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Estimation of Fractal Parameters of Tehran Stock Market Groups Time Series Using Discrete Wavelet Transform
Golmohammadpoor Azar, Kamran - 2014
Nowadays financial markets such as stock markets, gold and currency because of their significant returns are the investors’ main target. Their aim is to invest in a way that they can earn the highest profit. Among these markets, the stock market is of utmost importance since it deals with...
Persistent link: https://www.econbiz.de/10015244159
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بررسي عوامل موثر بر قيمت طلا و ارايه مدل پيش بيني قيمت آن به كمك شبكه هاي عصبي فازي
Sarfaraz, Leyla; Afsar, Amir - 2005
Throughout the history man has considered gold as a precious metal and its forcast has always been important. Traditional methods of forcast, e.g.Regresion, ARIMA, Exponential Smoothing, Moving Average, and methods of this kind have been applied. Only recently Artificial Intelligence, Neural...
Persistent link: https://www.econbiz.de/10015225469
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Day-ahead electricity price forecasting with emphasis on its volatility in Iran (GARCH combined with ARIMA models)
Pourghorban, Mojtaba; Mamipour, Siab - 2019
has complex behavior such as nonlinearity, nonstationarity, and high volatility. ARIMA is suitable in forecasting, but it … is not able to handle nonlinearity and volatility are existent in time series. Therefore, GARCH models are used to handle … volatility in the in time series forecasting. The proposed method is computed using the daily electricity price data of Iran …
Persistent link: https://www.econbiz.de/10015264450