[ProfitTrailer:Feeder] Market Trends Top X / BTCThis script will help you determine your MarketConditions Grouping for PtFeeder. You're able to input the specific top 10/20/xx pairs you want to use to fine-tune your groupings as well as specific BasePairs, there values will be automatically printed on the chart!
When measuring top coins trend, this is how many top coins to check by volume from the exchanges that you have configured PT Feeder for. For, the top 50 coins will be checked and their price change over the MeasureTimes property and the average change calculated. This average is used for the MaxTopCoinAverageChange property
If you like this kind of content, please 'like' and 'follow' and I'll continue publishing these kind of scripts!
Enjoy!
Cari dalam skrip untuk "profit"
Profitable L 1800 Candle Highlight [Beta]
Certainly! Here's a user guide for the provided Pine Script code:
User Guide: 1800 Candle Highlight Indicator
Overview:
The "1800 Candle Highlight" indicator is designed to visually emphasize the 18:00 (6:00 PM) candle on the chart, providing clarity on its open and close prices, and highlighting its timeframe with a distinctive color.
Key Features:
Candle Highlighting: The indicator identifies the candle that opens at 18:00 and visually distinguishes it from other candles on the chart.
Open and Close Prices: The indicator plots the open and close prices of the 18:00 candle as step lines, making it easy to identify price movements during that timeframe.
Background Color: It colors the background within the 18:00 candle's timeframe with a transparent blue shade, providing further emphasis on that period.
Start Marker: A downward triangle shape marks the start of the 18:00 candle, aiding in identifying the beginning of the highlighted timeframe.
Usage:
Overlay: The indicator is designed to be overlaid on the price chart, allowing users to visualize the highlighted candle alongside price movements.
Interpretation: Traders can observe the open and close prices of the 18:00 candle relative to previous and subsequent candles, aiding in analysis and decision-making.
Timeframe Focus: The highlighted candle's timeframe can serve as a reference point for analyzing price action during specific hours, such as the end of a trading day.
Installation:
Access: Users can access the Pine Script editor within the TradingView platform to create a new indicator.
Copy and Paste: Copy the provided Pine Script code and paste it into the editor.
Save and Apply: Save the indicator and apply it to the desired chart, adjusting settings as needed.
Customization:
Color Scheme: Users can customize the colors used for highlighting, open/close prices, and background to suit their preferences and chart aesthetics.
Styling: Adjustments can be made to line styles, widths, and marker sizes to enhance visibility and clarity.
Compatibility:
The indicator is compatible with TradingView's Pine Script version 5 and can be applied to various financial instruments and timeframes supported by the platform.
Disclaimer:
The "1800 Candle Highlight" indicator is provided for informational purposes only and should not be considered as financial advice. Users are encouraged to conduct thorough analysis and consider multiple factors before making trading decisions.
Profitable Supertrend v0.1 - AlphaThis a script to try detect the best combination of supertrend parameters in a space of time. Sadly the script is slow. Evaluate all possibilities params is hard for a pinescript and my knowledge too. In some cases, when you want evaluate many time could be the script fails for timeout. Perhaps with time I could enhance. For this problem of speed the calculate of combinatios it's not complete: In factor use a increment of 0.2 in each param (0.1, 0.3, 0.5 ...) in period the increment for each value is 3. The range for factor it's from 3.0 to 12.0. The range of period it's from 10 to 43
My knowledge don't let me go more far. Perhaps with time I can enhance the script.
PMax on RSI with Tillson T3Profit Maximizer Indicator on RSI with Tillson T3 Moving Average:
PMax uses ATR calculation inside, for this reason users couldn't manage to use PMax on RSI because RSI indicator doesn't have High and Low values in bars, but ATR needs that values. So I personally calculate RSI in a different way to have High and Low values of RSI wrt price bars.
IMPORTANT:
Because of the sudden movements and divergences on RSI, this indicator must firstly optimized for the charts before using. Optimization can be held by users for the meaningful parameters for each chart.
3 parameters are critical when optimizing:
First: Multiplier
Second: Tillson T3 Length
Third: T3 Volume Factor
Here are some information about Profit Maximizer:
PMax Indicator:
PMax Screener and Strategy:
PMax Explorer STRATEGY & SCREENERProfit Maximizer - PMax Explorer STRATEGY & SCREENER screens the BUY and SELL signals (trend reversals) for 20 user defined different tickers in Tradingview charts.
Simply input the name of the ticker in Tradingview that you want to screen.
Terminology explanation:
Confirmed Reversal: PMax reversal that happened in the last bar and cannot be repainted.
Potential Reversal: PMax reversal that might happen in the current bar but can also not happen depending upon the timeframe closing price.
