Williams Fractals with Style & Line Width Options (Aligned)Fractal indicator with the ability to adjust the size of the circle by adjusting the width!
Bill Williams Göstergeleri
ModelScopeSctipt for M7 teaching about WDRR and partials
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FGIHow it Works
The FGI uses two main conditions to determine fear and greed:
Fear Zone: This condition is met when the current price is significantly lower than its recent highest price, relative to its standard deviation. This suggests that the market may be experiencing a rapid decline, indicating fear among participants. When active, it plots a pink candlestick below the price bars.
Greed Zone: This condition is met when the inverse of the current price is significantly lower than the inverse of its recent highest price, also relative to its standard deviation. In simpler terms, this means the price is significantly higher than recent averages, suggesting excessive buying or greed. When active, it plots a green candlestick above the price bars.
Customizable Settings:
Source: You can choose the price data (e.g., ohlc4 which is the average of open, high, low, and close) the indicator uses for its calculations.
High Period: This setting determines the look-back period for calculating the highest price.
Stdev Period: This setting defines the period used for calculating the standard deviation.
Average Type: You can select whether the indicator uses a Weighted Moving Average (WMA) or a Simple Moving Average (SMA) for its internal calculations.
Show Alert Circle: This option allows you to display a small circle on the chart when a fear or greed condition is triggered.
SMA Fecho na Máxima, Mínima e NormalLarry Williams' Strategy - Short Moving Average Channel
✅ Indicators used:
High SMA: 3 periods
Low SMA: 3 periods
30-period Closing SMA: used as a trend filter
Fair Value Gap [Custom]📌 FVG Indicator – Smart Money Concepts Tool
This script is based on Smart Money Concepts (SMC) and automatically detects and marks Fair Value Gaps (FVG) on the chart, helping traders identify unbalanced price areas left behind by institutional moves.
🧠 What is an FVG?
An FVG (Fair Value Gap) is the price gap formed when the market moves rapidly, leaving behind a candle range where no trading occurred — typically between Candle 1’s high and Candle 3’s low (in a three-candle pattern). These gaps often signal imbalance, created during structural breaks or liquidity grabs, and may act as retrace zones or entry points.
🛠 Features:
✅ Automatically detects and highlights FVG zones (high-low range)
✅ Differentiates between open (unfilled) and closed (filled) FVGs
✅ Adjustable timeframe settings (works best on 1H–4H charts)
✅ Option to toggle display of filled FVGs
✅ Great for identifying pullback entries, continuation zones, or reversal setups
💡 Recommended Use:
After BOS/CHoCH, watch for price to return to the FVG for entry
Combine with Order Blocks and liquidity zones for higher accuracy
Best used as part of an ICT or SMC-based trading system
KST Strategy [Skyrexio]Overview
KST Strategy leverages Know Sure Thing (KST) indicator in conjunction with the Williams Alligator and Moving average to obtain the high probability setups. KST is used for for having the high probability to enter in the direction of a current trend when momentum is rising, Alligator is used as a short term trend filter, while Moving average approximates the long term trend and allows trades only in its direction. Also strategy has the additional optional filter on Choppiness Index which does not allow trades if market is choppy, above the user-specified threshold. Strategy has the user specified take profit and stop-loss numbers, but multiplied by Average True Range (ATR) value on the moment when trade is open. The strategy opens only long trades.
Unique Features
ATR based stop-loss and take profit. Instead of fixed take profit and stop-loss percentage strategy utilizes user chosen numbers multiplied by ATR for its calculation.
Configurable Trading Periods. Users can tailor the strategy to specific market windows, adapting to different market conditions.
Optional Choppiness Index filter. Strategy allows to choose if it will use the filter trades with Choppiness Index and set up its threshold.
