Mathematician trader

Discussion in 'Trading' started by Trish, Jan 9, 2010.

  1. Maybe not hard to understand but often difficult to apply properly in real life. For example, you can find various interpretations of %K, some are flat wrong. I think this article by my favourite guru Michael Harris is a good resource about %K and points out some of the difficulties in using it. IMO this paper also indicates the level of math a trader should be familiar with:

    %Kelly paper
     
    #21     Jan 10, 2010
  2. Without an understanding of how markets work, 'mathematical' trading is pure tactical hell.
     
    #22     Jan 10, 2010
  3. Thats very true in my experience. It would be like designing the assembly line before designing the car...
     
    #23     Jan 10, 2010
  4. How do markets work? I have never been able to figure that out in the years that I have followed them. The best that I have ever been able to do was...follow them. You sure as heck can't dictate to them or lead them. Not that I personally have any use for math in my own trading aside from adding and subtracting.

    You refer to "pure tactical hell." But isn't successful and consistent trading largely the result of tactical success? Whether you choose to trade trends or fade them, isn't profitable trading largely about getting on the train when it's headed in your chosen direction? And given the uncertainly of market movement, aren't predictive models largely full of shit? (As with the talking head market pundits, it's essential to place their inaccurate predictions alongside their accurate ones for a comprehensive assessment of their true value.)

    As I see it, engaging in an activity as laced with uncertainty as trading the markets is not unlike walking in the dark along an unfamiliar path. You keep walking carefully and not too aggressively until you reach an obstruction. When you reach inevitable obstructions, you move out of their way if you hope to continue. There is not a lot of strategy there, but a lot of tactics. Isn't that somewhat like trading, where you let your profits run, cut your losses short and don't trade too aggressively in order to survive in the long run?

    Just a final comment on your reference to "understanding how markets work." While I have familiarized myself with price action over the years and have established for myself where a relatively low-risk entry may be, I have no idea how the markets work. They are constantly contradicting themselves and each other. You're not suggesting that you can predict a trend change in advance are you? And surely you don't believe in "measured moves."
     
    #24     Jan 10, 2010
  5. heypa

    heypa

    Hey all you sophisticated complicated macho guys. IT ain't hard. When you dance with the market SHE ALWAYS LEADS! It ain't complicated you just have to follow and forget about leading.
    If it's going up you can buy.
    If it's going down you can sell.
    Note you never have to get in but you should get out when the above happens.
    Applies to swing trading only. Don't know about day trading.That requires leverage to succeed meaning exposure to ruin that I'm not willing to accept. It's a risk to return ratio that I can't handle.
    Swing trading only requires arithmetic which strains my math capabilities.
     
    #25     Jan 10, 2010
  6. nitro

    nitro

    If I may, let me rephrase your question: How can we tell at a 95% (99% ?) confidence level (reject/prove the null hypotheses) that some FX pair (stocks whatever) tend to move in certain % returns before changing direction, or persisting?

    The added insight into this problem is to be very precise in your definitions. How are you going to represent "changing direction" in a mathematically precise way that can be fed into statistical machinery? If you think about it, changing direction entails creating an angle in price/time space. Ok, we have something that is quantifiable, angles.

    Now comes the hard part. You can use standard statistics to try to see pattern in the returns data. However, it is important to understand that when you run any experiment, you are in essence testing two things, the hypotheses, and the tools you are using to test that hypotheses. It is very possible that the (mathematical) tools you use will be blind to structure in the data. For example, here is a book that describes 100 different statistical tests you can grind your data through:

    http://www.amazon.com/100-Statistical-Tests-Gopal-Kanji/dp/0761961518

    Imo the proper transform of your data is into spherical coordinates, and then run statistical tests on this data. For example, you could run your data through a V-test, sometimes called Modified Rayleigh. It is a test for randomness, checking whether angles in your data tend to cluster around a given angle. Perfect!

    Another possibility is to do the sort of analysis that Chaos Theorists do, i.e., Rescaled Range analysis. But that is probably too coarse.

    http://www.google.com/#hl=en&source=hp&q=rescaled+range+analysis&aq=f&aqi=g2&oq=&fp=e8d6ef47431c6a4a


     
    #26     Jan 10, 2010
  7. riseluxx

    riseluxx

    I'd take this post as a joke...but yeah, it wa funny.
     
    #27     Jan 10, 2010
  8. Just for fun: The St.Petersburg Paradox is an experiment that has an infinite expectancy. The problem is that the experiment is not real but requires a counterparty with infinite liquidity. Remember that LTCM had a valid concept of arbitrage but not enough money to play it out, as they used too much leverage (greed paired with false security derived from Gaussian distributions which should not be applied to non-random markets).

    Your reasoning does not seem to include the loss expectancy in case the market moves against you. The St. Petersburg experiment is "tails - she wins, heads ends the game", the FOREX market is "tails - she wins, heads she loses - and she always pays the fees". This is a little difference.

    To find a winning approach, a paradox does not help. If you can show that the distribution of returns is non-Gaussian, it is possible to find an edge. If an edge is easy to find, it is certainly difficult to trade. So this is what you can do:

    As you are certain to lose, just trade a paper account and ask a friend to enter exactly the opposite trades. If your friend trades real money, you can then share the returns :D
     
    #28     Jan 10, 2010
  9. spindr0

    spindr0

    ------------------------------------------------------------------------
    Quote from heypa:

    Hey all you sophisticated complicated macho guys. IT ain't hard. When you dance with the market SHE ALWAYS LEADS! It ain't complicated you just have to follow and forget about leading.
    ------------------------------------------------------------------------

    Don't knock that post. becasue of it, I signed up for dance lessons!

    :)
     
    #29     Jan 10, 2010
  10. bighog

    bighog Guest

    .................................................................................

    Gabflea has failed to learn how to play a game of odds. There in reality is no knowing "HOW MKTS WORK" Trading something is NOT figuring out how mkts work. If i was a baseball card trader i would care less how the cards were manufactured.

    and yes fleabag, we can predict much more in mkts than you can.............How else would we be winners in a game of chance? Measured moves: say price is in a range, has a false breakout and comes back and travels THROUGH the range and breaks out the other side with conviction...........yes you can predict price will proceed the distance of the previous range as a profit target. Trade the odds because thats the best the mkt will offer traders. Deal with what yiou have to work with and quit being so negative. :p HOG OUT!!!!

    PS: one final thought in this thread. math has its place in the world, rocket science etc, but trading something as easy as trends, etc requires only 6th grade math. Understand that and you will be far ahead of some math whiz. Trading is NOT reinventing the wheel. Trading is so easy it is difficult for the complicated.
     
    #30     Jan 11, 2010