Vertical Lines Every 12 Hours//@version=5
indicator("Vertical Lines Every 12 Hours", overlay=true)
// Get the current time in milliseconds since the Unix epoch
currentTime = time
// Calculate 12 hours in milliseconds (12 hours * 60 minutes/hour * 60 seconds/minute * 1000 milliseconds/second)
twelveHoursInMs = 12 * 60 * 60 * 1000
// Determine the timestamp of the last 12-hour mark
// We use 'time / twelveHoursInMs' to get the number of 12-hour blocks since epoch,
// then multiply by 'twelveHoursInMs' to get the start of the current 12-hour block.
// Adding 'twelveHoursInMs' ensures we plot at the *next* 12-hour mark.
// The modulo operator '%' helps us check if the current bar's time is exactly
// at a 12-hour interval relative to the start of the current day.
// This approach tries to align the lines consistently.
// A more robust way to do this is to check if the hour changes to 00:00 or 12:00 UTC (or your preferred timezone)
// and plot a line then. However, for "every 12 hours" relative to the chart's start,
// a simple time-based check is often sufficient.
// Let's refine the logic to hit specific 12-hour intervals like 00:00 and 12:00 daily (UTC as an example).
// You might need to adjust the timezone based on your chart's time zone settings and your preference.
// Get the hour of the day for the current bar's timestamp
hourOfDay = hour(time, "GMT") // "GMT" for UTC, adjust as needed (e.g., "America/New_York", "Asia/Jerusalem")
// Plot a vertical line if the hour is 0 (midnight) or 12 (noon)
if hourOfDay == 0 or hourOfDay == 12
line.new(x1=bar_index, y1=low, x2=bar_index, y2=high, extend=extend.both, color=color.blue, width=1)
지표 및 전략
Fester prozentualer Abstand zum Kursthe indicator delivers a fixed percent distance to the market price, made with AI support
NY opennew york open.
new york open hours of the past two weeks up until two days ahead are shown as vertical lines which is great for both analyzing past data and seeing where would future new york open align with compared to your own future analysis.
10-Period Simple Moving AverageSimple Moving Average 10 Period. Moving average 10 period. SMA. The SMA works on any timeframe (e.g., 1-minute, 1-hour, daily). The 10-period SMA will calculate based on the chart’s timeframe (e.g., 10 minutes on a 1-minute chart, 10 days on a daily chart). If you want to change the SMA period, edit the number in ta.sma(close, 10) to your desired period (e.g., ta.sma(close, 20) for a 20-period SMA).
My script//@version=5
indicator("XAUUSD High Win-Rate Strategy", shorttitle="XAUUSD HWR", overlay=true)
// ============================================================================
// XAUUSD HIGH WIN-RATE STRATEGY INDICATOR
// Based on Dual-Phase Momentum Filter System
// Designed for M1, M5 timeframes with H1/H4 bias confirmation
// ============================================================================
// Input Parameters
ma_length = input.int(55, title="MA Channel Length", minval=1, maxval=200)
atr_length = input.int(14, title="ATR Length", minval=1, maxval=50)
atr_multiplier = input.float(2.5, title="ATR Stop Loss Multiplier", minval=1.0, maxval=5.0, step=0.1)
rr_ratio = input.float(1.5, title="Risk:Reward Ratio", minval=1.0, maxval=3.0, step=0.1)
htf_bias = input.timeframe("60", title="Higher Timeframe for Bias")
show_levels = input.bool(true, title="Show Entry/Exit Levels")
show_signals = input.bool(true, title="Show Buy/Sell Signals")
show_channel = input.bool(true, title="Show MA Channel")
// ============================================================================
// CORE CALCULATIONS
// ============================================================================
// Moving Average Channel (55-period High/Low)
ma_high = ta.sma(high, ma_length)
ma_low = ta.sma(low, ma_length)
// Heiken Ashi Calculations
ha_close = (open + high + low + close) / 4
var float ha_open = na
ha_open := na(ha_open ) ? (open + close) / 2 : (ha_open + ha_close ) / 2
ha_high = math.max(high, math.max(ha_open, ha_close))
ha_low = math.min(low, math.min(ha_open, ha_close))
// Higher Timeframe Bias (200 SMA)
htf_sma200 = request.security(syminfo.tickerid, htf_bias, ta.sma(close, 200), lookahead=barmerge.lookahead_off)
