Department of Systems and Productivity Management (2013 - Present)
Financial Engineering
Engineering, Genoa, Genoa, Italy
Post Graduate Finance Level II
Finance, Collegio Carlo Alberto Turin Univ., Turin, Italy
Math
Math, Sharif Univ. of Tech, Tehran, Iran
Math.
Math., Sharif Univ. of Tech, Tehran, Iran
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After restructuring, Iran’s electricity market has become one of the most competitive markets in which generation companies offer their proposed price on several price benches. So, the decisions in this market can use statistical concepts. In this paper, a conceptual model is presented according to simultaneous analysis of probabilistic distribution for historical data of market clearing price and frequency of acceptance of bids. Based on this model, the probable value of market clearing price is measured through the risk of historical data price intervals and the decision is made about bidding strategy. Also, a method is proposed to calculate the probability of acceptance and risk of rejection of bids on the electricity market. The data
Project finance is based on the future cash flow of projects. Ensuring that the expected revenue of projects will cover the debt and equity obligations issued by lenders and shareholders is crucial. The uncertainty of solar resources is among the highest, and it causes fluctuations in the future cash flow of solar photovoltaic (PV) projects. To reduce this uncertainty, several methods such as measure-correlate-predict (MCP) analysis, have been applied. However, MCP is an oversimplified linear regression method that disregards the difference between the parameters and conditions of different hours throughout a day; hence, it cannot provide accurate and reliable results. Here, we propose a methodology based on Bayesian updating, which is a ro
The objective of this paper is to analyze the network topology of the Iranian overnight money market through methods of statistical mechanics applied to complex networks in order to assessing systemic risk. We investigate differences in the activities of 33 Iranian banks dividing into different four types between 2010-2015 by analyzing 66 montly adjacency matrixs. Using degree distribution analysis of the networks, we find that that Iranian interbank market network is scale-free network and cumulative degree, in-degree and out-degree follows the power-law distribution. In terms of the criterion of assortativity, the interbank market network of Iran is assortative and core-periphery with one or more banks as the money center. The results sho
Entering into the interbank market in order to balance profitability and liquidity risk management, depending on the conditions of short-term activities, banks are required to equip resources through this market or to lend short-term loans to other banks. Banks' commitments to each other mainly arise in the interbank market, which can lead to increased systemic risk due to the spillover effect. Therefore, the objective of this paper is to analyze the network dynamic stability of the Iranian overnight money market through methods of statistical mechanics applied to complex networks .The results show that the network structure changes during time depending economic conditions. Systemic risk measures such as clustering coefficient, average sho
Introduction At the core of any investment lies the return on investment. To gain a favorable return, an investor should take investment-related risks. The interaction between risk and return can lead to decisions on asset allocation. A key strategy in investment discussions is diversification in investment portfolio. Investment strategy is undetermined in different assets such as security, gold, currency and cryptocurrency. Despite the temporary recession and success of certain assets, it is hard to prioritize investment among assets (in terms of risk and return) to ensure that the investor makes the highest profit at the lowest risk. Thus, the present research used the Mean-CVaR model along with the Extreme value theory (EVT) based on Cop
According to the Basel III regulatory framework, uniform minimum liquidity requirements have been imposed on all types of banks. Using an agent-based model of a banking system, we investigate the effects of liquidity requirements on banks' insolvency under two policy experiments in one of which the minimum liquidity requirements are applied uniformly and in the other differentially across banks. The model introduces a banking system with 12 heterogeneous banks that must also comply with two liquidity requirements while performing their daily activities of taking deposits and making loans. The model is applied to the Iranian banking system. Results illustrate that because banks respond differently to liquidity requirements, applying one size
Nowadays, banks in the country are faced with serious problems in terms of their assets. One of the factors that led to this situation is the poor quality of banks' assets, which can be attributed to the lack of a rating system and an improper assessment of credit risk. This study predicts the probability of default during a specific time using the Cox regression model as well as the survival model of spline-based logistic regression. For modeling of credit risk, using these two methods, 10 variables related to 2861 customers of an Iranian bank were used. We compared two models using ROC method, the Cox regression model with AUC = 0.799 was more efficient than the spline-based logistic regression model with AUC = 0.746.
