Gold price estimation using a multi variable model

Abstract

Stock market analysis is a very popular area of research. Achieving good prediction in forecasting the stock markets is a very challenging task. The prediction of the future stock markets is done using cascading statistical models. This paper investigates the MCX commodity (Gold) on which the model is applied. Objective: To predict the trend of the gold commodity will remove the uncertainty in the future for the investors. Prediction techniques employed: Multi Variable Linear regression model, Time series models, Skewness and Kurtosis. Finding: The mammoth analysis of the attributes brings up the greater vision about the gold productand its importance to invest in that segment for it keeps the money in harmony with the real time drift in the price and its fluctuations. The data collected consists of commodity prices and volumes over the last 5 years on a monthly basis. The experimental results give us the predicted future values of the commodities. Inference: Prediction can also be valuable to support in planning about viable developments and provides a clear outcome for the future eventual market.

Cite this paper

@article{Sekar2017GoldPE, title={Gold price estimation using a multi variable model}, author={K. R. Sekar and Manav Srinivasan and K. S. Ravidiandran and Jay Sethuraman}, journal={2017 International Conference on Networks & Advances in Computational Technologies (NetACT)}, year={2017}, pages={364-369} }