An analysis of crude oil prices in the last decade (2011-2020): With deep learning approach

Author:

Sen AbhibasuORCID,Dutta Choudhury Karabi,Kumar Datta Tapan

Abstract

Crude Oil is one of the most important commodities in this world. We have studied the effects of Crude Oil inventories on crude oil prices over the last ten years (2011 to 2020). We tried to figure out how the Crude Oil price variance responds to inventory announcements. We then introduced several other financial instruments to study the relation of these instruments with Crude Oil variation. To undertake this task, we took the help of several mathematical tools including machine learning tools such as Long Short Term Memory(LSTM) methods, etc. The previous researches in this area primarily focussed on statistical methods such as GARCH (1,1) etc. (Bu (2014)). Various researches on the price of crude oil have been undertaken with the help of LSTM. But the variation of crude oil price has not yet been studied. In this research, we studied the variance of crude oil prices with the help of LSTM. This research will be beneficial for the options traders who would like to get benefit from the variance of the underlying instrument.

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference73 articles.

1. A Novel Agricultural Commodity Price Forecasting Model Based on Fuzzy Information Granulation and MEA-SVM Model;Y. Zhang;Mathematical Problems in Engineering,2018

2. Seasonal forecasting of agricultural commodity price using a hybrid STL and ELM method: Evidence from the vegetable market in China;T. Xiong;Neurocomputing,2018

3. Agricultural commodity futures prices prediction via long- and short-term time series network;H. Ouyang;Journal of Applied Economics,2019

4. Mustaffa, Z., Yusof, Y. and Kamaruddin, S., 2021. Enhanced artificial bee colony for training least squares support vector machines in commodity price forecasting.

5. A comparison of artificial neural network and time series models for forecasting commodity prices;N. Kohzadi;Neurocomputing,1996

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