Tradingview 전략 : Ichimoku Theories [LuxAlgo]

Overview

The Ichimoku Theories indicator combines four tools into one comprehensive system based on Goichi Hosoda's work:

1. Ichimoku Kinkō Hyō: Original Ichimoku indicator with its five main lines and Kumo (cloud).
2. Time Theory: Automatic time cycle identification and forecasting.
3. Wave Theory: Automatic wave identification to understand market structure.
4. Price Theory: Automatic identification of developing N waves and potential price targets.

Details

Ichimoku Kinkō Hyō

• Tenkan sen: Midpoint of the last 9 candles.
• Kinjun sen: Midpoint of the last 26 candles.
• Senkou span A: Midpoint between Tenkan Sen and Kijun Sen, plotted 26 candles into the future.
• Senkou span B: Midpoint of the last 52 candles, plotted 26 candles into the future.
• Chikou span: Closing price plotted 26 candles into the past.
• Kumo: Area between Senkou spans A and B.

Time Theory

• Identifies and forecasts market cycles based on Kihon Suchi sequence (9, 17, 26, etc.).
• Time Cycle Modes: SWINGS, HIGHS, KINJUN, WAVES.

Wave Theory

• Basic Waves: I (one leg), V (two legs), N (three legs).
• Complex Waves: P (contracting), Y (expanding), W (double top/bottom).

Price Theory

• Identifies developing N waves and calculates potential price targets (V, E, N, NT).

Python Code Implementation

import pandas as pd

def ichimoku_cloud(df):
    # Tenkan Sen (Conversion Line)
    nine_period_high = df['High'].rolling(window=9).max()
    nine_period_low = df['Low'].rolling(window=9).min()
    df['tenkan_sen'] = (nine_period_high + nine_period_low) / 2

    # Kijun Sen (Base Line)
    twenty_six_period_high = df['High'].rolling(window=26).max()
    twenty_six_period_low = df['Low'].rolling(window=26).min()
    df['kijun_sen'] = (twenty_six_period_high + twenty_six_period_low) / 2

    # Senkou Span A (Leading Span A)
    df['senkou_span_a'] = ((df['tenkan_sen'] + df['kijun_sen']) / 2).shift(26)

    # Senkou Span B (Leading Span B)
    fifty_two_period_high = df['High'].rolling(window=52).max()
    fifty_two_period_low = df['Low'].rolling(window=52).min()
    df['senkou_span_b'] = ((fifty_two_period_high + fifty_two_period_low) / 2).shift(26)

    # Chikou Span (Lagging Span)
    df['chikou_span'] = df['Close'].shift(-26)

    return df

# Example usage with a DataFrame `data` containing stock data
data = pd.read_csv('stock_data.csv')
ichimoku_data = ichimoku_cloud(data)
print(ichimoku_data.tail())

 

개요

Ichimoku Theories 지표는 Goichi Hosoda의 작업을 기반으로 한 네 가지 도구를 하나로 결합한 종합 시스템입니다:

1. Ichimoku Kinkō Hyō: 오리지널 Ichimoku 지표와 주요 5개 라인 및 Kumo(구름).
2. Time Theory: 자동 시간 주기 식별 및 예측.
3. Wave Theory: 시장 구조 이해를 위한 자동 파동 식별.
4. Price Theory: 진행 중인 N 파동 및 잠재적 가격 목표의 자동 식별.

세부사항

Ichimoku Kinkō Hyō

• Tenkan sen: 최근 9 캔들의 중간점.
• Kinjun sen: 최근 26 캔들의 중간점.
• Senkou span A: Tenkan Sen과 Kijun Sen의 중간점을 26 캔들 앞에 그림.
• Senkou span B: 최근 52 캔들의 중간점을 26 캔들 앞에 그림.
• Chikou span: 종가를 26 캔들 뒤로 그림.
• Kumo: Senkou spans A와 B 사이의 영역.

Time Theory

• Kihon Suchi 순서(9, 17, 26 등)를 기반으로 시장 주기를 식별 및 예측.
• Time Cycle Modes: SWINGS, HIGHS, KINJUN, WAVES.

Wave Theory

• Basic Waves: I (단일 다리), V (두 다리), N (세 다리).
• Complex Waves: P (수축), Y (확장), W (이중 천정/저점).

Price Theory

• 진행 중인 N 파동을 식별하고 잠재적 가격 목표(V, E, N, NT)를 계산.