Methodology
The strategy opens long trade when the following price met the conditions:
Close price is above the Alligator's jaw line
Close price is above the filtering Moving average
KST line of Know Sure Thing indicator shall cross over its signal line (details in justification of methodology)
If the Choppiness Index filter is enabled its value shall be less than user defined threshold
When the long trade is executed algorithm defines the stop-loss level as the low minus user defined number, multiplied by ATR at the trade open candle. Also it defines take profit with close price plus user defined number, multiplied by ATR at the trade open candle. While trade is in progress, if high price on any candle above the calculated take profit level or low price is below the calculated stop loss level, trade is closed.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.5, number of ATRs to calculate stop-loss level)
ATR Take Profit (by default = 3.5, number of ATRs to calculate take profit level)
Filter MA Type (by default = Least Squares MA, type of moving average which is used for filter MA)
Filter MA Length (by default = 200, length for filter MA calculation)
Enable Choppiness Index Filter (by default = true, setting to choose the optional filtering using Choppiness index)
Choppiness Index Threshold (by default = 50, Choppiness Index threshold, its value shall be below it to allow trades execution)
Choppiness Index Length (by default = 14, length used in Choppiness index calculation)
KST ROC Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #2 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #3 (by default = 20, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #4 (by default = 30, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #2 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #3 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #4 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST Signal Line Length (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is KST, Williams Alligator, Moving Average, ATR and Choppiness Index.
The KST (Know Sure Thing) is a momentum oscillator developed by Martin Pring. It combines multiple Rate of Change (ROC) values, smoothed over different timeframes, to identify trend direction and momentum strength. First of all, what is ROC? ROC (Rate of Change) is a momentum indicator that measures the percentage change in price between the current price and the price a set number of periods ago.
ROC = 100 * (Current Price - Price N Periods Ago) / Price N Periods Ago
In our case N is the KST ROC Length inputs from settings, here we will calculate 4 different ROCs to obtain KST value:
KST = ROC1_smooth × 1 + ROC2_smooth × 2 + ROC3_smooth × 3 + ROC4_smooth × 4
ROC1 = ROC(close, KST ROC Length #1), smoothed by KST SMA Length #1,
ROC2 = ROC(close, KST ROC Length #2), smoothed by KST SMA Length #2,
ROC3 = ROC(close, KST ROC Length #3), smoothed by KST SMA Length #3,
ROC4 = ROC(close, KST ROC Length #4), smoothed by KST SMA Length #4
Also for this indicator the signal line is calculated:
Signal = SMA(KST, KST Signal Line Length)
When the KST line rises, it indicates increasing momentum and suggests that an upward trend may be developing. Conversely, when the KST line declines, it reflects weakening momentum and a potential downward trend. A crossover of the KST line above its signal line is considered a buy signal, while a crossover below the signal line is viewed as a sell signal. If the KST stays above zero, it indicates overall bullish momentum; if it remains below zero, it points to bearish momentum. The KST indicator smooths momentum across multiple timeframes, helping to reduce noise and provide clearer signals for medium- to long-term trends.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
The next indicator is Moving Average. It has a lot of different types which can be chosen to filter trades and the Least Squares MA is used by default settings. Let's briefly explain what is it.
The Least Squares Moving Average (LSMA) — also known as Linear Regression Moving Average — is a trend-following indicator that uses the least squares method to fit a straight line to the price data over a given period, then plots the value of that line at the most recent point. It draws the best-fitting straight line through the past N prices (using linear regression), and then takes the endpoint of that line as the value of the moving average for that bar. The LSMA aims to reduce lag and highlight the current trend more accurately than traditional moving averages like SMA or EMA.
Key Features:
It reacts faster to price changes than most moving averages.
It is smoother and less noisy than short-term EMAs.
It can be used to identify trend direction, momentum, and potential reversal points.
ATR (Average True Range) is a volatility indicator that measures how much an asset typically moves during a given period. It was introduced by J. Welles Wilder and is widely used to assess market volatility, not direction.
To calculate it first of all we need to get True Range (TR), this is the greatest value among:
High - Low
abs(High - Previous Close)
abs(Low - Previous Close)
ATR = MA(TR, n) , where n is number of periods for moving average, in our case equals 14.
ATR shows how much an asset moves on average per candle/bar. A higher ATR means more volatility; a lower ATR means a calmer market.
The Choppiness Index is a technical indicator that quantifies whether the market is trending or choppy (sideways). It doesn't indicate trend direction — only the strength or weakness of a trend. Higher Choppiness Index usually approximates the sideways market, while its low value tells us that there is a high probability of a trend.
Choppiness Index = 100 × log10(ΣATR(n) / (MaxHigh(n) - MinLow(n))) / log10(n)
where:
ΣATR(n) = sum of the Average True Range over n periods
MaxHigh(n) = highest high over n periods
MinLow(n) = lowest low over n periods
log10 = base-10 logarithm
Now let's understand how these indicators work in conjunction and why they were chosen for this strategy. KST indicator approximates current momentum, when it is rising and KST line crosses over the signal line there is high probability that short term trend is reversing to the upside and strategy allows to take part in this potential move. Alligator's jaw (blue) line is used as an approximation of a short term trend, taking trades only above it we want to avoid trading against trend to increase probability that long trade is going to be winning.
