Saeed Samadi; Nasrin Ebrahimmi; Fariba Aghili
Abstract
Abstract
Given that gold is a commodity sensitive and strategic and its global price has been trend over the past years, in this study, we investigated the factors influencing the price of gold coins. The most important factors that can influence the price of gold in Iran: Global gold prices, Inflation ...
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Abstract
Given that gold is a commodity sensitive and strategic and its global price has been trend over the past years, in this study, we investigated the factors influencing the price of gold coins. The most important factors that can influence the price of gold in Iran: Global gold prices, Inflation expectations, Exchange rate fluctuations, Fluctuations in the stock index and the international sanctions. Also consider these results can be useful for investors and planners as well.
Because of the importance of the foreign exchange market and stock market, in this study, an attempt is In addition to the gold price and exchange rate fluctuation on the stock prices of gold coins In Iran from April 1380 to September 1390 to be considered. In order to study ARCH model be used to measure volatility.
The results show that the factors affecting the price of coins, exchange rate in the short term and in the long term, the most effective agent. Global gold prices are also a factor in the long-term and short-term is positive and significant.Although the long-term coefficients are larger than the short-term coefficients. This shows that in the long-term price of gold coins reacts more fluctuations in exchange rates and changes in the world price of gold.
Saeed Samadi; Minoo Nazifi Naeini
Abstract
Gold is a strategic commodity and its price is influenced by many factors. Neural network method has a special ability to forecast ad good fitness, and markov switching regression has a special ability to distinguish the shocks and regime that switch and the exact date of fluctuations.
Methodology: ...
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Gold is a strategic commodity and its price is influenced by many factors. Neural network method has a special ability to forecast ad good fitness, and markov switching regression has a special ability to distinguish the shocks and regime that switch and the exact date of fluctuations.
Methodology: In this study the proper model for gold price fluctuation is modeling after identifying the factor that affect on gold price in the period of 1980-2011. For modeling we use two non linear method, neural network and Markov Switching regression. The goal of this paper is not comparing the result of two method but also is better modeling and better forecasting with each model separately.
Results The neural network in this study has two layers and switching regression has two regimes. The results indicate that the neural network methods are well able to predict fluctuations in the gold price. Switching regression can identify the shocks during switching yeas. And it is diagnosed that the period of being in low volatility state in the gold market is more of a high volatility state. The results show that in neural network model, among factors affecting the gold price, exchange rate and the world price of gold have the greatest impact and in Markov models, CPI has the highest importance and influence on the gold price.
Saed Samadi; Mohammad Vaez; Mohammad Reza Ghasemi
Abstract
Due to the high costs of collecting the quarterize or seasonal statistical information and the need of econometricians for Modeleny and short analysis, the National Statistical Institutes decided to obtain quarterize time series as indirect methods of the short-term dynamics of the annual data.
In ...
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Due to the high costs of collecting the quarterize or seasonal statistical information and the need of econometricians for Modeleny and short analysis, the National Statistical Institutes decided to obtain quarterize time series as indirect methods of the short-term dynamics of the annual data.
In this article, two alternative approaches based on related indicators and pure mathematics has been introduced and then after temporal disaggregation of government oil revenues, consumer price index and liquidity, the approaches compared to each other.
The empirical results indicated that Boot, Feibes and Lisman methods deliverd the better results for two series (government oil revenues and consumer price index), whereas Chow and Lin approach is more approprate for liquidity, based on MSE and r2 criteria.
Also this paper shows that the best choice approach for temporal disaggregation of economic time series is not always possible.
Saeed Samadi; Amene Shahidi; Farzaneh Mohammadi
Abstract
صنعت برق در جهان، بیش از صد سال قدمت دارد و هر کشوری با توجه به این‌که دولت یا بخش خصوصی به چه میزان در صنعت برق دخالت دارد، ساختار تولیدی را برای خود انتخاب کرده است. اما ...
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صنعت برق در جهان، بیش از صد سال قدمت دارد و هر کشوری با توجه به این‌که دولت یا بخش خصوصی به چه میزان در صنعت برق دخالت دارد، ساختار تولیدی را برای خود انتخاب کرده است. اما به طور کلی اکنون در سرتاسر جهان، صنعت برق در حال حرکت به سمت بازارهای رقابتی و فرآیند تجدید ساختار است. صنعت برق در ایران نیز در حال گذار از ساختار انحصار طبیعی به بازارهای رقابتی و ساختار جدیدی است که تولیدکنندگان برای فروش انرژی به رقابت با یکدیگر میپردازند. در چنین شرایطی مطالعه وضعیت اقتصادی صنعت برق در ایران از اهمیت ویژهای برخوردار است. در مقاله حاضر تلاش شده است با استفاده از مدلهای هم‌جمعی و ARIMA، تقاضای برق مصرفی در ایران برآورد و پیشبینی گردد. نتایج حاصل از تحقیق، گویای این واقعیت است که واکنش مصرفکنندگان برق در ایران به تغییرات درآمد و قیمت کاملاً محدود است و بنابراین نیاز به طراحی مقررات اقتصادی در بازار برق ایران وجود دارد. همچنین پیشبینیهای مربوط به تقاضای برق در آینده نشان میدهد که تقاضای سرانه برق با نرخ رشد سالانه 4/4 درصد افزایش مییابد که حاکی از رشد بسیار بالای مصرف برق در ایران میباشد.
