Oil price: the Suez Canal factor and the role of sentiment

 

Suez Canal block - oil price

The oil price that had been going down at an alarming rate in the last two weeks, got a catalyst on Wednesday morning out of the blue, when a massive cargo ship ran aground in the Suez Canal in the middle of a storm.

With a gigantic obstacle blocking the path in the busy waterway, tankers have been spotted idling behind it, carrying millions of barrels of crude oil; understandably, the fear of an imminent supply shortage blew across the markets and the oil price went up.

The scenario, once again, proved the fact that the sentiment is the king in the paradoxically fluctuating crude oil markets; it is an unsurmountable challenge to the data analysts who work, day in, day out, in search of the magic formula to predict the price accurately.

So far, this pursuit has been of no avail.

Last week, most pundits, who monitor every conceivable factor that could determine the crude oil price, were in unison in declaring the decline in oil price; that, however, dramatically changed yesterday, when the news of the blockage of the Suez Canal started emerging.

In this context, until we come up with a mechanism to analyse the prevailing sentiment and quantify it, despite being monumental, the reliable prediction of oil price in a few days’ time, let alone in a month or so ahead, will be just a futile exercise.

Unfortunately, even super-complex algorithms, involving the Machine Learning, have made no difference either, despite crunching enormous amount data at an unbelievable speed.

In short, the Holy Grail of price formula is still as elusive as ever it has been, despite the amazing advances made in the Data Science.

Perhaps, if we manage to analyse the universal markets sentiment in an accurate manner, we may get closer to the magic formula that could predict something reliable.

In order to become a part of this seemingly-losing battle, I subjected an article on the Sues Canal blockade to a sentiment analysis algorithm, as shown in the animation above, and it was pretty negative; I repeated the experiment with a few more articles in the British newspapers in order to spice it up statistically and sentimental factor was fairly consistent; but the number was still fluctuating considerably.

All in all, the ball is now in data scientists’ court; they need to come up with algorithms to get the sentiment right – along with other factors, of course - in order to make the customers, who rely on their predictions to get the investors out of a sphere of perpetual nervousness.

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