ANALISIS RISIKO KREDIT ANGSURAN SISTEM FIDUSIA PADA PERUM PEGADAIAN CABANG PRAYA LOMBOK TENGAH

Penelitian ini berjudul “Analisis Risiko Kredit Angsuran Sistem Fidusia Pada PT. Pegadaian (Persero) Cabang Praya Lombok Tengah”. Tujuan Penelitian ini adalah untuk mengetahui bagaimana tingkat risiko kredit angsuran sistem fidusia yang dihadapi oleh Pegadaian Cabang Praya Lombok Tengah selama lima tahun terakhir yaitu dari tahun 2012 sampai dengan 2016.Pengumpulan data yang dilakukan adalah metode studi kasus. Jenis penelitian yang digunakan adalah penelitian deskriptif, dalam hal ini bagian yang akan dijelaskan/dideskripsikan adalah tingkat risiko kredit angsuran sistem fidusia pada Pegadaian Cabang Praya Lombok Tengah. Variabel yang yang digunakan dalam penelitian ini terdiri dari Nilai Risiko (Value at Risk/VaR), Hasil Ekspektasi (Expected Return), Risiko Kredit (Total Risk).Berdasarkan hasil analisis data dengan menggunakan VaR, maka hipotesispenelitian yang menyatakan tingkat risiko kredit angsuran sistem fidusia yang dihadapi oleh Pegadaian Cabang Praya Lombok Tengah tergolong tinggi dapat dibuktikan. Pernyataan ini didukung oleh temuan penelitian, yaitu nilai kerugian maksimum yang dihadapi Pegadaian Cabang Praya Lombok Tengah pada tahun 2016 dengan tingkat keyakinan 99 persen adalah sebesar Rp.115.317.868, dimana nilai relatifnya sebesar 14,19 persen masih lebih besar jika dibandingkan dengan annual interest sebesar 13,80 persen

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Return-Risk Evaluation of Investments

Rational Responses to Risks ◽

10.1093/oso/9780190089412.003.0008 ◽

2020 ◽

pp. 161-177

Author(s):

Paul Weirich

Keyword(s):

At Risk ◽

Probability Distribution ◽

Value At Risk ◽

Risk Evaluation ◽

Expected Return ◽

Factors Affecting ◽

Special Cases ◽

Mean Risk

In finance, a common way of evaluating an investment uses the investment’s expected return and the investment’s risk, in the sense of the investment’s volatility, or exposure to chance. A version of this method derives from a general mean-risk evaluation of acts, under the assumption that only money, risk, and their sources matter. Although the method does not require a measure of risk, finance investigates measures of risks to assist evaluations of risks. An investment creates possible returns, and the variance of the probability distribution of their utilities is a measure of the investment’s risk. This measure neglects some factors affecting an investment’s risk, and so is satisfactory only in special cases. Another measure of risk is known as value-at-risk, or VAR. It also neglects some factors affecting an investment’s risk, and so should be restricted to special cases.

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HOW TO PRICE INFORMATION BY KULLBACK-LEIBLER ENTROPY AND A MOMENT-RETURN RELATION FOR PORTFOLIOS

International Journal of Theoretical and Applied Finance ◽

10.1142/s0219024901001103 ◽

2001 ◽

Vol 04 (03) ◽

pp. 535-543

Author(s):

ANDREAS DE VRIES

Keyword(s):

At Risk ◽

Value At Risk ◽

Optimization Problem ◽

Portfolio Theory ◽

Price Information ◽

Expected Return ◽

Risk And Return ◽

Leibler Information ◽

Risk Constraint

A connection between the notion of information and the concept of risk and return in portfolio theory is deduced. This succeeds in two steps: A general moment-return relation for arbitrary assets is derived, thereafter the total expected return is connected to the Kullback-Leibler information. With this result the optimization problem to maximize the expected return of a portfolio consisting of n subportfolios by moment variation under a given value-at-risk constraint is solved. This yields an ansatz to price information.