Objective:? This paper analyzes the possibility of publishing mortality bonds. This class of securities provides attractive investment opportunities for capital market and is a good hedging tool for managing the risk of life insurance companies. It allows the insurers to access a new source of financing and provides some facilities for investors to diversify their portfolios. Methodology: In order to conduct pricing of mortality bonds, it is required to predict future rate of mortality. We used lee and carter model simulation mortality rate, because that is very flexible and can be used by limited data. Here, the mortality rate of 5 _year age groups for years between 1996 and 2016 was calculated. The reason for using Gregorian calendar is t
In recent years, many articles and researches have been published on the use of machine learning methods and algorithmic trading in financial markets in order to earn returns. The aim of this study is to create an automated trading system using image processing by convolutional neural network. For this purpose, initially, after receiving the data required for the selected stocks, 28 technical analysis indicators were selected and the values of each were calculated separately for each stock. Then the time series of these indicators were converted to 2D images, and as a result, for each data on the time series of the stock price, a 2D image with dimensions of 28 x 28 was created. After labeling each image with one of the buy, sell, and hold l
After the financial crisis of 2007-2009, in which liquidity problems led to insolvency and consequently the bankruptcy of many large banks and financial institutions such as Lehman Brothers, Basel Committee on Banking Supervision introduced liquidity requirements for the most part to reduce the possibility of bank insolvency caused by liquidity shocks. This research develops an agent-based model of a banking system to be used to analyze the impact of the liquidity requirements on the solvency position of banks. The model devises a banking system with 12 heterogeneous banks in which banks perform their traditional activities namely taking deposits and making loans. Banks can fulfill their liquidity needs by engaging in interbank lending, sel
We have studied the magnetophotonic crystals (MPCs) with excellent capabilities to enhance reflection and Kerr rotation simultaneously. In order to simultaneously investigate the symmetric and nonsymmetric spatial structures, we have considered the different repetition numbers for dielectric photonic crystals around the magnetic defect layer. To construction of dielectric Bragg mirrors, we have used of Al2O3 due to low refractive index and its unique optical features. The Ce:YIG with high magneto-optical features is utilized as magnetic material to increasing the magneto-optical responses of structures. By adjusting spatial features such as repetition numbers of PCs and thickness of magnetic defect layers, we have achieved the magneto-optic
Revised 25 Jan. 2019; Accepted 18 Feb. 2019; Published 15 Mar. 2019) Abstract: We studied magnetophotonic crystals (MPCs) with introduced magnetic defect layer sandwiched between magnetic and dielectric Bragg mirrors. These magnetophotonic crystals have excellent capabilities to enhance reflection and Kerr rotation simultaneously. By adjusting spatial configuration such as repetition numbers of Bragg mirrors and thickness of magnetic defect layer, we achieved the Kerr rotation angles more than 75 and reflection very close to 1. We briefly described the formulation of finite element method (FEM) and transfer matrix method (TMM). The electric field distribution and magnitude of it along the MPCs are simulated using FEM. Using the TMM, we calc
In this paper, employing of one-dimensional magnetophotonic crystals in infrared wavelengths range is considered. For this purpose, magnetophotonic multilayer structures, composed of magnetic defect layer surrounded by dielectric and MO Bragg mirrors, have been proposed. Ce: YIG with an optical thickness in the range of 0 to λs was used as a magnetic material. By using four by four transfer matrix method, the transmittance values and Faraday rotation (FR) angles of these structures were computed. The electric field distribution was obtained by Finite Element Method (FEM). By investigation of transmittance and FR angle of magnetophotonic crystals, it was possible to design the optimized structures with a rotation larger than 30 degrees and
The aim of this paper is evaluation and forecasting of credit risk of the companies that were applied for a loan in a commercial bank in Iran. So, by using cross-section random sampling by having 75% of total data as an in-sample and 25% as out-sample and also by using LINMAP model, financial statements and their performance in the bank were investigated during 1389-1393. The results indicate the efficiency of the method for forecasting credit behavior of the bank's customers. Considering the method advantages including its independence to the companies' financial background and precision in forecasting relative to prevailing methods, it is recommended to use this method as input to researches for banks' credit portfolio management.
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