Multi Color Normalized MACD + Candles (NMACD) [cI8DH]One simple indicator for volatility, divergence and relative momentum
Features:
- Normalized MACD (by slow MA)
- Candle MACD (fast MA length is set to 0 in candle mode, i.e. price minus slow MA)
- Multi color histogram
- Background coloring based on MACD direction
- Choice of different MA types (Exponential, Simple, Weighted, Smoothed, Triple EMA)
- Triple EMA smoothing
Benefits of normalization:
- Absolutely better than RSI for comparing across different periods and assets
Applications and benefits of candle visualization:
- Zero cross: most traders use MAs overlaid on the main chart and look for price distance and MA cross visually. In candle mode, this indicator measures the difference between price and the slow moving MA. When this indicator crosses zero, it means price is crossing the slow moving MA.
- Divergence: full candle visualization (OHLC) is not possible for most other indicators. Candle visualization allows measuring divergence between price high, low and close simultaneously. Some trades incorrectly measure divergence between high, low of price against indicator tops and bottoms while having the indicator input set to default (usually close). With this indicator, you don't need to worry about such complexities.
Recommended setting:
- Enjoy candle mode :)
- Source set to hlc3
Komut dosyalarını "Divergence" için ara
ULTRA RSI 2025//@version=6
indicator(title="ULTRA RSI 2025", shorttitle="ULTRA RSI 2025", format=format.price, precision=2)
// ==================== CONFIGURAÇÃO VISUAL FUTURISTA ====================
cyberTheme = input.string("IC", title="🎨 Tema Visual", options= , group="🎨 Visual Settings")
showGradients = input.bool(true, title="🎨 Exibir Preenchimentos em Gradiente", group="🎨 Visual Settings")
glowIntensity = input.float(0.3, title="🎨 Intensidade do Brilho", minval=0.0, maxval=1.0, step=0.1, group="🎨 Visual Settings")
// Cores para hline (usando input.color)
overboughtColor = input.color(color.new(#ff0000, 20), title="📈 Cor Sobrevendido", group="🎨 Visual Settings")
oversoldColor = input.color(color.new(#31fc09, 20), title="📉 Cor Sobrecomprado", group="🎨 Visual Settings")
midlineColor = input.color(color.new(#ffffff, 81), title="⚡ Cor da Linha Média", group="🎨 Visual Settings")
// ==================== CORES FUTURISTAS ====================
getThemeColors() =>
switch cyberTheme
"IC" =>
"Matrix Green" =>
"Tron Orange" =>
"Blade Runner Pink" =>
=>
= getThemeColors()
// Colores adicionales cyber
cyberGreen = color.new(#39FF14, 0)
cyberRed = color.new(#FF073A, 0)
darkCyber = color.new(#0D1117, 0)
neonWhite = color.new(#FFFFFF, 0)
// ==================== CÓDIGO RSI ORIGINAL (SIN MODIFICAR) ====================
rsiLengthInput = input.int(14, minval=1, title=" RSI Length", group=" RSI Settings")
rsiSourceInput = input.source(close, " Source", group=" RSI Settings")
calculateDivergence = input.bool(false, title=" Calculate Divergence", group=" RSI Settings", display = display.data_window, tooltip = "Calculating divergences is needed in order for divergence alerts to fire.")
change = ta.change(rsiSourceInput)
up = ta.rma(math.max(change, 0), rsiLengthInput)
down = ta.rma(-math.min(change, 0), rsiLengthInput)
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
// ==================== VISUAL FUTURISTA ====================
// Color dinámico para el RSI
getRsiColor(rsiValue) =>
if rsiValue >= 80
neonPrimary // Azul neón para sobrecomprado
else if rsiValue >= 70
color.new(neonPrimary, 30)
else if rsiValue <= 20
cyberRed // Rojo cyber para sobrevendido
else if rsiValue <= 30
color.new(cyberRed, 30)
else if rsiValue > 50
color.new(cyberGreen, 40)
else
color.new(neonSecondary, 50)
rsiColor = getRsiColor(rsi)
glowColor = color.new(rsiColor, math.round(100 - glowIntensity * 100))
// Plot RSI con efecto glow futurista
rsiPlot = plot(rsi, "🔮 Cyber RSI", color=rsiColor, linewidth=3)
plot(rsi, "✨ RSI Glow 1", color=glowColor, linewidth=5)
plot(rsi, "✨ RSI Glow 2", color=color.new(rsiColor, 90), linewidth=7)
// Líneas de banda con estilo cyber
rsiUpperBand = hline(70, "🔥 Cyber Overbought", color=overboughtColor, linestyle=hline.style_dashed, linewidth=2)
midline = hline(50, " Cyber Midline", color=midlineColor, linestyle=hline.style_dotted)
rsiLowerBand = hline(30, "❄️ Cyber Oversold", color=oversoldColor, linestyle=hline.style_dashed, linewidth=2)
// Background fills futuristas
midLinePlot = plot(50, color = na, editable = false, display = display.none)
// Fill condicional usando operador ternario
backgroundFillColor = showGradients ? color.new(darkCyber, 90) : na
overboughtFillColor = showGradients ? color.new(neonPrimary, 0) : na
overboughtFillColorBottom = showGradients ? color.new(neonPrimary, 100) : na
oversoldFillColorTop = showGradients ? color.new(neonSecondary, 100) : na
oversoldFillColorBottom = showGradients ? color.new(neonSecondary, 0) : na
fill(rsiUpperBand, rsiLowerBand, color=backgroundFillColor, title="🌃 Cyber Background")
fill(rsiPlot, midLinePlot, 100, 70, top_color = overboughtFillColor, bottom_color = overboughtFillColorBottom, title = "🌌 Cyber Overbought Zone")
fill(rsiPlot, midLinePlot, 30, 0, top_color = oversoldFillColorTop, bottom_color = oversoldFillColorBottom, title = "🌌 Cyber Oversold Zone")
// ==================== SMOOTHING MA (CÓDIGO ORIGINAL) ====================
GRP = "🌊 Smoothing"
TT_BB = "Only applies when 'SMA + Bollinger Bands' is selected. Determines the distance between the SMA and the bands."
