Title: Mcgowanjm Wire 2012 Source:
[None] URL Source:[None] Published:Feb 26, 2012 Author:Various Post Date:2012-02-26 09:15:13 by A K A Stone Keywords:None Views:1372123 Comments:2390
people tend to overweight small probability events.
So, what is behavioural economics?
Well, behavioural economics recognises the limits of human rationality, with ‘rationality’ being defined by the mainstream economic sense of the word, and comprises of a number of observations appertaining to human decision making that do not sit well with the neoclassical orthodoxy (Dolan et al. 2010). These include:
the observation that losses loom substantially larger than gains, a phenomenon known as loss aversion;
(ii) that reference points matter, such that people often care more about what they gain or lose around what they already have, rather than what they end up with;
(iii) that people tend to overweight small probabilities;
(iv) that people allocate their money to discrete bundles, so that the value that they attach to a particular amount of money will be contextual;
(v) the observation of motivational crowding, such that offering money to people to do something has been shown often to ‘crowd-out’ their intrinsic, altruistic motivation to do that very thing; and
(vi) ‘hyperbolic discounting’, which is the observation that people tend to place an enormous weight on the ‘immediate’ compared to the future, living for today at the expense of tomorrow.
In addition to the above stated observations, individuals often seemingly adopt a number of rules of thumb (or ‘heuristics’) when reaching their decisions, and apparently ‘satisfice’ rather than ‘optimise’, which goes against the grain of mainstream economics.
A far from exhaustive list of these rules of thumb include:
(a) the availability heuristic, in which people tend to assess the probability of an event by the ease with which similar instances can be brought to mind (e.g. many people erroneously think that the annual death rate from shark attacks is greater than that caused by falling coconuts);
(b) the anchoring heuristic, in which individuals often unconsciously focus upon, and can be manipulated by, entirely irrelevant cues when making decisions, and
(c) the overconfidence bias (e.g. most people think their driving ability is better than average), which has obvious implications for choices in financial markets, and elsewhere.
Behavioural economists have thus uncovered a library of systematic preference patterns and heuristics that cannot be explained by standard economic theory. Interestingly, although perhaps for many, on reflection, unsurprisingly, several of the observations and rules of thumb (e.g. the importance of reference points, availability, anchoring)
appear to suggest that humans are influenced very much by prominent, or ‘salient’, attributes in choice options – once their attention is focussed (sic) upon a particular feature of a task, they tend to overlook somewhat other potentially important information (for an entertaining example of this phenomenon, see selective attention test).
When the world pushes you to your knees, your are in the perfect position to pray. ... Ali ibn abi Talib (radiAllah anhu)
Which is where Jamie Dimon should be right about now....;}
Now here's Dimon/JPM's muse from 2008, explaining why
The Black Swan: Quotes & Warnings that the Imbeciles Chose to Ignore
is/was worth ignoring.
I'm wondering if Jamie spent some time with
Posted by Eric Falkenstein at 8:31 PM Sunday, December 07, 2008
Now THAT's an amazing date to be pontificating on how Behavioral Economics/Power Laws/Central Limit Theorums/ and the risk of Untold exposure to Non Linear Heavy Tail Risk is TOTALLY out of fashion.
As bush43 and a traitorous Congress REWARD WALL ST BANKSTERS for bringing the SYSTEM to its KNEES.
When the world pushes you to your knees, your are in the perfect position to pray. ... Ali ibn abi Talib (radiAllah anhu)
But INSTEAD of praying, these BANKSTERS get to run the ship into ANOTHER iceberg in order to speed the sinking.....LMFAO...8D
Notice how Falkenstein/Dimon NEVER consider FRAUD CONTROL in the following (VaR analysis;)?
" Value at Risk is a broad concept, that basically is a framework that has as its goal estimating a 99% or 95% worst-case-scenario, over an arbitrary period of time (day, week, year). Now, clearly many people underestimated the risk in mortgage-backed paper of all sorts, but this error was not particular to Value at Risk, rather, the assumption that housing prices would not decline, which then lead to errors in your stress test, or whatever you call your 'worst case scenario'. This error was made at many levels, by investors, issuers, rating agencies, banks who warehoused these loans, regulators, etc. Again, Value at Risk is pretty independent of this error, though the error would be reflected in any VAR that had such erroneous assumptions (garbage in, garbage out). Further, Value at risk is pretty agnostic as to method, whether you use data with really fat tails, 99.99% worst case scenarios, whatever you want. Blaming Value at Risk for the latest crisis is like blaming soup, rather than sanitation, for Typhoid Mary.
And with Jamie Dimon's EPIC FAIL, this arguement from Falkenstein has proved prescient and yet Falkenstein thought it was beautifully insane to even think about.....;}
" My argument still stands: he's basically someone who makes the perfect the enemy of the good. Like a communist reveling in the Great Depression, Taleb may take heart in recent events vindicating his worldview, but as Taleb knows, there are always 'lucky fools' who merely were fortunate. I would like to see a risk management report from Taleb, perhaps a page always saying "risk=inf", because of course, we could lose everything in WW3, a new virus,
***** all the banks fail, etc.*****
Every assumption isn't true, so make no assumptions. Be prepared for anything. Go long volatility (especially extreme tails). I don't think that's very good advice, though clearly it worked great this year (and funds he's affiliated have done very well, being long tail volatility).
Note to the reader: this was written a decade ago. A deeper explanation (which tells you that Jorion & his financial engineering IDIOTS are dangerous to society) is here: "The Fourth Quadrant", an EDGE (Third Culture)
"These patterns suggest that standard economic models based on the notion of equilibrium — markets will fluctuate but then settle down like the surface of a still pond — may not capture the whole story. Freak events may be a normal part of long-term economic behavior. If that’s true, then the mathematical methods guiding Wall Street’s estimation of risk are seriously flawed, offering a dangerous false sense of security.
“You have to understand that the bad events can be really, really bad,” says J. Doyne Farmer, who is trained in physics and does research spanning several disciplines at the Santa Fe Institute in New Mexico. “And there’s a significant chance that over a five-year period we will get hit by a really big event. That’s where the rubber really hits the road.”
My refutation of the VAR does not mean that I am against quantitative risk management - having spent all of my adult life as a quantitative trader, I learned the hard way the fails of such methods. I am simply against the application of unseasonned quantitative methods. I think that VAR would be a wonderful measurement if we had models designed for that purpose and knew something about their parameters. The validity of VAR is linked to the problem of probabilistic measurement of future events, particularly those deemed infrequent (more than 2 standard deviations) and those that concern multiple securities. I conjecture that the methods we currently use to measure such tail probabilities are flawed.
FLAWED
A Standard Deviation = a SIGMA Example: How far a random group of economists missed a BLS NFP report. Before 9/11 a 2 Sigma (Standard Deviation;) Event Miss was Unusual.
But after 9/11, we've regularly had 3&4 Sigma Events.
the informative book by Philippe Jorion, "It summarizes the expected maximum loss (or worst loss) over a target horizon within a given confidence interval".
