頻帶和通道
AKG2001_23 bollinger bands with customisable moving average type,1 dema, 8emas and a ichimoku cloud all in this indicator
Tractor-Trend V5Description of the indicator and the principle of its operation
This indicator is a multifunctional tool for analyzing trends and determining entry and exit points in the market. It uses a combination of moving averages, linear regression, volatility levels, and Fibonacci levels to build channels, identify trends, and generate signals. The indicator also includes visualization of overbought and oversold zones, as well as target levels for long and short positions.
The main components of the indicator
The Base Line:
The baseline is calculated based on a moving average (SMA or EMA) or linear regression.
The user can select the data source (for example, hl2 is the average value between high and low), the length of the moving average, and the length of the linear regression.
The baseline is used as a reference level to determine the trend.
Trend Channel:
The channel is built around a baseline using volatility (the difference between high and low).
The user can set the distance between the channel boundaries and the baseline.
The channel includes upper and lower bounds, as well as extended levels (extreme levels).
Golden Pocket:
This is the zone between the baseline and the 0.618 Fibonacci level.
The zone is used to identify potential reversal points or trend continuation.
Input signals (Long/Short):
Entry signals are generated when the price closes above or below the baseline and channel boundaries.
The indicator tracks the beginning and end of trends to avoid false signals.
Target Levels:
For long and short positions, target levels are calculated based on Fibonacci extensions.
The user can set up a multiplier for the target levels.
Overbought and Oversold zones (Overbought/Oversold):
The indicator determines the overbought and oversold zones based on the price crossing the channel boundaries.
There are also extreme zones that show stronger overbought/oversold levels.
Alerts:
The indicator generates alerts when the price breaks through the upper or lower boundary of the channel.
Advantages of the indicator
Flexibility of settings: the user can adapt the indicator to his preferences.
Multifunctional: the indicator combines elements of trend analysis, Fibonacci levels and volatility.
Visualization: clear representation of key levels and zones.
Recommendations
Use the indicator in combination with other technical analysis tools to confirm the signals.
Test the settings on historical data before using them in real trading.
Take into account market conditions (volatility, trend, sideways movement) when interpreting signals.
This indicator is suitable for traders who prefer to work with trend strategies and use Fibonacci levels to identify targets and pivot points.
// Base Line Inputs
Base_Show = input(defval = true, title = "Show Base line?", group = "Base line Settings")
Base_src = input(hl2, title = "Source", group = "Base line Settings")
Base_length = input.int(title = 'Length', minval = 1, maxval = 1000, defval = 50, group = "Base line Settings")
Base_linreg_length = input.int(title = 'Linear Regression Length', minval = 1, maxval = 1000, defval = 50, group = "Base line Settings")
Base_sma_or_ema = input(title = 'Use Simple MA?', defval = false, group = "Base line Settings")
Base_lin_reg = input(title = 'Use Linear Regression?', defval = false, group = "Base line Settings")
// Calculation Base Line
Base_bclose = Base_lin_reg ? ta.linreg(Base_src, Base_linreg_length, 0) : Base_src
Base_signal = Base_sma_or_ema ? ta.sma(Base_bclose, Base_length) : ta.ema(Base_bclose, Base_length)
//Trend Channel
float distance = input.float (2, "Bands Distance", step = 0.1, minval = 0.3, group = "Trend Channel Settings") // Distance for channel bands
Ex_Show = input(defval = false, title = "Show Extension?", group = "Trend Channel Settings")
series float volatility = ta.sma(high - low, Base_length) // Calculate volatility using the average true range
var bool is_long_trend_started = false
var bool is_short_trend_started = false
var bool is_trend_change = false
var bool is_long_trend = false
var bool is_short_trend = false
var bool can_long = false
var bool can_short = false
// Trend Channel Inputs
up_can = Base_signal + volatility * distance
up_can_Tar = up_can + volatility * distance * 2.5
up_can_Ex = up_can_Tar + volatility * distance
lo_can = Base_signal - volatility * distance
lo_can_Tar = lo_can - volatility * distance * 1.5
lo_can_Ex = lo_can_Tar - volatility * distance
// Golden Pocket Inputs
channel_range = up_can - lo_can
fib_618 = up_can - channel_range * 0.618
// CAN LONG/SHORT
//if time >= start_date_input
can_long := close >= Base_signal and close >= up_can and not is_long_trend
can_short := close <= Base_signal and close <= lo_can and not is_short_trend
if can_long
is_long_trend := true
is_short_trend := false
is_long_trend_started := is_long_trend_started ? false : true
else if can_short
is_short_trend := true
is_long_trend := false
is_short_trend_started := is_short_trend_started ? false : true
else
is_trend_change := false
can_long := false
can_short := false
is_short_trend_started := false
is_long_trend_started := false
is_trend_change := is_short_trend_started or is_long_trend_started
// Plot Base Line
GP_05 = plot(Base_Show ? Base_signal : na, color = is_long_trend ? color.rgb(6, 247, 14) : color.rgb(225, 190, 231), linewidth = 1, title = "Base line")
GP_0_618 = plot(fib_618, title = "Lower Border Golden Pocket (Fib 0.618)", color = is_long_trend ? color.rgb(6, 247, 14) : color.rgb(247, 9, 9), display = display.none)
fill(GP_05, GP_0_618, title = "Golden Pocket Background", color = is_long_trend ? color.rgb(245, 123, 0, 60) : color.rgb(255, 167, 38, 60))
// Plot Trend Channel
plotshape(is_long_trend and is_long_trend_started ? Base_signal : na, title="Long Label", style=shape.triangleup, location=location.belowbar, color=color.rgb(8, 153, 129), size=size.small)
plotshape(is_short_trend and is_short_trend_started ? Base_signal : na, title="Short Label", style=shape.triangledown, location=location.abovebar, color=color.rgb(233, 30, 99), size=size.small)
// Plot Channel Boundary
Range_Zone1 = plot(up_can, color = is_long_trend ? color.rgb(38, 198, 218) : color.rgb(156, 39, 176), title = "Channel Upper Boundary")
Range_Zone2 = plot(lo_can, color = is_long_trend ? color.rgb(38, 198, 218) : color.rgb(156, 39, 176), title = "Channel Lower Boundary")
