Momentum SNR VIP (Step 2)//@version=6
indicator("Momentum SNR VIP (Step 2)", overlay=true)
// === Inputs ===
lookback = input.int(20, "Lookback for S/R", minval=5)
rr_ratio = input.float(2.0, "Risk-Reward Ratio", minval=0.5, step=0.1)
plot(close, color=color.orange)
Göstergeler ve stratejiler
SuperTrend + ADX + Stochastic Stratejisi SuperTrend + ADX + Stochastic
Overview:
A trend-following and momentum-confirmation strategy using SuperTrend, ADX (>20 filter), and Stochastic oscillator. Optimized for Gold (XAUUSD) on the 10-minute chart.
Backtest Highlights (Last 1 Week):
Win Rate: 83.3% (5 out of 6 trades)
Net Profit: +56.35 USD (1 contract size)
Avg Trade Duration: ~58 bars (~9.6 hours)
Max Drawdown: 16.65 USD
Avg Win: 9.24 USD, Avg Loss: 0.82 USD
Largest Single Profit: 23.28 USD
Profit Factor: ~11.27
Core Logic:
Enter Long when:
* SuperTrend is bullish
* ADX > 20
* Stochastic %K > %D and %K < 80
Enter Short when:
* SuperTrend is bearish
* ADX > 20
* Stochastic %K < %D and %K > 20
No fixed TP/SL.
Positions closed on signal reversal.
VDN1 - T3 Tilson + IFT + ATRThis strategy combines three powerful indicators to create a high-quality and low-noise trading system:
🔹 T3 Tilson: Serves as the main trend indicator. It reacts smoothly to market direction changes while reducing noise.
🔹 Inverse Fisher Transform of RSI: A momentum filter that sharpens the signal precision. Only trades in the direction of positive or negative momentum.
🔹 ATR Filter: Avoids entries during low volatility (sideways) periods. Ensures the market is active enough before executing trades.
Core Logic:
* Long Entry: T3 Tilson rising + IFT(RSI) > 0 + ATR > threshold
* Short Entry: T3 Tilson falling + IFT(RSI) < 0 + ATR > threshold
* All trades use a fixed size of 1 unit for consistent risk evaluation.
Performance Notes:
* Works exceptionally well on index futures (e.g., NAS100, US30, GER40)
* Shows low drawdown and high profit factor (PF > 3) on those assets
* Also performs decently on XAUUSD, even with only \~32% win rate — thanks to favorable risk/reward
* BTC and ETH may require modified versions due to higher volatility and whipsaws
This is a master version — clean, unoptimized, and stable.
Use this as a core engine to build and test enhanced versions (e.g., with TP/SL, dynamic filters, etc.)
Happy testing and trading!
Momentum SNR VIP [3 TP + Max 50 Pip SL]//@version=6
indicator("Momentum SNR VIP ", overlay=true)
// === Settings ===
pip = input.float(0.0001, "Pip Size", step=0.0001)
sl_pip = 50 * pip
tp1_pip = 40 * pip
tp2_pip = 70 * pip
tp3_pip = 100 * pip
lookback = input.int(20, "Lookback for S/R", minval=5)
// === SNR ===
pivotHigh = ta.pivothigh(high, lookback, lookback)
pivotLow = ta.pivotlow(low, lookback, lookback)
supportZone = not na(pivotLow)
resistanceZone = not na(pivotHigh)
plotshape(supportZone, title="Support", location=location.belowbar, color=color.blue, style=shape.triangleup, size=size.tiny)
plotshape(resistanceZone, title="Resistance", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.tiny)
// === Price Action ===
bullishEngulfing = close < open and close > open and close > open and open <= close
bearishEngulfing = close > open and close < open and close < open and open >= close
bullishPinBar = close < open and (low - math.min(open, close)) > 1.5 * math.abs(close - open)
bearishPinBar = close > open and (high - math.max(open, close)) > 1.5 * math.abs(close - open)
buySignal = supportZone and (bullishEngulfing or bullishPinBar)
sellSignal = resistanceZone and (bearishEngulfing or bearishPinBar)
// === SL & TP ===
