The Experts below are selected from a list of 153 Experts worldwide ranked by ideXlab platform
Andre A Monteiro - One of the best experts on this subject based on the ideXlab platform.
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the multi state latent Factor Intensity model for credit rating transitions
Journal of Econometrics, 2008Co-Authors: Siem Jan Koopman, Andre Lucas, Andre A MonteiroAbstract:A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric Intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic Factors. The model has a generalized semi-Markov structure designed to accommodate many of the stylized facts of credit rating migrations. Parameter estimation is based on Monte Carlo maximum likelihood methods for which the details are discussed in this paper. A simulation experiment is carried out to show the effectiveness of the estimation procedure. An empirical application is presented for transitions in a 7 grade rating system. The model includes a common dynamic component that can be interpreted as the credit cycle. Asymmetric effects of this cycle across rating grades and additional semi-Markov dynamics are found to be statistically significant. Finally, we investigate whether the common Factor model suffices to capture systematic risk in rating transition data by introducing multiple Factors in the model. This discussion paper has resulted in a publication in the Journal of Econometrics , 142(1), 399-424.
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the multi state latent Factor Intensity model for credit rating transitions
Journal of Econometrics, 2008Co-Authors: Siem Jan Koopman, Andre Lucas, Andre A MonteiroAbstract:A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric Intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic Factors. The model has a generalized semi-Markov structure designed to accommodate many of the stylized facts of credit rating migrations. Parameter estimation is based on Monte Carlo maximum likelihood methods for which the details are discussed in this paper. A simulation experiment is carried out to show the effectiveness of the estimation procedure. An empirical application is presented for transitions in a 7 grade rating system. The model includes a common dynamic component that can be interpreted as the credit cycle. Asymmetric effects of this cycle across rating grades and additional semi-Markov dynamics are found to be statistically significant. Finally, we investigate whether the common Factor model suffices to capture systematic risk in rating transition data by introducing multiple Factors in the model.
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the multi state latent Factor Intensity model for credit rating transitions
Social Science Research Network, 2005Co-Authors: Siem Jan Koopman, Andre Lucas, Andre A MonteiroAbstract:A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric Intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic Factors. The model has a generalized semi-Markov structure designed to accommodate many of the stylized facts of credit rating migrations. Parameter estimation is based on Monte Carlo maximum likelihood methods for which the details are discussed in this paper. A simulation experiment is carried out to show the effectiveness of the estimation procedure. An empirical application is presented for transitions between investment grade, subinvestment grade, and default ratings for U.S. corporates. The model strongly suggests the presence of a common dynamic component that can be interpreted as the credit cycle. We also show that the impact of this credit cycle is asymmetric with respect to downgrade and upgrade probabilities.
Siem Jan Koopman - One of the best experts on this subject based on the ideXlab platform.
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the multi state latent Factor Intensity model for credit rating transitions
Journal of Econometrics, 2008Co-Authors: Siem Jan Koopman, Andre Lucas, Andre A MonteiroAbstract:A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric Intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic Factors. The model has a generalized semi-Markov structure designed to accommodate many of the stylized facts of credit rating migrations. Parameter estimation is based on Monte Carlo maximum likelihood methods for which the details are discussed in this paper. A simulation experiment is carried out to show the effectiveness of the estimation procedure. An empirical application is presented for transitions in a 7 grade rating system. The model includes a common dynamic component that can be interpreted as the credit cycle. Asymmetric effects of this cycle across rating grades and additional semi-Markov dynamics are found to be statistically significant. Finally, we investigate whether the common Factor model suffices to capture systematic risk in rating transition data by introducing multiple Factors in the model. This discussion paper has resulted in a publication in the Journal of Econometrics , 142(1), 399-424.
