Shashikant Suman, P. Kaushik, Sai Sri Nandan Challapalli, B. P. Lohani, Pradeep Kushwaha, A. Gupta
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Commodity Price Prediction for making informed Decisions while trading using Long Short-Term Memory (LSTM) Algorithm
Commodity markets are physical or virtual marketplaces where market players meet to buy or sell positions in commodities such as crude oil, gold, copper, silver, cotton, and wheat. People invest their hard-earned money based on some predictions to gain some profit from commodity market. Although, traditional methods such as technical analysis & fundamental analysis are very popular among traders, they are not as accurate as analysis by long short-term memory (LSTM) algorithm. In this paper, we have developed a model of well-known efficient LSTM algorithm to predict the commodity market price by utilizing a freely accessible dataset for commodity markets having open, high, low, and closing prices from historical data.