trending -Separate Pane Color BandThe "Donchian trendi multi time frame Color Band" is designed to identify trend directions based on swing highs and lows (similar to Donchian channel concepts, where trends are determined by breakouts from recent highs/lows). The indicator operates in a separate pane (overlay = false) and primarily visualizes:
Trend Direction: Determined by the relative positions of the most recent swing high and swing low. If the last swing high occurred after the last swing low, it's considered an uptrend (bullish); otherwise, a downtrend (bearish).
Adaptive Trend Band: A colored area plot in the indicator pane that represents an adaptive tracking period (influenced by volatility if enabled), filled with a color indicating the current trend (green for up, red for down).
Multi-Timeframe (MTF) Table: An optional table displayed in the top-right corner, showing the trend signal (Bullish or Bearish) for up to 6 user-defined higher timeframes. Each cell is colored based on the trend.
The indicator uses swing detection to gauge trend, incorporates optional volatility-based adaptation for responsiveness, and focuses on multi-timeframe analysis for broader market context. It's not a direct Donchian channel (which typically plots upper/lower bands), but borrows the idea of using highest/lowest prices over a period to detect pivots. It doesn't generate buy/sell signals explicitly but can be used for trend confirmation across timeframes.
Key features include tooltips for inputs, making it user-friendly, and limits on bars/labels for performance.
Key Inputs and Their Roles
The indicator provides customizable inputs grouped into "Swing Points", "Style", and "Multi Timeframe". Here's a breakdown:
Swing Period (prd): Default 50, minimum 2. This sets the lookback period (in bars) for identifying swing highs and lows. Higher values capture major swings (less noise, more lag); lower values detect minor swings (more responsive, but noisier).
Adaptive Price Tracking (baseAPT): Default 20, minimum 1. This base value controls the responsiveness of an adaptive tracking mechanism (similar to a VWAP or moving average length). Lower values make it tighter to price action; higher values smooth it out.
Adapt APT by ATR ratio (useAdapt): Default false. If enabled, the tracking period dynamically adjusts based on market volatility (measured via ATR - Average True Range). High volatility shortens the period for faster reaction; low volatility lengthens it for smoothness.
Volatility Bias (volBias): Default 10.0, minimum 0.1. This amplifies or dampens how much volatility affects the adaptive tracking. Values >1 make it more sensitive to volatility changes; <1 make it less reactive.
Up Color (S): Default lime (green). Color for bullish trends in the band and table.
Down Color (R): Default red. Color for bearish trends in the band and table.
Show MTF Table (show_table): Default true. Toggles the display of the multi-timeframe trend table.
Time frames (tf1 to tf6): Defaults: '1' (1-minute), '3' (3-minute), '15' (15-minute), '60' (1-hour), '240' (4-hour), 'D' (daily). These are the higher timeframes for which trend directions are calculated and shown in the table.
Usage and Interpretation
On the Chart: Add this to a TradingView chart (e.g., for stocks, crypto, forex). The colored area in the indicator pane shows the current timeframe's trend: green band = bullish, red = bearish. The band's height reflects the adaptive period (wider in low volatility if adaptation is on).
MTF Table: Use this for alignment across timeframes. If most/higher timeframes are bullish, it might confirm an uptrend on the current chart. Ideal for trend-following strategies (e.g., trade in the direction of higher TFs).
Customization Tips:
Increase prd for longer-term trends.
Enable useAdapt in choppy markets for better responsiveness.
Adjust timeframes to match your trading style (e.g., scalping: lower TFs; swing: higher).
Limitations:
Relies on historical bars (max_bars_back=5000), so it may not load on very long charts.
No alerts or signals built-in; it's visual-only.
The "Donchian" in the name is loose—it's more pivot-based than full channels.
Adaptation uses ATR, which assumes volatility drives trend responsiveness, but may lag in ranging markets.
Tendance
Mason’s Line IndicatorThe Macon Strategy is an idea conceived by Didier Darcet , co-founder of Gavekal Intelligence Software. Inspired by the Water Level, an instrument used by masons to check the horizontality or verticality of a wall. This method aims to measure the psychology of financial markets and determine if the market is balanced or tilting towards an unfavorable side, focusing on the behavioral risk of markets rather than economic or political factors.
The strategy examines the satisfaction and frustration of investors based on the distance between the low and high points of the market over a period of one year. Investor satisfaction is influenced by the current price of the index and the path taken to reach that price. The distance to the low point provides satisfaction, while the distance to the high point generates frustration. The balance between the two dictates investors’ desire to hold or sell their positions.
To refine the strategy, it is important to consider the opinion of a group of investors rather than just one individual. The members of a hypothetical investor club invest successively throughout the past year. The overall satisfaction of the market on a given day is a democratic expression of all participants.
If the overall satisfaction is below 50%, investors are frustrated and sell their positions. If it is above, they are satisfied and hold their positions. The position of the group of investors relative to the high and low points represents the position of the air bubble in the water level. Market performance is measured day by day based on participant satisfaction or dissatisfaction.
In conclusion, memory, emotions, and decision-making ability are closely linked, and their interaction influences investment decisions. The Macon Strategy highlights the importance of the behavioral dimension in understanding financial market dynamics. By studying investor behavior through this strategy, it is possible to better anticipate market trends and make more informed investment decisions.
Presentation of the Mason’s Line Indicator:
The main strategy of this indicator is to measure the average satisfaction of investors based on the position of an imaginary air bubble in a tube delimited by the market’s highs and lows over a given period. After calculating the satisfaction level, it is then normalized between 0 and 1, and a moving average can be used to visualize trends.
Key features:
Calculation of highs and lows over a user-defined period.
Determination of the position of the air bubble in the tube based on the closing price.
Calculation of the average satisfaction of investors over a selected period.
Normalization of the average satisfaction between 0 and 1.
Visualization of normalized or non-normalized average satisfaction levels, as well as their corresponding moving averages.
User parameters:
Period for min and max (days) : Sets the period over which highs and lows will be calculated (1 to 365 days).
Period for average satisfaction (days) : Determines the period over which the average satisfaction of investors will be calculated (1 to 365 days).
Period for SMA : Sets the period of the simple moving average used to smooth the data (1 to 1000 days).
Bubble_value : Adjustment of the air bubble value, ranging from 0 to 1, in increments of 0.025.
Normalized average satisfaction : Option to choose whether to display the normalized or non-normalized average satisfaction.
Please note that the Mason’s Line Indicator is not a guarantee of future market performance and should be used in conjunction with proper risk management. Always ensure that you have a thorough understanding of the indicator’s methodology and its limitations before making any investment decisions. Additionally, past performance is not indicative of future results.