maTypeInput = input.string("SMA", "Type", options = , group = GRP, display = display.data_window)
maLengthInput = input.int(14, "Length", group = GRP, display = display.data_window)
bbMultInput = input.float(2.0, "BB StdDev", minval = 0.001, maxval = 50, step = 0.5, tooltip = TT_BB, group = GRP, display = display.data_window)
var enableMA = maTypeInput != "None"
var isBB = maTypeInput == "SMA + Bollinger Bands"
// Smoothing MA Calculation (CÓDIGO ORIGINAL)
ma(source, length, MAtype) =>
switch MAtype
"SMA" => ta.sma(source, length)
"SMA + Bollinger Bands" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
"SMMA (RMA)" => ta.rma(source, length)
"WMA" => ta.wma(source, length)
"VWMA" => ta.vwma(source, length)
// Smoothing MA plots con colores cyber
smoothingMA = enableMA ? ma(rsi, maLengthInput, maTypeInput) : na
smoothingStDev = isBB ? ta.stdev(rsi, maLengthInput) * bbMultInput : na
plot(smoothingMA, "🌊 Cyber MA", color=color.new(color.yellow, 0), linewidth=2, display = enableMA ? display.all : display.none, editable = enableMA)
bbUpperBand = plot(smoothingMA + smoothingStDev, title = "🔺 Upper Cyber Band", color=neonPrimary, linewidth=2, display = isBB ? display.all : display.none, editable = isBB)
bbLowerBand = plot(smoothingMA - smoothingStDev, title = "🔻 Lower Cyber Band", color=neonSecondary, linewidth=2, display = isBB ? display.all : display.none, editable = isBB)
// Fill para Bollinger Bands
bbFillColor = isBB ? color.new(neonPrimary, 90) : na
fill(bbUpperBand, bbLowerBand, color=bbFillColor, title="🌌 Cyber Bollinger Fill", display = isBB ? display.all : display.none, editable = isBB)
// ==================== DIVERGENCE (CÓDIGO ORIGINAL CORREGIDO) ====================
lookbackRight = 5
lookbackLeft = 5
rangeUpper = 60
rangeLower = 5
bearColor = cyberRed
bullColor = cyberGreen
textColor = neonWhite
noneColor = color.new(color.white, 100)
// Función _inRange calculada en cada barra
_inRange(bool cond) =>
bars = ta.barssince(cond)
rangeLower <= bars and bars <= rangeUpper
plFound = false
phFound = false
bullCond = false
bearCond = false
rsiLBR = rsi
// Calcular _inRange en cada barra para evitar inconsistencias
plFoundPrev = not na(ta.pivotlow(rsi, lookbackLeft, lookbackRight) )
phFoundPrev = not na(ta.pivothigh(rsi, lookbackLeft, lookbackRight) )
inRangeBull = _inRange(plFoundPrev)
inRangeBear = _inRange(phFoundPrev)
if calculateDivergence
//------------------------------------------------------------------------------
// Regular Bullish
// rsi: Higher Low
plFound := not na(ta.pivotlow(rsi, lookbackLeft, lookbackRight))
rsiHL = rsiLBR > ta.valuewhen(plFound, rsiLBR, 1) and inRangeBull
// Price: Lower Low
lowLBR = low
priceLL = lowLBR < ta.valuewhen(plFound, lowLBR, 1)
bullCond := priceLL and rsiHL and plFound
//------------------------------------------------------------------------------
// Regular Bearish
// rsi: Lower High
phFound := not na(ta.pivothigh(rsi, lookbackLeft, lookbackRight))
rsiLH = rsiLBR < ta.valuewhen(phFound, rsiLBR, 1) and inRangeBear
// Price: Higher High
highLBR = high
priceHH = highLBR > ta.valuewhen(phFound, highLBR, 1)
bearCond := priceHH and rsiLH and phFound
// Divergence plots con estilo cyber
plot(
plFound ? rsiLBR : na,
offset = -lookbackRight,
title = "🚀 Cyber Bull Divergence",
linewidth = 3,
color = (bullCond ? bullColor : noneColor),
display = display.pane,
editable = calculateDivergence)
plotshape(
bullCond ? rsiLBR : na,
offset = -lookbackRight,
title = "🚀 Cyber Bull Signal",
text = "🚀 BULL",
style = shape.labelup,
location = location.absolute,
color = bullColor,
textcolor = textColor,
size = size.normal,
display = display.pane,
editable = calculateDivergence)
plot(
phFound ? rsiLBR : na,
offset = -lookbackRight,
title = "🔻 Cyber Bear Divergence",
linewidth = 3,
color = (bearCond ? bearColor : noneColor),
display = display.pane,
editable = calculateDivergence)
plotshape(
bearCond ? rsiLBR : na,
offset = -lookbackRight,
title = "🔻 Cyber Bear Signal",
text = "🔻 BEAR",
style = shape.labeldown,
location = location.absolute,
color = bearColor,
textcolor = textColor,
size = size.normal,
display = display.pane,
editable = calculateDivergence)
// ==================== TABLA DE INFORMACIÓN CYBER ====================
// Calcular ta.change en cada barra para consistencia
rsiChange3 = ta.change(rsi, 3)
if barstate.islast
var table infoTable = table.new(position.top_right, 2, 5,
bgcolor=color.new(darkCyber, 10),
border_width=2,
border_color=neonPrimary,
frame_width=3,
frame_color=neonSecondary)
table.clear(infoTable, 0, 0, 1, 4)
table.cell(infoTable, 0, 0, " ULTRA RSI", bgcolor=neonPrimary, text_color=neonWhite, text_size=size.small)
table.cell(infoTable, 1, 0, " INFO", bgcolor=neonSecondary, text_color=neonWhite, text_size=size.small)
table.cell(infoTable, 0, 1, " VALOR RSI", bgcolor=color.new(darkCyber, 30), text_color=neonPrimary, text_size=size.small)
table.cell(infoTable, 1, 1, str.tostring(math.round(rsi, 2)), bgcolor=color.new(darkCyber, 30), text_color=neonWhite, text_size=size.small)
rsiStatus = rsi >= 70 ? " SOBRENDIDO" : rsi <= 30 ? " SOBRECOMPRADO" : " NEUTRO"
statusColor = rsi >= 70 ? cyberRed : rsi <= 30 ? cyberGreen : neonWhite
table.cell(infoTable, 0, 2, " MOMENTO", bgcolor=color.new(darkCyber, 30), text_color=neonSecondary, text_size=size.small)
table.cell(infoTable, 1, 2, rsiStatus, bgcolor=color.new(darkCyber, 30), text_color=statusColor, text_size=size.small)
if enableMA
table.cell(infoTable, 0, 3, " EMA RSI", bgcolor=color.new(darkCyber, 30), text_color=neonPrimary, text_size=size.small)
table.cell(infoTable, 1, 3, str.tostring(math.round(smoothingMA, 2)), bgcolor=color.new(darkCyber, 30), text_color=neonWhite, text_size=size.small)
momentum = rsiChange3 > 0 ? " SUBINDO" : " CAINDO"
momentumColor = rsiChange3 > 0 ? cyberGreen : cyberRed
table.cell(infoTable, 0, 4, " TENDÊNCIA", bgcolor=color.new(darkCyber, 30), text_color=neonPrimary, text_size=size.small)
table.cell(infoTable, 1, 4, momentum, bgcolor=color.new(darkCyber, 30), text_color=momentumColor, text_size=size.small)
// ==================== ALERTS (CÓDIGO ORIGINAL) ====================
alertcondition(bullCond, title='🚀 Cyber Bullish Divergence', message="🎯 Found a new Cyber Bullish Divergence!")
alertcondition(bearCond, title='🔻 Cyber Bearish Divergence', message='🎯 Found a new Cyber Bearish Divergence!')
RSI Phan Ky FullThe RSI divergence indicator is like a magnifying glass that spots gaps between price swings and momentum. When price keeps climbing but RSI quietly sags, it’s a flashing U‑turn sign: the bulls are winded, and the bears are lacing up their boots. Flip it around—price is sliding yet RSI edges higher—and you’ve got bulls secretly stockpiling. Hidden divergences shore up the trend; regular divergences hint at a pivot. Blend those signals with overbought/oversold zones, support‑resistance, and volume, and RSI divergence turns into a radar that helps traders jump in with swagger and bail out just in time.
McClellan Oscillator - IRUS Optimized🧠 McClellan Oscillator (IRUS Index)
Type: Market Breadth Indicator
Category: Breadth, Momentum
Purpose: Gauge the internal strength of the IRUS index and anticipate trend reversals
📌 Based on
This indicator is built on the concept of advancing vs. declining issues — the number of stocks rising vs. falling each day within the IRUS index (a custom group of 40 Russian stocks).
It calculates the net advances (advancers minus decliners), then applies two exponential moving averages (EMA):
java
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Edit
McClellan Oscillator = EMA_19(Net Advances) - EMA_39(Net Advances)
Where:
Net Advances = Number of advancing stocks - Number of declining stocks
Calculated from a fixed set of 40 IRUS stocks
🧭 What it shows
Above 0 → more stocks are rising: market is internally strong.
Below 0 → more stocks are falling: underlying weakness.
Rising from below -100 → oversold breadth, possible bullish reversal.
Falling from above +100 → overbought breadth, possible correction.
🎯 How to use it
1. Buy/Sell Signals
Buy: Oscillator drops below -100 and turns up → oversold, potential rally.
Sell: Oscillator rises above +100 and turns down → overbought, risk of pullback.
2. Trend Strength Confirmation
Sustained above 0 → confirms bullish trend.
Crosses below 0 → early warning of weakening market breadth.
3. Divergences with IRUS Price
IRUS rises, but Oscillator falls → narrowing leadership, bearish divergence.
IRUS falls, but Oscillator rises → improving breadth, bullish divergence.
⚠️ Notes
The oscillator measures participation, not price.
Works best with daily timeframe.
Does not account for volume or magnitude of price moves.