// ATR for Stop Loss Calculation
atr = ta.atr(atr_length)
// RSI for Additional Confirmation
rsi = ta.rsi(close, 14)
// ============================================================================
// SIGNAL LOGIC
// ============================================================================
// Channel Filter - No trades when price is within the channel
in_channel = close > ma_low and close < ma_high
outside_channel = not in_channel
// Heiken Ashi Color
ha_bullish = ha_close > ha_open
ha_bearish = ha_close < ha_open
// Higher Timeframe Bias
htf_bullish = close > htf_sma200
htf_bearish = close < htf_sma200
// Entry Conditions
long_condition = outside_channel and close > ma_high and ha_bullish and htf_bullish
short_condition = outside_channel and close < ma_low and ha_bearish and htf_bearish
// Entry Signals (only on bar close to avoid repainting)
long_signal = long_condition and not long_condition
short_signal = short_condition and not short_condition
// ============================================================================
// TRADE LEVELS CALCULATION
// ============================================================================
var float entry_price = na
var float stop_loss = na
var float take_profit = na
var string trade_direction = na
// Calculate levels for new signals
if long_signal
entry_price := close
stop_loss := close - (atr * atr_multiplier)
take_profit := close + ((close - stop_loss) * rr_ratio)
trade_direction := "LONG"
if short_signal
entry_price := close
stop_loss := close + (atr * atr_multiplier)
take_profit := close - ((stop_loss - close) * rr_ratio)
trade_direction := "SHORT"
// ============================================================================
// VISUAL ELEMENTS
// ============================================================================
// MA Channel - Store plot IDs for fill function
ma_high_plot = plot(show_channel ? ma_high : na, color=color.blue, linewidth=1, title="MA High")
ma_low_plot = plot(show_channel ? ma_low : na, color=color.red, linewidth=1, title="MA Low")
// Fill the channel
fill(ma_high_plot, ma_low_plot, color=color.new(color.gray, 90), title="MA Channel")
// Higher Timeframe SMA200
plot(htf_sma200, color=color.purple, linewidth=2, title="HTF SMA200")
// Entry Signals
plotshape(show_signals and long_signal, title="Long Signal", location=location.belowbar,
style=shape.triangleup, size=size.normal, color=color.green)
plotshape(show_signals and short_signal, title="Short Signal", location=location.abovebar,
style=shape.triangledown, size=size.normal, color=color.red)
// Trade Levels
entry_plot = plot(show_levels and not na(entry_price) ? entry_price : na,
color=color.yellow, linewidth=2, style=line.style_dashed, title="Entry Price")
stop_plot = plot(show_levels and not na(stop_loss) ? stop_loss : na,
color=color.red, linewidth=2, style=line.style_dotted, title="Stop Loss")
target_plot = plot(show_levels and not na(take_profit) ? take_profit : na,
color=color.green, linewidth=2, style=line.style_dotted, title="Take Profit")
// ============================================================================
// ALERTS
// ============================================================================
// Alert Conditions
alertcondition(long_signal, title="Long Entry Signal",
message="XAUUSD Long Entry: Price={{close}}, SL=" + str.tostring(stop_loss) + ", TP=" + str.tostring(take_profit))
alertcondition(short_signal, title="Short Entry Signal",
message="XAUUSD Short Entry: Price={{close}}, SL=" + str.tostring(stop_loss) + ", TP=" + str.tostring(take_profit))
// ============================================================================
// INFORMATION TABLE
// ============================================================================
if barstate.islast and show_levels
var table info_table = table.new(position.top_right, 2, 8, bgcolor=color.white, border_width=1)
table.cell(info_table, 0, 0, "XAUUSD Strategy Info", text_color=color.black, text_size=size.normal)
table.cell(info_table, 1, 0, "", text_color=color.black)
table.cell(info_table, 0, 1, "Current Price:", text_color=color.black)
table.cell(info_table, 1, 1, str.tostring(close, "#.##"), text_color=color.black)
