TradersFriendCandles v2
TradersFriendCandles
A fully customizable candle‑color and banding indicator built on percentile + ATR, with optional EMA vs. ALMA trend filtering and higher‑timeframe support.
Key Features
Dynamic Percentile Center Line
Compute any Nth percentile over M bars (default 20th over 15) to serve as a reference “mid‑price” level.
ATR‑Based Bands
Envelope that percentile line with upper/lower bands at X × ATR (default 1×), plus an extended upper band at 3.5× ATR.
Higher‑Timeframe Mode
Plot bands based on a higher timeframe (e.g. daily bands on a 15m chart) so you can gauge macro support/resistance in micro timeframes.
Custom‑Color Candles
5 user‑editable colors for:
Strong bullish
Light bullish
Neutral
Light bearish
Strong bearish
Optional EMA vs. ALMA Trend Filter
When enabled, candles simply turn “bull” or “bear” based on fast EMA crossing above/below slow ALMA.
Border‑Only Coloring
Keep candle bodies transparent and color only the border & wick.
Live Plot Labels & Track Price
All lines carry titles and can display current values directly on the price scale.
Alerts
Strong Bull Breakout (price stays above upper band)
Strong Bear Breakdown (price closes below lower band)
EMA/ALMA crossovers
Inputs & Customization
Percentile level & lookback length
ATR length, multiplier, opacity
Fast EMA length, ALMA parameters (offset, length, sigma)
Toggle bands, lines, custom candles, higher‑timeframe mode
Pick your own colors via color‑picker inputs
Use TradersFriendCandles to visualize momentum shifts, dynamic support/resistance, and trend strength all in one overlay. Perfect for pinpointing breakouts, breakdowns, and filtering noise with adjustable sensitivity.
Médias Móveis
Candle % High/Low Bar + HL Order + MA by Barty&PitPapcioWhat does the indicator show?
The "Candle % High/Low Bar + HL Order + MA by Barty&PitPapcio" indicator displays the percentage deviation of each candle’s high and low relative to its open price. The zero line represents the candle’s open — bars above zero show upward movement from the open (to high), bars below zero show downward movement (to low).
Additionally, the indicator plots a dot above or below each bar indicating which came first during the candle — the high or the low — based on data from a lower timeframe two steps below the current chart (for example, on a 1-hour chart it uses 15-minute data).
Finally, the indicator calculates and plots a user-selectable moving average (EMA, SMA, or WMA) of these "first high or low" signals, helping identify trends whether the first move is more often upwards or downwards.
Where do the data come from?
Percentage values are calculated directly from the current chart’s candles:
highPerc=(High−Open)/Open×100%,
lowPerc=(Low−Open)/Open×100%
The timing of the first high or low for each candle is retrieved from a lower timeframe, stepping down two levels from the current timeframe (e.g. from 1H to 15 min), providing better precision in detecting the order of highs and lows that may be blurred on higher timeframes.
Additional features:
Full customization of colors for bars, dots, zero line, grid, and thicknesses.
Background grid with adjustable scale and style.
Safety checks for missing lower timeframe data.
A moving average smoothing the sequence of first high/low signals to reveal directional tendencies.
Suggested strategy for technical analysis support
Identify dominant candle direction: If the dot often appears above the bar (first high), it indicates buying pressure; if below (first low), selling pressure dominates.
Use percentage deviations: Large percent bars indicate heightened volatility and potential reversal points.
Moving average on order signals: The EMA of high/low first signals smooths the noise, showing the dominant trend in the sequence of price moves, useful for filtering other signals.
Combine with other tools: This indicator can act as a directional filter on multiple timeframes, synergizing well with momentum indicators, RSI, or support/resistance levels to confirm move strength.
Lots of love, Bartosz
CANX MA Crossover© CanxStixTrader
Moving average crossover systems measure drift in the market. They are great strategies for time-limited traders. KEEP IT SIMPLE
This strategy works both for buys and sells using the reaction line to guide your position against the reactions.
HOW TO USE THE INDICATOR
1) Choose your market and timeframe.
2) Choose the length.
3) Choose the multiplier.
4) Choose if the strategy is long-only or bidirectional (longs & shorts).
TIPS
The strategy works best in bullish markets as that is the primary direction that market such as stocks, indexes and metals like to move.
- Increase the multiplier to reduce whipsaws
- Increase the length to take fewer trades
- Decrease the length to take more trades
- Try a Long-Only strategy to see if that performs better.
The base set up when you load the indicator is for the 1 minute chart on gold. We found that it also works well on the US Indexes. For other markets you may need to change the length and multiplier to suit the market and back test its results.
Multi Moving Average with CustomizationCore Functionality
The indicator allows you to display up to 5 different moving averages on your chart simultaneously.
Each moving average can be fully customized with its own settings.
You can choose between
1. Simple Moving Average (SMA),
2. Exponential Moving Average (EMA)
3. Weighted Moving Average (WMA) types
Multi-Timeframe Support
One standout feature is the ability to display higher timeframe moving averages on lower timeframe charts.
For example, you can show a 200 EMA from the daily chart while viewing a 15-minute chart.
Advanced Visualization Features
The indicator includes several visualization enhancements:
1. MA Cloud - Creates a filled area between any two selected moving averages. The cloud automatically changes color based on which MA is on top - typically green when the faster MA is above (bullish) and red when below (bearish).
2. Golden/Death Cross Detection - Automatically detects and marks important MA crossover events:
* Golden Cross: When a shorter-term MA crosses above a longer-term MA (bullish signal)
* Death Cross: When a shorter-term MA crosses below a longer-term MA (bearish signal)
3. Trend Background - Colors the entire chart background based on whether price is above or below a specified MA, giving a clear visual indicator of the overall trend.
Alert System
The indicator can generate alerts when price crosses above or below any selected moving average. This feature is useful for automated trading signals or notifications, and can be configured to trigger once per bar.
Flexible Architecture
The code uses several programming techniques to maximize flexibility:
* Switch statements for selecting MA types and cloud values
* Conditional logic throughout the code
* Function abstraction for calculating MAs and handling multi-timeframe display
* String identifiers to select which MAs to use for cloud visualization
Unique Technical Aspects
1. The multi-timeframe plotting function solves the common problem of higher timeframe MAs looking distorted on lower timeframe charts.
2. The cloud feature uses string identifiers to select which MAs to use, allowing for any combination.
3. The indicator employs smart conditional logic to handle complex decision trees efficiently.
4. Every visual aspect (colors, line widths, display conditions) is customizable through the settings.
This indicator combines multiple technical analysis tools into a single, highly configurable package that can adapt to different trading styles and timeframes.
Its ability to correctly display higher timeframe MAs on lower timeframe charts makes it particularly valuable for traders who analyze multiple timeframes simultaneously.
