Thank you again Gamuchirai , yet another very interesting ,clearly written and well thought article , I thought of using the MQL graph Module :) . Great stuff and very interesting thought process . To help other users My broker uses UKBENT and USWTI as symbols so I needed to modify the scripts to suit from (UK Brent Oil and WTI_OIL).
I am looking forward to testing and understanding this in detail
Thank you again Gamuchirai , yet another very interesting ,clearly written and well thought article , I thought of using the MQL graph Module :) . Great stuff and very interesting thought process . To help other users My broker uses UKBENT and USWTI as symbols so I needed to modify the scripts to suit from (UK Brent Oil and WTI_OIL).
I am looking forward to testing and understanding this in detail
Hey Neil, it's always good to hear from you, man I'm glad I could be of help.
What are the chances that you were also thinking of using the graph module? It's like we're in sync.
I'm looking forward to your feedback and suggestions for improvements, if you have any cross your mind.
P.S. Side note: are you also watching AUD/JPY? I'm looking to go long and play on the yen's fundamental weakness.
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Check out the new article: Reimagining Classic Strategies: Crude Oil.
In this article, we revisit a classic crude oil trading strategy with the aim of enhancing it by leveraging supervised machine learning algorithms. We will construct a least-squares model to predict future Brent crude oil prices based on the spread between Brent and WTI crude oil prices. Our goal is to identify a leading indicator of future changes in Brent prices.
Global crude trade is dominated by two benchmarks, West Texas Intermediate (WTI) which is the North American benchmark and Brent which is used to quote the majority of the world's crude.
In this discussion, we will revisit a classic crude oil spread trading strategy, with the hopes that we will be able to find an optimal machine learning strategy to make this classic strategy more palatable in a modern oil market that is dominated by algorithms.
We will begin our discussion by first highlighting the differences between the two oil benchmarks mentioned above. From there, we will begin visualizing the Brent-WTI spread in MQL5 and discuss the classical spread trading strategy. This will set us up to demonstrate how one may utilize supervised machine learning on the spread between West Texas Intermediate and Brent oil prices to potentially uncover leading indicators of changes in price. After reading this article, you will have a firm grasp of the following:
Author: Gamuchirai Zororo Ndawana