Use with price action or other indicators for confirmation.
⚙️ Custom Implementation
This version is specifically adapted for the IRUS index, using a fixed list of 40 component stocks.
Optimized for Pine Script v6 and complies with TradingView's request limits (max 40).
SuperTrader Trend Analysis and Trade Study DashboardSuperTrader Trend Analysis and Trade Study Dashboard
Overview
This script offers a multi-faceted look at market behavior. It combines signals from different momentum indicators, daily cross checks, and a specialized dashboard to reveal trend strength, potential divergences, and how far price has traveled from its recent averages.
Three Musketeers Method
This script uses a special set of three indicators (the “Three Musketeers”) to determine bullish or bearish pressure on the current chart.
Trend Condition – Compares fast vs. slow EMAs (50 and 200) and checks which side of the line price is favoring.
Mean Reversion Condition – Watches RSI crossing typical oversold or overbought thresholds (e.g., crossing above 30 or below 70).
Bollinger Condition – Checks whether price pushes above/below the Bollinger Bands (based on a 20 SMA + standard deviations).
When at least two out of these three conditions align in a bullish way, the script issues a Buy Signal . Conversely, if at least two align in a bearish way, a Sell Signal is triggered. This “Three Musketeers” synergy ensures multiple confirmations before calling a potential market turn.
Mag 8 Daily Performance
The script tracks eight highly influential stocks (AAPL, AMZN, GOOG, NFLX, NVDA, TSLA, META, MSFT) to see which are green (higher) or red (lower) compared to yesterday’s close. It then prints a quick tally – helpful in gauging overall market mood via these major players.
Golden / Death Cross Signals
On a daily time frame, the script notes when the 50-day SMA crosses above or below the 200-day SMA. A “Golden Cross” often signals rising momentum, while a “Death Cross” can hint at oncoming weakness.
RSI & Divergence Checks
RSI helps identify hidden turning points. Whenever a bullish or bearish divergence is spotted, the script updates you via a concise readout.
Hardcoded Settings
EMA lengths for trend checks, Bollinger parameters, etc., are locked in, letting you focus on adjusting only the pivotal study inputs (e.g., RSI length, VIDYA momentum).
VIDYA Trend Line & Fill
Built on an adaptive Variable Index Dynamic Average, it plots a line that quickly reacts to changing momentum. Users can set a “Trend Band Distance” to mark ATR-based thresholds around that line, identifying possible breakouts or breakdowns.
YoYo Distance
This concept measures how far price strays from SMA(10). If it’s too far, the script colors your display to indicate potential snapbacks.
Gap Up/Down Probability
By weighing volume, MACD signals, and whether price sits above/below its midrange, the script estimates probabilities of a gap up or down on the next daily candle.
Table Output & Trend Label
Turning on Show Table Widget reveals a quick dashboard on the chart detailing RSI, CCI, divergences, bull/bear scores, and more. A label on the last bar further summarizes overall trend, gap distance, and the Mag 8 snapshot – perfect for a fast read of current market posture.
Use this script to unify multiple signals in one place, see how far price has ventured from typical patterns, and get daily cross signals plus real-time bullish/bearish calls – all at a glance.
Adaptive Stochastic Oscillator with Signals [AIBitcoinTrend]👽 Adaptive Stochastic Oscillator with Signals (AIBitcoinTrend)
The Adaptive Stochastic Oscillator with Signals is a refined version of the traditional Stochastic Oscillator, dynamically adjusting its lookback period based on market volatility. This adaptive approach improves responsiveness to market conditions, reducing lag while maintaining trend sensitivity. Additionally, the indicator includes real-time divergence detection and an ATR-based trailing stop system, allowing traders to manage risk and optimize trade exits effectively.
👽 What Makes the Adaptive Stochastic Oscillator Unique?
Unlike the standard Stochastic Oscillator, which uses a fixed lookback period, this version dynamically adjusts the period length using an ATR-based fractal dimension. This makes it more responsive to market conditions, filtering out noise while capturing key price movements.
Key Features:
Adaptive Lookback Calculation – Stochastic period changes dynamically based on volatility.
Real-Time Divergence Detection – Identify bullish and bearish divergences instantly.
Implement Crossover/Crossunder signals tied to ATR-based trailing stops for risk management
👽 The Math Behind the Indicator
👾 Adaptive Lookback Period Calculation
Traditional Stochastic Oscillators use a fixed-length period for their calculations, which can lead to inaccurate signals in varying market conditions. This version automatically adjusts its lookback period based on market volatility using an ATR-based fractal dimension approach.
How it Works:
The fractal dimension (FD) is calculated using the ATR (Average True Range) over a defined period.
FD values dynamically adjust the Stochastic lookback period between a minimum and maximum range.
This results in a faster response in high-volatility conditions and smoother signals during low volatility.
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Traders can anticipate trend reversals before they occur using real-time divergence detection.
Bullish Divergence Setup:
Identify price making a lower low while Stochastic %K makes a higher low.
Enter a long trade when Stochastic confirms upward momentum.
Bearish Divergence Setup:
Identify price making a higher high while Stochastic %K makes a lower high.
Enter a short trade when Stochastic confirms downward momentum.
👾 Trailing Stop & Signal-Based Trading
Bullish Setup:
✅Stochastic %K crosses above 90 → Buy signal.
✅A bullish trailing stop is placed at low - ATR × Multiplier.
✅Exit if the price crosses below the stop.
Bearish Setup:
✅Stochastic %K crosses below 10 → Sell signal.
✅A bearish trailing stop is placed at high + ATR × Multiplier.
✅Exit if the price crosses above the stop.
👽 Why It’s Useful for Traders
Adaptive Period Calculation: Dynamically adjusts to market volatility.
Real-Time Divergence Alerts: Helps traders identify trend reversals in advance.
ATR-Based Risk Management: Automatically adjusts stop levels based on price movements.
Works Across Multiple Markets & Timeframes: Useful for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
Min & Max Lookback Periods – Define the range for the adaptive Stochastic period.
Enable Divergence Analysis – Toggle real-time divergence detection.
Lookback Period – Set the number of bars for detecting pivot points.
Enable Trailing Stop – Activate the dynamic trailing stop feature.
ATR Multiplier – Adjust stop-loss sensitivity.
Line Width & Colors – Customize stop-loss visualization.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Easy CotHow to Use the Commitment of Traders (COT) Report for Market Analysis
The Commitment of Traders (COT) report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that breaks down the open interest in various futures markets. It categorizes traders into three main groups: Commercials, Non-Commercials, and Retail Traders (Non-Reportable positions). Understanding and analyzing the COT report can provide insights into market sentiment and potential reversals, especially in commodity, currency, and stock index futures.
Key Components of the COT Report
Commercials (Hedgers)
These are entities involved in the production or consumption of the underlying asset. For example, oil producers might hedge by selling oil futures to lock in prices, while airlines might buy futures to hedge against rising prices.
Commercials typically act as hedgers, so their positions can indicate the need for protection rather than speculative intent. Because they are less price-sensitive, their positions are usually opposite to the trend near market reversals.
Non-Commercials (Large Speculators)
This group includes hedge funds, asset managers, and large traders who take speculative positions to profit from price movements.
Non-Commercials are often trend-followers, meaning they increase long positions in an uptrend and short positions in a downtrend. When Non-Commercials become extremely bullish or bearish, it may signal a potential market reversal.
Retail Traders (Non-Reportable Positions)
These are smaller individual traders whose positions are too small to be reported individually.
Retail traders tend to be less experienced and are often on the wrong side of major market moves, so extreme positions by retail traders can sometimes signal a market turning point.
How to Interpret the COT Data
1. Identify Extreme Positions
Extreme Long or Short Positions: When a group reaches a historically extreme level of long or short positions, it often signals a potential reversal. For instance, if Non-Commercials are overwhelmingly long, it may indicate that the uptrend is overextended, and a reversal could be near.
Contrarian Indicator: Since Retail Traders are often on the wrong side, you may look for signals where they are extremely long or short, indicating a possible reversal in the opposite direction.