rawBuySL = low - 10 * pip
buySL = math.max(close - sl_pip, rawBuySL)
buyTP1 = close + tp1_pip
buyTP2 = close + tp2_pip
buyTP3 = close + tp3_pip
rawSellSL = high + 10 * pip
sellSL = math.min(close + sl_pip, rawSellSL)
sellTP1 = close - tp1_pip
sellTP2 = close - tp2_pip
sellTP3 = close - tp3_pip
// === Plot Buy/Sell Signal
plotshape(buySignal, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY")
plotshape(sellSignal, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL")
// === Plot SL & TP lines
plot(buySignal ? buySL : na, title="Buy SL", color=color.red, style=plot.style_linebr, linewidth=1)
plot(buySignal ? buyTP1 : na, title="Buy TP1", color=color.green, style=plot.style_linebr, linewidth=1)
plot(buySignal ? buyTP2 : na, title="Buy TP2", color=color.green, style=plot.style_linebr, linewidth=1)
plot(buySignal ? buyTP3 : na, title="Buy TP3", color=color.green, style=plot.style_linebr, linewidth=1)
plot(sellSignal ? sellSL : na, title="Sell SL", color=color.red, style=plot.style_linebr, linewidth=1)
plot(sellSignal ? sellTP1 : na, title="Sell TP1", color=color.green, style=plot.style_linebr, linewidth=1)
plot(sellSignal ? sellTP2 : na, title="Sell TP2", color=color.green, style=plot.style_linebr, linewidth=1)
plot(sellSignal ? sellTP3 : na, title="Sell TP3", color=color.green, style=plot.style_linebr, linewidth=1)
// === Labels
if buySignal
label.new(x=bar_index, y=buySL, text="SL : " + str.tostring(buySL, "#.0000"), style=label.style_label_down, color=color.red, textcolor=color.white)
label.new(x=bar_index, y=buyTP1, text="TP1 : " + str.tostring(buyTP1, "#.0000"), style=label.style_label_up, color=color.green, textcolor=color.white)
label.new(x=bar_index, y=buyTP2, text="TP2 : " + str.tostring(buyTP2, "#.0000"), style=label.style_label_up, color=color.green, textcolor=color.white)
label.new(x=bar_index, y=buyTP3, text="TP3 : " + str.tostring(buyTP3, "#.0000"), style=label.style_label_up, color=color.green, textcolor=color.white)
if sellSignal
label.new(x=bar_index, y=sellSL, text="SL : " + str.tostring(sellSL, "#.0000"), style=label.style_label_up, color=color.red, textcolor=color.white)
label.new(x=bar_index, y=sellTP1, text="TP1 : " + str.tostring(sellTP1, "#.0000"), style=label.style_label_down, color=color.green, textcolor=color.white)
label.new(x=bar_index, y=sellTP2, text="TP2 : " + str.tostring(sellTP2, "#.0000"), style=label.style_label_down, color=color.green, textcolor=color.white)
label.new(x=bar_index, y=sellTP3, text="TP3 : " + str.tostring(sellTP3, "#.0000"), style=label.style_label_down, color=color.green, textcolor=color.white)
// === Alerts
alertcondition(buySignal, title="Buy Alert", message="🟢 BUY at Support Zone + Price Action")
alertcondition(sellSignal, title="Sell Alert", message="🟡 SELL at Resistance Zone + Price Action")
Repeating Trend HighlighterThis custom indicator helps you see when the current price trend is similar to a past trend over the same number of candles. Think of it like checking whether the market is repeating itself.
You choose three settings:
• Lookback Period: This is how many candles you want to measure. For example, if you set it to 10, it looks at the price change over the last 10 bars.
• Offset Bars Ago: This tells the indicator how far back in time to look for a similar move. If you set it to 50, it compares the current move to what happened 50 bars earlier.
• Tolerance (%): This is how closely the moves must match to be considered similar. A smaller number means you only get a signal if the moves are almost the same, while a larger number allows more flexibility.
