Soheil Salimi Nasab; Gholam Hosein Golarzi; Abdolsadeh Neisy
Abstract
The purpose of this study is to investigate the effects and risk spillover from the global crude oil market on Tehran Stock Exchange Oil Group. For this purpose, we used a combination of copula models and switching models in this research. First, we will examine marginal models and examine Heston switching ...
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The purpose of this study is to investigate the effects and risk spillover from the global crude oil market on Tehran Stock Exchange Oil Group. For this purpose, we used a combination of copula models and switching models in this research. First, we will examine marginal models and examine Heston switching and Markov switching models in this market. Then we create the multivariate distribution function using Clayton's copula. The data analyzed in this research are related to the global crude oil markets and the Tehran Stock Exchange Oil Group from December 2011 to January 2023. This time period was chosen due to the examination of different regimes in the above markets and also the selection of the appropriate marginal model for these markets. The results show the crude oil market has influenced on Tehran Stock Exchange and also the Tehran Stock Exchange Oil Group indices. Volatility in this global market cause turbulence in the Tehran stock market and this market is affected by the global crude oil market. This is due to the influence of the global crude oil market on total prices in these markets. Heston switching model and its combination with copula models including Clayton copula can bring good results. This is confirmed by comparing this model with other models such as copula Markov switching models.
Samaneh Mohammadi Jarchelou; Kianoush Fathi Vajargah; Parvin Azhdari
Abstract
Investment is the selection of assets to hold and earn more pro t for greater prosperity in the future. The selection of a portfolio based on the theory of constraint is classical data covering analysis evaluation and ranking Sample function. The in vestment process is related to how investors act in ...
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Investment is the selection of assets to hold and earn more pro t for greater prosperity in the future. The selection of a portfolio based on the theory of constraint is classical data covering analysis evaluation and ranking Sample function. The in vestment process is related to how investors act in deciding on the types of tradable securities to invest in and the amount and timing. Various methods have been proposed for the investment process, but the lack of rapid computational methods for determining investment policies in securities analysis makes performance appraisal a long term challenge. An approach to the investment process consists of two parts. Major is securities analysis and portfolio management. Securities analysis involvesestimating the bene ts of each investment, while portfolio management involves analyzing the composition of investments and managing and maintaining a set of investments. Classical data envelopment analysis (DEA) models are recognized as accurate for rating and measuring efficient sample performance. Unluckily, this perspective often brings us to get overwhelmed when it's time to start a project. When it comes to limiting theory, the problem of efficient sample selection using a DEA models to test the performance of the PE portfolio is a real discontinuous boundary and concave has not been successful since 2011. In order to solve this problem, we recommend a DEA method divided into business units based on the Markowitz model. A search algorithm is used to introduce to business units and prove their validity. In any business unit, the boundary is continuous and concave. Therefore, DEA models could be applied as PE evaluation. To this end, 25 companies from the companies listed on the Tehran Stock Exchange for the period 1394 to 1399 were selected as the sample size of statistics in data analysis. To analyzethe data, after classi cation and calculations were analysed by MATLAB software, the simulation results show that performance evaluation based on constraint theory based on DEA approach and the Markowitz model presented in this paper is efficient and feasible in evaluating the portfolio of constraint theory.
Majid Lotfi Ghahroud; Farzad Jafari; Saeid Tajdini; Mohammad Farajnezhad; Mohammad Qezelbash
Abstract
This study examines the dynamics of the Iranian foreign exchange market and its impact on the exchange rate used by traders, and not the official rate in Iran. The study aims to extend Fama's theory of market efficiency and proposes a new model to define the opposite point called "Historical bias". The ...
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This study examines the dynamics of the Iranian foreign exchange market and its impact on the exchange rate used by traders, and not the official rate in Iran. The study aims to extend Fama's theory of market efficiency and proposes a new model to define the opposite point called "Historical bias". The study applied the ARIMA and Markov switching models and dynamic conditional correlation to measure the speed of information circulation and to investigate the origin of the Iranian foreign exchange market's impact on the trader rate of the Dollar market. The study analyzed the convergence of the Iranian foreign exchange market based on different rates, the exchange rate used by traders, and the official rate and its effect on developing CBDC in Iran. The results of this study show that based on Fama's theory of market efficiency the foreign exchange market in Iran could have a 15% history-oriented bias, which is significant and would be an important problem for the launching of CBDC in Iran.