Downtrend: Tickers that are currently in the sell zone
Uptrend: Tickers that are currently in the buy zone
Screener has also got a built in PMax indicator which users can confirm the reversals on graphs.
Screener explores the 20 tickers in current graph's time frame and also in desired parameters of the SuperTrend indicator.
Also you can optimize the parameters manually with the built in STRATEGY version.
PMax indicator :
Profit Maximizer - PMax is a brand new indicator developed by me.
It's a combination of two trailing stop loss indicators;
One is Anıl Özekşi's MOST (Moving Stop Loss) Indicator
and the other one is well known ATR based SuperTrend
Profit Maximizer - PMax tries to solve this problem. PMax combines the powerful sides of MOST (Moving Average Trend Changer) and SuperTrend (ATR price detection) in one indicator.
Backtest and optimization results of PMax are far better when compared to its ancestors MOST and SuperTrend. It reduces the number of false signals in sideways and give more reliable trade signals.
PMax is easy to determine the trend and can be used in any type of markets and instruments. It does not repaint.
The first parameter in the PMax indicator set by the three parameters is the period/length of ATR.
The second Parameter is the Multiplier of ATR which would be useful to set the value of distance from the built in Moving Average.
I personally think the most important parameter is the Moving Average Length and type.
PMax will be much sensitive to trend movements if Moving Average Length is smaller. And vice versa, will be less sensitive when it is longer.
As the period increases it will become less sensitive to little trends and price actions.
In this way, your choice of period, will be closely related to which of the sort of trends you are interested in.
We are under the effect of the uptrend in cases where the Moving Average is above PMax;
conversely under the influence of a downward trend, when the Moving Average is below PMax.
Built in Moving Average type defaultly set as EMA but users can choose from 8 different Moving Average types like:
SMA : Simple Moving Average
EMA : Exponential Movin Average
WMA : Weighted Moving Average
TMA : Triangular Moving Average
VAR : Variable Index Dynamic Moving Average aka VIDYA
WWMA : Welles Wilder's Moving Average
ZLEMA : Zero Lag Exponential Moving Average
TSF : True Strength Force
Tip: In sideways VAR would be a good choice
You can use PMax default alarms and Buy Sell signals like:
1-
BUY when Moving Average crosses above PMax
SELL when Moving Average crosses under PMax
2-
BUY when prices jumps over PMax line.
SELL when prices go under PMax line.
McGinley Dynamic debugged🔍 McGinley Dynamic Debugged (Adaptive Moving Average)
This indicator plots the McGinley Dynamic, a mathematically adaptive moving average designed to reduce lag and better track price action during both trends and consolidations.
✅ Key Features:
Adaptive smoothing: The McGinley Dynamic adjusts itself based on the speed of price changes.
Lag reduction: Compared to traditional moving averages like EMA or SMA, McGinley provides smoother yet responsive tracking.
Stability fix: This version includes a robust fix for rare recursive calculation issues, particularly on low-priced historical assets (e.g., Wipro pre-2000).
⚙️ What’s Different in This Debugged Version?
Implements manual clamping on the source / previous value ratio to prevent mathematical spikes that could cause flattening or distortion in the plotted line.
Ensures more stable behavior across all instruments and timeframes, especially those with historically low price points or volatile early data.
💡 Use Case:
Ideal for:
Trend confirmation
Entry filtering
Adaptive support/resistance visualization
Improving signal precision in low-volatility or high-noise environments
⚠️ Notes:
Works best when combined with volume filters or other trend indicators for validation.
This version is optimized for visual use—for signal generation, consider pairing it with additional logic or thresholds.
PROFIT INDICATORFirst let me tell you which indicators have been used in this script so that you have the confidence while taking the trade:
(a) Bollinger Band with 20 SMA Inside it - Currently it is off, you can turn it on from settings.
(b) HMA 33, I have added the option of using two HMA's simultaneously. You can use HMA, EMA, SMA as per your settings and it would be color trending.
(c) VWAP- you can turn it on from settings
(d) CPR- you can turn it on from settings
(e) EMA's 20, 50, 200. Currently off, you can turn it on from settings.
(d) SMA's 50 and 200. Currently off, yu can turn it on from settings, if you want to use 20 SMA you can use bollinger band basis that is 20 period SMA.
(f) Trend bar at bottom on the basis of 50 EMA.
(g) Half Trend
(h) Trend strength Detector
(d) EMA 50 high and low to show the pac channel. I am not using this however as per request I have added this. Currently, it is trun on and you can turn it off from settings.
(f) Auto Fib levels
Please use a stick note for few days and mention imp notes before taking trade to check if all the conditions are matching to take the trade.