fill(Range_Zone1, Range_Zone2, color = is_long_trend ? color.rgb(38, 197, 218, 80) : color.rgb(155, 39, 176, 80), title = "Channel Background")
// Plot Extension
plot(Ex_Show ? up_can_Ex : na, title = "Extreme Level Extension Upper Boundary Channel", color = color.rgb(95, 250, 224, 30))
plot(Ex_Show ? up_can_Tar : na, title = "First Level Extension Upper Boundary Channel", color = color.rgb(95, 250, 224, 50))
plot(Ex_Show ? lo_can_Tar : na, title = "First Level Extension Lower Boundary Channel", color = color.rgb(247, 116, 120, 50))
plot(Ex_Show ? lo_can_Ex : na, title = "Extreme Level Extension Lower Boundary Channel", color = color.rgb(247, 116, 120, 0))
// Overbought and Oversold Zones
show_OBOS_zones = input.bool(defval = true, title = "Show Overbought and Oversold Zones?", group = "Trend Channel Settings")
show_Ex_zones = input.bool(defval = true, title = "Show Extreme Overbought and Oversold Zones?", group = "Trend Channel Settings")
is_overbought = ta.crossunder(close, up_can_Tar)
is_oversold = ta.crossover(close, lo_can_Tar)
is_overboughtEx = ta.crossunder(close, up_can_Ex)
is_oversoldEx = ta.crossover(close, lo_can_Ex)
// Plot Overbought and Oversold
plotshape(is_overbought and show_OBOS_zones ? high : na, title = "Overbought", color = color.rgb(255, 245, 157), style = shape.circle, size = size.tiny, location = location.abovebar)
plotshape(is_oversold and show_OBOS_zones ? low : na, title = "Oversold", color = color.rgb(3, 249, 208), style = shape.circle, size = size.tiny, location = location.belowbar)
// Plot Extreme Overbought and Oversold
plotshape(is_overboughtEx and show_Ex_zones ? high : na, title = "Extreme Overbought", color = color.rgb(255, 152, 0), style = shape.diamond, size = size.tiny, location = location.abovebar)
plotshape(is_oversoldEx and show_Ex_zones ? low : na, title = "Extreme Oversold", color = color.rgb(3, 249, 3), style = shape.diamond, size = size.tiny, location = location.belowbar)
// Target Levels
mult_tar_input = input.float(title = "Multiplier for Target Levels", step = 0.1, defval = 1.5, minval = 0.1, group = "Target Levels Settings")
// Цвета для целевых уровней
color_long = input.color(color.rgb(8, 153, 129), title = "Color Targets for Long Positions", group = "Colors for Target Levels Setting")
color_short = input.color(color.rgb(233, 30, 99), title = "Color Targets for Short Positions", group = "Colors for Target Levels Setting")
// DC Calculation Extension (Targets Lines for Long)
long_1 = up_can - channel_range * -0.382 * mult_tar_input
long_2 = up_can - channel_range * -1 * mult_tar_input
long_3 = up_can - channel_range * -1.618 * mult_tar_input
long_4 = up_can - channel_range * -2.236 * mult_tar_input
long_5 = up_can - channel_range * -3 * mult_tar_input
// DC Calculation Extension (Targets Lines for Short)
short_1 = lo_can - channel_range * 0.382 * mult_tar_input
short_2 = lo_can - channel_range * 1 * mult_tar_input
short_3 = lo_can - channel_range * 1.618 * mult_tar_input
short_4 = lo_can - channel_range * 2.236 * mult_tar_input
short_5 = lo_can - channel_range * 3 * mult_tar_input
// Draw lines from triangles
var line long_line = na
var line short_line = na
var line long_line_reverse = na
var line short_line_reverse = na
if is_long_trend and is_long_trend_started
long_line := line.new(bar_index, Base_signal, bar_index, long_5, color = color_long, style = line.style_dotted, width = 2)
long_line_reverse := line.new(bar_index, Base_signal, bar_index, short_5, color = color.rgb(8, 153, 129, 100), style = line.style_dotted, width = 2)
if is_short_trend and is_short_trend_started
short_line := line.new(bar_index, Base_signal, bar_index, short_5, color = color_short, style = line.style_dotted, width = 2)
short_line_reverse := line.new(bar_index, Base_signal, bar_index, long_5, color = color.rgb(233, 30, 99, 100), style = line.style_dotted, width = 2)
//
// Функция для поиска точки пересечения линии тренда и горизонтального уровня
f_find_intersection(line_start, line_end, level) =>
if (line_start <= level and line_end >= level) or (line_start >= level and line_end <= level)
true
else
false
// Объявление массивов для хранения лучей-целей для длинных позиций
var line target_rays_long_1 = array.new_line(0)
var line target_rays_long_2 = array.new_line(0)
var line target_rays_long_3 = array.new_line(0)
var line target_rays_long_4 = array.new_line(0)
var line target_rays_long_5 = array.new_line(0)
// Отрисовка лучей-целей для long_1
if is_long_trend and is_long_trend_started
if f_find_intersection(Base_signal, long_5, long_1)
var line target_ray = na
target_ray := line.new(bar_index, long_1, bar_index + 1, long_1, color = color_long, style = line.style_dotted, width = 2, extend = extend.right)
array.push(target_rays_long_1, target_ray)
// Отрисовка лучей-целей для long_2
if is_long_trend and is_long_trend_started
if f_find_intersection(Base_signal, long_5, long_2)
var line target_ray = na
target_ray := line.new(bar_index, long_2, bar_index + 1, long_2, color = color_long, style = line.style_dotted, width = 2, extend = extend.right)
array.push(target_rays_long_2, target_ray)
// Отрисовка лучей-целей для long_3
if is_long_trend and is_long_trend_started
if f_find_intersection(Base_signal, long_5, long_3)
var line target_ray = na
target_ray := line.new(bar_index, long_3, bar_index + 1, long_3, color = color_long, style = line.style_dotted, width = 2, extend = extend.right)
array.push(target_rays_long_3, target_ray)
// Отрисовка лучей-целей для long_4
if is_long_trend and is_long_trend_started
if f_find_intersection(Base_signal, long_5, long_4)
var line target_ray = na
target_ray := line.new(bar_index, long_4, bar_index + 1, long_4, color = color_long, style = line.style_dotted, width = 2, extend = extend.right)
array.push(target_rays_long_4, target_ray)
// Отрисовка лучей-целей для long_5
if is_long_trend and is_long_trend_started
if f_find_intersection(Base_signal, long_5, long_5)
var line target_ray = na
target_ray := line.new(bar_index, long_5, bar_index + 1, long_5, color = color_long, style = line.style_dotted, width = 2, extend = extend.right)
array.push(target_rays_long_5, target_ray)
// Удаление лучей при изменении тренда
if is_short_trend and is_short_trend_started
if array.size(target_rays_long_1) > 0
for i = 0 to array.size(target_rays_long_1) - 1
line.delete(array.get(target_rays_long_1, i))
array.clear(target_rays_long_1)