Almost the same for Moving Average, but it approximates the long term trend, this is just the additional filter. If we trade in the direction of the long term trend we increase probability that higher risk to reward trade will hit the take profit. Choppiness index is the optional filter, but if it turned on it is used for approximating if now market is in sideways or in trend. On the range bounded market the potential moves are restricted. We want to decrease probability opening trades in such condition avoiding trades if this index is above threshold value.
When trade is open script sets the stop loss and take profit targets. ATR approximates the current volatility, so we can make a decision when to exit a trade based on current market condition, it can increase the probability that strategy will avoid the excessive stop loss hits, but anyway user can setup how many ATRs to use as a stop loss and take profit target. As was said in the Methodology stop loss level is obtained by subtracting number of ATRs from trade opening candle low, while take profit by adding to this candle's close.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2025.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 60%
Maximum Single Position Loss: -5.53%
Maximum Single Profit: +8.35%
Net Profit: +5175.20 USDT (+51.75%)
Total Trades: 120 (56.67% win rate)
Profit Factor: 1.747
Maximum Accumulated Loss: 1039.89 USDT (-9.1%)
Average Profit per Trade: 43.13 USDT (+0.6%)
Average Trade Duration: 27 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 1h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrexio commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation.
Williams VIX For Bottoms [DCD]Williams VIX Original - Authentic Volatility Fear Gauge
What This Indicator Does
The Williams VIX Fix measures market fear by calculating how far current lows deviate from recent highs, identifying potential market bottoms during high volatility periods. This implementation provides Larry Williams' original formula in its purest form.
How It Works
Core Formula:
VIX Fix = ((Highest High over 22 periods - Current Low) / Highest High over 22 periods) × 100
The calculation process:
Measures Relative Distance: Compares current low to highest high over lookback period
Converts to Percentage: Normalizes values for cross-market comparison
Applies Statistical Analysis: Uses Bollinger Bands (2 std dev) around VIX Fix values
Filters with Percentiles: 85th percentile threshold removes noise
Signal Generation
Green Flash Signals trigger when either condition is met:
VIX Fix exceeds upper Bollinger Band (2 standard deviations above 20-period MA)
VIX Fix exceeds Range High (85th percentile of recent values)
This dual-condition approach reduces false signals while capturing genuine volatility spikes.
What Makes This Original
Pure Formula Implementation: Uses Williams' exact original calculation without modifications
Dual Confirmation System: Combines Bollinger Bands with percentile analysis
Professional Visualization: Histogram display, background highlighting, and live value table
Comprehensive Alerts: Signal start/end notifications plus Green Flash alerts
How to Use
Primary Purpose: Spot high-probability reversal zones during market fear climaxes
Signal Interpretation:
Green triangle + background highlight = High volatility reversal zone
Higher VIX Fix values = Stronger fear/better reversal potential
Use with price action confirmation for best results
Optimal Settings:
Timeframes: 4H, Daily, Weekly
Markets: All (stocks, crypto, forex, commodities)
Combine with support levels and candlestick patterns
Key Parameters:
VIX Fix Length (22): Lookback period for highest high
Std Dev Multiplier (2.0): Bollinger Band sensitivity
Percentile High (0.85): Only top 15% of readings trigger signals
The VIX Fix excels at identifying market fear climaxes that coincide with significant price bottoms, making it valuable for swing traders seeking high-probability entries during market stress.
Stephis Supply & Demand Zones v3
📉 Support
Definition: Support is a price level where a downtrend can be expected to pause or reverse due to a concentration of buying interest.
Why it matters: When the price of an asset falls to a support level, traders expect buyers to step in, preventing the price from falling further.
Visual clue: On a chart, support often appears as a horizontal line where the price has bounced up multiple times.
📈 Demand
Definition: Demand refers to the willingness and ability of buyers to purchase an asset at a given price.
In trading context: High demand typically pushes prices up, while low demand can lead to price drops.
Relation to support: A support level exists because of demand—buyers are willing to buy at that price, creating a floor.
🧠 How They Work Together
When price approaches a support level, traders watch to see if demand increases—if it does, the price may bounce.
If the support level is broken, it may signal that demand has weakened, and the price could fall further.