Buy Condition:-
1. Bolling band should be widely open.
2. Check the support and resistance from CPR. Candle should close above support in green.
3. Check the trend bar at bottom, it should be green, if it is grey in colour dont enter in trade.
4. Candle should be closing above EMA 50 and its upto you if you need additional confirmation, you can use EMA 20, 50, 200 and SMA 50 and 200, this is optional.
5. You can use VWAP as support or resistance and you can turn it on from settings.
6. Trending HMA of 33 should be in green for buy.
7. Half trend Indicator should give buy signal.
8. Trend Strength Indicator for checking the strength of the trend, if the arrow is big upside, you can go for buy.
9. Exit from buy trade when it start showing very small arrow which means trend is about to change.
10.Exit buy trade at 61.8 Fib level
Sell Condition:-
1. Bolling band should be widely open.
2. Check the support and resistance from CPR. Candle should close below resistance in red.
3. Check the trend bar at bottom, it should be red, if it is grey in colour dont enter in trade.
4. Candle should be closing below EMA 50 and its upto you if you need additional confirmation, you can use EMA 20, 50, 200 and SMA 50 and 200, this is optional.
5. You can use VWAP as support or resistance and you can turn it on from settings.
6. Trending HMA of 33 should be in red for sell.
7. Half trend Indicator should give sell signal.
8. Trend Strength Indicator for checking the strength of the trend, if the arrow is big downside, you can go for sell.
9. Exit from sell trade when down arrows start showing very small in size which means trend is about to change.
10.Exit sell trade at 61.8 Fib level
PMax on Rsi w/T3 *Strategy*Profit Maximizer Indicator on RSI with Tillson T3 Moving Average:
PMax uses ATR calculation inside, for this reason users couldn't manage to use PMax on RSI because RSI indicator doesn't have High and Low values in bars, but ATR needs that values. So I personally calculate RSI in a different way to have High and Low values of RSI wrt price bars.
IMPORTANT:
Because of the sudden movements and divergences on RSI , this indicator must firstly optimized for the charts before using. Optimization can be held by users for the meaningful parameters for each chart.
3 parameters are critical when optimizing:
First: Multiplier
Second: Tillson T3 Length
Third: T3 Volume Factor
Says, Kıvanç Özbilgiç. Here's the strategy version for you to backtest & optimize properly.
Enjoy.
$EURUSD 1 Minute Chart StrategyYou must be using the renko chart with traditional settings with the block size set at .0001. This can be done by going to settings. Style at the bottom should be changed from ATR to traditional. The set the block size as .0001.
Profit target areaUpdate.
- you can specify count of bars used to detect reversal pattern
- you can specify count of bars used to determine lowest or highest price to place support or resistance
- area between lines is filled by green - ascending, red - descending trend
To trade:
- open position using stop command on S/R
- close position using limit command on retracement line
- close position when background colour indicates trend change
(erratum: last balloon on right should say "buy limit")
Candle Breakout StrategyShort description (one-liner)
Candle Breakout Strategy — identifies a user-specified candle (UTC time), draws its high/low range, then enters on breakouts with configurable stop-loss, take-profit (via Risk:Reward) and optional alerts.
Full description (ready-to-paste)
Candle Breakout Strategy
Version 1.0 — Strategy script (Pine v5)
Overview
The Candle Breakout Strategy automatically captures a single "range candle" at a user-specified UTC time, draws its high/low as a visible box and dashed level lines, and waits for a breakout. When price closes above the range high it enters a Long; when price closes below the range low it enters a Short. Stop-loss is placed at the opposite range boundary and take-profit is calculated with a user-configurable Risk:Reward multiplier. Alerts for entries can be enabled.
This strategy is intended for breakout style trading where a clearly defined intraday range is established at a fixed time. It is simple, transparent and easy to adapt to multiple symbols and timeframes.
How it works (step-by-step)
On every bar the script checks the current UTC time.
When the first bar that matches the configured Target Hour:Target Minute (UTC) appears, the script records that candle’s high and low. This defines the breakout range.
A box and dashed lines are drawn on the chart to display the range and extended to the right while the range is active.
The script then waits for price to close outside the box:
Close > Range High → Long entry
Close < Range Low → Short entry
When an entry triggers:
Stop-loss = opposite range boundary (range low for longs, range high for shorts).
Take-profit = entry ± (risk × Risk:Reward). Risk is computed as the distance between entry price and stop-loss.
After entry the range becomes inactive (waitingForBreakout = false) until the next configured target time.
Inputs / Parameters
Target Hour (UTC) — the hour (0–23) in UTC when the range candle is detected.
Target Minute — minute (0–59) of the target candle.
Risk:Reward Ratio — multiplier for computing take profit from risk (0.5–10). Example: 2 means TP = entry + 2×risk.
Enable Alerts — turn on/off entry alerts (string message sent once per bar when an entry occurs).