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the multi state latent Factor Intensity model for credit rating transitions
Journal of Econometrics, 2008Co-Authors: Siem Jan Koopman, Andre Lucas, Andre A MonteiroAbstract:A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric Intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic Factors. The model has a generalized semi-Markov structure designed to accommodate many of the stylized facts of credit rating migrations. Parameter estimation is based on Monte Carlo maximum likelihood methods for which the details are discussed in this paper. A simulation experiment is carried out to show the effectiveness of the estimation procedure. An empirical application is presented for transitions in a 7 grade rating system. The model includes a common dynamic component that can be interpreted as the credit cycle. Asymmetric effects of this cycle across rating grades and additional semi-Markov dynamics are found to be statistically significant. Finally, we investigate whether the common Factor model suffices to capture systematic risk in rating transition data by introducing multiple Factors in the model.
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the multi state latent Factor Intensity model for credit rating transitions
Social Science Research Network, 2005Co-Authors: Siem Jan Koopman, Andre Lucas, Andre A MonteiroAbstract:A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric Intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic Factors. The model has a generalized semi-Markov structure designed to accommodate many of the stylized facts of credit rating migrations. Parameter estimation is based on Monte Carlo maximum likelihood methods for which the details are discussed in this paper. A simulation experiment is carried out to show the effectiveness of the estimation procedure. An empirical application is presented for transitions between investment grade, subinvestment grade, and default ratings for U.S. corporates. The model strongly suggests the presence of a common dynamic component that can be interpreted as the credit cycle. We also show that the impact of this credit cycle is asymmetric with respect to downgrade and upgrade probabilities.
Andre Lucas - One of the best experts on this subject based on the ideXlab platform.
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the multi state latent Factor Intensity model for credit rating transitions
Journal of Econometrics, 2008Co-Authors: Siem Jan Koopman, Andre Lucas, Andre A MonteiroAbstract:A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric Intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic Factors. The model has a generalized semi-Markov structure designed to accommodate many of the stylized facts of credit rating migrations. Parameter estimation is based on Monte Carlo maximum likelihood methods for which the details are discussed in this paper. A simulation experiment is carried out to show the effectiveness of the estimation procedure. An empirical application is presented for transitions in a 7 grade rating system. The model includes a common dynamic component that can be interpreted as the credit cycle. Asymmetric effects of this cycle across rating grades and additional semi-Markov dynamics are found to be statistically significant. Finally, we investigate whether the common Factor model suffices to capture systematic risk in rating transition data by introducing multiple Factors in the model. This discussion paper has resulted in a publication in the Journal of Econometrics , 142(1), 399-424.
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the multi state latent Factor Intensity model for credit rating transitions
Journal of Econometrics, 2008Co-Authors: Siem Jan Koopman, Andre Lucas, Andre A MonteiroAbstract:A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric Intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic Factors. The model has a generalized semi-Markov structure designed to accommodate many of the stylized facts of credit rating migrations. Parameter estimation is based on Monte Carlo maximum likelihood methods for which the details are discussed in this paper. A simulation experiment is carried out to show the effectiveness of the estimation procedure. An empirical application is presented for transitions in a 7 grade rating system. The model includes a common dynamic component that can be interpreted as the credit cycle. Asymmetric effects of this cycle across rating grades and additional semi-Markov dynamics are found to be statistically significant. Finally, we investigate whether the common Factor model suffices to capture systematic risk in rating transition data by introducing multiple Factors in the model.
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the multi state latent Factor Intensity model for credit rating transitions
Social Science Research Network, 2005Co-Authors: Siem Jan Koopman, Andre Lucas, Andre A MonteiroAbstract:A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric Intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic Factors. The model has a generalized semi-Markov structure designed to accommodate many of the stylized facts of credit rating migrations. Parameter estimation is based on Monte Carlo maximum likelihood methods for which the details are discussed in this paper. A simulation experiment is carried out to show the effectiveness of the estimation procedure. An empirical application is presented for transitions between investment grade, subinvestment grade, and default ratings for U.S. corporates. The model strongly suggests the presence of a common dynamic component that can be interpreted as the credit cycle. We also show that the impact of this credit cycle is asymmetric with respect to downgrade and upgrade probabilities.
Kevin T Duffydeno - One of the best experts on this subject based on the ideXlab platform.