Adaptive Dual MA Trend FilterAdaptive Dual MA Trend Filter is a versatile Pine Script™ indicator that delivers clear, reliable trend signals using customizable moving averages:
Dual‑Stage Filtering – Apply any traditional MA (SMA, EMA, VWMA, HMA, RMA, TEMA, DEMA, FRAMA, TRIMA) or advanced smoothing (ALMA, T3) as your “main” and “filter” MAs. The filter MA is double‑smoothed for noise suppression, then converted into a robust “double‑filtered” baseline.
Flexible Inputs – Select lengths, sources (close, high, low, hl2), offsets, sigma, and volume factors to tailor the responsiveness and smoothness to your favorite timeframe or asset class.
Intuitive Signals – The script detects confirmed bullish (green) and bearish (red) trend shifts as:
Circle marker on the MA line
Triangle arrows below/above bars
Full candles and MA line colored by current trend
Clean Overlay – Works directly on your price chart, with optional semi‑transparent fills for extra visual clarity.
Theme Support – Choose from Vibrant, Pastel, Neon, Classic, Monochrome, Solarized, or Material palettes for seamless chart styling.
Ideal for swing traders and intraday scalpers alike, Multi‑Source Double‑Filter Trend offers both “set‑and‑forget” simplicity and deep customization for power users.
Usage
Add to chart → Inputs → tweak MA types/lengths
Watch for color changes and markers
Combine with volume or momentum filters for entry confirmation
Enjoy clearer trend identification and smoother trade signals!
Disclaimer
This script is for educational and informational purposes only. Not financial advice. Use at your own risk.
UT Bot + Hull MA Confirmed Signal DelayOverview
This indicator is designed to detect high-probability reversal entry signals by combining "UT Bot Alerts" (UT Bot Alerts script adapted from QuantNomad - Originally developed by Yo_adriiiiaan and idea of original code for "UT Bot Alerts" from HPotter ) with confirmation from a Hull Moving Average (HMA) Developed by Alan Hull . It focuses on capturing momentum shifts that often precede trend reversals, helping traders identify potential entry points while filtering out false signals.
🔍 How It Works
This strategy operates in two stages:
1. UT Bot Momentum Trigger
The foundation of this script is the "UT Bot Alerts" , which uses an ATR-based trailing stop to detect momentum changes. Specifically:
The script calculates a dynamic stop level based on the Average True Range (ATR) multiplied by a user-defined sensitivity factor (Key Value).
When price closes above this trailing stop and the short-term EMA crosses above the stop, a potential buy setup is triggered.
Conversely, when price closes below the trailing stop and the short-term EMA crosses below, a potential sell setup is triggered.
These UT Bot alerts are designed to identify the initial shift in market direction, acting as the first filter in the signal process.
2. Hull MA Confirmation
To reduce noise and false triggers from the UT Bot alone, this script delays the entry signal until price confirms the move by crossing the Hull Moving Average (or its variants: HMA, THMA, EHMA) in the same direction as the UT Bot trigger:
A Buy Signal is generated only when:
A UT Bot Buy condition is active, and
The price closes above the Hull MA.
Or, if a UT Bot Buy condition was recently triggered but price hadn’t yet crossed above the Hull MA, a delayed buy is signaled when price finally breaks above it.
A Sell Signal is generated only when:
A UT Bot Sell condition is active, and
The price closes below the Hull MA.
Similarly, a delayed sell signal can occur if price breaks below the Hull MA shortly after a UT Bot Sell trigger.
This dual-confirmation process helps traders avoid premature entries and improves the reliability of reversal signals.
📈 Best Use Cases
Reversal Trading: This strategy is particularly well-suited for catching early trend reversals rather than trend continuations. It excels at identifying momentum pivots that occur after pullbacks or exhaustion moves.
Heikin Ashi Charts Recommended: The script offers a Heikin Ashi mode for smoothing out noise and enhancing visual clarity. Using Heikin Ashi candles can further reduce whipsaws and highlight cleaner shifts in trend direction.
MACD Alignment: For best results, trade in the direction of the MACD trend or use it as a filter to avoid counter-trend trades.
⚠️ Important Notes
Entry Signals Only: This indicator only plots entry points (Buy and Sell signals). It does not define exit strategies, so users should manage trades manually using trailing stops, profit targets, or other exit indicators.
No Signal = No Confirmation: You may see a UT Bot trigger without a corresponding Buy/Sell signal. This means the price did not confirm the move by crossing the Hull MA, and therefore the setup was considered too weak or incomplete.
⚙️ Customization
UT Bot Sensitivity: Adjust the “Key Value” and “ATR Period” to make the UT Bot more or less reactive to price action.
Use Heikin Ashi: Toggle between standard candles or Heikin Ashi in the indicator settings for a smoother trading experience.
The HMA length may also be modified in the indicator settings from its standard 55 length to increase or decrease the sensitivity of signal.
This strategy is best used by traders looking for a structured, logic-based way to enter early into reversals with added confirmation to reduce risk. By combining two independent systems—momentum detection (UT Bot) and trend confirmation (Hull MA)—it aims to provide high-confidence entries without overwhelming complexity.
Let the indicator guide your entries—you manage the exits.
Examples of use:
Futures:
Stock:
Crypto:
As shown in the snapshots this strategy, like most, works the best when price action has a sizeable ATR and works the least when price is choppy. Therefore it is always best to use this system when price is coming off known support or resistance levels and when it is seen to respect short term EMA's like the 9 or 15.
My personal preference to use this system is for day trading on a 3 or 5 minute chart. But it is valid for all timeframes and simply marks a high probability for a new trend to form.
Sources:
Quant Nomad - www.tradingview.com
Yo_adriiiiaan - www.tradingview.com
HPotter - www.tradingview.com
Hull Moving Average - alanhull.com
EMA 10/20/50 Alignment Strategy### 📘 **Strategy Name**
**EMA 10/20/50 Trend Alignment Strategy**
---
### 📝 **Description (for Publishing)**
This strategy uses the alignment of Exponential Moving Averages (EMAs) to identify strong bullish trends. It enters a long position when the short-term EMA is above the mid-term EMA, which is above the long-term EMA — a classic sign of trend strength.
#### 🔹 Entry Criteria:
* **EMA10 > EMA20 > EMA50**: A bullish alignment that signals momentum in an upward direction.
* The strategy enters a **long position** when this alignment occurs.
#### 🔹 Exit Criteria:
* The long position is closed when the EMA alignment breaks (i.e., the trend weakens or reverses).
#### 🔹 Additional Features:
* Includes a **date range filter**, allowing you to backtest the strategy over a specific period.
* Uses **100% of available capital** for each trade (position size auto-scales with account balance).
