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"Penerapan Manajemen Risiko baik bagi institusi keuangan ataupun institusi lain dirasa semakin diperlukan. Bila pada perbankan pelaksanaanya sudah diatur secara detil dalam Basle Accord dan diawasi ketat oleh Bank Indonesia sebagai Bank Sentral Republik Indonesia. Maka bagi institusi keuangan lain seperti asuransi, hal ini belum diatur sedemikian detil. Namun untuk menjaga kesehatan suatu perusahaan asuransi. Pemerintah teiah menetapkan ketentuan ketentuan Solvabilitas Minimum (BTSM). Salah satu ketentuannya adalah menentukan pengenaan faktor risiko tertentu pada aset saham yang dimiliki. Pada tesis ini Penulis mencoba untuk mengaplikasikan penerapan manajemen risiko dengan menghitung nilai Value at Risk (VaR) dengan menggunakan dua metode yaitu metode Variance Covariance dan metode Historical Simulation kemudian membandingkan dengan faktor risiko yang ditetapkan oleh Pemerintah dalam ketentuan BTSM tersebut. Hasilnya menemukan bahwa nilai VaR yang dihasi1kan dengan menggunakan metode historical simulation tidak valid dan Penulis menyarankan untuk menggunakan metode Variance Covariance sebagai metode dalam pengambilan keputusan investasi. Sedangkan BTSM dapat dilakukan untuk mengalokasikan modal.

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Applying risk management to financial institution or any other institutions is increasingly necessary. While the implementation of risk management in banking had been arranged in detail by Basle Accord and strictly supervised by Bank of Indonesia as a central bank of Republic of Indonesia, not in other financial institution like insurance. For an insurance institution to be solvency, government has carried out the regulation by stipulating The Minimum Solvability Rate Limit. One of those stipulations is to put risk factor as a subject in the share asset possession.

In this thesis, the Writer try to applicate the implementation of risk management by calculating value at risk (VaR) using two method Variance Covariance and Historical Simulation then compare it to risk factor determined in The Minimum Solvability Rate Limit. As the result is value at risk (VaR) using historical simulation is not valid, while only the variance covariance method is. So the Writer recommended to use variance covariance method to be used in taking investment decision and use The Minimum Solvability Rate Limit for a capital allocation."

"ContentsForeword -- Preface -- Acknowledgments -- Introduction -- Institutional background -- Operational risk -- Financial disasters -- The systemic disaster of 2007-2008 -- Managing financial risk -- VaR and stress testing -- Model risk -- Managing spot risk -- Managing forward risk -- Managing vanilla options risk -- Managing exotic options risk -- Credit risk -- Counterparty credit risk -- Bibliography -- About the companion website -- Index."

"Managing financial risks comes down to understanding how to reduce a complex business environment into workable concepts and models. "The AMA Handbook of Financial Risk Management" provides readers with the tools they need for dealing with the most important areas of financial decision making. Filled with strategies, principles, and measurement techniques, the book shows readers how to: categorize financial risks; reduce risks from cash flow and budget exposures; analyze operating risks; understand assessments or risk and return; and, manage risks in capital investment decisions. Providing both explanations and practical applications, the book clarifies the factors that affect the value of a firm, considerations such as time and the proper use of debt, and risks inherent in the capital structure of the firm and the valuation of business combinations. This is a comprehensive guide that enables risk managers and anyone involved in the financial management of an organization to know what factors are at stake and how to protect their bottom line.;"

"Risk Management and Financial Institutions explains all aspects of financial risk and financial institution regulation, helping readers better understand the financial markets and potential dangers. This new fourth edition has been updated to reflect the major developments in the industry, including the finalization of Basel III, the fundamental review of the trading book, SEFs, CCPs, and the new rules affecting derivatives markets. There are new chapters on enterprise risk management and scenario analysis. Readers learn the different types of risk, how and where they appear in different types of institutions, and how the regulatory structure of each institution affects risk management practices. Comprehensive ancillary materials include software, practice questions, and all necessary teaching supplements, facilitating more complete understanding and providing an ultimate learning resource."