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public capital and the Factor Intensity of the manufacturing sector
Urban Studies, 1991Co-Authors: Kevin T DuffydenoAbstract:Numerous studies have examined the effect of local fiscal policy on business activity. Few have emphasised local public services and fewer still have examined the effect of local fiscal policy on the composition of business activity. Using newly derived estimates of regional public infrastructure, the effect of public capital on the Factor Intensity of the manufacturing sector of 36 SMSAs during the 1970-78 period is examined. The findings of this study indicate that public investment can play an important role in determining the composition of a region's industrial sector.
Fatimah, Jeanny Maria - One of the best experts on this subject based on the ideXlab platform.
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PENGENDALIAN PERILAKU EMOSIONAL ANAK TK MELALUI KOMUNIKASI ANTARA GURU DENGAN ORANG TUA DI KEC. BIRINGKANAYA KOTA MAKASSAR
'Fakultas Ilmu Sosial dan Ilmu Politik Universitas Hasanuddin', 2016Co-Authors: Ashary Yuniartanty, Fatimah, Jeanny MariaAbstract:Abstract This study aims to determine (a) to describe emotional behavior of kindergarten children in the district. Biringkanaya Makassar, (b) to describe communication between teachers and parents of kindergarten children in the district. Biringkanaya Makassar and (c) to determine control of the emotional behavior of kindergartners through communication between teachers and parents In the district Biringkanaya Makassar.This study is an ex- post-facto quantitative, where the population is around the kindergarten students in the district. Biringkanaya Makassar of 1,779 children in 79 institutions spread kindergarten in 7 (seven) wards. With the sampling method, then selected 84 children as respondents in this study. The relationship between the independent variables were analyzed by using Simple Linear Regression Analysis. The results showed that (a) the child's emotional behavior of the most prominent forms of aggressiveness is tempered (80,36%), anxiety is crying (48,21%), withdrawal is not much to say (48,21%) as well as excessive fear is the fear of meeting a stranger (36,31%) (b) communication media is most often used in solving problems of emotional behavior children are face to face, and (c) intensive communication negatively correlated with children's emotional behavior, which means more intensive communication, the more reduced (controlled) the child's emotional behavior. Approximately 32.8% of control children's emotional behavior is caused by Factor Intensity of communication between teachers and parents to discuss the child's emotional behavior problems in kindergarten Biringkanaya MakassarAbstrak Penelitian ini bertujuan untuk (a) mengetahui gambaran perilaku emosional anak TK di Kec. Biringkanaya Kota Makassar, (b) mengetahui gambaran komunikasi antara guru dengan orang tua anak TK di Kec. Biringkanaya Kota Makassar dan (c) mengetahui pengendalian perilaku emosional anak TK melalui komunikasi antara guru dengan orang tua di Kecamatan Biringkanaya Kota Makassar. Penelitian ini merupakan eks-post-fakto yang kuantitatif. Populasinya adalah seluruh murid TK di Kecamatan Biringkanaya Kota Makassar sebesar 1.779 anak yang menyebar pada 79 lembaga TK di 7 (tujuh) kelurahan. Sampel penelitian ini 84 orang anak sebagai responden. Hubungan antara variabel bebas dianalisis dengan menggunakan Analisis Regresi Linier Sederhana. Hasil penelitian menunjukkan bahwa (a) perilaku emosional anak bentuk agresivitas yang paling menonjol adalah marah (80,36%) , kecemasan adalah menangis (48,21%), menarik diri adalah tidak banyak bicara (48,21%) serta takut berlebihan adalah takut bertemu orang asing (36,31%) (b) media komunikasi yang paling sering digunakan dalam menyelesaikan permasalahan perilaku emosional anak adalah tatap muka serta (c) intensif komunikasi berkorelasi negatif dengan perilaku emosional anak, yang artinya semakin intensif komunikasi , maka semakin berkurang (terkendali) perilaku emosional anak. Sekitar 32,8% pengendalian perilaku emosional anak disebabkan oleh faktor intensitas komunikasi antara guru dengan orang tua dalam membicarakan permasalahan perilaku emosional anak di TK Biringkanaya Kota Makassar.