table.cell(info_table, 0, 2, "ATR (14):", text_color=color.black)
table.cell(info_table, 1, 2, str.tostring(atr, "#.##"), text_color=color.black)
table.cell(info_table, 0, 3, "RSI (14):", text_color=color.black)
table.cell(info_table, 1, 3, str.tostring(rsi, "#.##"), text_color=color.black)
table.cell(info_table, 0, 4, "HTF Bias:", text_color=color.black)
table.cell(info_table, 1, 4, htf_bullish ? "BULLISH" : "BEARISH",
text_color=htf_bullish ? color.green : color.red)
table.cell(info_table, 0, 5, "In Channel:", text_color=color.black)
table.cell(info_table, 1, 5, in_channel ? "YES" : "NO",
text_color=in_channel ? color.red : color.green)
if not na(trade_direction)
table.cell(info_table, 0, 6, "Last Signal:", text_color=color.black)
table.cell(info_table, 1, 6, trade_direction,
text_color=trade_direction == "LONG" ? color.green : color.red)
table.cell(info_table, 0, 7, "Risk/Reward:", text_color=color.black)
table.cell(info_table, 1, 7, "1:" + str.tostring(rr_ratio, "#.#"), text_color=color.black)
// ============================================================================
// BACKGROUND COLORING
// ============================================================================
// Color background based on trend and channel status
bg_color = color.new(color.white, 100)
if htf_bullish and not in_channel
bg_color := color.new(color.green, 95)
else if htf_bearish and not in_channel
bg_color := color.new(color.red, 95)
else if in_channel
bg_color := color.new(color.yellow, 95)
bgcolor(bg_color, title="Background Trend Color")
// ============================================================================
// STRATEGY NOTES
// ============================================================================
// This indicator implements the Dual-Phase Momentum Filter System:
// 1. MA Channel Filter: Avoids trades when price is between 55-period high/low MAs
// 2. Heiken Ashi Confirmation: Requires momentum alignment for entries
// 3. Higher Timeframe Bias: Uses 200 SMA on higher timeframe for direction
// 4. ATR-based Risk Management: Dynamic stop losses based on volatility
// 5. Fixed Risk:Reward Ratio: Consistent 1:1.5 profit targets
//
// Usage Instructions:
// 1. Apply to M1 or M5 timeframe for optimal signals
// 2. Set higher timeframe to H1 or H4 for bias confirmation
// 3. Wait for signals outside the MA channel
// 4. Enter trades only when all conditions align
// 5. Use provided stop loss and take profit levels
// 6. Risk no more than 0.5% of account per trade
//
// Best Trading Sessions: Asian and New York
// Avoid: Low liquidity periods and major news events
Dynamic RSIThis script is now updated to show the background fill as green and red for bullish and bearish periods
TradersPostDeluxeLibrary "TradersPostDeluxe"
TradersPost integration. It's currently not very deluxe
SendEntryAlert(ticker, action, quantity, orderType, takeProfit, stopLoss, id, price, timestamp, timezone)
Sends an alert to TradersPost to trigger an Entry
Parameters:
ticker (string) : Symbol to trade. Default is syminfo.ticker
action (series Action) : TradersPostAction (.buy, .sell) default = buy
quantity (float) : Amount to trade, default = 1
orderType (series OrderType) : TradersPostOrderType, default =e TradersPostOrderType.market
takeProfit (float) : Take profit limit price
stopLoss (float) : Stop loss price
id (string) : id for the trade
price (float) : Expected price
timestamp (int) : Time of the trade for reporting, defaults to timenow
timezone (string) : associated with the time, defaults to syminfo.timezone
Returns: Nothing
SendExitAlert(ticker, price, timestamp, timezone)
Sends an alert to TradersPost to trigger an Exit
Parameters:
ticker (string) : Symbol to flatten
price (float) : Documented planned price
timestamp (int) : Time of the trade for reporting, defaults to timenow
timezone (string) : associated with the time, defaults to syminfo.timezone
Returns: Nothing
Z-Score Mean Reversion (EURUSD)Made by Laila
Works best on 1 min/5 min timeframe ( 68% winrate)
Z-Score Mean Reversion Indicator (EURUSD)
This Pine Script indicator identifies potential buy and sell opportunities based on Z-score mean reversion for the EUR/USD pair.
