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One More Holy Grail

This is a discussion on One More Holy Grail within the Trading tools forums, part of the Trading Forum category; Originally Posted by igorad Hi, Please take a look at 2 ExFit oscillators: ExFit Stochastic and ExFit Fisher. Code: extern ...

      
   
  1. #21
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    Quote Originally Posted by igorad View Post
    Hi,

    Please take a look at 2 ExFit oscillators: ExFit Stochastic and ExFit Fisher.

    Code:
    extern int     Length         =  25;   //Period of Smoothing
    extern int     Order          =   2;   //Fitting Order
    extern double  WeightFactor   =   2;   //WeightFactor(eg. 2-EMA,1-Wilder) 
    extern double  OverSold       =  30;   //OverSold Level
    extern double  OverBought     =  70;   //OverBought Level
    extern int     Window         = 500;   //Window size in bars
    Attachment 5254

    Regards,
    Igor
    Hi Igor ,

    Are these indicators continuation of poly fit series or are they calculated differently?Thanks.

  2. #22
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    Quote Originally Posted by Tovim View Post
    Hi Igor ,

    Are these indicators continuation of poly fit series or are they calculated differently?Thanks.
    Hi Tovim,

    No, these indicators are absolutely different from the polyfit series because they use the exponential fitting algorithm.

    Regards,
    Igor

  3. #23
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    Igorad,

    I ve sent you 2 private messages. Coulnd't reach you. Can you get back to me please?

    Thank you.

  4. #24
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    Thats chinese "After life" Currency..lol

  5. #25
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    Upgrade to MetaTrader 4 Build 600 and Higher

    The new version of the MetaTrader 4 terminal features the updated structure of user data storage. In earlier versions all programs, templates, profiles etc. were stored directly in terminal installation folder. Now all necessary data required for a particular user are stored in a separate directory called data folder. Read the article to find answers to frequently asked questions.




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  6. #26
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    Discovering the Forex Holy Grail

    By: DailyForex.com

    This is a title that is hard to read or write without smiling. The “holy grail” is the mother of all Forex jokes and cynical constructions. Yet it exists, is staring us all in the face, but is widely ignored, because the psychological stresses of working with the grail are paradoxically greater than most people can cope with.
    Before the existence of the holy grail can be proven, it has to be defined, as many grail hunters are not really clear about what it is they are looking for.

    The Forex Holy Grail Concept


    The holy grail is a system or strategy with clear rules that works well enough to ensure effortless trading which is profitable overall. Very often such a system is seemingly found, only for it to fail later, at which point the grail quest must begin again. This is also a larger metaphor for the journey undergone by many retail traders as they struggle to achieve profitability by hopping between different systems and styles.

    The major mistakes that less experienced traders make when they build strategies are either to base them on too limited an amount of historical data, or to over-optimize them with too many indicators that make it curve-fitted. This is important to understand, and if you are one of these traders, the sooner that you come to the realization that this is a fruitless and time-wasting path, the better it will be for you. I hope this article will shorten your path to profitability.

    The Holy Grail Revealed


    The answer is simple. Instead of trying to build the perfect strategy that most profitably fits the historical data, take a step back, relax, and contemplate the big picture of how markets statistically tend to move. After all, as the holy grail is surely a robustly profitable trading strategy that never stops working, logic holds that it has to take advantage of a permanent and persistent “flaw” or phenomenon in the market. So forget about candlesticks and indicators for the time being, and think about speculative markets. What phenomena do they exhibit that might be exploited by the trader? There are two that are common and repetitive:

    Mean Reversion – after the price pulls away from a longer-term average price, sooner or later it always returns to the average price, which is another way of saying “what goes up, must come down”.

