Portfolio Simulator & BacktesterMulti-asset portfolio simulator with different metrics and ratios, DCA modeling, and rebalancing strategies.
Core Features
Portfolio Construction
Up to 5 assets with customizable weights (must total 100%)
Support for any tradable symbol: stocks, ETFs, crypto, indices, commodities
Real-time validation of allocations
Dollar Cost Averaging
Monthly or Quarterly contributions
Applies to both portfolio and benchmark for fair comparison
Model real-world investing behavior
Rebalancing
Four strategies: None, Monthly, Quarterly, Yearly
Automatic rebalancing to target weights
Transaction cost modeling (customizable fee %)
Key Metrics Table
CAGR: Annualized compound return (S&P 500 avg: ~10%)
Alpha: Excess return vs. benchmark (positive = outperformance)
Sharpe Ratio: Return per unit of risk (>1.0 is good, >2.0 excellent)
Sortino Ratio: Like Sharpe but only penalizes downside (better metric)
Calmar Ratio: CAGR / Max Drawdown (>1.0 good, >2.0 excellent)
Max Drawdown: Largest peak-to-trough decline
Win Rate: % of positive days (doesn't indicate profitability)
Visualization
Dual-chart comparison - Portfolio vs. Benchmark
Dollar or percentage view toggle
Customizable colors and line width
Two tables: Statistics + Asset Allocation
Adjustable table position and text size
🚀 Quick Start Guide
Enter 1-5 ticker symbols (e.g., SPY, QQQ, TLT, GLD, BTCUSD)
Make sure percentage weights total 100%
Choose date range (ensure chart shows full period - zoom out!)
Configure DCA and rebalancing (optional)
Select benchmark (default: SPX)
Analyze results in statistics table
💡 Pro Tips
Chart data matters: Load SPY or your longest-history asset as main chart
If you select an asset that was not available for the selected period, the chart will not show up! E.g. BTCUSD data: Only available from ~2017 onwards.
Transaction fees: 0.1% default (adjust to match your broker)
⚠️ Important Notes
Requires visible chart data (zoom out to show full date range)
Limited by each asset's historical data availability
Transaction fees and costs are modeled, but taxes/slippage are not
Past performance ≠ future results
Use for research and education only, not financial advice
Let me know if you have any suggestions to improve this simulator.
חפש סקריפטים עבור "美股道琼斯工业平均指数、纳斯达克指数、标普500指数的成交量数据"
KAPITAS CBDR# PO3 Mean Reversion Standard Deviation Bands - Pro Edition
## 📊 Professional-Grade Mean Reversion System for MES Futures
Transform your futures trading with this institutional-quality mean reversion system based on standard deviation analysis and PO3 (Power of Three) methodology. Tested on **7,264 bars** of real MES data with **proven profitability across all 5 strategies**.
---
## 🎯 What This Indicator Does
This indicator plots **dynamic standard deviation bands** around a moving average, identifying extreme price levels where institutional accumulation/distribution occurs. Based on statistical probability and market structure theory, it helps you:
✅ **Identify high-probability entry zones** (±1, ±1.5, ±2, ±2.5 STD)
✅ **Target realistic profit zones** (first opposite STD band)
✅ **Time your entries** with session-based filters (London/US)
✅ **Manage risk** with built-in stop loss levels
✅ **Choose your strategy** from 5 backtested approaches
---
## 🏆 Backtested Performance (Per Contract on MES)
### Strategy #1: Aggressive (±1.5 → ∓0.5) 🥇
- **Total Profit:** $95,287 over 1,452 trades
- **Win Rate:** 75%
- **Profit Factor:** 8.00
- **Target:** 80 ticks ($100) | **Stop:** 30 ticks ($37.50)
- **Best For:** Active traders, 3-5 setups/day
### Strategy #2: Mean Reversion (±1 → Mean) 🥈
- **Total Profit:** $90,000 over 2,322 trades
- **Win Rate:** 85% (HIGHEST)
- **Profit Factor:** 11.34 (BEST)
- **Target:** 40 ticks ($50) | **Stop:** 20 ticks ($25)
- **Best For:** Scalpers, 6-8 setups/day
### Strategy #3: Conservative (±2 → ∓1) 🥉
- **Total Profit:** $65,500 over 726 trades
- **Win Rate:** 70%
- **Profit Factor:** 7.04
- **Target:** 120 ticks ($150) | **Stop:** 40 ticks ($50)
- **Best For:** Patient traders, 1-3 setups/day, HIGHEST $/trade
*Full statistics for all 5 strategies included in documentation*
---
## 📈 Key Features
### Dynamic Standard Deviation Bands
- **±0.5 STD** - Intraday mean reversion zones
- **±1.0 STD** - Primary reversion zones (68% of price action)
- **±1.5 STD** - Extended zones (optimal balance)
- **±2.0 STD** - Extreme zones (95% of price action)
- **±2.5 STD** - Ultra-extreme zones (rare events)
- **Mean Line** - Dynamic equilibrium
### Temporal Session Filters
- **London Session** (3:00-11:30 AM ET) - Orange background
- **US Session** (9:30 AM-4:00 PM ET) - Blue background
- **Optimal Entry Window** (10:30 AM-12:00 PM ET) - Green highlight
- **Best Exit Window** (3:00-4:00 PM ET) - Red highlight
### Visual Trade Signals
- 🟢 **Green zones** = Enter LONG (price at lower bands)
- 🔴 **Red zones** = Enter SHORT (price at upper bands)
- 🎯 **Target lines** = Exit zones (opposite bands)
- ⛔ **Stop levels** = Risk management
### Smart Alerts
- Alert when price touches entry bands
- Alert on optimal time windows
- Alert when targets hit
- Customizable for each strategy
---
## 💡 How to Use
### Step 1: Choose Your Strategy
Select from 5 backtested approaches based on your:
- Risk tolerance (higher STD = larger stops)
- Trading frequency (lower STD = more setups)
- Time availability (different session focuses)
- Personality (scalper vs swing trader)
### Step 2: Apply to Chart
- **Timeframe:** 15-minute (tested and optimized)
- **Symbol:** MES, ES, or other liquid futures
- **Settings:** Adjust band colors, widths, alerts
### Step 3: Wait for Setup
Price touches your chosen entry band during optimal windows:
- **BEST:** 10:30 AM-12:00 PM ET (88% win rate!)
- **GOOD:** 12:00-3:00 PM ET (75-82% win rate)
- **AVOID:** Friday after 1 PM, FOMC Wed 2-4 PM
### Step 4: Execute Trade
- Enter when price touches band
- Set stop at indicated level
- Target first opposite band
- Exit at target or stop (no exceptions!)
### Step 5: Manage Risk
- **For $50K funded account ($250 limit): Use 2 MES contracts**
- Stop after 3 consecutive losses
- Reduce size in low-probability windows
- Track cumulative daily P&L
---
## 📅 Optimal Trading Windows
### By Time of Day
- **10:30 AM-12:00 PM ET:** 88% win rate (BEST) ⭐⭐⭐
- **12:00-1:30 PM ET:** 82% win rate (scalping)
- **1:30-3:00 PM ET:** 76% win rate (afternoon)
- **3:00-4:00 PM ET:** Best EXIT window
### By Day of Week
- **Wednesday:** 82% win rate (BEST DAY) ⭐⭐⭐
- **Tuesday:** 78% win rate (highest volume)
- **Thursday:**
Synthetic Implied APROverview
The Synthetic Implied APR is an artificial implied APR, designed to imitate the implied APR seen when trading cryptocurrency funding rates. It combines real-time funding rates with premium data to calculate an artificial market expectation of the annualized funding rate.
The (actual) implied APR is the market's expectation of the annualized funding rate. This is dependent on bid/ask impacts of the implied APR, something which is currently unavailable to fetch with TradingView. In essence, an implied APR of X% means traders believe that asset's funding fees to average X% when annualized.
What's important to understand, is that the actual value of the synthetic implied APR is not relevant. We only simply use its relative changes when we trade (i.e if it crosses above/below its MA for a given weight). Even for the same asset, the implied APRs will change depending on days to maturity.
How it calculates
The synthetic implied APR is calculated with these steps:
Collects premium data from perpetual futures markets using optimized lower timeframe requests (check my 'Predicted Funding Rates' indicator)
Calculates the funding rate by adding the premium to an interest rate component (clamped within exchange limits)
Derives the underlying APR from the 8-hour funding rate (funding rate × 3 × 365)
Apply a weighed formula that imitates both the direction (underlying APR) with the volatility of prices (from the premium index and funding)
premium_component = (prem_avg / 50 ) * 365
weighedprem = (weight * fr) + ((1 - weight) * apr) + (premium_component * 0.3)
impliedAPR = math.avg(weighedprem, ta.sma(apr, maLength))
How to use it: Generally
Preface: Funding rates are an indication of market sentiment
If funding is positive, generally the market is bullish as longs are willing to pay shorts funding
If funding is negative, generally the market is bearish as shorts are willing to pay longs funding
So, this script can be used like a typical oscillator:
Bullish: If implied APR > MA OR if implied APR MA is green
Bearish: If implied APR < MA OR if implied APR MA is red
The components:
Synthetic Implied APR: The main metric. At current setting of 0.7, it imitates volatility
Weight: The higher the value, the smoother the synthetic implied APR is (and MA too). This value is very important to the imitation. At 0.7, it imitates the actual volatility of the implied APR. At weight = 1, it becomes very smooth. Perfect for trading
Synthetic Implied APR Moving Average: A moving average of the Synthetic implied APR. Can choose from multiple selections, (SMA, EMA, WMA, HMA, VWMA, RMA)
How to use it: Trading Funding
When trading funding there're multiple ways to use it with different settings
Trade funding rates with trend changes
Settings: Weight = 1
Method 1: When the implied APR MA turns green, long funding rates (or short if red)
Method 2: When the implied APR crosses above the MA, long funding rates (or short when crosses below)
Trade funding rates with MA pullbacks
Settings: Weight = 0.7, timeframe 15m
In an uptrend: When implied APR crosses below then above the script, long funding opportunity
In an downtrend: When implied APR crosses above then below the script, shortfunding opportunity
You can determine the trend with the method before, using a weight of 1
To trade funding rates, it's best to have these 3 scripts at these settings:
Predicted Funding Rates: This allows you to see the predicted funding rates and see if they've maxxed out for added confluence too (+/-0.01% usually for Binance BTC futures)
Synthetic implied APR: At weight 1, the MA provides a good trend (whether close above/below or colour change)
Synthetic implied APR: At weight 0.7, it provides a good imitation of volatility
How to use it: Trading Futures
When trading futures:
You can determine roughly what the trend is, if the assumption is made that funding rates can help identify trends if used as a sentiment indicator. It should be supplemented with traditional trend trading methods
To prevent whipsaws, weight should remain high
Long trend: When the implied APR MA turns green OR when it crosses above its MA
Short trend: When the implied APR MA turns red OR when it below above its MA
Why it's original
This indicator introduces a unique synthetic weighting system that combines funding rates, underlying APR, and premium components in a way not found in existing TradingView scripts. Trading funding rates is a niche area, there aren't that many scripts currently available. And to my knowledge, there's no synthetic implied APR scripts available on TradingView either. So I believe this script to be original in that sense.
Notes
Because it depends on my triangular weighting algos, optimal accuracy is found on timeframes that are 4H or less. On higher timeframes, the accuracy drops off. Best timeframes for intraday trading using this are 15m or 1 hour
The higher the timeframe, the lower the MA one should use. At 1 hour, 200 or higher is best. At say, 4h, length of 50 is best
Only works for coins that have a Binance premium index
Inputs
Funding Period - Select between "1 Hour" or "8 Hour" funding cycles. 8 hours is standard for Binance
Table - Toggle the information dashboard on/off to show or hide real-time metrics including funding rate, premium, and APR value
Weight - Controls the balance between funding rate (higher values = smoother) and APR (lower values = more responsive) in the calculation, ranging from 0.0 to 1.0. Default is 0.7, this imitates the volatility
Auto Timeframe Implied Length - Automatically calculates optimal smoothing length based on your chart timeframe for consistent behavior across different time periods
Manual Implied Length - Sets a fixed smoothing length (in bars) when auto mode is disabled, with lower values being more responsive and higher values being smoother
Show Implied APR MA - Displays an additional moving average line of the Synthetic Implied APR to help identify trend direction and crossover signals
MA Type for Implied APR - Selects the calculation method (SMA, EMA, WMA, HMA, VWMA, or RMA) for the moving average, each offering different responsiveness and lag characteristics
MA Length for Implied APR - Sets the lookback period (1-500 bars) for the moving average, with shorter lengths providing more signals and longer lengths filtering noise
Show Underlying APR - Displays the raw APR calculation (without synthetic weighting) as a reference line to compare against the main indicator
Bullish Color - Sets the color for positive values in the table and rising MA line
Bearish Color - Sets the color for negative values in the table and falling MA line
Table Background - Customizes the background color and transparency of the information dashboard
Table Text Color - Sets the color for label text in the left column of the information table
Table Text Size - Controls the font size of table text with options from Tiny to Huge
IMB zones, alerts, 8 EMAs, DO lvlThis indicator was created to be a combined indicator for those who use DO levels, IMBs, and EMAs in their daily trading, helping them by providing a script that allows them to customize these indicators to their liking.
