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hosseini--arian
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Customer Churn Prediction in the Iran Insurance Industry
, M.Sc. Thesis Sharif University of Technology ; Aslani, Shirin (Supervisor) ; Arian, Hamid Reza (Supervisor)
Abstract
Insurance companies in Iran operate in a completely competitive and dynamic environment. Because customer acquisition in these companies is significantly more expensive than customer retention, with timely forecasting of churning customers, they can manage their customers more effectively. In this study, in order to predict customer churn in the insurance industry, the data of one of the Iranian insurance companies that has more than two million insurers were used. In order to identify important data and variables, previous studies were reviewed, and on the other hand, the Central Insurance Regulations of the Islamic Republic of Iran, as well as the information of the insurance contracts of...
An Integrated Multi-criteria Decision Making Approach for a Sustainable Supply Chain Network Design
, M.Sc. Thesis Sharif University of Technology ; Shavandi, Hassan (Supervisor)
Abstract
Growing concerns towards social and environmental issues besides economic in supply chain causes that the sustainable supply chain become one of the most important concepts in a supply chain. Likewise, a supply chain network design which is profound influence on long-run economic, environmental, and social decisions is one of the key and strategic topics in a supply chain. In this study, we represent an integrated approach for a three-layer sustainable supply chain network design with routing and different transportation modes, the objectives of which are minimizing total costs, a minimizing 〖CO〗_2 emissions of transportation, and maximizing total values of social purchasing. In this...
Characterization of Plasma Etching Process Using Plasmonic Structures
, M.Sc. Thesis Sharif University of Technology ; Rashidian, Bizhan (Supervisor)
Abstract
plasma characterization has become an essential tool for characterization of etching process in fabrication of nano-electronic devices. The existing methods, such as Langmuir probe and interferometry, have shown drawbacks including disturbing the plasma and sensitivity to mechanical and thermal stability of the measuring systems. In recent years, due to the scale down of microelectronic devices and increase of their sensitivity to disturbance in the plasma etching process, a demand for measuring methods offering less disturbance has arisen. Plasmonic structures, owing to their unprecedented field enhancement and confinement, have been extensively studied. Their sub-wavelength dimensions,...
Pathwise grid valuation of fixed-income portfolios with applications to risk management
, Article Heliyon ; Volume 8, Issue 7 , 2022 ; 24058440 (ISSN) ; Chaghazardi, A ; Arian, H ; Sharif University of Technology
Elsevier Ltd
2022
Abstract
Numerical calculation of Value-at-Risk (VaR) for large-scale portfolios poses great challenges to financial institutions. The problem is even more daunting for large fixed-income portfolios as their underlying instruments have exposure to higher dimensions of risk factors. This article provides an efficient algorithm for calculating VaR using a historical grid-based approach with volatility updating and shows its efficiency in computational cost and accuracy. Our VaR computation algorithm is flexible and simple, while one can easily extend it to cover other nonlinear portfolios such as derivative portfolios on equities and FX securities. © 2022
Portfolio Value-at-Risk and expected-shortfall using an efficient simulation approach based on Gaussian Mixture Model
, Article Mathematics and Computers in Simulation ; Volume 190 , 2021 , Pages 1056-1079 ; 03784754 (ISSN) ; Sharifi, A ; Arian, H ; Sharif University of Technology
Elsevier B.V
2021
Abstract
Monte Carlo Approaches for calculating Value-at-Risk (VaR) are powerful tools widely used by financial risk managers across the globe. However, they are time consuming and sometimes inaccurate. In this paper, a fast and accurate Monte Carlo algorithm for calculating VaR and ES based on Gaussian Mixture Models is introduced. Gaussian Mixture Models are able to cluster input data with respect to market's conditions and therefore no correlation matrices are needed for risk computation. Sampling from each cluster with respect to their weights and then calculating the volatility-adjusted stock returns leads to possible scenarios for prices of assets. Our results on a sample of US stocks show that...