    Fat Tails within the Returns Distribution Curve – in plain language, markets tend to overreact, rising and falling excessively due to the human sentiments of greed and fear acting upon market participants.
    Can either of these phenomena be exploited? Looking at mean reversion first, it is possible but problematic, as stop losses may need to be very wide and profits are by definition limited. I cannot see this as the basis for a holy grail.
    The overreaction of markets and their tendency to produce excessive returns on a statistical basis is the holy grail, or rather, provides the basis for a holy grail: a methodology that will make effortless profits over time.

    The best way this can be explained is to imagine taking a handful of salt grains and throwing them up in the air. Suppose you were then able to measure the distance of each grain of salt from the throwing point. You would find that most of them would be relatively close to you, with a few outliers that had travelled further away. If you make a graph showing the distribution of the results, the graph would look like a bell curve, which is a typical and “normal” distribution:


    The bottom axis shows the distance travelled by each grain of salt. The percentages show how many grains travelled each given distance.

    Now suppose that you were constantly buying and selling randomly in the Forex market, and you measured and recorded the maximum possible gain of each trade over thousands of trades and thousands of days. If you constructed a version of the above graph with those results and superimposed it upon the earlier graph, the result would look something like this, with the dotted lines representing the market’s returns distributions:


    So, it can be established that speculative markets such as the Forex market produce more excessive returns, both positive and negative, than can be expected from a “normal” returns distributions model. A greater number of excessive price events happen than would normally be produced by simple randomness. In plain language, the market offers more big winners and losers than it really should.

    Here is the holy grail: the use of tight stop losses will remove the excessive losing events, and the use of wide take profit targets will allow the “fat tail” of excessively positive returns to be captured. Yes, it can be this simple, although it is not without a few potential pitfalls.

    In order to illustrate exactly how the fat tail phenomenon can be exploited, let’s examine some back test data run on Gold and the major Yen crosses from 2011 to 2013 over a period of 3 years. These were the most volatile and trending instruments in the Forex markets during most of this period. If a very simple trading strategy of entering upon the next bar break of any engulfing bar on the H4 chart in the direction of the engulf was followed, using a stop loss placed just the other side of the engulfing candle, the following results would have been achieved by instrument and reward to risk profit targets:


    Notice how a very simple, straightforward strategy that takes no account whatsoever of trend, direction and support and resistance can be made into a positive expectancy of 53 cents gain for every dollar risk, simply by not taking profit until reward has reached 50 times risk!

    It would be simple to improve these results by moving stop losses to break even after a certain period of time on every trade. This is because the strongest winners usually will only retest the entry, if at all, relatively quickly.

    Even the Holy Grail has Pitfalls


    The holy grail exists, but it has to be handled with caution. You can find the grail by trading the right instruments that move with maximum volatility, i.e. those markets that are most attractive to speculation, and using simple entry strategies to ensure you participate in the market’s excessive movements in the direction of your trade. You do not have to be right or forecast the major moves: you just have to be there, cut your losers short, and let your winners run. The natural tendency of the market to produce fat tails will do your work for you.

    There are two major pitfalls that this might lead you to. The first is that you will be better served by a more intelligent exit strategy than simply aiming for a fixed reward to risk multiple. You need to be booking wins above 10 R:R, ideally towards 25 R:R or even beyond, but each trade will be different. Look to exit around those levels but use some intelligence and discretion. Also, being prepared to move stops to break even when the trade is a certain distance or time in profit should help.

    The second major pitfall lies in the fact that this type of strategy will always produce very low win rates, where you will lose as much as over 90% of your trades. This will inevitably cause very large losing streaks which will severely test both your mental strength and your money management strategy. The grail gives gold, but it is hot to touch and burns the unwary! Do you have what it takes to sit through twenty or more losing trades in a row? Do you have a money management strategy that will properly protect you from ruin should you begin with a long losing streak? Will you be diversified and uncorrelated enough in order to keep losing streak risk to a minimum?

    One final danger is worth a mention. It is natural to try to filter entries. However it is very problematic to distinguish entries that are likely to reach a ratio of 25:1. Furthermore, missing just one of these winners will set back your overall expectancy, unless the method used will also filter out at least 25 losing trades at the same time.
    These are some questions to ponder and investigate. Spend some time back testing. The holy grail has been placed in your hands!