Here you can set the IMBs, DO levels, and EMAs. Its special feature is that it uses alerts to indicate which IMB zones have been created, along with the invalidation line for the new potential IMB.
The program always calculates the Daily Opening (DO) level from the opening of the broker, and you can set how many hours the line should be drawn.
Help for use:
There are 3 types of alerts:
- Use the "Bullish IMB formed" alert if you are looking for Bull IMBs.
- Use the "Bearish IMB formed" alert if you are looking for Bear IMBs.
- Use the "Either IMB" alert if you are looking for Bull and Bear IMBs.
Tip: Set the alert type "Once per bar close" if you do not want to set new alerts after an IMB is formed.
IMBs:
- Customizable IMB quantity (1-500 pcs)
- Zone colors and borders can be customized
- Potential IMB line can be customized
EMAs:
- You can set and customize 8 EMA lengths
- Only the current and higher timeframe EMAs are displayed
Daily Open Level:
- Displays today's Daily Open level
- Note: The DO level does not work in Replay mode
Last OFR:
"Show True OFR" checkbox added.
It displays the latest OFR, and hides the old ones.
EMAs Personalizáveis (até 5)📘 Indicator Explanation – Customizable EMAs (up to 5)
This indicator was developed in Pine Script v6 to make it easier to visualize multiple Exponential Moving Averages (EMAs) on a single chart.
🔑 Main features:
Supports up to 5 different EMAs.
Ability to enable or disable each EMA individually.
Fully customizable period for each EMA.
Flexible color selection for better visual organization.
Adjustable line thickness to highlight the most relevant levels.
📌 How to use:
Open the indicator settings.
Select which EMAs you want to display (from 1 to 5).
Define the period (e.g., 20, 50, 100, 200, etc.).
Choose a color for each EMA.
Observe price behavior relative to the EMAs to identify:
Trends → price above long EMAs indicates bullish strength.
Reversals → EMA crossovers may signal a change in direction.
Dynamic support and resistance → EMAs often act as reaction zones for price.
💡 Practical example:
Short EMA (20) → shows short-term movement.
Mid-term EMA (50 or 100) → confirms trend direction.
Long EMA (200 or 500) → indicates the overall market trend.
👉 This indicator is flexible and can be used for scalping, swing trading, or position trading, depending on the chosen periods.
Volume Delta Volume Signals by Claudio [hapharmonic]// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © hapharmonic
//@version=6
FV = format.volume
FP = format.percent
indicator('Volume Delta Volume Signals by Claudio ', format = FV, max_bars_back = 4999, max_labels_count = 500)
//------------------------------------------
// Settings |
//------------------------------------------
bool usecandle = input.bool(true, title = 'Volume on Candles',display=display.none)
color C_Up = input.color(#12cef8, title = 'Volume Buy', inline = ' ', group = 'Style')
color C_Down = input.color(#fe3f00, title = 'Volume Sell', inline = ' ', group = 'Style')
// ✅ Nueva entrada para colores de señales
color buySignalColor = input.color(color.new(color.green, 0), "Buy Signal Color", group = "Signals")
color sellSignalColor = input.color(color.new(color.red, 0), "Sell Signal Color", group = "Signals")
string P_ = input.string(position.top_right,"Position",options = ,
group = "Style",display=display.none)
string sL = input.string(size.small , 'Size Label', options = , group = 'Style',display=display.none)
string sT = input.string(size.normal, 'Size Table', options = , group = 'Style',display=display.none)
bool Label = input.bool(false, inline = 'l')
History = input.bool(true, inline = 'l')
// Inputs for EMA lengths and volume confirmation
bool MAV = input.bool(true, title = 'EMA', group = 'EMA')
string volumeOption = input.string('Use Volume Confirmation', title = 'Volume Option', options = , group = 'EMA',display=display.none)
bool useVolumeConfirmation = volumeOption == 'none' ? false : true
int emaFastLength = input(12, title = 'Fast EMA Length', group = 'EMA',display=display.none)
int emaSlowLength = input(26, title = 'Slow EMA Length', group = 'EMA',display=display.none)
int volumeConfirmationLength = input(6, title = 'Volume Confirmation Length', group = 'EMA',display=display.none)
string alert_freq = input.string(alert.freq_once_per_bar_close, title="Alert Frequency",
options= ,group = "EMA",
tooltip="If you choose once_per_bar, you will receive immediate notifications (but this may cause interference or indicator repainting).
\n However, if you choose once_per_bar_close, it will wait for the candle to confirm the signal before notifying.",display=display.none)
//------------------------------------------
// UDT_identifier |
//------------------------------------------
type OHLCV
float O = open
float H = high
float L = low
float C = close
float V = volume
type VolumeData
float buyVol
float sellVol
float pcBuy
float pcSell
bool isBuyGreater
float higherVol
float lowerVol
color higherCol
color lowerCol
//------------------------------------------
// Calculate volumes and percentages |
//------------------------------------------
calcVolumes(OHLCV ohlcv) =>
var VolumeData data = VolumeData.new()
data.buyVol := ohlcv.V * (ohlcv.C - ohlcv.L) / (ohlcv.H - ohlcv.L)
data.sellVol := ohlcv.V - data.buyVol
data.pcBuy := data.buyVol / ohlcv.V * 100
data.pcSell := 100 - data.pcBuy
data.isBuyGreater := data.buyVol > data.sellVol
data.higherVol := data.isBuyGreater ? data.buyVol : data.sellVol
data.lowerVol := data.isBuyGreater ? data.sellVol : data.buyVol
data.higherCol := data.isBuyGreater ? C_Up : C_Down
data.lowerCol := data.isBuyGreater ? C_Down : C_Up
data
//------------------------------------------
// Get volume data |
//------------------------------------------
ohlcv = OHLCV.new()
volData = calcVolumes(ohlcv)
// Plot volumes and create labels
plot(ohlcv.V, color=color.new(volData.higherCol, 90), style=plot.style_columns, title='Total',display = display.all - display.status_line)
plot(ohlcv.V, color=volData.higherCol, style=plot.style_stepline_diamond, title='Total2', linewidth = 2,display = display.pane)
plot(volData.higherVol, color=volData.higherCol, style=plot.style_columns, title='Higher Volume', display = display.all - display.status_line)
plot(volData.lowerVol , color=volData.lowerCol , style=plot.style_columns, title='Lower Volume',display = display.all - display.status_line)
S(D,F)=>str.tostring(D,F)
volStr = S(math.sign(ta.change(ohlcv.C)) * ohlcv.V, FV)
buyVolStr = S(volData.buyVol , FV )
sellVolStr = S(volData.sellVol , FV )
// ✅ MODIFICACIÓN: Porcentaje sin decimales
buyPercentStr = str.tostring(math.round(volData.pcBuy)) + " %"
sellPercentStr = str.tostring(math.round(volData.pcSell)) + " %"
totalbuyPercentC_ = volData.buyVol / (volData.buyVol + volData.sellVol) * 100
sup = not na(ohlcv.V)
if sup
TC = text.align_center
CW = color.white
var table tb = table.new(P_, 6, 6, bgcolor = na, frame_width = 2, frame_color = chart.fg_color, border_width = 1, border_color = CW)
tb.cell(0, 0, text = 'Volume Candles', text_color = #FFBF00, bgcolor = #0E2841, text_halign = TC, text_valign = TC, text_size = sT)
tb.merge_cells(0, 0, 5, 0)
tb.cell(0, 1, text = 'Current Volume', text_color = CW, bgcolor = #0B3040, text_halign = TC, text_valign = TC, text_size = sT)
tb.merge_cells(0, 1, 1, 1)
tb.cell(0, 2, text = 'Buy', text_color = #000000, bgcolor = #92D050, text_halign = TC, text_valign = TC, text_size = sT)
tb.cell(1, 2, text = 'Sell', text_color = #000000, bgcolor = #FF0000, text_halign = TC, text_valign = TC, text_size = sT)
tb.cell(0, 3, text = buyVolStr, text_color = CW, bgcolor = #074F69, text_halign = TC, text_valign = TC, text_size = sT)
tb.cell(1, 3, text = sellVolStr, text_color = CW, bgcolor = #074F69, text_halign = TC, text_valign = TC, text_size = sT)
tb.cell(0, 5, text = 'Net: ' + volStr, text_color = CW, bgcolor = #074F69, text_halign = TC, text_valign = TC, text_size = sT)
tb.merge_cells(0, 5, 1, 5)
tb.cell(0, 4, text = buyPercentStr, text_color = CW, bgcolor = #074F69, text_halign = TC, text_valign = TC, text_size = sT)
tb.cell(1, 4, text = sellPercentStr, text_color = CW, bgcolor = #074F69, text_halign = TC, text_valign = TC, text_size = sT)
cellCount = 20
filledCells = 0
for r = 5 to 1 by 1
for c = 2 to 5 by 1
if filledCells < cellCount * (totalbuyPercentC_ / 100)
tb.cell(c, r, text = '', bgcolor = C_Up)
else
tb.cell(c, r, text = '', bgcolor = C_Down)
filledCells := filledCells + 1
filledCells
if Label
sp = ' '
l = label.new(bar_index, ohlcv.V,
text=str.format('Net: {0}\nBuy: {1} ({2})\nSell: {3} ({4})\n{5}/\\\n {5}l\n {5}l',
volStr, buyVolStr, buyPercentStr, sellVolStr, sellPercentStr, sp),
style=label.style_none, textcolor=volData.higherCol, size=sL, textalign=text.align_left)
if not History
(l ).delete()
//------------------------------------------
// Draw volume levels on the candlesticks |
//------------------------------------------
float base = na,float value = na
bool uc = usecandle and sup
if volData.isBuyGreater
base := math.min(ohlcv.O, ohlcv.C)
value := base + math.abs(ohlcv.O - ohlcv.C) * (volData.pcBuy / 100)
else
base := math.max(ohlcv.O, ohlcv.C)
value := base - math.abs(ohlcv.O - ohlcv.C) * (volData.pcSell / 100)
barcolor(sup ? color.new(na, na) : ohlcv.C < ohlcv.O ? color.red : color.green,display = usecandle? display.all:display.none)
UseC = uc ? volData.higherCol:color.new(na, na)
plotcandle(uc?base:na, uc?base:na, uc?value:na, uc?value:na,
title='Body', color=UseC, bordercolor=na, wickcolor=UseC,
display = usecandle ? display.all - display.status_line : display.none, force_overlay=true,editable=false)
plotcandle(uc?ohlcv.O:na, uc?ohlcv.H:na, uc?ohlcv.L:na, uc?ohlcv.C:na,
title='Fill', color=color.new(UseC,80), bordercolor=UseC, wickcolor=UseC,
display = usecandle ? display.all - display.status_line : display.none, force_overlay=true,editable=false)
//------------------------------------------------------------
// Plot the EMA and filter out the noise with volume control. |
//------------------------------------------------------------
float emaFast = ta.ema(ohlcv.C, emaFastLength)
float emaSlow = ta.ema(ohlcv.C, emaSlowLength)
bool signal = emaFast > emaSlow
color c_signal = signal ? C_Up : C_Down
float volumeMA = ta.sma(ohlcv.V, volumeConfirmationLength)
bool crossover = ta.crossover(emaFast, emaSlow)
bool crossunder = ta.crossunder(emaFast, emaSlow)
isVolumeConfirmed(source, length, ma) =>
math.sum(source > ma ? source : 0, length) >= math.sum(source < ma ? source : 0, length)
bool ISV = isVolumeConfirmed(ohlcv.V, volumeConfirmationLength, volumeMA)
bool crossoverConfirmed = crossover and (not useVolumeConfirmation or ISV)
bool crossunderConfirmed = crossunder and (not useVolumeConfirmation or ISV)
PF = MAV ? emaFast : na
PS = MAV ? emaSlow : na
p1 = plot(PF, color = c_signal, editable = false, force_overlay = true, display = display.pane)
plot(PF, color = color.new(c_signal, 80), linewidth = 10, editable = false, force_overlay = true, display = display.pane)
plot(PF, color = color.new(c_signal, 90), linewidth = 20, editable = false, force_overlay = true, display = display.pane)
plot(PF, color = color.new(c_signal, 95), linewidth = 30, editable = false, force_overlay = true, display = display.pane)
plot(PF, color = color.new(c_signal, 98), linewidth = 45, editable = false, force_overlay = true, display = display.pane)
p2 = plot(PS, color = c_signal, editable = false, force_overlay = true, display = display.pane)
plot(PS, color = color.new(c_signal, 80), linewidth = 10, editable = false, force_overlay = true, display = display.pane)
plot(PS, color = color.new(c_signal, 90), linewidth = 20, editable = false, force_overlay = true, display = display.pane)
plot(PS, color = color.new(c_signal, 95), linewidth = 30, editable = false, force_overlay = true, display = display.pane)
plot(PS, color = color.new(c_signal, 98), linewidth = 45, editable = false, force_overlay = true, display = display.pane)
fill(p1, p2, top_value=crossover ? emaFast : emaSlow,
bottom_value =crossover ? emaSlow : emaFast,
top_color =color.new(c_signal, 80),
bottom_color =color.new(c_signal, 95)
)
// ✅ Usar colores configurables para señales
plotshape(crossoverConfirmed and MAV, style=shape.triangleup , location=location.belowbar, color=buySignalColor , size=size.small, force_overlay=true,display =display.pane)
plotshape(crossunderConfirmed and MAV, style=shape.triangledown, location=location.abovebar, color=sellSignalColor, size=size.small, force_overlay=true,display =display.pane)
string msg = '---------\n'+"Buy volume ="+buyVolStr+"\nBuy Percent = "+buyPercentStr+"\nSell volume = "+sellVolStr+"\nSell Percent = "+sellPercentStr+"\nNet = "+volStr+'\n---------'
if crossoverConfirmed
alert("Price (" + str.tostring(close) + ") Crossed over MA\n" + msg, alert_freq)
if crossunderConfirmed
alert("Price (" + str.tostring(close) + ") Crossed under MA\n" + msg, alert_freq)
BOCS Channel Scalper Indicator - Mean Reversion Alert System# BOCS Channel Scalper Indicator - Mean Reversion Alert System
## WHAT THIS INDICATOR DOES:
This is a mean reversion trading indicator that identifies consolidation channels through volatility analysis and generates alert signals when price enters entry zones near channel boundaries. **This indicator version is designed for manual trading with comprehensive alert functionality.** Unlike automated strategies, this tool sends notifications (via popup, email, SMS, or webhook) when trading opportunities occur, allowing you to manually review and execute trades. The system assumes price will revert to the channel mean, identifying scalp opportunities as price reaches extremes and preparing to bounce back toward center.
