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You're reading from  Algorithmic Short Selling with Python

Product typeBook
Published inSep 2021
PublisherPackt
ISBN-139781801815192
Edition1st Edition
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Author (1)
Laurent Bernut
Laurent Bernut
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Laurent Bernut

Laurent Bernut has 2 decades of experience in alternative investment space. After the US CPA, he compiled financial statements in Japanese and English for a Tokyo Stock Exchange-listed corporation. After serving as an analyst in two Tokyo-based hedge funds, he joined Fidelity Investments Japan as a dedicated quantitative short-seller. Laurent has built numerous portfolio management systems and developed several quantitative models across various platforms. He currently writes and runs algorithmic strategies and is an undisputed authority on short selling on Quora, where he was nominated top writer for 2017, 2018, and 2019.
Read more about Laurent Bernut

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Myth #6: Short selling increases risk

"Facts do not cease to exist because they are ignored."

– Aldous Huxley

Short selling is risky. Not knowing how to sell short is, however, a lot riskier. Market participants are not risk-averse when they choose not to learn the craft. They are conservative to the point of being risk-seeking. Think of it as emergency drills. A refusal to practice the drills does not make the risks of fire, tsunami, or earthquake go away. People choose to go about their business unprepared for rare but life-threatening events. Being a market participant is not just about buy-and-hope, fair-weather sailing. Things can, and will, get rough.

At a subconscious level, every single market participant has this nagging subconscious fear of a bear market around the corner. They know they will give back some of the gains. Their best-case scenario is to sell before the bear and wait it out. This sometimes drives them to sell too early and miss out on big moves. As Peter Lynch said: "Far more money has been lost by investors preparing for corrections, or trying to anticipate corrections, than has been lost in corrections themselves."

Since no amount of academic research is ever going to drive the point across, let's look inside and play a game. Pick two pieces of paper, draw two columns. On the first one, write down your fears about bear markets. What is going to happen to your gains, portfolio, net worth, and job? How do you prepare for it? Be specific about when and how it manifests in your daily work. For example, do you check the markets more often than you think you should? Do you scan news for potentially bearish catalysts? Are you overly conservative or do you take risky bets while you think you can?

Next, imagine you were so serene about your ability to make money in down markets as to casually say: "Bull markets. Bear markets. They all taste like chicken." What would you do differently? Would you hold your positions longer? Would you size them differently? Would you be checking the news all the time? Write all the feelings on the second piece of paper. Once this is done, pick the first piece of paper and address all the fears one by one in the right-hand column. About half of your fears are emotional vampires that rob you of energy. They dissipate under the light of logical scrutiny.

Deep down, we all know that not being able to sell short is a lot riskier than not shorting at all because it gives you the ability to profit from both bull and bear markets.

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Algorithmic Short Selling with Python
Published in: Sep 2021Publisher: PacktISBN-13: 9781801815192
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Author (1)

author image
Laurent Bernut

Laurent Bernut has 2 decades of experience in alternative investment space. After the US CPA, he compiled financial statements in Japanese and English for a Tokyo Stock Exchange-listed corporation. After serving as an analyst in two Tokyo-based hedge funds, he joined Fidelity Investments Japan as a dedicated quantitative short-seller. Laurent has built numerous portfolio management systems and developed several quantitative models across various platforms. He currently writes and runs algorithmic strategies and is an undisputed authority on short selling on Quora, where he was nominated top writer for 2017, 2018, and 2019.
Read more about Laurent Bernut