if array.size(target_rays_long_2) > 0
for i = 0 to array.size(target_rays_long_2) - 1
line.delete(array.get(target_rays_long_2, i))
array.clear(target_rays_long_2)
if array.size(target_rays_long_3) > 0
for i = 0 to array.size(target_rays_long_3) - 1
line.delete(array.get(target_rays_long_3, i))
array.clear(target_rays_long_3)
if array.size(target_rays_long_4) > 0
for i = 0 to array.size(target_rays_long_4) - 1
line.delete(array.get(target_rays_long_4, i))
array.clear(target_rays_long_4)
if array.size(target_rays_long_5) > 0
for i = 0 to array.size(target_rays_long_5) - 1
line.delete(array.get(target_rays_long_5, i))
array.clear(target_rays_long_5)
// Объявление массивов для хранения лучей-целей для коротких позиций
var line target_rays_short_1 = array.new_line(0)
var line target_rays_short_2 = array.new_line(0)
var line target_rays_short_3 = array.new_line(0)
var line target_rays_short_4 = array.new_line(0)
var line target_rays_short_5 = array.new_line(0)
// Отрисовка лучей-целей для short_1
if is_short_trend and is_short_trend_started
if f_find_intersection(Base_signal, short_5, short_1)
var line target_ray = na
target_ray := line.new(bar_index, short_1, bar_index + 1, short_1, color = color_short, style = line.style_dotted, width = 2, extend = extend.right)
array.push(target_rays_short_1, target_ray)
// Отрисовка лучей-целей для short_2
if is_short_trend and is_short_trend_started
if f_find_intersection(Base_signal, short_5, short_2)
var line target_ray = na
target_ray := line.new(bar_index, short_2, bar_index + 1, short_2, color = color_short, style = line.style_dotted, width = 2, extend = extend.right)
array.push(target_rays_short_2, target_ray)
// Отрисовка лучей-целей для short_3
if is_short_trend and is_short_trend_started
if f_find_intersection(Base_signal, short_5, short_3)
var line target_ray = na
target_ray := line.new(bar_index, short_3, bar_index + 1, short_3, color = color_short, style = line.style_dotted, width = 2, extend = extend.right)
array.push(target_rays_short_3, target_ray)
// Отрисовка лучей-целей для short_4
if is_short_trend and is_short_trend_started
if f_find_intersection(Base_signal, short_5, short_4)
var line target_ray = na
target_ray := line.new(bar_index, short_4, bar_index + 1, short_4, color = color_short, style = line.style_dotted, width = 2, extend = extend.right)
array.push(target_rays_short_4, target_ray)
// Отрисовка лучей-целей для short_5
if is_short_trend and is_short_trend_started
if f_find_intersection(Base_signal, short_5, short_5)
var line target_ray = na
target_ray := line.new(bar_index, short_5, bar_index + 1, short_5, color = color_short, style = line.style_dotted, width = 2, extend = extend.right)
array.push(target_rays_short_5, target_ray)
// Удаление лучей при изменении тренда
if is_long_trend and is_long_trend_started
if array.size(target_rays_short_1) > 0
for i = 0 to array.size(target_rays_short_1) - 1
line.delete(array.get(target_rays_short_1, i))
array.clear(target_rays_short_1)
if array.size(target_rays_short_2) > 0
for i = 0 to array.size(target_rays_short_2) - 1
line.delete(array.get(target_rays_short_2, i))
array.clear(target_rays_short_2)
if array.size(target_rays_short_3) > 0
for i = 0 to array.size(target_rays_short_3) - 1
line.delete(array.get(target_rays_short_3, i))
array.clear(target_rays_short_3)
if array.size(target_rays_short_4) > 0
for i = 0 to array.size(target_rays_short_4) - 1
line.delete(array.get(target_rays_short_4, i))
array.clear(target_rays_short_4)
if array.size(target_rays_short_5) > 0
for i = 0 to array.size(target_rays_short_5) - 1
line.delete(array.get(target_rays_short_5, i))
array.clear(target_rays_short_5)
//
// Alerts
buy_alert_disp = input.bool(title = "TT Show Long", defval = true, tooltip = "Appears, if the price breaks through the upper limit channel", group = "Alerts")
sell_alert_disp = input.bool(title = "TT Show Short", defval = true, tooltip = "Appears, if the price breaks through the lower limit channel", group = "Alerts")
buy_alert = is_long_trend and is_long_trend_started
sell_alert = is_short_trend and is_short_trend_started
if buy_alert_disp and buy_alert
alert("TT Show Long", alert.freq_once_per_bar_close)
if sell_alert_disp and sell_alert
alert("TT Show Short", alert.freq_once_per_bar_close)
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专业级交易系统Belonging to the oscillation trading strategy.abcdefg,aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
"Multi-MA Trend Ribbon" 20,21+36,50,100,200,300 EMA
Name: Multi-MA Trend Ribbon
Description:
The "Multi-MA Trend Ribbon" is a versatile technical analysis indicator designed for use on trading platforms like TradingView. It primarily serves to visualize market trends through multiple moving averages (MAs), offering traders a comprehensive view of price movement over various time frames. Here's a detailed breakdown of its features and functionality:
Key Features:
Multiple Moving Averages:
Supports up to 7 different MAs, with default lengths at 20, 50, 100, 200, 300, 21, and 36 periods.
Each MA can be individually turned on or off, providing flexibility in analysis.
Types of MAs include EMA (Exponential Moving Average), SMA (Simple Moving Average), HMA (Hull Moving Average), WMA (Weighted Moving Average), DEMA (Double Exponential Moving Average), VWMA (Volume Weighted Moving Average), and VWAP (Volume Weighted Average Price).
Ribbon Display:
Offers an option to transform the display into a "Ribbon" where all MAs are colored uniformly based on the trend direction.
The color changes based on whether the shortest MA (typically MA1) is above or below the longest MA (typically MA5), indicating bullish or bearish trends respectively.
Customization:
Users can customize colors for bullish and bearish trends.
The indicator allows setting all MAs to a uniform type or mixing different types.
Adjustable length for each MA.
Trend Identification:
Identifies trends based on the crossover between the first and fifth MA:
Bullish Trend: When the shortest MA crosses above the longest MA.
Bearish Trend: When the longest MA crosses above the shortest MA.
Visualization Enhancements:
MAs can be plotted with different colors when not in ribbon mode for easy distinction.
The space between MAs can be filled with color when in ribbon mode, enhancing the visual trend signal.
Alerts:
Generates alerts when a bullish or bearish trend change is detected based on MA crossovers.