When the current price move is close enough to the past move you picked, the background of your chart turns light green. This makes it easy to spot repeating trends without studying numbers manually.
You’ll also see two lines under your chart if you enable them: a blue line showing the percentage change of the current move and an orange line showing the change in the past move. These help you compare visually.
This tool is useful in several ways. You can use it to confirm your trading setups, for example if you suspect that a strong rally or pullback is happening again. You can also use it to filter trades by combining it with other indicators, so you only enter when trends repeat. Many traders use it as a learning tool, experimenting with different lookback periods and offsets to understand how often similar moves happen.
If you are a scalper working on short timeframes, you can set the lookback to a small number like 3–5 bars. Swing traders who prefer daily or weekly charts might use longer lookbacks like 20–30 bars.
Keep in mind that this indicator doesn’t guarantee price will move the same way again—it only shows similarity in how price changed over time. It works best when you use it together with other signals or market context.
In short, it’s like having a simple spotlight that tells you: “This move looks a lot like what happened before.” You can then decide if you want to act on that information.
If you’d like, I can help you tweak the settings or combine it with alerts so it notifies you when these patterns appear.
Enhanced RSI Divergence StrategyCore Strategy Logic
1. Higher Timeframe (HTF) Context
Purpose: Align with the dominant trend (e.g., "bullish made new highs").
Tools:
Price action (breakouts, key support/resistance levels).
Trend confirmation (e.g., 50EMA on 1H/4H charts).
2. Lower Timeframe (LTF) Entry Triggers
Momentum Breakdown (Short Example):
Signal: Price makes "high of the day" + reversal candlestick (e.g., bearish engulfing).
Confirmation: RSI divergence or volume spike.
Support Reversion (Long/Short):
Signal: False breakout (e.g., "faked bullish breakout and reversed").
Confirmation: Wick rejection at HTF support/resistance.
3. Trade Execution
Entry: On 5-minute close after trigger.
Stop Loss (SL):
Current: Fixed ticks (e.g., 7-13 pts) → Issue: Too tight for US100 volatility.
Improved: 1.5x ATR(14) or beyond recent swing high/low.
Take Profit (TP):
Current: Fixed price levels (e.g., 21523).
Improved: Tiered exits (50% at 1:1 RR, trail rest).
4. Position Sizing
Fixed contracts (e.g., 10 per trade).
Better Approach: Risk 1-2% of capital per trade (adjust size based on SL distance).
Key Strengths
HTF+LTF Alignment: Avoids counter-trend traps by trading in HTF direction.
Flexibility: Adapts to momentum and mean-reversion setups.
Journaling: Tracks emotions/mistakes (critical for improvement).
EMAs + LSMA Cross Alert (Mejorado)his indicator is designed to identify buy and sell signals based on the behavior of multiple exponential moving averages (EMAs) and a Least Squares Moving Average (LSMA). It includes 5 EMAs and one LSMA, with visual and alert features.
📌 Components:
EMA 4 (purple)
EMA 9 (Fuchsia)
EMA 21 (blue)
EMA 50 (Green)
EMA 200 (maroon)
LSMA 30 (Orange)
🔍 Signal Logic:
✅ Buy Signal:
The LSMA (30) must be below both EMA 4 and EMA 9.
A bullish crossover occurs: EMA 4 crosses above EMA 9.
Only one signal is triggered per crossover, avoiding repeated alerts during trend continuation.
❌ Sell Signal:
The LSMA (30) must be above both EMA 4 and EMA 9.
A bearish crossover occurs: EMA 4 crosses below EMA 9.
Only one signal is triggered per crossover, avoiding repeated alerts during trend continuation.
🖥️ Visual Features:
Option to show/hide each EMA and the LSMA.
Buy/Sell markers appear at cross points.
A white background highlight marks the candle where the signal occurs (optional).
Visuals scale dynamically with the chart zoom and axes.
🔔 Alerts:
Custom alert conditions for Buy and Sell.
Alerts can trigger push notifications to the TradingView mobile app, email, or webhook.
Configured to avoid repeating alerts unless the trend resets and a new valid crossover occurs.
