Nassim Taleb wrote the Fourth Quadrant to which I linked to the following NakedCapitalism post from April 2009 - Taleb Presentation on the Fourth Quadrant. This is where Dr. Taleb discusses the extraordinary circumstances encountered in the Fourth Quadrant of his 2x2 model of simplicity-complexity-risk-reward and that members of the Fourth Quadrant do not generally exhibit Gaussian Normal distribution patterns as so much in our world does.
Then yesterday the crew at ZeroHedge identified their view of the new (un)norml - the "fact" that you can have record level of debt accumulation in the month of February in tandem with the record lowest interest paid on said debt. Whack-a-doo, a favorite trading mentor would say.
And this morning, another piece - BELOW, this time from AlephBlog, the new (un)norml of economics and finance - price and market behaviour - human behaviour is not Norml. Huh, I've known that about myself for quite some time, but now we're seeing that maybe some of that predictability and randomness are not exactly as it has seemed.
I can certainly atest in my own life, and with the awareness I have - timing is everything - everywhere - everytime. As individuals making our way through our days, we make assessments and evaluations of risk/reward everyday. The vast majority of the time, the rewards (achieving what we expect) holds true. I need to go to the grocery store to get milk. Generally I will be successful. But it is the unexpected outcome that can sometimes have the most unanticipated result - the risk/reward is possibly redefined.
In my trading the risk/reward analysis has become a cornerstone to my efforts. And now I watch myself applying the same mental processes to everyday decisions. Sorta-boring, and sorta-not-so-boring, and actually quite interesting. Another excellent example of boiling down our everyday existence into a trail of decisions, our expectations or outcome, and the end result.
Nassim Taleb has another book that has been recommended to me by my older brother - Fooled by Randomness (Amazon Book Review).
If the prescriptions for getting rich that are outlined in books such as The Millionaire Next Door and Rich Dad Poor Dad are successful enough to make the books bestsellers, then one must ask, Why aren't there more millionaires? In Fooled by Randomness, Nassim Nicholas Taleb, a professional trader and mathematics professor, examines what randomness means in business and in life and why human beings are so prone to mistake dumb luck for consummate skill. This eccentric and highly personal exploration of the nature of randomness meanders from the court of Croesus and trading rooms in New York and London to Russian roulette, Monte Carlo engines, and the philosophy of Karl Popper. Part of what makes this book so good is Taleb's ability to make seemingly arcane mathematical concepts (at least to this reviewer) entirely relevant in evaluating and understanding everything from the stock market to the success of those millionaires cited in the aforementioned bestsellers. Here's an articulate, wise, and humorous meditation on the nature of success and failure that anyone who wants a little more of the former would do well to consider. Highly recommended. --Harry C. Edwards
The Rules, Part III
Okay, here is tonight’s rule:
The assumption of normality for asset price changes is wrong in virtually every financial market setting. The proper distributions are fatter tailed and more negatively skewed.
Normality allows researchers to publish, regardless of the truth.
Normality allows risk managers and regulators to pretend that adequate reserves are held against disaster. It also allows businessmen to achieve acceptable ROEs, while accepting a probability of ruin far in excess of what is prudent.
The normal distribution is a wonderful creation, because it is so simple. All we need to know is the mean and the variance, which are very simple to calculate. And… it seems close to fitting a large number of phenomena in nature where the behavior of one party does not affect the behavior of others.
But in economics and finance, the assumption of normality is perpetually violated. I would guess that it is wrong more often than it is right. Academics continue to drag out studies assuming normality because it allows them to publish. academics get statistically significant results more often than they should, because they pursue specification searches, and get to results that they can publish via data mining (and ARIMA error terms — unless there is an a priori reason them, they facilitate specification searches).
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