Market Mind Games
In the book Market Mind Games: A Radical Psychology of Investing, Trading, and Risk, author Denise Shull argues that rather than trying to control their emotions, traders should tap into their emotions to get better investing results. The main themes of the book are that math is bad, trying to control your emotions is bad, and using the author’s methods would help you avoid losses.
To paint a picture of a radical new approach to trading, Shull devotes the first half of the book to rejecting math and controlling emotions. She then goes on to describe her methods in the second half of the book. However, where she gives concrete advice, the tips turn out not to be particularly radical at all.
The author’s most direct attack on the idea that traders should control their emotions is to argue that damaged people who have no emotions aren’t capable of making any decisions at all. However, controlling emotions doesn’t mean eradicating them. It means staying calm and thinking before acting. Shull seems to be deliberately misunderstanding what people mean when they say that traders should control their emotions.
Much of the book is taken up with a fictitious story of some traders who find success and love by following Shull’s teachings “which implicitly meant an overthrow of the dominance of numbers.” Between this story, the repetition, and the parts that are difficult to make any sense of, this book could be easily cut down to a fairly short paper.
Rejection of Math
It is difficult to summarize Shull’s criticisms of math because I couldn’t make sense of them. Here is an example of sentence the author bolded presumably because she believes that it has high significance:
“Logically, if you have a probability that you know will only apply for a limited time and by definition that probability tells you that you have some significant chance of being wrong, even while it still applies, how much do you really know?”
I can’t argue with that, but I am reminded of a quote from Wolfgang Pauli: “This paper is so bad it is not even wrong.”
The author tries to paint Nassim Taleb of black swan fame and Benoit Mandelbrot as being on her side, but they didn’t reject all of mathematics; they rejected the normal probability distribution as a model of extreme events.
Here are more interesting quotes that are hard to argue with:
“Market numbers ... differ as a category from other kinds of numbers such as arithmetic or algebraic numbers.”
“The essential infinite number of choices when it comes to the question of how much longer to hang onto a trade means, by definition, certainty and truth cannot exist.”
“Solving the eternal puzzle of markets depends entirely on your ability to fluidly wield the sword of numbers as a language and not as a law.”
Bold Claims
Had the author’s “interpretive language perspective been in place in the years preceding 2008,” and “if a common sense context ... had been able to get a seat at the table, ... the billion- and trillion-dollar bonfires might not have been quite so dramatic.”
After watching Bernie Madoff during a panel discussion in 2007, Shull wrote the note “he is hiding something.”
Shull likens her ideas of your brain as “an emotional-context operator” to the transition from believing “the Earth was flat” to knowing “that the Earth is round.”
Useful Advice
“Arrange your days so that you can be working from peak or near-peak energy the majority of the time.” This isn’t exactly a new idea, but it is some good advice that actually makes sense.
Shull equates “controlling your emotions” with “rationalizing mistakes.” She sensibly says that rationalizing mistakes is a bad idea. However, rationalizing mistakes is the opposite of controlling your emotions. Her advice for avoiding rationalizing looks to me like a suggested method for controlling emotions rather than a rejection of controlling emotions.
The author says that the “all intellect all the time” approach leads to traders wondering “why they keep making the same mistakes.” Not repeating mistakes is good advice, but I don’t see how making the same mistakes repeatedly qualifies as using your intellect. In my own experience, it is when I’m driven by emotion that I repeat mistakes. When I control my emotions and think, I tend to avoid repeating mistakes.
When you’re sitting at your trading screen and are annoyed that some trades went against you, you should “leave the screen” and come back later with a “surge of energy” and “renewed confidence.” This is good advice, but I see it as a good way to control your emotions rather than an example of why controlling your emotions is somehow bad.
After some trades go badly, desperately trying to get back to even is a bad idea because it “often escalates into a temper tantrum of trades,” which traders should avoid. Shull claims that this is the result of trying to control your emotions. Once again, I see this kind of behaviour as a result of not controlling your emotions.