Customer Churn Prediction in Therapy Policy in Iran
, M.Sc. Thesis Sharif University of Technology ; Aslani, Shirin (Supervisor) ; Arian, Hamidreza (Supervisor)
Abstract
Using customer relationship management systems has led to the formation of databases containing businesses customer information. Increased competition in the markets, limited resources and high costs of attracting new customers compared to retaining existing customers have made customer retention an inevitable subject for business owners. Meanwhile, insurance companies, which due to their long history have suitable databases of product information and their customers, have resorted to using their databases to manage the relationship with their customers. In this research, while predicting customers churn in health insurance, as one of the most widely used products of domestic insurance...
Comparative evaluation of advanced gas turbine cycles with modified blade cooling models [electronic resource]
, Article Proceedings of the ASME Turbo Expo ; Volume 4, Pages 537-546 , 2006 ; Sharif University of Technology
2006
Abstract
Advanced gas turbine cycles use advanced blade cooling technologies to reach high turbine inlet temperature. Accurate modeling and optimization of these cycles depend on blade cooling model. In this study, different models have been used to simulate gas turbine performance. The first model is the continuous model and the second is stage-by-stage model with alternative methods for calculating coolant, stagnation pressure loss and SPR. Variation of specific heat and enthalpy with temperature are included in both models. The composition of gas stream in turbine is changed step by step due to air cooling. These models are validated by two case study gas turbine results, which show good agreement...
Estimation of a Portfolio's Value-at-Risk Using Variational Auto-Encoders
, M.Sc. Thesis Sharif University of Technology ; Arian, Hamidreza (Supervisor) ; Talebian, Masoud (Supervisor)
Abstract
One of the most crucial aspects of financial risk management is risk measurement. Advanced AI-based solutions can provide the proper tools for assessing global markets, given the complexity of the global economy and the violation of typical modeling assumptions. A new strategy for quantifying stock portfolio risk based on one of the machine learning models known as Variational Autoencoders is provided in this dissertation. The suggested method is a generative model that can learn the stocks' dependency structure without relying on assumptions about stock return covariance and produce various market scenarios using cross-sectional stock return data with a higher signal-to-noise ratio. We...
Calculating Value at Risk for Bond Portfolios by Selecting Basic Scenarios in the Historical Simulation Method
, M.Sc. Thesis Sharif University of Technology ; Zamani, Shiva (Supervisor) ; Arian, Hamid Reza (Supervisor)
Abstract
In many methods of calculating Value-at-Risk (VaR), we need to calculate the value of the portfolio several times for different scenarios. Because an explicit formula is not available to calculate the value of some fixed income assets, calculating VaR for portfolios containing these assets imposes a heavy computational burden. In this study, we introduce a new method for calculating VaR for such portfolios. In this method, some of the existing scenarios are selected as basic scenarios and the value of the portfolio is calculated only for each of them. Next, using the calculated values, the portfolio values for other scenarios are estimated by interpolation (or extrapolation). Finally, by...
Investor Experience in Chabahar Free Zone: Scale Generation
, M.Sc. Thesis Sharif University of Technology ; Najmi, Manoochehr (Supervisor) ; Arian, Hamidreza (Supervisor)
Abstract
Free economic zones in Iran have been established with the goal of developing infrastructure, improving living conditions, fostering economic growth, attracting capital and increasing income, productive job creation, regulating job and goods market, maintaining active presence in international and regional markets, manufacturing and exporting of goods and providing public services. Yet many free economic zones have fallen short of these goals. Considering the government's inability to fund the development of the free economic zones with its limited financial capacity and shortcomings in terms of management system, it is imperative to the development of these regions that private sector...
