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International Journal of Quantitative Research and Modeling
Published by Research Collaboration Community
ISSN : 27225046     EISSN : 2721477X     DOI : https://doi.org/10.46336/ijqrm
Core Subject : Science, Social, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Environmental Science Physics
International Journal of Quantitative Research and Modeling (IJQRM) is published 4 times a year and is the flagship journal of the Research Collaboration Community (RCC). It is the aim of IJQRM to present papers which cover the theory, practice, history or methodology of Quatitative Research (QR) and Mathematical Moodeling (MM). However, since Quatitative Research (QR) and Mathematical Moodeling (MM) are primarily an applied science, it is a major objective of the journal to attract and publish accounts of good, practical case studies. Consequently, papers illustrating applications of Quatitative Research (QR) and Mathematical Modeling (MM) to real problems are especially welcome. In real applications of Quatitative Research (QR) and Mathematical Moodeling (MM): forecasting, inventory, investment, location, logistics, maintenance, marketing, packing, purchasing, production, project management, reliability and scheduling. In a wide variety of environments: community Quatitative Research (QR) and Mathematical Moodeling (MM), education, energy, finance, government, health services, manufacturing industries, mining, sports, and transportation. In technical approaches: decision support systems, expert systems, heuristics, networks, mathematical programming, multicriteria decision methods, problems structuring methods, queues, and simulation Computational Intelligence Computing and Information Technologies Continuous and Discrete Optimization Decision Analysis and Decision Support Mathematics Education Engineering Management Environment, Energy and Natural Resources Financial Engineering Heuristics Industrial Engineering Information Management Information Technology Inventory Management Logistics and Supply Chain Management Maintenance Manufacturing Industries Marketing Engineering Markov Chains Mathematics Actuarial Sciences Big Data Analysis Operations Research Military and Homeland Security Networks Operations Management Planning and Scheduling Policy Modeling and Public Sector Production Management Queuing Theory Revenue & Risk Management Services Management Simulation Statistics Stochastic Models Strategic Management Systems Engineering Telecommunications Transportation Risk Management Modeling of Economics And so on
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 6 Documents
 1 
Search results for , issue "Vol 1, No 1 (2020)" : 6 Documents clear
ON QUASI NEWTON METHOD FOR SOLVING FUZZY NONLINEAR EQUATIONS Umar A Omesa; Mustafa Mamat; Ibrahim M Sulaiman; Sukono Sukono
International Journal of Quantitative Research and Modeling Vol 1, No 1 (2020)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (512.04 KB) | DOI: 10.46336/ijqrm.v1i1.1

Abstract

This paper presents Quasi Newton’s (QN) approach for solving fuzzy nonlinear equations. The method considers an approximation of the Jacobian matrix which is updated as the iteration progresses. Numerical illustrations are carried, and the results shows that the proposed method is very encouraging.
STOCK PORTFOLIO ANALYSIS USING MARKOWITZ MODEL Indah Nur Nur Safitri; Sudradjat Sudradjat; Eman Lesmana
International Journal of Quantitative Research and Modeling Vol 1, No 1 (2020)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (355.191 KB) | DOI: 10.46336/ijqrm.v1i1.6

Abstract

A common problem that often occurs in investment is the selection of the optimal portfolio according to the wishes of investors. This thesis ueds the Markowitz Model as a basis to formed a model to choose the optimal portfolio that provided the lowest risk. Efforts to minimize risk were carried out by conducting a diversification strategy. After the selection of several companies with the criteria of capitalization value and DER (Debt Equity Ratio), a combination of stocks is formed to form a portfolio. The formed portfolio was then analyzed to determine the optimal proportion of each stock. Using the Markowitz model, which is then solved by Non Linear Programming, an optimal portfolio is obtained with the proportion of each stock minimizing risk. In general, the results of this analysis indicate that portfolios with more stocks will produce lower risks compared to portfolios with fewer stocks, thus providing optimal diversification solutions, namely portfolios with members of five stocks with optimal risk of 0.886%.
A COMPARATIVE STUDY OF SOME MODIFICATIONS OF CG METHODS UNDER EXACT LINE SEARCH Yasir Salih; Mustafa Mamat; Sukono Sukono
International Journal of Quantitative Research and Modeling Vol 1, No 1 (2020)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (428.404 KB) | DOI: 10.46336/ijqrm.v1i1.2

Abstract

Conjugate Gradient (CG) method is a technique used in solving nonlinear unconstrained optimization problems. In this paper, we analysed the performance of two modifications and compared the results with the classical conjugate gradient methods of. These proposed methods possesse global convergence properties for general functions using exact line search. Numerical experiments show that the two modifications are more efficient for the test problems compared to classical CG coefficients.
THE GARCH MODEL VOLATILITY OF SHARIA STOCKS ASSOCIATED CAUSALITY WITH MARKET INDEX Endang Soeryana Hasbullah; Endang Rusyaman; Alit Kartiwa
International Journal of Quantitative Research and Modeling Vol 1, No 1 (2020)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (372.5 KB) | DOI: 10.46336/ijqrm.v1i1.3

Abstract

The purpose of this paper is to examine the volatility of Islamic stocks related to the causality of the composite stock price index (CSPI). The aim is to investigate the causality of several levels of stock returns with the movement of the CSPI, and determine its volatility as a measure of risk. To determine the causality relationship is done by using the granger causality test method, with Vector Autoregressive (VAR) modeling. Whereas to determine the volatility is done using the Generalized Autoregressive Conditional Heteroscedastisiy (GARCH) model approach. The results of the causality test show that there is a direct relationship that affects and is influenced by the CSPI, and the relationship that affects each other between the company's stock market and the movement of the CSPI. While the volatility follows the GARCH model (1, 1). Based on the results of this study are expected to be used as consideration in making investment decisions in the analyzed stocks.
THE VALIDATION OF NEW FORMULA OF ISLAMIC HOME FINANCING AMONG FINANCE EXPERTISE’S Puspa Liza Binti Ghazali; Sharifah Arni binti Syed Jaaffar
International Journal of Quantitative Research and Modeling Vol 1, No 1 (2020)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (329.145 KB) | DOI: 10.46336/ijqrm.v1i1.4

Abstract

Islamic banks in Malaysia practiced a different type of shariah principle that may offer advantage and disadvantages to Islamic home financing’s customer. Instead of analyzing the percentage of acceptance to Barakah Model Islamic home financing among public, a set of questionnaires were distributed among Islamic financial expertise. Barakah model need to be validate as to check it is fit according to Islamic finance’s need or not. The Barakah model is designed to cater the lower income earners especially RM 3500 and below with extra benefit to protect the house owner if anything happens in future.
A GARCH APPROACH TO VaR CALCULATION IN FINANCIAL MARKET Nurfadhlina Abdul Halim; Endang Soeryana; Alit Kartiwa
International Journal of Quantitative Research and Modeling Vol 1, No 1 (2020)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (283.537 KB) | DOI: 10.46336/ijqrm.v1i1.5

Abstract

Value at Risk (VaR) has already becomes a standard measurement that must be carried out by financial institution for both internal interest and regulatory. VaR is defined as the value that portfolio will loss with a certain probability value and over a certain time horizon (usually one or ten days). In this paper we examine of VaR calculation when the volatility is not constant using generalized autoregressive conditional heteroscedastic (GARCH) model. We illustrate the method to real data from Indonesian financial market that is the stock of PT. Indosat Tbk.

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