2. Look for Divergences
Divergence Between Groups: If Non-Commercials (speculators) and Retail Traders are moving in opposite directions, it could indicate that a trend is losing momentum and a reversal is possible.
Commercials vs. Non-Commercials: Commercials are often positioned opposite to Non-Commercials. If there’s a divergence where Non-Commercials are highly bullish, but Commercials are increasingly bearish, it might suggest a coming reversal.
3. Trend Confirmation and Reversal Signals
Trend Confirmation: If both Non-Commercials and Retail Traders are aligned in one direction, it might confirm the trend. However, keep in mind that such alignment may signal the later stages of a trend.
Reversal Signals: Look for signs when Non-Commercials are reaching a peak in one direction while Retail Traders peak in the opposite. Such situations can often indicate that the current trend is close to exhaustion.
Using the COT Report in Trading Strategies
Contrarian Trading Strategy
Extreme Positions as Reversal Signals: Use COT data to identify extreme positions. For instance, if Non-Commercials have a very high long position in a commodity, it might suggest that a bullish trend is overextended and a bearish reversal could be near.
Retail Trader Extremes: If Retail Traders are heavily long or short, consider taking the opposite position once you have additional confirmation signals (e.g., technical indicators).
Following the Trend with Large Speculators
Non-Commercials tend to be trend-followers, so if you see them increasingly long (or short) on an asset, it could be a signal to follow the trend until extreme levels are reached.
Using Divergences for Entry and Exit Points
Entry: If Non-Commercials are long, but Retail Traders are heavily short, consider entering a long position as it may confirm the trend.
Exit: If Non-Commercials begin to reduce their positions while Retail Traders increase theirs, it might be time to consider exiting, as the trend could be losing momentum.
30D Vs 90D Historical VolatilityVolatility equals risk for an underlying asset's price meaning bullish volatility is bearish for prices while bearish volatility is bullish. This compares 30-Day Historical Volatility to 90-Day Historical Volatility.
When the 30-Day crosses under the 90-day, this is typically when asset prices enter a bullish trend.
Conversely, When the 30-Day crosses above the 90-Day, this is when asset prices enter a bearish trend.
Peaks in volatility are bullish divergences while troughs are bearish divergences.
Standardized PSAR Oscillator [AlgoAlpha]Enhance your trading experience with the "Standardized PSAR Oscillator" 🪝, a powerful tool that combines the Parabolic Stop and Reverse (PSAR) with standardization techniques to offer more nuanced insights into market trends and potential reversals.
🔑 Key Features:
- 🛠 Customizable PSAR Settings: Adjust the starting point, increment, and maximum values for the PSAR to tailor the indicator to your strategy.
- 📏 Standardization: Smooth out volatility by standardizing the PSAR values using a customizable EMA, making reversals easier to identify.
- 🎨 Dynamic Color-Coding: The oscillator changes colors based on market conditions, helping you quickly spot bullish and bearish trends.
- 🔄 Divergence Detection: Automatic detection of bullish and bearish divergences with customizable sensitivity and confirmation settings.
- 🔔 Alerts: Set up alerts for key events like zero-line crossovers and trend weakening, ensuring you never miss a critical market move.
🚀 How to Use:
✨ Add the Indicator: Add the indicator to favorites by pressing the star icon, adjust the settings to suite your needs.
👀 Monitor Signals: Watch for the automatic plotting of divergences and reversal signals to identify potential market entries and exits.
🔔 Set Alerts: Configure alerts to get notified of key changes without constantly monitoring the charts.
🔍 How It Works:
The Standardized PSAR Oscillator is an advanced trading tool that refines the traditional PSAR (Parabolic Stop and Reverse) indicator by incorporating several key enhancements to improve trend analysis and signal accuracy. The script begins by calculating the PSAR, a widely used indicator known for its effectiveness in identifying trend reversals. To make the PSAR more adaptive and responsive to market conditions, it is standardized using an Exponential Moving Average (EMA) of the high-low range over a user-defined period. This standardization helps to normalize the PSAR values, making them more comparable across different market conditions.
To further enhance signal clarity, the standardized PSAR is then smoothed using a Weighted Moving Average (WMA). This combination of EMA and WMA creates an oscillator that not only captures trend direction but also smooths out market noise, providing a cleaner signal. The oscillator's values are color-coded to visually indicate its position relative to the zero line, with additional emphasis on whether the WMA is rising or falling—this helps traders quickly interpret the trend’s strength and direction.
The oscillator also includes built-in divergence detection by comparing pivot points in price action with those in the oscillator. This feature helps identify potential discrepancies between the price and the oscillator, signaling possible trend reversals. Alerts can be configured for when the oscillator crosses the zero line or when a trend shows signs of weakening, ensuring that traders receive timely notifications to act on emerging opportunities. These combined elements make the Standardized PSAR Oscillator a robust tool for enhancing your trading strategy with more reliable and actionable signals
RSI - ARIEIVhe RSI MAPPING - ARIEIV is a powerful technical indicator based on the Relative Strength Index (RSI) combined with moving averages and divergence detection. This indicator is designed to provide a clear view of overbought and oversold conditions, as well as identifying potential reversals and signals for market entries and exits.
Key Features:
Customizable RSI:
The indicator offers flexibility in adjusting the RSI length and data source (closing price, open price, etc.).
The overbought and oversold lines can be customized, allowing the RSI to signal critical market zones according to the trader’s strategy.
RSI-Based Moving Averages (MA):
Users can enable a moving average based on the RSI with support for multiple types such as SMA, EMA, WMA, VWMA, and SMMA (RMA).
For those who prefer Bollinger Bands, there’s an option to use the moving average with standard deviation to detect market volatility.
Divergence Detection:
Detects both regular and hidden divergences (bullish and bearish) between price and RSI, which can indicate potential market reversals.
These divergences can be customized with specific colors for easy identification on the chart, allowing traders to quickly spot significant market shifts.
Zone Mapping:
The script maps zones of buying and selling strength, filling the areas between the overbought and oversold levels with specific colors, highlighting when the market is in extreme conditions.
Strength Tables:
At the end of each session, a table appears on the right side of the chart, displaying the "Buying Strength" and "Selling Strength" based on calculated RSI levels. This allows for quick analysis of the dominant pressure in the market.
Flexible Settings:
Many customization options are available, from adjusting the number of decimal places to the choice of colors and the ability to toggle elements on or off within the chart.
ADX-DI - Made EasyThis indicator is a visually improved version of ADX. It makes it much easier to see what's happening by simplifying those confusing, intersecting lines. With this, you can detect the ADX direction more clearly. All the features are also explained in the tooltips of the input fields. Some extra features are included, such as average top and bottom calculation and divergences.
Please note that the divergences on ADX are just experimental and are based on calculations, so there is no guarantee the direction will change.
buy/sell signals with Support/Resistance (InvestYourAsset) 📣The present indicator is a MACD based buy/sell signals indicator with support and resistance, that can be used to identify potential buy and sell signals in a security's price.
📣It is based on the MACD (Moving Average Convergence Divergence) indicator, which is a momentum indicator that shows the relationship between two moving averages of a security's price.
📣 The indicator also plots support and resistance levels, which can be used to confirm buy and sell signals. The support and resistance can also be used as a stoploss for existing position.
👉 To use the indicator, simply add it to your trading chart. The indicator will plot three sections:
📈 Price and Signals: This section plots the security's price and the MACD buy and sell signals.
📈 MACD Oscillator: This section plots the MACD oscillator, which is a histogram that shows the difference between the two moving averages.
📈 Moving Averages: This section plots the two moving averages that the MACD oscillator is based on.
📈 Support and Resistance: This section plots support and resistance levels, which are calculated based on the security's recent price action.
👉 To identify buy and sell signals, you can look for the following:
📈 Buy signal: When shorter Moving Average crosses over longer Moving Average.
📈 Sell signal: When shorter moving average crosses under longer moving average.
📈 You can also look for divergences between the MACD oscillator and the security's price. A divergence occurs when the MACD oscillator is moving in one direction, but the security's price is moving in the opposite direction. Divergences can be a sign of a potential trend reversal.