Asghar Abolhasani Hastiany; Alireza Zamanpour
Abstract
This study aims to optimize the portfolio using the genetic operator and network centralization. The statistical population of the study is the top 50 companies of Tehran Stock Exchange, in the first quarter of 2021, and to calculate the size of centrality, we used the difference in the overall performance ...
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This study aims to optimize the portfolio using the genetic operator and network centralization. The statistical population of the study is the top 50 companies of Tehran Stock Exchange, in the first quarter of 2021, and to calculate the size of centrality, we used the difference in the overall performance of each company compared to all the top companies, based on a standard hybridization indicator. Then based on the companies’ performance in the capital market, the geometric mean of risk and return of efficient companies are determined, and given the real limitations of the budget, the requirements and expectations of the investors compared to the market’s performance and the risk-free investment, the problem of decision-making for the composition of the investment in the form of a multi-purpose paradigm is formulated. By using the modified optimization algorithm and the genetic algorithm with dual operators, we optimized the investment’s composition. Finally, we use the compound linear regression with data analysis approach to evaluate the effect of individual and systemic operators on determining the investment strategy, and the results represented the positive effect of these two operators.
Ali Safdari-Vaighani; Pooya Garshasebi
Abstract
The financial markets reveal stylized facts that could not be captured by Black-Scholes partial differential equations (PDEs). In this research, we investigate 3/2 stochastic volatility to pricing options which is more compatible with the interpretation of implied volatility. Numerical study and ...
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The financial markets reveal stylized facts that could not be captured by Black-Scholes partial differential equations (PDEs). In this research, we investigate 3/2 stochastic volatility to pricing options which is more compatible with the interpretation of implied volatility. Numerical study and calibrations show that the 3/2 model incorporating jumps effectively encompasses key market characteristics attributed. However, it requires more estimating parameters in comparison to the pure diffusion model. Stochastic volatility models with jumps describe the log return features of the financial market although more parameters are involved in estimations.
Samaneh Bani Asadi; Azim Rivaz
Abstract
The European option can be exercised only at the expiration date while an American option can be exercised on or at any time before the expiration date.In this paper, we will study the numerical solutions of a class of complex partial differential equations (PDE) systems with free boundary conditions. ...
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The European option can be exercised only at the expiration date while an American option can be exercised on or at any time before the expiration date.In this paper, we will study the numerical solutions of a class of complex partial differential equations (PDE) systems with free boundary conditions. This kind of problems arise naturally in pricing (finite-maturity) American options, which is applies to a wide variety of asset price models including the constant elasticity of variance (CEV), hyper-exponential jump-diffusion (HEJD) and the finite moment log stable (FMLS) models. Developing efficient numerical schemes will have significant applications in finance computation. These equations have already been solve by the Hybrid Laplace transformfinite difference methods and the Laplace transform method(LTM). In this paper we will introduce a method to solve these equations by Tau method. Also, we will show that using this method will end up to a faster convergence. Numerical examples demonstrate the accuracy and velocity of the method in CEV models.
Maryam Moradi; Najme Neshat; Amir Mohammad Ahmadzade Semeskande
Abstract
Safe investment can be experienced by incorporating human experience and modern predicting science. Artificial Intelligence (AI) plays a vital role in reducing errors in this winning layout. This study aims at performance analysis of Deep Learning (DL) and Machine Learning (ML) methods in modellingand ...