GX Credit Spread SignalThe GX Credit Spread Signal is an advanced indicator designed for traders who trade options strategies on the SPX index, especially using vertical credit spreads. It combines traditional technical analysis with volatility and option pricing concepts to provide relevant signals and projections on the chart.
Main features:
Trend analysis: Uses opening gap, position relative to VWAP and simple moving average (SMA 50) to indicate bullish or bearish bias right after the first 15-minute candle.
Safe range projection: Calculates a range based on the ATR (Average True Range) multiplied by a safety factor, suggesting potential strikes for credit spreads.
Quantitative estimates:
Calculates the estimated delta of options via the Black-Scholes formula approximation.
Estimated probability of expiring out of the money (OTM).
Chart visualizations: Displays projected ATR lines, previous day's levels (high, low, close) and an informative panel with strikes, delta, OTM probability, ATR and VWAP data.
Configurable alerts: Notifications for detected bullish or bearish bias, helping the trader to identify opportunities quickly.
This indicator is ideal for those who day trade with SPX options, facilitating decision-making by combining technical analysis, volatility and option probabilities in one place.
Range Bar Gaps DetectorRange Bar Gaps Detector
Overview
The Range Bar Gaps Detector identifies price gaps across multiple range bar sizes (12, 24, 60, and 120) on any trading instrument, helping traders spot potential support/resistance zones or breakout opportunities. Designed for Pine Script v6, this indicator detects gaps on range bars and exports data for use in companion scripts like Range Bar Gaps Overlap, making it ideal for multi-timeframe gap analysis.
Key Features
Multi-Range Gap Detection: Identifies gaps on 12, 24, 60, and 120-range bars, capturing both bullish (gap up) and bearish (gap down) price movements.
Customizable Sensitivity: Includes a user-defined minimum deviation (default: 10% of 14-period SMA) for 12-range gaps to filter out noise.
7-Day Lookback: Automatically prunes gaps older than 7 days to focus on recent, relevant price levels.
Data Export: Serializes up to 10 gaps per range (tops, bottoms, start bars, highest/lowest prices, and age) for seamless integration with overlap analysis scripts.
Debugging Support: Plots gap counts and aggregation data in the Data Window for easy verification of detected gaps.
How It Works
The indicator aggregates price movements to simulate higher range bars (24, 60, 120) from a base range bar chart. It detects gaps when the price jumps significantly between bars, ensuring gaps meet the minimum deviation threshold for 12-range bars. Gaps are stored in arrays, serialized for external use, and pruned after 7 days to maintain efficiency.
Usage
Add to your range bar chart (e.g., 12-range) to detect gaps across multiple ranges.
Use alongside the Range Bar Gaps Overlap indicator to visualize gaps and their overlaps as boxes on the chart.
Check the Data Window to confirm gap counts and sizes for each range (12, 24, 60, 120).
Adjust the "Minimal Deviation (%) for 12-Range" input to control gap detection sensitivity.
Settings
Minimal Deviation (%) for 12-Range: Set the minimum gap size for 12-range bars (default: 10% of 14-period SMA).
Range Sizes: Fixed at 24, 60, and 120 for higher range bar aggregation.
Notes
Ensure the script is published under your TradingView username (e.g., GreenArrow2005) for use with companion scripts.
Best used on range bar charts to maintain consistent gap detection.
For advanced overlap analysis, pair with the Range Bar Gaps Overlap indicator to highlight zones where gaps from different ranges align.
Ideal For
Traders seeking to identify key price levels for support/resistance or breakout strategies.
Multi-timeframe analysts combining gap data across various range bar sizes.
Developers building custom indicators that leverage gap data for advanced charting.