* No short positions, stop loss, or take profit are applied — this is a trend-following strategy meant to ride bullish moves.
---
### ✅ Best For:
* Traders looking for a **simple, trend-based entry system**
* Testing price momentum strategies during specific market regimes
* Visualizing EMA stacking patterns in historical data
StoRsi# StoRSI Indicator: Combining RSI and Stochastic with multiTF
## Overview
The StoRSI indicator combines Relative Strength Index (RSI) and Stochastic oscillators in a single view to provide powerful momentum and trend analysis. By displaying both indicators together with multi-timeframe analysis, it helps traders identify stronger signals when both indicators align.
## Key Components
### 1. RSI (Relative Strength Index)
### 2. Stochastic Oscillator
### 3. EMA (Exponential Moving Average)
### 4. Multi-Timeframe Analysis
## Visual Features
- **Color-coded zones**: Highlights overbought/oversold areas
- **Signal backgrounds**: Shows when both indicators align
- **Multi-timeframe table**: Displays RSI, Stochastic, and trend across timeframes
- **Customizable colors**: Allows full visual customization
## Signal Generation (some need to uncomment in code)
The indicator generates several types of signals:
1. **RSI crosses**: When RSI crosses above/below overbought/oversold levels
2. **Stochastic crosses**: When Stochastic %K crosses above/below overbought/oversold levels
3. **Combined signals**: When both indicators show the same condition
4. **Trend alignment**: When multiple timeframes show the same trend direction
## Conclusion
The StoRSI indicator provides a comprehensive view of market momentum by combining two powerful oscillators with multi-timeframe analysis. By looking for alignment between RSI and Stochastic across different timeframes, traders can identify stronger signals and filter out potential false moves. The visual design makes it easy to spot opportunities at a glance, while the customizable parameters allow adaptation to different markets and trading styles.
For best results, use this indicator as part of a complete trading system that includes proper risk management, trend analysis, and confirmation from price action patterns.
Smart Fib StrategySmart Fibonacci Strategy
This advanced trading strategy combines the power of adaptive SMA entries with Fibonacci-based exit levels to create a comprehensive trend-following system that self-optimizes based on historical market conditions. Credit goes to Julien_Eche who created the "Best SMA Finder" which received an Editors Pick award.
Strategy Overview
The Smart Fibonacci Strategy employs a two-pronged approach to trading:
1. Intelligent Entries: Uses a self-optimizing SMA (Simple Moving Average) to identify optimal entry points. The system automatically tests multiple SMA lengths against historical data to determine which period provides the most robust trading signals.
2. Fibonacci-Based Exits: Implements ATR-adjusted Fibonacci bands to establish precise exit targets, with risk-management options ranging from conservative to aggressive.
This dual methodology creates a balanced system that adapts to changing market conditions while providing clear visual reference points for trade management.
Key Features
- **Self-Optimizing Entries**: Automatically calculates the most profitable SMA length based on historical performance
- **Adjustable Risk Parameters**: Choose between low-risk and high-risk exit targets
- **Directional Flexibility**: Trade long-only, short-only, or both directions
- **Visualization Tools**: Customizable display of entry lines and exit bands
- **Performance Statistics**: Comprehensive stats table showing key metrics
- **Smoothing Option**: Reduces noise in the Fibonacci bands for cleaner signals
Trading Rules
Entry Signals
- **Long Entry**: When price crosses above the blue center line (optimal SMA)
- **Short Entry**: When price crosses below the blue center line (optimal SMA)
### Exit Levels
- **Low Risk Option**: Exit at the first Fibonacci band (1.618 * ATR)
- **High Risk Option**: Exit at the second Fibonacci band (2.618 * ATR)
Strategy Parameters
Display Settings
- Toggle visibility of the stats table and indicator components
Strategy Settings
- Select trading direction (long, short, or both)
- Choose exit method (low risk or high risk)
- Set minimum trades threshold for SMA optimization
SMA Settings
- Option to use auto-optimized or fixed-length SMA
- Customize SMA length when using fixed option
Fibonacci Settings
- Adjust ATR period and SMA basis for Fibonacci bands
- Enable/disable smoothing function
- Customize Fibonacci ratio multipliers
Appearance Settings
- Modify colors, line widths, and transparency
Optimization Methodology
The strategy employs a sophisticated optimization algorithm that:
1. Tests multiple SMA lengths against historical data
2. Evaluates performance based on trade count, profit factor, and win rate
3. Calculates a "robustness score" that balances profitability with statistical significance
4. Selects the SMA length with the highest robustness score
This ensures that the strategy's entry signals are continuously adapting to the most effective parameters for current market conditions.
Risk Management
Position sizing is fixed at $2,000 per trade, allowing for consistent exposure across all trading setups. The Fibonacci-based exit system provides two distinct risk management approaches:
- **Conservative Approach**: Using the first Fibonacci band for exits produces more frequent but smaller wins
- **Aggressive Approach**: Using the second Fibonacci band allows for larger potential gains at the cost of increased volatility
Ideal Usage
This strategy is best suited for:
- Trending markets with clear directional moves
- Timeframes from 4H to Daily for most balanced results
- Instruments with moderate volatility (stocks, forex, commodities)
Traders can further enhance performance by combining this strategy with broader market analysis to confirm the prevailing trend direction.
Smooth Fibonacci BandsSmooth Fibonacci Bands
This indicator overlays adaptive Fibonacci bands on your chart, creating dynamic support and resistance zones based on price volatility. It combines a simple moving average with ATR-based Fibonacci levels to generate multiple bands that expand and contract with market conditions.
## Features
- Creates three pairs of upper and lower Fibonacci bands
- Smoothing option for cleaner, less noisy bands
- Fully customizable colors and line thickness
- Adapts automatically to changing market volatility
## Settings
Adjust the SMA and ATR lengths to match your trading timeframe. For short-term trading, try lower values; for longer-term analysis, use higher values. The Fibonacci factors determine how far each band extends from the center line - standard Fibonacci ratios (1.618, 2.618, and 4.236) are provided as defaults.
## Trading Applications
- Use band crossovers as potential entry and exit signals
- Look for price bouncing off bands as reversal opportunities
- Watch for price breaking through multiple bands as strong trend confirmation
- Identify potential support/resistance zones for placing stop losses or take profits
Fibonacci Bands combines the reliability of moving averages with the adaptability of ATR and the natural market harmony of Fibonacci ratios, offering a robust framework for both trend and range analysis.
Why EMA Isn't What You Think It IsMany new traders adopt the Exponential Moving Average (EMA) believing it's simply a "better Simple Moving Average (SMA)". This common misconception leads to fundamental misunderstandings about how EMA works and when to use it.