Conclusion
There may be some useful advice in this book, but it is far from radical. Rather than an assault on the idea that traders should control their emotions, I see parts of this book as suggested methods for controlling emotions. These suggestions largely amount to recognizing these emotions when they come up and looking at what they mean.
To paint a picture of a radical new approach to trading, Shull devotes the first half of the book to rejecting math and controlling emotions. She then goes on to describe her methods in the second half of the book. However, where she gives concrete advice, the tips turn out not to be particularly radical at all.
The author’s most direct attack on the idea that traders should control their emotions is to argue that damaged people who have no emotions aren’t capable of making any decisions at all. However, controlling emotions doesn’t mean eradicating them. It means staying calm and thinking before acting. Shull seems to be deliberately misunderstanding what people mean when they say that traders should control their emotions.
Much of the book is taken up with a fictitious story of some traders who find success and love by following Shull’s teachings “which implicitly meant an overthrow of the dominance of numbers.” Between this story, the repetition, and the parts that are difficult to make any sense of, this book could be easily cut down to a fairly short paper.
Rejection of Math
It is difficult to summarize Shull’s criticisms of math because I couldn’t make sense of them. Here is an example of sentence the author bolded presumably because she believes that it has high significance:
“Logically, if you have a probability that you know will only apply for a limited time and by definition that probability tells you that you have some significant chance of being wrong, even while it still applies, how much do you really know?”
I can’t argue with that, but I am reminded of a quote from Wolfgang Pauli: “This paper is so bad it is not even wrong.”
The author tries to paint Nassim Taleb of black swan fame and Benoit Mandelbrot as being on her side, but they didn’t reject all of mathematics; they rejected the normal probability distribution as a model of extreme events.
Here are more interesting quotes that are hard to argue with:
“Market numbers ... differ as a category from other kinds of numbers such as arithmetic or algebraic numbers.”
“The essential infinite number of choices when it comes to the question of how much longer to hang onto a trade means, by definition, certainty and truth cannot exist.”
“Solving the eternal puzzle of markets depends entirely on your ability to fluidly wield the sword of numbers as a language and not as a law.”
Bold Claims
Had the author’s “interpretive language perspective been in place in the years preceding 2008,” and “if a common sense context ... had been able to get a seat at the table, ... the billion- and trillion-dollar bonfires might not have been quite so dramatic.”
After watching Bernie Madoff during a panel discussion in 2007, Shull wrote the note “he is hiding something.”
Shull likens her ideas of your brain as “an emotional-context operator” to the transition from believing “the Earth was flat” to knowing “that the Earth is round.”
Useful Advice
“Arrange your days so that you can be working from peak or near-peak energy the majority of the time.” This isn’t exactly a new idea, but it is some good advice that actually makes sense.
Shull equates “controlling your emotions” with “rationalizing mistakes.” She sensibly says that rationalizing mistakes is a bad idea. However, rationalizing mistakes is the opposite of controlling your emotions. Her advice for avoiding rationalizing looks to me like a suggested method for controlling emotions rather than a rejection of controlling emotions.
The author says that the “all intellect all the time” approach leads to traders wondering “why they keep making the same mistakes.” Not repeating mistakes is good advice, but I don’t see how making the same mistakes repeatedly qualifies as using your intellect. In my own experience, it is when I’m driven by emotion that I repeat mistakes. When I control my emotions and think, I tend to avoid repeating mistakes.
When you’re sitting at your trading screen and are annoyed that some trades went against you, you should “leave the screen” and come back later with a “surge of energy” and “renewed confidence.” This is good advice, but I see it as a good way to control your emotions rather than an example of why controlling your emotions is somehow bad.
After some trades go badly, desperately trying to get back to even is a bad idea because it “often escalates into a temper tantrum of trades,” which traders should avoid. Shull claims that this is the result of trying to control your emotions. Once again, I see this kind of behaviour as a result of not controlling your emotions.
Conclusion
There may be some useful advice in this book, but it is far from radical. Rather than an assault on the idea that traders should control their emotions, I see parts of this book as suggested methods for controlling emotions. These suggestions largely amount to recognizing these emotions when they come up and looking at what they mean.
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