My script//@version=5
indicator("MA + OI + Volume Breakout", overlay=true)
// === MA Parameters ===
ma_type = input.string("EMA", title="MA Type", options= )
ma(src, len, type) =>
type == "SMA" ? ta.sma(src, len) :
type == "EMA" ? ta.ema(src, len) :
ta.wma(src, len)
ma5 = ma(close, 5, ma_type)
ma21 = ma(close, 21, ma_type)
ma50 = ma(close, 50, ma_type)
ma100 = ma(close, 100, ma_type)
plot(ma5, "5-day MA", color=color.yellow, linewidth=2)
plot(ma21, "21-day MA", color=color.orange, linewidth=2)
plot(ma50, "50-day MA", color=color.fuchsia, linewidth=2)
plot(ma100, "100-day MA", color=color.blue, linewidth=2)
// === Trend Signal ===
bullish_trend = ma5 > ma21 and ma21 > ma50 and ma50 > ma100
bearish_trend = ma5 < ma21 and ma21 < ma50 and ma50 < ma100
bgcolor(bullish_trend ? color.new(color.green, 85) : bearish_trend ? color.new(color.red, 85) : na)
// === Volume Breakout ===
vol_avg = ta.sma(volume, 20)
vol_breakout = volume > 1.5 * vol_avg
plotshape(vol_breakout, title="Volume Breakout", location=location.belowbar, style=shape.circle, color=color.aqua, size=size.tiny)
// === Open Interest Overlay (assumes OI data via external input or future integration) ===
// Placeholder: simulate OI input (replace with `request.security(syminfo.tickerid, ..., ...)` if available)
oi = input.float(na, title="Open Interest (external feed)")
oi_avg = ta.sma(oi, 20)
oi_breakout = oi > 1.2 * oi_avg
plotshape(not na(oi) and oi_breakout, title="OI Spike", location=location.belowbar, style=shape.diamond, color=color.purple, size=size.tiny)
plot(oi, title="Open Interest", color=color.gray, display=display.none) // Optional: hidden line for alerts
// === Composite Signal ===
strong_long = bullish_trend and vol_breakout and oi_breakout
plotshape(strong_long, title="Strong Long Signal", location=location.belowbar, style=shape.labelup, text="LONG", size=size.small, color=color.lime)
// === Screener Logic ===
// Use `strong_long` as your filter condition in a screener or dashboard output
Previous 10 Weekly Highs/Lows z s s bsf bsfd sfdv svdvvdsfvsdvsddvbadvvf zfvdzcxvdsfzv dfcvfdcxvsfdzvzdsfcx
VWAP SlopePositive (green) bars mean today’s (or this interval’s) VWAP is higher than the prior one → volume‐weighted average price is drifting up → bullish flow.
Negative (red) bars mean VWAP is lower than before → volume is skewed to sellers → bearish flow.
Bar height shows how much VWAP has shifted, so taller bars = stronger conviction.
Why it’s useful:
It gives you a real-time read on whether institutions are consistently buying at higher prices or selling at lower prices.
Use it as a bias filter: for shorts you want to see red bars (VWAP down-slope) at your entry, and for longs green bars (VWAP up-slope).
Because it updates tick-by-tick (or per bar), you get a live snapshot of volume-weighted momentum on top of your price‐action and oscillator signals.