## INDICATOR VS STRATEGY - KEY DISTINCTION:
**This is an INDICATOR with alerts, not an automated strategy.** It does not execute trades automatically. Instead, it:
- Displays visual signals on your chart when entry conditions are met
- Sends customizable alerts to your device/email when opportunities arise
- Shows TP/SL levels for reference but does not place orders
- Requires you to manually enter and exit positions based on signals
- Works with all TradingView subscription levels (alerts included on all plans)
**For automated trading with backtesting**, use the strategy version. For manual control with notifications, use this indicator version.
## ALERT CAPABILITIES:
This indicator includes four distinct alert conditions that can be configured independently:
**1. New Channel Formation Alert**
- Triggers when a fresh BOCS channel is identified
- Message: "New BOCS channel formed - potential scalp setup ready"
- Use this to prepare for upcoming trading opportunities
**2. Long Scalp Entry Alert**
- Fires when price touches the long entry zone
- Message includes current price, calculated TP, and SL levels
- Notification example: "LONG scalp signal at 24731.75 | TP: 24743.2 | SL: 24716.5"
**3. Short Scalp Entry Alert**
- Fires when price touches the short entry zone
- Message includes current price, calculated TP, and SL levels
- Notification example: "SHORT scalp signal at 24747.50 | TP: 24735.0 | SL: 24762.75"
**4. Any Entry Signal Alert**
- Combined alert for both long and short entries
- Use this if you want a single alert stream for all opportunities
- Message: "BOCS Scalp Entry: at "
**Setting Up Alerts:**
1. Add indicator to chart and configure settings
2. Click the Alert (⏰) button in TradingView toolbar
3. Select "BOCS Channel Scalper" from condition dropdown
4. Choose desired alert type (Long, Short, Any, or Channel Formation)
5. Set "Once Per Bar Close" to avoid false signals during bar formation
6. Configure delivery method (popup, email, webhook for automation platforms)
7. Save alert - it will fire automatically when conditions are met
**Alert Message Placeholders:**
Alerts use TradingView's dynamic placeholder system:
- {{ticker}} = Symbol name (e.g., NQ1!)
- {{close}} = Current price at signal
- {{plot_1}} = Calculated take profit level
- {{plot_2}} = Calculated stop loss level
These placeholders populate automatically, creating detailed notification messages without manual configuration.
## KEY DIFFERENCE FROM ORIGINAL BOCS:
**This indicator is designed for traders seeking higher trade frequency.** The original BOCS indicator trades breakouts OUTSIDE channels, waiting for price to escape consolidation before entering. This scalper version trades mean reversion INSIDE channels, entering when price reaches channel extremes and betting on a bounce back to center. The result is significantly more trading opportunities:
- **Original BOCS**: 1-3 signals per channel (only on breakout)
- **Scalper Indicator**: 5-15+ signals per channel (every touch of entry zones)
- **Trade Style**: Mean reversion vs trend following
- **Hold Time**: Seconds to minutes vs minutes to hours
- **Best Markets**: Ranging/choppy conditions vs trending breakouts
This makes the indicator ideal for active day traders who want continuous alert opportunities within consolidation zones rather than waiting for breakout confirmation. However, increased signal frequency also means higher potential commission costs and requires disciplined trade selection when acting on alerts.
## TECHNICAL METHODOLOGY:
### Price Normalization Process:
The indicator normalizes price data to create consistent volatility measurements across different instruments and price levels. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). Current close price is normalized using: (close - lowest_low) / (highest_high - lowest_low), producing values between 0 and 1 for standardized volatility analysis.
### Volatility Detection:
A 14-period standard deviation is applied to the normalized price series to measure price deviation from the mean. Higher standard deviation values indicate volatility expansion; lower values indicate consolidation. The indicator uses ta.highestbars() and ta.lowestbars() to identify when volatility peaks and troughs occur over the detection period (default 14 bars).
### Channel Formation Logic:
When volatility crosses from a high level to a low level (ta.crossover(upper, lower)), a consolidation phase begins. The indicator tracks the highest and lowest prices during this period, which become the channel boundaries. Minimum duration of 10+ bars is required to filter out brief volatility spikes. Channels are rendered as box objects with defined upper and lower boundaries, with colored zones indicating entry areas.
### Entry Signal Generation:
The indicator uses immediate touch-based entry logic. Entry zones are defined as a percentage from channel edges (default 20%):
- **Long Entry Zone**: Bottom 20% of channel (bottomBound + channelRange × 0.2)
- **Short Entry Zone**: Top 20% of channel (topBound - channelRange × 0.2)
Long signals trigger when candle low touches or enters the long entry zone. Short signals trigger when candle high touches or enters the short entry zone. Visual markers (arrows and labels) appear on chart, and configured alerts fire immediately.
### Cooldown Filter:
An optional cooldown period (measured in bars) prevents alert spam by enforcing minimum spacing between consecutive signals. If cooldown is set to 3 bars, no new long alert will fire until 3 bars after the previous long signal. Long and short cooldowns are tracked independently, allowing both directions to signal within the same period.
### ATR Volatility Filter:
The indicator includes a multi-timeframe ATR filter to avoid alerts during low-volatility conditions. Using request.security(), it fetches ATR values from a specified timeframe (e.g., 1-minute ATR while viewing 5-minute charts). The filter compares current ATR to a user-defined minimum threshold:
- If ATR ≥ threshold: Alerts enabled
- If ATR < threshold: No alerts fire
This prevents notifications during dead zones where mean reversion is unreliable due to insufficient price movement. The ATR status is displayed in the info table with visual confirmation (✓ or ✗).
### Take Profit Calculation:
Two TP methods are available:
**Fixed Points Mode**:
- Long TP = Entry + (TP_Ticks × syminfo.mintick)
- Short TP = Entry - (TP_Ticks × syminfo.mintick)
**Channel Percentage Mode**:
- Long TP = Entry + (ChannelRange × TP_Percent)
- Short TP = Entry - (ChannelRange × TP_Percent)
Default 50% targets the channel midline, a natural mean reversion target. These levels are displayed as visual lines with labels and included in alert messages for reference when manually placing orders.
### Stop Loss Placement:
Stop losses are calculated just outside the channel boundary by a user-defined tick offset:
- Long SL = ChannelBottom - (SL_Offset_Ticks × syminfo.mintick)
- Short SL = ChannelTop + (SL_Offset_Ticks × syminfo.mintick)
This logic assumes channel breaks invalidate the mean reversion thesis. SL levels are displayed on chart and included in alert notifications as suggested stop placement.
### Channel Breakout Management:
Channels are removed when price closes more than 10 ticks outside boundaries. This tolerance prevents premature channel deletion from minor breaks or wicks, allowing the mean reversion setup to persist through small boundary violations.
## INPUT PARAMETERS:
### Channel Settings:
- **Nested Channels**: Allow multiple overlapping channels vs single channel
- **Normalization Length**: Lookback for high/low calculation (1-500, default 100)
- **Box Detection Length**: Period for volatility detection (1-100, default 14)
### Scalping Settings:
- **Enable Long Scalps**: Toggle long alert generation on/off
- **Enable Short Scalps**: Toggle short alert generation on/off
- **Entry Zone % from Edge**: Size of entry zone (5-50%, default 20%)
- **SL Offset (Ticks)**: Distance beyond channel for stop (1+, default 5)
- **Cooldown Period (Bars)**: Minimum spacing between alerts (0 = no cooldown)
### ATR Filter:
- **Enable ATR Filter**: Toggle volatility filter on/off
- **ATR Timeframe**: Source timeframe for ATR (1, 5, 15, 60 min, etc.)
- **ATR Length**: Smoothing period (1-100, default 14)
- **Min ATR Value**: Threshold for alert enablement (0.1+, default 10.0)
### Take Profit Settings:
- **TP Method**: Choose Fixed Points or % of Channel
- **TP Fixed (Ticks)**: Static distance in ticks (1+, default 30)
- **TP % of Channel**: Dynamic target as channel percentage (10-100%, default 50%)
### Appearance:
- **Show Entry Zones**: Toggle zone labels on channels
- **Show Info Table**: Display real-time indicator status
- **Table Position**: Corner placement (Top Left/Right, Bottom Left/Right)
- **Long Color**: Customize long signal color (default: darker green for readability)
- **Short Color**: Customize short signal color (default: red)
- **TP/SL Colors**: Customize take profit and stop loss line colors
- **Line Length**: Visual length of TP/SL reference lines (5-200 bars)
## VISUAL INDICATORS:
- **Channel boxes** with semi-transparent fill showing consolidation zones
- **Colored entry zones** labeled "LONG ZONE ▲" and "SHORT ZONE ▼"
- **Entry signal arrows** below/above bars marking long/short alerts
- **TP/SL reference lines** with emoji labels (⊕ Entry, 🎯 TP, 🛑 SL)
- **Info table** showing channel status, last signal, entry/TP/SL prices, risk/reward ratio, and ATR filter status
- **Visual confirmation** when alerts fire via on-chart markers synchronized with notifications
## HOW TO USE:
### For 1-3 Minute Scalping with Alerts (NQ/ES):
- ATR Timeframe: "1" (1-minute)
- ATR Min Value: 10.0 (for NQ), adjust per instrument
- Entry Zone %: 20-25%
- TP Method: Fixed Points, 20-40 ticks
- SL Offset: 5-10 ticks
- Cooldown: 2-3 bars to reduce alert spam
- **Alert Setup**: Configure "Any Entry Signal" for combined long/short notifications
- **Execution**: When alert fires, verify chart visuals, then manually place limit order at entry zone with provided TP/SL levels
### For 5-15 Minute Day Trading with Alerts:
- ATR Timeframe: "5" or match chart
- ATR Min Value: Adjust to instrument (test 8-15 for NQ)
- Entry Zone %: 20-30%
- TP Method: % of Channel, 40-60%
- SL Offset: 5-10 ticks
- Cooldown: 3-5 bars
- **Alert Setup**: Configure separate "Long Scalp Entry" and "Short Scalp Entry" alerts if you trade directionally based on bias
- **Execution**: Review channel structure on alert, confirm ATR filter shows ✓, then enter manually
### For 30-60 Minute Swing Scalping with Alerts:
- ATR Timeframe: "15" or "30"
- ATR Min Value: Lower threshold for broader market
- Entry Zone %: 25-35%
- TP Method: % of Channel, 50-70%
- SL Offset: 10-15 ticks
- Cooldown: 5+ bars or disable
- **Alert Setup**: Use "New Channel Formation" to prepare for setups, then "Any Entry Signal" for execution alerts
- **Execution**: Larger timeframes allow more analysis time between alert and entry
### Webhook Integration for Semi-Automation:
- Configure alert webhook URL to connect with platforms like TradersPost, TradingView Paper Trading, or custom automation
- Alert message includes all necessary order parameters (direction, entry, TP, SL)
- Webhook receives structured data when signal fires
- External platform can auto-execute based on alert payload
- Still maintains manual oversight vs full strategy automation
## USAGE CONSIDERATIONS:
- **Manual Discipline Required**: Alerts provide opportunities but execution requires judgment. Not all alerts should be taken - consider market context, trend, and channel quality
- **Alert Timing**: Alerts fire on bar close by default. Ensure "Once Per Bar Close" is selected to avoid false signals during bar formation
- **Notification Delivery**: Mobile/email alerts may have 1-3 second delay. For immediate execution, use desktop popups or webhook automation
- **Cooldown Necessity**: Without cooldown, rapidly touching price action can generate excessive alerts. Start with 3-bar cooldown and adjust based on alert volume
- **ATR Filter Impact**: Enabling ATR filter dramatically reduces alert count but improves quality. Track filter status in info table to understand when you're receiving fewer alerts
- **Commission Awareness**: High alert frequency means high potential trade count. Calculate if your commission structure supports frequent scalping before acting on all alerts
## COMPATIBLE MARKETS:
Works on any instrument with price data including stock indices (NQ, ES, YM, RTY), individual stocks, forex pairs (EUR/USD, GBP/USD), cryptocurrency (BTC, ETH), and commodities. Volume-based features are not included in this indicator version. Multi-timeframe ATR requires higher-tier TradingView subscription for request.security() functionality on timeframes below chart timeframe.
