Introduction and course of study
The “The Forex Exchanger” project is based on the simple concept of what the forex market really is: a market for currency exchange.
I have always considered that one of the most profitable ways to trade in the forex market is one of the few logical things to do: buy currencies when they are being sold massively, and sell currencies when they are also being bought.
Of course, the concept of overbought/oversold (from this moment I will call it OBOS) is very easy and short to describe the logic behind the strategy but it is definitely a good starting point.
As most traders should know, using the OBOS approach can give very nice inputs but also a lot of pullback if the expected move doesn’t happen.
For this reason, I have always spent a lot of time and great effort studying consistent methods of catching the best probability entries to make the price pay for a trade: it basically consists of waiting for a good price momentum in the direction of the entry before making a decision. He. She.
Easy to say but not easy to do, or at least, not always…
Even if the entries are as accurate as possible, it is possible for the market to move against them. Fortunately, there are a few things that can help the strategy to recover the loss better, such as calculating the average price with additional entries, but this means that this will be necessary to increase the bids and risks.
Given the basic idea of OBOS, the fact that the market will reverse is arithmetic: we are trading forex, not cryptocurrency.
Reversing the market is mathematical but it is impossible to predict when, for this reason, the most important and sensitive thing is to calculate the average price in a logical and smart way and only if there are good probability settings.
More logic and cleverness we manage it, less time we’ll stay in the market and we’ll suffer less pullback: that’s the key.
All profit targets are formed on each of the characteristics of the pair and will not be equal between two different times or at two different times. This makes the strategy fully adjustable to different situations and pairs, taking into account its intrinsic characteristics, volatility and temporary behaviors.
I have used a lot of different precautions to make this strategy less effective from external factors like: different brokers, news releases, spreads, slippage, etc.
I know very well that there are developers who like to improve their Expert Advisors (EAs), statistically forcing them to provide the best equity possible, but that was never my goal and never will be!
What they are doing is basically shaping the EA to perform perfectly in the past. It is only useful for introducing (and boosting sales of their products) but not for making the strategy more robust (which I hope is the main objective of every trader in the world).
Anyway, I’m not here to discredit other people’s posts but to give me the value I deserve.
To achieve good consistency I used some important details like:
Check high time frames setup scenarios.
Using indicators on lower time frames with large time values to reduce market noise and restore strong and clear information.
News that was completely ignored in the past (I will never think about it in the future, but I can manually intervene due to global political and economic situations: nothing any algorithm can predict!)
ATR was used and pips/pips were never used. (This is quite evident when working on multiple symbols that have completely different properties, volatility, average ranges and hash values!)
I found a lot of interesting things that worked well for several years in the entire forex market (28 pairs, exotic pairs not considered).
I always make improvements step by step, focusing on “improving concepts rather than parameters”.
This means, for example, that I would never try to make improvements around the value of RSI intervals using 10,11,12,13,14,15,16 etc., and find the best performance in the past: it doesn’t make sense.
I prefer checking if the RSI works better than another oscillator or if the RSI set of rules has worked better on others to capture and analyze a given scenario: this is what would be considered a smart optimization and this is the approach I always keep in mind when I study and build a strategy.
Let me begin by saying that every performance estimate for an investment is based solely on past performance and, as such, must be taken into account up to a certain level and not as an accurate prediction of the future: this seems reasonable to someone but not to him. all people.
The real difficulty of all strategies lies not in shaping them to trade perfectly in the past, but in making the strategy itself able to adapt to different market scenarios and “survive” in very different situations.
As we explained earlier, all tests and optimizations of this strategy were not focused on maximizing profits with it, but on finding a good balance of all these factors: profit factor, maximum drawdown, average hold of positions, linear regression of the equity line, ratio Expected annual growth compared to the maximum decline% and others.
The result is simple: by combining all the factors, I can perform more reliable tests without choosing the “most profitable”, but the most stable and sustainable strategy.
Here are some background screenshots of the strategy over the past five years.
balance and fairness
Monte Carlo prediction
Check Monte Carlo
The expected growth depends on the combination of risks. All of the above tests are performed with a “moderate” risk factor.
In my opinion, the option is the best compromise because there is an interesting ratio between growth and risk.
With this option, the expected profit per month will be around 6-7% and annual growth around 80-120% (deviations up or down can occur for many different factors that cannot be expected).
Most of the time the maximum drawdown will be less than 30%.
Q: Is this strategy suitable for any type of investor?
A: This is definitely a suitable strategy for a long-term investment. Its main objective is to provide consistent profits on a monthly basis (and above). It makes no sense to analyze the results on a daily or weekly basis (this is true for almost all investments in the world).
Q: Is this strategy over-processed or exaggerated?
A: Absolutely not. All of my improvements to this strategy (and all of my strategies in general) focus on “improving concepts rather than parameters”. I have already explained before what I mean by this.
Q: How much rollback can I get?
A: Of course it depends on the risk profile. In any case, even if the setting used for undo is a maximum of 30%, be aware that it will be lower most of the time, with few possibilities of it being greater.
Q: Do I have new deals every day?
A: No, since the markets do not allow for many edges and to trade (and make money) consistently, it is necessary to wait for good probability setups.