Gold Price Prediction using Machine Learning

Abstract

We predict future gold rates supported twenty two market variables victimization machine learning technique.One machine learning algorithm, random forest regression were used in analyzing these knowledge[1]. Historically, gold was used for supporting trade transactions around the world besides alternative modes of payment. Various states maintained and increased their gold reserves and were recognized as rich and progressive states. In present times, precious metals like gold area unit control with central banks of all countries to make sure re-payment of foreign debts, and conjointly to control inflation. Moreover, it conjointly reflects the Imoney strength of the country[2]. Besides government agencies, varied transnational firms and people have conjointly invested with in gold reserves. In ancient events of Asian countries, gold is in addition presented as gifts/souvenirs and in marriages, gold ornaments are conferred as gift in Republic of India. KEYWORDS: Price prediction, Machine Learning, Supervised Learning, Linear Regression, Python , Power Bi , Tableau.

Predictive Machine Learning models to estimate the price of gold [Modelos predictivos de Machine Learning para estimar el precio del oro]

“…The use of algorithms to estimate the price of Au has emerged as a strategic and advanced tool in the financial field (Ghule & Gadhave, 2022). In such a dynamic market and susceptible to various influences, the ability to anticipate fluctuations in the value of gold has become crucial for investors, analysts and traders (Makala & Li, 2021).…”

“…In summary, the application of a machine learning model to forecast the price of gold represents a significant advance in the ability to anticipate market fluctuations (Tebin & James, 2022). This approach not only seeks to improve the accuracy of predictions, but also to offer a valuable tool for those seeking to make informed decisions in an increasingly complex and dynamic financial environment.…”