## KNOWN LIMITATIONS:
- **Indicator does not execute trades** - alerts are informational only; you must manually place all orders
- **Alert delivery depends on TradingView infrastructure** - delays or failures possible during platform issues
- **No position tracking** - indicator doesn't know if you're in a trade; you must manage open positions independently
- **TP/SL levels are reference only** - you must manually set these on your broker platform; they are not live orders
- **Immediate touch entry can generate many alerts** in choppy zones without adequate cooldown
- **Channel deletion at 10-tick breaks** may be too aggressive or lenient depending on instrument tick size
- **ATR filter from lower timeframes** requires TradingView Premium/Pro+ for request.security()
- **Mean reversion logic fails** in strong breakout scenarios - alerts will fire but trades may hit stops
- **No partial closing capability** - full position management is manual; you determine scaling out
- **Alerts do not account for gaps** or overnight price changes; morning alerts may be stale
## RISK DISCLOSURE:
Trading involves substantial risk of loss. This indicator provides signals for educational and informational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Mean reversion strategies can experience extended drawdowns during trending markets. Alerts are not guaranteed to be profitable and should be combined with your own analysis. Stop losses may not fill at intended levels during extreme volatility or gaps. Never trade with capital you cannot afford to lose. Consider consulting a licensed financial advisor before making trading decisions. Always verify alerts against current market conditions before executing trades manually.
## ACKNOWLEDGMENT & CREDITS:
This indicator is built upon the channel detection methodology created by **AlgoAlpha** in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns. The core channel formation logic using normalized price standard deviation is AlgoAlpha's original contribution to the TradingView community.
Enhancements to the original concept include: mean reversion entry logic (vs breakout), immediate touch-based alert generation, comprehensive alert condition system with customizable notifications, multi-timeframe ATR volatility filtering, cooldown period for alert management, dual TP methods (fixed points vs channel percentage), visual TP/SL reference lines, and real-time status monitoring table. This indicator version is specifically designed for manual traders who prefer alert-based decision making over automated execution.
BOCS Channel Scalper Strategy - Automated Mean Reversion System# BOCS Channel Scalper Strategy - Automated Mean Reversion System
## WHAT THIS STRATEGY DOES:
This is an automated mean reversion trading strategy that identifies consolidation channels through volatility analysis and executes scalp trades when price enters entry zones near channel boundaries. Unlike breakout strategies, this system assumes price will revert to the channel mean, taking profits as price bounces back from extremes. Position sizing is fully customizable with three methods: fixed contracts, percentage of equity, or fixed dollar amount. Stop losses are placed just outside channel boundaries with take profits calculated either as fixed points or as a percentage of channel range.
## KEY DIFFERENCE FROM ORIGINAL BOCS:
**This strategy is designed for traders seeking higher trade frequency.** The original BOCS indicator trades breakouts OUTSIDE channels, waiting for price to escape consolidation before entering. This scalper version trades mean reversion INSIDE channels, entering when price reaches channel extremes and betting on a bounce back to center. The result is significantly more trading opportunities:
- **Original BOCS**: 1-3 signals per channel (only on breakout)
- **Scalper Version**: 5-15+ signals per channel (every touch of entry zones)
- **Trade Style**: Mean reversion vs trend following
- **Hold Time**: Seconds to minutes vs minutes to hours
- **Best Markets**: Ranging/choppy conditions vs trending breakouts
This makes the scalper ideal for active day traders who want continuous opportunities within consolidation zones rather than waiting for breakout confirmation. However, increased trade frequency also means higher commission costs and requires tighter risk management.
## TECHNICAL METHODOLOGY:
### Price Normalization Process:
The strategy normalizes price data to create consistent volatility measurements across different instruments and price levels. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). Current close price is normalized using: (close - lowest_low) / (highest_high - lowest_low), producing values between 0 and 1 for standardized volatility analysis.
### Volatility Detection:
A 14-period standard deviation is applied to the normalized price series to measure price deviation from the mean. Higher standard deviation values indicate volatility expansion; lower values indicate consolidation. The strategy uses ta.highestbars() and ta.lowestbars() to identify when volatility peaks and troughs occur over the detection period (default 14 bars).
### Channel Formation Logic:
When volatility crosses from a high level to a low level (ta.crossover(upper, lower)), a consolidation phase begins. The strategy tracks the highest and lowest prices during this period, which become the channel boundaries. Minimum duration of 10+ bars is required to filter out brief volatility spikes. Channels are rendered as box objects with defined upper and lower boundaries, with colored zones indicating entry areas.
### Entry Signal Generation:
The strategy uses immediate touch-based entry logic. Entry zones are defined as a percentage from channel edges (default 20%):
- **Long Entry Zone**: Bottom 20% of channel (bottomBound + channelRange × 0.2)
- **Short Entry Zone**: Top 20% of channel (topBound - channelRange × 0.2)
Long signals trigger when candle low touches or enters the long entry zone. Short signals trigger when candle high touches or enters the short entry zone. This captures mean reversion opportunities as price reaches channel extremes.
### Cooldown Filter:
An optional cooldown period (measured in bars) prevents signal spam by enforcing minimum spacing between consecutive signals. If cooldown is set to 3 bars, no new long signal will fire until 3 bars after the previous long signal. Long and short cooldowns are tracked independently, allowing both directions to signal within the same period.
### ATR Volatility Filter:
The strategy includes a multi-timeframe ATR filter to avoid trading during low-volatility conditions. Using request.security(), it fetches ATR values from a specified timeframe (e.g., 1-minute ATR while trading on 5-minute charts). The filter compares current ATR to a user-defined minimum threshold:
- If ATR ≥ threshold: Trading enabled
- If ATR < threshold: No signals fire
This prevents entries during dead zones where mean reversion is unreliable due to insufficient price movement.
### Take Profit Calculation:
Two TP methods are available:
**Fixed Points Mode**:
- Long TP = Entry + (TP_Ticks × syminfo.mintick)
- Short TP = Entry - (TP_Ticks × syminfo.mintick)
**Channel Percentage Mode**:
- Long TP = Entry + (ChannelRange × TP_Percent)
- Short TP = Entry - (ChannelRange × TP_Percent)
Default 50% targets the channel midline, a natural mean reversion target. Larger percentages aim for opposite channel edge.
### Stop Loss Placement:
Stop losses are placed just outside the channel boundary by a user-defined tick offset:
- Long SL = ChannelBottom - (SL_Offset_Ticks × syminfo.mintick)
- Short SL = ChannelTop + (SL_Offset_Ticks × syminfo.mintick)
This logic assumes channel breaks invalidate the mean reversion thesis. If price breaks through, the range is no longer valid and position exits.
### Trade Execution Logic:
When entry conditions are met (price in zone, cooldown satisfied, ATR filter passed, no existing position):
1. Calculate entry price at zone boundary
2. Calculate TP and SL based on selected method
3. Execute strategy.entry() with calculated position size
4. Place strategy.exit() with TP limit and SL stop orders
5. Update info table with active trade details
The strategy enforces one position at a time by checking strategy.position_size == 0 before entry.
### Channel Breakout Management:
Channels are removed when price closes more than 10 ticks outside boundaries. This tolerance prevents premature channel deletion from minor breaks or wicks, allowing the mean reversion setup to persist through small boundary violations.
### Position Sizing System:
Three methods calculate position size:
**Fixed Contracts**:
- Uses exact contract quantity specified in settings
- Best for futures traders (e.g., "trade 2 NQ contracts")
**Percentage of Equity**:
- position_size = (strategy.equity × equity_pct / 100) / close
- Dynamically scales with account growth
**Cash Amount**:
- position_size = cash_amount / close
- Maintains consistent dollar exposure regardless of price
## INPUT PARAMETERS:
### Position Sizing:
- **Position Size Type**: Choose Fixed Contracts, % of Equity, or Cash Amount
- **Number of Contracts**: Fixed quantity per trade (1-1000)
- **% of Equity**: Percentage of account to allocate (1-100%)
- **Cash Amount**: Dollar value per position ($100+)
### Channel Settings:
- **Nested Channels**: Allow multiple overlapping channels vs single channel
- **Normalization Length**: Lookback for high/low calculation (1-500, default 100)
- **Box Detection Length**: Period for volatility detection (1-100, default 14)
### Scalping Settings:
- **Enable Long Scalps**: Toggle long entries on/off
- **Enable Short Scalps**: Toggle short entries on/off
- **Entry Zone % from Edge**: Size of entry zone (5-50%, default 20%)
- **SL Offset (Ticks)**: Distance beyond channel for stop (1+, default 5)
- **Cooldown Period (Bars)**: Minimum spacing between signals (0 = no cooldown)
### ATR Filter:
- **Enable ATR Filter**: Toggle volatility filter on/off
- **ATR Timeframe**: Source timeframe for ATR (1, 5, 15, 60 min, etc.)
- **ATR Length**: Smoothing period (1-100, default 14)
- **Min ATR Value**: Threshold for trade enablement (0.1+, default 10.0)
### Take Profit Settings:
- **TP Method**: Choose Fixed Points or % of Channel
- **TP Fixed (Ticks)**: Static distance in ticks (1+, default 30)
- **TP % of Channel**: Dynamic target as channel percentage (10-100%, default 50%)
### Appearance:
- **Show Entry Zones**: Toggle zone labels on channels
- **Show Info Table**: Display real-time strategy status
- **Table Position**: Corner placement (Top Left/Right, Bottom Left/Right)
- **Color Settings**: Customize long/short/TP/SL colors
## VISUAL INDICATORS:
- **Channel boxes** with semi-transparent fill showing consolidation zones
- **Colored entry zones** labeled "LONG ZONE ▲" and "SHORT ZONE ▼"
- **Entry signal arrows** below/above bars marking long/short entries
- **Active TP/SL lines** with emoji labels (⊕ Entry, 🎯 TP, 🛑 SL)
- **Info table** showing position status, channel state, last signal, entry/TP/SL prices, and ATR status
## HOW TO USE:
### For 1-3 Minute Scalping (NQ/ES):
- ATR Timeframe: "1" (1-minute)
- ATR Min Value: 10.0 (for NQ), adjust per instrument
- Entry Zone %: 20-25%
- TP Method: Fixed Points, 20-40 ticks
- SL Offset: 5-10 ticks
- Cooldown: 2-3 bars
- Position Size: 1-2 contracts
### For 5-15 Minute Day Trading:
- ATR Timeframe: "5" or match chart
- ATR Min Value: Adjust to instrument (test 8-15 for NQ)
- Entry Zone %: 20-30%
- TP Method: % of Channel, 40-60%
- SL Offset: 5-10 ticks
- Cooldown: 3-5 bars
- Position Size: Fixed contracts or 5-10% equity
### For 30-60 Minute Swing Scalping:
- ATR Timeframe: "15" or "30"
- ATR Min Value: Lower threshold for broader market
- Entry Zone %: 25-35%
- TP Method: % of Channel, 50-70%
- SL Offset: 10-15 ticks
- Cooldown: 5+ bars or disable
- Position Size: % of equity recommended
## BACKTEST CONSIDERATIONS:
- Strategy performs best in ranging, mean-reverting markets
- Strong trending markets produce more stop losses as price breaks channels
- ATR filter significantly reduces trade count but improves quality during low volatility
- Cooldown period trades signal quantity for signal quality
- Commission and slippage materially impact sub-5-minute timeframe performance
- Shorter timeframes require tighter entry zones (15-20%) to catch quick reversions
- % of Channel TP adapts better to varying channel sizes than fixed points
- Fixed contract sizing recommended for consistent risk per trade in futures
**Backtesting Parameters Used**: This strategy was developed and tested using realistic commission and slippage values to provide accurate performance expectations. Recommended settings: Commission of $1.40 per side (typical for NQ futures through discount brokers), slippage of 2 ticks to account for execution delays on fast-moving scalp entries. These values reflect real-world trading costs that active scalpers will encounter. Backtest results without proper cost simulation will significantly overstate profitability.
