Pembentukan Portofolio Cryptocurrency Menggunakan Model Markowitz dan Evaluasi Risiko dengan Pendekatan Extreme Value Theory

Salsabila, Nisrina Aulia (2025) Pembentukan Portofolio Cryptocurrency Menggunakan Model Markowitz dan Evaluasi Risiko dengan Pendekatan Extreme Value Theory. Other thesis, Institut Teknologi Sepeuluh Nopember.

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Abstract

Perkembangan teknologi digital mempercepat adopsi aset kripto sebagai instrumen investasi berimbal hasil tinggi, namun pasar yang sangat volatil dan saling berkorelasi menjadikannya rentan terhadap risiko ekstrem. Peristiwa seperti runtuhnya Terra-Luna dan FTX menegaskan bahwa guncangan pada satu aset dapat memicu dampak sistemik. Kondisi ini menekankan pentingnya diversifikasi portofolio dan pengukuran risiko yang mampu menangkap perilaku ekor ekstrem guna menjaga stabilitas investasi. Penelitian ini bertujuan membentuk portofolio efisien menggunakan Model Markowitz serta mengukur risiko kerugian ekstrem melalui pendekatan Extreme Value Theory (EVT) berbasis Value at Risk (VaR). Data penelitian mencakup harga penutupan harian sepuluh aset kripto berkapitalisasi tertinggiperiode Januari 2022 hingga September 2025. Hasil analisis menetapkan bahwa portofolio efisien terpilih terbentuk dari komposisi Bitcoin (BTC) dengan bobot 77% dan Binance Coin (BNB) sebesar 23%. Kombinasi ini menunjukkan kinerja yang lebih baik dibandingkan strategi aset tunggal karena mampu mengurangi risiko nonsistematis melalui diversifikasi. Pengukuran risiko ekstrem menggunakan distribusi Generalized Extreme Value (GEV) menghasilkan estimasi Value at Risk (VaR) sebesar -1,32%, -1,39%, dan -1,45% pada tingkat kepercayaan 90%, 95%, dan 99%. Hasil analisis menunjukkan bahwa metode Extreme Value Theory (EVT) mampu merepresentasikan risiko ekor distribusi dengan baik. Investor disarankan memanfaatkan strategi diversifikasi portofolio yang disertai pengukuran risiko berbasis Extreme Value Theory, dengan evaluasi menggunakan periode pengamatan yang lebih panjang untuk memperoleh estimasi risiko jangka panjang yang lebih stabil.
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The development of digital technology is accelerating the adoption of crypto assets as high-yield investment instruments, but highly volatile and intercorrelated markets make them vulnerable to extreme risks. Events such as the collapse of Terra-Luna and FTX confirm that shocks to a single asset can trigger systemic impacts. This condition emphasizes the importance of portfolio diversification and risk measurement that is able to capture extreme tail behavior to maintain investment stability. This study aims to form an efficient portfolio using the Markowitz Model and measure the risk of extreme losses through the Extreme Value Theory (EVT) approach based on Value at Risk (VaR). The research data includes the daily closing prices of the ten highest-capitalized crypto assets for the period from January 2022 to September 2025. The results of the analysis determined that the selected efficient portfolio was formed from the composition of Bitcoin (BTC) with a weight of 77% and Binance Coin (BNB) with a weight of 23%. This combination shows better performance than a single asset strategy because it is able to reduce non-systematic risks through diversification. Extreme risk measurement using the Generalized Extreme Value (GEV) distribution resulted in an estimated Value at Risk (VaR) of -1.32%, -1.39%, and -1.45% at 90%, 95%, and 99% confidence levels. The results of the analysis show that the Extreme Value Theory (EVT) method is able to represent the risk of the distribution tail well. Investors are advised to utilize a portfolio diversification strategy accompanied by risk measurement based on Extreme Value Theory, with evaluation using a longer observation period to obtain a more stable long-term risk estimate.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Aset kripto, Portofolio, Model Markowitz, Value at Risk, Extreme Value Theory, Manajemen risiko,Crypto assets, Portofolio, Markowitz Model, Value at Risk, Extreme Value Theory, Risk management.
Subjects:	H Social Sciences > HG Finance > HG4012 Mathematical models H Social Sciences > HG Finance > HG4529 Investment analysis H Social Sciences > HG Finance > HG4529.5 Portfolio management H Social Sciences > HG Finance > HG8054.5 Risk (Insurance)
Divisions:	Faculty of Vocational > 49501-Business Statistics
Depositing User:	Nisrina Aulia Salsabila
Date Deposited:	14 Jan 2026 00:50
Last Modified:	14 Jan 2026 00:50
URI:	http://repository.its.ac.id/id/eprint/129173

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