The Z-score is calculated by comparing the current price to its simple moving average (SMA), measured in terms of standard deviations. If the price deviates significantly from the average—either above or below—it may revert back toward the mean.
A buy signal is generated when the Z-score drops below -2, suggesting the price is abnormally low and may rise. A sell signal is triggered when the Z-score rises above +2, indicating the price is unusually high and may fall.
On the chart, the script plots the Z-score along with horizontal lines at +2, -2, and 0. Green and red arrows highlight potential buy and sell points based on these thresholds.
Kenan Ortalama Göstergesi [16 MA] All averages are in a single indicator, 4 from each average, you can change the colors as you wish.
Trend-Filter [John Ehlers]Indicator Description — Trend-Filter
This indicator uses the SuperSmoother filter, created by John Ehlers, to smooth price data and identify trends with greater accuracy and less noise. It counts the number of consecutive bars in uptrend or downtrend to measure the strength of the movement and changes the line and background colors for easy visualization.
How to use this indicator:
SuperSmoother filter: smooths the price to reveal a clearer trend direction by filtering out fast oscillations and market noise.
Bar counting: monitors sequences of bars maintaining an up or down trend to identify consistent moves.
Dynamic colors:
Green line indicates a strong uptrend.
Red line indicates a strong downtrend.
Yellow line shows a neutral or undefined trend.
Optional colored background visually reinforces trend strength with transparency so it does not interfere with price reading.
Visual signals: arrows appear on the chart to mark the start of a strong trend, helping entry or exit decisions.
Adjustable parameters:
SuperSmoother Length: controls the filter smoothing (higher = smoother, less noise).
Trend Threshold: minimum number of consecutive bars to consider a strong trend.
Smooth colors: enable or disable line color smoothing.
Show signals: toggle trend start arrows on/off.
Show dynamic background: toggle the colored background indicating trend strength.
Recommendations:
Use alongside other technical analysis tools and risk management.
Can be applied on any timeframe, but interpretation is more reliable on charts with reasonable data volume.
Ideal for traders seeking to identify consistent trends and avoid market noise.
Support & Resistance by WhalesDesk Support & Resistance by whales Desk.
This indicates mark automatically Support & Resistance on chart.
Zweig Composite System (Weekly Smoothed)Uses 10-week (≈50-day) moving averages
Pulls weekly data for yield, breadth, and price
Maintains original Zweig thresholds for signal reliability
Displays a green triangle labeled "Zweig" when all 3 conditions align
Zweig Composite System🧠 Zweig Composite Strategy Components:
Price Momentum
Bullish when price is above a 10-week (≈50-day) moving average.
Monetary Policy (Interest Rate Direction)
Bullish when interest rates are falling (Fed is easing).
We simulate this with 10-year Treasury yields trending down.
Breadth Thrust
Already included (strong upward surge in market breadth).
Bollinger Bands Trading Signals with Win Rate AnalysisAdvanced Bollinger Bands Analysis System
English Description
This comprehensive Bollinger Bands analysis system incorporates multiple advanced techniques beyond basic price crossings, providing a sophisticated approach to market analysis and signal generation.
