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"Penelitian ini menggunakan Data Envelopment Analysis (DEA) untuk memfasilitasi proses optimasi portofolio Black-Litterman (BL). DEA menghasilkan estimasi imbal hasil berdasarkan pada efficient frontier multi variabel yang dibentuk untuk setiap aset. Penelitian ini menggunakan dua komponen sebagai input dalam DEA: CVaR dan ukuran likuiditas LMX. Memakai implied excess return hasil proses reverse optimization BL sebagai output, model menghasilkan estimasi imbal hasil untuk setiap aset, yang berfungsi sebagai view dalam pembentukan portofolio posterior BL. Penggunaan BL akan memastikan proses optimasi portofolio posterior yang mean-variance efficient.Hasil penelitian menunjukkan bahwa DEA dapat digunakan sebagai metode untuk merumuskan view yang kompatibel dengan prior distribution BL. Studi lebih lanjut dapat ditempuh untuk menemukan kombinasi indikator input-output DEA yang lebih baik sekaligus memperhatikan karakter efficient frontier DEA. Pengembangan model lebih lanjut dapat pula dilakukan untuk memasukkan berbagai aspek kompleksitas pasar ataupun berbagai variabel yang mencerminkan informasi yang tak terduga.

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This study employs Data Envelopment Analysis (DEA) to facilitate the Black-Litterman (BL) optimization process. DEA generates expected return estimation based on multi variables efficient frontier that can be formed flexibly for each asset. This study employs two components as inputs in DEA: CVaR and LMx measure of liquidity. Based on the implied excess return indicated by BL reverse optimization process as an output, the model produces return estimation for each asset, which serves as views in BL posterior portfolio. The use of BL will ensure the posterior portfolio optimization process in accordance with mean-variance efficient condition.The results indicate that DEA may be used as a method to formulate view that is compatible with BL prior distribution. Future studies using DEA should attempt to find better combination of Input-Output indicators and also pay attention to the character of DEA efficient frontier. Further model development should consider market complexity in mean-variance optimization setup, or to combine a variety of variables reflecting unanticipated information."

"Performance gap in business management practices in Indonesia comparing to global rivals is caused by "structural problem". Indonesia environment is not "conductive" for business activities. This fact can be seen in annual research reports by World Bank through its affiliation company (International Finance Corp) with grand themes "Doing Business". In that report, Indonesia have low rank in many aspects that support "business-friendly environment". This paper tried to describe that without proper handling in its structural problems, there will be difficult for Indonesian businessman/woman to "closing the performance gap" with global rivals. This paper will describe some experience in other countries that facing 'gap' in business management practices because of the same problem like Indonesia and this paper also discussed some alternatives strategy for government as regulator, especially to handle this problem."