Portfolio Management: Combining Hierarchical Models with Prior Hierarchical Structure
, M.Sc. Thesis Sharif University of Technology ; Arian, Hamid Reza (Supervisor) ; Zamani, Shiva (Supervisor)
Abstract
I investigate methods of integrating prior hierarchical structure into hierarchical portfolio optimization methods. My contributions to the literature are forming a prior hierarchical structure based on investors' priorities and generating a unique representative distance matrix, which can be used as an input to other portfolio optimization methods too. In addition, I use SIC and GICs industry classifications as priory information for S&P500 companies and use them as a complementary input to the Hierarchical Risk Parity model and Hierarchical Equal Risk Contribution and compare the resultant portfolios' performance with (López de Prado, 2019)’s method of integrating prior information and...
Integrating Supervised and Unsupervised Machine Learning Algorithms for Profit-based Credit Scoring
, M.Sc. Thesis Sharif University of Technology ; Arian, Hamid Reza (Supervisor) ; Zamani, Shiva (Supervisor)
Abstract
In this study, we combined supervised and unsupervised machine learning algorithms, included the benefits of true identification of good borrowers and costs of false identification of bad borrowers, and then proposed a model for predicting the default of loan applicants with a profit-based approach. The results show that our proposed model has the best performance in profit measure in comparison with individual supervised models. In fact, we first divided the data into two train sets and one test set. We have constructed our model by training unsupervised models on the first train set and supervised models on the second train set. The results of implementing the model on the Australian and...
Patch testing in Iranian children with allergic contact dermatitis
, Article BMC Dermatology ; Volume 16, Issue 1 , 2016 ; 14715945 (ISSN) ; Ehsani, A ; Sajjadi, S. S ; Aghazadeh, N ; Arian, E ; Sharif University of Technology
BioMed Central Ltd
2016
Abstract
Background: Allergic contact dermatitis is a common disorder in adults and children alike and appears to be on the increase. The purpose of this study was to determine the sensitization trends in Iranian children with contact dermatitis. Methods: The result of 109 patch tests performed using the 24 allergens of the European Standard Series in patients below 18 years old from September 2007 to March 2009 were recorded and analyzed. The tests were evaluated at 48 and 72 h after performing. Results: The study population consisted of 72 (66.1 %) females and 37 (33.9 %) males. Hands were the most commonly affected anatomic site. In the final evaluation of the tests on day three, 51 (46.8 %)...
Optimal Distance Calculation Method for Portfolio Optimization using
Nested Cluster Optimization
,
M.Sc. Thesis
Sharif University of Technology
;
Arian, Hamid Reza
(Supervisor)
;
Zamani, Shiva
(Supervisor)
Abstract
In the basic model of this thesis, which is called nested cluster optimization, only one distance function is used for clustering to form clusters with similar characteristics, while depending on whether the optimization model is long-only or long-short, different functions can be used. The aim of this thesis is to find the optimal distance function between assets in the simple nested cluster optimization so that during three different and separate strategies, based on three criteria of the lowest risk, the highest Sharpe ratio, and the highest return, the optimal distance function of assets is selected and clustering and finally weighting the portfolio to be done. The optimal distance...
Bitcoin Price Prediction based on Artificial Intelligence Models
, M.Sc. Thesis Sharif University of Technology ; Arian, Hamid Reza (Supervisor) ; Talebian, Masoud (Supervisor)
Abstract
Cryptocurrencies (cryptos), as a new type of money, are considered a medium of exchange, an investment asset, and a hedging tool in today's world. In 2008, bitcoin as the first cryptocurrency was introduced, which has survived through recent years and has gained more and more popularity every day. Cryptos are one of the first applications of blockchain, the technology that many expect to revolutionize the future world in different ways. We aim to investigate what affects the bitcoin price, based on artificial intelligence and, in particular, machine learning. First, we find features impacting bitcoin price via a thorough investigation of the literature. Then, applying machine learning and...