Data Table:
Optionally displays a table on the chart showing:
Current trend (Bullish or Bearish)
Values of all enabled MAs at the current price bar
Average True Range (ATR) for volatility context
The table's location is user-selectable (top-right, top-left, bottom-left, bottom-right).
Cross Plotting:
Option to plot crosses on the chart where trend changes occur, serving as visual markers for entry or exit signals.
Use Cases:
Trend Confirmation: Traders can use the ribbon to confirm trend directions over multiple time frames.
Trading Signals: Crossovers between MAs can be used to generate buy or sell signals.
Support/Resistance: The MAs can act as dynamic support or resistance levels.
Advantages:
Highly customizable to fit various trading strategies.
Provides both a clear visual trend indication and detailed numerical data.
Considerations:
In volatile markets, frequent crossovers might lead to false signals, so it's beneficial to combine with other indicators or analysis methods for confirmation.
MA 10/20 Ribbon ĐH3. Ứng dụng trong giao dịch
Xác định xu hướng:
Khi MA 10 nằm trên MA 20 → thị trường có xu hướng tăng.
Khi MA 10 nằm dưới MA 20 → thị trường có xu hướng giảm.
Inside BarsInside Bars Indicator
Description:
This indicator identifies and highlights price action patterns where a bar's high and low
are completely contained within the previous bar's range. Inside bars are significant
technical patterns that often signal a period of price consolidation or uncertainty,
potentially leading to a breakout in either direction.
Trading Literature & Theory:
Inside bars are well-documented in technical analysis literature:
- Steve Nison discusses them in "Japanese Candlestick Charting Techniques" as a form
of harami pattern, indicating potential trend reversals
- Thomas Bulkowski's "Encyclopedia of Chart Patterns" categorizes inside bars as
a consolidation pattern with statistical significance for breakout trading
- Alexander Elder references them in "Trading for a Living" as indicators of
decreasing volatility and potential energy build-up
- John Murphy's "Technical Analysis of the Financial Markets" includes inside bars
as part of price action analysis for market psychology understanding
The pattern is particularly significant because it represents:
1. Volatility Contraction: A narrowing of price range indicating potential energy build-up
2. Institutional Activity: Often shows large players absorbing or distributing positions
3. Decision Point: Market participants evaluating the previous bar's significance
Trading Applications:
1. Breakout Trading
- Watch for breaks above the parent bar's high (bullish signal)
- Monitor breaks below the parent bar's low (bearish signal)
- Multiple consecutive inside bars can indicate stronger breakout potential
2. Market Psychology
- Inside bars represent a period of equilibrium between buyers and sellers
- Shows market uncertainty and potential energy building up
- Often precedes significant price movements
Best Market Conditions:
- Trending markets approaching potential reversal points
- After strong momentum moves where the market needs to digest gains
- Near key support/resistance levels
- During pre-breakout consolidation phases
Complementary Indicators:
- Volume indicators to confirm breakout strength
- Trend indicators (Moving Averages, ADX) for context
- Momentum indicators (RSI, MACD) for additional confirmation
Risk Management:
- Use parent bar's range for stop loss placement
- Wait for breakout confirmation before entry
- Consider time-based exits if breakout doesn't occur
- More reliable on higher timeframes
Note: The indicator works best when combined with proper risk management
and overall market context analysis. Avoid trading every inside bar pattern
and always confirm with volume and other technical indicators.
EDGE Market Maker StrategyDCAA HedgeFlow System
Objective: Provide real-time, structured analysis for ENS/USDT trades by focusing on market maker liquidity flows and footprints, rather than traditional retail indicators. This approach is designed to grant an institutional-level execution edge.
1. Liquidity-Based Market Assessment
• Liquidity Zones: Locate areas where market makers trap retail (bull/bear traps).
• Order Book Imbalances: Highlight significant buy/sell pressure absorption.
• Volume Clusters & Absorption: Detect liquidity exhaustion points.
• Market Maker Footprints: Pinpoint institutional positioning.
Restriction: Do not use static support/resistance. All levels must derive from liquidity traps, absorption points, and institutional footprints.
2. DCAA & Trade Optimization
Analyze and recommend optimal DCAA levels by examining market maker absorption and real-time positioning, instead of offering fixed levels.
• Short DCAA: Identify zones where short sellers are trapped before a reversal; confirm entries via VWAP, CVD, and Open Interest.
• Long DCAA: Identify accumulation zones where market makers absorb liquidations; confirm entries using order book absorption and volume imbalances.
3. Take-Profit Analysis: Liquidity Exit Points
Provide dynamic TP zones that update in real time based on liquidity exhaustion—never static.
• Short TP: Reveal zones where sellers are absorbed and liquidity fades; confirm via volume divergence, order book imbalances, and market maker exits.
• Long TP: Identify zones where buyers are absorbed before market makers exit; confirm via VWAP alignment and liquidity exhaustion.
4. Market Maker Trap Detection
Analyze bull/bear traps with liquidity data:
• Bull Trap: Detect resistance absorption that traps late buyers; confirm with CVD divergence and order book shifts.
• Bear Trap: Identify stop-hunt areas where market makers absorb forced liquidations; confirm with VWAP and Open Interest spikes.
Provide a probability (%) for each trap scenario to guide risk assessment.
5. Hedge Strategy Analysis
Recommend hedging only if order flow confirms institutional absorption:
• Short Hedge: Identify zones for short hedging to counter bullish market maker shifts.
• Long Hedge: Identify zones for long hedging against stop hunts and forced liquidations.
Hedge recommendations must adapt to VWAP shifts, liquidity depth, and institutional moves.
6. Order Flow Tracking: Institutional Footprint Analysis
Track and validate:
• VWAP: Confirm institutional absorption or positioning.
• CVD (Cumulative Volume Delta): Detect trapped buyers/sellers.
• Open Interest: Confirm accumulation or liquidation trends.
All conditions must be met before finalizing DCAA or TP levels.
7. Structured Execution
For every ENS/USDT analysis:
1. Identify liquidity traps, absorption zones, and market maker footprints.
2. Confirm stop hunts or liquidation events before finalizing DCAA zones.
3. Integrate VWAP, CVD, and Open Interest data to validate trades.
4. Provide dynamic TP zones (not static) based on real-time liquidity.
5. Evaluate hedges according to shifts in market maker positioning.
8. Analysis Restrictions & Optimization
• No static S/R or retail indicators (e.g., moving averages, RSI, MACD).
• No predefined TP levels—always dynamic and liquidity-based.
• Prioritize liquidity tracking, volume imbalances, institutional footprints.
• Offer probability-based breakout, breakdown, and ranging assessments using real-time data.
