Full Description
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Physical Description | xiv, 104 hlm. : ill. ; 29 cm. |
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Holding Institution | Universitas Indonesia |
Location | Perpustakaan UI, Lantai 3 |
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Call Number | Barcode Number | Availability |
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S62334 | 14-19-322011778 | TERSEDIA |
No review available for this collection: 20422553 |
Abstract
Tujuan dari penelitian ini adalah untuk mengukur risiko sistemik pada dengan sebuah metode yang mampu menghitung prediksi kerugian modal pada bank ketika pasar sedang jatuh, yaitu Marginal Expected Shortfall (MES). Di mana bank yang mengalami kerugian modal akan menghadapi permasalahan keuangan, yang dikhawatirkan dapat menular pada bank dan perusahaan keuangan lainnya, hingga sistem keuangan secara keseluruhan. MES yang digunakan pada penelitian ini adalah metode yang diajukan oleh Brownlees dan Engle (2012) untuk bank-bank yang terdaftar di bursa efek Indonesia pada periode 2009 hingga 2013. Kemudian, penelitian ini dilanjutkan dengan mencari tahu faktor-faktor neraca apa saja yang mempengaruhi MES sebagai ukuran dari risiko sistemik. Adapun variabel kontrol yang mempengaruhi MES sebagai risiko sistemik adalah non-performing loan, ukuran bank, dan tingkat diversifikasi pinjaman.
The aim of this study was to measure systemic risk using Marginal Expected Shortfall (MES), a method that is capable of calculating expected equity loss on banks when the market itself in left tail. Capital shortage suffered by the bank makes it facing financial distress, which it feared may affect the other banks and financial companies, until a whole financial system. MES used in this study is the method proposed by Brownlees and Engle (2012) with the sample of Indonesian banks listed on IDX for the period 2009 to 2013. Then, this research followed by knowing the balance sheet factors that influence the MES as a measure of systemic risk. Control variables which can influence MES value are non-performing loan, size, and loans diversification.
The aim of this study was to measure systemic risk using Marginal Expected Shortfall (MES), a method that is capable of calculating expected equity loss on banks when the market itself in left tail. Capital shortage suffered by the bank makes it facing financial distress, which it feared may affect the other banks and financial companies, until a whole financial system. MES used in this study is the method proposed by Brownlees and Engle (2012) with the sample of Indonesian banks listed on IDX for the period 2009 to 2013. Then, this research followed by knowing the balance sheet factors that influence the MES as a measure of systemic risk. Control variables which can influence MES value are non-performing loan, size, and loans diversification.