"Salah satu alat ukur risiko yang memiliki peran penting dalam manajemen portofolio adalah Value-at-Risk VaR . VaR didefinisikan sebagai jumlah kerugian portofolio yang mungkin terjadi dengan tingkat kepercayaan yang tinggi, selama periode waktu tertentu. Secara matematis, VaR adalah persentil dari distribusi loss. Secara umum, return pergerakan harga saham dimodelkan dengan gerak Brown. Sementara itu, distribusi loss dari instrumen keuangan lebih berisfat leptokurtic dari distribusi normal dan cenderung memiliki fat tails . Oleh karena itu, karakteristik dari distribusi loss tersebut tidak memenuhi asumsi distribusi normal. Dengan demikian, proses Variance Gamma VG adalah proses stokastik alternatif untuk mendeskripsikan model dari distribusi return harga saham. Proses VG didefinisikan sebagai gerak Brown dengan perubahan waktu acak mengikuti proses Gamma. Pada penerapannya dalam pasar modal, perhitungan VaR akan dilakukan pada Indeks Harga Saham Gabungan Indonesia IHSG .

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One of the measures of risk which has an important role in managing portfolio is Value at Risk VaR . VaR is defined as the amount of possible portfolio losses with a high level of certainty, over a specific time frame. From statistical point of view, VaR is the percentile of the loss distribution. In general, return of the stock prices is modeled with Brownian motion. Meanwhile, return distributions of financial instruments are more leptokurtic than normal distribution and tend to have the fat tails . Therefore, these characteristics of return distributions are countering the normality assumption. Accordingly, a Variance Gamma VG process is an alternative stochastic process to describe the model for the return distribution of stock prices. This process is defined as Brownian motion with random time change following gamma process. On purpose of risk management application, the calculation of VaR will be carried out by using Indonesia Composite Index IDX . "

"Dalam rangka mewujudkan sistem pembayaran yang efisien, cepat, aman dan handal, Bank Indonesia selaku Bank Sentral telah menerapkan sistem pembayaran berupa Real-Time Gross Settlement (RTGS). Sistem ini telah diterapkan hampir disebagian besar wilayah Asia Pasifik yang meliputi Hong Kong, Korea, Australia, China, New Zealand, dan Thailand. Di Indonesia sistem ini dikenal dengan sebutan BI-RTGS.Selain sistem BI-RTGS, Bank Indonesia juga memberikan sistem pembayaran nasional berupa Sistem Kliring Nasional Bank Indonesia (SKNBI). Diharapkan melalui kedua sistem tersebut akan tercipta pembayaran yang efisien, cepat, aman dan handal.Peraturan Bank Indonesia (PBI) Nomor 6/8/PBI/2004 tanggal 11 Maret 2004 tentang Sistem BI-RTGS dan PBI Nomor 7/18/PBI/2005 tanggal 22 Juli 2005 tentang SKNBI telah mengadopsi standar international business practice maupun core principle BIS. Dengan demikian Bank XYZ sebagai peserta sistem BI-RTGS dan SKNBI wajib tunduk kepada kedua PBI tersebut di atas dan sudah barang tentu menimbulkan konsekuensi yaitu timtutan agar pegawai Bank XYZ yang ditempatkan pada operasional sistem pembayaran bekerja lebih teliti, hati-hati dan seksama agar dapat meminimalkan atau meniadakan risiko yang mungkin dapat muncul dalam pelaksanaan transfer dana melalui kedua sistem dimaksud.Kesalahan pengiriman dana untuk rekening atau nama nasabah penerima yang dituju dipeserta penerima ataupun kesalahan dalam nilai nominal dan double pengiriman adalah beberapa contoh dari risiko operasional dari sisi peserta pengirim, sedangkan kesalahan dalam menentukan judgement terhadap perintah kiriman dana masuk dari peserta pengirim merupakan contoh risiko operasional dari sisi peserta penerima.Adanya kewajiban dari peserta pengirim untuk menerbitkan perintah kiriman dana baru kepada rekening yang dituju atau nasabah penenma yang benar tanpa menunggu pengembalian dana membuat pengalokasian dana cadangan untuk risiko operasional sangat penting. Besarnya alokasi dana cadangan ini harus dihitung dengan suatu metode pendekatan yang dikenal dengan sebutan Value at Risk (VaR).Pengukuran VaR untuk risiko operasional dapat dilakukan dengan beberapa metode pendekatan dan yang sederhana, sedikit komplek, dan sangat komplek. Tingkat keakuratan pengukuran terhadap aktual loss berbanding lurus dengan tingkat kompleksitas metode yang diterapkan. Adapun metode pengukuran risiko operasional dibagi menjadi 2, yaitu metode Standard dan Advanced Measurement Approach (AMA). Metode Standard terdiri dari Basic Indicator Approach (BIA), Standardized Approach (SA), Alternative Standardized Approach (ASA). Sedangkan AMA terdiri dari Internal Measurement Approach (IMA), Loss Distribution Approach (LDA), Scoreboard Approach, Bootstrapping Approach, Bayesian Method, dan Extreme Value Theory ( EVT).Metode AMA adalah metode yang dianggap menghasilkan pengukuran risiko operasional yang lebih baik yang dapat digunakan bagi perusahaan maupun perbankan dibandingkan dengan metode-metode lainnya seperti BIA, SA, ASA. Metode AMA menggunakan pendekatan internal dalam mengukur risiko operasional, sehingga metode ini terlepas dan aturan Basel.Dalam mengukur risiko operasional perusahaan, LDA mengharuskan untuk menggunakan data kerugian operasional intemal perusahaan masing-masing. Data kerugian tersebut dikelompokkan menjadi data iiekuensi kejadian dan data severitas kerugian. Dalam metode LDA, terdapat 2 cara pendekatan pengukuran yaitu dengan pendekatan actuarial method dan aggregation method. Dalam penelitian ini, metode pengukuran yang digunakan adalah dengan menggunakan AMA-LDA aggregation method.Dari hasil pengukuran yang dilakukan dan setelah dilakukan uji back resting, dapat ditarik kesimpulan bahwa penerapan metode pengukuran AMA-LDA aggregation method cocok diterapkan bagi Bank XYZ untuk mengukur besamya cadangan dana yang hams disediakan akibat potensi kerugian risiko operasional dalam sistem pembayaran nasional di keempat cabang Bank XYZ.

