List of Articles Copula Functions

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  1 - Modeling and Bivariate Analysis of Meteorological Drought Using Data Generation with Climate Change Approach (Case Study: Lake Urmia)
  Farzad Khezri Mohsen Irandost Navid Jalalkamali Najme Yazdanpanah
  10.30495/wsrcj.2021.19213
  Background and Aim: Climate Climate change is one of the important factors that will affect different parts of human life on the planet and will have detrimental effects on the environment, socio-economic, and especially water resources. Knowledge of climate change More

  Background and Aim: Climate Climate change is one of the important factors that will affect different parts of human life on the planet and will have detrimental effects on the environment, socio-economic, and especially water resources. Knowledge of climate change can provide comprehensive plans in various areas of management regarding the monitoring of droughts and their potential risks. Drought can occur in any area, even wetlands. This phenomenon depends on various factors and parameters and one of the most important symbols of this phenomenon is the occurrence of drought is a decrease in rainfall and therefore the analysis of precipitation data is of special importance to study drought. The purpose of this study is to analyze drought variables using SPI and SPImod indices and detailed functions.Method:  In this study, to model the multivariate analysis of drought in Lake Urmia basin using RCP8.5 and RCP4.5 representative concentration pathway scenarios, data and models of atmospheric circulation of historical data (1991-2010) for three near horizons (2030- 2011), medium (2065-2046) and round (2099-2080) were simulated and produced. Then, using SPImod index and copula functions, drought multivariate analysis was performed in MATLAB software environment. In general, first, using the mentioned indicators (two indicators, SPI and SPImod), the characteristics of drought intensity and duration were extracted, then, using coding in MATLAB software environment, eight families of Archimedean detailed functions were used.Results: The results of multivariate analysis showed that the Joe copula function is the best copula function for drought multivariate analysis (For analysis of both severity and duration of drought for the study area). Also, the results of probability and the joint return period showed that in the coming periods, at least droughts of the same level as historical droughts and even more severe will occur. Thus, by studying the period of combined and conditional returns and Kendall, the results showed that at a certain critical probability level, the amount of Kendall return period is much more than the standard return period, so that this difference increases with increasing that certain amount.Conclusion: The results obtained with the climate change approach on the meteorological drought of Lake Urmia showed that in the coming periods we will see an increase in temperature, which will affect the rate of trade in the region and water resources, on the other hand, because the data Meteorology and hydrology are used to calculate the types of droughts, so droughts affected by climate change will be so that in future periods 46% to 48% of the months will be dry in different horizons. Finally, the results of the time series of indicators showed that during the statistical period at least 40% of the months were dry and this intensity of droughts in the Urmia station is much higher than others. The modified SPI largely eliminates the disadvantages of conventional SPIs and takes into account seasonal variations in precipitation in the calculation of the SPI index. Manuscript profile
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  2 - Multivariate Analysis of Hydrological Droughts in Urmia Lake basin Using Artificial Data Generation Technique and Copula Functions
  Babak Shahinejad Zahra Shams Zabihollah Khani temeliyeh Azadeh Arshia
  10.30495/wsrcj.2022.20328
  Background and Aim: From a hydrological point of view, measuring the flow of rivers, lakes and groundwater is a measure of drought and there is a baseline time between the lack of rainfall and the decrease of running water of inlets and lakes and groundwater. More studi More