🔁 Opposite Concept: Resistance & Supply
Resistance is the opposite of support—it's a level where selling pressure (supply) may stop a price from rising.
Just like demand creates support, supply creates resistance.
Zigzag Simple [SCL]🟩 OVERVIEW
Draws zigzag lines from pivot Highs to pivot Lows. You can choose between three different ways of calculating pivots:
• True Highs and Lows
• Williams pivots
• Oscillator pivots
🟩 HOW TO USE
This indicator can be used to understand market structure, which is arguably the primary thing you need to be aware of when trading. The zigzag by itself does not display a market structure bias, nor any information about prices of pivots, HH and HL labels, or anything like that. Nevertheless, a simple zigzag is perhaps the easiest and most intuitive way to understand what price is doing.
Choose a pivot style that you like, customise the colours and line style, and enjoy!
🟩 PIVOT TYPES EXPLAINED
True Highs and Lows
This is not an invention of mine (all credit to my humble mentor), but I haven't seen anyone else code them up. A true High is a close below the low of the candle with the highest high. A true Low is a close above the high of a candle with the lowest low. These are solid, price action-based pivots that can sometimes confirm quickly.
Williams pivots
This is how most people calculate pivots. They're simply the highest high for x bars back and x bars forwards. They're the vanilla of pivots IMO: serviceable but not very interesting. They're very convenient to code because there are built-in Pine functions for them: ta.pivothigh and ta.pivotlow . They confirm a predictable number of bars after they happen, which is great for coding but also makes the trader wait for confirmation.
Oscillator pivots
This is a completely different concept, which uses momentum in order to define pivots. For example, when you get a rise in momentum and momentum then drops a configurable amount, it confirms a pivot high, and vice versa for a pivot low. I don't know if anyone else does it –- although some indicators do mark pivots in momentum itself, and plenty do divergences, I wasn't able to find one that specifically marked *pivots in price* because of pivots in momentum 🤷♂️
Anyway, while this approach needs a whole investigation on its own, here we simply plot some pivots in a smoothed RSI. This indicator doesn't plot the actual momentum values -- for a more visual understanding of how this works, refer to the examples in the OscillatorPivots library.
🟩 UNIQUE ADVANTAGES
In contrast to other zigzag indicators available, this one lets you choose between the standard and some more unique methods of generating the zigzags. Additionally, because it's based on libraries, it is relatively easy for programmers to use as a basis for experimentation.
🟩 GEEK STUFF
Although there is considerable practical use for pivot-based zigzags in trading, this script is primarily a demonstration in coding -- specifically the power of libraries!
Most of the script consists of setup, especially defining inputs. The final section sacrifices some readability for conciseness, simply to emphasise how little code you need when the heavy lifting is done by libraries .
The actual calculations and drawing are achieved in just 8 lines.
The equivalent code in the libraries is ~250 lines long.
All libraries used are my own, public and open-source:
• MarketStructure
• DrawZigZag
• OscillatorPivots
Simple Fractals with Wick Filter & BOSThis advanced fractal indicator combines traditional Williams Fractal analysis with sophisticated wick filtering and Break of Structure (BOS) detection to identify high-probability reversal points and structural breaks in price action.
🔍 How It Works
Fractal Detection: Uses the classic Williams Fractal methodology to identify swing highs and lows. A fractal high occurs when a candle's high is greater than N periods before and after it. Similarly, a fractal low occurs when a candle's low is lower than N periods on both sides.
Wick Filtering: Only displays fractals where the rejection wick meets a minimum threshold, ensuring the fractal represents genuine price rejection rather than minor fluctuations.
Break of Structure (BOS): Monitors when strong candles close beyond previous fractal levels within a specified lookback period, indicating potential trend changes or continuation patterns.
⚙️ Parameter Guide
Periods (Default: 7) - Controls fractal sensitivity
Wick Threshold (Default: 0.4 / 40%) - Minimum wick size relative to total candle range
BOS Lookback Bars (Default: 90) - How far back to monitor fractal levels for potential breaks
Strong Candle Body % (Default: 0.5 / 50%) - Minimum body size required to trigger BOS, Higher values reduce false signals but may miss some valid breaks
📊 Visual Elements
Colored Dots: Small circles mark validated fractals
Top Wick Fractals: Customizable color (default red) above bars
Bottom Wick Fractals: Customizable color (default green) below bars
BOS Lines: Dotted horizontal lines connecting fractal origin to break point
Green Lines: Bullish BOS (price closes above fractal high)
Red Lines: Bearish BOS (price closes below fractal low)
Faded Fractals (Optional): Shows all fractals that didn't meet wick requirements for comparison
🔔 Alerts
The indicator includes built-in alerts for:
High fractal formation with sufficient wick
Low fractal formation with sufficient wick
Liquidity-Quant Execution Score (LQES)Liquidity-Quant Execution Score (LQES)
Precision execution insights made simple — your go-to score for market clarity.
