Cross-Timeframe Trend-vs-Noise Index
อินดิเคเตอร์
เวอร์ชัน 1.0, Jul 2026
Windows, Mac
Trading product for Cross-Timeframe Trend-vs-Noise Index อินดิเคเตอร์ Market Structure ATR, image 2
Trading product for Cross-Timeframe Trend-vs-Noise Index อินดิเคเตอร์ Market Structure ATR, image 3
Trading product for Cross-Timeframe Trend-vs-Noise Index อินดิเคเตอร์ Market Structure ATR, image 4
Trading product for Cross-Timeframe Trend-vs-Noise Index อินดิเคเตอร์ Market Structure ATR, image 5
ตั้งแต่ 17/09/2024
1
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คำอธิบาย

Multi Timeframe Tradeability Index

The Multi Timeframe Tradeability Index is an advanced market condition analyzer that identifies when the market is statistically favorable for trading. Instead of generating buy or sell signals, it measures how tradeable current market conditions are across multiple timeframes, allowing you to focus only on periods where price action is clean, directional, and capable of producing meaningful moves.

Unlike traditional indicators that rely on fixed thresholds, this indicator continuously adapts to each timeframe by comparing current market behavior with its own historical baseline. This self calibrating approach allows it to work across Forex, indices, commodities, cryptocurrencies, and other CFD markets without requiring manual optimization.

How It Works

The indicator evaluates six independent characteristics of the market on every timeframe.

Trend versus randomness using the Market Meanness Index.

Smoothness versus choppiness using Fractal Dimension.

Signal to noise ratio to determine whether meaningful swings dominate random fluctuations.

Trend cleanliness by measuring how efficiently price moves instead of constantly reversing.

Trading opportunity frequency by counting significant swing legs.

Net directional progress to determine whether price is making meaningful progress rather than repeatedly retracing.

Each factor is normalized relative to its own historical behavior using statistical z score analysis. This means the indicator evaluates whether current conditions are unusually favorable rather than simply above or below an arbitrary threshold.

The normalized factors are combined into a weighted score ranging from 0 to 100.

The indicator also includes a transaction cost filter that prevents short timeframes from receiving high scores when average price swings are too small to realistically overcome spreads and commissions.

Dashboard

The dashboard analyzes six timeframes simultaneously.

M1

M5

M15

H1

H4

D1

Each timeframe receives one of three ratings.

GOOD indicates highly favorable market conditions.

FAIR indicates acceptable but less ideal conditions.

POOR indicates that market structure is currently unfavorable.

The indicator automatically highlights the highest scoring timeframe together with its current Tradeability Score.

Interpreting the Scores

80 to 100 indicates exceptional trading conditions with strong directional movement and low market noise.

60 to 79 indicates very good conditions where trading strategies are likely to perform well.

40 to 59 indicates average conditions where selectivity is recommended.

Below 40 indicates poor market structure with excessive randomness, choppiness, or insufficient movement.

Higher scores do not predict market direction. They simply indicate that whichever direction develops is statistically more likely to produce cleaner and more tradable price action.

Main Parameters

Analysis Windows control how much market history is used for calculating each factor.

Self Calibration Baseline determines how historical normalization is performed.

Swing Detection adjusts the sensitivity used for identifying significant price swings.

Factor Weights allow advanced users to emphasize or reduce the importance of each market characteristic.

Cost Gate controls how aggressively transaction costs affect the final rating.

Grading settings define the score thresholds for GOOD and FAIR classifications.

Dashboard settings allow complete control over panel size and screen position.

Best Use Cases

Finding the most tradeable timeframe before looking for entries.

Avoiding sideways, noisy, or low quality market conditions.

Filtering signals from existing trading strategies.

Improving discretionary trading by focusing only on statistically favorable environments.

Supporting algorithmic systems with an adaptive market condition filter.

Who Is It For

This indicator is suitable for beginners who want objective guidance on when market conditions are favorable, as well as experienced discretionary and algorithmic traders looking for an adaptive market quality filter that works across multiple instruments and timeframes.

Important Notes

This indicator is not a buy or sell signal generator.

It does not predict future price direction.

It measures only the quality of current market conditions.

For best results, combine it with your existing entry, exit, and risk management strategy. The highest probability trades typically occur when your own trading setup aligns with timeframes that receive a GOOD Tradeability rating.

สรุป

สรุปโดย AI
The Cross-Timeframe Trend-vs-Noise Index is an adaptive market condition indicator designed to identify the most tradeable timeframes across multiple markets including Forex, indices, commodities, cryptocurrencies, and CFDs. It evaluates six independent market characteristics—trend versus randomness, smoothness versus choppiness, signal-to-noise ratio, trend cleanliness, trading opportunity frequency, and net directional progress—using statistical z-score normalization against historical baselines. This self-calibrating approach allows it to adapt continuously without manual optimization.
The indicator provides a weighted Tradeability Score from 0 to 100 for six timeframes (M1, M5, M15, H1, H4, D1), classifying each as GOOD, FAIR, or POOR based on current market quality. It includes a transaction cost filter to account for realistic trading conditions on shorter timeframes. The dashboard highlights the highest scoring timeframe and its score, helping traders focus on periods with clean, directional price action suitable for trading.
This tool does not generate buy or sell signals nor predict price direction; instead, it serves as a market quality filter to improve discretionary or algorithmic trading by signaling when conditions are statistically favorable. Key parameters allow customization of analysis windows, swing detection sensitivity, factor weights, and grading thresholds. It is suitable for traders seeking objective guidance on market structure and tradeability across multiple instruments and timeframes.
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Market Structure
ATR
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ตั้งแต่ 17/09/2024
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