Advanced Analysis Methods:
Multi-Level Bollinger Bands
Inner Bands (1σ): Early warning zones
Standard Bands (2σ): Traditional support/resistance
Outer Bands (2.5σ): Extreme levels
BB Width Analysis
Measures market volatility in real-time
Percentile ranking over 100 periods
Identifies low volatility periods before breakouts
Percent B (%B) Indicator
Shows price position within BB range (0-100%)
More precise than simple band touches
Values >80% = overbought, <20% = oversold
Bollinger Squeeze Detection
Identifies periods of extremely low volatility
Predicts imminent large price moves
Automatic squeeze ending alerts
Pattern Recognition
W Pattern: Double bottom at lower band (bullish reversal)
M Pattern: Double top at upper band (bearish reversal)
Band bounce detection with threshold filtering
Multi-Timeframe Confirmation
Higher timeframe trend filter
Reduces false signals in counter-trend setups
Signal Generation Strategies:
Basic Crosses: Traditional band crossing signals
BB Width: Volatility-based entry timing
Percent B: Precise overbought/oversold signals
Squeeze Breakout: Post-consolidation momentum
Pattern Recognition: Reversal pattern signals
Advanced Combined: Multi-factor confirmation system
Key Features:
Real-time %B and BB Width monitoring
Squeeze status visualization
Pattern recognition with visual markers
Comprehensive win rate statistics for each method
Multi-timeframe analysis capabilities
Volume confirmation filtering
中文介绍
这是一个全面的布林带分析系统，融合了超越基础价格穿越的多种高级技术，提供了复杂的市场分析和信号生成方法。
高级分析方法：
多层布林带
内轨（1σ）：早期预警区域
标准轨（2σ）：传统支撑阻力
外轨（2.5σ）：极端水平
布林带宽度分析
实时测量市场波动性
100周期百分位排名
识别突破前的低波动期
%B指标
显示价格在布林带范围内的位置（0-100%）
比简单的轨道触及更精确
数值>80%=超买，<20%=超卖
布林带挤压检测
识别极低波动性期间
预测即将到来的大幅价格变动
自动挤压结束警报
形态识别
W型：下轨双底（看涨反转）
M型：上轨双顶（看跌反转）
带阈值过滤的轨道反弹检测
多时间周期确认
更高时间周期趋势过滤
减少逆趋势设置中的假信号
信号生成策略：
基础穿越：传统轨道穿越信号
布林带宽度：基于波动性的入场时机
%B指标：精确的超买超卖信号
挤压突破：整理后动量信号
形态识别：反转形态信号
高级组合：多因子确认系统
核心特性：
实时%B和布林带宽度监控
挤压状态可视化
带可视标记的形态识别
每种方法的全面胜率统计
多时间周期分析能力
成交量确认过滤
应用场景：
波动性交易：利用挤压期后的爆发
均值回归：在极端位置寻找反转
趋势跟踪：通过%B和宽度确认趋势
风险管理：基于统计数据优化策略
市场状态分析：全面了解当前市场环境
Chebyshev-Gauss RSIThe Chebyshev-Gauss RSI is a variant of the standard Relative Strength Index (RSI) that uses the Chebyshev-Gauss Moving Average (CG-MA) for smoothing gains and losses instead of a traditional Simple or Exponential Moving Average. This results in a more responsive and potentially smoother RSI line.
This version is enhanced with features from the built-in TradingView RSI indicator, including:
A selectable smoothing moving average of the RSI line.
Bollinger Bands based on the smoothing MA.
Automatic divergence detection.
How it works:
It calculates the upward and downward price changes (gains and losses).
It applies the Chebyshev-Gauss Moving Average to smooth these gains and losses over a specified lookback period.
The smoothed values are used to calculate the Relative Strength (RS) and then the final RSI value.
