Technical Analysis alone will not give you an edge
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Thread: Technical Analysis alone will not give you an edge

  1. #1
    Good evening my fellow traders, I have been a student of the market since 2011 when I combined FF. The whole concept of investing, and obtaining profit through fluctuations in price movement has fascinated me. I have not been fortunate enough to blow accounts as many of you have, I enjoyed relative success in the markets earlier on which fueled my hubris. I surmised that observing charts, studying patterns, utilizing some type of money management subject and system has been responsible for my success. I have studied Technical Analysis tools broadly, Parabolic SAR, from MACD, Stochastics, RSI, S/D, S/R, candle stick patterns, you name it.

    I have began taking trading seriously recently, not just as an interest and a passion except to dedie my time like this a second carrier. I see many here purport to have the ability to forecast price, to stick to the market, many here will inform me that you've learned the skill to do this successfully. I'll respectfully disagree with you, I go as far as to call it Bull shit. In almost any area of human history where a phenomenon is not well known, not understood, or plainly random... there'll be superstition, there'll be an array of different methods, some contradictory that is only going to work because of pure chance. I claim yours is not any different.

    When analyzing such a happening, the very best tools at our disposal is the scientific method... 1- ask a question, two - do study, 3- formulate a theory, 4- test your theory, 5- evaluate your outcomes, 6- communie your findings.

    From readying probability theory and statistics I claim you cannot profit from arbitrary data, do you concur with my claim? If you do not let us talk about your ideas here as I am prepared to change my thoughts given the signs.
    In case you do not contest my claim then the very first question one needs to ask is.... Is the market arbitrary? Then hypothesis should be that it is; unless the evidence points to it not being arbitrary.

    So how do we test for randomness? Let us begin with asking this questions in the statistical sense.... For the data to be arbitrary a distribution that is random must be followed by it? Can you concur? Below are just two distributions

    1- fitted into the euro/usd named DEXUSEU in the Saint Lous FRED, this data is a complete of 4227 euro logarithmic returns


    here is the density of a randomly generated data of a sample size of 4227


    when we do a QQ plot of euro.log, normally distributed data we can see the fit


    My ideas: the euro log density seems to possess more peakedness and thicker tails, this however just shows that the volatility of the data differs not that it is or isn't predictable. Therefore, how do we do a test for randomness?

    Statistically we would see if there is any serial correlation (auto correlation) significance: Autocorrelation, also called serial correlation or cross-autocorrelation, https://en.wikipedia.org/wiki/Autoco...on#cite_note-1 is the https://en.wikipedia.org/wiki/Cross-correlation of a https://en.wikipedia.org/wiki/Signal...mation_theory) with itself at different points in time (that is what the cross stands for). Informally, it is the similarity between observations as a function of the time lag between these. It's a mathematical tool for finding repeating patterns, like the existence of a periodic sign obscured by sound, or identifying the https://en.wikipedia.org/wiki/Missing_fundamental frequency in a sign implied by its https://en.wikipedia.org/wiki/Harmonic frequencies. It's frequently used in https://en.wikipedia.org/wiki/Signal_processing for assessing functions or series of values, for example https://en.wikipedia.org/wiki/Time_domain signals. -- wikipedia


    here is your auto correlation of a random information


    here is also the Partial Auto correlation function:
    In https://en.wikipedia.org/wiki/Time_series_analysis, the partial autocorrelation function (PACF) gives the https://en.wikipedia.org/wiki/Partial_correlation of a time string with its own lagged values, controlling for the worth of the time series at all shorter lags. It contrasts with an https://en.wikipedia.org/wiki/Autocorrelation_function, which does not control for other lags.
    This function has an important role in data analyses aimed at identifying the extent of the lag within an https://en.wikipedia.org/wiki/Autoregressive_model. The use of this function has been introduced as a member of the https://en.wikipedia.org/wiki/Box–Jenkins method of time series modelling, where by plotting the partial autocorrelative works one could determine the appropriate lags de within an AR (p) https://en.wikipedia.org/wiki/Autoregressive_model or within an extended https://en.wikipedia.org/wiki/Autore...moving_average (p,d,q) model.