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Safe investment can be experienced by incorporating human experience and modern predicting science. Artificial Intelligence (AI) plays a vital role in reducing errors in this winning layout. This study aims at performance analysis of Deep Learning (DL) and Machine Learning (ML) methods in modellingand predicting the stock returns time series based on the return rate of previous periods and a set of exogenous variables. The data used includes the weekly data of the stock return index of 200 companies included in the Tehran Stock Exchange market from 2016 to 2021. Two Long Short-Term Memory (LSTM)and Deep Q-Network (DQN) models as DL processes and two Random Forest (RF) and Support Vector Machine (SVM) models as ML algorithms were selected. The results showed the superiority of DLalgorithms over ML, which can indicate the existence of strong dependence patterns in these time series, as well as relatively complex nonlinear relationships with uncertainty between the determinant variables. Meanwhile, LSTM with R-squared equals to 87 percent and the analysis of the results of five other evaluation models have shown the highest accuracy and the least error of prediction. On the other hand, the RF model results in the least prediction accuracy by including the highest amount of error.
Shohre Hadidifard; Mona Parsaei; Nafiseh Shahmoradi
Abstract
The substitution hypothesis postulates that various corpo- rate governance forms and dividend disbursements serve as alternatives. Given that transparent information disclosure mitigates agency issues by lessening information asymmetry and fortifying corporate governance, this study aims to explore the ...
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The substitution hypothesis postulates that various corpo- rate governance forms and dividend disbursements serve as alternatives. Given that transparent information disclosure mitigates agency issues by lessening information asymmetry and fortifying corporate governance, this study aims to explore the influence of Material Information Dis- closure which includes Groups A, B and Other Cases—characterized by their promptitude and significance—on dividends. Examining the period from 2018 to 2021 and encompassing a sample of 173 listed firms from the Tehran Stock Exchange, the findings affirm the substitution hypothesis. Moreover, Board independence is identified as a moderator in the rela- tionship between Material Information Disclosures and dividend. Fur- thermore, the findings indicate that during the Covid-19 period, Group A and Other Cases were more potent factors for dividend reduction than Group B disclosure.
Asma Khadimallah; Fathi Abid
Abstract
This paper has potential implications for the management of the bank. We examine a bank capital structure with contingent convertible debt to improve financial stability. This type of debt converts to equity when the bank is facing financial difficulties and a conversion trigger occurs. We use a leverage ...
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This paper has potential implications for the management of the bank. We examine a bank capital structure with contingent convertible debt to improve financial stability. This type of debt converts to equity when the bank is facing financial difficulties and a conversion trigger occurs. We use a leverage ratio, which is introduced in Basel III to trigger conversion instead of traditional capital ratios. We formulate an optimization problem for a bank to choose an asset allocation strategy to maximize the expected utility of the bank's asset value. Our study presents an application of stochastic optimal control theory to a banking portfolio choice problem. By applying a dynamic programming principle to derive the HJB equation, we define and solve the optimization problem in the power utility case.The numerical results show that the evolution of the optimal asset allocation strategy is really affected by the realization of the stochastic variables characterizing the economy. We carried out a sensitivity analysis of risk aversion, time and volatility. We also reveal that the optimal asset allocation strategy is relatively sensitive to risk aversion as well as that the allocation in CoCo and equity decreases as the investment horizon increases. Finally, sensitivity analysis highlights the importance of dynamic considerations in optimal asset allocation based on the stochastic characteristics of investment opportunities.
Moslem Peymany
Abstract
This study emphasizes on the mathematical modeling procedure of stock price behavior and option valuation in order to highlight the role and importance of advanced mathematics and subsequently computer software in financial analysis. To this end, following price process modeling and explaining the procedure ...
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This study emphasizes on the mathematical modeling procedure of stock price behavior and option valuation in order to highlight the role and importance of advanced mathematics and subsequently computer software in financial analysis. To this end, following price process modeling and explaining the procedure of option pricing based on it, the resulting model is solved using advanced numerical methods and is executed by MATLAB software. As derivatives pricing models are based on price behavior of underling assets and are subject to change as a result of variation in the behavior of the asset, studying the price behavior of underlying asset is of significant importance. A number of such models (such as Geometric Brownian Motion and jump-diffusion model) are, therefore, analyzed in this article, and results of their execution based on real data from Tehran Stock Exchange total index are presented by parameter estimation and simulation methods and also by using numerical methods.