👉 To confirm buy and sell signals, you can look for support and resistance levels take a look at below snapshot. If a buy signal occurs at a support level, it is a stronger signal than if it occurs at a random price level. Similarly, if a sell signal occurs at a resistance level, it is a stronger signal than if it occurs at a random price level.
⚡ Here is a example of how to use the indicator to identify buy signal:
☑ Add the indicator to your trading chart.
☑Look for a buy signal when short MA crosses over Long MA.
☑Look for the buy signal to occur at a support level.
☑Enter a long position at the next candle.
☑Place a stop loss order below the support level.
☑Take profit when the MACD line crosses below the signal line, or when the security reaches a resistance level.
⚡ Here is an example of how to use the indicator to identify a sell signal:
☑Add the indicator to your trading chart.
☑Look for a sell signal, when shorter moving average crosses under longer moving average.
☑Look for the sell signal to occur at a resistance level.
☑Enter a short position at the next candle.
☑Place a stop loss order above the resistance level.
☑Take profit when the MACD line crosses above the signal line, or when the security reaches a support level.
✅Things to consider while using the indicator:
📈Look for buy signals in an uptrend and sell signals in a downtrend. This will increase the likelihood of your trades being successful.
📈Place your stop losses below the previous swing low or support for buy signals and above the previous swing high or resistance for sell signals. This will help to limit your losses if the trade goes against you.
📈Consider taking profits at key resistance and support levels. This will help you to lock in your profits and avoid giving them back to the market.
Follow us for timely updates regarding indicators that we may publish in future and give it a like if you appreciate the indicator.
Composite Momentum IndicatorComposite Momentum Indicator" combines the signals from several oscillators, including Stochastic, RSI, Ultimate Oscillator, and Commodity Channel Index (CCI) by averaging the standardized values (Z-Scores). Since it is a Z-Score based indicators the values will be typically be bound between +3 and -3 oscillating around 0. Here's a summary of the code:
Input Parameters: Users can customize the look-back period and set threshold values for overbought and oversold conditions. They can also choose which oscillators to include in the composite calculation.
Oscillator Calculations: The code calculates four separate oscillators - Stochastic, RSI, Ultimate Oscillator, and CCI - each measuring different aspects of market momentum.
Z-Scores Calculation: For each oscillator, the code calculates a Z-Score, which normalizes the oscillator's values based on its historical standard deviation and mean. This allows for a consistent comparison of oscillator values across different timeframes.
Composite Z-Score: The code aggregates the Z-Scores from the selected oscillators, taking into account user preferences (whether to include each oscillator). It then calculates an average Z-Score to create the "Composite Momentum Oscillator."
Conditional Color Coding: The composite oscillator is color-coded based on its average Z-Score value. It turns green when it's above the overbought threshold, red when it's below the oversold threshold, and blue when it's within the specified range.
Horizontal Lines: The code plots horizontal lines at key levels, including 0, ±3, ±2, and ±1, to help users identify important momentum levels.
Gradient Fills: It adds gradient fills above the overbought threshold and below the oversold threshold to visually highlight extreme momentum conditions.
Combining the Stochastic, RSI, Ultimate Oscillator, and Commodity Channel Index (CCI) into one composite indicator offers several advantages for traders and technical analysts:
Comprehensive Insight: Each of these oscillators measures different aspects of market momentum and price action. Combining them into one indicator provides a more comprehensive view of the market's behavior, as it takes into account various dimensions of momentum simultaneously.
Reduced Noise: Standalone oscillators can generate conflicting signals and produce noisy readings, especially during choppy market conditions. A composite indicator smoothes out these discrepancies by averaging the signals from multiple indicators, potentially reducing false signals.
Confirmation and Divergence: By combining multiple oscillators, traders can seek confirmation or divergence signals. When multiple oscillators align in the same direction, it can strengthen a trading signal. Conversely, divergence between the oscillators can warn of potential reversals or weakening trends.
Customization: Traders can tailor the composite indicator to their specific trading strategies and preferences. They have the flexibility to include or exclude specific oscillators, adjust look-back periods, and set threshold levels. This adaptability allows for a more personalized approach to technical analysis.
Clarity and Efficiency: Rather than cluttering the chart with multiple individual oscillators, a composite indicator condenses the information into a single plot. This enhances the clarity of the chart and makes it easier for traders to quickly interpret market conditions.
Overbought/Oversold Identification: Combining these oscillators can improve the identification of overbought and oversold conditions. It reduces the likelihood of false signals since multiple indicators must align to trigger these extreme conditions.
Educational Tool: For novice traders and analysts, a composite indicator can serve as an educational tool by demonstrating how different oscillators interact and influence each other's signals. It allows users to learn about multiple technical indicators in one glance.
Efficient Use of Screen Space: A single composite indicator occupies less screen space compared to multiple separate indicators. This is especially beneficial when analyzing multiple markets or timeframes simultaneously.
Holistic Approach: Instead of relying on a single indicator, a composite approach encourages a more holistic assessment of market conditions. Traders can consider a broader range of factors before making trading decisions.
Increased Confidence: A composite indicator can boost traders' confidence in their decisions. When multiple reliable indicators align, it can provide a stronger basis for taking action in the market.
In summary, combining the Stochastic, RSI, Ultimate Oscillator, and CCI into one composite indicator enhances the depth and reliability of technical analysis. It simplifies the decision-making process, reduces noise, and offers a more complete picture of market momentum, ultimately helping traders make more informed and well-rounded trading decisions.
* Feel free to compare against individual oscillatiors*
Disparity IndexThe Disparity Index is a technical momentum indicator that measures the relative position of the most recent closing price to a selected moving average. It calculates the percentage difference between the closing price and the moving average, providing insights into price momentum and potential reversals.
The formula for the Disparity Index is: * 100, where Close is the most recent closing price and n-period MA is the chosen moving average over n periods.
The Disparity Index can be used in various ways:
Trend Identification: The Disparity Index helps identify the relationship between the price and a chosen moving average. A positive value indicates that the price is above the moving average, suggesting bullish momentum, while a negative value suggests bearish momentum.
Overbought and Oversold Conditions: The Disparity Index can be used to identify potential overbought and oversold conditions. When the index reaches an extremely high value, it may indicate an overbought condition, implying a possible price correction. Conversely, an extremely low value can signal an oversold condition, indicating a potential price rebound.
Divergence: Traders can use the Disparity Index to identify divergence between the price and the indicator. Divergence occurs when the price and the Disparity Index move in opposite directions, potentially signaling an upcoming price reversal.
Personal Strategy: When the Disparity Index generates a green background, it suggests a potential bullish signal. This occurs when the Disparity Index crosses above the oversold threshold or exhibits a bullish reversal pattern. The green background signifies an area where buyers may have gained control, indicating a favorable environment for initiating long positions. This approach allows you to capitalize on potential upward price movements and join the uptrend.
On the other hand, when the Disparity Index generates a red background, it implies a potential bearish signal. This occurs when the Disparity Index crosses below the overbought threshold or exhibits a bearish reversal pattern. The red background highlights a zone where sellers might dominate, indicating a higher likelihood of downward price movements. By considering selling opportunities in these zones, you can position yourself to profit from potential downside moves and align with the prevailing downtrend.
The Disparity Index can be customized by using different types of moving averages such as simple moving averages (SMAs), exponential moving averages (EMAs), or weighted moving averages (WMAs). Additionally, it can be smoothed using another moving average to reduce noise and generate smoother signals, improving trend identification.
In trending markets, the Disparity Index is particularly effective as a trend indicator due to its ability to quickly capture price changes. It can provide early indications of trend strength and potential reversals, allowing traders to enter or exit positions in a timely manner. This advantage over traditional moving averages makes the Disparity Index a valuable tool for trend-following strategies.
Enjoy!
(mab) Volume IndexThis script implements the (mab) Volume Index (MVI) which is a volume momentum oscillator. The formula is similar to the formula of RSI but uses volume instead of price. The price is calculated as the average of open, high, low and close prices and is used to determine if the volume is counted as up-volume or down-volume.