EMA and SMA differ at their core. SMA use a window of finite number of data points, giving equal weight to each data point in the calculation period. This makes SMA a Finite Impulse Response (FIR) filter in signal processing terms. Remember that FIR means that "all that we need is the 'period' number of data points" to calculate the filter value. Anything beyond the given period is not relevant to FIR filters – much like how a security camera with 14-day storage automatically overwrites older footage, making last month's activity completely invisible regardless of how important it might have been.
EMA, however, is an Infinite Impulse Response (IIR) filter. It uses ALL historical data, with each past price having a diminishing - but never zero - influence on the calculated value. This creates an EMA response that extends infinitely into the past—not just for the last N periods. IIR filters cannot be precise if we give them only a 'period' number of data to work on - they will be off-target significantly due to lack of context, like trying to understand Game of Thrones by watching only the final season and wondering why everyone's so upset about that dragon lady going full pyromaniac.
If we only consider a number of data points equal to the EMA's period, we are capturing no more than 86.5% of the total weight of the EMA calculation. Relying on he period window alone (the warm-up period) will provide only 1 - (1 / e^2) weights, which is approximately 1−0.1353 = 0.8647 = 86.5%. That's like claiming you've read a book when you've skipped the first few chapters – technically, you got most of it, but you probably miss some crucial early context.
▶️ What is period in EMA used for?
What does a period parameter really mean for EMA? When we select a 15-period EMA, we're not selecting a window of 15 data points as with an SMA. Instead, we are using that number to calculate a decay factor (α) that determines how quickly older data loses influence in EMA result. Every trader knows EMA calculation: α = 1 / (1+period) – or at least every trader claims to know this while secretly checking the formula when they need it.
Thinking in terms of "period" seriously restricts EMA. The α parameter can be - should be! - any value between 0.0 and 1.0, offering infinite tuning possibilities of the indicator. When we limit ourselves to whole-number periods that we use in FIR indicators, we can only access a small subset of possible IIR calculations – it's like having access to the entire RGB color spectrum with 16.7 million possible colors but stubbornly sticking to the 8 basic crayons in a child's first art set because the coloring book only mentioned those by name.
For example:
Period 10 → alpha = 0.1818
Period 11 → alpha = 0.1667
What about wanting an alpha of 0.17, which might yield superior returns in your strategy that uses EMA? No whole-number period can provide this! Direct α parameterization offers more precision, much like how an analog tuner lets you find the perfect radio frequency while digital presets force you to choose only from predetermined stations, potentially missing the clearest signal sitting right between channels.
Sidenote: the choice of α = 1 / (1+period) is just a convention from 1970s, probably started by J. Welles Wilder, who popularized the use of the 14-day EMA. It was designed to create an approximate equivalence between EMA and SMA over the same number of periods, even thought SMA needs a period window (as it is FIR filter) and EMA doesn't. In reality, the decay factor α in EMA should be allowed any valye between 0.0 and 1.0, not just some discrete values derived from an integer-based period! Algorithmic systems should find the best α decay for EMA directly, allowing the system to fine-tune at will and not through conversion of integer period to float α decay – though this might put a few traditionalist traders into early retirement. Well, to prevent that, most traditionalist implementations of EMA only use period and no alpha at all. Heaven forbid we disturb people who print their charts on paper, draw trendlines with rulers, and insist the market "feels different" since computers do algotrading!
▶️ Calculating EMAs Efficiently
The standard textbook formula for EMA is:
EMA = CurrentPrice × alpha + PreviousEMA × (1 - alpha)
But did you know that a more efficient version exists, once you apply a tiny bit of high school algebra:
EMA = alpha × (CurrentPrice - PreviousEMA) + PreviousEMA
The first one requires three operations: 2 multiplications + 1 addition. The second one also requires three ops: 1 multiplication + 1 addition + 1 subtraction.
That's pathetic, you say? Not worth implementing? In most computational models, multiplications cost much more than additions/subtractions – much like how ordering dessert costs more than asking for a water refill at restaurants.
Relative CPU cost of float operations :
Addition/Subtraction: ~1 cycle
Multiplication: ~5 cycles (depending on precision and architecture)
Now you see the difference? 2 * 5 + 1 = 11 against 5 + 1 + 1 = 7. That is ≈ 36.36% efficiency gain just by swapping formulas around! And making your high school math teacher proud enough to finally put your test on the refrigerator.
▶️ The Warmup Problem: how to start the EMA sequence right
How do we calculate the first EMA value when there's no previous EMA available? Let's see some possible options used throughout the history:
Start with zero : EMA(0) = 0. This creates stupidly large distortion until enough bars pass for the horrible effect to diminish – like starting a trading account with zero balance but backdating a year of missed trades, then watching your balance struggle to climb out of a phantom debt for months.
Start with first price : EMA(0) = first price. This is better than starting with zero, but still causes initial distortion that will be extra-bad if the first price is an outlier – like forming your entire opinion of a stock based solely on its IPO day price, then wondering why your model is tanking for weeks afterward.
Use SMA for warmup : This is the tradition from the pencil-and-paper era of technical analysis – when calculators were luxury items and "algorithmic trading" meant your broker had neat handwriting. We first calculate an SMA over the initial period, then kickstart the EMA with this average value. It's widely used due to tradition, not merit, creating a mathematical Frankenstein that uses an FIR filter (SMA) during the initial period before abruptly switching to an IIR filter (EMA). This methodology is so aesthetically offensive (abrupt kink on the transition from SMA to EMA) that charting platforms hide these early values entirely, pretending EMA simply doesn't exist until the warmup period passes – the technical analysis equivalent of sweeping dust under the rug.
Use WMA for warmup : This one was never popular because it is harder to calculate with a pencil - compared to using simple SMA for warmup. Weighted Moving Average provides a much better approximation of a starting value as its linear descending profile is much closer to the EMA's decay profile.
These methods all share one problem: they produce inaccurate initial values that traders often hide or discard, much like how hedge funds conveniently report awesome performance "since strategy inception" only after their disastrous first quarter has been surgically removed from the track record.
▶️ A Better Way to start EMA: Decaying compensation
Think of it this way: An ideal EMA uses an infinite history of prices, but we only have data starting from a specific point. This creates a problem - our EMA starts with an incorrect assumption that all previous prices were all zero, all close, or all average – like trying to write someone's biography but only having information about their life since last Tuesday.
But there is a better way. It requires more than high school math comprehension and is more computationally intensive, but is mathematically correct and numerically stable. This approach involves compensating calculated EMA values for the "phantom data" that would have existed before our first price point.