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In order to achieve efficient, fast, secured and reliable payment system, Bank of Indonesia as the regulator has applied Real-Time Grass Settlement (RTGS) payment system. This system has been applied in most countries among Asia-Pasitic region, including Hong Kong, Korea, Australia, China, New Zealand, and Thailand. In Indonesia, this system is known as BI-RTGS.

Besides BI-RTGS system, Bank of Indonesia also provides national (domestic) payment system which is known as ?Sistem Kliring Nasional Bank Indonesia (SKNBI)? or ?National Clearing System of Bank Indonesia". By applying both systems, It is expected that we can have an efficient, quick, secured and reliable payment system.

Peraturan Bank Indonesia (PBI) or Bank of Indonesia Policies point 6/8/PBI/2004 on March 11th 2004 regarding to BI-RTGS System and PBI point 7/18/PBI/2005 on July 22nd 2005 regarding to SKNBI have adopted intemational business practice and BIS core principle standard. Thercby Bank XYZ as participant of BI-RTGS and SKNBI systems is required to obey both PBI above and get consequence, that the officers of Bank XYZ at operational payment system are required to work more accurately and carefully in order to minimize or eliminate any risks which might emerge in fund transfer involving both systems.

Mistaken account or customer name of fund recipient, mistaken nominal value and double transfer are some examples of operational risks on the side of fund sender. In the other hand, miss-judgement against incoming fund transfer order is the operational risk on the side of fund recipient.

Obligation of fund sender to issue order for new fund transfer to directed account or recipient without waiting for fund retum makes it very important to have spare fund allocation for operational risk. The amount of the spare fund has to be calculated using a method known as Value at Risk (VaR).

VaR measurement for operational risk can be performed using simple methods, slightly more complex methods or very complex methods. More complexity of the used method means higher accuracy level of the measurement against actual loss. There are two types of operational risk measurement methods: Standard and Advanced Measurement Approach (AMA). Standard method includes Basic Indicator Approach (BIA), Standardized Approach (SA), and Altemative Standardized Approach (ASA). AMA method includes Intemal Measurement Approach (IMA), Loss Distribution Approach (LDA), Scoreboard Approach, Bootstrapping Approach, Bayesian Method, and Extreme Value Theory (EVT).