What you see:
A dynamic line score plotted clearly below your chart that reflects the market’s execution strength.
Color-coded threshold bands —
The upper red band signals zones where caution is advised (potential bearish conditions).
The lower green band marks areas of potential bullish strength.
A shaded purple zone between the bands that highlights “normal” or neutral conditions.
Features:
Designed to give you a clear sense of market execution dynamics without complex numbers.
Adjustable input parameters allow you to tailor the sensitivity and timeframe to your strategy.
Includes fixed alert conditions to notify you when the score crosses key zones — so you never miss important signals.
How to use it:
Watch for the score crossing above the upper red line — this could hint at increasing market pressure to the downside.
When the score drops below the lower green line, it may suggest bullish momentum picking up.
Use the middle purple zone to identify calm or balanced periods — ideal for preparation or cautious trading.
Why traders rely on LQES:
This indicator translates complex market execution data into one straightforward, visually intuitive score — making it easier to spot shifts in liquidity and price action that matter most for smart entries and exits.
No need to second guess. Just watch the score, respect the zones, and integrate it smoothly with your trading plan.
VIDYA (Chande)This script brings you VIDYA – the Variable Index Dynamic Average, developed by Tushar Chande. It’s not your typical moving average. Unlike the standard SMA or EMA, VIDYA adapts its speed and smoothness based on real-time market momentum using the Chande Momentum Oscillator (CMO).
Think of it like a moving average that gets faster during strong trends and slows down during sideways or choppy markets — just like how a smart trader would!
🧠 What Makes VIDYA Different?
Traditional moving averages use fixed smoothing, so they lag more during big moves or chop during weak trends.
VIDYA fixes that by adapting its behavior dynamically:
When momentum is strong → VIDYA reacts faster 🚀
When momentum is weak → VIDYA smooths out the noise 🧘
⚙️ How It Works (Explained Simply):
1️⃣ CMO Calculation (Chande Momentum Oscillator):
We look at the past cmoLength candles (default 9) and:
i) Add up all the positive price changes (gains)
ii) Add up all the negative price changes (losses)
iii) Use those to compute a normalized momentum score between -100 and +100
📌 CMO = (Gains - Losses) / (Gains + Losses)
• This gives us a momentum reading that powers the next step.
2️⃣ Dynamic Alpha Smoothing:
• We convert the absolute value of the CMO into an alpha — this is the "speed" of the VIDYA.
📌 Higher momentum = higher alpha → faster response
📌 Lower momentum = lower alpha → smoother behavior
3️⃣ VIDYA Formula:
• Finally, we apply the smoothing:
📌 VIDYA = α × Price + (1 - α) × Previous VIDYA
• This equation continuously adapts to market behavior — trending or ranging.
📊 What’s Plotted?
🟠 The VIDYA Line:
A smooth, responsive line plotted on your price chart that adjusts in real-time with price momentum.
🔎 How to Use It:
✅ Use it like a moving average, but smarter:
• Price > VIDYA and rising → Trend is likely up
• Price < VIDYA and falling → Trend is likely down
• Flat VIDYA = Possible consolidation or sideways market
✅ Combine with:
• Breakout strategies (VIDYA confirms momentum)
• Reversal entries (look for price crossing VIDYA)
• Volatility filters (ignore signals when VIDYA flattens)
🧪 Bonus Tip:
Pair this with a volume indicator (like my Volume Confirmation Bars or Volume Strength Highlight) to confirm whether momentum is backed by real participation or just a fakeout.
📩 Want alerts, dual-timeframe overlays, or VIDYA with other base inputs (like typical price or HLC3)? Let me know — happy to expand this for your setup!
Stay adaptive, not reactive — trade smarter with VIDYA! 🧠📉📈
9:15 Range with 0.09% BufferThis strategy is based on the first 9:15 AM candle for Nifty, which is considered a key reference point (also called the "GAN level entry"). It defines a range around the high and low of the 9:15 candle with a 0.09% buffer on both sides.
