New Algorithm Uses Superstition To Trade Stocks

Many different individuals have tried to devise an algorithm which can make smart stock decisions. However, most of these attempts have ended up in failures. Now, a new experimental algorithm has been devised which makes use of superstition to decide when to trade stocks.


Shing Tat Chung has been interested in the whole notion of superstitions since a long time. He has been writing about his ideas about superstitions on his personal blog. He was the one who came up with the idea of a ‘Superstitious robot’ who can make stock decisions based on superstitious notions.

According to Chung, “I wanted to poke fun at our superstitions. But I also wanted to highlight our irrational nature in a way that is less critical and more about encouraging dialogue.”

The algorithm that Chung is using makes use of an Automated Trading System. However, it runs on superstitions, rather than other facts and analysis. For instance, the robot wouldn’t buy any stocks on the 13th of a month since it is considered unlucky. Moreover, the robot also considers the growth of the moon as a bad omen. A new moon is lucky whereas the full moon is an unlucky omen, prompting the robot to shed its stock in the last days of the month.

Chung launched the project on June 1st and intends to continue it for a year, after which he will benchmark the performance of his superstitious bot against other algorithms. So far, the performance of the bot hasn’t been particularly good. Ever since its launch, it has fallen by 12 percent in its overall value. Perhaps that is why Chung states in every email he sends to the investors that, “Please be aware, that this is an unproven, highly speculative, experiment and a project with the risk of total loss.”

Source: BBC

Courtesy: The Verge

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Salman

Salman Latif is a software engineer with a specific interest in social media, big data and real-world solutions using the two.Other than that, he is a bit of a gypsy. He also writes in his own blog. You can find him on Google+ and Twitter .

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