Best Market Model: Geometric Brownian Motion?

I'm wondering if the EMH and geometric brownian motion is still the best model for financial market behavior? Note, I'm not asking if it is a perfect model, since most of us know the weakness of this theory. I'm no academician in this field, so I'm not up to date on the latest market theories.

I know activities like insider trading and front running are baked into price movements, but those aren't of themselves, a market model. If not EMH/GBM, what are some other competing theories of market behavior which can account for these more questionable behaviors?

I post this in TA so I can continue the long and tiresome discussion on whether TA is bullshit. I'm becoming more of a believer that it is.
 
I'm wondering if the EMH and geometric brownian motion is still the best model for financial market behavior? Note, I'm not asking if it is a perfect model, since most of us know the weakness of this theory. I'm no academician in this field, so I'm not up to date on the latest market theories.

I know activities like insider trading and front running are baked into price movements, but those aren't of themselves, a market model. If not EMH/GBM, what are some other competing theories of market behavior which can account for these more questionable behaviors?

I post this in TA so I can continue the long and tiresome discussion on whether TA is bullshit. I'm becoming more of a believer that it is.
The real question is, what strategy does your model lead to? Seems to me EMH just leads to coin flips, which is unacceptable for trading.
 
Behavioural economics has a lot of ideas that could be a bit more interesting than EMH. The most famous one is "prospect theory" of Kahneman and Tversky.
 
I think it depends on what you want the model for. Is it do risk management? Then a combination of EMH, brownian motion, if used correctly isn't a bad model and has the advantage of simplicity. Is it to predict the market? Well these models tell you can't predict the market, and shouldn't try.

Behavioural finance isn't yet, and perhaps never will be, a consistent complete theory like EMH; but it has the advantage of being able to explain a lot of patterns in the market, so I am a big fan of it. Prospect theory, which explains why trend following works, is probably the kernel of this complete theory.

A second vote for "Thinking fast and slow". If you are short of time there is an older book, "Beyond greed and fear" Hersh Shefrin, which is brief and very finance focused.

If you're really short of time here's a quote from the chapter in a book I'm writing at the moment.

When the ideas of classical finance were developed in the 1950's economists assumed that people behaved in a purely rational way, resulting in perfectly efficient markets. Over time many apparent anomalies in this theory were discovered. But these were easily dismissed by the academic establishment as irrelevant, statistically insignificant or explainable through some combination of risk factors. Crucially nobody was able to come up with an alternative model that was as self consistent and elegant as the efficient markets hypothesis.

From the 1980's onwards the field was penetrated by academics from the discipline of psychology. For these experts in the human mind the economist's framework of pure rationalism must have been highly amusing. A key insight these interlopers brought in was that our brains are loaded with baggage from our distant past.

Parts of our grey matter are still hardwired for survival in a hostile environment where quick thinking was better than slow thoughtful consideration. As a result we have deep rooted instinctive behavior that makes it extremely difficult to behave in the rational way that classical finance expects. The new field that the interlopers created was behavioral finance,and it did have its own unifying model:prospect theory.

Prospect theory explains why investors behave irrationally when confronted with certain trading decisions, such as whether to sell out of a position which is now showing a loss. Most people show the greatest reluctance to take losses, as I did in 2010 with BP. Conversely if the position has risen in value they are happy to take profits and sell quickly, as in my 2004 BP trade.

The former situation has been catchily described as “get-evenitis” by Hersh Shefrin. This aversion to taking losses is a very powerful instinct. Humans do not seem to view a paper loss as real until it has been crystallised, so we can postpone the painful feeling of losing money. We are also reluctant to admit that we made a mistake with our initial purchase. Selling is an admission of failure.

The main motivation behind selling positions at a small profit appears to be to minimise regret. If the stock fell back after reaching a new high we would castigate ourselves for not taking profits earlier.

Both of these effects are at odds with classical theory,which states that peoples actions and preferences for risk are unrelated to whether they have made paper profits or losses. In contrast prospect theory says we take more risks in a losing position to get even. But we want less risk when winning, preferring a certain gain to a chance of losing our profits.




I'm wondering if the EMH and geometric brownian motion is still the best model for financial market behavior? Note, I'm not asking if it is a perfect model, since most of us know the weakness of this theory. I'm no academician in this field, so I'm not up to date on the latest market theories.

I know activities like insider trading and front running are baked into price movements, but those aren't of themselves, a market model. If not EMH/GBM, what are some other competing theories of market behavior which can account for these more questionable behaviors?

I post this in TA so I can continue the long and tiresome discussion on whether TA is bullshit. I'm becoming more of a believer that it is.
 