Parissa Ghonji; Ghadir Mahdavi; Mitra Ghanbarzadeh
Abstract
Insurance companies routinely conduct assessments to estimate loss reserves, crucial for anticipating liabilities arising from claim settlements. These estimations are particularly sensitive to the temporal dynamics of claims processing, encompassing the duration from filing to resolution. In this study, ...
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Insurance companies routinely conduct assessments to estimate loss reserves, crucial for anticipating liabilities arising from claim settlements. These estimations are particularly sensitive to the temporal dynamics of claims processing, encompassing the duration from filing to resolution. In this study, advanced cross-sectional regression techniques are employed, leveraging cargo insurance market data to gauge reported loss reserves. The comprehensive model integrates various influencing factors such as written premiums, paid claims, reinsurance issued premiums, inflation rates, and return on investment. Notably, the analysis unveils a non-significant negative association between inflation rates and loss reserves. Additionally, a negative correlation is observed between paid claims and loss reserves, while a statistically significant positive relationship emerges between written premiums and loss reserves, shedding light on intricate patterns within the insurance market.
Mehrdokht Khani; Abdolsadeh Neisy
Abstract
In this paper, we first present a nonlinear structural model for pricing mortgage-backed securities. These derivatives are considered to be the primary cause of the 2008 financial crisis that was raised in the United States. We focus our work on pass-through mortgages, which pay both the principal and ...
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In this paper, we first present a nonlinear structural model for pricing mortgage-backed securities. These derivatives are considered to be the primary cause of the 2008 financial crisis that was raised in the United States. We focus our work on pass-through mortgages, which pay both the principal and interest to the investors. We begin our work by introducing the factors that affect the market of mortgage-backed securities. Then, by applying some assumptions and conditions to the parameters of the initial model, and without the loss of generality, we show that this model can be greatly simplified. We focus our attention on how the change in interest rates can affect the value of mortgage-backed securities. Various numerical methods can be used to solve the reduced model that is achieved. We adapt the mesh-less method of radial basis functions to solve the reduced model. The numerical results indicate that the method that we have used can capture the market trends in a specific interval.
Fathi Abid; Ons Triki; Asma Khadimallah
Abstract
This paper investigates the effects of contingent capital, a debt instrument that automatically converts into equity if the value of the asset is below a predetermined threshold on the pricing process of a bank assets’. A traceable form of the contingent convertible bond is analyzed to find a closed-form ...
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This paper investigates the effects of contingent capital, a debt instrument that automatically converts into equity if the value of the asset is below a predetermined threshold on the pricing process of a bank assets’. A traceable form of the contingent convertible bond is analyzed to find a closed-form solution for the price of this bond using barrier and growth options. We examine the interaction between growth options and financing policy in a dynamic business model. The contribution of this paper is to extend Hilscher and Raviv [10] and Tan and Yang [22] research to include the evaluation of all aspects of banks' financial structure, with an emphasis on explicitly calculating the likelihood of the default event. The fundamental theorem of asset pricing and the first passage of time method have been used to generate closed formulas that are amenable to practical analysis. The potential benefits from contingent capital as financing and risk management instrument can be assessed through their contribution to reducing the probability of default. The appropriate choice of contingent capital parameters, the rate, and the conversion threshold can reduce shareholders incentives to change risk.
Azadeh Ghasemifard; Seddigheh Banihashemi; Afshin Babaei
Abstract
The aim of this paper is to numerically price the European double barrier option by calculating the governing fractional Black-Scholes equation in illiquid markets. Incorporating the price impact into the underlying asset dynamic, which means that trading strategies affect the ...
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The aim of this paper is to numerically price the European double barrier option by calculating the governing fractional Black-Scholes equation in illiquid markets. Incorporating the price impact into the underlying asset dynamic, which means that trading strategies affect the underlying price, we consider markets with finite liquidity. We survey both cases of first-order feedback and full feedback. Asset evolution satisfies a stochastic differential equation with fractional noise, which is more realistic in markets with statistical dependence. Moreover, the Sinc-collocation method is used to price the option. Numerical experiments show that the results highly correspond to our expectation of illiquid markets.
