Grim future for day trading as a career

Discussion in 'Wall St. News' started by Q3D, Dec 9, 2015.

  1. Chris Mac

    Chris Mac

    Hey, why not ?
    I think i spent at least 20 000 hours, maybe 30 000 hours with the markets.
    During this time, 10 000 hours were dedicated to my Bloomberg, I read about 200+ books, thousands of articles, attended hundreds meetings, seminars...
    And I still learn and am happy with it.

    Merry Christmas.

    CM
     
    #181     Dec 24, 2015
    nakachalet likes this.
  2. @mohammedtrader, you said the followings:

    1....it can be very profitable for highly intellifent traders....

    2....Those who lose are not that smart and should not be trading....

    personally i find it very difficult to accept what you said.

    with due respect, you meant only those highly intellligent persons are profitable

    and those who are not profitable are not smart....?!!!!

    are you working, trading or making a living around a small circle of friends who
    feed on one another's close-ended competitiveness and misinfo?

    or are you boldly proclaiming that since you are a pro daytrader, you can attest to the fact that
    you are highly intelligent and highly profitable as well, perhaps?

    anyway, trading comrade, wishing you a very merrry christmas and
    a very prosperous coming new year as well.

    happy holidays everyone and a safe one too.
     
    #182     Dec 26, 2015
    Chris Mac likes this.
  3. @nakachalet
    Not only for becoming a member, but for training, mostly 1 on 1 with their brokers, and i get a lot of benefits, tips, tutorials, personal broker and more.
    For now i am pleased. We will have to talk in a few months, to see if that investment was worth it or not, right now i am just breaking even, soon i will make some profit (hopefully).
     
    #183     Jan 19, 2016
  4. @Aaron Cole

    glad you did help to enlighten my curiosity.

    but are you saying, even with their brokers' personal attention, you are still not
    making any profit....?

    with their masters' personal attention and all, they are still not able to pick and choose
    trades that would help you to become profitable....?

    wow.... that is really amazing then....

    beware you all wannabes....

    well, best wishes for you, hope you'll become profitable soon, k?

    nakachalet@gmail.com
     
    #184     Jan 19, 2016
  5. Q3D

    Q3D

    http://news.discovery.com/tech/apps/superhuman-a-i-can-locate-any-image-160226.htm

    "Computer vision specialist Tobias Weyand and his colleagues at Google created a deep-learning program called PlaNet, and trained it to identify locations where photos were taken based on visual cues.

    Putting the Art in Artificial Intelligence: Photos

    Imagine the ultimate game of “Where in the World is Carmen Sandiego?” Only way harder. The Googlers started by dividing up the globe into a grid, excluding the oceans and polar regions. Then they created a database for PlaNet that contained 126 million geolocated photos pulled from the Internet, Technology Review reported.

    Since PlaNet is an artificial neural network, it can learn. So the team taught the network how to identify a photograph’s location on the grid just using information contained in the pixels.

    To test PlaNet’s accuracy, Weyand and his team fed it 2.3 million geotagged Flickr images. From there, PlaNet narrowed down 48 percent of them to the right continent, 28.4 percent to the right country, 10.1 percent to the right city, and 3.6 percent to the actual street."


    The relevance of the above article to the current discussion is that artificial intelligence is now self-learning and improving at a high rate with visual pattern recognition algorithms, whereas in the past speed of processing and memory storage were AIs main advantages over human intelligence, which has been reflected in the drastic alteration in price action over the past ten years in financial markets at lower timeframes (and higher timeframes, with the markets being fractal) due to high frequency trading.

    When, not if, AI's self-evolving with visual pattern recognition is implemented in the financial markets and combined with quantum-computer high-frequency trading, the inevitable result will be increased market efficiency and there will be no inefficiency left in the markets for non-technologically privileged market participants, i.e. human discretionary traders, especially at lower timeframes, where quantum speed combined with visual processing by AI will create oscillations in the market which will appear to inferior human intelligence and perception as either random or moving at such a speed that there is no possible way to impose order on such price movement for a day trader.

    The process towards price action evolving in this direction has been accelerating in the past decade with HFT taking over a majority of the volume on the index futures markets and will only continue in the decades to come. Casino slot machines will soon look like a much more inefficient and thus exploitable alternative to the financial markets at time frames day traders trade off of.
     
