ARIMA – the official site of the Central Bank of Nepal https://www.nrb.org.np the official Site of the Central Bank of Nepal Tue, 16 Jan 2024 06:49:38 +0000 en-US hourly 1 https://wordpress.org/?v=5.3.18 https://www.nrb.org.np/contents/uploads/2020/01/logo.jpg ARIMA – the official site of the Central Bank of Nepal https://www.nrb.org.np 32 32 Hybrids ARIMA-ANN models for GDP forecasting in Nepal https://www.nrb.org.np/er-article/hybrids-arima-ann-models-for-gdp-forecasting-in-nepal/?utm_source=rss&utm_medium=rss&utm_campaign=hybrids-arima-ann-models-for-gdp-forecasting-in-nepal Tue, 16 Jan 2024 06:49:38 +0000 https://www.nrb.org.np/?post_type=er-article&p=97865 Forecasting Nepal’s Gross Domestic Product (GDP) holds paramount importance for effective resource planning and allocation. In this research, Artificial Neural Networks (ANNs) have been introduced to predict the GDP time series, wherein the data have been dissected into linear and nonlinear components. The linear aspects have been handled by the ARIMA model, while the ANNs […]

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]]> Forecasting Nepal’s Gross Domestic Product (GDP) holds paramount importance for effective resource planning and allocation. In this research, Artificial Neural Networks (ANNs) have been introduced to predict the GDP time series, wherein the data have been dissected into linear and nonlinear components. The linear aspects have been handled by the ARIMA model, while the ANNs managed the nonlinear elements. Additionally, the study has delved into hybrid models, resulting in additive and multiplicative combinations of ARIMA and ANN. These hybrid models have aimed to enhance forecasting performance, minimize errors, and improve accuracy compared to standalone models. The findings revealed that both ANN and hybrid models surpassed other approaches in terms of prediction accuracy.

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]]> Forecasting NEPSE Index: An ARIMA and GARCH Approach https://www.nrb.org.np/er-article/forecasting-nepse-index-an-arima-and-garch-approach/?utm_source=rss&utm_medium=rss&utm_campaign=forecasting-nepse-index-an-arima-and-garch-approach Mon, 09 Dec 2019 17:41:57 +0000 http://uat.nrb.org.np/?post_type=er-article&p=558 In this study, an attempt has been made to demonstrate the usefulness of univariate time series analysis as both an analytical and forecasting tool for Nepali stock Market. The data set covers the daily closing value of NEPSE index for two and half years starting from the middle of 2012 to end 2015. The forecasting […]

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]]> In this study, an attempt has been made to demonstrate the usefulness of univariate time series analysis as both an analytical and forecasting tool for Nepali stock Market. The data set covers the daily closing value of NEPSE index for two and half years starting from the middle of 2012 to end 2015. The forecasting analysis indicates the usefulness of the developed model in explaining the variations, trend and fluctuations in the values of the price index of Nepali stock exchange. Explanation of the fit of the model is described using the Correlogram, Unit Root tests and ARCH tests, which finally confirm that the ARIMA and EGARCH are good in forecasting and predicting daily stock index of Nepal. Furthermore, it is inferred that the daily stock price index contains an autoregressive, seasonal and moving average components; hence, one can predict stock returns through the identified models.

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