Trading algorithms running our economy – what happens if the bots fail?

20

October

2017

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The other day I was browsing through TechCrunch looking for inspiration for my new blog and I came across the article “Dow Jones said that Google was buying Apple, and the bots bought it”. Turns out Dow Jones shot some fake news out in the world saying that Google was buying Apple for $9 billion – and the bots bought it. Apple’s stock went up around $2.

Now this made me think, if it is that easy to influence the trading algorithms that run our economy, isn’t it dangerous? What if people want to manipulate it in a negative way? I did some more research and found another article this one was from the Business Insider: “The Pentagon is worried about hackers causing a stock market crash”. Here the author argued that” manipulating stocks higher is a time-honored game that routinely receives kudos from all around” but what happens when hackers try to influence the algorithmic trading in a negative way? What happens when hacks result in stock prices actually falling in a major way?  According to the author this is when the Pentagon will intervene with all its power. Right now the Pentagon is working with various players from the stock trading industry “to figure out how hackers could unleash chaos in the US financial system” and how they can act to fight this.

Indeed this is a logical thing to do but to me it’s funny how the Pentagon only intervenes when there is a negative influence on the prices. From an opportunistic point of view I could understand, but is this this correct ethical way? Should governments tolerate everything that brings up stock prices and is thus “good for the economy”? This would mean that players that have the technical knowledge to do so could easily get economic benefit in contrast to people that would not have this. I think the whole industry, especially now that algorithms are running most of it, should get a thorough review on how it is regulated and when it should be intervened. What do you think? Let me know in the comments!

 

Sources:

https://techcrunch.com/2017/10/10/dow-jones-said-that-google-was-buying-apple-the-algos-bought-it/?ncid=rss&utm_source=feedburner&utm_medium=feed&utm_campaign=sfgplus&sr_share=googleplus&%3Fncid=sfgplus

http://www.businessinsider.com/pentagon-stock-market-crash-darpa-2017-10?IR=T

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1 thought on “Trading algorithms running our economy – what happens if the bots fail?”

  1. Thanks for sharing these insights. Due to your article, I started reading about this topic and found more information on High Frequency Trading (HFT) and its risks. In addition to your post, I would like to mention that not only hackers or criminals with malicious motives are dangers. Because the trading algorithms are designed in such a way to respond quickly to the market, an error in the systems / algorithms of one trading company could lead to a lemming’s effect.

    We have seen such a flash crash in May 2010 on Wall Street. Within fifteen minutes, the Dow Jones index tumbled six hundred points, to recover almost as quickly. What happened was that a mutual fund sold an extraordinarily large number of futures contracts. The HFT systems/algorithms of other traders responded rapidly and started selling as well. This behavior sent the market into a free fall (Ackerman, 2015).

    In 2012 HFT accounted for half of all of the business transacted on Wall Street (Popper, 2012). As this percentage most probably has increased even further and given the risks described above, the HFT industry definitely should be thoroughly reviewed and regulated. The latter seems rather difficult however (Henning, 2014).

    References:

    Ackerman, A. (2015), Regulators Sound Alarm on High-Frequency Trading Firms; Rapidly accumulating risk poses threat to global markets, says Senior Supervisors Group, The Wall Street Journal, April 15, 2015, p. 10.

    Henning, P.J (2014). Why High-Frequency Trading Is So Hard to Regulate, The New York Times, October 20, 2014, p. BU4.

    Popper, N. (2012). Searching for a Speed Limit in High-Frequency Trading, The New York Times, September 9, 2012, p. BU1

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