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    Articleman:
    I have been thinking on the same thing. But one thing is for shure, this is HARD psychologically. You would almost have to have an EA to do this for two reasons: 1. You can't miss a trade. It could be the rare winner. 2. You can't feel doubt and not take a trade, it could be the winner.
    mr.green likes this.

  8. #28
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    I have started to think that a reverse martingale but with some winnings set aside is a bit of a holy grail.
    Reverse martingale is where you increase the risk when you win and lower when you lose. It is supposed to give more return since winners and losers have a tendency to come in clusters.

    I have written this as a comment to a blogpost but I repost it here:

    For example:
    Risking 1% of 100000 (1000 in first round in other words).
    Lets say a RR of 1,5 (but most would probably prefer higher),
    (Winning percent 50%, doesn’t really change the calculations but how often we get winnings streaks.
    Lets risk a lets say a forth won capital since last loser.

    We first win 1500 Lets risk 375 extra next time. If a loser we are now down 1% of 101500 and 375 extra. 100110 in other words.
    Not that bad, still positive.

    Lets say I win four a row then a loser (not THAT uncommon with 50% winners),
    With 1% risked of current capital I get:
    100000
    101500
    103022,5
    104568
    106136

    105074

    With using an antimartingale of 25% risked of winnings since last loser
    100000
    101500
    103585
    106483
    110512

    106779

    I have run simple excel simulations of this and over the long run never seen this system get beat by the straight linear system.

    I alse have run a monte carlo simulation of this a few times (1000 trades in a series 10000 times) and the average is always better (by a lot) with using a modified anti martingale. The lowest outcome is lower (it actually is quite easy to calculate worst case compared to linear since that is if you get every other winner and losers. But frankly. That is highly unlikely.

    Over 1000 trades (10000 simulations) the average difference (difference calculated as winnings anti martingale/winnings linear) between the systems are average 3,8. Min 0,778 and max 139. Repeated simulations get similar results (the min stays basically the same, average is just under 4… the max varies wildly though. 400. 200 etc.)


    So... I guess... smart money managing is my "holy grail".

  9. #29
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    The Forex Holy Grail Revisited

    By: DailyForex.com

    Last week I wrote about the market phenomena that is the true “holy grail” of the Forex markets. The phenomena is the statistical tendency of market to produce excessive returns, which can be “gamed” profitably by letting winning trades run to large reward to risk multiples, which cutting losing trades short by using relatively tight stop losses. If the most volatile instruments are traded in this style, it is possible to be nicely profitable over time without having to really make any analysis or decisions. Despite that, this path has some serious pitfalls that must be avoided intelligently. In this week’s article I will go into more detail about what those pitfalls are, and some of the best ways to deal with them.

    Back to the Data


    We can begin by taking a look at the historical data showing how entries upon next bar breaks of H4 engulfing candles performed on the most volatile instruments from 2011 to 2013, a three year period, depending upon the reward to risk multiples that might have been selected as targets for trade exits:


    This table contains two immediately useful pieces of information. Firstly, we would have taken a total of 2,810 trades. Secondly, the positive expectancy per trade rises dramatically until a reward to risk ratio of 25:1 is reached, after which it rises very slowly before falling off a cliff at above 50:1. Let’s say we have been following the 25:1 model. This data is not shown in the above table, but of those 2,810 trades taken, only 139 were 25:1 winners. This means that approximately 95% of the trades were losing trades. These numbers would put a severe strain on any kind of money management strategy, as the probability of suffering enormous losing streaks would be extremely high. It is more likely than not there was a streak of between 100 and 120 consecutive losing trades during that three year period.

    There are three possible ways to improve the methodology:


    • Be more selective with entries
    • Be more selective with exits
    • Risk a consistent and very small percentage of capital per trade (Money Management)


    Let’s address each one in turn.