9. Market Maker Validation
Before finalizing a trade:
1. VWAP: Must confirm institutional absorption (yes → proceed; no → reassess).
2. CVD: Must show divergence with trapped traders (yes → proceed; no → delay).
3. Open Interest: Must confirm accumulation/liquidation (yes → proceed; no → wait).
4. Stop Hunt: Must have confirmation of a completed stop hunt or liquidation (yes → proceed; no → hold off).
Any conclusion not supported by liquidity data should be rejected.
10. Continuous Refinement
This strategy refines analysis accuracy by:
• Tracking historical forecasts and adjusting probability models.
• Adapting liquidity zone detection with real-time data updates.
• Speeding up detection of stop hunts and hedge signals.
Final Confirmation: Institutional-Grade Analysis Tool
All analysis must be rooted in liquidity flow and smart money positioning. The goal is to optimize trade execution with risk-adjusted insights, eliminate retail inefficiencies, and adapt dynamically to market conditions—functioning as a truly institutional-level analysis engine for ENS/USDT.
Use or adapt these instructions to maintain an institutional-grade focus on liquidity-driven market dynamics.
Range Filtered Trend Signals [AlgoAlpha]Introducing the Range Filtered Trend Signals , a cutting-edge trading indicator designed to detect market trends and ranging conditions with high accuracy. This indicator leverages a combination of Kalman filtering and Supertrend analysis to smooth out price fluctuations while maintaining responsiveness to trend shifts. By incorporating volatility-based range filtering, it ensures traders can differentiate between trending and ranging conditions effectively, reducing false signals and enhancing trade decision-making.
:key: Key Features
:white_check_mark: Kalman Filter Smoothing – Minimizes market noise while preserving trend clarity.
:bar_chart: Supertrend Integration – A dynamic trend-following mechanism for spotting reversals.
:fire: Volatility-Based Range Detection – Detects trending vs. ranging conditions with precision.
:art: Color-Coded Trend Signals – Instantly recognize bullish, bearish, and ranging market states.
:gear: Customizable Inputs – Fine-tune Kalman parameters, Supertrend settings, and color themes to match your strategy.
:bell: Alerts for Trend Shifts – Get real-time notifications when market conditions change!
:tools: How to Use
Add the Indicator – Click the star icon to add it to your TradingView favorites.
Analyze Market Conditions – Observe the color-coded signals and range boundaries to identify trend strength and direction.
Use Alerts for Trade Execution – Set alerts for trend shifts and market conditions to stay ahead without constantly monitoring charts.
:mag: How It Works
The Kalman filter smooths price fluctuations by dynamically adjusting its weighting based on market volatility. It helps remove noise while keeping the signal reactive to trend changes. The Supertrend calculation is then applied to the filtered price data, providing a robust trend-following mechanism. To enhance signal accuracy, a volatility-weighted range filter is incorporated, creating upper and lower boundaries that define trend conditions. When price breaks out of these boundaries, the indicator confirms trend continuation, while signals within the range indicate market consolidation. Traders can leverage this tool to enhance trade timing, filter false breakouts, and identify optimal entry/exit zones.
MACD & Bollinger Bands Overbought OversoldMACD & Bollinger Bands Reversal Detector
This indicator combines the power of MACD divergence analysis with Bollinger Bands to help traders identify potential reversal points in the market.
Key Features:
MACD Calculation & Divergence:
The script calculates the standard MACD components (MACD line, Signal line, and Histogram) using configurable fast, slow, and signal lengths. It includes a simplified divergence detection mechanism that flags potential bearish divergence—when the price makes a new swing high but the MACD fails to confirm the move. This divergence can serve as an early warning that the bullish momentum is waning.
Bollinger Bands:
A 20-period simple moving average (SMA) is used as the basis, with upper and lower bands drawn at 2 standard deviations. These bands help visualize overbought and oversold conditions. For example, a close at or above the upper band suggests the market may be overextended (overbought), while a close at or below the lower band may indicate oversold conditions.
Visual Alerts:
The indicator plots the Bollinger Bands on the chart along with labels marking overbought and oversold conditions. Additionally, it marks potential bearish divergence with a downward triangle, providing a quick visual cue to traders.
Usage Suggestions:
Confluence with Other Signals:
Use the divergence signals and Bollinger Band conditions as filters. For example, even if another indicator suggests a long entry, you might avoid it if the price is overbought or if MACD divergence warns of weakening momentum.
Customization:
All key parameters, such as the MACD lengths, Bollinger Band period, and multiplier, are fully configurable. This flexibility allows you to adjust the indicator to suit different markets or trading styles.
Disclaimer:
This script is provided for educational purposes only. Always perform your own analysis and backtesting before trading with live capital.
Grouped EMAsThis indicator displays grouped EMAs across multiple timeframes (5m, 15m, 30m, and 60m) on a single chart. It allows traders to easily track key EMA levels across different timeframes for better trend analysis and decision-making.
Key Features:
Adjustable EMA Length: Change the EMA period once, and it updates across all timeframes simultaneously.
Multi-Timeframe Support: Displays 365 EMA High and Low for 5-minute, 15-minute, 30-minute, and 60-minute intervals.
Clear Color Coding: Each timeframe is color-coded for quick visual recognition.
How to Use:
Adjust the EMA length using the input option to set your preferred period.
Observe the EMAs across different timeframes to identify support, resistance, and trend directions.
Combine with other indicators or price action strategies for enhanced trading insights.
This tool is ideal for traders looking to simplify multi-timeframe analysis while maintaining flexibility with the EMA period.
Enjoy more informed trading and enhanced trend analysis with Grouped EMAs!
MTF Signal XpertMTF Signal Xpert – Detailed Description
Overview:
MTF Signal Xpert is a proprietary, open‑source trading signal indicator that fuses multiple technical analysis methods into one cohesive strategy. Developed after rigorous backtesting and extensive research, this advanced tool is designed to deliver clear BUY and SELL signals by analyzing trend, momentum, and volatility across various timeframes. Its integrated approach not only enhances signal reliability but also incorporates dynamic risk management, helping traders protect their capital while navigating complex market conditions.
Detailed Explanation of How It Works:
Trend Detection via Moving Averages
Dual Moving Averages:
MTF Signal Xpert computes two moving averages—a fast MA and a slow MA—with the flexibility to choose from Simple (SMA), Exponential (EMA), or Hull (HMA) methods. This dual-MA system helps identify the prevailing market trend by contrasting short-term momentum with longer-term trends.