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EFFECTS OF MULTIPLE CRITERIA ON PORTFOLIO OPTIMIZATION

International Journal of Information Technology & Decision Making ◽

10.1142/s0219622014500047 ◽

2014 ◽

Vol 13 (01) ◽

pp. 77-99 ◽

Cited By ~ 6

Author(s):

TUNCER ŞAKAR CEREN ◽

MURAT KÖKSALAN

Keyword(s):

At Risk ◽

Portfolio Optimization ◽

Decision Maker ◽

Value At Risk ◽

Efficient Frontier ◽

Conditional Value At Risk ◽

Computational Studies ◽

Expected Return ◽

Risk Criteria ◽

Return Variance

We study the effects of considering different criteria simultaneously on portfolio optimization. Using a single-period optimization setting, we use various combinations of expected return, variance, liquidity and Conditional Value at Risk criteria. With stocks from Borsa Istanbul, we make computational studies to show the effects of these criteria on objective and decision spaces. We also consider cardinality and weight constraints and study their effects on the results. In general, we observe that considering alternative criteria results in enlarged regions in the efficient frontier that may be of interest to the decision maker. We discuss the results of our experiments and provide insights.

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Optimal Reinsurance Revisited – A Geometric Approach

Astin Bulletin ◽

10.2143/ast.40.1.2049226 ◽

2010 ◽

Vol 40 (1) ◽

pp. 221-239 ◽

Cited By ~ 94

Author(s):

Ka Chun Cheung

Keyword(s):

At Risk ◽

Minimization Problem ◽

Value At Risk ◽

Geometric Approach ◽

Risk Exposure ◽

Total Risk ◽

Optimal Reinsurance ◽

Conditional Tail Expectation

AbstractIn this paper, we reexamine the two optimal reinsurance problems studied in Cai et al. (2008), in which the objectives are to find the optimal reinsurance contracts that minimize the value-at-risk (VaR) and the conditional tail expectation (CTE) of the total risk exposure under the expectation premium principle. We provide a simpler and more transparent approach to solve these problems by using intuitive geometric arguments. The usefulness of this approach is further demonstrated by solving the VaR-minimization problem when the expectation premium principle is replaced by Wang's premium principle.

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A New Portfolio Rebalancing Model with Transaction Costs

Journal of Applied Mathematics ◽

10.1155/2014/942374 ◽

2014 ◽

Vol 2014 ◽

pp. 1-7 ◽

Cited By ~ 2

Author(s):

Meihua Wang ◽

Cheng Li ◽

Honggang Xue ◽

Fengmin Xu

Keyword(s):

At Risk ◽

Transaction Costs ◽

Cost Function ◽

Transaction Cost ◽

Value At Risk ◽

Financial Data ◽

Conditional Value At Risk ◽

Expected Return ◽

Portfolio Rebalancing ◽

Proposed Model

A portfolio rebalancing model with self-finance strategy and consideration of V-shaped transaction cost is presented in this paper. Our main contribution is that a new constraint is introduced to confirm that the rebalance necessity of the existing portfolio needs to be adjusted. The constraint is constructed by considering both the transaction amount and transaction cost without any additional supply to the investment amount. The V-shaped transaction cost function is used to calculate the transaction cost of the portfolio, and conditional value at risk (CVaR) is used to measure the risk of the portfolios. Computational tests on practical financial data show that the proposed model is effective and the rebalanced portfolio increases the expected return of the portfolio and reduces the CVaR risk of the portfolio.

