ichimoku

The system processes market time-series data using pandas and numpy to calculate the five-line Ichimoku Kinko Hyo components, generating automated trend reversal signals by applying a triple-filter logic for TK crossovers and cloud positions.

The triple-filter logic combines TK crossovers with cloud position and cloud direction filters to systematically generate high-quality, bias-free trend-following entry and exit signals for market analysis.

This Ichimoku signal generator applies quantitative technical analysis to time-series data and supports both crypto and equity assets for market scanning and strategy development.

Yes, pandas and numpy are required dependencies for calculating Tenkan-sen and Kijun-sen indicators, as they handle the time-series calculations and signal filtering required for the Ichimoku five-line system.

The cloud position filter validates TK crossover signals against cloud direction to ensure only high-quality trend continuation and reversal points are identified, reducing false signals in quantitative strategy development.

A limitation of using Ichimoku Kinko Hyo for automated market analysis is its reliance on historical time-series data; while the triple-filter logic reduces false signals, it cannot predict sudden market anomalies outside established trend patterns.