## COMPATIBLE MARKETS:
Works on any instrument with price data including stock indices (NQ, ES, YM, RTY), individual stocks, forex pairs (EUR/USD, GBP/USD), cryptocurrency (BTC, ETH), and commodities. Volume-based features require data feed with volume information but are optional for core functionality.
## KNOWN LIMITATIONS:
- Immediate touch entry can fire multiple times in choppy zones without adequate cooldown
- Channel deletion at 10-tick breaks may be too aggressive or lenient depending on instrument tick size
- ATR filter from lower timeframes requires higher-tier TradingView subscription (request.security limitation)
- Mean reversion logic fails in strong breakout scenarios leading to stop loss hits
- Position sizing via % of equity or cash amount calculates based on close price, may differ from actual fill price
- No partial closing capability - full position exits at TP or SL only
- Strategy does not account for gap openings or overnight holds
## RISK DISCLOSURE:
Trading involves substantial risk of loss. Past performance does not guarantee future results. This strategy is for educational purposes and backtesting only. Mean reversion strategies can experience extended drawdowns during trending markets. Stop losses may not fill at intended levels during extreme volatility or gaps. Thoroughly test on historical data and paper trade before risking real capital. Use appropriate position sizing and never risk more than you can afford to lose. Consider consulting a licensed financial advisor before making trading decisions. Automated trading systems can malfunction - monitor all live positions actively.
## ACKNOWLEDGMENT & CREDITS:
This strategy is built upon the channel detection methodology created by **AlgoAlpha** in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns. The core channel formation logic using normalized price standard deviation is AlgoAlpha's original contribution to the TradingView community.
Enhancements to the original concept include: mean reversion entry logic (vs breakout), immediate touch-based signals, multi-timeframe ATR volatility filtering, flexible position sizing (fixed/percentage/cash), cooldown period filtering, dual TP methods (fixed points vs channel percentage), automated strategy execution with exit management, and real-time position monitoring table.
AMHA + 4 EMAs + EMA50/200 Counter + Avg10CrossesDescription:
This script combines two types of Heikin-Ashi visualization with multiple Exponential Moving Averages (EMAs) and a counting function for EMA50/200 crossovers. The goal is to make trends more visible, measure recurring market cycles, and provide statistical context without generating trading signals.
Logic in Detail:
Adaptive Median Heikin-Ashi (AMHA):
Instead of the classic Heikin-Ashi calculation, this method uses the median of Open, High, Low, and Close. The result smooths out price movements, emphasizes trend direction, and reduces market noise.
Standard Heikin-Ashi Overlay:
Classic HA candles are also drawn in the background for comparison and transparency. Both HA types can be shifted below the chart’s price action using a customizable Offset (Ticks) parameter.
EMA Structure:
Five exponential moving averages (21, 50, 100, 200, 500) are included to highlight different trend horizons. EMA50 and EMA200 are emphasized, as their crossovers are widely monitored as potential trend signals. EMA21 and EMA100 serve as additional structure layers, while EMA500 represents the long-term trend.
EMA50/200 Counter:
The script counts how many bars have passed since the last EMA50/200 crossover. This makes it easy to see the age of the current trend phase. A colored label above the chart displays the current counter.
Average of the Last 10 Crossovers (Avg10Crosses):
The script stores the last 10 completed count phases and calculates their average length. This provides historical context and allows traders to compare the current cycle against typical past behavior.
Benefits for Analysis:
Clearer trend visualization through adaptive Heikin-Ashi calculation.
Multi-EMA setup for quick structural assessment.
Objective measurement of trend phase duration.
Statistical insight from the average cycle length of past EMA50/200 crosses.
Flexible visualization through adjustable offset positioning below the price chart.
Usage:
Add the indicator to your chart.
For a clean look, you may switch your chart type to “Line” or hide standard candlesticks.
Interpret visual signals:
White candles = bullish phases
Orange candles = bearish phases
EMAs = structural trend filters (e.g., EMA200 as a long-term boundary)
The counter label shows the current number of bars since the last cross, while Avg10 represents the historical mean.
Special Feature:
This script is not a trading system. It does not provide buy/sell recommendations. Instead, it serves as a visual and statistical tool for market structure analysis. The unique combination of Adaptive Median Heikin-Ashi, multi-EMA framework, and EMA50/200 crossover statistics makes it especially useful for trend-followers and swing traders who want to add cycle-length analysis to their toolkit.
BOCS AdaptiveBOCS Adaptive Strategy - Automated Volatility Breakout System
WHAT THIS STRATEGY DOES:
This is an automated trading strategy that detects consolidation patterns through volatility analysis and executes trades when price breaks out of these channels. Take-profit and stop-loss levels are calculated dynamically using Average True Range (ATR) to adapt to current market volatility. The strategy closes positions partially at the first profit target and exits the remainder at the second target or stop loss.
TECHNICAL METHODOLOGY:
Price Normalization Process:
The strategy begins by normalizing price to create a consistent measurement scale. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). The current close price is then normalized using the formula: (close - lowest_low) / (highest_high - lowest_low). This produces values between 0 and 1, allowing volatility analysis to work consistently across different instruments and price levels.
Volatility Detection:
A 14-period standard deviation is applied to the normalized price series. Standard deviation measures how much prices deviate from their average - higher values indicate volatility expansion, lower values indicate consolidation. The strategy uses ta.highestbars() and ta.lowestbars() functions to track when volatility reaches peaks and troughs over the detection length period (default 14 bars).
Channel Formation Logic:
When volatility crosses from a high level to a low level, this signals the beginning of a consolidation phase. The strategy records this moment using ta.crossover(upper, lower) and begins tracking the highest and lowest prices during the consolidation. These become the channel boundaries. The duration between the crossover and current bar must exceed 10 bars minimum to avoid false channels from brief volatility spikes. Channels are drawn using box objects with the recorded high/low boundaries.
Breakout Signal Generation:
Two detection modes are available:
Strong Closes Mode (default): Breakout occurs when the candle body midpoint math.avg(close, open) exceeds the channel boundary. This filters out wick-only breaks.
Any Touch Mode: Breakout occurs when the close price exceeds the boundary.
When price closes above the upper channel boundary, a bullish breakout signal generates. When price closes below the lower boundary, a bearish breakout signal generates. The channel is then removed from the chart.
ATR-Based Risk Management:
The strategy uses request.security() to fetch ATR values from a specified timeframe, which can differ from the chart timeframe. For example, on a 5-minute chart, you can use 1-minute ATR for more responsive calculations. The ATR is calculated using ta.atr(length) with a user-defined period (default 14).
Exit levels are calculated at the moment of breakout:
Long Entry Price = Upper channel boundary
Long TP1 = Entry + (ATR × TP1 Multiplier)
Long TP2 = Entry + (ATR × TP2 Multiplier)
Long SL = Entry - (ATR × SL Multiplier)
For short trades, the calculation inverts:
Short Entry Price = Lower channel boundary
Short TP1 = Entry - (ATR × TP1 Multiplier)
Short TP2 = Entry - (ATR × TP2 Multiplier)
Short SL = Entry + (ATR × SL Multiplier)
Trade Execution Logic:
When a breakout occurs, the strategy checks if trading hours filter is satisfied (if enabled) and if position size equals zero (no existing position). If volume confirmation is enabled, it also verifies that current volume exceeds 1.2 times the 20-period simple moving average.
If all conditions are met:
strategy.entry() opens a position using the user-defined number of contracts
strategy.exit() immediately places a stop loss order
The code monitors price against TP1 and TP2 levels on each bar
When price reaches TP1, strategy.close() closes the specified number of contracts (e.g., if you enter with 3 contracts and set TP1 close to 1, it closes 1 contract). When price reaches TP2, it closes all remaining contracts. If stop loss is hit first, the entire position exits via the strategy.exit() order.
Volume Analysis System:
The strategy uses ta.requestUpAndDownVolume(timeframe) to fetch up volume, down volume, and volume delta from a specified timeframe. Three display modes are available:
Volume Mode: Shows total volume as bars scaled relative to the 20-period average
Comparison Mode: Shows up volume and down volume as separate bars above/below the channel midline
Delta Mode: Shows net volume delta (up volume - down volume) as bars, positive values above midline, negative below
The volume confirmation logic compares breakout bar volume to the 20-period SMA. If volume ÷ average > 1.2, the breakout is classified as "confirmed." When volume confirmation is enabled in settings, only confirmed breakouts generate trades.
INPUT PARAMETERS:
Strategy Settings:
Number of Contracts: Fixed quantity to trade per signal (1-1000)
Require Volume Confirmation: Toggle to only trade signals with volume >120% of average
TP1 Close Contracts: Exact number of contracts to close at first target (1-1000)
Use Trading Hours Filter: Toggle to restrict trading to specified session
Trading Hours: Session input in HHMM-HHMM format (e.g., "0930-1600")
Main Settings:
Normalization Length: Lookback bars for high/low calculation (1-500, default 100)
Box Detection Length: Period for volatility peak/trough detection (1-100, default 14)
Strong Closes Only: Toggle between body midpoint vs close price for breakout detection
Nested Channels: Allow multiple overlapping channels vs single channel at a time
ATR TP/SL Settings:
ATR Timeframe: Source timeframe for ATR calculation (1, 5, 15, 60, etc.)
ATR Length: Smoothing period for ATR (1-100, default 14)
Take Profit 1 Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 2.0)
Take Profit 2 Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 3.0)
Stop Loss Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 1.0)
Enable Take Profit 2: Toggle second profit target on/off
VISUAL INDICATORS:
Channel boxes with semi-transparent fill showing consolidation zones
Green/red colored zones at channel boundaries indicating breakout areas
Volume bars displayed within channels using selected mode
TP/SL lines with labels showing both price level and distance in points
Entry signals marked with up/down triangles at breakout price
Strategy status table showing position, contracts, P&L, ATR values, and volume confirmation status
HOW TO USE:
For 2-Minute Scalping:
Set ATR Timeframe to "1" (1-minute), ATR Length to 12, TP1 Multiplier to 2.0, TP2 Multiplier to 3.0, SL Multiplier to 1.5. Enable volume confirmation and strong closes only. Use trading hours filter to avoid low-volume periods.
For 5-15 Minute Day Trading:
Set ATR Timeframe to match chart or use 5-minute, ATR Length to 14, TP1 Multiplier to 2.0, TP2 Multiplier to 3.5, SL Multiplier to 1.2. Volume confirmation recommended but optional.
For Hourly+ Swing Trading:
Set ATR Timeframe to 15-30 minute, ATR Length to 14-21, TP1 Multiplier to 2.5, TP2 Multiplier to 4.0, SL Multiplier to 1.5. Volume confirmation optional, nested channels can be enabled for multiple setups.
BACKTEST CONSIDERATIONS:
Strategy performs best during trending or volatility expansion phases
Consolidation-heavy or choppy markets produce more false signals
Shorter timeframes require wider stop loss multipliers due to noise
Commission and slippage significantly impact performance on sub-5-minute charts
Volume confirmation generally improves win rate but reduces trade frequency
ATR multipliers should be optimized for specific instrument characteristics
COMPATIBLE MARKETS:
Works on any instrument with price and volume data including forex pairs, stock indices, individual stocks, cryptocurrency, commodities, and futures contracts. Requires TradingView data feed that includes volume for volume confirmation features to function.
KNOWN LIMITATIONS:
Stop losses execute via strategy.exit() and may not fill at exact levels during gaps or extreme volatility
request.security() on lower timeframes requires higher-tier TradingView subscription
False breakouts inherent to breakout strategies cannot be completely eliminated
Performance varies significantly based on market regime (trending vs ranging)
Partial closing logic requires sufficient position size relative to TP1 close contracts setting
RISK DISCLOSURE:
Trading involves substantial risk of loss. Past performance of this or any strategy does not guarantee future results. This strategy is provided for educational purposes and automated backtesting. Thoroughly test on historical data and paper trade before risking real capital. Market conditions change and strategies that worked historically may fail in the future. Use appropriate position sizing and never risk more than you can afford to lose. Consider consulting a licensed financial advisor before making trading decisions.
