock's presence in the IDX30, depending on liquidity, market capitalization, and company fundamentals as indicated by financial ratios. Therefore, to focus decision-making and long-term investment strategies, it is necessary to analyze the risks associated with financial ratios that significantly impact the endurance of a stock in the IDX30. This enables the measurement of a stock's likelihood to remain in the IDX30 for a certain period. The method that can be used is survival analysis with the Cox Proportional Hazard (CPH) model. The advantage of the CPH model is that it does not assume a specific distribution shape for the baseline hazard, allowing the model to adapt to various risk patterns in the data. Additionally, the model can be modified to account for time-dependent covariates.. The analysis results are expected to provide insights for investors regarding the financial ratios that significantly influence the duration of a stock's presence in the IDX30. The analysis results indicate that the ROE variable and the type of sector significantly influence the survival time of stocks in the IDX30. Furthermore, an increase in ROE reduces the risk of stocks being removed from the IDX30, and all sectors have a higher risk of being excluded from the IDX30 compared to the basic materials sector

Item Type:	Thesis (Diploma)
Uncontrolled Keywords:	Cox Proportional Hazard, IDX30, Time Dependent Covariates
Subjects:	H Social Sciences > HA Statistics > HA31.3 Regression. Correlation. Logistic regression analysis. H Social Sciences > HG Finance > HG4915 Stocks--Prices Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry)
Divisions:	Faculty of Vocational > 49501-Business Statistics
Depositing User:	Putu Manik Sesa Arianthi
Date Deposited:	14 Jan 2025 04:03
Last Modified:	14 Jan 2025 04:03
URI:	http://repository.its.ac.id/id/eprint/116287

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