Previous 10 Weekly Highs/Lowsvbcsvbabvdvbnsvnsiavonvbdobvasvbjsdavbdsoajvbdjaovbajv bajv adsjkv jksdv jkav kjsdf
Momentum SNR VIP [INDICATOR ONLY]//@version=6
indicator("Momentum SNR VIP ", overlay=true)
// === Inputs ===
lookback = input.int(20, "Lookback for S/R", minval=5)
rr_ratio = input.float(2.0, "Risk-Reward Ratio", minval=0.5, step=0.1)
// === SNR Detection ===
pivotHigh = ta.pivothigh(high, lookback, lookback)
pivotLow = ta.pivotlow(low, lookback, lookback)
supportZone = not na(pivotLow)
resistanceZone = not na(pivotHigh)
plotshape(supportZone, title="Support", location=location.belowbar, color=color.blue, style=shape.triangleup, size=size.tiny)
plotshape(resistanceZone, title="Resistance", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.tiny)
// === Price Action ===
bullishEngulfing = close < open and close > open and close > open and open <= close
bearishEngulfing = close > open and close < open and close < open and open >= close
bullishPinBar = close < open and (low - math.min(open, close)) > 1.5 * math.abs(close - open)
bearishPinBar = close > open and (high - math.max(open, close)) > 1.5 * math.abs(close - open)
buySignal = supportZone and (bullishEngulfing or bullishPinBar)
sellSignal = resistanceZone and (bearishEngulfing or bearishPinBar)
// === SL & TP ===
buySL = low - 10
buyTP = close + (close - buySL) * rr_ratio
sellSL = high + 10
sellTP = close - (sellSL - close) * rr_ratio
// === Plot Signals
plotshape(buySignal, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY")
plotshape(sellSignal, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL")
plot(buySignal ? buySL : na, title="Buy SL", color=color.red, style=plot.style_linebr, linewidth=1)
plot(buySignal ? buyTP : na, title="Buy TP", color=color.green, style=plot.style_linebr, linewidth=1)
plot(sellSignal ? sellSL : na, title="Sell SL", color=color.red, style=plot.style_linebr, linewidth=1)
plot(sellSignal ? sellTP : na, title="Sell TP", color=color.green, style=plot.style_linebr, linewidth=1)
// === Labels (Fixed)
if buySignal
label.new(x=bar_index, y=buySL, text="SL : " + str.tostring(buySL, "#.00"), style=label.style_label_down, color=color.red, textcolor=color.white)
label.new(x=bar_index, y=buyTP, text="TP 1 : " + str.tostring(buyTP, "#.00"), style=label.style_label_up, color=color.green, textcolor=color.white)
if sellSignal
label.new(x=bar_index, y=sellSL, text="SL : " + str.tostring(sellSL, "#.00"), style=label.style_label_up, color=color.red, textcolor=color.white)
label.new(x=bar_index, y=sellTP, text="TP 1 : " + str.tostring(sellTP, "#.00"), style=label.style_label_down, color=color.green, textcolor=color.white)
// === Alerts
alertcondition(buySignal, title="Buy Alert", message="🟢 BUY at Support Zone + Price Action")
alertcondition(sellSignal, title="Sell Alert", message="🟡 SELL at Resistance Zone + Price Action")
Normalized Reserve Risk (Proxy Z-Score)normalised version of the reserve risk indicator on btc magazine because the btc magazine one is poo .
💼 Momentum SNR VIP//@version=5
indicator("Momentum", overlay=true)
// === SNR Detection ===
lookback = input.int(20, "Lookback for S/R", minval=5)
pivotHigh = ta.pivothigh(high, lookback, lookback)
pivotLow = ta.pivotlow(low, lookback, lookback)
// Plot SNR Zones
plotshape(pivotHigh, title="Resistance", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.small)
plotshape(pivotLow, title="Support", location=location.belowbar, color=color.blue, style=shape.triangleup, size=size.small)
// === Price Action Detection ===
// Bullish Engulfing
bullishEngulfing = close < open and close > open and close > open and open <= close
// Bearish Engulfing
bearishEngulfing = close > open and close < open and close < open and open >= close
// Pin Bar Bullish
bullishPinBar = close > open and (low - math.min(open, close)) > 1.5 * (math.abs(close - open))
// Pin Bar Bearish
bearishPinBar = close < open and (math.max(open, close) - high) > 1.5 * (math.abs(close - open))
// === Combined Signal at SNR ===
supportZone = not na(pivotLow)
resistanceZone = not na(pivotHigh)
buySignal = (bullishEngulfing or bullishPinBar) and supportZone
sellSignal = (bearishEngulfing or bearishPinBar) and resistanceZone
// Plot Buy/Sell Arrows
plotshape(buySignal, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY")
plotshape(sellSignal, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL")
// === SL & TP Calculation ===
rr_ratio = input.float(2.0, "Risk Reward Ratio", minval=0.5, step=0.5)
buySL = low
buyTP = close + (close - low) * rr_ratio
sellSL = high
sellTP = close - (high - close) * rr_ratio
plot(buySignal ? buySL : na, title="Buy SL", color=color.red, style=plot.style_linebr, linewidth=1)
plot(buySignal ? buyTP : na, title="Buy TP", color=color.green, style=plot.style_linebr, linewidth=1)
plot(sellSignal ? sellSL : na, title="Sell SL", color=color.red, style=plot.style_linebr, linewidth=1)
plot(sellSignal ? sellTP : na, title="Sell TP", color=color.green, style=plot.style_linebr, linewidth=1)
// === Alerts ===
alertcondition(buySignal, title="Buy Alert", message="GOLD: Potential BUY @ SNR Zone + Price Action")
alertcondition(sellSignal, title="Sell Alert", message="GOLD: Potential SELL @ SNR Zone + Price Action")
H turnoverTrading Value refers to the total monetary amount of all transactions for a particular stock or the entire market over a specific period. It is calculated by multiplying the trading volume (the number of shares traded) by the price at which they were traded. For example, if 10,000 shares of a stock are traded in a day at an average price of 50,000 KRW, the trading value for that day would be 500,000,000 KRW.
