![McDonald's Pattern [LuxAlgo] chart preview](/_next/image?url=%2Fmedia%2Ffull%2F26206.png&w=3840&q=90&dpl=dpl_Jt27hmzh6tNsGuJ13vyBBWgv8XSW)
A meme-inspired trading indicator that identifies a McDonald's logo-shaped pattern using cubic Bezier curves, detecting specific market tops and bottoms with a unique visual representation.
Explore complementary indicator rolesHow it works
The indicator uses a rolling maximum and minimum method to detect market tops and bottoms, fitting these points into a cubic Bezier curve. It analyzes the distance and relationship between these points to approximate an M-shaped pattern reminiscent of the McDonald's logo.
The script calculates a pattern score displayed on the chart, indicating how closely the detected pattern matches the ideal configuration. It uses a specific length parameter to adjust the sensitivity of top and bottom detection
Why it may be useful
This playful indicator offers traders a unique and entertaining way to visualize market movements through a recognizable shape. While primarily a meme tool, it can spark creative thinking about market patterns and price action.
The visual representation helps traders quickly identify potential trend reversals or specific market structures. The scoring system provides an additional layer of pattern recognition, encouraging traders to think critically about market dynamics
When to explore it
The McDonald's pattern indicator works best in markets with clear trending characteristics and distinct price movements. Traders might find it most useful in cryptocurrency or volatile markets where price swings are more pronounced.
It's particularly interesting for swing traders looking for unconventional pattern recognition methods. The indicator should be used alongside more traditional analysis tools and not as a standalone trading strategy
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What we’ve verified
Access, alerts and repainting behaviour have not been independently verified for this indicator. Check the creator’s current publication and settings.
General descriptions and classifications are recovered research. Verified details above identify the specific checks we have completed. Check the creator’s current publication for later changes.

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