Assessment of Risk Arising from Changes in Implied Volatility in Option Portfolios
, M.Sc. Thesis Sharif University of Technology ; Arian, Hamid Reza (Supervisor) ; Zamani, Shiva (Supervisor)
Abstract
This study delves into the intricate realm of risk evaluation within the domain of specific financial derivatives, notably options. Unlike other financial instruments, like bonds, options are susceptible to broader risks. A distinctive trait characterizing this category of instruments is their non-linear price behavior relative to their pricing parameters. Consequently, evaluating the risk of these securities is notably more intricate when juxtaposed with analogous scenarios involving fixed-income instruments, such as debt securities. A paramount facet in options risk assessment is the inherent uncertainty stemming from first-order fluctuations in the underlying asset’s volatility. The...
The Predicting Power of Investors’ Sentiment for Cryptocurrency Returns
, M.Sc. Thesis Sharif University of Technology ; Arian, Hamid Reza (Supervisor) ; Hagh Panah, Farshad (Co-Supervisor)
Abstract
Classical financial literature believes that people's decisions in financial markets are rational and that asset prices remain at their intrinsic value. On the other hand, behavioral finance literature believes that there are limitations in investors' decision-making and the impact of decisions on emotions, and states that investors' emotions directly affect asset prices. The aim of this research is to investigate which of the famous indicators introduced in the literature as a representative of the emotional behavior of investors has a better performance in predicting the returns of cryptocurrencies. For this purpose, in the first step, the information related to the calculation of three...
Monte Carlo simulation of Feynman-α and Rossi-α techniques for calculation of kinetic parameters of Tehran research reactor
, Article Annals of Nuclear Energy ; Volume 38, Issue 10 , 2011 , Pages 2140-2145 ; 03064549 (ISSN) ; Vosoughi, N ; Hosseini, M ; Sharif University of Technology
2011
Abstract
Noise analysis techniques including Feynman-α (variance-to-mean) and Rossi-α (correlation) have been simulated by MCNP computer code to calculate the prompt neutron decay constant (α0), effective delayed neutron fraction (βeff) and neutron generation time (Λ) in a subcritical condition for the first operating core configuration of Tehran Research Reactor (TRR). The reactor core is considered to be in zero power (reactor power is less than 1 W) in the entire simulation process. The effect of some key parameters such as detector efficiency, detector position and its dead time on the results of simulation has been discussed as well. The results of proposed method in the current study are...
Semisolid Stir Joining of AZ91 Magnesium alloy
, M.Sc. Thesis Sharif University of Technology ; Aashuri, Hosseini (Supervisor)
Abstract
AZ91 is the most applicable alloy of magnesium alloys.Semisolid stir welding of AZ91 magnesium alloy was investigated due to its welding problem such oxide formation, hot cracking in weld metal, and high residual stress through solidification with special focus on the effect of the welding temperatures, stirring rates, and tool shape. The interlayer with thickness of 2mm was located between two AZ91 pieces with 7.5mm thickness. Then, they were heated to the desired temperatures (515C, 530C and 540C), the semisolid temperature of both base metal and interlayer. A grooved stirrer with six rotational speeds from 0rpm to 2000rpm was introduced into the stir weld seam and the welded coupons...
Calculation of fuel burn up and radioactive inventory for HEU fuel element of Tehran Research Reactor
, Article International Conference on Nuclear Engineering, Proceedings, ICONE, 17 May 2010 through 21 May 2010 ; Volume 2 , 2010 ; 9780791849309 (ISBN) ; Vosoughi, N ; Hosseini, M ; Nuclear Engineering Division ; Sharif University of Technology
2010
Abstract
This paper presents a new approach for fuel burn up evaluation and radioactive inventory calculation used in Tehran Research Reactor. The approach is essentially based upon the utilization of a program written by C# which integrates the cell and core calculation codes, i.e., WIMSD-4 and CITVAP, respectively. Calculation of fuel burn up and radioactive inventories has been done for 26 core configuration of Tehran Research Reactor with HEU fuel element. The present inventory and fuel enrichment of each fuel element have been calculated