Here's how phantom data compensation works:
We start our normal EMA calculation:
EMA_today = EMA_yesterday + α × (Price_today - EMA_yesterday)
But we add a correction factor that adjusts for the missing history:
Correction = 1 at the start
Correction = Correction × (1-α) after each calculation
We then apply this correction:
True_EMA = Raw_EMA / (1-Correction)
This correction factor starts at 1 (full compensation effect) and gets exponentially smaller with each new price bar. After enough data points, the correction becomes so small (i.e., below 0.0000000001) that we can stop applying it as it is no longer relevant.
Let's see how this works in practice:
For the first price bar:
Raw_EMA = 0
Correction = 1
True_EMA = Price (since 0 ÷ (1-1) is undefined, we use the first price)
For the second price bar:
Raw_EMA = α × (Price_2 - 0) + 0 = α × Price_2
Correction = 1 × (1-α) = (1-α)
True_EMA = α × Price_2 ÷ (1-(1-α)) = Price_2
For the third price bar:
Raw_EMA updates using the standard formula
Correction = (1-α) × (1-α) = (1-α)²
True_EMA = Raw_EMA ÷ (1-(1-α)²)
With each new price, the correction factor shrinks exponentially. After about -log₁₀(1e-10)/log₁₀(1-α) bars, the correction becomes negligible, and our EMA calculation matches what we would get if we had infinite historical data.
This approach provides accurate EMA values from the very first calculation. There's no need to use SMA for warmup or discard early values before output converges - EMA is mathematically correct from first value, ready to party without the awkward warmup phase.
Here is Pine Script 6 implementation of EMA that can take alpha parameter directly (or period if desired), returns valid values from the start, is resilient to dirty input values, uses decaying compensator instead of SMA, and uses the least amount of computational cycles possible.
// Enhanced EMA function with proper initialization and efficient calculation
ema(series float source, simple int period=0, simple float alpha=0)=>
// Input validation - one of alpha or period must be provided
if alpha<=0 and period<=0
runtime.error("Alpha or period must be provided")
// Calculate alpha from period if alpha not directly specified
float a = alpha > 0 ? alpha : 2.0 / math.max(period, 1)
// Initialize variables for EMA calculation
var float ema = na // Stores raw EMA value
var float result = na // Stores final corrected EMA
var float e = 1.0 // Decay compensation factor
var bool warmup = true // Flag for warmup phase
if not na(source)
if na(ema)
// First value case - initialize EMA to zero
// (we'll correct this immediately with the compensation)
ema := 0
result := source
else
// Standard EMA calculation (optimized formula)
ema := a * (source - ema) + ema
if warmup
// During warmup phase, apply decay compensation
e *= (1-a) // Update decay factor
float c = 1.0 / (1.0 - e) // Calculate correction multiplier
result := c * ema // Apply correction
// Stop warmup phase when correction becomes negligible
if e <= 1e-10
warmup := false
else
// After warmup, EMA operates without correction
result := ema
result // Return the properly compensated EMA value
▶️ CONCLUSION
EMA isn't just a "better SMA"—it is a fundamentally different tool, like how a submarine differs from a sailboat – both float, but the similarities end there. EMA responds to inputs differently, weighs historical data differently, and requires different initialization techniques.
By understanding these differences, traders can make more informed decisions about when and how to use EMA in trading strategies. And as EMA is embedded in so many other complex and compound indicators and strategies, if system uses tainted and inferior EMA calculatiomn, it is doing a disservice to all derivative indicators too – like building a skyscraper on a foundation of Jell-O.
The next time you add an EMA to your chart, remember: you're not just looking at a "faster moving average." You're using an INFINITE IMPULSE RESPONSE filter that carries the echo of all previous price actions, properly weighted to help make better trading decisions.
EMA done right might significantly improve the quality of all signals, strategies, and trades that rely on EMA somewhere deep in its algorithmic bowels – proving once again that math skills are indeed useful after high school, no matter what your guidance counselor told you.
Consecutive Candles Above/Below EMADescription:
This indicator identifies and highlights periods where the price remains consistently above or below an Exponential Moving Average (EMA) for a user-defined number of consecutive candles. It visually marks these sustained trends with background colors and labels, helping traders spot strong bullish or bearish market conditions. Ideal for trend-following strategies or identifying potential trend exhaustion points, this tool provides clear visual cues for price behavior relative to the EMA.
How It Works:
EMA Calculation: The indicator calculates an EMA based on the user-specified period (default: 100). The EMA is plotted as a blue line on the chart for reference.
Consecutive Candle Tracking: It counts how many consecutive candles close above or below the EMA:
If a candle closes below the EMA, the "below" counter increments; any candle closing above resets it to zero.
If a candle closes above the EMA, the "above" counter increments; any candle closing below resets it to zero.
Highlighting Trends: When the number of consecutive candles above or below the EMA meets or exceeds the user-defined threshold (default: 200 candles):
A translucent red background highlights periods where the price has been below the EMA.
A translucent green background highlights periods where the price has been above the EMA.
Labeling: When the required number of consecutive candles is first reached:
A red downward arrow label with the text "↓ Below" appears for below-EMA streaks.
A green upward arrow label with the text "↑ Above" appears for above-EMA streaks.
Usage:
Trend Confirmation: Use the highlights and labels to confirm strong trends. For example, 200 candles above the EMA may indicate a robust uptrend.
Reversal Signals: Prolonged streaks (e.g., 200+ candles) might suggest overextension, potentially signaling reversals.
Customization: Adjust the EMA period to make it faster or slower, and modify the candle count to make the indicator more or less sensitive to trends.
Settings:
EMA Length: Set the period for the EMA calculation (default: 100).
Candles Count: Define the minimum number of consecutive candles required to trigger highlights and labels (default: 200).
Visuals:
Blue EMA line for tracking the moving average.
Red background for sustained below-EMA periods.
Green background for sustained above-EMA periods.
Labeled arrows to mark when the streak threshold is met.
This indicator is a powerful tool for traders looking to visualize and capitalize on persistent price trends relative to the EMA, with clear, customizable signals for market analysis.
Explain EMA calculation
Other trend indicators
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ADX EMA's DistanceIt is well known to technical analysts that the price of the most volatile and traded assets do not tend to stay in the same place for long. A notable observation is the recurring pattern of moving averages that tend to move closer together prior to a strong move in some direction to initiate the trend, it is precisely that distance that is measured by the blue ADX EMA's Distance lines on the chart, normalized and each line being the distance between 2, 3 or all 4 moving averages, with the zero line being the point where the distance between them is zero, but it is also necessary to know the direction of the movement, and that is where the modified ADX will be useful.
This is the well known Directional Movement Indicator (DMI), where the +DI and -DI lines of the ADX will serve to determine the direction of the trend.
MK Multi-Timeframe MA RibbonThe MK Ribbon MTF is an overlay indicator that lets you plot up to eight independently configurable moving averages on any chart.
