Discussing the article: "From Novice to Expert: Developing a Liquidity Strategy"

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Liquidity zones are commonly traded by waiting for the price to return and retest the zone of interest, often through the placement of pending orders within these areas. In this article, we leverage MQL5 to bring this concept to life, demonstrating how such zones can be identified programmatically and how risk management can be systematically applied. Join the discussion as we explore both the logic behind liquidity-based trading and its practical implementation.

Through our analysis, we have established that a liquidity zone can often be represented by a single candle. Such a candle typically emerges after a period of price pause or consolidation and encapsulates liquidity that has formed over time or across lower timeframes. This behavior is precisely what produces the structural model we are working with in this study.

For clarity and accessibility, we deliberately adopt a simplified approach. Rather than relying on complex multi-bar formations, we define our conditions using minimal price information. This allows us to focus on the core mechanics of the strategy while making the initial implementation in code straightforward and easier to validate.

The objective of this strategy is to return price to the identified liquidity structure (see Fig. 1 below) and build positions from that area, ultimately targeting the most recent swing high or swing low, depending on whether the setup is bullish or bearish. While the concept of a retest is central to this model, it is also important to recognize that it has become a common and widely studied idea. As a result, such levels are increasingly vulnerable to manipulation. Market participants with significantly larger capital can push prices beyond obvious boundaries, triggering stop losses and forcing weaker positions out of the market before the intended move unfolds. 

Author: Clemence Benjamin

[Alexander Balandin]

Здравствуйте, Бенджамин . Оптимизировал ваш советник на m30 (на m1 не анализировал, так как слишком маленький TP- и мой брокер не разрешает открытие сделки) в 1-м режиме - "каждый тик на основе реальных тиков" и во 2-м режиме - "все тики" (это необходимо, так как МТ5 в 1-м режиме находит скачки цены, котрых нет в РЕАЛЬНОСТИ, и за счет этого дает очень положительную прибыльность тестирования!!! - что неверно в реальности). К сожалению, во 2-м режиме стратегии "все тики" после оптимизации не дала ни 1го положительного результата, либо результаты положительные, но очень очень слабые (а в 1-м режиме наоборот!! результаты сумасшедшие - если включить увеличение ЛОТА балансового баланса, получилось за 3 года 3000% с просадкой по балансу 1% ...). Анализировал 3 актива (акции, не фьючерсы!). ГАЗП, ВТБР, АФЛТ

ps Изучив ваш метод определения ликвидности ЗОН (к сожалению, немного написано об этом в статье), считаю, что тестирование в 2м режиме не должно влиять на определение вашего МЕТОДОМ зоны ликвидности.

С уважением, Александр.

Hello, Benjamin. I optimized your EA on m30 (I didn't analyze it on m1 because the TP was too small and my broker doesn't allow trades). It used mode 1 - "every tick based on real ticks" and mode 2 - "every tick" (this is necessary because MT5 in mode 1 finds price spikes that don't exist in REALITY, resulting in very positive testing profitability!!! - which isn't true in real life). Unfortunately, after optimization, the "every tick" strategy in mode 2 didn't produce a single positive result, or the positive results were very, very weak (and in mode 1, it was the opposite!! The results were incredible - if you include the balance LOT increase, the result was 3000% over 3 years with a balance drawdown of 1%...). I analyzed 3 assets (stocks, not futures!). GAZP, VTBR, AFLT

ps. Having studied your method for determining the liquidity of the zones (unfortunately, little is written about this in the article), I believe that testing in the second mode should not affect the determination of your METHOD'S liquidity zone.

Sincerely, Alexander.