AMA is a method which is considered as the one provides better operational risk measurement, that can be used in banking or other companies, compared with other methods, such as BIA, SA and ASA. AMA method uses internal approach in measuring operational risk, making this method not to depend on Basel rule.

In measuring company operational risk, usage of LDA demands intemal operational loss data of each company to be used. This loss data is grouped into occurrence frequency data and loss severity data. In LDA method, there are two methods of measurement, namely actuarial method and aggregation method. In this research, the method to be used is AMA- LDA aggregation method.

From the measurement and back testing result, we can get conclusion that applying AMA-LDA aggregation method is lit for Bank XYZ in measuring the amount of spare fund that must be provided due to potential loss of operational risk in national payment system which is used in four of its branches."

"The objective of this research is to examine maximum losses when investor invests on syariah based stock. Markowitz model is used for constructing the optimal portfolio. Value at Risk Model is also used for calculating the expected losses. The research indicates that volatility seems to cluster in a predictable fashion. Therefore the research forecasts variances used exponentially weighted moving average (EWMA) model. This research also aims to evaluate whether the EWMA model can predict variances reasonably well. The data used in this research are syariah based stock which had been included in Jakarta Islamic Index (JII) during the year 2005-2006. This research provides that VAR models using an EWMAforecast are good enough for predicting risk. The number of exception of 508 daily datas are only less than 5% or valid at confident level 95%. As benchmark we also use historical method and monte carlo simulation to compare performance of EWMA forecast."

"ABSTRAKDKI Jakarta merupakan pasar yang membuka peluang bisnis yang sangat besar bagi industri jasa yang menawarkan layanan digital bagi ibu pra, periode, dan pasca kehamilan dengan adanya 170.000 ibu hamil setiap tahunnya. Peluang bisnis itulah yang menyebabkan terciptanya ide pembuatan platform online terintegrasi berbasis website yang menyediakan berbagai macam kebutuhan seorang ibu, di antaranya informasi seputar kehamilan, layanan booking dokter secara online, dan layanan online gift registry. Akan tetapi, sebelum melakukan investasi bisnis, terlebih dahulu dibutuhkan penelitian terkait perhitungan kelayakan finansial penerapan platform tersebut. Penelitian ini menyajikan hasil perhitungan kelayakan finansial penerapan platform tersebut dengan menggunakan pendekatan Net Present Value, Internal Rate of Return, dan Payback Period. Berdasarkan hasil penelitian, diketahui bahwa penerapan platform ini akan menghasilkan nilai Net Present Value sebesar Rp 48.342.103.113, Internal Rate of Return sebesar 44%, dan Payback Period selama 7 tahun sehingga bisnis ini dapat dinyatakan layak untuk dijalankan. Selain itu, di akhir penelitian juga dilakukan analisis sensitivitas dari model kelayakan finansial dimana ditemukan bahwa variabel yang paling berpengaruh terhadap hasil akhir kelayakan finansial adalah variabel inflasi gaji, discount rate, dan pendapatan tahunan.

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ABSTRACTWith an average number of 170,000 pregnant women annually, Jakarta opens huge business opportunities for service industries that offer digital services for mothers in maternity period. That opportunity brings out the creation of the idea of an integrated online website that provides a wide range of needs of a mother, including information regarding pregnancy, doctors? online booking service, and a baby gift registry service. However, before making a decision to make an investment to such business, it is required to calculate the financial feasibility study related to the implementation of the platform. This study presents the results of the calculation of the financial feasibility of the implementation of the platform by using the approach of several feasibility study methods such as Net Present Value, Internal Rate of Return and Payback Period. After the research has been conducted and findings are generated, it is known that the implementation of this platform will yield a Net Present Value of Rp 48,342,103,113, an Internal Rate of Return of 44%, and 7 years worth of Payback Period, which resulted in a conclusion that the investment is feasible to run. In addition, at the end of the study, sensitivity analysis of the financial model is also conducted in which three variables that have the most influence on the final value of the financial feasibility of the platform are known. Those sensitive variables are wage inflation rate, discount rate, and annual revenue"