scholarly journals Estimating the Accuracy of the Return on Investment (ROI) Performance Evaluations

10.28945/2338 ◽  
2015 ◽  
Vol 10 ◽  
pp. 217-233 ◽  
Author(s):  
Alexei Botchkarev
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Information Systems ◽  
Return On Investment ◽  
Systematic Research ◽  
Informed Decisions ◽  
Visual Basic For Applications ◽  
Systematic Effort ◽  
Measurement And Evaluation ◽  
Analytical Expressions

Return on Investment (ROI) is one of the most popular performance measurement and evaluation metrics. ROI analysis (when applied correctly) is a powerful tool in comparing solutions and making informed decisions on the acquisitions of information systems. The purpose of this study is to provide a systematic research of the accuracy of the ROI evaluations in the context of information systems implementations. Measurements theory and error analysis, specifically propagation of uncertainties methods, were used to derive analytical expressions for ROI errors. Monte Carlo simulation methodology was used to design and deliver a quantitative experiment to model costs and returns estimating errors and calculate ROI accuracies. Spreadsheet simulation (Microsoft Excel spreadsheets enhanced with Visual Basic for Applications) was used to implement Monte Carlo simulations. The main contribution of the study is that this is the first systematic effort to evaluate ROI accuracy. Analytical expressions have been derived for estimating errors of the ROI evaluations. Results of the Monte Carlo simulation will help practitioners in making informed decisions based on explicitly stated factors influencing the ROI uncertainties.

scholarly journals A Novel Monte-Carlo Simulation-Based Model for Malware Detection (eRBCM)

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2881
Author(s):  
Muath Alrammal ◽  
Munir Naveed ◽  
Georgios Tsaramirsis
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Information Systems ◽  
Malware Detection ◽  
New Model ◽  
Malicious Activity ◽  
Model Based ◽  
Simulation Based ◽  
Computer Based ◽  
Reinforcement Model

The use of innovative and sophisticated malware definitions poses a serious threat to computer-based information systems. Such malware is adaptive to the existing security solutions and often works without detection. Once malware completes its malicious activity, it self-destructs and leaves no obvious signature for detection and forensic purposes. The detection of such sophisticated malware is very challenging and a non-trivial task because of the malware’s new patterns of exploiting vulnerabilities. Any security solutions require an equal level of sophistication to counter such attacks. In this paper, a novel reinforcement model based on Monte-Carlo simulation called eRBCM is explored to develop a security solution that can detect new and sophisticated network malware definitions. The new model is trained on several kinds of malware and can generalize the malware detection functionality. The model is evaluated using a benchmark set of malware. The results prove that eRBCM can identify a variety of malware with immense accuracy.

Monte Carlo Simulation-Based Benefit-Cost Analysis Combined with Analytical Hierarchy Process to Support ITS Investment with Consideration of Connected Vehicle Technology

2018 ◽  
Vol 2672 (19) ◽  
pp. 1-12 ◽  
Author(s):  
Samaneh Khazraeian ◽  
Mohammed Hadi
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Analytical Hierarchy Process ◽  
Return On Investment ◽  
Intelligent Transportation System ◽  
Investment Analysis ◽  
Connected Vehicle ◽  
Freeway Traffic ◽  
Benefit Cost Analysis ◽  
Hierarchy Process

Decisions to invest in alternative intelligent transportation system (ITS) technologies are expected to increase in complexity, particularly with the introduction of connected vehicles (CV) and automated vehicles (AV) in the coming years. Traditional alternative analyses based on deterministic return on investment analysis are unable to capture the risks and uncertainties associated with the investment problem. In addition, these methods cannot account for agency preferences and constraints that cannot be converted to dollar values. This study utilizes a combination of a stochastic return on investment and a multi-criteria decision analysis method referred to as the Analytical Hierarchy Process (AHP) to select between ITS deployment alternatives considering emerging technologies. The approach is applied in a case study of the selection between using CV data and point detector data to support the freeway traffic data collection and monitoring service. The four objectives specified in the AHP analysis are providing the required functions, providing the required performance, minimizing the risks and constraints, and maximizing the return on investment. A stochastic return-on-investment analysis using a Monte Carlo simulation was used to calculate the return on investment values for input to the AHP method.

scholarly journals Calculation and Management of Premium Funds in Sharia Insurance (Ta'min, Takaful or Tadhamun)

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Khusnul Khotimah ◽  
Mahmudi Mahmudi ◽  
Nina Fitriyati
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Interest Rates ◽  
Conventional Method ◽  
Return On Investment ◽  
Equation System ◽  
Type Model ◽  
First Year ◽  
Operating Surplus ◽  
Annual Premium