    #185     Feb 27, 2016
  6. BRING THEM ON.... LOL

    there are just as many who can hardly wait....
    to see it comes to pass....

    so we can likewise, but with even more finality,
    pick and choose our targets, even more often
    and more accurately than nowadays....

    just like to juxtapose and see....

    what have we got to lose.... except a few dollars
    here and there....

    bring them on....

    not cocky but with certain degree of assurance, of course.... LOL
     
    #186     Feb 27, 2016
  7. There will always be room for money management controlled trading as the markets have always been random from a participants perspective. Any order is self-imposed in reality. Nothing wrong with this as it provides a framework---and confidence to plunge. But at the core, its still random outcomes. B
     
    #187     Feb 27, 2016
  8. Handle123

    Handle123

    When I started I thought I was a pretty smart guy, markets took all that away. When you actually trading with mouse in your hand, it is far better to be dumber than a post and be able to follow all the rules that were back tested. Let the smart part of you learn to program, reason what patterns work and concentrate 95% on what to do after you are in.

    And those who are not profitable are not smart as they didn't develop to memory good rules that worked over 3,000 sample size. You need to know all the answers before the questions in split seconds.
     
    #188     Feb 27, 2016
    fortydraws likes this.
  9. @Handle123

    u sounded more like a vendor than a trader,
    with all due respect.

    the everlasting axioms in trading is.... past performances are not indicative of future results....

    ur setups may be profitable in the morning session,
    but in the afternoon session, it most likely will be
    another kind of ball game....

    not just for you, but for everyone who trades for a living.... LOL

    what about BACK TESTING AND SUCH....?

    go figure its applicability out for today's trading circumstances.... before attempting to put your money on the table, K?

    if the trading aparatus or setups from the morning trading session are NOT even
    half way profitable for the afternoon session, WHAT ON EARTH COULD A
    TRADER EXPECT FROM BACKTESTING MILLION-SAMPLE from yonder years....?
    again with all due respect.

    just my own thought which might be worth nothing to anyone else,
    but just a thought anyway for those interested to ponder further....
     
    Last edited: Feb 27, 2016
    #189     Feb 27, 2016
  10. dealmaker

    dealmaker

    Human Traders Beat Technology on the Trading Desk
    Greenwich Associates found that firms spend more money on traders’ compensation than technology – drawing the conclusion talent beats technology.
    Traders Magazine Online News, February 26, 2016

    John D'Antona Jr.

    [​IMG]


    In the battle for trading desk supremacy, it’s the human buyside trader that bests technology.
    And all human traders can now breathe a sigh of relief in this age of algorithms, smart order routers and data servers.

    According to a recent report from market consultancy Greenwich Associates firms spend more money on traders’ compensation than technology – drawing the conclusion talent beats technology. The results of the
    Greenwich Associates 2015 Trading Desk Optimization Studyshow that the buy side spent an estimated $15.6 billion to fulfill trader compensation and technology expenditures last year. The average budget per desk grew at a similar 4% rate, to $4.57 million.

    The bulk of the increased spending in fixed income went to trader compensation. In 2015, 70% of fixed-income budgets were devoted to compensation--up sharply from 62% in 2014—with the remainder spent on technology. The split for equity trading desk budgets was steady at 70/30 in favor of compensation from year to year.

    Although e-trading in most market segments continues to grow, the idea that talent trumps technology is taking over. “Technology is only as good as the people behind it, and buy-side trading desks are putting their money where their mouth is,” said Kevin Kozlowski, Greenwich Associates Analyst, and author of the study. “Buyside trading desks need to be staffed with skilled technicians who have a strong understanding of both the financial markets and the advanced trading technologies used to execute trades.”

    Technology After Talent

    Nearly 60% of the trading desk technology budget was comprised of just two key expenditures. Thirty-five percent of the estimated total covers the cost of access and licensing fees for market data terminals used on the trading desks—like Bloomberg, Thomson Reuters and FactSet. An additional 23% pays for the order management systems (OMS).

    “After several years of rapid adoption of new technology and tools to assist in trading, institutional investors are poised to take the next steps as the markets continue to evolve,” Kozlowski said.
     
    #190     Feb 27, 2016