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Kalman Filter [DCAUT]

█ Kalman Filter Indicator [DCAUT]
📊 OVERVIEW
The Kalman Filter is an advanced signal processing algorithm developed by Rudolf Kalman in 1960. Originally designed for navigation, robotics, and signal processing applications, this algorithm has recently found its way into financial technical analysis.
In financial markets, the Kalman Filter excels at filtering out noise from price data while delivering smooth yet responsive trend lines. The indicator intelligently balances historical trends with current market data, reducing lag while maintaining smoothness - a significant improvement over traditional moving averages.
🎯 CONCEPTS
How It Works
Key Benefits
📋 PARAMETER SETUP
Data Source
Choose your price input - OHLC4 offers the most balanced results, while Close focuses purely on closing price trends.
Process Noise - Controls Responsiveness
Measurement Noise - Controls Smoothness
📈 READING THE SIGNALS
Visual Cues
Entry/Exit Signals
📄 License: MIT License
👨💻 Developer: DCAUT Team
📊 OVERVIEW
The Kalman Filter is an advanced signal processing algorithm developed by Rudolf Kalman in 1960. Originally designed for navigation, robotics, and signal processing applications, this algorithm has recently found its way into financial technical analysis.
In financial markets, the Kalman Filter excels at filtering out noise from price data while delivering smooth yet responsive trend lines. The indicator intelligently balances historical trends with current market data, reducing lag while maintaining smoothness - a significant improvement over traditional moving averages.
🎯 CONCEPTS
How It Works
- Recursive Estimation: Continuously blends historical trends with current price action for optimal estimates
- Adaptive Weighting: Fine-tune responsiveness to new data through parameter adjustment
- Noise Reduction: Cleanly separates genuine price signals from random market noise
- Balanced Response: Optimizes the trade-off between speed and smoothness
Key Benefits
- Fewer False Signals: Significantly reduces whipsaws and erroneous trade signals
- Reduced Lag: Responds to price changes faster than conventional moving averages
- Market Adaptive: Adjustable sensitivity to match different market conditions
- Proven Technology: Built on decades of signal processing research and development
📋 PARAMETER SETUP
Data Source
Choose your price input - OHLC4 offers the most balanced results, while Close focuses purely on closing price trends.
Process Noise - Controls Responsiveness
- 0.01-0.03: Conservative setting for long-term trends and stable markets
- 0.05: Default setting that works well in most market conditions
- 0.08-0.15: Aggressive setting for short-term and intraday trading
Measurement Noise - Controls Smoothness
- 0.5-1.0: Less smoothing for stable markets requiring higher sensitivity
- 1.0: Default setting providing balanced responsiveness and smoothness
- 1.5-2.5: Extra smoothing for volatile markets like cryptocurrencies
📈 READING THE SIGNALS
Visual Cues
- Green Line: Bullish trend - upward price momentum detected
- Red Line: Bearish trend - downward price momentum detected
Entry/Exit Signals
- Golden Cross: Price breaks above the Kalman Filter line
- Bullish signal suggesting potential upward movement
- Consider long entry opportunities - Death Cross: Price breaks below the Kalman Filter line
- Bearish signal suggesting potential downward movement
- Consider exit strategies or short opportunities
📄 License: MIT License
👨💻 Developer: DCAUT Team
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オープンソーススクリプト
TradingViewの精神に則り、この作者はスクリプトのソースコードを公開しているので、その内容を理解し検証することができます。作者に感謝です!無料でお使いいただけますが、このコードを投稿に再利用する際にはハウスルールに従うものとします。
免責事項
これらの情報および投稿は、TradingViewが提供または保証する金融、投資、取引、またはその他の種類のアドバイスや推奨を意図したものではなく、またそのようなものでもありません。詳しくは利用規約をご覧ください。