Key points about trading value:
Market Activity and Liquidity: A high trading value indicates an active and liquid market.
Flow of Investment Funds: Increasing trading value suggests more money is flowing into the market or a particular stock.
Relationship with Price Movements: When both trading value and price rise together, it often signals strong buying interest. Conversely, significant price changes with low trading value may be less reliable.
Market Sentiment Indicator: Changes in trading value can reflect shifts in investor interest and sentiment.
In summary, trading value is the total amount of money exchanged in trades and serves as an important indicator of market activity, liquidity, and investor sentiment.
H IchimokuIchimoku Kinko Hyo (commonly called the Ichimoku Cloud) is a comprehensive technical analysis indicator developed by Japanese journalist Goichi Hosoda in the 1960s. Its name translates to “one glance equilibrium chart,” reflecting the tool’s purpose: to provide a quick, holistic view of market trend, momentum, and support/resistance levels.
The Ichimoku Cloud consists of five main components:
Tenkan-sen (Conversion Line): The average of the highest high and lowest low over the past 9 periods.
Kijun-sen (Base Line): The average of the highest high and lowest low over the past 26 periods.
Senkou Span A (Leading Span A): The average of the Tenkan-sen and Kijun-sen, plotted 26 periods ahead.
Senkou Span B (Leading Span B): The average of the highest high and lowest low over the past 52 periods, plotted 26 periods ahead.
Chikou Span (Lagging Span): The current closing price plotted 26 periods back.
The area between Senkou Span A and B forms the “cloud” (Kumo), which visually highlights key support and resistance zones. Prices above the cloud indicate an uptrend, below the cloud a downtrend, and within the cloud a consolidating or neutral market.
Ichimoku is valued for its ability to provide a broad, forward-looking perspective on price action, helping traders identify trends, momentum, and potential reversal points at a glance.
Full SMA Pullback Strategy with DMIFull SMA Pullback Strategy with DMI with buy sell signal generating capabilities in combination with various SMAs(9/20/50/100/200)
Chaithanya Tattva Volume Zones📜 "Chaitanya Tattva" Volume Zones:-
A Sacred Framework of Supply, Demand & Market Energy
In the world of financial markets, price is said to reflect all information. But the true pulse of the market — its life force, its intent, and its moment of truth — is most vividly expressed not in price itself, but in volume.
Chaitanya Tattva Volume Zones is a spiritually inspired volume-based tool that transforms your chart into a canvas of market consciousness, revealing moments where supply and demand engage in visible energetic spikes. These moments are often disguised as ordinary candles, but with this tool, you uncover zones of intent — footprints left by the market’s deeper intelligence.
🌟 Why “Chaitanya Tattva”?
Chaitanya (चैतन्य) is a Sanskrit word meaning consciousness, awareness, or the spark of life energy. It is that which animates — the subtle intelligence behind all movement.
Tattva (तत्त्व) refers to essence, truth, or the underlying principle of a thing. In classical yogic philosophy, the tattvas are the elemental building blocks of reality.
Together, Chaitanya Tattva represents the conscious essence — the living pulse that animates the market through volume surges and imbalances.