  Background and Aim: From a hydrological point of view, measuring the flow of rivers, lakes and groundwater is a measure of drought and there is a baseline time between the lack of rainfall and the decrease of running water of inlets and lakes and groundwater. More studies have been done on meteorological droughts compared to hydrological droughts. Therefore, the purpose of this study is multivariate analysis of hydrological droughts in Lake Urmia basin using artificial data generation models and Copula functions. Therefore, using a combination of the above methods for the analysis of hydrological droughts was used as a new method for the analysis of hydrological droughts.Method:In this study, in order to multivariate analysis of hydrological droughts in the Urmia Lake basin, the flow data of 28 hydrometric stations in which the flow regime is real were used during a statistical period of 40 years (1978-2017). Also, Ar (1) model was used to generate artificial data and SDImod index was used for drought analysis. For this purpose, artificial data were generated in 1000 sequence. Since univariate drought analysis and analysis based on historical data can not show the horizontal of future droughts alone, so using the Ar (1) model, annual data were generated and then using the model The Valencia and Schakke generated monthly artificial data. Then drought characteristics (intensity and duration) were extracted for both historical and generation data series and common distributions in hydrology were fitted to intensity, duration and flow data. Then the transfer probability matrix and their steady state condition matrix (SSC) were also calculated. Also, multivariate analysis of hydrological droughts was performed using ten Archimedean Copula functions. The above coding was done in MATLAB software environment.Results: The results of this study showed that after examining the homogeneity of data and their static test, most of the data had the necessary homogeneity and the results of data homogeneity showed that the coefficient of explanation was above 0.9 and the results of static test and Their trend showed that the data were within the allowable range of 1.2 ±2.1 and ±1.96. The results of fitting the data on the common statistical distributions showed that the Log Pearson Type3 (LP3) function was known as the superior distribution functions on the flow data and the gamma and exponential distribution functions on the severity and duration of the drought, respectively. The number of drought periods based on different scales of SDImod index showed that for different periods the number of drought periods for short-term scales was more than long-term scales. Also, the average intensity and duration of drought for generated and historical data indicate an increase in the intensity of drought for generated data compared to historical data. The results of classifying drought periods for historical and generated data showed that approximately 68% of the data were in the normal range during the statistical period and 32% were other classes. The result of the Copula functions showed that the Joe Copula function in the first order and Filip Gumble and Galambos functions in the next order were known as the superior Copula functions.Conclusion: Finally, the results showed that the artificial data generation models for annual and monthly data for statistical years less than 30 years maintain the statistical characteristics of mean, standard deviation, skewness and correlation between two consecutive months, while increasing The number of statistical years of model performance becomes more favorable. The cumulative probability of non-annual drought and the probability of normal and wet season in hot months of the year is higher than other months of the year. Also, with increasing periods of drought, the cumulative probability of non-drought increases, so that with increasing periods, this probability decreases and becomes almost zero. The results of the joint and conditional return periods as well as the Kendall return period showed that the probability of drought occurring in future periods is expected to be at least similar to the historical data. The results also showed that the Joe Copula function was recognized as the superior Copula function for historical and generated data. Accordingly, the theoretical Copula function is close to the 45 degree angle bisector against the experimental Copula function. Manuscript profile
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  3 - Latent Volatility Modeling and Bayesian Analysis of stochastic Volatility of Intraday Data of Tehran Stock Exchange Index Based on Markov Monte Carlo Chain
  Saeed Shahriyari Peyman Iman zadeh Mehdi Khoshnood
  In this study, latent volatility modeling and Bayesian analysis of stochastic Volatility of intraday data of Tehran Stock Exchange index based on Markov Monte Carlo chain in uncertainty conditions (downward crisis of stock market index) have been developed. The method o More

  In this study, latent volatility modeling and Bayesian analysis of stochastic Volatility of intraday data of Tehran Stock Exchange index based on Markov Monte Carlo chain in uncertainty conditions (downward crisis of stock market index) have been developed. The method of the current research is a correlational description. For this purpose, at first, the distribution of the logarithm of the squared return as a measure of the realized volatilities was simulated using the stochastic Volatility model to obtain the latent volatilities, and then by using the hybrid MCMC-Copula model, the parameters affecting the stochastic Volatilities were identified and estimated in the training phase. Finally, using the results obtained from the training phase, in the test phase, the comparison of Copula and GARCH models was done. The results showed that the Copula Gumble, Galambos, Joe, Clayton and Frank provide similar and lower MSE and RMSE indices than the GARCH base model, and therefore the model based on copula provides the possibility of serial dependence in the latent volatility process. The findings of the current research can be useful for financial and investment companies for portfolio management and portfolio management in different conditions of market volatilities in order to achieve the investor's goals and increase the value of the portfolio. Manuscript profile
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  4 - Portfolio optimization by using the Copula Approach and multivariate conditional value at risk in Tehran Stock Exchange
  Mirfeiz Fallahshams Amir Sadeghi
  One of the main problems of shareholders in the stock market is the discovery, quantification and calculation of market risk. In many studies, one-way distributions are used to estimate risk metrics that usually do not give credible results to the investor. Because the More