AbstractThis research discusses the calculation of the premium of term life-insurance based on sharia principles. The difference between the conventional method and the sharia principle is in the concept of interest rates. In this research, the concept of interest in the conventional method is replaced by the Return on Investment (ROI) that changes stochastically following the Langevin type model. The Monte-Carlo simulation is applied to generate the ROI with some initial values. On the mechanism of premium management, we apply the system without a saving element and the Al-Mudharabah relationship where the participants will get a sharing-profit of the operating surplus if they don’t make a claim until the end of the agreement period. We assume that the administrative expenses only charged in the first year. Therefore, the operating surplus will be greater after the first year. In addition, we do 20 times of Monte–Carlo simulations to generate the ROI with initial value are 7.5%, 9%, and 10%. The result shows that the annual premiums become smaller when the ROI become greater and vice versa. This is because the company get a smaller return when the initial of ROI is small. So the annual premium will be greater. The annual premium for male participants is greater than women because the rate of death of men is greater than women. The other factors that make the annual premium more expensive are length of the agreement and greater compensation.Keywords: Langevin type model, stochastic differential equation, system without a saving element, Al-Mudharabah principle, Monte–Carlo simulation. AbstrakPenelitian ini membahas mengenai perhitungan dana premi asuransi jiwa berjangka berdasarkan prinsip–prinsip syariah. Perbedaan antara metode konvensional dengan prinsip syariah adalah pada konsep tingkat bunga. Pada penelitian ini, konsep bunga digantikan dengan nilai Return on Investment (ROI) yang berubah secara stokastik mengikuti model tipe Langevin. Simulasi Monte–Carlo diterapkan untuk membangkitkan nilai ROI menggunakan beberapa nilai awal. Pada mekanisme pengelolaan dana premi, kami menerapkan sistem tanpa unsur tabungan dan hubungan Al-Mudharabah dimana peserta akan mendapatkan bagi hasil atas surplus operasional jika peserta tersebut tidak melakukan klaim sampai akhir masa perjanjian. Kami mengasumsikan bahwa biaya administrasi hanya dibebankan pada tahun pertama. Sehingga surplus operasional akan menjadi lebih besar setelah tahun pertama. Selain itu, kami melakukan 20 kali simulasi Monte–Carlo untuk membangkitkan ROI dengan nilai awal 7.5%, 9%, dan 10%. Hasil menunjukkan bahwa premi tahunan akan semakin kecil jika nilai awal dari ROI membesar dan sebaliknya. Hal ini disebabkan oleh keuntungan perusahaan yang kecil jika nilai awal ROI semakin kecil sehingga premi tahunan haruslah lebih besar. Premi tahunan untuk peserta laki-laki cenderung lebih besar daripada premi tahunan peserta wanita. Hal ini karena tingkat kematian laki-laki lebih tinggi daripada wanita. Faktor lain yang membuat premi tahunan lebih besar adalah lamanya masa kontrak asuransi dan kompensasi yang semakin besar.Kata kunci: Model tipe Langevin, persamaan diferensial stokastik, sistem tanpa unsur tabungan, prinsip Al-Mudharabah, simulasi Monte–Carlo.

scholarly journals A Case Study for Business Integration as a Service

2014 ◽  
pp. 229-254 ◽  
Author(s):  
Victor Chang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Analysis ◽  
Return On Investment ◽  
Cost Savings ◽  
Computational Results ◽  
Cloud Adoption ◽  
The Cost ◽  
The University

This chapter presents Business Integration as a Service (BIaaS) to allow two services to work together in the Cloud to achieve a streamline process. The authors illustrate this integration using two services, Return on Investment (ROI) Measurement as a Service (RMaaS) and Risk Analysis as a Service (RAaaS), in the case study at the University of Southampton. The case study demonstrates the cost-savings and the risk analysis achieved, so two services can work as a single service. Advanced techniques are used to demonstrate statistical services and 3D Visualisation services under the remit of RMaaS and Monte Carlo Simulation as a Service behind the design of RAaaS. Computational results are presented with their implications discussed. Different types of risks associated with Cloud adoption can be calculated easily, rapidly, and accurately with the use of BIaaS. This case study confirms the benefits of BIaaS adoption, including cost reduction and improvements in efficiency and risk analysis. Implementation of BIaaS in other organisations is also discussed. Important data arising from the integration of RMaaS and RAaaS are useful for management and stakeholders of University of Southampton.

scholarly journals The financial survival probability of living annuitants

2013 ◽  
Vol 6 (1) ◽  
pp. 167-178 ◽  
Author(s):  
Duncan Palmer ◽  
Niel Krige
Keyword(s):  
South Africa ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Survival Probability ◽  
Return On Investment ◽  
Retirement Planning ◽  
Initial Capital ◽  
Financial Survival ◽  
The Relationship

This study addresses the question of how long a given amount of capital will be able to fund a living annuitant if the following five parameters are known: expected retirement duration (i.e. years between date of retirement and date of death), return on investment, inflation, annual withdrawal amount and initial capital amount available. A model (the Pension Model) that graphically depicts the relationship between these parameters was developed. This model facilitates retirement planning by showing how retirement duration and withdrawal rates change the financial “Survival Probability” (SP), which is the probability of having enough capital to maintain a desired withdrawal rate for the expected retirement duration. The underlying model is based on long-term historical investment yields of equities, bonds and cash in South Africa using Monte Carlo simulation with Cholesky factorisation.

scholarly journals A Case Study for Business Integration as a Service

2015 ◽  
pp. 964-989
Author(s):  
Victor Chang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Analysis ◽  
Return On Investment ◽  
Cost Savings ◽  
Computational Results ◽  
Cloud Adoption ◽  
The Cost ◽  
The University

This chapter presents Business Integration as a Service (BIaaS) to allow two services to work together in the Cloud to achieve a streamline process. The authors illustrate this integration using two services, Return on Investment (ROI) Measurement as a Service (RMaaS) and Risk Analysis as a Service (RAaaS), in the case study at the University of Southampton. The case study demonstrates the cost-savings and the risk analysis achieved, so two services can work as a single service. Advanced techniques are used to demonstrate statistical services and 3D Visualisation services under the remit of RMaaS and Monte Carlo Simulation as a Service behind the design of RAaaS. Computational results are presented with their implications discussed. Different types of risks associated with Cloud adoption can be calculated easily, rapidly, and accurately with the use of BIaaS. This case study confirms the benefits of BIaaS adoption, including cost reduction and improvements in efficiency and risk analysis. Implementation of BIaaS in other organisations is also discussed. Important data arising from the integration of RMaaS and RAaaS are useful for management and stakeholders of University of Southampton.

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