ACKNOWLEDGMENT & CREDITS:
This strategy is built upon the channel detection methodology created by AlgoAlpha in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns and sharing this innovative technique with the TradingView community. The enhancements added to the original concept include automated trade execution, multi-timeframe ATR-based risk management, partial position closing by contract count, volume confirmation filtering, and real-time position monitoring.
Initial Balance SMC-V3
Initial Balance SMC-V3 – An Advanced Mean Reversion Indicator for Index Markets
The Initial Balance SMC-V3 indicator is the result of continuous refinement in mean reversion trading, with a specific focus on index markets (such as DAX, NASDAQ, S&P 500, etc.). Designed for high-liquidity environments with controlled volatility, it excels at precisely identifying value zones and statistical reversal points within market structure.
🔁 Mean Reversion at Its Core
At the heart of this indicator lies a robust mean reversion logic: rather than chasing extreme breakouts, it seeks returns toward equilibrium levels after impulsive moves. This makes it especially effective in ranging markets or corrective phases within broader trends—situations where many traders get caught in false breakouts.
🎯 Signals Require Breakout + Confirmation
Signals are never generated impulsively. Instead, they require a clear sequence of confirmations:
Break of a key level (e.g., Initial Balance high/low or an SMC zone);
Price re-entry into the range accompanied by a crossover of customizable moving averages (SMA, EMA, HULL, TEMA, etc.);
RSI filter to avoid entries in overbought/oversold extremes;
Volatility filter (ATR) to skip low-volatility, choppy conditions.
This multi-layered approach drastically reduces false signals and significantly improves trade quality.
📊 Built-in Multi-Timeframe Analysis
The indicator features native multi-timeframe logic:
H1 / 15-minute charts: for structural analysis and identification of Supply & Demand zones (SMC);
M1 / M5 charts: for precise trade execution, with targeted entries and dynamic risk management.
SMC zones are calculated on higher timeframes (e.g., 4H) to ensure structural reliability, while actual trade signals trigger on lower timeframes for maximum precision.
⚙️ Advanced Customization
Full choice of moving average type (SMA, EMA, WMA, RMA, VWMA, HULL, TEMA, ZLEMA, etc.);
Revenge Trading logic: after a stop loss is hit without reaching the 1:1 breakeven level, the indicator automatically prepares for a counter-trade;
Dynamic ATR-based stop loss with customizable multiplier;
Session filters to trade only during optimal liquidity windows (e.g., European session).
🧠 Who Is It For?
This indicator is ideal for traders who:
Primarily trade indices;
Prefer mean reversion strategies over pure trend-following;
Seek a disciplined, rule-based system with multiple confluence filters;
Use a multi-timeframe approach to separate analysis from execution.
In short: Initial Balance SMC-V3 is more than just an indicator—it’s a complete trading framework for mean reversion on index markets, where every signal emerges from a confluence of statistical, structural, and temporal factors.
Happy trading! 📈
Institutional Levels (CNN) - [PhenLabs]📊Institutional Levels (Convolutional Neural Network-inspired)
Version : PineScript™v6
📌Description
The CNN-IL Institutional Levels indicator represents a breakthrough in automated zone detection technology, combining convolutional neural network principles with advanced statistical modeling. This sophisticated tool identifies high-probability institutional trading zones by analyzing pivot patterns, volume dynamics, and price behavior using machine learning algorithms.
The indicator employs a proprietary 9-factor logistic regression model that calculates real-time reaction probabilities for each detected zone. By incorporating CNN-inspired filtering techniques and dynamic zone management, it provides traders with unprecedented accuracy in identifying where institutional money is likely to react to price action.
🚀Points of Innovation
● CNN-Inspired Pivot Analysis - Advanced binning system using convolutional neural network principles for superior pattern recognition
● Real-Time Probability Engine - Live reaction probability calculations using 9-factor logistic regression model
● Dynamic Zone Intelligence - Automatic zone merging using Intersection over Union (IoU) algorithms
● Volume-Weighted Scoring - Time-of-day volume Z-score analysis for enhanced zone strength assessment
● Adaptive Decay System - Intelligent zone lifecycle management based on touch frequency and recency
● Multi-Filter Architecture - Optional gradient, smoothing, and Difference of Gaussians (DoG) convolution filters
🔧Core Components
● Pivot Detection Engine - Advanced pivot identification with configurable left/right bars and ATR-normalized strength calculations
● Neural Network Binning - Price level clustering using CNN-inspired algorithms with ATR-based bin sizing
● Logistic Regression Model - 9-factor probability calculation including distance, width, volume, VWAP deviation, and trend analysis
● Zone Management System - Intelligent creation, merging, and decay algorithms for optimal zone lifecycle control
● Visualization Layer - Dynamic line drawing with opacity-based scoring and optional zone fills
🔥Key Features
● High-Probability Zone Detection - Automatically identifies institutional levels with reaction probabilities above configurable thresholds
● Real-Time Probability Scoring - Live calculation of zone reaction likelihood using advanced statistical modeling
● Session-Aware Analysis - Optional filtering to specific trading sessions for enhanced accuracy during active market hours
● Customizable Parameters - Full control over lookback periods, zone sensitivity, merge thresholds, and probability models
● Performance Optimized - Efficient processing with controlled update frequencies and pivot processing limits
● Non-Repainting Mode - Strict mode available for backtesting accuracy and live trading reliability
🎨Visualization
● Dynamic Zone Lines - Color-coded support and resistance levels with opacity reflecting zone strength and confidence scores
● Probability Labels - Real-time display of reaction probabilities, touch counts, and historical hit rates for active zones
● Zone Fills - Optional semi-transparent zone highlighting for enhanced visual clarity and immediate pattern recognition
● Adaptive Styling - Automatic color and opacity adjustments based on zone scoring and statistical significance
📖Usage Guidelines
● Lookback Bars - Default 500, Range 100-1000, Controls the historical data window for pivot analysis and zone calculation
● Pivot Left/Right - Default 3, Range 1-10, Defines the pivot detection sensitivity and confirmation requirements
● Bin Size ATR units - Default 0.25, Range 0.1-2.0, Controls price level clustering granularity for zone creation
● Base Zone Half-Width ATR units - Default 0.25, Range 0.1-1.0, Sets the minimum zone width in ATR units for institutional level boundaries
● Zone Merge IoU Threshold - Default 0.5, Range 0.1-0.9, Intersection over Union threshold for automatic zone merging algorithms
● Max Active Zones - Default 5, Range 3-20, Maximum number of zones displayed simultaneously to prevent chart clutter
● Probability Threshold for Labels - Default 0.6, Range 0.3-0.9, Minimum reaction probability required for zone label display and alerts
● Distance Weight w1 - Controls influence of price distance from zone center on reaction probability
● Width Weight w2 - Adjusts impact of zone width on probability calculations
● Volume Weight w3 - Modifies volume Z-score influence on zone strength assessment
● VWAP Weight w4 - Controls VWAP deviation impact on institutional level significance
● Touch Count Weight w5 - Adjusts influence of historical zone interactions on probability scoring
● Hit Rate Weight w6 - Controls prior success rate impact on future reaction likelihood predictions
● Wick Penetration Weight w7 - Modifies wick penetration analysis influence on probability calculations
● Trend Weight w8 - Adjusts trend context impact using ADX analysis for directional bias assessment
✅Best Use Cases
● Swing Trading Entries - Enter positions at high-probability institutional zones with 60%+ reaction scores
● Scalping Opportunities - Quick entries and exits around frequently tested institutional levels
● Risk Management - Use zones as dynamic stop-loss and take-profit levels based on institutional behavior
● Market Structure Analysis - Identify key institutional levels that define current market structure and sentiment
● Confluence Trading - Combine with other technical indicators for high-probability trade setups
● Session-Based Strategies - Focus analysis during high-volume sessions for maximum effectiveness
⚠️Limitations
● Historical Pattern Dependency - Algorithm effectiveness relies on historical patterns that may not repeat in changing market conditions
● Computational Intensity - Complex calculations may impact chart performance on lower-end devices or with multiple indicators
● Probability Estimates - Reaction probabilities are statistical estimates and do not guarantee actual market outcomes
● Session Sensitivity - Performance may vary significantly between different market sessions and volatility regimes
● Parameter Sensitivity - Results can be highly dependent on input parameters requiring optimization for different instruments
💡What Makes This Unique
● CNN Architecture - First indicator to apply convolutional neural network principles to institutional-level detection
● Real-Time ML Scoring - Live machine learning probability calculations for each zone interaction
● Advanced Zone Management - Sophisticated algorithms for zone lifecycle management and automatic optimization
● Statistical Rigor - Comprehensive 9-factor logistic regression model with extensive backtesting validation
● Performance Optimization - Efficient processing algorithms designed for real-time trading applications
🔬How It Works
● Multi-timeframe pivot identification - Uses configurable sensitivity parameters for advanced pivot detection
● ATR-normalized strength calculations - Standardizes pivot significance across different volatility regimes
● Volume Z-score integration - Enhanced pivot weighting based on time-of-day volume patterns
● Price level clustering - Neural network binning algorithms with ATR-based sizing for zone creation
● Recency decay applications - Weights recent pivots more heavily than historical data for relevance
● Statistical filtering - Eliminates low-significance price levels and reduces market noise
● Dynamic zone generation - Creates zones from statistically significant pivot clusters with minimum support thresholds
● IoU-based merging algorithms - Combines overlapping zones while maintaining accuracy using Intersection over Union
● Adaptive decay systems - Automatic removal of outdated or low-performing zones for optimal performance
● 9-factor logistic regression - Incorporates distance, width, volume, VWAP, touch history, and trend analysis
● Real-time scoring updates - Zone interaction calculations with configurable threshold filtering
● Optional CNN filters - Gradient detection, smoothing, and Difference of Gaussians processing for enhanced accuracy
💡Note
This indicator represents advanced quantitative analysis and should be used by traders familiar with statistical modeling concepts. The probability scores are mathematical estimates based on historical patterns and should be combined with proper risk management and additional technical analysis for optimal trading decisions.
Asian Stock Open (00:00 UTC Daily)Simple TSE daily open indicator, 500 line history, to help prepare for potential weekly open volatility from Asia trading
FlowSpike ES — BB • RSI • VWAP + AVWAP + News MuteThis indicator is purpose-built for E-mini S&P 500 (ES) futures traders, combining volatility bands, momentum filters, and session-anchored levels into a streamlined tool for intraday execution.
Key Features:
• ES-Tuned Presets
Automatically optimized settings for scalping (1–2m), daytrading (5m), and swing trading (15–60m) timeframes.
• Bollinger Band & RSI Signals
Entry signals trigger only at statistically significant extremes, with RSI filters to reduce false moves.
• VWAP & Anchored VWAPs
Session VWAP plus anchored VWAPs (RTH open, weekly, monthly, and custom) provide high-confidence reference levels used by professional order-flow traders.
• Volatility Filter (ATR in ticks)
Ensures signals are only shown when the ES is moving enough to offer tradable edges.
• News-Time Mute
Suppresses signals around scheduled economic releases (customizable windows in ET), helping traders avoid whipsaw conditions.
• Clean Alerts
Long/short alerts are generated only when all conditions align, with optional bar-close confirmation.
Why It’s Tailored for ES Futures:
• Designed around ES tick size (0.25) and volatility structure.
• Session settings respect RTH hours (09:30–16:00 ET), the period where most liquidity and institutional flows concentrate.
• ATR thresholds and RSI bands are pre-tuned for ES market behavior, reducing the need for manual optimization.
⸻
This is not a generic indicator—it’s a futures-focused tool created to align with the way ES trades day after day. Whether you scalp the open, manage intraday swings, or align to weekly/monthly anchored flows, FlowSpike ES gives you a clear, rules-based signal framework.
$ - HTF Sweeps & PO3HTF Sweeps & PO3 Indicator
The HTF Sweeps & PO3 indicator is a powerful tool designed for traders to visualise higher timeframe (HTF) candles, identify liquidity sweeps, and track key price levels on a lower timeframe (LTF) chart. Built for TradingView using Pine Script v6, it overlays HTF candle data and highlights significant price movements, such as sweeps of previous highs or lows, to help traders identify potential liquidity sweep and reversal points. The indicator is highly customisable, offering a range of visual and alert options to suit various trading strategies.
Features
Higher Timeframe (HTF) Candle Visualisation:
- Displays up to three user-defined HTF candles (e.g., 15m, 1H, 4H) overlaid on the LTF chart.
- Customisable candle appearance with adjustable size (Tiny to Huge), offset, spacing, and colours for bullish/bearish candles and wicks.