    PACF of the Euro

    PACF of arbitrary information


    Decision: as you can see that the Euro does not breach the confidence intervals, the data does not seem to be connected which affirms the hypothesis of arbitrary data. Below are the results of the correlation

    Autocorrelations of series'x', by lag
    0 1 2 3 4 5 6 7 8 9 10 11
    1.000 0.012 -0.013 0.000 0.035 -0.035 0.016 0.028 -0.002 -0.003 -0.019 0.006
    12 13 14 15 16 17 18 19 20 21 22 23
    0.013 0.018 -0.004 -0.012 -0.006 0.013 0.005 0.016 0.008 -0.012 0.011 -0.012
    24 25 26 27 28 29 30 31 32 33 34 35
    0.008 -0.004 0.007 0.002 0.005 0.017 -0.004 -0.002 -0.003 -0.008 -0.007 0.007
    36
    -0.011
    gt; acf(rnorm(4227), plot=FALSE)
    Autocorrelations of string'rnorm(4227)', by lag
    0 1 2 3 4 5 6 7 8 9 10 11
    1.000 -0.029 0.034 -0.034 0.010 0.007 0.004 -0.006 -0.002 -0.024 0.009 0.000
    12 13 14 15 16 17 18 19 20 21 22 23
    -0.015 -0.020 0.006 -0.006 0.013 0.005 -0.003 0.001 0.010 0.002 0.014 -0.002
    24 25 26 27 28 29 30 31 32 33 34 35
    -0.006 0.011 -0.001 -0.008 -0.013 0.004 0.017 0.004 0.020 -0.012 0.014 0.002
    36
    -0.007

    let us look for trend and volatility in the data that the first one is euro, the next is a random normally distributed data




    I will see a gap in the distribution, the top red and lower red lines are at sigma a single (standard deviations 1 and -1) the red line at the middle is that the SMA of 22 = monthly, the yellow lines is that the SMA 22*12= 264 which will signify a yearly smoothing, the blue line is to illue H0

    Brain sees a gap in the distribution but the monthly smoothing looks similar I can see either actual or imagined signs of tendency in the data.

    Lets look at the Hurst Exponent

    gt; hurstexp(x)
    Simple R/S Hurst estimation: 0.5614027
    Corrected R over S Hurst exponent: 0.5815521
    Empirical Hurst exponent: 0.5223035
    Corrected empirical Hurst exponent: 0.5014898
    Theoretical Hurst exponent: 0.5211121

    gt; hurstexp(rnorm(4227))
    Simple R/S Hurst estimation: 0.5169296
    Corrected R over S Hurst exponent: 0.5302739
    Empirical Hurst exponent: 0.5114854
    Corrected empirical Hurst exponent: 0.4897964
    Theoretical Hurst exponent: 0.5211121