Chebyshev-Gauss Convergence DivergenceThe Chebyshev-Gauss Convergence Divergence is a momentum indicator that leverages the Chebyshev-Gauss Moving Average (CG-MA) to provide a smoother and more responsive alternative to traditional oscillators like the MACD. For more information see the moving average script:
How it works:
It calculates a fast CG-MA and a slow CG-MA. The CG-MA uses Gauss-Chebyshev quadrature to compute a weighted average, which can offer a better trade-off between lag and smoothness compared to simple or exponential MAs.
The Oscillator line is the difference between the fast CG-MA and the slow CG-MA.
A Signal Line, which is a simple moving average of the Oscillator line, is plotted to show the average trend of the oscillator.
A Histogram is plotted, representing the difference between the Oscillator and the Signal Line. The color of the histogram bars changes to indicate whether momentum is strengthening or weakening.
How to use:
Crossovers: A buy signal can be generated when the Oscillator line crosses above the Signal line. A sell signal can be generated when it crosses below.
Zero Line: When the Oscillator crosses above the zero line, it indicates upward momentum (fast MA is above slow MA).When it crosses below zero, it indicates downward momentum.
Divergence: Like with the MACD, look for divergences between the oscillator and price action to spot potential reversals.
Histogram: The histogram provides a visual representation of the momentum. When the bars are growing, momentum is increasing. When they are shrinking, momentum is fading.
VWAP Supply & Demand Zones with Trading SignalsVWAP Supply & Demand Zones with Trading Signals & Win Rate Stats
English Description
This advanced VWAP Supply & Demand indicator combines volume-weighted average price analysis with dynamic supply/demand zone detection to generate high-probability trading signals. The indicator offers four distinct signal generation methods:
Signal Methods:
Zone Bounce: Identifies reversal signals when price rejects from established supply/demand zones
VWAP Cross: Generates signals based on price crossing above or below the VWAP line
Zone Break: Captures breakout signals when price breaks through key supply/demand levels
Combined: Utilizes multiple confirmation factors for enhanced signal reliability
Key Features:
Real-time supply/demand zone creation and management
Zone strength validation through touch counting
Volume and momentum confirmation filters
Strong signal identification for zones with multiple tests
Comprehensive 10-minute win rate statistics tracking
Visual zone display with automatic extension and break detection
Signal Quality Levels:
Regular Signals: Meet basic criteria with optional volume confirmation
Strong Signals: Generated from zones with multiple touches (≥2 by default), indicating higher reliability
The indicator automatically tracks signal performance over 10-minute intervals using precise time-based calculations, providing detailed win rate statistics for overall performance, long/short signals, strong signals, and individual signal methods.
中文介绍
这是一个结合成交量加权平均价格(VWAP)分析和动态供需区域检测的高级交易指标，用于生成高概率交易信号。该指标提供四种不同的信号生成方法：
信号方法：
区域反弹: 当价格从已建立的供需区域反弹时识别反转信号
VWAP穿越: 基于价格穿越VWAP线生成信号
区域突破: 当价格突破关键供需水平时捕获突破信号
组合方法: 利用多重确认因子增强信号可靠性
核心特性：
实时供需区域创建和管理
通过触及次数验证区域强度
成交量和动量确认过滤器
识别多次测试区域的强势信号
全面的10分钟胜率统计追踪
可视化区域显示，自动延伸和突破检测
信号质量等级：
普通信号: 满足基本条件，可选成交量确认
强势信号: 来自多次触及的区域（默认≥2次），表示更高可靠性
该指标使用精确的时间基础计算自动追踪10分钟间隔的信号表现，提供总体表现、多空信号、强势信号和各种信号方法的详细胜率统计。
CGMALibrary "CGMA"
This library provides a function to calculate a moving average based on Chebyshev-Gauss Quadrature. This method samples price data more intensely from the beginning and end of the lookback window, giving it a unique character that responds quickly to recent changes while also having a long "memory" of the trend's start. Inspired by reading rohangautam.github.io
What is Chebyshev-Gauss Quadrature?