This tool is not just a technical indicator — it is a spiritual observation device that aligns with the rhythm of volume and price action. It doesn't predict the market. It reveals when the market has already spoken — loudly, clearly, and energetically.
📈 What Does the Tool Do?
Chaitanya Tattva Volume Zones identifies exceptional volume spikes within the recent price history and visually marks the areas where market intent has been most active.
Specifically, the tool:
Scans for volume spikes that exceed all the volume of the last N bars (default is 20)
Confirms whether the spike happened on a bullish candle (close > open) or bearish candle (close < open)
For a bullish spike, it marks a Supply Zone — the area between the high and close of the candle
For a bearish spike, it marks a Demand Zone — the area between the low and close
Visually paints these zones with soft translucent boxes (red for supply, green for demand) that extend forward across multiple bars
🧘♂️ The Spiritual Framework
🔴 Supply = "Agni" — The Fire of Expansion
When a bullish candle erupts with historically high volume, it symbolizes the fire (Agni) of market optimism and upward expansion. It means that buyers have absorbed available supply at that level and established dominance — but such fire may also signal exhaustion, making it a potential supply barrier if price returns.
These Supply Zones are areas where:
Sellers are likely to re-engage
Smart money may be unloading
Future resistance can be anticipated
But unlike traditional indicators, this tool doesn’t guess. It reacts only to a clear volume-based event — when market energy surges — and locks in that awareness through zone marking.
🟢 Demand = "Prithvi" — The Grounding of Price
On the other hand, a bearish candle with extremely high volume represents the Earth (Prithvi) — grounding the price with firm hands. A strong volume drop often means buyers are stepping in, absorbing the selling pressure.
These Demand Zones are areas where:
Buying interest is proven
Market memory is stored
Future support can be expected
By respecting these zones, you're aligning your trading with natural market boundaries — not theoretical ones.
🧠 How Is It Different from Regular Volume Tools?
While most volume indicators show bars on a lower panel, they leave interpretation up to the trader. “High” or “low” becomes subjective.
Chaitanya Tattva Volume Zones is different:
It quantifies "spike": a bar must exceed all previous N volumes
It qualifies the intent: was the spike bullish or bearish?
It marks zones on the price chart: no need to guess levels
It preserves market memory: the zones persist visually for easy reference
In essence, this tool doesn’t just report volume — it interprets volume’s context and visually encodes it into the chart.
🧘 How to Use
1. Support/Resistance Mapping
Use the tool to understand where volume proved itself. If price revisits a red zone, expect possible rejection (resistance). If price revisits a green zone, expect possible absorption (support).
2. Entry Triggers
You may enter:
Long near demand zones if bullish confirmation appears
Short near supply zones if bearish confirmation appears
3. Stop Placement
Stops can be placed just beyond the zone boundary to align with areas where smart money historically defended.
4. Breakout Confidence
When price breaks through one of these zones with momentum, it often signals a new energetic wave — the old balance has been overcome.
🔔 Key Features
Volume spike detection across any timeframe
Clear visual zones — no clutter, no lag
Highly customizable: zone width, volume lookback, colors
Philosophy-aligned with supply and demand theory, Wyckoff, and Order Flow
🌌 A Metaphysical View of Volume
In yogic science, volume is akin to Prana — life-force energy. A market is not moved by price alone but by intent, force, and participation — all encoded in volume.
Just as a human body pulses with blood when action intensifies, the market pulses with volume when institutional decisions are made.
These pulses become sacred footprints — and Chaitanya Tattva Volume Zones helps you walk mindfully among them.
🔮 Final Thoughts
In a sea of indicators that shout at you with every tick, Chaitanya Tattva is calm. It speaks only when energy concentrates, only when the market sends a signal born of intent.
It doesn’t predict.
It doesn’t repaint.
It simply shows the truth, when the truth becomes undeniable.
Like a sage that speaks only when needed, it waits for volume to prove itself — then draws a memory into space, a zone where traders can re-align their actions with what the market has already honored.
Use it not just to trade —
But to listen.
To observe.
To follow the Chaitanya — the conscious pulse of the market’s own breath.