For each MA you can choose its length, type (EMA, SMA, WMA, or HMA), timeframe (current chart, Daily, Weekly, or Monthly), and easily toggle it on or off. Each MA line colors itself above, below, or equal to price—green, red, or gray by default—and you can freely customize those colors to suit your theme.
You also get optional semi-transparent “Golden Cross” and “Death Cross” labels for daily 50/200 SMA crossovers, which you can enable or disable separately, so you can tailor the ribbon and signals exactly to your workflow.
A.K Dynamic EMA/SMA / MTF S&R Zones Toolkit with AlertsThe A.K Dynamic EMA/SMA / MTF Support & Resistance Zones Toolkit is a powerful all-in-one technical analysis tool designed for traders who want a clean yet comprehensive market view. Whether you're scalping lower timeframes or swing trading higher timeframes, this indicator gives you both the structure and signals to take action with confidence.
Key Features:
✅ Customizable EMA/SMA Suite
Display key Exponential and Simple Moving Averages including 5, 9, 20, 50, 100, and 200 EMAs, plus optional 50 SMA for trend filtering. Each line can be toggled individually and color-customized.
✅ Multi-Timeframe Support & Resistance Zones
Automatically detects dynamic S/R zones on key timeframes (5min, 15min, 30min, 1H, 4H, 1D) using swing highs/lows. Zones are color-coded by strength and whether they're broken or active, providing a clear visual roadmap for price reaction levels.
✅ Zone Strength & Break Detection
Distinguishes between strong and weak zones based on price proximity and reaction depth, with visual shading and automatic label updates when a level is broken.
✅ Price Action-Based Buy/Sell Signals
Generates BUY signals when bullish candles react to strong support (supply) zones, and SELL signals when bearish candles react to strong resistance (demand) zones. All logic is adjustable — including candle body vs wick detection, tolerance range, and strength thresholds.
✅ Alerts Engine
Built-in TradingView alerts for price touching support/resistance or triggering buy/sell signals. Perfect for automation or hands-free monitoring.
✅ Optional Candle & Trend Filters
Highlight bullish/bearish candles visually for additional confirmation.
Optional RSI display and 50-period SMA trend filter to guide directional bias.
🧠 Use Case Scenarios:
Identify dynamic supply & demand zones across multiple timeframes.
Confirm trend direction with EMAs and SMA filters.
React quickly to clean BUY/SELL signals based on actual price interaction with strong zones.
Customize it fully to suit scalping, day trading, or swing trading strategies.
📌 Recommended Settings:
Use default zone transparency (65%) and offset (250 bars) for optimal visual clarity.
Enable alerts to get notified when price enters key S/R levels or when a trade signal occurs.
Combine this tool with your entry/exit plan for better decision-making under pressure.
💡 Pro Tip: Add this indicator to a clean chart and let the zones + EMAs guide your directional bias. Use alerts to avoid screen-watching and improve discipline.
Created by:
Version: Pine Script v6
Platform: TradingView
Moving Average Candles**Moving Average Candles — MA-Based Smoothed Candlestick Overlay**
This script replaces traditional price candles with smoothed versions calculated using various types of moving averages. Instead of plotting raw price data, each OHLC component (Open, High, Low, Close) is independently smoothed using your selected moving average method.
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### 📌 Features:
- Choose from 13 MA types: `SMA`, `EMA`, `RMA`, `WMA`, `VWMA`, `HMA`, `T3`, `DEMA`, `TEMA`, `KAMA`, `ZLEMA`, `McGinley`, `EPMA`
- Fully configurable moving average length (1–1000)
- Color-coded candles based on smoothed Open vs Close
- Works directly on price charts as an overlay
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### 🎯 Use Cases:
- Visualize smoothed market structure more clearly
- Reduce noise in price action for better trend analysis
- Combine with other indicators or strategies for confluence
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> ⚠️ **Note:** Since all OHLC values are based on moving averages, these candles do **not** represent actual market trades. Use them for trend and structure analysis, not trade entries based on precise levels.
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*Created to support traders seeking a cleaner visual representation of price dynamics.*
Rube Goldberg Top/Bottom Finder [theUltimator5]This is what I call the Rube Goldberg Top and Bottom Finder. It is an overly complex method of plotting a simple buy or sell label on a chart.
I utilize several standard TA techniques along with several of my own to try and locate ideal Buy/Sell conditions. I came up with the name because there are way too many conditional variables to come up with a single buy or sell condition, when most standard indicators use simple crossovers or levels.
There are two unique triggers that are calculated using completely independent techniques. If both triggers turn true within a small timeframe between each other, the buy/sell trigger turns true and plots a "buy" or "sell" label on the chart.
This indicator was designed to be fully functioning out of the box and can be customized only if the user wishes to. It is effective on all timeframes, but longer timeframes (daily +) may require signal length adjustment for best results.
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The signals used in the leading trigger are as follows:
(1)RSI
The user can select among any of the following moving averages (base is EMA) (#3) , and have an RSI generated at a user defined length (base is 14). (#4)
SMA, EMA, DEMA, TEMA, WMA, VWMA, SMMA, HMA, LSMA, ALMA
The user can select whether or not the RSI is filtered with the following options:
None, Kalman, Double EMA, ALMA
The filter conditions are hard coded to minimize the amount of selections that the user is required to make to reduce the user interface complexity.
The user can define overbought (base 70) and oversold (base 30) conditions. (#2)
When the RSI crosses above or below the threshold values, the plot will turn red. This creates condition 1 of the leading trigger.
(2) ADX and DI
This portion of the indicator is a derivative of my ADX Divergence and Gap Monitor indicator.
This technique looks at the ADX value as well as for spikes in either +DI or -DI for large divergences. When the ADX reaches a certain threshold and also outpaces a preset ADX moving average, this creates condition 2 of the leading trigger.
There is an additional built-in functionality in this portion of the indicator that looks for gaps. It triggers when the ADX is below a certain threshold value and either the +DI or -DI spike above a certain threshold value, indicating a sudden gap in price after a period of low volatility.
The user can set whether or nor to show when a gap appears on the chart or as a label on the plot below the chart (disabled by default) . If the user chooses to overlay gaps on the chart, it creates a horizontal fill showing the starting point of the gap. The theory here is that the price will return at some point in the near future to the starting point of the gap.
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(3) DI based Multi-Symbol reference and divergence
Part of the script computes both the +DI (positive directional index) and -DI (negative directional index) for the currently selected chart symbol and three reference symbols.
The averaged directional move of the reference symbols are compared to the current ticker on your chart and if the divergence exceeds a certain threshold, then the third condition of the trigger is met.
The components that are referenced are based on what stock/chart you are looking at. The script automatically detects if you are looking at a crypto, and uses a user selectable toggle between Large Cap or Small Cap. (#1) The threshold levels are determined by the asset type and market cap.
