Pattern Bot

Overview

PTRNBOT is a sophisticated pattern detection bot designed to analyze price action and identify pivot patterns. By leveraging historical patterns, this bot provides traders with insights into potential market movements, empowering them to make more informed trading decisions. With the introduction of Quant Mode, users can gain deeper insights by analyzing similarity measures using advanced mathematical techniques.
Key Features

Pivot Pattern Detection: PTRNBOT scans for pivot highs and lows, forming recognizable patterns that have historically signaled significant price movements. These patterns are clearly marked on the chart for easy identification and analysis.

Historical Pattern Analysis: The bot not only detects current patterns but also analyzes past occurrences of similar patterns, providing insights into what happened the last time these setups appeared. This historical context helps traders anticipate potential future moves.

Quant Mode:
Enable Deep Analysis: Activate Quant Mode to display similarity measures, including Euclidean distance, Dynamic Time Warping (DTW), Cosine Similarity, and Pearson Correlation.
Quantitative Insights: Quant Mode provides a detailed comparison of current and historical patterns, allowing traders to quantify how closely the patterns match.
Toggle On/Off: Easily toggle Quant Mode on or off depending on your analysis needs.

Customizable Parameters: Adjust parameters such as pattern length, lookback periods, and the option to enable Quant Mode to tailor the indicator to your specific trading strategy.

Visual Indicators: The indicator plots shapes on the chart to signify different pivot types (Higher High, Higher Low, Lower High, Lower Low), making it simple to spot critical price action.

Dynamic Data Table: Displays a summary table of detected patterns, including similarity scores and historical occurrences. The table adapts based on whether Quant Mode is enabled, providing a clear snapshot of potential next patterns.

How It Works

Pivot Detection: The indicator uses the ta.pivothigh and ta.pivotlow functions to identify significant pivot points on the price chart, marking them with shapes for easy visualization.

Pattern Recognition: Once a pattern is detected, it extracts the sequence of pivots and compares them against historical patterns stored in its database. This comparison helps identify patterns that have previously led to profitable moves.

Similarity Analysis (Enabled with Quant Mode):
Euclidean Distance: Measures the straight-line distance between current and past pattern points, providing a metric for pattern similarity.
Dynamic Time Warping (DTW): Calculates the similarity between time series with shifts and distortions, offering a more flexible pattern comparison.
Cosine Similarity: Evaluates the angle between pattern vectors, indicating directional alignment and strength of correlation.
Pearson Correlation: Assesses linear relationships between the patterns, highlighting potential correlations.

Historical Outcome Prediction: By analyzing similarity scores, the PTRNBOT predicts potential future movements based on historical outcomes of similar patterns.

Table Display: The indicator optionally displays a table on the chart, summarizing past patterns, similarity scores, and possible next patterns. This feature can be toggled on or off, and it adapts based on Quant Mode activation.

Usage

Pattern Length: Adjust the pattern length to match your trading strategy. Longer patterns capture broader trends, while shorter patterns focus on quick moves.

Lookback Periods: Set the left and right lookback periods to refine the detection of pivots. These parameters control how far the bot looks back to confirm a pivot.

Quant Mode: Enable Quant Mode for a deeper analysis of pattern similarities, providing additional context and confidence in potential price movements.

Benefits

Enhanced Pattern Recognition: The PTRNBOT’s ability to detect and analyze patterns gives traders a significant edge in predicting market moves.

Historical Insights: By comparing current patterns with historical data, traders can make more informed decisions based on past outcomes.

Quantitative Analysis: Quant Mode offers a detailed comparison of patterns, allowing traders to quantify the potential similarity and impact of current patterns on future movements.

User-Friendly Visualization: Clear visual cues and a concise data table make it easy for traders to quickly assess pattern significance and potential next moves.

Conclusion

With the PTRNBOT, traders have a powerful ally in identifying pivotal patterns and predicting potential price action. By leveraging historical data and advanced similarity metrics, this indicator helps traders stay ahead of market trends and seize profitable opportunities with confidence. Activate Quant Mode for an in-depth analysis and elevate your trading strategy with PTRNBOT.