  One of the main problems of shareholders in the stock market is the discovery, quantification and calculation of market risk. In many studies, one-way distributions are used to estimate risk metrics that usually do not give credible results to the investor. Because the distribution of assets is generally a broad sequence, and the results of computations are not acceptable for the consideration of the univariate normal distribution and the use of parametric methods. In this paper, using the Coppola theory, we calculate risk-weighted value (VaR) and conditional value-at-risk (CVaR). After estimating the multivariate T- Copula and the normal distribution of multivariate, the Monte Carlo method is used to generate a scenario for calculating the variance of the portfolio as well as risk estimation. Also, the calculations performed using the loss function method are tested and the accuracy of the approximations is verified. Finally, the minimum value of the copula based on the variance of the portfolio as well as its CVaR value is considered as the function of the portfolio planning, and the optimal portfolio is obtained by considering the weight of each share index. In the calculation of the 1200 index, we consider a sample basket of different industries, by calculating VaR and CVaR with confidence levels of 95 and 99 percent. The results obtained from the efficiency and reliability of the Monte Carlo simulation by the Copula T-Student versus the normalized multivariate distribution. Manuscript profile
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  5 - The Analysis and Test of Spillover and Volatility of Global Markets for Petrochemical Products and Base Metals (Based on Copula family models)
  Mahsa Banakar Hashem nikoomaram Hasan Ghalibaf Asl Mehrzad Minouie
  Fluctuations in commodity prices in global markets have always influenced the behavior and decisions of investors in financial markets. In this research, using the Copula family models, financial contagion or volatility spillover on global price of petrochemical product More

  Fluctuations in commodity prices in global markets have always influenced the behavior and decisions of investors in financial markets. In this research, using the Copula family models, financial contagion or volatility spillover on global price of petrochemical products and base metals on the on the stock price index of eight selected industries of Tehran Stock Exchange listed companies during a period of 10 years (2008-2018) has been reviewed. The research method is descriptive-analytical in nature and applied in terms of purpose. The research hypotheses were tested using an econometric approach based on Copula models and programming in MATLAB software. The results show that the effects of overflow of these variables on the index of selected industries are significant but different.Examination of different models of Copula method showed that T-Student model is most suitable for transmitting spillover effects, which indicates the symmetrical effects of price variables in global markets of petrochemical products and base metals on the index performance of selected industries. And then Clayton and Gumble models are in the next rank. Manuscript profile
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  6 - Investment Portfolio Optimization of Insurance Companies with Copulas and Extreme Value Approach
  arash goodarzi reza Tehrani Ali souri
  This study determines the optimal investment portfolio of insurance companies by considering underwriting activities. investment decisions in insurance companies are affected by underwriting activities. In this paper, the investment optimization problem of insurers is m More

  This study determines the optimal investment portfolio of insurance companies by considering underwriting activities. investment decisions in insurance companies are affected by underwriting activities. In this paper, the investment optimization problem of insurers is modeled using the copula-based conditional risk value, taking into account the results of insurance activities. Also, since the emphasis is on tails of distribution, the probability distribution of variables in tails is estimated using Pareto distribution and in other parts of the distribution using the Empirical probability distribution. Data collected on monthly basis covers two periods in-sample, between 2006 to 2015 and out-of-sample, between 2016 to 2019.The findings show that the optimum portfolio includes eighty percent of risky assets (stock and real estate) and only twenty percent of risk-free assets (bank deposits) and it is outside the legal constraints set by Central Insurance Therefore, legal constraints prevent insurance companies from the optimal selection of investment portfolio. Also, the comparison of out-of-sample performance with in-sample performance of portfolios shows that portfolios based on copula functions have better and more robust performance than traditional models. Manuscript profile
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  7 - Modeling Extreme Dependence of Tehran Stock Exchange (TSE) to Crude Oil Price: An Approach based on Copula Functions
  Hamid Abrishami Mohsen Mehara Mojtaba Mohammadian
  10.30495/eco.2022.1949896.2614
  The objective of this study is to model the extreme dependence structure from the crude oil price to Tehran Stock Exchange (TSE) index. For this purpose, the conditional extreme value theory (C-EVT) was used to model the marginal distribution of returns on stock and oil More

