Have you heard of Didier Sornette?

Excerpt from Deming's SOPK

http://www.maaw.info/ArtSumDeming93.htm

"The Theory of Knowledge
The theory of knowledge includes an understanding that management in any form is prediction. A statement, if it conveys knowledge, predicts a future outcome including the risk of being wrong. Prediction requires theory. Without theory, experience has no meaning and there is no learning. Copying examples without understanding the underlying theory may lead to disaster. Any number of examples cannot establish a theory. "



Quote from harrytrader:

Trading is a Business except if you're doing it as a hobby. Business implies Planning, Planning implies some Prediction methods. You can use more or less sophisticated methods it will depend on the needs and capabilities of your business. It could just be a model based on experience that has been transformed into a framework or it could be a more sophisticated and robust model which is basically what scientific means. A business without planning won't last long...

>as a wise venture capitalist once said, 'there's really no such >thing as a unique idea, and 'good' ideas are a dime a dozen. it's >the execution that counts.'
And execution success depends for 80% on Preparation that is to say planning above. The man who is the best well-known guru of Quality Management - who is Edwards Deming - has created the Universal Wheel (or Spiral) of progress known under the acronym PDCA: Plan Do Check Action (meaning Correction). As you can see Plan is the first step.

Saying that "it's the execution that counts." is a lapalissade. What counts is a good execution and if we are discussing about how to have good execution we have to look for methodology and then methodology will answer: planning and this would imply prediction. Those who pretend to use signals only and not try to forecast the market are just fooling themselves: by market's efficient theory there is no possible signal since every signal should be considered as blank noise. So if there is a potential signal it means a prediction can be done even if it is fuzzy it is still a prediction for example about the market's direction.
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Quote from harrytrader:

>This is all a waste of time. These Phd's have finally found a field >where they can get decent-paying jobs and are trying to milk it >for all its worth.
Did you ever wonder that those that work for Wall Street are paid NOT to be competent arf arf ! Because in other fields as in engineering they would be destroyed and lose their jobs ! But some researchers are independant and among them they are true founders. I don't need Sornette's model - since I have my own and I don't trade on long term basis - but for long term his model can be worth and as usual another point of view is always interesting.

>William O'Neill and Jeff Cooper both frequently make the >observation that it is not necessary to predict the market but >only to understand where you are now.
Try to drive your car by looking at its wheels and tell me the results: Yes you must understand where you are now BUT you must also look a few meters in front of you :).
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I must agree that failure is richly rewarded on Wall Street, although failure is a relative term since someone is making moeny, just not investors.

The car analogy is flawed because you can see ahead quite clearly. The proper analogy would be driving down a cliff-side highway in total darkness with no lights. It might a very good idea to watch your wheels carefully. Certainly looking in the rear view mirror and extrapolating ahead would be disastrous.
 
This can give an idea of the model results on stock : this was the kind of analysis I made 2 years ago. Stock is far from as precise as indice which is statistically understandable (since the standard deviation of an indice is about to be proportional to those of a stock by the squareroot of number of stocks) .

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Quote from harrytrader:

Two years ago I have made a mailing with those kind of alerts I know people like that but it bored me I stopped to do so :).
Perharps I will do it again one day.
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Quote from darkhorse:


trying to crack the markets with heavy math is going in the wrong direction imho.

guys like Sornette are greedy. they don't want to have occasional clarity, they want to crack the whole code. it's like yo, i don't just want to know the best way to catch fish, i want to figure out how to know where all the fish in the ocean are at this exact moment right NOW. No can do- too much science, not enough common sense. Some weird kind of 'gee i wish i were omnisicient' complex. I wonder if psychologists have a term for it.
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Well said.
This guy makes money from writing not trading.
So he will write more.. and more... and more...
 
Is DS full of BS?

I REMEMBER DISTINCTLY and I even have it printed out over the summer that there will be this HUGE drop in teh SP500 starting in Sept and Oct! I swear I saw it on his homepage. Then when you check it now, he took out that graph! WTF?! And then he extended the prediction til 2004. And if 2004 doesn't have a big drop he'll extend it to 2005. haha!

I mean he might be right eventually that between now and 2004 there will be a huge drop in the SP500. But long term forecasting can have error terms of a FEW MONTHS or QUARTERS! And that would be disastrous trading off of that variance! Imagine him advise some institutional/hf managers to put on a huge short position in Aug. They would have been fried with this up move even though he might be right eventually...

I think simple TA will tell you when and IF the big move comes. When it comes you'll see. Predictions are useless. With all that effor and analysis expended on figuring th next big move, he's missing the up move in the last few months. Just follow the market.

What do you think harrytrader? I know you are a fan of predictions...
 
I thought I saw a nice little graph with a rally and then a big dump in the fall too. If he did remove the graph and rewrite his dates and I were an academic I would make sure this intellectual dishonesty was well known.

Of course he will talk about how his model had bad data and upon data scrubbing the model spit out this new graph. Really all he needs is some good prechterizations.
 
Quote from misctrader:

What do you think harrytrader? I know you are a fan of predictions...
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What I think is that stochastic modelling of stock market are too poor - including the last co-integration type of model. They are adapted for global risk assessment of investors type profile or arbitrage / volatility strategies but not for some type of speculative trading with huge leverage where precision is critical. The stock market must have a very weird correlation structure as would say Mandelbrott - since he said that for the Nile - that stochastic models have difficulty to capture, I have explained globally why here :

http://www.elitetrader.com/vb/showthread.php?s=&threadid=23134&perpage=6&pagenumber=21

"In econometric modelling - as in other fields - there are normally two class of modelisation :
- stochastic (from the simplest like ARMA, to more complex like Box & jenkins that are classically used in short term forecasting of products like champaign - I said that because it is on that that I learned them - and in financial modelling they have been extended with Garch and so like models - see the link I about Jean Philippe Bouchaud audio conference) and
- deterministic. The research on deterministic models is much recent in forecasting techniques and according to a statistical book "Methods for short term forecasting" (translated from french) it has only begun since the 1990 and at the moment nobody has never found something very convincing in financial modelling and one of the reason is that tools for detecting deterministic models are not very accurate. For example in another book I already quoted which is "modelisation of stock market returns" (sorry also translated from french) they show that the market must have some deterministic components but that the lyapounov exponents - which characterise such process - are too weak to be able to assess the hypothetical model. So by default they try to model long term memory effect with stochastics models that extend the classical ones above (farima, wavelet decomposition).

Is it astonishing ? No because to get a deterministic model you must know the real factors that is difficult since it would be like trying to read in the mind of God's market . And even using more sophisticated stochastic approach won't change the instrinsic wall of uncertainty attached to stochastic model not because of absolute impossibilty but because of the structural form of the class solution. Of course it will be possible to detect interesting things but it will stay shadows compared to a true deterministic model."
 
Harry- while I still do not completely understand what people say when they throw the word around deterministic, at least now I know what they think they are saying ior n the rare cases what they are saying.

Harry you are either getting better at writing in English or my filter has adapted well, because your signal to noise ratio has improved dramatically.

thanks
 
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