Mahboubeh Aalaei; Khadijeh Ebrahimnezhad
Abstract
In this article, fuzzy random variables are used to model interest rate uncertainty used in the calculation of whole life insurance premiums, and calculate the effect of this uncertainty on the price of life settlements. The fuzzy results obtained from deterministic and probabilistic pricing approaches ...
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In this article, fuzzy random variables are used to model interest rate uncertainty used in the calculation of whole life insurance premiums, and calculate the effect of this uncertainty on the price of life settlements. The fuzzy results obtained from deterministic and probabilistic pricing approaches have been compared with the results of the stochastic approach. Also, the results have been analyzed for Iran life table, which has been issued to insurance companies since 1400, and for France life table, which was previously used by insurance companies. In addition, since 5-year survival probability for each cancers in Iran was lower than in the United States, the probability adjustment coefficient for Iran was higher than that of the United States. In addition, the interval obtained for the fuzzy probability price and the stochastic price for both Iran and France life tables are close to each other. But in most cases, the fuzzy price obtained based on the deterministic approach has a significant distance from the stochastic and fuzzy probability approaches. Also, the findings of the research indicate that the price calculated using the fuzzy deterministic approach for Iran life table is higher than France life table. While the results for fuzzy probabilistic approach and stochastic approach are completely opposite. In the other words, the price calculated for the Iran life table is lower than the France life table. This difference comes from the fact that the adjustment coefficients for these life tables are calculated for each person separately from related life tables.
Alireza Khalili Golmankhaneh; Karmina K. Ali; Resat Yilmazer; Mohammed K. A. Kaabar
Abstract
In this article, the price adjustment equation has been proposed and studied in the frame of fractal calculus which plays an important role in market equilibrium. Fractal time has been recently suggested by researchers in physics due to the self-similar properties and fractional dimension. We investigate ...
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In this article, the price adjustment equation has been proposed and studied in the frame of fractal calculus which plays an important role in market equilibrium. Fractal time has been recently suggested by researchers in physics due to the self-similar properties and fractional dimension. We investigate the economic models from the viewpoint of local and non-local fractal Caputo derivatives. We derive some novel analytical solutions via the fractal Laplace transform. In fractal calculus, a useful local fractal derivative is a generalized local derivative in the standard computational sense, and the non-local fractal Caputo fractal derivative is a generalization of the non-local fractional Caputo derivative. The economic models involving fractal time provide a new framework that depends on the dimension of fractal time. The suggested fractal models are considered as a generalization of standard models that present new models to economists for fitting the economic data. In addition, we carry out a comparative analysis to understand the advantages of the fractal calculus operator on the basis of the additional fractal dimension of time parameter, denoted by $alpha$, which is related to the local derivative, and we also indicate that when this dimension is equal to $1$, we obtain the same results in the standard fractional calculus as well as when $alpha$ and the nonlocal memory effect parameter, denoted by $gamma$, of the nonlocal fractal derivative are both equal to $1$, we obtain the same results in the standard calculus.
Hadi Bagherzadeh Valami
Abstract
In this paper, considering risks of a portfolio such as mean return, variance of returns, and moments of higher order as output variables including desirable and undesirable outputs, we introduce a non-radial and slack based score to measure efficiency of portfolios. Using the present measure, ranking ...
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In this paper, considering risks of a portfolio such as mean return, variance of returns, and moments of higher order as output variables including desirable and undesirable outputs, we introduce a non-radial and slack based score to measure efficiency of portfolios. Using the present measure, ranking of portfolios is provided which is consistent with standard risk-return ratios in finance. We provide illustrations to show the effects of this contribution on the measures of technical efficiency and ranking of portfolios on a sample set of daily prices of banks and credit institutions listed on the first stock market of Tehran Securities Exchange (TSE). The advantage of this paper is to present a model based on stock market returns and risk, which is based on the DEA view of the production possibility set. Of course, in making it, the quadratic property of variance and the origin of coordinates have been used as a moderating point.