The upper buffer level acts as a potential resistance.
The lower buffer level acts as a potential support.
When the price crosses above the upper buffer, it signals a possible entry for a Call option (CE) or a long position.
When the price crosses below the lower buffer, it signals a possible entry for a Put option (PE) or a short position.
This approach helps traders identify early breakout opportunities based on the opening candle range, aiming to capture momentum moves in either direction during the trading session.
Bull & Bear Power Separados📄 English Description for TradingView
Bull & Bear Power – Elder Style
This indicator displays the strength of buyers (Bull Power) and sellers (Bear Power) separately, based on Alexander Elder’s original concept.
It uses a 13-period Exponential Moving Average (EMA) as the baseline, calculating:
Bull Power = High – EMA
Bear Power = Low – EMA
✔️ Bull Power (green) shows buying pressure.
✔️ Bear Power (red) shows selling pressure.
Great for analyzing true market momentum and spotting early signs of potential trend reversals.
Can be used as confirmation together with moving averages (e.g., MMA30 and MMA50) or price action signals.
✅ On 1H gold charts (XAUUSD), it has shown solid behavior in filtering entries during clear trends.
Developed and shared for educational purposes by El Bit Criollo.
MestreDoFOMO MACD VisualMasterDoFOMO MACD Visual
Description
MasterDoFOMO MACD Visual is a custom indicator that combines a unique approach to MACD with stochastic logic and simulated Renko-based direction signals. It is designed to help traders identify entry and exit opportunities based on market momentum and trend changes, with a clear and intuitive visualization.
How It Works
Stylized MACD with Stochastic: The indicator calculates the MACD using EMAs (exponential moving averages) normalized by stochastic logic. This is done by subtracting the lowest price (lowest low) from a defined period and dividing by the range between the highest and lowest price (highest high - lowest low). The result is a MACD that is more sensitive to market conditions, magnified by a factor of 10 for better visualization.
Signal Line: An EMA of the MACD is plotted as a signal line, allowing you to identify crossovers that indicate potential trend reversals or continuations.
Histogram: The difference between the MACD and the signal line is displayed as a histogram, with distinct colors (fuchsia for positive, purple for negative) to make momentum easier to read.
Simulated Renko Direction: Uses ATR (Average True Range) to calculate the size of Renko "bricks", generating signals of change in direction (bullish or bearish). These signals are displayed as arrows on the chart, helping to identify trend reversals.
Purpose
The indicator combines the sensitivity of the Stochastic MACD with the robustness of Renko signals to provide a versatile tool. It is ideal for traders looking to capture momentum-based market movements (using the MACD and histogram) while confirming trend changes with Renko signals. This combination reduces false signals and improves accuracy in volatile markets.
Settings
Stochastic Period (45): Sets the period for calculating the Stochastic range (highest high - lowest low).
Fast EMA Period (12): Period of the fast EMA used in the MACD.
Slow EMA Period (26): Period of the slow EMA used in the MACD.
Signal Line Period (9): Period of the EMA of the signal line.
Overbought/Oversold Levels (1.0/-1.0): Thresholds for identifying extreme conditions in the MACD.
ATR Period (14): Period for calculating the Renko brick size.
ATR Multiplier (1.0): Adjusts the Renko brick size.
Show Histogram: Enables/disables the histogram.
Show Renko Markers: Enables/disables the Renko direction arrows.
How to Use
MACD Crossovers: A MACD crossover above the signal line indicates potential bullishness, while below suggests bearishness.
Histogram: Fuchsia bars indicate bullish momentum; purple bars indicate bearish momentum.
Renko Arrows: Green arrows (upward triangle) signal a change to an uptrend; red arrows (downward triangle) signal a downtrend.
Overbought/Oversold Levels: Use the levels to identify potential reversals when the MACD reaches extreme values.
Notes
The chart should be set up with this indicator in isolation for better clarity.
Adjust the periods and ATR multiplier according to the asset and timeframe used.
Use the built-in alerts ("Renko Up Signal" and "Renko Down Signal") to set up notifications of direction changes.
This indicator is ideal for day traders and swing traders who want a visually clear and functional tool for trading based on momentum and trends.
Jesus Vix Spike ComboThis script will:
Show you vix spikes with your 4 different settings.
Draw a white line at the start of each vix.
Draw a dotted green line for 3 spikes in 6 minutes.
Draw a dotted pink line for 3 spikes in 16 minutes.