It's a numerical method to approximate the integral of a function f(x) that is weighted by 1/sqrt(1-x^2) over the interval . The approximation is a simple sum: ∫ f(x)/sqrt(1-x^2) dx ≈ (π/n) * Σ f(xᵢ) where xᵢ are special points called Chebyshev nodes.
How is this applied to a Moving Average?
A moving average can be seen as the "mean value" of the price over a lookback window. The mean value of a function with the Chebyshev weight is calculated as:
Mean = /
The math simplifies beautifully, resulting in the mean being the simple arithmetic average of the function evaluated at the Chebyshev nodes:
Mean = (1/n) * Σ f(xᵢ)
What's unique about this MA?
The Chebyshev nodes xᵢ are not evenly spaced. They are clustered towards the ends of the interval . We map this interval to our lookback period. This means the moving average samples prices more intensely from the beginning and the end of the lookback window, and less intensely from the middle. This gives it a unique character, responding quickly to recent changes while also having a long "memory" of the start of the trend.
Chebyshev-Gauss Moving AverageThis indicator applies the principles of Chebyshev-Gauss Quadrature to create a novel type of moving average. Inspired by reading rohangautam.github.io
What is Chebyshev-Gauss Quadrature?
It's a numerical method to approximate the integral of a function f(x) that is weighted by 1/sqrt(1-x^2) over the interval . The approximation is a simple sum: ∫ f(x)/sqrt(1-x^2) dx ≈ (π/n) * Σ f(xᵢ) where xᵢ are special points called Chebyshev nodes.
How is this applied to a Moving Average?
A moving average can be seen as the "mean value" of the price over a lookback window. The mean value of a function with the Chebyshev weight is calculated as:
Mean = /
The math simplifies beautifully, resulting in the mean being the simple arithmetic average of the function evaluated at the Chebyshev nodes:
Mean = (1/n) * Σ f(xᵢ)
What's unique about this MA?
The Chebyshev nodes xᵢ are not evenly spaced. They are clustered towards the ends of the interval . We map this interval to our lookback period. This means the moving average samples prices more intensely from the beginning and the end of the lookback window, and less intensely from the middle. This gives it a unique character, responding quickly to recent changes while also having a long "memory" of the start of the trend.
Power IndicatorThe Power Indicator is a customizable EMA (Exponential Moving Average) overlay designed to help traders visually assess market trends across short-, medium-, and long-term timeframes. It plots five key EMAs — 10, 20, 50, 100, and 200 — directly on your price chart, providing a quick glance at the overall momentum and structure of the market.
Functionality:
This indicator includes the following features:
Five EMAs Plotted:
- EMA 10 → Short-term trend
- EMA 20 → Near-term trend
- EMA 50 → Medium-term trend
- EMA 100 → Intermediate trend
- EMA 200 → Long-term trend
User-defined Colors:
Each EMA has its own color setting, allowing full customization for better visibility and style matching.
🖥️Overlay on Price Chart:
EMAs are drawn directly over candles to align with your trading chart.
Real-Time Updates:
EMAs update dynamically with every new price bar.
⚙️ How to Use & Modify Settings
To customize the indicator:
- Add the indicator to your chart.
- Click the gear icon (⚙️) next to the script name.
- Under the Inputs tab, you'll see:
- EMA 10 Color – Choose your preferred color
- EMA 20 Color – Choose your preferred color
- EMA 50 Color – Choose your preferred color
- EMA 100 Color – Choose your preferred color
- EMA 200 Color – Choose your preferred color
You can adjust the colors to match your theme or emphasize specific EMAs.
MACDelta Scalping Indicator – AI-Tuned for Indian IndicesThis indicator is designed for intraday scalping on Indian indices such as the Nifty Metal Index. It fuses momentum analysis through MACD with dynamic Fibonacci retracement zones derived from recent price pivots, forming a "Delta Wave" region that acts as a price pressure zone.
