Fractals, TA and other things - a new trading blog

Posted on July 1, 2008
Tags: Blogs I read, Trading Resources |

My good friend JP has started a new blog called Fractals, Technical Analysis and other things.. JP trades the forex market when he’s not busy being a philosopher, mathematician and super book devouring machine :-)

Here’s an interesting thought from a post explaining his interest in fractals:

Something I completely agree with, but then, if a technical analyst is to reject this Random Walk view of price movement, shouldn’t he reject as well the mathematical ramifications of this assumption rather than to use them as tools. In a Gaussian model, the average (the mean) clearly is a good information to consider, it is the quantity that has the highest probability to be realised, and the closest to the average, the higher the probability is.

The large pool of experimental data we have from financial markets, however, tells us that they don’t follow a Gaussian distribution, they diverge from it in various ways but a remarkable one is that they are fat-tailed , which means that the probability for the variable to be far away from the average is actually higher than in the Gaussian model (i.e. extreme variations are more frequent than what is predicted by the model). And that is important, because it tends to make our beloved Average less useful, in terms of prediction, while the differences are not such that Averages don’t retain any usefulness. But more precise tools may likely be derived from a more fitting model of the real price movement.

Comments

3 Responses to “Fractals, TA and other things - a new trading blog”

dc on July 2nd, 2008 11:39 am

will be interesting to see what the “more precise tools may likely be derived from a more fitting model of the real price movement” will be…

beyond gaussian distributions, one will probably be looking at pareto distributions, as the fractal researcher mandelbrot did.

a price series is a fascinating thing, much like a well-made up lady - looks can be deceiving. what looks normal on closer examination reveals those nasty fat tails. but not to worry, any one of those fashionable GARCH models will help in wide-vol control.
some prefer their ladies, like their price series, to be more independent. a robust method like r/s analysis can help find out whether your paramour has persistent dependency issues…

but in the end, all we want to know is if a price series will exhibit persistent, auto-correlated behaviour ie, will it trend and trend meaningfully…

as i write this, crude inventories came in much lower than expected -
schizo CL zigged than zagged before taking off, coy ES took a few hesitant steps back, petulant ER stormed off…

correlations and persistencies wax and wane,
in the end what is important for a trader, is to have his buy and sell stops ready when a market moves and ride the trend meaningfully…
Jean-Philippe on July 2nd, 2008 3:38 pm

Yes, just a short reply.
I will try to minimize the use of mathematics, at least, in a first time, to concentrate indeed on what interest the average trader: When to get in and out of a trade, and where to put stops, and how to get an idea of what objective should one look for.

As for the family of short-term dependence process (Markov,ARCH,ARMA,…), I will not look at them, precisely because they are short-term dependent, while price movement displays long-term dependency.

But again, I will try to restrict the use of mathematics to cases which would appear obscure or unfounded without it. Whenever I can convey the same in simple english, I will do it, it’s also easier for me, since I don’t know how to use Latex on blogspot (when needed, I will just attach images of formula, but it’s a bit heavy to do it too often)
eyal on July 3rd, 2008 11:53 am

guys - I would have joined this conversation happily if I had something smart to add :-) Alas, I’m just a simple trader so I’ll just say I definitely agree that positioning yourself ahead of the action is key, and of course having some small statistical edge in doing so is the name of the game.