Insurance Portfolio Risk Aggregation - A Practitioner's View

Amid instability of financial markets and macroeconomic situation the necessity of improving bank risk-management instrument arises. New economic reality defines the need for searching for more advanced approaches of estimating banks vulnerability to exceptional, but plausible events. Stress-testing belongs to such instruments. The paper reviews and compares the models of market risk stress-testing of the portfolio of different financial instruments. These days the topic of the paper is highly acute due to the fact that now stress-testing is becoming an integral part of anticrisis risk-management amid macroeconomic instability and appearance of new risks together with close interest to the problem of risk-aggregation. The paper outlines the notion of stress-testing and gives coverage of goals, functions of stress-tests and main criteria for market risk stress-testing classification. The paper also stresses special aspects of scenario analysis. Novelty of the research is explained by elaborating the programme of aggregated complex multifactor stress-testing of the portfolio risk based on scenario analysis. The paper highlights modern Russian and foreign models of stress-testing both on solo-basis and complex. The paper lays emphasis on the results of stress-testing and revaluations of positions for all three complex models: methodology of the Central Bank of stress-testing portfolio risk, model relying on correlations analysis and copula model. The models of stress-testing on solo-basis are different for each financial instrument. Parametric StressVaR model is applicable to shares and options stress-testing;model based on "Grek" indicators is used for options; for euroobligation regional factor model is used. Finally some theoretical recommendations about managing market risk of the portfolio are given.

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Insurance Portfolio Risk Retention

North American Actuarial Journal ◽

10.1080/10920277.2017.1317272 ◽

2017 ◽

Vol 21 (4) ◽

pp. 526-551 ◽

Cited By ~ 2

Author(s):

Edward Frees

Keyword(s):

Portfolio Risk ◽

Insurance Portfolio ◽

Risk Retention

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Managing Portfolio Risk with Credit Derivatives

AIMR Conference Proceedings ◽

10.2469/cp.v2005.n1.3458 ◽

2005 ◽

Vol 2005 (1) ◽

pp. 78-84

Author(s):

Marc P. Seidner

Keyword(s):

Credit Derivatives ◽

Portfolio Risk

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Rethinking Portfolio Risk in Asset Management

CFA Digest ◽

10.2469/dig.v43.n2.46 ◽

2013 ◽

Vol 43 (2) ◽

pp. 138-139

Author(s):

Vipul K. Bansal

Keyword(s):

Asset Management ◽

Portfolio Risk

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ANALISIS PORTOFOLIO INVESTASI PADA SAHAM LQ45 DENGAN METODE MEAN VARIAN SATU KONSTRAIN

Jurnal Varian ◽

10.30812/varian.v1i2.68 ◽

2018 ◽

Vol 1 (2) ◽

pp. 22-29

Author(s):

Gilang Primajati

Keyword(s):

Capital Markets ◽

Minimum Variance ◽

Return Rate ◽

Optimal Portfolio ◽

Portfolio Diversification ◽

Portfolio Risk ◽

Expected Return ◽

Positive Weight ◽

The Mean

In the capital markets, especially the investment market, the establishment of a portfolio is something that must be understood by investors. Portfolio formation by investors to maximize profits as much as possible by minimizing the risk of losses that may occur. Portfolio diversification is defined as portfolio formation in such a way that it can reduce portfolio risk without sacrificing returns. Optimal portfolio with efficient-portfolio mean criteria, investors only invest in risk assets only. Investors do not include risk free assets in their portfolios. The efficient variance portfolio is defined as a portfolio that has minimum variance among the overall possible portfolio that can be formed, at the same expected return rate. The mean method of one constraint variant can be used as the basis for optimal portfolio determination. The shares of LQ-45 used are shares of AALI, BBCA, UNVR, TLKM and ADHI. AALI shares received a positive weight of 7%, BBCA 48%, UNVR 16%, TLKM 26% and ADHI 3%

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ANALISIS PORTOFOLIO OPTIMAL DENGAN MENGGUNAKAN MODEL INDEKS TUNGGAL PADA SAHAM IDX BUMN20 DI BURSA EFEK INDONESIA JANUARI 2018-JANUARI 2019

JEM17: Jurnal Ekonomi Manajemen ◽

10.30996/jem17.v4i2.3023 ◽

2019 ◽

Vol 4 (2) ◽

Author(s):

Mochamad Andik Firmansyah

Keyword(s):

Stock Exchange ◽

Optimal Portfolio ◽

Rate Of Return ◽

Portfolio Risk ◽

Expected Return ◽

Purposive Sampling ◽

Single Index ◽

Index Model ◽

Market Return ◽

Single Index Model

Penelitian ini bertujuan untuk menentukan level of expected return dan the best risk of optimal portfolio formation dengan menggunakan Single Index Model pada saham IDX BUMN 20 yang tercatat di Indonesia Stock Exchange dari bulan Januari 2018 sampai January 2019. Saham IDX BUMN 20 yang tercatat di Indonesia Stock Exchange dengan populasi sebanyak 20 perusahaan. Dengan menggunakan populasi sebesar 20 perusahaan maka peneliti menggunakan purposive sampling, dan ternyata hanya 18 perusahaan saja yang ditemukan memenuhi kriteria penelitian ini. Penelitian ini juga menggunakan metode Kuantitatif Deskriptif. Analisa data pada penelitian ini untuk menentukan saham-saham mana saja yang termasuk the optimal portfolio, dan juga the level of proportion of 1 funds yang termasuk juga dalam kategori the optimal portfolio dan the level of expected return serta the best risk of the optimal portfolio yang terbentuk dengan menggunakan Single Index Model. Hasil dari penelitian ini menunjukan bahwa terdapat 5 perusahaan dengan kategori the optimal portfolio dari 18 sampel perusahaan pada saham IDX BUMN 20 dengan tingkat tertinggi dari level of proportion of 1 funds ditemukan pada PTBA share sat 1.89333 or 189,333%, di lain pihak dengan tingkat terendah adalah pada TLKM shares at -2.13488 or -213.488% yang berarti bahwa saham TLKM adalah negatif dan harus dijual dalam jangka waktu pendek sebesar 213,488% dari dana yang dimiliki oleh para inventor dan menghasilkan rate of return yang diharapkan dari formasi optimal portfolio sebesar 0.17583 or 17.583% lebih tinggi dari yang diharapkan oleh market return sebesar 0.00264 or 0.264% dan memiliki tingkat portfolio risk borne sebesar 0.10384 or 10,384%, lebih kecil dari the risk of market sebesar 0.03367 or 3,367% dan beta market sebesar 1.Kata Kunci : Portfolio, Optimal Portfolio, Single Index Model.

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