- Option to show timeframe labels above or below HTF candles with configurable size and position.
Liquidity Sweep Detection:
- Identifies bullish and bearish sweeps when price moves beyond the high or low of a previous HTF candle and meets specific conditions.
- Displays sweeps on both LTF and HTF with customisable line styles (Solid, Dashed, Dotted), widths, and colours.
- Option to show only the most recent sweep per candle to reduce chart clutter.
Invalidated Sweep Tracking:
- Detects and visualises invalidated sweeps (when price moves past a sweep level in the opposite direction).
- Configurable display for invalidated sweeps on LTF and HTF with distinct line styles and colours.
Previous High/Low Lines:
- Plots horizontal lines at the high and low of the previous HTF candle, extending on both LTF and HTF.
- Customisable line style, width, and color for easy identification of key levels.
- Real-Time Sweep Detection:
-Optional real-time sweep visualisation for active candles, enabling traders to monitor developing price action.
Alert System:
- Triggers alerts for sweep formation (when a new sweep is detected).
- Triggers alerts for sweep invalidation (when a sweep is no longer valid).
- Alerts include details such as timeframe, ticker, and price level for precise notifications.
Performance Optimisation:
- Efficiently manages resources with configurable limits for lines, labels, boxes, and bars (up to 500 each).
- Cleans up outdated visual elements to maintain chart clarity.
Flexible Configuration:
- Supports multiple timeframes for HTF candles with user-defined settings for visibility and number of candles displayed (1–60).
- Toggle visibility for HTF candles, sweeps, invalidated sweeps, and high/low lines independently for LTF and HTF.
This indicator is ideal for traders focusing on liquidity hunting, order block analysis, or price action strategies, providing clear visual cues and alerts to enhance decision-making.
Candlestick Themes NYSE Pro [GPXalgo]The Critical Role of Color in Trading Performance
Professional trading environments demand visual systems that support rapid decision-making while
minimizing cognitive load and visual fatigue. The NYSE trading desk color schemes have evolved
through decades of refinement, incorporating feedback from over 10,000 active traders and
quantitative performance analysis.
Key Design Principles
1. Contrast Optimization
Minimum contrast ratio of 7:1 for critical data elements against dark backgrounds (#0A0A0A to
#1C1C1C).
2. Semantic Consistency
Universal color language across all trading platforms and instruments.
3. Fatigue Mitigation
Spectral distribution optimized for extended viewing periods without degradation in pattern
recognition.
4. Information Hierarchy
Clear visual prioritization of price action, volume, and technical indicators.
Scientific Foundation
Visual Perception in Trading Contexts
Neurological Processing
The human visual cortex processes color information 60,000 times faster than text. In trading
contexts, this translates to:
• 0.13 seconds average recognition time for color-coded signals
• 0.45 seconds for text-based information
• 72% improvement in pattern recognition with optimized color schemes
Circadian Rhythm Consideration
Trading desk colors are calibrated to minimize melatonin suppression during extended sessions:
• Blue light emission reduced by 65% compared to standard displays
• Warm-spectrum alternatives for overnight sessions
• Adaptive brightness curves aligned with natural circadian cycles
Eye Strain Metrics
Laboratory studies (n=500 traders, 6-month period) demonstrate:
• 43% reduction in reported eye strain
• 31% decrease in headache frequency• 28% improvement in focus duration
• 17% increase in profitable trade execution
Implementation Standards
Display Calibration Requirements
Monitor Specifications
Minimum 1000:1 contrast ratio
sRGB coverage ≥ 99%
Delta E < 2.0 color accuracy
Brightness: 120-150 cd/m² (dark environment)
Color temperature: 5800K ± 200K
Multi-Monitor Consistency
• Maximum ΔE variance between displays: 1.5
• Synchronized brightness across array
• Uniform color profiles (ICC v4)
Accessibility Compliance
WCAG 2.1 Level AA Standards
Normal text: 4.5:1 contrast minimum
Large text: 3:1 contrast minimum
Interactive elements: 3:1 contrast minimum
Focus indicators: 3:1 contrast minimum
Colorblind Accommodation All critical information maintains distinguishability under:
• Protanopia (red-blind)
• Deuteranopia (green-blind)
• Tritanopia (blue-blind)
Mongoose Global Conflict Risk Index v1Overview
The Mongoose Global Conflict Risk Index v1 is a multi-asset composite indicator designed to track the early pricing of geopolitical stress and potential conflict risk across global markets. By combining signals from safe havens, volatility indices, energy markets, and emerging market equities, the index provides a normalized 0–10 score with clear bias classifications (Neutral, Caution, Elevated, High, Shock).
This tool is not predictive of headlines but captures when markets are clustering around conflict-sensitive assets before events are widely recognized.
Methodology
The indicator calculates rolling rate-of-change z-scores for eight conflict-sensitive assets:
Gold (XAUUSD) – classic safe haven
US Dollar Index (DXY) – global reserve currency flows
VIX (Equity Volatility) – S&P 500 implied volatility
OVX (Crude Oil Volatility Index) – energy stress gauge
Crude Oil (CL1!) – WTI front contract
Natural Gas (NG1!) – energy security proxy, especially Europe
EEM (Emerging Markets ETF) – global risk capital flight
FXI (China ETF) – Asia/China proxy risk
Rules:
Safe havens and vol indices trigger when z-score > threshold.
Energy triggers when z-score > threshold.
Risk assets trigger when z-score < –threshold.
Each trigger is assigned a weight, summed, normalized, and scaled 0–10.
Bias classification:
0–2: Neutral
2–4: Caution
4–6: Elevated
6–8: High
8–10: Conflict Risk-On
How to Use
Timeframes:
Daily (1D) for strategic signals and early warnings.
4H for event shocks (missiles, sanctions, sudden escalations).
Weekly (1W) for sustained trends and macro build-ups.
What to Look For:
A single trigger (for example, Gold ON) may be noise.
A cluster of 2–3 triggers across Gold, USD, VIX, and Energy often marks early stress pricing.
Elevated readings (>4) = caution; High (>6) = rotation into havens; Shock (>8) = market conviction of conflict risk.
Practical Application:
Monitor as a heatmap of global stress.
Combine with fundamental or headline tracking.
Use alert conditions at ≥4, ≥6, ≥8 for systematic monitoring.
Notes
This indicator is for informational and educational purposes only.
It is not financial advice and should be used in conjunction with other analysis methods.
US Net Liquidity + M2 / US Debt (FRED)US Net Liquidity + M2 / US Debt
🧩 What this chart shows
This indicator plots the ratio of US Net Liquidity + M2 Money Supply divided by Total Public Debt.
US Net Liquidity is defined here as the Federal Reserve Balance Sheet (WALCL) minus the Treasury General Account (TGA) and the Overnight Reverse Repo facility (ON RRP).
M2 Money Supply represents the broad pool of liquid money circulating in the economy.
US Debt uses the Federal Government’s total outstanding debt.
By combining net liquidity with M2, then dividing by total debt, this chart provides a structural view of how much monetary “fuel” is in the system relative to the size of the federal debt load.
🧮 Formula
Ratio
=
(
Fed Balance Sheet
−
(
TGA
+
ON RRP
)
)
+
M2
Total Public Debt
Ratio=
Total Public Debt
(Fed Balance Sheet−(TGA+ON RRP))+M2
An optional normalization feature scales the ratio to start at 100 on the first valid bar, making long-term trends easier to compare.
🔎 Why it matters
Liquidity vs. Debt Growth: The numerator (Net Liquidity + M2) captures the monetary resources available to markets, while the denominator (Debt) reflects the expanding obligation of the federal government.
Market Signal: Historically, shifts in net liquidity and money supply relative to debt have coincided with major turning points in risk assets like equities and Bitcoin.
Context: A rising ratio may suggest that liquidity conditions are improving relative to debt expansion, which can be supportive for risk assets. Conversely, a falling ratio may highlight tightening conditions or debt outpacing liquidity growth.
⚙️ How to use it
Overlay this chart against S&P 500, Bitcoin, or gold to analyze correlations with asset performance.
Watch for trend inflections—does the ratio bottom before equities rally, or peak before risk-off periods?
Use normalization for long historical comparisons, or raw values to see the absolute ratio.
📊 Data sources
This indicator pulls from FRED (Federal Reserve Economic Data) tickers available in TradingView:
WALCL: Fed balance sheet
RRPONTSYD: Overnight Reverse Repo
WTREGEN: Treasury General Account
M2SL: M2 money stock
GFDEBTN: Total federal public debt
⚠️ Notes
Some FRED series are updated weekly, others monthly—set your chart timeframe accordingly.
If any ticker is unavailable in your plan, replace it with the equivalent FRED symbol provided in TradingView.
This indicator is intended for macro analysis, not short-term trading signals.
Volume Bubbles & Liquidity Heatmap [LuxAlgo]The Volume Bubbles & Liquidity Heatmap indicator highlights volume and liquidity clearly and precisely with its volume bubbles and liquidity heat map, allowing to identify key price areas.
Customize the bubbles with different time frames and different display modes: total volume, buy and sell volume, or delta volume.
🔶 USAGE
The primary objective of this tool is to offer traders a straightforward method for analyzing volume on any selected timeframe.
By default, the tool displays buy and sell volume bubbles for the daily timeframe over the last 2,000 bars. Traders should be aware of the difference between the timeframe of the chart and that of the bubbles.
The tool also displays a liquidity heat map to help traders identify price areas where liquidity accumulates or is lacking.
🔹 Volume Bubbles
The bubbles have three possible display modes:
Total Volume: Displays the total volume of trades per bubble.
Buy & Sell Volume: Each bubble is divided into buy and sell volume.
Delta Volume: Displays the difference between buy and sell volume.
Each bubble represents the trading volume for a given period. By default, the timeframe for each bubble is set to daily, meaning each bubble represents the trading volume for each day.
The size of each bubble is proportional to the volume traded; a larger bubble indicates greater volume, while a smaller bubble indicates lower volume.
The color of each bubble indicates the dominant volume: green for buy volume and red for sell volume.
One of the tool's main goals is to facilitate simple, clear, multi-timeframe volume analysis.
The previous chart shows Delta Volume bubbles with various chart and bubble timeframe configurations.
To correctly visualize the bubbles, traders must ensure there is a sufficient number of bars per bubble. This is achieved by using a lower chart timeframe and a higher bubble timeframe.
As can be seen in the image above, the greater the difference between the chart and bubble timeframes, the better the visualization.
🔹 Liquidity Heatmap
The other main element of the tool is the liquidity heatmap. By default, it divides the chart into 25 different price areas and displays the accumulated trading volume on each.
The image above shows a 4-hour BTC chart displaying only the liquidity heatmap. Traders should be aware of these key price areas and observe how the price behaves in them, looking for possible opportunities to engage with the market.
The main parameters for controlling the heatmap on the settings panel are Rows and Cell Minimum Size. Rows modifies the number of horizontal price areas displayed, while Cell Minimum Size modifies the minimum size of each liquidity cell in each row.
As can be seen in the above BTC hourly chart, the cell size is 24 at the top and 168 at the bottom. The cells are smaller on top and bigger on the bottom.
The color of each cell reflects the liquidity size with a gradient; this reflects the total volume traded within each cell. The default colors are:
Red: larger liquidity
Yellow: medium liquidity
Blue: lower liquidity
🔹 Using Both Tools Together
This indicator provides the means to identify directional bias and market timing.
The main idea is that if buyers are strong, prices are likely to increase, and if sellers are strong, prices are likely to decrease. This gives us a directional bias for opening long or short positions. Then, we combine our directional bias with price rejection or acceptance of key liquidity levels to determine the timing of opening or closing our positions.
Now, let's review some charts.
This first chart is BTC 1H with Delta Weekly Bubbles. Delta Bubbles measure the difference between buy and sell volume, so we can easily see which group is dominant (buyers or sellers) and how strong they are in any given week. This, along with the key price areas displayed by the Liquidity Heatmap, can help us navigate the markets.
We divided market behavior into seven groups, and each group has several bubbles, numbered from 1 to 17.
Bubbles 1, 2, and 3: After strong buyers market consolidates with positive delta, prices move up next week.
Bubbles 3, 4, and 5: Strength changes from buyers to sellers. Next week, prices go down.
Bubbles 6 and 7: The market trades at higher prices, but with negative delta. Next week, prices go down.
Bubbles 7, 8, and 9: Strength changes from sellers to buyers. Next weeks (9 and 10), prices go up.
Bubbles 10, 11, and 12: After strong buyers prices trade higher with a negative delta. Next weeks (12 and 13) prices go down.
Bubbles 12, 14, and 15: Strength changes from sellers to buyers; next week, prices increase.
Bubbles 15 and 16: The market trades higher with a very small positive delta; next week, prices go down.
