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Abstrak :
[ABSTRAK
Tesis ini membahas mengenai pengukuran kontribusi risiko sistemik dan hubungannya dengan karakteristik individu bank pada perbankan Indonesia dengan periode pengamatan dari 2003 s.d 2013.Metode yang digunakan untuk mengukur kontribusi risiko sistemik adalah CoVaR (Girardi dan Ergun, 2013) dan MES (Acharya, 2010). CoVaR digunakan untuk melihat kontribusi risiko sistemik masing-masing bank terhadap sistem keuangan apabila bank mengalami distress sedangkan MES digunakan untuk melihat bagaimana kontribusi risiko sistemik masing-masing bank apabila sistem keuangan mengalami distress. Dari hasil pengukuran ditemukan bank yang memiliki nilai Delta CoVaR terbesar adalah BMRI, BBRI, BBCA dan BBNI.Ke 4 (empat) bank tersebut merupakan bank terbesar di Indonesia. Hal ini menunjukan bahwa bank yang akan memberikant kontribusi risiko kepada sistem sebesar nilai Delta CoVaR nya saat bank mengalami distress. Sebaliknya dari hasil pengukuran MES diketahui bahwa bank yang akan memberikan kontribusi risiko sistemik terbesar saat sistem mengalami distress adalah BBRI. Hasil penelitian menunjukan bahwa karakteristik individu bank seperti ukuran bank dan VaR memiliki pengaruh yang signifikan terhadap besar kontribusi risiko sistemik bank di Indonesia. Kondisi makroekonomi seperti inflasi secara signifikan mempengaruhi nilai kontribusi risiko sistemik dari masingmasing bank di Indonesia.

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ABSTRACT
This thesis discusses the contribution of systemic risk and its relationship with the individual characteristics of banks in the Indonesian banking with the observation period from 2003 until 2013. The method used to measure systemic risk contribution is CoVaR (Girardi and Ergun, 2013) and MES (Acharya, 2010). CoVaR looks ay the returns of the financial system when an institution is in financial distress while MES looks at the returns of an institution when the financial system is in distress. From the results of measurements we found that the bank has the largest value of Delta CoVaR areBMRI , BBRI , BBCA and BBNI . All of the bank are the largest bank in Indonesia. This shows that the bank will contribute to the system at its current value of Delta CoVaR bankswhile experiencing distress. On the other hand, the result measurement of the MES is that BBRI will provide the largest contribution to systemic risk when the system it experiencing distress.The results showed that individual characteristics such as bank size and VaR has a significant effect on the bank contribution to systemic risk in Indonesia. Macroeconomic conditions such as inflation significantly affect the value of systemic risk contribution of each bank in Indonesia.;This thesis discusses the contribution of systemic risk and its relationship with the individual characteristics of banks in the Indonesian banking with the observation period from 2003 until 2013. The method used to measure systemic risk contribution is CoVaR (Girardi and Ergun, 2013) and MES (Acharya, 2010). CoVaR looks ay the returns of the financial system when an institution is in financial distress while MES looks at the returns of an institution when the financial system is in distress. From the results of measurements we found that the bank has the largest value of Delta CoVaR areBMRI , BBRI , BBCA and BBNI . All of the bank are the largest bank in Indonesia. This shows that the bank will contribute to the system at its current value of Delta CoVaR bankswhile experiencing distress. On the other hand, the result measurement of the MES is that BBRI will provide the largest contribution to systemic risk when the system it experiencing distress.The results showed that individual characteristics such as bank size and VaR has a significant effect on the bank contribution to systemic risk in Indonesia. Macroeconomic conditions such as inflation significantly affect the value of systemic risk contribution of each bank in Indonesia., This thesis discusses the contribution of systemic risk and its relationship with the individual characteristics of banks in the Indonesian banking with the observation period from 2003 until 2013. The method used to measure systemic risk contribution is CoVaR (Girardi and Ergun, 2013) and MES (Acharya, 2010). CoVaR looks ay the returns of the financial system when an institution is in financial distress while MES looks at the returns of an institution when the financial system is in distress. From the results of measurements we found that the bank has the largest value of Delta CoVaR areBMRI , BBRI , BBCA and BBNI . All of the bank are the largest bank in Indonesia. This shows that the bank will contribute to the system at its current value of Delta CoVaR bankswhile experiencing distress. On the other hand, the result measurement of the MES is that BBRI will provide the largest contribution to systemic risk when the system it experiencing distress.The results showed that individual characteristics such as bank size and VaR has a significant effect on the bank contribution to systemic risk in Indonesia. Macroeconomic conditions such as inflation significantly affect the value of systemic risk contribution of each bank in Indonesia.]

Abstrak :
Tujuan dari penelitian ini adalah untuk menganalisis peringkat risiko sistemik dari enam metodologi pengukuran risiko sistemik yang dikenal serta mengembangkan peringkat risiko sistemik komposit menggunakan metode Principal Component Analysis (PCA), mengacu pada Nucera et al. (2016). Systemically Important Financial Institutions (SIFIs) didefinisikan sebagai 10 perusahaan yang memiliki risiko sistemik tertinggi dalam setiap pemeringkatan dari total sampel 60 lembaga keuangan yang go public selama periode 2008-2016. Dari hasil studi, peringkat komposit yang kami kembangkan lebih konsisten dalam menjelaskan komposisi SIFIs dari kebanyakan pemeringkatan risiko sistemik individu lainnya. Dari hasil PCA, ditemukan bahwa peringkat komposit yang kami hasilkan terutama dijelaskan oleh metode pemeringkatan berbasis data pasar. Lebih lanjut, kami menemukan perbedaan yang substantial antara pemeringkatan berbasis data pasar dan pemeringkatan berbasis data fundamental dalam menjelaskan peringkat risiko komposit. Oleh karena itu, dapat diduga bahwa peringkat risiko sistemik komposit, yang menggabungkan aspek pasar dan fundamental, akan memberikan informasi yang lebih lengkap bagi pengambil kebijakan dalam membuat keputusan di masa depan. ...... The aim of this study is to incorporate systemic risk ranking from six generally accepted metrics and develop a single composite ranking using Principle Component Analysis, based on Nucera et al. (2016). We analyze the Systemically Important Financial Institutions (SIFIs) to gather information difference between systemic risk metrics. We identify SIFIs as the top 10 companies in each systemic risk metrics ranking, using a sample of 60 listed financial institutions in Indonesia over the period 2008-2016. We find that our single composite ranking is more consistent in term of SIFIs composition than most individual risk rankings. Furthermore, according to factor loadings of the first component, our single composite ranking is mainly based on market-based instead of fundamental. Based on second factor loading, we find that market-based metrics and fundamental-based metrics deviated substantially in constructing our composite ranking. Therefore, we suspect that our single composite ranking, that combines both market and fundamental aspect, will provide better insight for the regulator to make a decision.