On Finding Success Trading Forex

Will DuxonWill Duxon subscriber Posts: 3 Member

A 2014 research study carried out by the European Central Bank using information gathered from leading European brokerage firms reportedly found that close to 70% of retail Forex traders are losing money overall while trading foreign currency pairs.

Similarly, a survey conducted by Chris Davison of Trent University in London found that, according to the self-reporting of traders responding to his questionnaire, only 18% made a large profit over the previous six months with another 19.5% making a small profit.

Approximately 63% of those that remained said they either broke even, experienced a small loss, or suffered a large one. So why are 60% to 70% of all retail traders failing to thrive in the Forex market, and less than 20% reporting that they are realizing substantial gains?

When I settled on buying and selling foreign currency pairs as the means of making money via the Internet that had the greatest potential for returning significant revenue in exchange for the time and effort I would be putting into it, I chose to answer this question by adopting two biblical principles as my guide.

To unlock the secrets to success in the Forex market, I would test everything and hold fast to that which was good, as advised in first Thessalonians, chapter 5, verse 21.

I would also heed the lesson conveyed in the 16th chapter of Matthew, where the Messiah took the Sadducees and Pharisees to task for not being able to interpret the signs of the times. And as encountered again in the 12th chapter of Luke, where the Lord admonished a crowd for not knowing how to judge the times in which they were living.

Indeed, anyone attempting to trade foreign currency pairs without the ability to forecast what’s coming is almost guaranteed to meet with disappointment. I therefore made it my business to discover the Forex equivalent of a red sky, or a south wind, or clouds in the west; signs that would enable me to see beyond the horizon to know with some degree of certainty where price would most likely find itself at some point in the not-too-distant future.

Much to my surprise, this led me to reject many of the strategies wholeheartedly endorsed by any number of trading gurus, such as Elliott waves, Fibonacci ratios, harmonic patterns and the like.

Moreover, when strategies involving moving average convergence divergence, stochastic oscillators, the relative strength index and other indicators failed to live up to their reputations, I had no qualms about discarding them and searching elsewhere for the “signs of the times” which, if interpreted correctly, would result in market forecasts of unusual accuracy.

As it turns out, I found that the absolute best “atmospheric barometer” for predicting the direction in which an exchange rate might ultimately be headed was what’s known as a moving average. I therefore set about systematically evaluating all the potential moving averages one might use to forecast price action in a given time frame until I uncovered the single best measure uniquely suited for each of the respective temporal settings.

I later discovered that what I had done was develop what others refer to as a “baseline.”

Comments

  • Will DuxonWill Duxon subscriber Posts: 3 Member

    According to Global Prime, a baseline is a personal decision based on one’s own findings and there is no one-size-fits-all type of baseline. I strongly disagree with this however, though I completely agree with their contention that, after years of back testing, you must pick the baseline that best contributes to trigger the right entry signals to ride a trend while even more importantly, warning you when to abort the trade.

    But from my standpoint, a baseline should not amount to a personal decision. Rather, it should be a process of crunching the numbers so that you arrive at the one moving average which yields the highest winning percentage. Preference has nothing to do with it. It’s all about analyzing statistical data until you have objectively pinpointed the single variable leading to the most reliable, verifiable results.

    To paraphrase some of the text they posted on July 9, 2019: “When looking to build a system from the ground up, a baseline can be a priceless piece of information, one that can provide a mechanical way of entering the market and keep you disciplined in terms of engaging under the right conditions.”

    They state that a baseline is simply a moving average that is going to be the road-map to guiding you as…[to] when a pair is classified as bullish or bearish by analyzing where the close occurs. However, I would modify this to a certain extent, and say that a baseline is simply a moving average that serves as a road-map guiding you as to whether an asset’s sentiment/bias is bullish or bearish by observing whether candlesticks are tending to form above or below it, and whether the line is sloping up, down, or not at all.

    The author states that “over the years, I’ve come across a handful of moving averages that do an excellent job in being accurately respected. In my own experience, a daily exponential moving average the likes of the 5, 13 or 21 can act as great visual cue to build a personal perception of a market in a bullish or bearish phase.”