Ha, for a general guide to Kahneman's life's work, expressed in everyday terms, you should read his excellent book "Thinking, Fast and Slow".

I know the book was a best seller and recommended by a lot of traders. I was scratching my head when the book description had nothing to do about trading or even economics in general. I'll check it out. Thanks.
 
I know the book was a best seller and recommended by a lot of traders. I was scratching my head when the book description had nothing to do about trading or even economics in general. I'll check it out. Thanks.
It has to do with how people, broadly, make decisions... So it has a LOT of relevance to trading, really.
 
I'm wondering if the EMH and geometric brownian motion is still the best model for financial market behavior? Note, I'm not asking if it is a perfect model, since most of us know the weakness of this theory. I'm no academician in this field, so I'm not up to date on the latest market theories.

I know activities like insider trading and front running are baked into price movements, but those aren't of themselves, a market model. If not EMH/GBM, what are some other competing theories of market behavior which can account for these more questionable behaviors?

I post this in TA so I can continue the long and tiresome discussion on whether TA is bullshit. I'm becoming more of a believer that it is.

You need to define "best model". Then there are various questions that you can ask: given a finite realization from a GBM is it possible that a real instrument could have a "similar" (to be defined precisely) realization? The answer is yes.

Or if you have a real price trajectory, could I find a GBM which is "likely" to generate something "similar". Of course you can.

If you have a finite real price trajectory can you say that it does not exist a GBM which could have generated it ? You can't.

In very practical and intuitive terms, the GBM is, imho, highly "unrealistic" for several reasons. Simply being familiar with both simulated data and real trading will make you convinced that the realizations of a pure GBM, observed in a large number, "look and feel" in general quite "unrealistic". In the real world, there is no such a thing like constant volatility or constant drift (as in the GBM). GBM realizations tend to "reverse" much less than most instruments do (especially energy/commodities related). Also they tend to reach "farther" than real instruments do. Of course there are ways to modify or combine GBMs and other generators to make a simulation "feel" a bit more "realistic" (at least to an experienced trader).

GBM is just a model that has no many other justifications than being relatively "simple" (say, formally tractable). For the rest, the real world has no obligation to even come close to these human fantasies and simplistic models. Actually, it has no obligation to satisfy any "model" one can think of.


>TA is bullshit. I'm becoming more of a believer that it is

It's just guessing, based on visual hints and optical illusions. There is nothing "technical" about it, apart the use of the pompous adjective to somehow disguise the guessing activity as something justified by some more "legitimate" reason. Whatever you guess, sometimes it will come true, sometimes it will not, and you can actually "believe" whatever you like, as there is no way to confirm or confute a causality connection. And when things are not even falsifiable, some would argue we are out of the domain of "science". (Check out: http://en.wikipedia.org/wiki/Falsifiability#Falsificationism)
 
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I post this in TA so I can continue the long and tiresome discussion on whether TA is bullshit.

It's just guessing, based on visual hints and optical illusions. There is nothing "technical" about it, apart the use of the pompous adjective to somehow disguise the guessing activity as something justified by some more "legitimate" reason.


To be sure I won't devote much time to what is certain to be an endless discussion, but here we go for a start. These guys found there was 'some value' within a certain time period. Whether that 'value' can be monetized and if that time period phenomenon still persists I leave to others. I am only addressing a request for continuation (quote 1) and a hint at "non technicality" and falsification (quote 2).

*******************************************************************
Foundations of Technical Analysis:Computational Algorithms, Statistical Inference, and Empirical Implementation
-ANDREW W. LO, HARRY MAMAYSKY, AND JIANG WANG
THE JOURNAL OF FINANCE • VOL. LV, NO. 4 • AUGUST 2000

ABSTRACT
Technical analysis, also known as “charting,” has been a part of financial practice
for many decades, but this discipline has not received the same level of academic
scrutiny and acceptance as more traditional approaches such as fundamental analysis.
One of the main obstacles is the highly subjective nature of technical analysis—
the presence of geometric shapes in historical price charts is often in the eyes
of the beholder. In this paper, we propose a systematic and automatic approach to
technical pattern recognition using nonparametric kernel regression, and we apply
this method to a large number of U.S. stocks from 1962 to 1996 to evaluate the
effectiveness of technical analysis. By comparing the unconditional empirical distribution
of daily stock returns to the conditional distribution—conditioned on specific
technical indicators such as head-and-shoulders or double-bottoms—we find
that over the 31-year sample period, several technical indicators do provide incremental
information and may have some practical value
 
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