The leading trigger highlights under several conditions:
1) All (3) portions of the trigger result in true simultaneously
OR
2) Any of triggers 2 or 3 reach a certain threshold that indicates extreme market/price divergence as well as trigger 1 being overbought or oversold.
AND
3) If the trigger didn't highlight
For the lagging part of the trigger:
The lagging trigger is used as a confirmation after the leading trigger to indicate a possible optimized entry/exit point. It can also be used by itself, as well as the leading indicator.
The lagging indicator utilizes the parabolic Stop And Reverse (SAR). It utilizes the RSI length that is defined in portion 1 of the leading trigger as well as the overbought and oversold thresholds. I have found excellent results in catching reversals because it catches rate-of-change events rather than price reversals alone.
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When both the leading triggers FOLLOWED BY the lagging trigger result in true within a user defined timeframe, then the buy or sell trigger results in true, plotting a label on the chart.
All portions of the leading and lagging indicators can be toggled on or off, but most of them are toggled off by default in order to reduce noise on the plot.
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The leading, lagging, and buy/sell triggers each have built-in alerts that can be toggled on or off in the alert menu.
I have an optional built-in toggle to show green or red dots on the RSI line using two separate RSI lengths that are amplified and plot based on RSI divergence and strength. This can be used as a visual confirmation (or rejection) against the chart overlay plots.
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This indicator is not a strategy, so there are no built-in exits or stop losses.
Simple Volatility ConeThe Simple Volatility Cone indicator projects the potential future price range of a stock based on recent volatility. It calculates rolling standard deviation from log returns over a defined window, then uses a confidence interval to estimate the upper and lower bounds the price could reach over a future time horizon. These bounds are plotted directly on the chart, offset into the future, allowing traders to visualize expected price dispersion under a geometric Brownian motion assumption. This tool is useful for risk management, trade planning, and visualizing the potential impact of volatility.
MVRV | Lyro RS📊 MVRV | Lyro RS is a powerful on-chain valuation tool designed to assess the relative market positioning of Bitcoin (BTC) or Ethereum (ETH) based on the Market Value to Realized Value (MVRV) ratio. It highlights potential undervaluation or overvaluation zones, helping traders and investors anticipate cyclical tops and bottoms.
✨ Key Features :
🔁 Dual Asset Support: Analyze either BTC or ETH with a single toggle.
📐 Dynamic MVRV Thresholds: Automatically calculates median-based bands at 50%, 64%, 125%, and 170%.
📊 Median Calculation: Period-based median MVRV for long-term trend context.
💡 Optional Smoothing: Use SMA to smooth MVRV for cleaner analysis.
🎯 Visual Threshold Alerts: Background and bar colors change based on MVRV position relative to thresholds.
⚠️ Built-in Alerts: Get notified when MVRV enters under- or overvalued territory.
📈 How It Works :
💰 MVRV Calculation: Uses data from IntoTheBlock and CoinMetrics to obtain real-time MVRV values.
🧠 Threshold Bands: Median MVRV is used as a baseline. Ratios like 50%, 64%, 125%, and 170% signal various levels of market extremes.
🎨 Visual Zones: Green zones for undervaluation and red zones for overvaluation, providing intuitive visual cues.
🛠️ Custom Highlights: Toggle individual threshold zones on/off for a cleaner view.
⚙️ Customization Options :
🔄 Switch between BTC or ETH for analysis.
📏 Adjust period length for median MVRV calculation.
🔧 Enable/disable threshold visibility (50%, 64%, 125%, 170%).
📉 Toggle smoothing to reduce noise in volatile markets.
📌 Use Cases :
🟢 Identify undervalued zones for long-term entry opportunities.
🔴 Spot potential overvaluation zones that may precede corrections.
🧭 Use in confluence with price action or macro indicators for better timing.
⚠️ Disclaimer :
This indicator is for educational purposes only. It should not be used in isolation for making trading or investment decisions. Always combine with price action, fundamentals, and proper risk management.
Bollinger Bands Z-ScoreBollinger Bands Z-Score Indicator
This indicator transforms the classic Bollinger Bands into a Z-Score oscillator displayed in a separate pane. It standardizes the Bollinger Bands’ basis line by calculating the Z-Score over a user-defined period, allowing you to see how many standard deviations the price deviates from the mean.
Upper and Lower Fixed Lines: These are set at +2 and -2 Z-Score levels, representing common thresholds for overbought and oversold conditions.
Z-Score Oscillator: The normalized Bollinger Bands oscillate smoothly between these fixed boundaries, providing a clearer perspective on volatility extremes.
Z-Score Table: Displayed on the right side, this table shows the current Z-Score value, along with fixed maximum (+2) and minimum (-2) limits, making it easy to track current momentum and volatility in real-time.
Use Cases:
Identify overextended price moves with standardized volatility measures.
Spot potential reversals or continuation setups by observing the Z-Score crossing key levels.
Complement traditional Bollinger Bands analysis with a statistically normalized perspective.
Input Parameters:
Length: The period used for Bollinger Bands and Z-Score calculation.
MA Type: Choose the moving average type for the basis line (SMA, EMA, SMMA, WMA, VWMA).
StdDev: Multiplier for the standard deviation bands.
Z-Score Length: The lookback period used to compute the mean and standard deviation for Z-Score normalization.
This indicator is perfect for traders seeking a statistically sound and visually clear representation of Bollinger Bands volatility and extremes.
Dskyz (DAFE) GENESIS Dskyz (DAFE) GENESIS: Adaptive Quant, Real Regime Power
Let’s be honest: Most published strategies on TradingView look nearly identical—copy-paste “open-source quant,” generic “adaptive” buzzwords, the same shallow explanations. I’ve even fallen into this trap with my own previously posted strategies. Not this time.
What Makes This Unique
GENESIS is not a black-box mashup or a pre-built template. It’s the culmination of DAFE’s own adaptive, multi-factor, regime-aware quant engine—built to outperform, survive, and visualize live edge in anything from NQ/MNQ to stocks and crypto.
True multi-factor core: Volume/price imbalances, trend shifts, volatility compression/expansion, and RSI all interlock for signal creation.
Adaptive regime logic: Trades only in healthy, actionable conditions—no “one-size-fits-all” signals.
Momentum normalization: Uses rolling, percentile-based fast/slow EMA differentials, ALWAYS normalized, ALWAYS relevant—no “is it working?” ambiguity.
Position sizing that adapts: Not fixed-lot, not naive—not a loophole for revenge trading.
No hidden DCA or pyramiding—what you see is what you trade.
Dashboard and visual system: Directly connected to internal logic. If it’s shown, it’s used—and nothing cosmetic is presented on your chart that isn’t quantifiable.
