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Forecasting is an important aid in effective and efficient planning. It is a current topic of growing important in business and economic analysis. It is an attempt is predict the future by examining the past. It consists of generating unbiased estimates of future magnitude of some variable, on the basis of past and present knowledge and experience. The present work of the reasearch is focused on development of some forecasting methods with special reference to Auto Regressive Integrated Moving Average (ARIMA) and Artificial Neural Network (ANN) methods along with residual measures. The empirical study is analyzed based on residual measures like MSE, RMSE and MAPE. It is shown that ANN out performs ARIMA in Forecasting stock market indices.
| Autorius: | P. Balasubramanyam, M. Venkataramanaiah, Balasiddamuni Pagadala, |
| Leidėjas: | LAP LAMBERT Academic Publishing |
| Išleidimo metai: | 2013 |
| Knygos puslapių skaičius: | 212 |
| ISBN-10: | 3659389692 |
| ISBN-13: | 9783659389696 |
| Formatas: | 220 x 150 x 13 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „On Some Aspects of Forecasting Methods: A Comparative Performance of Advanced Forecasting Models“
