The primary object of this paper is to compare the traditional time series models with deep learning algorithm.The ARIMA model is developed to forecast Indian Gold prices using daily data for the period 2016 to 2020 obtained from World Gold Council.We fitted the ARIMA (2,1,2) model which exhibited the least AIC values. In the meanwhile, MLP, CNN and LSTM models are also examined to forecast the gold prices in India. Mean absolute error, mean absolute percentage error and root mean squared errors used to evaluate the forecasting performance of the models. Hence, LSTM model superior than that of the other three models for forecasting the gold prices in India
In recent years, there are many studies rely on forecasting with artificial neural networks. In this...
In this research, two hybrid systems are proposed whose components are the Autoregressive Integrated...
In recent years, the investors pay major attention to invest in gold market ecause of huge profits i...
Developing an accurate model of gold price is crucial as gold price have a great effect on the inves...
Forecast of prices of financial assets including gold is of considerable importance for planning the...
The main objective of this study is to predict monthly price of gold. The monthly sample data of gol...
In recent years, there are many studies rely on forecasting with artificial neural networks. In this...
Gold is one of the popular investment tools among people who are resistant to inflation. However, go...
An accurate prediction is certainly significant in financial data analysis. Investors have used a se...
Gold has always been valued throughout human history, playing a significant impact on the economy. ...
Gold is considered an important form of investment as love for the yellow metal has lured the people...
Gold is a valuable metal which is widely used to accumulate capital and also as the raw material for...
This study compares the accuracy of different forecasting techniques for gold and silver returns in ...
As one of the most frequently traded commodities in the world, gold has been hugely impacted by th...
This paper aims to use the tree-based methods for time series data forecasting and compare between D...
In recent years, there are many studies rely on forecasting with artificial neural networks. In this...
In this research, two hybrid systems are proposed whose components are the Autoregressive Integrated...
In recent years, the investors pay major attention to invest in gold market ecause of huge profits i...
Developing an accurate model of gold price is crucial as gold price have a great effect on the inves...
Forecast of prices of financial assets including gold is of considerable importance for planning the...
The main objective of this study is to predict monthly price of gold. The monthly sample data of gol...
In recent years, there are many studies rely on forecasting with artificial neural networks. In this...
Gold is one of the popular investment tools among people who are resistant to inflation. However, go...
An accurate prediction is certainly significant in financial data analysis. Investors have used a se...
Gold has always been valued throughout human history, playing a significant impact on the economy. ...
Gold is considered an important form of investment as love for the yellow metal has lured the people...
Gold is a valuable metal which is widely used to accumulate capital and also as the raw material for...
This study compares the accuracy of different forecasting techniques for gold and silver returns in ...
As one of the most frequently traded commodities in the world, gold has been hugely impacted by th...
This paper aims to use the tree-based methods for time series data forecasting and compare between D...
In recent years, there are many studies rely on forecasting with artificial neural networks. In this...
In this research, two hybrid systems are proposed whose components are the Autoregressive Integrated...
In recent years, the investors pay major attention to invest in gold market ecause of huge profits i...