    For a time, I too felt that “a handful of moving averages can do an excellent job in being accurately respected,” but I have since come around to adopting the view that, after enough testing, one MA invariably turns out to be the best.

    The author then invites visitors to the web page to “look at how a baseline alone, in this case a 13-day EMA, which as a spoiler I must state would only constitute an initial component out of building one’s full system, would have fared.”

    Indeed, a baseline SHOULD constitute only one component within a full system. But then the author writes “the GBPUSD daily chart below triggered a total of 19 entries so far in 2019, with the simple rule being if price closes above the baseline we go long and when the close is below the baseline we go short.”

    But from my perspective, this is a silly rule. As long as the baseline remains in a definite downward slope, I personally would ONLY go short. For the author, the exit signal occurs when the price closes in the opposite side of the baseline, but for me, the exit signal occurs as soon as the short-term trend pulls back in the opposite direction against the prevailing trend, which is in effect, a take-profit signal.

    The author later states that “the ATR is an essential tool for risk management.” However, rather than use ATR I prefer to use typical price ranges in multiple time frames, as defined by dynamic, adaptive price range envelopes.

    And whereas the author recommends using volume to separate the wheat from the chaff, I’m not really all that concerned with volume. Up is up and down is down. Volume does not change this, so I’m not at all worried about it.

    As for not overlooking building confidence through back testing, it’s all about live testing for me. If I’m making money every single day, that’s all the validation I need. If up is up today, it was up yesterday too, and it will still be up tomorrow. A 5% incline from the surface today is the same as a 5% incline from the surface two thousand years ago, so why should I need to back test it? Moreover, it is not altered by market conditions, whether trending, choppy or ranging, so expanding simulations for testing is great, but once that’s complete, changing market conditions almost becomes a nonissue.

  • Will DuxonWill Duxon subscriber Posts: 3 Member

    According to Brian Millard, "moving averages are…extremely powerful tools, but unfortunately the majority of investors have no idea of how to harness this power."

    I would not dare to make such a generalized statement, but I have in fact found that how to best put moving averages to use for me personally is unlike most of the available advice that’s out there.

    Some traders, such as Nick McDonald of Trade with Precision, recommend employing the same set of moving averages, irrespective of the time frame in which one is trading. Nick suggests using the 10-, 20- 50-, 100-, and 200-period SMAs. On the other hand, Investopedia suggests that the 5-, 8- and 13-bar simple moving averages offer perfect inputs for day traders seeking quick profits on the long and short sides.

    Then again, Norm Fosback, the former head of the Institute for Econometric Research, states that "there are no magic numbers in trend following... It should be a basic requirement of any moving average trend following system that practically all moving average lengths predict successfully to a greater or less degree."

    Indeed, I have often read that the moving average one chooses is not as important as getting familiar with the way in which price interacts with it (or something to that effect).

    All of this notwithstanding, I have arrived at a somewhat rare view of moving averages most closely resembling the thoughts of those who promote the use of a “baseline.”

    To paraphrase Global Prime, a baseline is a mechanical way of entering the market and keeping you disciplined in terms of engaging under the right conditions.

    But my personal definition starts with cycle theory, which holds that cyclical forces, both long and short, drive price movements, and can be used to anticipate turning points. (According to Brian Millard, Jim Hurst’s work on cycle theory was based in part on a belief that some 23% of price motion is based on cyclic movements which are additive in nature and can be seen clearly if envelopes are constructed around the price movement.)

    It also incorporates Edgar Peters’ fractal market hypothesis, which views financial markets as fractal in the sense that they follow a cyclical and replicable pattern. (Fractals might be defined as "fragmented geometric shapes that can be broken down into parts which replicate the shape of the whole.")

    So to generate a baseline, I conduct a thorough analysis to uncover the cyclical waves which are formed in the wake of price action, then define their general frequency and magnitude, and finally plot a centered moving average that comes as close as possible to approximating the zero amplitude of the corresponding waves/cycles.

    Consequently, the claim that there is no "best" moving average is not a notion to which I subscribe—opting instead to use baselines which I calculate in the manner just described.

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