Swing Failure Pattern SFP

How To Trade Swing Failure Patterns: Unlock the Secrets

The Swing Failure Pattern (SFP) is a powerful trading strategy for understanding liquidity and price action. Experienced traders often use it to identify potential trend reversals and capitalize on key support and resistance levels. You’ll learn how to trade Swing Failure Patterns, from identifying the setup to determining entries, invalidation points, and profit-taking levels.

What makes this pattern so effective is its adaptability to any time frame, making it a versatile tool for both short-term scalpers and long-term swing traders. The SFP provides a unique edge in predicting market movements by focusing on how price interacts with significant highs and lows.

In this article, we’ll explore its fundamentals and application in various market conditions. Understanding this strategy can elevate your approach to analyzing and trading market trends, whether you’re a beginner or a seasoned trader.

What is the Swing Failure Pattern?

The Swing Failure Pattern (SFP) is a liquidity-based strategy typically used by larger traders to fill their orders. It’s a valuable technique for identifying potential trend reversals, and its easy readability and application make it powerful and highly effective.

The SFP focuses on price action, so we must pay special attention to the candlesticks and their wicks. In this pattern, the price attempts to swing above a significant high or below a significant low but fails to sustain the move, resulting in a trend reversal.

A great advantage of the SFP is that it occurs in all time frames (TF). We can find it from 1-minute TF to 4-hours TF, or even daily, weekly, or monthly; the higher the time frame, the stronger its effect on the market.

Swing Failure Pattern - Liquidity Grabs

Market Conditions for a Swing Failure Pattern

Low-volume environments are usually built over extended periods, forming a range. The Swing Failure Pattern strategy works perfectly in this context, taking advantage of the accumulated orders during this time.

When the market is in a range or consolidation, and the volume is relatively low, larger traders find it challenging to open new positions. If they want to open large positions, they could significantly move the price, generating slippage and adversely affecting the result of the trade.

Slippage refers to the discrepancy between a trade’s expected price and the price at which it is executed. It often occurs due to market volatility, low trading volume, and order type.

SFP: How Liquidity works

To understand the theory behind the SFP, it’s necessary to comprehend how liquidity works.

We know two ways to open a position: market orders and limit orders. Market orders can move the market as they are executed immediately. Limit orders are placed in the order book, waiting for a seller or buyer to fill the position.

If we have a large capital to trade and the market has low volume, we could face the following liquidity issues if our average volume entry is greater than the average volume range.

Opening a position through a limit order will not guarantee that all contracts will be executed, as there are not enough buyers or sellers in that range. On the other hand, opening a position using a market order with a big position size could execute the order at the desired price. Opening a long could cause the order to execute at a much higher price or, if opening short, a lower price than expected.

Swing Failure Pattern Liquidity Areas

In a range, we expect most retail traders to participate and place stop losses at the edges. We use this information to fill our larger orders, either using limit orders or market orders. The swing failure pattern is a technique that will help us find where most of the orders are sitting.

How to trade Swing Failure Patterns

The foundation of the Swing Failure Pattern strategy is the identification of significant support and resistance levels. These are swing highs or swing lows, areas where the price has reversed, indicating an important supply and demand zone. Here are two techniques to take into consideration when identifying levels of support and resistance for the SFP:

  • Confirming the Market Structure: As discussed before, the ideal market condition to trade an SFP is during the price consolidation or range. A range is characterised by an asset moving within a narrow, horizontal boundary. In a ranging environment, we expect to see the price print a series of equal highs and lows, with partial rises and partial declines.

Swing Failure Pattern Range Market Structure

  • Identifying Swing Highs and Swing Lows: Swing highs and lows are local maximums or minimums where the price stops the trend and starts to reverse. A swing high can be identified by a low with two candles on either side being lower. A swing low is identified by a candle high with 2 candles on either side being higher.

Candlestick Swing High and Swing Low

  • Supply and Demand zones: In trading, supply refers to the areas on a price chart where selling pressure is strong enough to prevent a further rise in price. The demand zone refers to the areas where the buying pressure is strong enough to prevent a further fall in price.

Supply Zone and Demand Zone

The identification of the Swing Failure Patterns setup

The benefit of the SFP as a setup is the clear entry and invalidation area given. When the market is in a consolidation phase, we wait for the high or low to be taken. There’s no specific time for this, and we should be patient. When the price takes the highs/lows, it would be through a wick, and the candle will close back within the previous range, gaining acceptance.

Entry and Invalidation

The entry of the SFP setup is clear; the confirmation would be a candle close within the previous range or a candle close below the significant high or above the significant low. The invalidation of the SFP setup is just above the new high or below the new low recently made.

Example of Bullish SFP

In a Bullish SFP, the price takes the low through a wick and closes back above the significant reference point; the probability of reaching the high of the range next is high. In this instance, we take profits at the top of the range.

Swing Failure Pattern Entry

Example of Bearish SFP

In a Bearish SFP, the price takes the high through a wick and closes back below the significant reference point; the probability of reaching the low of the range next is high. In this instance, we take profits at the bottom of the range.

Taking Profits

Taking profits on the SFP setup will mostly depend on the levels within the range. Generally, we use day trading indicators such as Session VWAPs or fixed-range volume pulls to determine the continuation probabilities. However, considering only the price action, there’s a high probability of the price reaching the opposite side of the range.

A good practice is always combining other levels of confluences within the range to take partial profits as the SFP develops. The indicators that can be used are:

  • VWAP Indicator
  • Value Area High and Value Area Low (Fixed Range Volume Profile tool)
  • Point of Control (POC) of the range or previous days
  • Horizontal levels, such as Daily, Weekly and Monthly

The indicators and tools mentioned will provide pivotal levels where the price can bounce and could serve to take partial profits as the SFP develops within the range. However, as mentioned before, the high probability lies in favour of the price reaching the contrary side of the range.

Conclusions

The Swing Failure Pattern will help us spot nice areas of liquidity, allowing us to trade a trend, a market reversal, or just a bounce. It can occur in all time frames, so it will fit most traders’ styles, from the 5-minute up to weekly or monthly timeframes.

With time and experience, it is possible to master the Swing Failure Pattern strategy and find interesting statistics around this pattern, considering the market conditions. The high risk and reward setup makes it a powerful strategy for traders in every market, from the traditional market to futures and from stocks to cryptocurrencies.

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