Hamid Abbaskhani; Asgar Pakmaram; Nader Rezaei; Jamal Bahri Sales
Abstract
Despite the growing need for research on the going concern and bankruptcy of companies, most of the conducted studies have used the approach of quantitative data for predicting the going concern and bankruptcy of companies; on the other hand, it is possible to manage these quantitative data by company ...
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Despite the growing need for research on the going concern and bankruptcy of companies, most of the conducted studies have used the approach of quantitative data for predicting the going concern and bankruptcy of companies; on the other hand, it is possible to manage these quantitative data by company managers. As a result, there appears to be a need to examine alternative methods for predicting going concern and bankruptcy based on qualitative data from the auditor's report. The purpose of this research is to determine the ability to predict the going concern of the companies using quantitative and qualitative data. The study period was from 2011 to 2021, with a sample of 54 companies admitted to the Tehran Stock Exchange. The results of the first hypothesis test show that the coefficient of determination of text-mining approach model prediction with the presence of a life cycle variable is greater than the determination coefficient of text-mining approach model prediction with the presence of a company size variable. The test of the second hypothesis shows that the difference in the increasing explanatory power of the first model compared to the second model in the companies accepted in the stock exchange is significant.
Moch. Fandi Ansori; Nurcahya Yulian Ashar
Abstract
One of central bank regulations that has direct impact on the banking industry is loan benchmark interest rate. Banks use it as a reference rate to determine their loan interest rate. In this paper, we study the role of loan benchmark interest rate on banking loan dynamics. The model is in the form of ...
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One of central bank regulations that has direct impact on the banking industry is loan benchmark interest rate. Banks use it as a reference rate to determine their loan interest rate. In this paper, we study the role of loan benchmark interest rate on banking loan dynamics. The model is in the form of a difference equation that follows a gradient adjustment process. We study the loan equilibrium's stability via bifurcation theory. It is found that the benchmark rate must be set between the flip and transcritical values. Some numerical simulations are performed to confirm the analytical result. The stochastic case of the benchmark rate is also studied. In addition, we perform numerical sensitivity analysis of the benchmark rate with the model's other parameters.
S. Pourmohammad Azizi; RajabAli Ghasempour; Amirhossein Nafei
Abstract
This study explores the application of dynamic systems for modeling and valuing catastrophe bonds to establish a more intelligent and adaptive approach to determining their volatility parameter. These financial instruments hold significant importance for insurance companies in safeguarding against the ...
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This study explores the application of dynamic systems for modeling and valuing catastrophe bonds to establish a more intelligent and adaptive approach to determining their volatility parameter. These financial instruments hold significant importance for insurance companies in safeguarding against the risk of insolvency stemming from the escalating frequency and severity of natural disasters worldwide. Employing mathematical principles, this research formulated a pricing partial differential equation and introduced a dynamic system for its resolution. The damage model was assumed to follow a stochastic process, and a radial basis neural network was utilized to estimate the volatility parameter of this stochastic process by leveraging historical data. The study scrutinized the pricing framework of catastrophe bonds related to floods and storms in China, ultimately demonstrating that the proposed methodology proved effective and computationally efficient when contrasted with alternative approaches.
Mehran Kaviani; Ali Mohammad Ghanbari; Moslem Peymany
Abstract
Business expansions being engaged in variety of industries in purpose of getting bigger market share, role of corporate governance within the financial decision. One of the important issues in corporate governance is block trading with purpose of control or invest in target firms. If the plan is to acquire ...
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Business expansions being engaged in variety of industries in purpose of getting bigger market share, role of corporate governance within the financial decision. One of the important issues in corporate governance is block trading with purpose of control or invest in target firms. If the plan is to acquire majority of shares and decision making, block trade along with paying premium are of great importance. The purpose of this study is to determine factors affecting on premium of block trading of firms listed in Tehran Stock Exchange or Iran Fara Bourse. Due to the significant impact of companies in refining and petrochemical sectors on whole economy and capital market, this kind of firms should have been considered specially. Multivariate regression and ordinary least squares (OLS) method was used to study the model related to the influential factors on the paid premium of the block trading. Finding of the research shows that financial structure, features of block trading, profitability and efficiency are among factors affecting on premium and also the type of company does not effect on premium.