Draw a green line extending right if it takes out a past low in the last 200 bars plus a spike.
It will also:
Place a white dot on the 5th candle if the price rises past the vix starting point,
a white omega sign on the 6th candle if price rises past the vix starting point,
and a large white dot on the 7th candle past the vix starting point if the price is higher.
It will also:
Show higher time frame EMAs and other emas.
Has some alerts added also.
I have only been using this on the 1 minute chart with $OANDA:SPX500USD.
Ill write about the strategy I use for this soon. But basically you wait for a drop and for some prominent lows to be taken out, then a vix, then your white dot, omega then the large white dot to enter, expect a 100% expansion from the vix low. More aggressive entry's would be the first white dot or 3 green candles in a row. Backtest to see.
Thanks for checking it out. Let me know if it can be better.
The original script is from Xxattaxx and Christ Moody I believe, thank you for sharing all your hard work.
Range Filter Strategy with ATR TP/SLHow This Strategy Works:
Range Filter:
Calculates a smoothed average (SMA) of price
Creates upper and lower bands based on standard deviation
When price crosses above upper band, it signals a potential uptrend
When price crosses below lower band, it signals a potential downtrend
ATR-Based Risk Management:
Uses Average True Range (ATR) to set dynamic take profit and stop loss levels
Take profit is set at entry price + (ATR × multiplier) for long positions
Stop loss is set at entry price - (ATR × multiplier) for long positions
The opposite applies for short positions
Input Parameters:
Adjustable range filter length and multiplier
Customizable ATR length and TP/SL multipliers
All parameters can be optimized in TradingView's strategy tester
You can adjust the input parameters to fit your trading style and the specific market you're trading. The ATR-based exits help adapt to current market volatility.
Range Filter + ATR Strategy (Low Drawdown)Key Features for Low Drawdown:
Range Filter: Identifies trends while filtering out market noise
ATR-based Position Sizing: Adjusts position size based on volatility to risk a fixed percentage of capital
Trailing Stops: Uses ATR-based trailing stops to lock in profits and limit losses
Conservative Risk Parameters: Defaults to 1% risk per trade (adjustable)
Trend Confirmation: Requires two consecutive closes above/below the range filter
How to Use:
The strategy enters long when price is above the upper range filter for two consecutive bars
Enters short when price is below the lower range filter for two consecutive bars
Uses ATR to size positions appropriately for current volatility
Implements trailing stops based on ATR to protect profits
Optimization Tips:
Adjust the Range Filter period based on your timeframe
Modify the risk percentage (1% is conservative)
Tweak the ATR multiple for trailing stops (1.5 is moderate)
Consider adding a time-based exit if drawdown is still too high
Median True Range {Darkoexe}Simple and sweet, this is the median true range. It reviews the size of the previous period amount of candles, and displays the candle size value that is the median of those previous values.
//Darkoexe
Chess Game🧠 Concept
This script is an experimental chess game simulation built entirely in Pine Script, rendered as an overlay on a trading chart. It does not support interactivity like mouse clicks or real-time move detection, but instead relies on manual inputs to simulate moves and visualize board state.
This was created purely for educational purposes—to test the creative boundaries of Pine Script and explore how far visual scripting can be pushed within the limits of a financial charting tool.
🎯 Goals
Render a full 8×8 chessboard with labeled rows (1–8) and columns (a–h)
Display all pieces using Unicode chess symbols
Allow users to simulate moves using manual input
Validate basic move legality
Display turn status, current move, and instructions
🔧 How It Works
Chessboard Rendering
Uses tabel.new() to display 64 tiles and corresponding pieces.
Light and dark squares alternate based on standard chessboard layout logic ((row + column) % 2).
Pieces
All pieces (white and black) are placed at their initial positions using Unicode characters:
♙ ♖ ♘ ♗ ♕ ♔ for White
♟︎ ♜ ♞ ♝ ♛ ♚ for Black
⚠️ Limitations
Pine Script is not a general-purpose programming language. This game is non-interactive and must be controlled using input.int() and input.bool() for every move.
No click or drag-and-drop functionality.No timers, clocks, or multiplayer.No automated check/checkmate detection (yet!).No visual indication of selected squares (though that could be added with color-coded highlights)
📌 Why I Built This
TradingView is made for charting markets, but I wanted to see how far I could stretch it. Chess is grid-based like many financial charts, so I challenged myself to bring chess logic into Pine Script just for fun and learning.