Current bubble/week 17 is not yet finished. Right now, it is trading lower, but with a smaller negative delta than last week. This may signal that sellers are losing strength and that a potential reversal will follow, with prices trading higher.
This is the same BTC 1H chart, but with price rejections from key liquidity areas acting as strong price barriers.
When prices reach a key area with strong liquidity and are rejected, it signals a good time to take action.
By observing price behavior at certain key price levels, we can improve our timing for entering or exiting the markets.
🔶 DETAILS
🔹 Bubbles Display
From the settings panel, traders can configure the bubbles with four main parameters: Mode, Timeframe, Size%, and Shape.
The image above shows five-minute BTC charts with execution over the last 3,500 bars, different display modes, a daily timeframe, 100% size, and shape one.
The Size % parameter controls the overall size of the bubbles, while the Shape parameter controls their vertical growth.
Since the chart has two scales, one for time and one for price, traders can use the Shape parameter to make the bubbles round.
The chart above shows the same bubbles with different size and shape parameters.
You can also customize data labels and timeframe separators from the settings panel.
🔶 SETTINGS
Execute on last X bars: Number of bars for indicator execution
🔹 Bubbles
Display Bubbles: Enable/Disable volume bubbles.
Bubble Mode: Select from the following options: total volume, buy and sell volume, or the delta between buy and sell volume.
Bubble Timeframe: Select the timeframe for which the bubbles will be displayed.
Bubble Size %: Select the size of the bubbles as a percentage.
Bubble Shape: Select the shape of the bubbles. The larger the number, the more vertical the bubbles will be stretched.
🔹 Labels
Display Labels: Enable/Disable data labels, select size and location.
🔹 Separators
Display Separators: Enable/Disable timeframe separators and select color.
🔹 Liquidity Heatmap
Display Heatmap: Enable/Disable liquidity heatmap.
Heatmap Rows: select number of rows to be displayed.
Cell Minimum Size: Select the minimum size for each cell in each row.
Colors.
🔹 Style
Buy & Sell Volume Colors.
Weighted Sector ADD (sign-weighted)What it is
A true, cap-weighted advances/declines (ADD) proxy for the S&P 500 using sector ETFs. Each sector contributes +1 if it’s up on the bar, −1 if it’s down, 0 if flat. Those signals are then weighted by your sector weights (auto-normalized to 100%) and summed into a single breadth line. The result is a fast, low-noise read of how much of the S&P (by sector weight) is advancing vs. declining right now.
- Tracks participation, not price magnitude—perfect for spotting “broad vs. narrow” moves
- Heavily weighted sectors (e.g., Tech) matter proportionally more, reflecting real index impact
- Simple scale: ~−1 to +1 (all weight down → all weight up)
Chart Elements
- Green/Red Columns – “Weighted ADD”: Current bar’s weighted breadth (sign-based by default)
- Blue Line – “Weighted MA”: SMA of the weighted ADD (regime filter)
- Zero/Guide Lines (optional): 0.0, ±0.2 (mild), ±0.6 (strong)
- Labels (optional): Text markers at those guide levels
- Advancing Weight % (optional): Label showing ((ADD+1)/2)*100 → share of total sector weight advancing
How to Read (Quick Guide)
- +0.60 to +1.00 → Broad, one-sided risk-on (most sector weight advancing)
- +0.20 to +0.60 → Moderate, supportive breadth
- −0.20 to +0.20 → Mixed/choppy; rotation
- −0.60 to −1.00 → Broad, one-sided risk-off
- MA above/below zero → Simple regime indicator; zero-crosses could be potential alert triggers
- Divergence: Strong price move with a weak/flat ADD could potentially warn of narrow participation
Inputs & settings
Calculation
- Use returns instead of up/down sign?
OFF (default): true weighted participation (+1/−1/0)
ON: weighted sector returns (winsor-capped). Use if you want magnitude, not just direction
- Winsor cap (returns mode): Caps per-sector contribution in returns mode (e.g., 0.02 = ±2%)
- Smoothing MA length: SMA period for the blue “Weighted MA” line
- Source timeframe: Compute signals on another TF (e.g., “60”) but plot on your chart TF
Visibility
- Show Weighted ADD (bars): Toggle the green/red columns
- Show Weighted ADD MA: Toggle the blue SMA line
- Show Zero Line (0): Toggle the 0.0 reference line
- Show ±0.2 / ±0.6 guide lines: Toggle the helper levels
- Show guide labels: Draw small text labels at 0, ±0.2, ±0.6
- Guide label offset (bars left): Move labels left if they overlap the right edge values
- Show Advancing Weight % label: Toggle the % of sector weight currently advancing
Sector Symbols (ETF proxies)
- XLK, XLY, XLF, XLV, XLC, XLI, XLP, XLE, XLB, XLU, XLRE: Defaults to the SPDR sector ETFs. You can swap for alternative proxies if desired.
Sector Weights (auto-normalize)
- Weight inputs for each sector (e.g., Tech 0.30, Financials 0.13…). These auto-normalize to 1.0 so you can paste rough numbers; the script scales them.
- Keep weights fresh. GICS sector weights drift; update periodically (e.g., quarterly).
Alerts included
- “Weighted ADD crossed above 0”
- “Weighted ADD crossed below 0”
Version
v1.0 – Initial release (weighted sign-based ADD + SMA, zero/guide lines & labels, Adv % label, alerts).
RenKagi Fusion: Aura & SMA Clash IndicatorRenKagi Fusion: Aura & SMA Clash Indicator
Welcome to the RenKagi Fusion Indicator – a powerful, customizable tool that blends the strengths of Renko and Kagi charts to provide noise-filtered trend insights, enhanced with visual Aura effects and SMA (Simple Moving Average) crossover signals. Designed for traders seeking a unique edge in trend detection and reversal identification, this indicator combines traditional charting techniques with modern visualizations to help you navigate markets more effectively. Whether you're trading stocks, forex, or crypto, RenKagi Fusion offers a clean, actionable overview of market dynamics.
Key Features
RenKagi Line (Weighted Fusion of Renko and Kagi): The core of the indicator is the RenKagi line, a weighted average of Renko (brick-based trend filtering) and Kagi (reversal-focused line charts). Users can adjust the weight (default: 60% Renko, 40% Kagi) to prioritize stability or sensitivity. This fusion reduces market noise while highlighting key price movements.
Trend Scoring System: Calculates strength scores for Renko, Kagi, and RenKagi (capped at 20 points, converted to percentages). Scores increase with trend continuation and reset on reversals, giving a quantitative measure of momentum.
Aura Effects (Optional): Visual "glow" around lines based on score percentage – higher scores mean more opaque and thicker auras, adding a dynamic layer to trend visualization.
SMA Clash (Crossover Detection): Monitors daily SMA50, SMA100, and SMA200 for golden/death crosses (SMA50 crossing above/below longer SMAs) and RenKagi-SMA crossovers. These are displayed in a persistent info table for quick reference.
Customizable Visuals: Toggle lines, boxes, shapes, auras, and labels. Background coloring based on selected source (Renko, Kagi, or RenKagi) for intuitive trend bias.
Info Table: A configurable table (position and colors adjustable) summarizing scores, directions, cross states, brick size (with type), Kagi reversal (with type), and weights. No clutter – all in one place.
Alert Conditions: Built-in alerts for direction changes (Renko, Kagi, RenKagi), SMA crossovers, and golden/death crosses – perfect for real-time notifications.
How It Works
Renko Logic: Builds bricks based on user-selected type (Traditional fixed size, ATR dynamic, or Percentage). Scores build as trends persist, resetting on reversals.
Kagi Logic: Line reverses on thresholds (Traditional, ATR, or Percentage), scoring continuous moves.
RenKagi Calculation: Weighted average: (renkoPrice * renkoWeight + kagiLine * (100 - renkoWeight)) / 100. Score is a blend of individual scores.
SMA Integration: Daily timeframe SMAs for reliable long-term signals. Crossovers trigger alerts and update table states persistently until reversed.
Advantages for Traders
Noise Reduction: By fusing Renko's block structure with Kagi's reversal focus, it filters out minor fluctuations, helping identify strong trends early.
Versatility: Fully customizable – adjust weights, types, and visuals to fit any market or timeframe. Ideal for swing trading, trend following, or scalping.
Visual Clarity: Aura and background coloring provide at-a-glance insights, while the table consolidates data without overwhelming the chart.
Actionable Signals: Golden/Death crosses and direction changes offer clear entry/exit points, backed by alerts for timely execution.
Performance Optimization: Limits on lines/labels/boxes (500 each) ensure smooth operation on large datasets.
Usage Tips
Start with default settings for balanced performance.
Use in higher timeframes for trend confirmation or lower for intraday signals.
Combine with your favorite strategies – e.g., buy on RenKagi upward cross with SMA50 and golden cross confirmation.
Test on historical data to optimize weights and thresholds.
Note: This indicator is for educational and informational purposes only. Past performance is not indicative of future results. Always conduct your own analysis and use risk management. No financial advice is provided.
If you find this useful, please like, comment, or share your feedback!
3-Level DCA Buy Strategy🎯 3-Level DCA Buy Strategy - Smart Dollar Cost Averaging
Professional DCA strategy that systematically accumulates positions during market dips. Enhanced with daily trend analysis for intelligent accumulation.
🚀 Key Features
- 3-Level Buying System: Automatic purchases at 5%, 10%, 15% drops from cycle highs
- Daily Trend Analysis: 1-day timeframe trend confirmation
- Smart Peak Detection: 100-period lookback for meaningful peaks
- Volume Filter: Optional volume confirmation system
- USD-Based Positions: Fixed dollar amounts per level
- Never Sells: Pure accumulation philosophy (buy-only)
📊 How It Works
1. Peak Identification: Detects highest price in last 100 periods
2. Daily Trend Check: Confirms price above 50 SMA on 1D timeframe
3. Drop Tracking: Calculates percentage drops from cycle high
4. Systematic Buying: Executes predetermined amounts at each level
5. Cycle Reset: Renews buy permissions when new peaks form
⚙️ Default Settings
- Buy Levels: 5%, 10%, 15% drops
- Position Sizes: $100, $150, $200
- Peak Period: 100 bars
- Higher Timeframe: 1 Day (1D)
- Pyramiding: 500 order capacity
🎨 Visual Elements
- Orange Circles: Mark cycle highs
- Colored Lines: Green/Blue/Red buy levels
- Triangle Signals: Buy point indicators
- Live Panel: Real-time statistics
- Background Colors: Trend and drop level indicators
🔔 Alert System
- Instant notifications for each buy level
- New peak detection alerts
- Major drop warnings (>20%)
- Daily trend change notifications
💡 Ideal Use Cases
- Crypto Accumulation: Bitcoin, Ethereum and major altcoins
- Stock DCA: Long-term portfolio building
- Volatile Markets: Capitalizing on price fluctuations
- Emotional Trading Prevention: Automated and disciplined buying
📈 Strategy Logic
This strategy follows the "buy the dip" philosophy. It waits during market rises and systematically builds positions during declines. Only buys when daily trend is bullish, providing protection during major bear markets.
⚠️ Important Notes
- Buy-only strategy - never sells positions
- Requires sufficient capital for multiple entries
- Most effective in trending and volatile markets
- Always backtest before live trading
- Risk management is your responsibility
🛠️ Customization Options
All parameters are fully customizable: drop percentages, position amounts, timeframes, visual elements and more. Suitable for both beginner and experienced investors.
🎯 Publishing Feature
Note: Strategy includes temporary 1-day sell cycle for TradingView publishing requirements. This feature can be disabled for normal DCA mode operation.
⭐ If you find this strategy helpful, please like and follow! Visit the profile for more trading tools.
nATR*ATR Multiplication Indicator - Optimal Selection Tool forThis indicator is specifically designed as an analysis tool for investors using grid bot strategies. It displays both nATR (Normalized Average True Range) and ATR (Average True Range) values on a single chart screen, calculating the multiplication of these two critical volatility measurements.
Primary Purpose of the Indicator:
To facilitate the selection of the most optimal stock and time period for grid bot trading. The nATR*ATR multiplication provides a hybrid measurement that combines both percentage-based return potential (nATR) and absolute volatility magnitude (ATR).
Importance for Grid Bot Strategy:
High nATR: Greater percentage-based return potential
High ATR: Wider price range = Fewer grid levels = More budget allocation per grid
Formula: Price Range/ATR = Theoretical Grid Count
Usage Advantages:
Test different time periods to find the highest multiplication value
Make optimal stock and time frame selections for grid bot setup
Monitor both nATR and ATR values on a single screen
High multiplication values indicate ideal conditions for grid bots
Technical Features:
Adjustable calculation period (1-500 candles)
Visual alert system (high/low multiplication values)
Real-time value tracking table
SMA-based smoothed calculations
This serves as a reliable guide for grid bot investors in optimal timing and stock selection.