Shokouh Shahbeyk
Abstract
In this paper, we discuss some of the concepts of robustness for uncertain multi-objective optimization problems. An important factor involved with multi objective optimization problems is uncertainty. The uncertainty may arise fromthe estimation of parameters in the model, error of computation, the ...
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In this paper, we discuss some of the concepts of robustness for uncertain multi-objective optimization problems. An important factor involved with multi objective optimization problems is uncertainty. The uncertainty may arise fromthe estimation of parameters in the model, error of computation, the structure of a problem, and so on. Indeed, some parameters are often unknown at the beginning of solving a multi-objective optimization problem. One of the mostimportant and popular approaches for dealing with uncertainty is robust optimization. Markowitz's portfolio optimization problem is strongly sensitive to the perturbations of input parameters. We consider Markowitz's portfolio optimization problem with ellipsoid uncertainty set and apply set-based minmax and lower robust efficiency to this problem. The concepts of robust efficiency are used in the real stock market and compared to each other. Finally, the increase and decrease effects of uncertainty set parameters on these robust efficient solutions are verified.
Nafiseh Shahmoradi; Hasan Ghalibaf Asl
Abstract
A large number of investors have been attracted to the Iran Mercantile Exchange as a result of launching Bahar Azadi Coin future contracts, also known as gold coin future contracts, since 2007. The nature of gold price as a physical-commodity and financial asset, as well as other contributing factors ...
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A large number of investors have been attracted to the Iran Mercantile Exchange as a result of launching Bahar Azadi Coin future contracts, also known as gold coin future contracts, since 2007. The nature of gold price as a physical-commodity and financial asset, as well as other contributing factors to the gold futures market, extremely complicates the analysis of the relationship between the underlying variables.One of the methods to forecast the price volatility is the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model. However, the high percentage of errors in such prediction has forced researchers to apply a variety of techniques in the hope of more accurate projections. Similarly, in this study, a hybrid model of the GARCH and Artificial Neural Network model (ANN) was used to predict the volatility of gold coin spot and future prices in the Iran Mercantile Exchange.In this study, variables such as global gold price, spot or future gold coin price (depending on which one is analyzed), US Dollar/IR Rial, world price of OPEC crude oil, and Tehran Stock Exchange Index were considered as factors affecting the price of gold coin. The results of the study indicate that the ANN-GARCH model provides a better prediction model compared to the Autoregressive models. Moreover, the ANN-GARCH model was utilized to compare the predictive power of spot and future gold coin prices, and it revealed that gold coin future price fluctuations predicted spot price of gold coin more accurately.
Alexey Zaytsev
Abstract
Modern research often requires the use of economic models with multiple agents that interact over time. In this paper we research overlapping generations models, hereinafter OLG. In these models, the phenomenon of the multiplicity of long-term equilibrium may arise. This fact proves to be important for ...
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Modern research often requires the use of economic models with multiple agents that interact over time. In this paper we research overlapping generations models, hereinafter OLG. In these models, the phenomenon of the multiplicity of long-term equilibrium may arise. This fact proves to be important for the theoretical justification of some economic effects, such as the collapse of the market and others. However, there is little theoretical research on the possibility of multiple equilibria in these models. At the same time, the works that exist are devoted to models with only few periods. This is due to the fact that the complexity of algorithms that calculate all long-term equilibria grows too fast with realistically selected lifespan values. However, solutions of some OLG models after the introduction of additional variables can become polynomial systems. Thus it is possible to represent many long-term equilibria as an algebraic variety. In particular, the Gr¨obner basis method became popular. However, this approach can only be used effectively when there are few variables. In this paper we consider the task of finding long-term equilibrium in overlapping generations models with many periods. We offer an algorithm for finding the system’s solutions and use it to investigate the presence of multiple solutions in realistically calibrated models with long-lived agents. We also examine these models for multiple equilibria using the Monte Carlo method and replicate previously known results using a new algorithm.