I created MVI to replace OBV on my charts, because OBV is not as simple to read and find e.g. divergences. MVI is much easier to read because it is an oscillator with a minimum value of 0 and a maximum value of 100. It's easy to find divergences too. I like to display MVI over the volume bars. However, you can display it in a separate pain as well.
ERDAL SARIDAS Visual RSIOne-stop shop for all your divergence needs, including:
(1) A single metric for divergence strength across multiple indicators.
(2) Labels that make it easy to spot where the truly strong divergence is by showing the overall divergence strength value along with the number of divergent indicators. Hovering over the label shows a breakdown of each divergent indicator and its individual divergence strength value.
(3) Fully customizable, including inputs for pivot lengths, divergence types, and weights for every component of the divergence strength calculation. This allows you to quickly and easily optimize the output for any chart. Don't worry, the default settings will have you covered if you're not interested in what's going on under the hood.
The Divergence Strength Calculation:
The total divergence strength value is the sum of the divergence strengths of all indicators for which divergence was detected at a given bar. Each indicator's individual divergence strength is comprised of two basic components: (1) |ΔPrice| - the magnitude of the change in price over the divergence period (pivot-to-pivot), and (2) |ΔIndicator| - the magnitude of the change in indicator value over the divergence period.
Because different indicators' scales and volatility can vary greatly, the Δ values are expressed in terms of standard deviation to ensure that the values are meaningful and equitable across all indicators and assets/instruments/currency pairs, etc:
|ΔIndicator| = |indicator_value_1 - indicator_value_2| / 2 * StDev(indicator_series,100)
Calculation Weights:
All components of the calculation are weighted and can be modified on the Inputs page in settings (weights are simply multipliers). For example, if you think hidden divergence should carry less weight than regular divergence, you can assign it a lesser weight. Or if you think RSI divergence is worth more than OBV divergence, you can adjust their weights accordingly. List of weights:
Regular divergence weight - default = 1
Hidden divergence weight - default = 1
ΔPrice weight - default = 0.5 (multiplied by the ΔPrice component)
ΔIndicator weight - default = 1.5 (multiplied by the ΔIndicator component)
RSI weight - default = 1.1
OBV weight - default = 0.8
MACD weight - default = 0.9
STOCH weight - default = 0.9
Development for additional indicators is ongoing, as is research into the optimal weight configuration(s).
Other Inputs:
Pivot lengths - specify the number of bars before and after each pivot high/low to consider it a valid candidate for divergence.
Lookback bars and Lookback pivots - specify the number of bars or the number of pivots to look back across.
Price sources - specify separate price sources for bullish and bearish divergence
Display settings - specify how lines and labels should display, including which divergence strength values should show the largest labels. Include/exclude specific divergence types and indicators.
Please report any bugs, or let me know if you have any enhancement suggestions or requests for additional indicators.
LS Volatility Index█ OVERVIEW
This indicator serves to measure the volatility of the price in relation to the average.
It serves four purposes:
1. Identify abnormal prices, extremely stretched in relation to an average;
2. Identify acceptable prices in the context of the main trend;
3. Identify market crashes;
4. Identify divergences.
█ CONCEPTS
The LS Volatility Index was originally described by Brazilian traders Alexandre Wolwacz (Stormer) , Fabrício Lorenz , and Fábio Figueiredo (Vlad)
Basically, this indicator can be used in two ways:
1. In a mean reversion strategy , when there is an unusual distance from it;
2. In a trend following strategy , when the price is in an acceptable region.
Perhaps the version presented here may have some slight differences, but the core is the same.
The original indicator is presented with a 21-period moving average, but here this value is customizable.
I made some fine tuning available, namely:
1. The possibility of smoothing the indicator;
2. Choose the type of moving average;
3. Customizable period;
4. Possibility to show a moving average of the indicator;
5. Color customization.
█ CALCULATION
First, the distance of the price from a given average in percentage terms is measured.
Then, the historical average volatility is obtained.
Finally the indicator is calculated through the ratio between the distance and the historical volatility.
To facilitate visualization, the result is normalized in a range from 0 to 100.
When it reaches 0, it means the price is on average.
When it hits 100, it means the price is way off average (stretched).
█ HOW TO USE IT
Here are some examples:
1. In a return-to-average strategy
2. In a trend following strategy
3. Identification of crashes and divergences
█ THANKS AND CREDITS
- Alexandre Wolwacz (Stormer), Fabrício Lorenz, Fábio Figueiredo (Vlad)
- Feature scaler (for normalization)
- HPotter (for calc of Historical Volatility)
SMT Pair (Nephew_Sam_)// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © Nephew_Sam_
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This code for version is entirely different from the previous two SMT divergence indicators that I had published in terms of effeciency.
There is an option to have upto 10 custom pairs and 1 default pair (if outside the 10) for your SMT/correlated pair.
The divergence lines are not perfect and is still under development.
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This indicator shows a secondary SMT/correlated pair at them bottom pane as a line or bar chart and draws lines if there are any divergences between the primary and secondary pair.
ie .
GBPUSD - EURUSD
EURUSD - DXY (inversed)
XAUUSD - XAGUSD
Options:
1. Show the secondary pair in lines or candlesticks
2. Divergences between pivot points (I'm yet to implement last pivot to live price)
3. Set 10 primary-smt pairs + a default pair for every other.
4. For every pair there is an option to inverse the price of the smt pair
(Hover over the tips in the indicator settings to learn more)
MACD-X Overlay, More Than MACD by DGTMoving Average Convergence Divergence – MACD
The most popular indicator used in technical analysis , the moving average convergence divergence ( MACD ), created by Gerald Appel. MACD is a trend-following momentum indicator , designed to reveal changes in the strength, direction, momentum, and duration of a trend in a financial instrument’s price
Historical evolution of MACD ,
- Gerald Appel created the MACD line,
- Thomas Aspray added the histogram feature to MACD
- Giorgos E. Siligardos created a leader of MACD
MACD employs two Moving Averages of varying lengths (which are lagging indicators) to identify trend direction and duration. Then, MACD takes the difference in values between those two Moving Averages (MACD Line) and an EMA of those Moving Averages (Signal Line) and plots that difference between the two lines as a histogram which oscillates above and below a center Zero Line. The histogram is used as a good indication of a security's momentum.
The MACD indicator is typically good for identifying three types of basic signals;
Signal Line Crossovers
A Signal Line Crossover is the most common signal produced by the MACD . On the occasions where the MACD Line crosses above or below the Signal Line, that can signify a potentially strong move. The standard interpretation of such an event is a recommendation to buy if the MACD line crosses up through the Signal Line (a "bullish" crossover), or to sell if it crosses down through the Signal Line (a "bearish" crossover). These events are taken as indications that the trend in the financial instrument is about to accelerate in the direction of the crossover.
Zero Line Crossovers
Zero Line Crossovers occur when the MACD Line crossed the Zero Line and either becomes positive (above 0) or negative (below 0). A change from positive to negative MACD is interpreted as "bearish", and from negative to positive as "bullish". Zero crossovers provide evidence of a change in the direction of a trend but less confirmation of its momentum than a signal line crossover
Divergence
Divergence is another signal created by the MACD . Simply, divergence occurs when the MACD and actual price are not in agreement. A "positive divergence" or "bullish divergence" occurs when the price makes a new low but the MACD does not confirm with a new low of its own. A "negative divergence" or "bearish divergence" occurs when the price makes a new high but the MACD does not confirm with a new high of its own. A divergence with respect to price may occur on the MACD line and/or the MACD Histogram
Moving Average Crossovers , another hidden signal that MACD Indicator identifies
Many traders will watch for a short-term moving average to cross above a longer-term moving average and use this to signal increasing upward momentum. This bullish crossover suggests that the price has recently been rising at a faster rate than it has in the past, so it is a common technical buy sign. Conversely, a short-term moving average crossing below a longer-term average is used to illustrate that the asset's price has been moving downward at a faster rate and that it may be a good time to sell.