Crossover Logic:
A BUY signal is initiated when the fast MA crosses above the slow MA, coupled with the condition that the current price is above the lower Bollinger Band. This suggests that the market may be emerging from a lower price region. Conversely, a SELL signal is generated when the fast MA crosses below the slow MA and the price is below the upper Bollinger Band, indicating potential bearish pressure.
Recent Crossover Confirmation:
To ensure that signals reflect current market dynamics, the script tracks the number of bars since the moving average crossover event. Only crossovers that occur within a user-defined “candle confirmation” period are considered, which helps filter out outdated signals and improves overall signal accuracy.
Volatility and Price Extremes with Bollinger Bands
Calculation of Bands:
Bollinger Bands are calculated using a 20‑period simple moving average as the central basis, with the upper and lower bands derived from a standard deviation multiplier. This creates dynamic boundaries that adjust according to recent market volatility.
Signal Reinforcement:
For BUY signals, the condition that the price is above the lower Bollinger Band suggests an undervalued market condition, while for SELL signals, the price falling below the upper Bollinger Band reinforces the bearish bias. This volatility context adds depth to the moving average crossover signals.
Momentum Confirmation Using Multiple Oscillators
RSI (Relative Strength Index):
The RSI is computed over 14 periods to determine if the market is in an overbought or oversold state. Only readings within an optimal range (defined by user inputs) validate the signal, ensuring that entries are made during balanced conditions.
MACD (Moving Average Convergence Divergence):
The MACD line is compared with its signal line to assess momentum. A bullish scenario is confirmed when the MACD line is above the signal line, while a bearish scenario is indicated when it is below, thus adding another layer of confirmation.
Awesome Oscillator (AO):
The AO measures the difference between short-term and long-term simple moving averages of the median price. Positive AO values support BUY signals, while negative values back SELL signals, offering additional momentum insight.
ADX (Average Directional Index):
The ADX quantifies trend strength. MTF Signal Xpert only considers signals when the ADX value exceeds a specified threshold, ensuring that trades are taken in strongly trending markets.
Optional Stochastic Oscillator:
An optional stochastic oscillator filter can be enabled to further refine signals. It checks for overbought conditions (supporting SELL signals) or oversold conditions (supporting BUY signals), thus reducing ambiguity.
Multi-Timeframe Verification
Higher Timeframe Filter:
To align short-term signals with broader market trends, the script calculates an EMA on a higher timeframe as specified by the user. This multi-timeframe approach helps ensure that signals on the primary chart are consistent with the overall trend, thereby reducing false signals.
Dynamic Risk Management with ATR
ATR-Based Calculations:
The Average True Range (ATR) is used to measure current market volatility. This value is multiplied by a user-defined factor to dynamically determine stop loss (SL) and take profit (TP) levels, adapting to changing market conditions.
Visual SL/TP Markers:
The calculated SL and TP levels are plotted on the chart as distinct colored dots, enabling traders to quickly identify recommended exit points.
Optional Trailing Stop:
An optional trailing stop feature is available, which adjusts the stop loss as the trade moves favorably, helping to lock in profits while protecting against sudden reversals.
Risk/Reward Ratio Calculation:
MTF Signal Xpert computes a risk/reward ratio based on the dynamic SL and TP levels. This quantitative measure allows traders to assess whether the potential reward justifies the risk associated with a trade.
Condition Weighting and Signal Scoring
Binary Condition Checks:
Each technical condition—ranging from moving average crossovers, Bollinger Band positioning, and RSI range to MACD, AO, ADX, and volume filters—is assigned a binary score (1 if met, 0 if not).
Cumulative Scoring:
These individual scores are summed to generate cumulative bullish and bearish scores, quantifying the overall strength of the signal and providing traders with an objective measure of its viability.
Detailed Signal Explanation:
A comprehensive explanation string is generated, outlining which conditions contributed to the current BUY or SELL signal. This explanation is displayed on an on‑chart dashboard, offering transparency and clarity into the signal generation process.
On-Chart Visualizations and Debug Information
Chart Elements:
The indicator plots all key components—moving averages, Bollinger Bands, SL and TP markers—directly on the chart, providing a clear visual framework for understanding market conditions.
Combined Dashboard:
A dedicated dashboard displays key metrics such as RSI, ADX, and the bullish/bearish scores, alongside a detailed explanation of the current signal. This consolidated view allows traders to quickly grasp the underlying logic.
Debug Table (Optional):
For advanced users, an optional debug table is available. This table breaks down each individual condition, indicating which criteria were met or not met, thus aiding in further analysis and strategy refinement.
Mashup Justification and Originality
MTF Signal Xpert is more than just an aggregation of existing indicators—it is an original synthesis designed to address real-world trading complexities. Here’s how its components work together:
Integrated Trend, Volatility, and Momentum Analysis:
By combining moving averages, Bollinger Bands, and multiple oscillators (RSI, MACD, AO, ADX, and an optional stochastic), the indicator captures diverse market dynamics. Each component reinforces the others, reducing noise and filtering out false signals.
Multi-Timeframe Analysis:
The inclusion of a higher timeframe filter aligns short-term signals with longer-term trends, enhancing overall reliability and reducing the potential for contradictory signals.
Adaptive Risk Management:
Dynamic stop loss and take profit levels, determined using ATR, ensure that the risk management strategy adapts to current market conditions. The optional trailing stop further refines this approach, protecting profits as the market evolves.
Quantitative Signal Scoring:
The condition weighting system provides an objective measure of signal strength, giving traders clear insight into how each technical component contributes to the final decision.
How to Use MTF Signal Xpert:
Input Customization:
Adjust the moving average type and period settings, ATR multipliers, and oscillator thresholds to align with your trading style and the specific market conditions.
Enable or disable the optional stochastic oscillator and trailing stop based on your preference.
Interpreting the Signals:
When a BUY or SELL signal appears, refer to the on‑chart dashboard, which displays key metrics (e.g., RSI, ADX, bullish/bearish scores) along with a detailed breakdown of the conditions that triggered the signal.
Review the SL and TP markers on the chart to understand the associated risk/reward setup.
Risk Management:
Use the dynamically calculated stop loss and take profit levels as guidelines for setting your exit points.
Evaluate the provided risk/reward ratio to ensure that the potential reward justifies the risk before entering a trade.
Debugging and Verification:
Advanced users can enable the debug table to see a condition-by-condition breakdown of the signal generation process, helping refine the strategy and deepen understanding of market dynamics.
Disclaimer:
MTF Signal Xpert is intended for educational and analytical purposes only. Although it is based on robust technical analysis methods and has undergone extensive backtesting, past performance is not indicative of future results. Traders should employ proper risk management and adjust the settings to suit their financial circumstances and risk tolerance.