📊 Inputs and What They Mean (Read Carefully)
Maximum Raw Score: How many distinct factors can contribute to regime/trade confidence (default 4). If you extend the quant logic, increase this.
RSI Length / Min RSI for Shorts / Max RSI for Longs: Fine-tunes how “overbought/oversold” matters; increase the length for smoother swings, tighten floors/ceilings for more extreme signals.
⚡ Regime & Momentum Gates
Min Normed Momentum/Score (Conf): Raise to demand only the strongest trends—your filter to avoid algorithmic chop.
🕒 Volatility & Session
ATR Lookback, ATR Low/High Percentile: These control your system’s awareness of when the market is dead or ultra-volatile. All sizing and filter logic adapts in real time.
Trading Session (hours): Easy filter for when entries are allowed; default is regular trading hours—no surprise overnight fills.
📊 Sizing & Risk
Max Dollar Risk / Base-Max Contracts: All sizing is adaptive, based on live regime and volatility state—never static or “just 1 contract.” Control your max exposures and real $ risk. ATR will effect losses in high volatility times.
🔄 Exits & Scaling
Stop/Trail/Scale multipliers: You choose how dynamic/flexible risk controls and profit-taking need to be. ATR-based, so everything auto-adjusts to the current market mode.
Visuals That Actually Matter
Dashboard (Top Right): Shows only live, relevant stats: scoring, status, position size, win %, win streak, total wins—all from actual trade engine state (not “simulated”).
Watermark (Bottom Right): Momentum bar visual is always-on, regime-aware, reflecting live regime confidence and momentum normalization. If the bar is empty, you’re truly in no-momentum. If it glows lime, you’re riding the strongest possible edge.
*No cosmetics, no hidden code distractions.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 1 min (but works on all timeframes)
Order size: Adaptive, 1–3 contracts
No pyramiding, no hidden DCA
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Why It Wins
While others put out “AI-powered” strategies with little logic or soul, GENESIS is ruthlessly practical. It is built around what keeps traders alive:
- Context-aware signals, not just patterns
- Tight, transparent risk
- Inputs that adapt, not confuse
- Visuals that clarify, not distract
- Code that runs clean, efficient, and with minimal overfitting risk (try it on QQQ, AMD, SOL, etc. out of the box)
Disclaimer (for TradingView compliance):
Trading is risky. Futures, stocks, and crypto can result in significant losses. Do not trade with funds you cannot afford to lose. This is for educational and informational purposes only. Use in simulation/backtest mode before live trading. No past performance is indicative of future results. Always understand your risk and ownership of your trades.
This will not be my last—my goal is to keep raising the bar until DAFE is a brand or I’m forced to take this private.
Use with discipline, use with clarity, and always trade smarter.
— Dskyz , powered by DAFE Trading Systems.
(DAFE) DEVMA - Crossover (Deviation Moving Average) (DAFE) DEVMA - Crossover (Deviation Moving Average)
Let’s keep pushing the edge. After the breakthrough of Deviation over Deviation (DoD)—which gave traders a true lens into volatility’s hidden regime shifts—many asked: “What’s next?” The answer is DEVMA: a crossover engine built not on price, but on the heartbeat of the market itself.
Why is this different?
DEVMA isn’t just a moving average crossover. It’s a regime detector that tracks the expansion and contraction of deviation—giving you a real-time readout of when the market’s energy is about to shift. This is the next step for anyone who wants to anticipate volatility, not just react to it.
What sets DEVMA apart:
Volatility-First Logic:Both fast and slow lines are moving averages of deviation, not price. You’re tracking the market’s “energy,” not just its direction. This is the quant edge that most scripts miss.
Regime-Colored Lines:
The fast and slow DEVMA lines change color in real time—green/aqua for expansion, maroon/orange for contraction—so you can see regime shifts at a glance.
Quant-Pro Visuals:
Subtle glow, clean cross markers, and a minimalist dashboard keep your focus on what matters: the regime, not the noise.
Static Regime Thresholds:
Reference lines at 1.5 and 0.5 (custom colors) give you instant context for “normal” vs. “extreme” volatility states.
No Price Chasing:
This isn’t about following price. It’s about anticipating the next volatility regime—before the crowd even knows what’s coming.
How this builds on DoD:
DoD showed you when volatility itself was about to change. DEVMA takes that insight and turns it into a crossover engine—so you can see, filter, and act on regime shifts in real time. If DoD was the radar, DEVMA is the navigation system.
Inputs/Signals—explained for clarity:
Deviation Lookback:
Controls the sensitivity of the regime detector. Shorter = more signals, longer = only the rarest events.
Fast/Slow DEVMA Lengths:
Fine-tune how quickly the regime lines react. Fast for scalping, slow for swing trading.
Source Selection:
Choose from price, volume, volatility, or VoVix. Each source gives you a different lens on market stress. VoVix is for those who want to see the “regime quake” before the aftershocks.
VoVix Parameters:
Fine-tune the volatility-of-volatility engine for your market. Lower ATR Fast = more responsive; higher ATR Slow = more selective.
Bottom line:
DEVMA is for those who want to see the market’s heartbeat, not just its shadow. Use it to filter your trades, time your entries, or simply understand the market’s true rhythm. Every input is there for a reason. Every plot is a direct readout of the quant logic. Use with discipline, and make it your own.
Disclaimer:
Trading is risky. This script is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results.
*Updated the Dashboard/Metrics Display for better visibility
Use with discipline. Trade your edge.
— Dskyz, for DAFE Trading Systems
ZMVZMV-STRATEGY
Z – Zero-Based Thinking
At the core of the ZMV-STRATEGY lies zero-based thinking: the practice of assessing actions, projects, or goals as if starting from scratch. This principle encourages:
Eliminating outdated assumptions
Prioritizing current relevance over historical momentum
Making decisions based on present and future potential, not sunk costs
M – Momentum Mapping
Momentum is essential for sustained progress. The "M" emphasizes:
Identifying key areas where traction exists
Mapping energy flows within a team, project, or market
Leveraging small wins to catalyze exponential growth
V – Value Alignment
Finally, the “V” represents value alignment, which ensures that:
Every move aligns with core values and purpose
Stakeholders are engaged through shared vision
Ethical, meaningful impact is prioritized alongside metrics
EMA Validation4 EMA with Support/Resistance Validation (EMA-V)
This indicator displays four Exponential Moving Averages (EMAs) with customizable periods (default: 21, 50, 100, 200) and visually validates their roles as support or resistance.
Each EMA changes color based on its behavior: green for respected support , red for respected resistance, or default colors when unvalidated.
Ideal for traders seeking to identify reliable support and resistance levels across multiple timeframes.