    Selective Entries


    Our problem is that we are currently set to enter a very large number of trades, the vast majority of which will be losers. If we can find a way to enter significantly less trades without suffering a proportionate fall in the expectancy per trade, we can worry less about the strain of likely losing streaks.

    The danger here is that when profit rests upon a relatively small number of winning trades, you have to be very careful not to cut yourself out of many of those. Fortunately, using the historical data from 2011 to 2013, there seems to be a relatively simple filter which does the job.
    To win large trades, a trend has to be present. In an uptrend, the price pulls back within the trend making a major low, and then resumes its original direction. By only taking engulfing candles in such an uptrend that make a low lower than the previous 4 candles, or that directly follow such a candle, we are able to filter out a lot of the losing trades, without sacrificing too many of the winning trades. Here is a table of the performance over the same three year period using this entry filter:


    It can be seen that overall, the total number of trades is reduced by slightly more than one third, but the winning trades tend to be reduced by a smaller percentage, resulting in rises in the expectancies from 3:1 to 50:1. The probable consecutive losing streak is reduced to somewhere between 80 and 90 trades, which is also an improvement. It is noticeable that this filter had a strongly negative effect upon the Gold trades.
    Other entry filters that could improve performance would include entering only after engulfing candles with relatively small ranges, as the total positive distance required to be a winner is shorter. Time of day and trend filters can also be applied, although these can be pretty risky. For example, Gold tends to short well before the London open and long well after the London close. The Yen pairs tend to perform well following the first candle representing the initial few hours of the Tokyo session. Bounces off major support or resistance levels can also be the origins of good trades, although it is surprising how many of the best resumptions within trends begin ahead of these levels.

    Selective Exits


    So far, we have only looked a methodology that exits at a fixed R multiple. This could be refined by setting a target based upon an average volatility or number of pips, so that trades with larger risks can be exited at smaller R multiples. Additionally, there is the question of raising stop losses to break even and beyond. We have no hard data, but it is likely that moving the stop loss to break even somewhere between two days and one week after entry, or after the trade has moved a certain favourable distance, would enhance the results. Caution is required here as there are often retests of entry zones in long-term position trading using an H4 chart.

    Of course, should the instrument being traded in an uptrend fail to make a major higher high a little way short of the desired target, it would make sense to exit at that point and take the profit.

    Money Management


    It is vital to use robust and intelligent money management techniques to minimise the risk of catastrophic loss. As a losing streak of 80 consecutive trades was probably during the three year period, risking a percentage of capital rather than an absolute amount based upon the starting capital is essential. For example, risking 1% of the starting capital on each trade would result in an 80% loss at the end of the losing streak followed by a 25% addition by the first winning trade, resulting in a total of 45%. Risking 1% of the total capital would result in a 55% loss, followed by a recovery of approximately 17%, resulting in a total of 72%.

    Always bear in mind that the more of your account you lose, the harder it becomes to make it back. A 50% loss requires a 100% gain just to get back to break even.

    A more appropriate risk per trade would be something like 0.25% of the account, which would result in a draw down to about 81% of the starting total after the likely losing streak, recovering to about 93% after the close of the first winning trade. It all depends upon your individual risk tolerance and tolerance of account draw down.

    One final warning: when you are trading correlated pairs, as in this example where three of the four instruments are Yen crosses, an additional defensive measure can be taken of reducing the total risk when taking multiple trades at the same time in the same direction. This will be especially important where all the trades are long Yen. In fact, a careful study might show that the best trades are the ones that set up on all three of the Yen pairs simultaneously, or at least that this situation produces an enhanced statistical edge.

    Trading in this systematic way requires careful study of historical data, without curve fitting. Before trying this with real money, test rigorously and be honest in answering your own questions, and be sure to study thoroughly and carefully.


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    mr.green likes this.

  10. #30
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    Hello Igor

    It is possible for you , to code Alerts to the ExFit v.2 also with Notification ,if the Colour is changing , please?

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