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Peluang dan tantangan pasar modal Indonesia menghadapi era perdagangan bebas

The Indonesian capital market and free trade; articles.

tumbuh dan berkembang pula berbagai jenis lembaga keuangan lain seperti ,
asuransi , lembaga - lembaga pembiayaan bukan bank ( leasing , modal ventura
, anjak piutang dll ) dan pasar modal . Kegiatan intermediasi tersebut harus ...

Pasar modal Indonesia

retrospeksi lima tahun swastanisasi BEJ

Jakarta Stock Exchange under private management.

... 15,6 Sumber : Dirjen Lembaga Keuangan Depkeu Tabel 3.7 Dana yang
Dikelola oleh Dana Pensiun dan Perusahaan Asuransi ( Dalam Miliar Rupiah )
Uraian Jumlah 1 2 3 4 5 6 7 Perusahaan Asuransi Kerugian Asuransi Jiwa
Perusahaan ...

Transparency and Ambiguity in Central Bank Safety Net Operations

To mitigate the risks of contagion from problems arising in the banking sector, many countries operate some form of banking sector safety net. Such safety nets generally involve a judicious mixture of transparency and ambiguity. This ambiguity may be important to counter moral hazard effects but may lead to excessive forbearance in the face of banking problems. While the scope for ambiguity has been declining, some ambiguity in the handling of individual institutions remains. In any case, ex post transparency is essential for reviewing the propriety of any assistance and preserving the authorities’ future reputation and policy credibility.

To mitigate the risks of contagion from problems arising in the banking sector, many countries operate some form of banking sector safety net.

Analysis of Incomplete Multivariate Data

The last two decades have seen enormous developments in statistical methods for incomplete data. The EM algorithm and its extensions, multiple imputation, and Markov Chain Monte Carlo provide a set of flexible and reliable tools from inference in large classes of missing-data problems. Yet, in practical terms, those developments have had surprisingly little impact on the way most data analysts handle missing values on a routine basis. Analysis of Incomplete Multivariate Data helps bridge the gap between theory and practice, making these missing-data tools accessible to a broad audience. It presents a unified, Bayesian approach to the analysis of incomplete multivariate data, covering datasets in which the variables are continuous, categorical, or both. The focus is applied, where necessary, to help readers thoroughly understand the statistical properties of those methods, and the behavior of the accompanying algorithms. All techniques are illustrated with real data examples, with extended discussion and practical advice. All of the algorithms described in this book have been implemented by the author for general use in the statistical languages S and S Plus. The software is available free of charge on the Internet.

3.2 The EM algorithm 3.2.1 Definition EM capitalizes on the interdependence
between missing data Ymis and parameters 6. The fact that Ymis contains
information relevant to estimating 0, and 6 in turn helps us to find likely values of
Ymis, ...