  The objective of this study is to model the extreme dependence structure from the crude oil price to Tehran Stock Exchange (TSE) index. For this purpose, the conditional extreme value theory (C-EVT) was used to model the marginal distribution of returns on stock and oil market during the period 2008 to 2021. Then, the dependence structure of the extreme return was estimated by Copula models. The results showed that the crude oil market has contagion effects on the TSE. These effects are asymmetric and there is more dependence on the left tail. In other words, as crude oil price falls, decline of the total index is expected and these effects are greater when a positive simultaneous change occurs between variables. Due to the financial risks of the existence of contagion, considering structural extreme dependence can calculate the portfolio risk accurately and reliably. Therefore, it is suggested to pay attention to the structure of extreme dependencies between assets in order to optimize the portfolio. Manuscript profile
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  8 - The Analysis and Test of Spillover and Volatility Models in Tehran Stock Exchange (based on Copula family model)
  Mahsa Banakar Hashem Nikoomaram Hasan Ghalibaf Asl Mehrzad Minouei
  The present research examines the Financial Contagion or Volatility Spillover by financial assets such as exchange rates, gold and global variables on the stock market index. The correlation and Contagion between variables of global prices of gold, oil, and the dollar e More

  The present research examines the Financial Contagion or Volatility Spillover by financial assets such as exchange rates, gold and global variables on the stock market index. The correlation and Contagion between variables of global prices of gold, oil, and the dollar exchange rate on the index of 8 selected Tehran stock exchange industries over a period of 10 years (2008-2018) was examined. Method of the research is applied in terms of purpose and analytical-descriptive in terms of the nature. To test the research hypotheses using econometric approach based on Copula models, programming was performed in MATLAB software. The results of the show that the effects of volatility spillover of these variables on the index of selected industries are significant but different. The different models of the Copula method show that the Clayton and Gumbel models are most suitable for transmitting spillover effects in the upper and lower distribution of the range. The t-student model is in the next rank. In other words, the overflow effects of macro variables mostly affect one of the high (positive return) and low (negative return) domains, which indicates the existence of asymmetric effects on the return behavior of the selected industries of the stock exchange. Manuscript profile
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  9 - Modeling the latent Volatilities of the stock exchange index using the copula-stochastic Volatility model
  Saeed Shahriyari Peyman Iman zadeh mehdi khoshnood
  In this study, a hybrid copula-stochastic volatility model based on Monte-Carlo Markov chain is developed to evaluate the latent volatilities of the TSE Index. The data used to estimate the models include the values of the total index of the TSE from the beginning of 20 More

  In this study, a hybrid copula-stochastic volatility model based on Monte-Carlo Markov chain is developed to evaluate the latent volatilities of the TSE Index. The data used to estimate the models include the values of the total index of the TSE from the beginning of 2020 to the beginning of 2021 on a daily basis with a frequency of 30 minutes. Also, in order to determine the error, data from the date (03/27/2021) to (12/21/2021) has been used in 15-minute intervals. the square logarithm distribution of returns as a measure of realized volatilities is first simulated using a stochastic volatility model to obtain latent volatilities and then using a mixture of copula family distributions and the MCMC, modeling and estimation were performed in the training phase and finally in the test phase using out-of-sample data to estimate the stochastic volatility of the test phase was investigated. The results show that among the functions of Copula Gumble, Galambos, Joe, Clayton and Frank in the test phase, 3 Copula Gumble, Galambos, Joe have acceptable performance and among these functions, the Gumble-Stochastic Volatility based on MCMC with the lowest error rate among the out-sample data recorded better performance. Manuscript profile
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  10 - Testing of Reciprocal Transfer of Bubble in Stock Exchange, Currency and Gold Markets (A case study: in Iran Using Copula Functions)
  Yagoob Zahedi nader rezaei vadoud Najjari
  The main goal of this research is to investigate the formation and spread of bubbles in the financial markets of the stock exchange, currency and gold markets using semi-experimental studies, considering that previous studies in this field mostly study the effect of vol More

  The main goal of this research is to investigate the formation and spread of bubbles in the financial markets of the stock exchange, currency and gold markets using semi-experimental studies, considering that previous studies in this field mostly study the effect of volatility transmission or the effect of the return of one asset on the return of another market. Therefore, no study has been done in this field or it is limited; In this study, the data was collected in the period from 1389 to 1400 and was analyzed by descriptive and econometric statistical methods. The results of the analysis of the right-sequence unit root test show the existence of bubbles in all three markets under study. It shows the results of the analysis of vector auto-regression tests and copula (joint) functions. The structure of dependence between the three financial markets is quite dynamic and this dependence is greater when the market is in a developing situation than in a recession. Also, the sequential dependence between the gold coin and the exchange rate is much stronger than the dependence between the stock market and gold. Manuscript profile