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"Credit ratings merupakan salah satu faktor yang dapat mempengaruhi keputusan struktur modal perusahaan. Beberapa perusahaan dewasa ini menentukan proporsi tertentu dari struktur modal untuk mencapai suatu tingkat rating. Penelitian ini ingin membuktikan apakah perusahaan-perusahaan non-keuangan di Indonesia memiliki tingkah laku struktur modal tertentu setelah terjadinya perubahan credit ratings. Dengan menggunakan data credit rating yang diterbitkan oleh Pefindo serta sampel seluruh perusahaan non-keuangan yang diperingkat oleh Pefindo, penelitian menyimpulkan bahwa perubahan credit rating belum menjadi faktor yang dipertimbangkan perusahaan dalam keputusan struktur modal. Penelitian membuktikan bahwa perusahaan-perusahaan non-keuangan di Indonesia belum menargetkan tingkat minimum credit rating dalam membuat keputusan struktur modal.

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Credit ratings is one of the key factors that could affect a firm?s capital structure decision. Some of the firms nowadays decide on a certain capital structure proportion to achieve their rating target. This research tries to see whether nonfinancial firms' capital structure decision in Indonesia behave accordingly to changes in credit ratings. Using credit ratings published by Pefindo and a sample of all non-financial firms rated by Pefindo, this research concludes that changes in credit ratings are still not considered as one of the factors for capital structure decision. This research shows that non-financial firms in Indonesia does not use a minimum credit ratings target for capital structure decision making."

"Tujuan penelitian ini adalah untuk menentukan matriks perubahan probabilitas transisi rating kredit dengan mempertimbangkan perubahan faktor makro, yaitu: tingkat inflasi, nilai tukar rupiah terhadap USD, dan tingkat suku bunga SBI yang secara signifikan mempengaruhinya, serta menentukan keakuratan metode Macro Simulation Approach dengan backtesting dan Kupiec Test. Unit analisis dalam penelitian ini adalah seluruh debitur kredit korporasi PT Bank BHS selama kurun waktu Oktober 2005 ? Agustus 2008.Setelah dilakukan penelitian, disimpulkan bahwa perubahan probabilitas transisi rating kredit dengan mempertimbangkan perubahan faktor makro dapat ditentukan melalui matriks conditional. Matriks transisi conditional menunjukkan probabilitas terjadinya transisi kredit dari rating awal menjadi rating akhir sebagai akibat pengaruh faktor makro. Pendekatan Macro Simulation Approach menunjukkan bahwa tidak semua perubahan probabilitas transisi rating kredit dipengaruhi oleh faktor makro. Faktor makro yang mempengaruhi secara signifikan antara lain yaitu:1. Tingkat inflasi mempengaruhi perubahan probabilitas transisi rating A+ menjadi BB+ dan kestabilan rating AA, AA-, BBB+, serta BB-.2. Nilai tukar rupiah terhadap USD mempengaruhi perubahan probabilitas transisi rating A menjadi AA+, rating BBB menjadi BBB-, dan kestabilan rating BBB+.3. Tingkat suku bunga SBI mempengaruhi perubahan probabilitas transisi rating A+ menjadi BB+ dan kestabilan rating AA-, BBB+, serta BB-.Berdasarkan hasil backtesting dengan tingkat keyakinan 95% dapat disimpulkan bahwa Macro Simulation Approach sebagai metode dalam mengestimasi faktorfaktor makro yang mempengaruhi perubahan probabilitas transisi rating kredit PT. Bank BHS cukup akurat. Sedangkan berdasarkan perhitungan Kupiec Test, diperoleh nilai Likelihood Ratio sebesar 3.7353 dan nilai Chi-square sebesar 3.8415. Angka Likelihood Ratio yang lebih kecil dibandingkan Chi-square menunjukkan bahwa model persamaan regresi dimana probabilitas transisi rating sebagai variabel dependen dan faktor makro sebagai variabel independen cukup akurat. Dengan demikian, dapat disimpulkan bahwa metode Macro Simulation Approach cukup akurat untuk memprediksi perubahan probabilitas transisi rating kredit PT. Bank BHS.

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The purpose of the research is to define the changes matrix of credit ratings transition probability by taking into accounts the following macro factor changes: inflation rates, IDR/USD exchange rates, and the SBI rates, each of which play significant role, and to measure the accuracy of the Macro Simulation Approach through means of Backtesting and Kupiec Test. The analytical units used in the research are the entire corporate credit debtors of PT Bank BHS during Oktober 2005 - Agustus 2008.Having conducted the research, it is concluded that the changes in credit ratings transition probability in consideration with macro factor changes can be measured by conditional matrix. The conditional transitional matrix demonstrated that the probability of transition from early rating into final rating is affected by changes in macro factor. Whereas the Macro Simulation Approach showed us that not all the changes in credit ratings transition probability are affected by macro factors. While, the macro factors affecting significantly are:1. Inflation rates influenced the changes in probability of transition from A+ ratings to BB+ ratings and the stability of AA, AA-, BBB-, and BB- ratings.2. IDR/USD exchange rates influenced the changes in probability of transition from A ratings to AA+ ratings, BBB ratings to BBB-, and the stability of BBB+ ratings.3. SBI rates influenced the changes in probability of transition from A+ ratings to BB+ ratings and the stability of AA-, BBB+, and BB- ratings.Based on the results of the backtesting with 95% confidence level, it is concluded that the Macro Simulation Approach as the method used to estimate the macro factors affecting the changes in probability of PT BHS? credit ratings transition is considerably accurate. Meanwhile, through Kupiec Test, a Likelihood Ratio of 3.7353 and a Chi-square of 3.8415 is achieved. Smaller Likelihood Ratio as compared to Chi-square implies a regression equation model of which the ratings transition probability as dependent variable and macro factors as independent variables are considerably accurate. As such, it is concluded the Macro Simulation Approach is considerably accurate to predict the changes in PT BHS? credit ratings transition probability."

"ABSTRACTThis study investigates whether a change in credit ratings lead to a change in daily excess stock returns. The sample includes daily stock price data for US firms listed on the Standard & Poors 500 from January 2006 to December 2015. Firms excess stock returns are compared with the market in a 14-day window around credit rating downgrades and upgrades. Our results are asymmetric, that is, there is a significant reaction to credit ratings downgrades but not to upgrades. In addition, we report weak evidence of upgrades in credit ratings since the 2008 global credit crisis leading to significant changes in security prices."