EconomicsMedicine

V. Radhamani, D. Manju, P. Bobby, M. Javagar, V. Nivetha, P. Rinubha

2022Ymer

DOI: 10.37896/ymer21.07/14

tlooto Summary

Predicting gold rates with live data and investing on golds at the right time is quite useful, and the random forest method provides more accurate results.

Abstract

Since ancient times, gold has been cherished for its value and worth. Back then, gold was primarily used for trading purposes and as a method of remuneration. But now, it is looked upon as an investment and is found to exhibit the wealth of a country. Expensive metals like gold, in critical times, are used to assure the reimbursement of money borrowed as well. Thereby, gold is not only found to behold the rich, but also the poor. During pandemic crises, like the Covid-19, investments on gold in early times, might have a beneficial impact. Hence, predicting gold rates with live data and investing on golds at the right time is quite useful. Various machine learning algorithms like the linear regression, decision tree and random forest have been used to predict the gold rates. By using different algorithms, we've come to a conclusion that the random forest method provides more accurate results. Keywords: Gold rates, prediction, live gold rates, random forest, decision tree, linear regression, predictive analytics

Citation format

RADHAMANI, V., et al. Gold price prediction using ml algorithms. Ymer, 2022, 21.