MTF Signal Xpert represents a comprehensive, original approach to trading signal generation. By blending trend detection, volatility assessment, momentum analysis, multi-timeframe alignment, and adaptive risk management into one integrated system, it provides traders with actionable signals and the transparency needed to understand the logic behind them.
Dynamic Stop Loss & Take ProfitDynamic Stop Loss & Take Profit is a versatile risk management indicator that calculates dynamic stop loss and take profit levels based on the Average True Range (ATR). This indicator helps traders set adaptive exit points by using a configurable ATR multiplier and defining whether they are in a Long (Buy) or Short (Sell) trade.
How It Works
ATR Calculation – The indicator calculates the ATR value over a user-defined period (default: 14).
Stop Loss and Take Profit Multipliers – The ATR value is multiplied by a configurable factor (ranging from 1.5 to 4) to determine volatility-adjusted stop loss and take profit levels.
Trade Type Selection – The user can specify whether they are in a Long (Buy) or Short (Sell) trade.
Long (Buy) Trade:
Stop Loss = Entry Price - (ATR × Stop Loss Multiplier)
Take Profit = Entry Price + (ATR × Take Profit Multiplier)
Short (Sell) Trade:
Stop Loss = Entry Price + (ATR × Stop Loss Multiplier)
Take Profit = Entry Price - (ATR × Take Profit Multiplier)
Features
Configurable ATR length and multipliers
Supports both long and short trades
Clearly plotted Stop Loss (red) and Take Profit (green) levels on the chart
Helps traders manage risk dynamically based on market volatility
This indicator is ideal for traders looking to set adaptive stop loss and take profit levels without relying on fixed price targets.
Volume Alert with Adaptive Trend - MissouriTimElevate your market analysis with our "Volume Alert with Adaptive Trend" indicator. This powerful tool combines real-time volume spike notifications with a sophisticated adaptive trend channel, providing traders with both immediate and long-term market insights. Customize your trading experience with adjustable volume alert thresholds and trend visualization options.
Features Summary
Volume Alert Features:
Volume Spike Detection:
Alerts you when volume exceeds a user-defined multiplier of the 20-period Simple Moving Average (SMA) of volume, helping identify potential market interest or significant price movements.
Visual Notification:
A "Volume Alert" label appears on the chart in a striking purple color (#7300E6) with white text, making high volume bars easily noticeable.
Customizable Sensitivity:
The volume spike threshold is adjustable, allowing you to set how sensitive the alert should be to volume changes, tailored to your trading strategy.
Alerts:
An alert condition is set to notify you when a volume spike occurs, ensuring you don't miss potential trading opportunities.
Adaptive Trend Features
Adaptive Channel:
Visualizes market trends through a dynamic channel that adjusts to price movements, offering insights into trend direction, strength, and potential reversal points.
Lookback Period:
Choose between short-term or long-term trend analysis with a toggle that adjusts the calculation period for the trend channel.
Channel Customization:
Fine-tune the trend channel with options for deviation multiplier, line styles, colors, transparency, and extension preferences to match your visual trading preferences.
Non-Repainting:
The trend lines are updated only on the current bar, ensuring the integrity of historical data for backtesting and strategy development.
Integrated Utility
Combination of Tools: This indicator marries the immediacy of volume alerts with the strategic depth of trend analysis, offering a comprehensive view of market dynamics.
User Customization: With inputs for both volume alerts and trend visualization, the indicator can be tailored to suit various trading styles, from scalping to swing trading.
This indicator ensures you're always in tune with market movements, providing crucial information at a glance to inform your trading decisions.
Bollinger Bands with Narrow ConsolidationThe indicator is based on the standard Bollinger Bands indicator in TradingView. Its main difference is the ability to display narrow consolidation zones (with an adjustable percentage) and generate signals in these zones.
Narrow consolidation zones can be considered as a signal before the start of a strong trend, whether upward or downward.
Индикатор построен на стандартном индикаторе полос боллинджера в трейдинг вью. Его отличие заключается в том, что здесь есть возможность отображения зон узкой консолидации (процент настраивается) и генерации сигналов на этих зонах.
Зоны узкой консолидации можно рассматривать как сигнал перед началом сильного треда как восходящего, так и нисходящего.
Enhanced Bollinger Bands Strategy with SL/TP// Title: Enhanced Bollinger Bands Strategy with SL/TP
// Description:
// This strategy is based on the classic Bollinger Bands indicator and incorporates Stop Loss (SL) and Take Profit (TP) levels for automated trading. It identifies potential long and short entry points based on price crossing the lower and upper Bollinger Bands, respectively. The strategy allows users to customize several parameters to suit different market conditions and risk tolerances.
// Key Features:
// * **Bollinger Bands:** Uses Simple Moving Average (SMA) as the basis and calculates upper and lower bands based on a user-defined standard deviation multiplier.
// * **Customizable Parameters:** Offers extensive customization, including SMA length, standard deviation multiplier, Stop Loss (SL) in pips, and Take Profit (TP) in pips.
// * **Long/Short Position Control:** Allows users to independently enable or disable long and short positions.
// * **Stop Loss and Take Profit:** Implements Stop Loss and Take Profit levels based on pip values to manage risk and secure profits. Entry prices are set to the band levels on signals.
// * **Visualizations:** Provides options to display Bollinger Bands and entry signals on the chart for easy analysis.
// Strategy Logic:
// 1. **Bollinger Bands Calculation:** The strategy calculates the Bollinger Bands using the specified SMA length and standard deviation multiplier.
// 2. **Entry Conditions:**
// * **Long Entry:** Enters a long position when the closing price crosses above the lower Bollinger Band and the `Enable Long Positions` setting is enabled.
// * **Short Entry:** Enters a short position when the closing price crosses below the upper Bollinger Band and the `Enable Short Positions` setting is enabled.
// 3. **Exit Conditions:**
// * **Stop Loss:** Exits the position if the price reaches the Stop Loss level, calculated based on the input `Stop Loss (Pips)`.
// * **Take Profit:** Exits the position if the price reaches the Take Profit level, calculated based on the input `Take Profit (Pips)`.
// Input Parameters:
// * **SMA Length (length):** The length of the Simple Moving Average used to calculate the Bollinger Bands (default: 20).
// * **Standard Deviation Multiplier (mult):** The multiplier applied to the standard deviation to determine the width of the Bollinger Bands (default: 2.0).
// * **Enable Long Positions (enableLong):** A boolean value to enable or disable long positions (default: true).
// * **Enable Short Positions (enableShort):** A boolean value to enable or disable short positions (default: true).