    the Hurst exponent is just another measure of randomness especially Persistence, positive where Hgt;50 Hlt;1 would indie a trending element Whilst Hgt;0 Hlt;50 would reveal mean reversion.
    The Hurst exponent is used as a measure of https://en.wikipedia.org/wiki/Long-range_dependency of https://en.wikipedia.org/wiki/Time_series. It is related to the https://en.wikipedia.org/wiki/Autocorrelation of the time series, and the rate at which these decrease since the lag between pairs of values increases. Studies between the Hurst exponent were originally developed in https://en.wikipedia.org/wiki/Hydrology for its practical matter of discovering optimal dam sizing for its https://en.wikipedia.org/wiki/Nile_river's volatile rain and drought conditions that was detected during a lengthy period of time. Https://en.wikipedia.org/wiki/Hurst_...nt#cite_note-1https://en.wikipedia.org/wiki/Hurst_...nt#cite_note-2 The title Hurst exponent, or Hurst coefficient, derives from https://en.wikipedia.org/wiki/Harold_Edwin_Hurst (1880--1978), who had been the lead writer in these types of studies; the use of the typical notation H to its coefficient relates to his title too.
    In https://en.wikipedia.org/wiki/Fractal_geometry, The generalized Hurst exponent was denoted by https://en.wikipedia.org/wiki/H_(disambiguation) or Hq in honor of both Harold Edwin Hurst and https://en.wikipedia.org/wiki/Otto_Ludwig_Holder (1859--1937) by https://en.wikipedia.org/wiki/Benoît_Mandelbrot (1924--2010). Https://en.wikipedia.org/wiki/Hurst_...nt#cite_note-3 H is directly related to https://en.wikipedia.org/wiki/Fractal_dimension, D, and is a measure of a data collection' wild or mild randomness. Https://en.wikipedia.org/wiki/Hurst_...nt#cite_note-4
    The Hurst exponent is popularly called the index of addiction or index of long-range dependence. It quantifies the relative trend of a time series to cluster in a way or to regress closely to the expression. Https://en.wikipedia.org/wiki/Hurst_...nt#cite_note-5 A value H in the range 0.5--1 indies a time string with long-term positive autocorrelation, meaning that a high value in the show will probably be followed by another high value and the values a very long time into the future will also tend to be high. A value in the range 0 -- 0.5 indies a time show with long-term shifting between low and high values in adjacent pairs, meaning that a single high value will probably be followed by a low value and the value then will tend to be higher, with this inclination to switch between low and high values lasting quite a while later on. A value of H=0.5 can indie a completely uncorrelated show, but in fact it is the value applicable to series where the autocorrelations at little time lags could be negative or positive but where the absolute values of the autocorrelations decay exponentially rapidly to zero. This compared to the typically https://en.wikipedia.org/wiki/Power_law rust for the 0.5 lt; H lt; 1 and 0 lt; H lt; 0.5 instances. --wikipedia

    now we can assess the Runs Test for randomness


    gt; runs.test(x,plot=TRUE)
    Runs Test
    data: x
    statistic = 2.1203, runs = 2163, n1 = 2080, n2 = 2107, n = 4187, p-value =
    0.03398
    alternative theory: nonrandomness

    gt; runs.test(rnorm(4227))
    Runs Test
    data: rnorm(4227)
    statistic = 1.3846, runs = 2159, n1 = 2113, n2 = 2113, n = 4226, p-value =
    0.1662
    alternative theory: nonrandomness

    since you can observe the P-value about the data x =eur/usd seems be contrary to the hypothesis of randomness

    to complete my opinion, I assert that with the statistical instruments at our disposal it is quite tough to inform the Eurusd data from a Random normally distributed data, so T/A alone would be similarly hard to differentiate from a brownian motion monte carlo simulation and the real market. I assert you cannot profit from T/A alone the allegations of profiting are likely to be false.

  2. #2
    Quote Originally Posted by ;
    Hi There, My five cents worth You will never WIN if you are frightened to LOSE.
    My $2,000,000 values, '' There would be a greater percentage of statisticians from the retail trading area if our lives depended on it

  3. #3
    Very good conversation. I will give example to you which you can't predict future movements looking in the last price action.

    That is 2.12.2015.

    I am trading USD CAD long using current sentiment and price action. I wager that CAD will weaken because OPEC will not agree on oil production cuts with Saudi Arabia. But then stuff happened. News hit the wires that majority of OPEC members consented manufacturing cut:



    However, in 3 minutes another news hit the wires which gulf countries (like Saudi Arabia) will not support production reduction:



    It turned out majority of OPEC members weren't significant tiny nations, who have little influence in OPEC.

    Great luck with RSI, MACD and other fairy tales indiors to predict this.