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Multi-stage stochastic model in portfolio selection problem

Filomat ◽

10.2298/fil1803991b ◽

2018 ◽

Vol 32 (3) ◽

pp. 991-1001

Author(s):

Shokoofeh Banihashemi ◽

Ali Azarpour ◽

Marziye Kaveh

Keyword(s):

At Risk ◽

Portfolio Selection ◽

Value At Risk ◽

Risk Measures ◽

Risk Measure ◽

Selection Problem ◽

Conditional Value At Risk ◽

Expected Return ◽

Portfolio Selection Problem ◽

Multi Stage

This paper is a novel work of portfolio-selection problem solving using multi objective model considering four parameters, Expected return, downside beta coefficient, semivariance and conditional value at risk at a specified confidence level. Multi-period models can be defined as stochastic models. Early studies on portfolio selection developed using variance as a risk measure; although, theories and practices revealed that variance, considering its downsides, is not a desirable risk measure. To increase accuracy and overcoming negative aspects of variance, downside risk measures like semivarinace, downside beta covariance, value at risk and conditional value at risk was other risk measures that replaced in models. These risk measures all have advantages over variance and previous works using these parameters have shown improvements in the best portfolio selection. Purposed models are solved using genetic algorithm and for the topic completion, numerical example and plots to measure the performance of model in four dimensions are provided.

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Conditional Value-at-Risk-Based Portfolio Optimization

Metaheuristic Approaches to Portfolio Optimization - Advances in Information Quality and Management ◽

10.4018/978-1-5225-8103-1.ch004 ◽

2019 ◽

pp. 82-108

Author(s):

Jhuma Ray ◽

Siddhartha Bhattacharyya ◽

N. Bhupendro Singh

Keyword(s):

At Risk ◽

Portfolio Optimization ◽

Value At Risk ◽

Risk Measures ◽

Real Life ◽

Conditional Value At Risk ◽

Market Theory ◽

Market Conditions ◽

Expected Return ◽

Multi Objective

Over the past few decades, an extensive research on the multi-objective decision making and combinatorial optimization of real world's financial transactions has taken place. The modern capital market theory problem of portfolio optimization stands to be a multi-objective problem aiming at the maximization of the expected return of the portfolio in turn minimizing portfolio risk. The conditional value-at-risk (CVaR) is a widely used measure for determining the risk measures of a portfolio in volatile market conditions. A heuristic approach to portfolio optimization problem using ant colony optimization (ACO) technique centering on optimizing the conditional value-at-risk (CVaR) measure in different market conditions based on several objectives and constraints has been reported in this paper. The proposed ACO approach is proved to be reliable on a collection of several real-life financial instruments as compared to its value-at-risk (VaR) counterpart. The results obtained show encouraging avenues in determining optimal portfolio returns.

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Value-at-Risk Efficient Portfolio Selection Using Goal Programming

Review of Pacific Basin Financial Markets and Policies ◽

10.1142/s0219091508001313 ◽

2008 ◽

Vol 11 (02) ◽

pp. 187-200 ◽

Cited By ~ 9

Author(s):

Hsin-Hung Chen

Keyword(s):

At Risk ◽

Portfolio Selection ◽

Goal Programming ◽

Asset Allocation ◽

Value At Risk ◽

Expected Return ◽

Allocation Model ◽

Proposed Model ◽

Portfolio Selection Model ◽

The Empirical Analysis

The purpose of this study is to apply polynomial goal programming to establish a new portfolio selection model that considers the tradeoffs between expected return and Value-at-Risk (VaR) of portfolios and the flexibility of incorporating investor's preferences. The historical data of 10 international stock markets of Pacific Rim countries were used in the empirical analysis. The results showed that the proposed model demonstrated the ability to resolve the problems of a traditional asset allocation model. The validity and fitness of the proposed model were confirmed.

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Extremwerttheorie und Value-at-Risk

WiSt - Wirtschaftswissenschaftliches Studium ◽

10.15358/0340-1650-2015-5-259 ◽

2015 ◽

Vol 44 (5) ◽

pp. 259-267

Author(s):

Frank Schuhmacher ◽

Benjamin R. Auer

Keyword(s):

At Risk ◽

Value At Risk

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