// * **Pip Value (pipValue):** The value of a pip for the traded instrument. This is crucial for accurate Stop Loss and Take Profit calculations (default: 0.0001 for most currency pairs). **Important: Adjust this value to match the specific instrument you are trading.**
// * **Stop Loss (Pips) (slPips):** The Stop Loss level in pips (default: 10).
// * **Take Profit (Pips) (tpPips):** The Take Profit level in pips (default: 20).
// * **Show Bollinger Bands (showBands):** A boolean value to show or hide the Bollinger Bands on the chart (default: true).
// * **Show Entry Signals (showSignals):** A boolean value to show or hide entry signals on the chart (default: true).
// How to Use:
// 1. Add the strategy to your TradingView chart.
// 2. Adjust the input parameters to optimize the strategy for your chosen instrument and timeframe. Pay close attention to the `Pip Value`.
// 3. Backtest the strategy over different periods to evaluate its performance.
// 4. Use the `Enable Long Positions` and `Enable Short Positions` settings to customize the strategy for specific market conditions (e.g., only long positions in an uptrend).
// Important Notes and Disclaimers:
// * **Backtesting Results:** Past performance is not indicative of future results. Backtesting results can be affected by various factors, including market volatility, slippage, and transaction costs.
// * **Risk Management:** This strategy is provided for informational and educational purposes only and should not be considered financial advice. Always use proper risk management techniques when trading. Adjust Stop Loss and Take Profit levels according to your risk tolerance.
// * **Slippage:** The strategy takes into account slippage by specifying a slippage parameter on the `strategy` declaration. However, real-world slippage may vary.
// * **Market Conditions:** The performance of this strategy can vary significantly depending on market conditions. It may perform well in trending markets but poorly in ranging or choppy markets.
// * **Pip Value Accuracy:** **Ensure the `Pip Value` is correctly set for the specific instrument you are trading. Incorrect pip value will result in incorrect stop loss and take profit placement.** This is critical.
// * **Broker Compatibility:** The strategy's performance may vary depending on your broker's execution policies and fees.
// * **Disclaimer:** I am not a financial advisor, and this script is not financial advice. Use this strategy at your own risk. I am not responsible for any losses incurred while using this strategy.
VWAP + KCVolume Weighted Average Price (VWAP) is a technical analysis tool used to measure the average price weighted by volume. VWAP is typically used with intraday charts as a way to determine the general direction of intraday prices. It's similar to a moving average in that when price is above VWAP, prices are rising and when price is below VWAP, prices are falling. VWAP is primarily used by technical analysts to identify market trend.
The Keltner Channels (KC) indicator is a banded indicator similar to Bollinger Bands and Moving Average Envelopes. They consist of an Upper Envelope above a Middle Line as well as a Lower Envelope below the Middle Line. The Middle Line is a moving average of price over a user-defined time period. Either a simple moving average or an exponential moving average are typically used. The Upper and Lower Envelopes are set a (user-defined multiple) of a range away from the Middle Line. This can be a multiple of the daily high/low range, or more commonly a multiple of the Average True Range.
Fib Speed Resistance Fan"Fib Speed Resistance Fan," automatically draws Fibonacci Speed Resistance Fan lines based on the first and third candles of the trading session. Here’s a breakdown of its functionality:
Functionality
Session Start Time Identification
The script identifies the first candle at 9:15 AM using timestamp(), which ensures it captures the market's opening candle.
Candle Indexing
It determines the index of the first candle (firstCandleIndex) using ta.barssince(time >= sessionStart).
The third candle is found by adding two bars to the first candle's index (thirdCandleIndex = firstCandleIndex + 2).
Ensuring Single Execution
A boolean flag hasDrawn ensures that the lines are drawn only once and do not update on future candles.
Validating Data
It checks if the firstCandleIndex and thirdCandleIndex are valid (validSession).
If conditions are met, it extracts the highs and lows of the first and third candles.
Fibonacci Calculation
The script calculates a 0.75 level price between the first candle high/low and third candle low/high.
This level helps in drawing intermediate Fibonacci fan lines.
Drawing the Fibonacci Speed Resistance Fan
If conditions are valid and hasDrawn is false, the script draws:
Main fan lines from:
First candle high → Third candle low (Blue line)
First candle low → Third candle high (Blue line)
Price Step Channel [BigBeluga]Price Step Channel is designed to provide a structured look at price trends through a dynamic step line channel, highlighting trend direction and volatility boundaries.
🔵 Key Features:
Step Line with Boundaries: The central step line adjusts with price movements, creating upper and lower boundaries based on price volatility. The channel is green during uptrends and red during downtrends, visually signaling the trend’s direction.
Fakeout Markers: "✖" markers identify potential fakeouts—moments when the price breaches the channel boundary without confirming a trend change. These markers help you spot possible mean reversion points.
Dynamic Boundary Labels: Labels at the end of the channel show the price levels of the upper and lower boundaries. In uptrends, the upper label turns green; in downtrends, the lower label turns red, providing an instant read on the trend's direction.
Customizable Display: You can toggle off the boundaries and labels for a cleaner view, focusing only on the step line and its color-coded trend signals.
🔵 When to Use:
Price Step Channel is ideal for traders looking to follow structured trends with defined volatility boundaries. The step line and color-coded channel provide clear trend insights, while the fakeout markers and customizable display options enhance flexibility in different market conditions. Whether you’re focusing on clean trend signals or detailed boundary interactions, this tool adapts to your style.
Moving Average Crossover StrategyCertainly! Below is an example of a professional trading strategy implemented in Pine Script for TradingView. This strategy is a simple moving average crossover strategy, which is a common approach used by many traders. It uses two moving averages (a short-term and a long-term) to generate buy and sell signals.
Input Parameters:
shortLength: The length of the short-term moving average.
longLength: The length of the long-term moving average.
Moving Averages:
shortMA: The short-term simple moving average (SMA).
longMA: The long-term simple moving average (SMA).
Conditions:
longCondition: A buy signal is generated when the short-term MA crosses above the long-term MA.
shortCondition: A sell signal is generated when the short-term MA crosses below the long-term MA.
Trade Execution:
The strategy enters a long position when the longCondition is met.
The strategy enters a short position when the shortCondition is met.
Plotting:
The moving averages are plotted on the chart.
Buy and sell signals are plotted as labels on the chart.
How to Use:
Copy the script into TradingView's Pine Script editor.
Adjust the shortLength and longLength parameters to fit your trading style.
Add the script to your chart and apply it to your desired timeframe.
Backtest the strategy to see how it performs on historical data.
This is a basic example, and professional traders often enhance such strategies with additional filters, risk management rules, and other indicators to improve performance.