  4. #4
    Quote Originally Posted by ;
    Very good discussion. I will give example to you that you cannot predict future movements looking at the last price action. That is 2.12.2015. I am trading USD CAD using current sentiment and price action. I bet that CAD will weaken since OPEC won't agree on oil production cuts with Saudi Arabia. But then things happened. News hit the wires that majority of OPEC members agreed on production cut: image But in 3 minutes the following news hit the wires that gulf countries (including Saudi Arabia) won't support creation cut: image It was...
    I think you have missed the point around TA, and FA, too. Fundamentals could force a reset of TA, which explains the reason why traders go defensive before FA (unexpected FA's collapse under the egory of shit happens, and you just put them behind you and move on). So, like I have advoed in other threads in FF and here, a crystal clear image of construction emerges, and also after the FA has been digested, it is possible to return to commerce and a TA. Once this FA was from the market, the CAD traded technically , and has done so through past week. Hope you have some of the move up, as most professional traders have been inside it and bidding it up as oil plunged.

  5. #5
    Is the evidence based on a 1 minuet chart

    Quote Originally Posted by ;
    Very very good discussion. I will provide example to you which you can't predict future movements appearing at the past price action. This is 2.12.2015. I'm trading USD CAD using current sentiment and price action. I bet that CAD will weaken since OPEC won't agree on oil production cuts with Saudi Arabia. But then things happened. News hit the cables which majority of OPEC members agreed on production cut: image But in 3 minutes the following news hit the wires which gulf countries (including Saudi Arabia) won't encourage production cut: image It was...

  6. #6
    Quote Originally Posted by ;
    quote I think you've missed the point about TA, and FA, also. Fundamentals could force a reset of TA, which explains the reason why traders go defensive ahead of FA (unexpected FA's fall under the egory of shit happens, and you simply put them behind you and move on). So, as I have advoed here and in other threads in FF, once the FA has been digested, and a image of arrangement emerges, it is possible to return to commerce and a TA. Once this FA was in the market, the CAD traded technically again, and has done. Hope you got...
    I think you missed the reality.

    There are lots of events occurring daily. Some are proposed and some are not planned. I would rather learn how to trade the occasions to wait for some reset that will be destroyed by yet another event that is unplanned.

  7. #7
    Quote Originally Posted by ;
    is the evidence based on a 1 minuet chart quote
    No, I simply employed 1m for my own notes.

    I have many such events that interval 100 pips. For example:



    23 November 11.10 GMT. News hit on the cables, that government official of Saudi Arabia reported they will do what to stabilize oil price/market.
    CAD fortified 100 pips over the course of the day.

    Great luck with just TA about this. It was no. The news.

  8. #8
    Quote Originally Posted by ;
    quote I believe you missed the facts. There are various events happening. Some are planned and some are not intended. I would rather learn how to exchange the occasions, then to wait for some reset which will be ruined by another unplanned event.
    I'm sorry but you do not have a reasonable grasp on the Currency Market market. If you feel this, then you need to find another line of work. That is beyond wrong.
    Edit: I'd stay away from the 1M charts, and begin your thinking and analysis on daily or 4H. Maybe your perspective will change.

  9. #9
    Your thinking in a fundamental way,also I would think fundamental is defiantly suited to this longer term retail guy,

    Fundermental is the issue for you,I would def suggest you do not follow it in great detail
    btw oil so cad,possess some very ugly drivers right now fundamentally,


    Quote Originally Posted by ;
    quote I believe you missed the reality. There are various events happening daily. Some are planned and some are not intended. I would rather learn how to trade the occasions, then to wait around for a few reset which will be ruined by yet another event that is unplanned.

  10. #10
    I have no idea how your approaching it,if I were to scalp identification take something low spread reliable,EU,
    then chuck a Bollinger on,then once I visit price make a change outside input,its a 5 min chart don't expect to much
    you can I guess also track something such as h1,avert planned news
    over the years you can see further outside / prettier price
    further it goes,




    Quote Originally Posted by ;
    Very good discussion. I will give example to you that you cannot predict moves appearing at the past price action. This is 2.12.2015. I'm trading USD CAD with current sentiment and price action. I bet that CAD will weaken because OPEC won't agree on oil production cuts with Saudi Arabia. But then things happened. News hit the wires that majority of OPEC members consented production cut: image But in 3 minutes another news hit the wires that gulf countries (like Saudi Arabia) will not support creation cut: image It was...

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