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A Lazy Person’s Guide to Happiness

Happiness is an active process, not something you get by sitting back and waiting. It’s something to be grabbed by the horns or more vulnerable areas and then conquered. At least, this is the gist of the message from Tony Robbins and gurus of his ilk.

Many also say happiness is not something we can buy, or steal, or work too hard to acquire. If you work too hard at it, you end up obsessing over your own state of mind—Am I happy? … Really though? And like love, if you have to ask, the answer is no.

So what’s the right way to think about effort and happiness? Should I be trying for “happiness” per se—or something more magnanimous, like purpose or meaning?

Or money? Is happiness actually all about money? That would be a real twist.

More here – The Atlantic

It Does Not Mean What You Think It Means

The interview in the post below with Daniel Kahneman got me going back over some old links that looked at the application of his and Amos Tversky’s ideas to trading and the chestnut I keep coming up against is the following question.

You have been given a choice between either –

a. $100 guaranteed, or

b. A 50/50 chance to receive either $200 or nothing.

The point is made that people will invariably opt for the first choice despite the fact that the mathematical expectancy of the two choices is the same (I have something to say about this in a minute) This is used to illustrate the point that traders invariably engage in the self defeating action of cutting their profits short. My rationale as to why we do this is probably buried somewhere deep in the evolution of our psychology, which in turn is linked to our desire to maximise our own pleasure. Consider this, you are one of our ancestors and you come across a fresh kill on the tundra. A bounty like this is rare because life is harsh, short and brutish. Naturally you grab whatever you can and run away, after all the kill belongs to something else and you don’t want to be around when it gets back. You are rewarded handsomely for this behaviour by avoiding starvation long enough to breed, thereby passing on this behaviour. My guess is that those ancestors of ours who stuck around to be pigs generally didn’t live long enough to have offspring. Over millennia this behaviour finds a modern translation in that you can never go broke taking a profit and it becomes the bane of all traders.

The reverse of this problem is offered as an example of how poor we are at dealing with losses. The problem is generally framed as you have been given a choice between either –

a. a guaranteed loss of $100.

b. A 50/50 chance to lose either $200 or nothing.

Traditionally, traders opt for the latter – so we have the perfect storm of cutting profits short but letting losses run. This is the reverse of the often quoted maxim for successful trading.

However, this example has always troubled me. I understand the point it is trying to make and I think that point is valid and true, the majority of people do what Jessie Livermore describes as doing exactly the wrong thing – selling the thing which gives you a profit and keeping the thing that makes you a loss. My discomfort with this example is that it offers a coin toss and not a continuum. Trading is not a coin toss it is a continuum and our trades reflect it, so whilst the lesson for traders is valid the example used to get there is weak. The question would be better phrased and more reflective of trading if it were presented as over time you have a 50/50 chance of receiving $200 – this reflects the actuality of expectancy.

There is another point of difficulty I have with the problem and it is one of both scale and economic utility. Let me rephrase the initial question as –

You have been given a choice between either –

a. $1B guaranteed, or

b. A 50/50 chance to receive either $2B or nothing.

The psychological import of the question changes as the scale changes – this is always a problem I have had with psychology as opposed to physics. The answer should remain the same irrespective of the scale of the problem. But in the real world you would be insane to risk a guaranteed $1B on a coin toss . The decision to not risk it would not be reflective of being a poor trading but upon understanding that there was nothing you could buy with $2B that you could not buy with $1B. The decision reflects one of economic utility as much it does the psychology of those making the decision. Interestingly, there is a modern example of investors walking away from such a guaranteed payoff.  In 2010 Google offered to buy Groupon for an estimated $6B , it was rumoured that this offer came on the back of Yahoo offering $3B a month earlier. Groupon knocked back both offers – needless to say the company is valued nowhere near that now.

Trading is a complex psychological endevour and whilst some simple models do make strong points we need to be aware that the models have limitations and that trading is a fluid game that at times demands that you act in ways that a psychologist might not approve of.

 

 

 

Why We Contradict Ourselves and Confound Each Other


 

Two For One on Stupid Things People Do And Believe

Why Do We Believe Stupid Things – David Harding

Why Do Smart People Do Foolish Things – Scientific American

What I Learned from Losing $200 Million

I’d lost almost $200 million in October. November wasn’t looking any better.

It was 2008, after the Lehman Brothers bankruptcy. Markets were in turmoil. Banks were failing left and right. I worked at a major investment bank, and while I didn’t think the disastrous deal I’d done would cause its collapse, my losses were quickly decimating its commodities profits for the year, along with the potential pay of my more profitable colleagues. I thought my career could be over. I’d already started to feel those other traders and salespeople keeping their distance, as if I’d contracted a disease.

More here – Nautilus

The Ignorance of the Crowd

In 1907,  Francis Galton asked participants at a county fair to estimate the weight of an ox. While most individuals guessed rather poorly, the median guess was within 1 percent of the ox’s true weight. It’s not a mysterious finding, as some people guess high and others guess low. When the group gets large, these cancel out and leave behind a better guess. Despite the simplicity, the implications are profound. Humans have the potential to make better choices when doing so collectively.

In the last few decades experimental and theoretical work has shown that collective wisdom is by no means guaranteed. The simple model demonstrated by Galton breaks down as soon as individuals begin to interact and share information. Whether or not the crowd is wise or foolish depends on the type of information individuals have, and is very sensitive to the network structure on which they interact. Unlike in Galton’s experiment, guesses can spread. A few loud, wrong individuals can be amplified and dominate the decision-making process.

More here – Scientific American

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