Moving Average Crossovers in reality is Zero Line Crossovers, the value of the MACD indicator is equal to zero each time the two moving averages cross over each other. For easy interpretation by trades, Zero Line Crossovers are simply described as positive or negative MACD
False signals
Like any forecasting algorithm, the MACD can generate false signals. A false positive, for example, would be a bullish crossover followed by a sudden decline in a financial instrument. A false negative would be a situation where there is bearish crossover, yet the financial instrument accelerated suddenly upwards
What is “MACD-X” and Why it is “More Than MACD”
In its simples form, MACD-X implements variety of different calculation techniques applied to obtain MACD Line. Different calculation techniques lead to different values for MACD Line, as will further discuss below, and as a consequence the signal line and the histogram values will differentiate accordingly.
Main features of MACD-X ;
1- Plotting of the Oscillator presented on top of the price chart (main chart) and applicable on both log and linear scale. Maximum plotting length is limited to 250 bars
2- Introduces different proven techniques applied on MACD calculation, such as MACD-AS (Histogram), MACD-Leader and MACD-Source, besides the traditional MACD (MACD-TRADITIONAL)
• MACD-Traditional, by Gerald Appel
It is the MACD that we know, stated as traditional just to avoid confusion with other techniques used with this study
• MACD-Histogram, by Thomas Aspray
The MACD-Histogram measures the distance between MACD and its signal line (the 9-day EMA of MACD ). Aspray developed the MACD-Histogram to anticipate signal line crossovers in MACD . Because MACD uses moving averages and moving averages lag price, signal line crossovers can come late and affect the reward-to-risk ratio of a trade. Bullish or bearish divergences in the MACD-Histogram can alert chartists to an imminent signal line crossover in MACD
Aspray's contribution served as a way to anticipate (and therefore cut down on lag) possible MACD crossovers which are a fundamental part of the indicator.
• MACD-Leader, by Giorgos E. Siligardos, PhD
MACD Leader has the ability to lead MACD at critical situations. Almost all smoothing methods encounter in technical analysis are based on a relative-weighted sum of past prices, and the Leader is no exception. The concealed weights of MACD Leader are such that more relative weight is used in the more recent prices than the respective weights used by the components of MACD . In effect, the Leader expresses more changes in average price dynamics for the recent price movement than MACD , thus eventually leading MACD , especially when significant trend changes are about to take place.
• MACD-Source, a custom experimental interpretation of mine,
MACD Source, presents an application of MACD that evaluates Source/MA Ratio, relatively with less lag, as a basis for MACD Line, also can be expressed as source convergence/divergence to its moving average. Among the various techniques for removing the lag between price and moving average (MA) of the price, one in particular stands out: the addition to the moving average of a portion of the difference between the price and MA. MACD Source, is based on signal length mean of the difference between Source and average value of shot length and long length moving average of the source (Source/MA Ratio), where the source is actual value and hence no lag and relatively less lag with the average value of moving average of the source .
MACD Source provides relatively early crossovers comparing to MACD and better momentum direction indications, assuming the lengths are set to same values
3- Alerts presented for MACD and Signal Line Crosses both for Early Warning and Confirmed Crossovers
For more, You are kindly invited to have a look to other MACD or similar studies presented on separate pane
MACD-X, More Than MACD by DGT , P-MACD by DGT and Price Distance to its MA by DGT
Disclaimer : Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitutes professional and/or financial advice. You alone the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Advanced RSI HelperHere is Advanced RSI Helper. An advanced RSI represented in a candle type chart. It contains a Stochastic and a Pivot Detector (High-Low) and RSI divergences.
It also contains a Filter which you can configure the upper, lower zone to colorize the bars on the chart only when you are overbought or oversold, when you are in range the bars appear "transparent".
You also have the option of placing alerts for divergences or when the rsi exceeds the upper zone 1 / 2 or lower zone 1 / 2.
if you encounter any bugs do not hesitate to let me know in the comment area. The same goes for your suggestions.
Cheers and remember, risk management is the most important!
MACD-X, More Than MACD by DGTMoving Average Convergence Divergence – MACD
The most popular indicator used in technical analysis, the moving average convergence divergence (MACD), created by Gerald Appel. MACD is a trend-following momentum indicator, designed to reveal changes in the strength, direction, momentum, and duration of a trend in a financial instrument’s price
Historical evolution of MACD,
- Gerald Appel created the MACD line,
- Thomas Aspray added the histogram feature to MACD
- Giorgos E. Siligardos created a leader of MACD
MACD employs two Moving Averages of varying lengths (which are lagging indicators) to identify trend direction and duration. Then, MACD takes the difference in values between those two Moving Averages (MACD Line) and an EMA of those Moving Averages (Signal Line) and plots that difference between the two lines as a histogram which oscillates above and below a center Zero Line. The histogram is used as a good indication of a security's momentum.
Mathematically expressed as;
macd = ma(source, fast_length) – ma(source, slow_length)
signal = ma(macd, signal_length)
histogram = macd – signal
where exponential moving average (ema) is in common use as a moving average (ma)
fast_length = 12
slow_length = 26
signal_length = 9
The MACD indicator is typically good for identifying three types of basic signals ;
Signal Line Crossovers
A Signal Line Crossover is the most common signal produced by the MACD. On the occasions where the MACD Line crosses above or below the Signal Line, that can signify a potentially strong move. The standard interpretation of such an event is a recommendation to buy if the MACD line crosses up through the Signal Line (a "bullish" crossover), or to sell if it crosses down through the Signal Line (a "bearish" crossover). These events are taken as indications that the trend in the financial instrument is about to accelerate in the direction of the crossover.
Zero Line Crossovers
Zero Line Crossovers occur when the MACD Line crossed the Zero Line and either becomes positive (above 0) or negative (below 0). A change from positive to negative MACD is interpreted as "bearish", and from negative to positive as "bullish". Zero crossovers provide evidence of a change in the direction of a trend but less confirmation of its momentum than a signal line crossover
Divergence
Divergence is another signal created by the MACD. Simply, divergence occurs when the MACD and actual price are not in agreement. A "positive divergence" or "bullish divergence" occurs when the price makes a new low but the MACD does not confirm with a new low of its own. A "negative divergence" or "bearish divergence" occurs when the price makes a new high but the MACD does not confirm with a new high of its own. A divergence with respect to price may occur on the MACD line and/or the MACD Histogram
Moving Average Crossovers , another hidden signal that MACD Indicator identifies
Many traders will watch for a short-term moving average to cross above a longer-term moving average and use this to signal increasing upward momentum. This bullish crossover suggests that the price has recently been rising at a faster rate than it has in the past, so it is a common technical buy sign. Conversely, a short-term moving average crossing below a longer-term average is used to illustrate that the asset's price has been moving downward at a faster rate and that it may be a good time to sell.
Moving Average Crossovers in reality is Zero Line Crossovers, the value of the MACD indicator is equal to zero each time the two moving averages cross over each other. For easy interpretation by trades, Zero Line Crossovers are simply described as positive or negative MACD
False signals
Like any forecasting algorithm, the MACD can generate false signals. A false positive, for example, would be a bullish crossover followed by a sudden decline in a financial instrument. A false negative would be a situation where there is bearish crossover, yet the financial instrument accelerated suddenly upwards
What is “MACD-X” and Why it is “More Than MACD”
In its simples form, MACD-X implements variety of different calculation techniques applied to obtain MACD Line, ability to use of variety of different sources , including Volume related sources, and can be plotted along with MACD in the same window and all those features are available and presented within a single indicator, MACD-X
Different calculation techniques lead to different values for MACD Line, as will further discuss below, and as a consequence the signal line and the histogram values will differentiate accordingly. Mathematical calculation of both signal line and the histogram remain the same.