Core Logic and Workflow:
Momentum Signal via MACD:
The indicator uses a customized MACD setup with parameters (fast length 14, slow length 25, signal length 9) to detect shifts in momentum. It tracks MACD crossover events (both bullish and bearish) to time potential reversals.
Delta Wave Fibonacci Zone:
Using a rolling window of 10 bars, it calculates recent pivot highs and lows, defining a dynamic price range. From this, it determines key Fibonacci retracement levels at 50% and 61.8%. This “golden zone” identifies a price region where reversals are more probable.
Signal Confirmation Window:
To ensure relevance, the indicator only triggers sell signals within a strict 3-bar window after a bearish MACD crossover. It also confirms that the price crosses below the upper Fibonacci boundary (50% retracement) within this timeframe, indicating confirmed downside pressure.
Visual Alerts:
When conditions align, the indicator plots clear “SELL” markers above the bars on the chart for easy identification by the trader.
AI Fine-Tuning:
The original logic was further optimized using Agentic AI, which refined parameter values and timing windows, minimizing false signals and enhancing trade signal quality.
Backtesting & Performance:
Extensive backtesting from 2009 to 2022 on Indian indices shows the indicator reliably signals significant corrections and short-term downswings. Notably, it outperformed the Nifty Metal Index during periods of technical correction, validating its practical utility for scalping strategies.
Key Levels + IB + VAH/VAL + FVG The full TradingView Pine Script with:
⏰ Session time zone selection
🟩 Initial Balance (IB) with parameterized duration
📦 Fair Value Gaps (FVG)
📊 Simulated Volume Profile: VAH / VAL / POC
🔁 Extended key levels across full session
SmartPulse: Advanced Intraday Signal Strategy for Indian IndicesSmartPulse is a robust and intelligent intraday trading strategy tailored specifically for Indian indices (such as Nifty and Bank Nifty) on the 15-minute timeframe. It is built to provide high-probability reversal signals by combining price action with volatility, momentum, and trend-based filters.
This strategy leverages a multi-layered approach to filter out noise and low-quality setups by analyzing:
Candle wick-to-body ratios to detect potential exhaustion zones
ATR-based consolidation detection to avoid trades in choppy markets
EMA trend alignment (EMA 20 vs EMA 50) to trade in the direction of strength
Optional RSI and volume filters to add momentum confirmation and improve accuracy
Intraday time filtering, aligned with Indian market session hours (9:05 AM to 3:20 PM IST)
It identifies reversal setups using prior candle analysis (e.g., long top wick on bearish candles or long bottom wick on bullish candles), followed by confirmation from the current candle and real-time indicators like ATR and volume. Traders can choose between basic signals (candlestick-based) and enhanced signals (with filters), or even restrict to trend-aligned signals for additional safety.
🟢 Long Signals are generated when:
Previous candle shows signs of seller exhaustion (long upper wick on a red candle)
Current candle confirms bullish momentum
Market is not consolidating
Volume and RSI (optional) support the move
Optionally aligned with an uptrend (EMA 20 > EMA 50)
🔴 Short Signals are generated when:
Previous candle shows signs of buyer exhaustion (long lower wick on a green candle)
Current candle confirms bearish momentum
Market is not consolidating
Volume and RSI (optional) support the move
Optionally aligned with a downtrend (EMA 20 < EMA 50)
✅ Key Features:
High-precision reversal signal detection
ATR-based consolidation filter to avoid chop
Optional volume and RSI-based signal validation
EMA-based trend alignment for safer entries
Real-time visual signals, alert conditions, and an info table showing market status
Fully aligned with Indian intraday trading hours
This strategy is ideal for scalpers, momentum traders, and intraday swing traders who seek reliable, filtered entries with minimal false signals in the fast-paced Indian stock market environment.