Main features of MACD-X ;
1- Introduces different proven techniques applied on MACD calculation , such as MACD-Histogram, MACD-Leader and MACD-Source, besides the traditional MACD (MACD-TRADITIONAL)
• MACD-Traditional , by Gerald Appel
It is the MACD that we know, stated as traditional just to avoid confusion with other techniques used with this study
• MACD-Histogram , by Thomas Aspray
The MACD-Histogram measures the distance between MACD and its signal line (the 9-day EMA of MACD). Aspray developed the MACD-Histogram to anticipate signal line crossovers in MACD. Because MACD uses moving averages and moving averages lag price, signal line crossovers can come late and affect the reward-to-risk ratio of a trade. Bullish or bearish divergences in the MACD-Histogram can alert chartists to an imminent signal line crossover in MACD
The MACD-Histogram represents the difference between MACD and its 9-day EMA, the signal line. Mathematically,
macdx = macd - ma(macd, signal_length)
Aspray's contribution served as a way to anticipate (and therefore cut down on lag) possible MACD crossovers which are a fundamental part of the indicator.
Here come a question, what if repeat the same calculations once more (macdh2 = macdh - ma(macdh, signal_length), will it be even better, this question will remain to be tested
• MACD-Leader , by Giorgos E. Siligardos, PhD
MACD Leader has the ability to lead MACD at critical situations. Almost all smoothing methods encounter in technical analysis are based on a relative-weighted sum of past prices, and the Leader is no exception. The concealed weights of MACD Leader are such that more relative weight is used in the more recent prices than the respective weights used by the components of MACD. In effect, the Leader expresses more changes in average price dynamics for the recent price movement than MACD, thus eventually leading MACD, especially when significant trend changes are about to take place.
Siligardos creates two less-laggard moving averages indicators in its formula using the same periods as follows
Indicator1 = ma(source, fast_length) + ma(source - ma(source, fast_length), fast_length)
Indicator2 = ma(source, slow_length) + ma(source - ma(source, slow_length), slow_length)
and then take the difference:
Indicator1 - Indicator2
The result is a new MACD Leader indicator
macdx = macd + ma(source - fast_ma, fast_length) - ma(source - slow_ma, slow_length)
• MACD-Source , a custom experimental interpretation of mine ,
MACD Source, presents an application of MACD that evaluates Source/MA Ratio, relatively with less lag, as a basis for MACD Line, also can be expressed as source convergence/divergence to its moving average. Among the various techniques for removing the lag between price and moving average (MA) of the price, one in particular stands out: the addition to the moving average of a portion of the difference between the price and MA. MACD Source, is based on signal length mean of the difference between Source and average value of shot length and long length moving average of the source (Source/MA Ratio), where the source is actual value and hence no lag and relatively less lag with the average value of moving average of the source . Mathematically expressed as,
macdx = ma(source - avg( ma(source, fast_length), ma(source, slow_length) ), signal_length)
MACD Source provides relatively early crossovers comparing to MACD and better momentum direction indications, assuming the lengths are set to same values
For further details, you are invited to check the following two studies, where the first seeds were sown of the MACD-Source idea
Price Distance to its Moving Averages study, adapts the idea of “Prices high above the moving average (MA) or low below it are likely to be remedied in the future by a reverse price movement", presented in an article by Denis Alajbeg, Zoran Bubas and Dina Vasic published in International Journal of Economics, Commerce and Management
First MACD like interpretation comes with the second study named as “ P-MACD ”, where P stands for price, P-MACD study attempts to display relationship between Price and its 20 and 200-period moving average. Calculations with P-MACD were based on price distance (convergence/divergence) to its 200-period moving average, and moving average convergence/divergence of 20-period moving average to 200-period moving average of price.
Now as explained above, MACD Source is a one adapted with traditional MACD, where Source stands for Price, Volume Indicator etc, any source applicable with MACD concept
2- Allows usage of variety of different sources, including Volume related indicators
The most common usage of Source for MACD calculation is close value of the financial instruments price. As an experimental approach, this study will allow source to be selected as one of the following series;
• Current Close Price (close)
• Average of High, Low, and Close Price (hlc3)
• On Balance Volume (obv)
• Accumulation Distribution (accdist)
• Price Volume Trend (pvt)
Where,
-Current Close Price and Average of High, Low, and Close Price are price actions of the financial instrument
- Accumulation Distribution is a volume based indicator designed to measure underlying supply and demand
- On Balance Volume (OBV) , is a momentum indicator that measures positive and negative volume flow
- Price Volume Trend (PVT) is a momentum based indicator used to measure money flow
3- Can be plotted along with MACD in the same window using the same scaling
Default setting of MACD-X will display MACD-Source with Current Close Price as a source and traditional MACD can be plotted eighter as a companion of MACD-X or can be selected to be plotted alone.
Applying both will add ability to compare, or use as a confirmation of one other
In case, traditional MACD Is plotted along with MACD-X to avoid misinterpreting, the lines plotted, the area between MACD-X Line and Signal-X Line is highlighted automatically, even if the highlight option not selected. Otherwise highlight will be applied only if that option selected
4- 4C Histogram
Histogram is plotted with four colors to emphasize the momentum and direction
5- Customizable
Additional to ability of selecting Calculation Method, Source, plotting along with MACD, there are few other option that allows users to customize the MACD-X indicator
Lengths are configurable, default values are set as 12, 26, 9 respectively for fast, slow and smoothing length. Setting lengths to 8,21,5 respectively Is worth checking, slower length moving averages will lead to less lag and earlier reaction to price actions but yet requires a caution and back testing before applying
Highlight the area between MACD-X Line and Signal-X Line, with colors emphasising the direction
Label can be added to display Calculation Method, Source and Length settings, the aim of this label is to server only as a reminder to trades to be aware of settings while they are occupied with charts, analysis etc.
Here comes another question, which is of more importance having the reminder or having the indicators with multi timeframe feature? Build-in Multi Time Frame features of Pine is not supported when labels and lines introduced in the script, there are other methods but brings complexity. To be studied further, this version will be with labels for time being.
Epilogue
MACD-X is an alternative variant of MACD, the insight/signals provided by MACD are also applicable to MACD-X with early and clear warnings for the changes in the trend.
If MACD is essential to your analysis, then it is my guess that after using the MACD-X for a while and familiarizing yourself with its unique character and personality, you will make it an inseparable companion to other indicators in your charts.
The various signals generated by MACD/MACD-X are easily interpreted and very few indicators in technical analysis have proved to be more reliable than the MACD, and this relatively simple indicator can quickly be incorporated into any short-term trading strategy
Disclaimer : Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitutes professional and/or financial advice. You alone the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Apirine Slow Candlestick RSI [ChuckBanger]This is just a candle stick version of Apirine Slow RSI. The yellow line is Apirine Slow RSI with the option to set an offset to it to filter out nice. RSI oscillating between 0 and 100. And whats good with Apirine version is it generates both OB/OS signals and midline (50) cross over signals and divergences. As author suggests, bullish/bearish divergences generated by the indicator are not as effective during strong trends. To avoid fading an established trend, the system is used in conjunction with a trend confirmation tool like ADX indicator.
The script spits out red and green diamonds as a potential long and short signals when the yellow line crosses close of the RSI candles. And combine it with trend confirmation tool like ADX, and if you apply it correctly. You have a very robust trading system. Good luck traders
RSI + Composite Index [SHK]One of the most powerful indicator based and divergence strategies i have ever seen was made by Constance Brown.
The Composite Index:
The best way to think of the Composite Index as it applies to the RSI is to think of the RSI as Windows 3.0 and the Composite Index as Windows 10. Constance Brown discovered that the RSI, while it does create and detect divergences, does is not as accurate as it could be. It’s a bit of an oxymoron to say this but the RSI is a momentum indicator without any momentum calculation attached to it. The RSI actually misses a significant amount of important moves and even generates some bad moves. What Constance Brown did with the RSI is to input a momentum calculation within the RSI itself.
Usage:
1. Check hidden and regular divergences on RSI+COMPOSITE_INDEX and PRICE+COMPOSITE_INDEX.
2. After finding divergence wait for COMPOSITE_INDEX to cross under/over it's moving averages to trigger.
Useful Note:
"RSI overbought/oversold as filter", "RSI and COMPOSITE_INDEX trendline as trigger", "RSI 50 Over/Under as trend direction detection", ... can be add to this strategy.
Enjoy!