Show Last Box Only (internal behavior) — when enabled the previous box is deleted at the next range creation so only the most recent range is visible (default behavior in the script).
Visuals & On-chart Info
A semi-transparent blue box shows the recorded range and extends to the right while active.
Dashed horizontal lines mark the range high and low.
On-chart shapes: green triangle below bar for Long signals, red triangle above bar for Short signals.
An information table (top-right) displays:
Target Time (UTC)
Active Range (Yes / No)
Range High
Range Low
Risk:Reward
Alerts
If Enable Alerts is on, the script sends an alert with the following formats when an entry occurs:
Long alert:
🟢 LONG SIGNAL
Entry Price:
Stop Loss:
Take Profit:
Short alert:
🔴 SHORT SIGNAL
Entry Price:
Stop Loss:
Take Profit:
Use TradingView's alert dialog to create alerts based on the script — select the script’s alert condition or use the alert() messages.
Recommended usage & tips
Timeframe: This strategy works on any timeframe but the definition of "candle at target time" depends on the chart timeframe. For intraday breakout styles, use 1m — 60m charts depending on the session you want to capture.
Target Time: Choose a time that is meaningful for the instrument (e.g., market open, economic release, session overlap). All times are handled in UTC.
Position Sizing: The script’s example uses strategy.percent_of_equity with 100% default — change default_qty_value or strategy settings to suit your risk management.
Filtering: Consider combining this breakout with trend filters (EMA, ADX, etc.) to reduce false breakouts.
Backtesting: Always backtest over a sufficiently large and recent sample. Pay attention to slippage and commission settings in TradingView’s strategy tester.
Known behavior & limitations
The script registers the breakout on close outside the recorded range. If you prefer intrabar breakout rules (e.g., high/low breach without close), you must adjust the condition accordingly.
The recorded range is taken from a single candle at the exact configured UTC time. If there are missing bars or the chart timeframe doesn't align, the intended candle may differ — choose the target time and chart timeframe consistently.
Only a single active position is allowed at a time (the script checks strategy.position_size == 0 before entries).
Example setups
EURUSD (Forex): Target Time 07:00 UTC — captures London open range.
Nifty / Index: Target Time 09:15 UTC — captures local session open range.
Crypto: Target Time 00:00 UTC — captures daily reset candle for breakout.
Risk disclaimer
This script is educational and provided as-is. Past performance is not indicative of future results. Use proper risk management, test on historical data, and consider slippage and commissions. Do not trade real capital without sufficient testing.
Change log
v1.0 — Initial release: range capture, box and level drawing, long/short entry by close breakout, SL at opposite boundary, TP via Risk:Reward, alerts, info table.
If you want, I can also:
Provide a short README version (2–3 lines) for the TradingView “Short description” field.
Add a couple of suggested alert templates for the TradingView alert dialog (if you want alerts that include variable placeholders).
Convert the disclaimer into multiple language versions.
Gold 15m: Trend + S/R + Liquidity Sweep (RR 1:2)This strategy is designed for short-term trading on XAUUSD (Gold) using the 15-minute timeframe. It combines trend direction, support/resistance pivots, liquidity sweep detection, and momentum confirmation to identify high-probability reversal setups in line with the dominant market trend.
⚙️ Core Logic:
Trend Filter (EMA 200):
The strategy only takes long positions when price is above the 200 EMA and short positions when price is below it.
Support/Resistance via Pivots:
Dynamic swing highs and lows are identified using pivot points. These act as local supply and demand levels where liquidity is likely to accumulate.
Liquidity Sweep Detection:
A bullish liquidity sweep occurs when price briefly breaks below the last pivot low (grabbing liquidity) and then closes back above it.
A bearish sweep occurs when price breaks above the last pivot high and then closes back below.
Momentum & Candle Strength:
The strategy filters signals based on candle range and body size to ensure entries occur during strong price reactions, not weak retracements.
Risk Management (1:2 RR):
Stop-loss is placed slightly beyond the last pivot level using ATR-based buffers, and take-profit is set at 2× the risk distance, maintaining a reward-to-risk ratio of 1:2.
💼 Trade Logic Summary:
Long Entry:
After a bullish liquidity sweep & reclaim, momentum confirmation, and trend alignment (above EMA 200).
Short Entry:
After a bearish sweep & reclaim, momentum confirmation, and trend alignment (below EMA 200).
Exit:
Automated via ATR-based Stop Loss and Take Profit targets.
📊 Customization Options:
Adjustable EMA length, pivot settings, ATR multipliers, and RR ratio.
Option to enable/disable trend filter.
Toggle display of S/R zones on chart.
🧠 Best Use:
Works best during London and New York sessions when Gold shows strong momentum.
Can be adapted for forex pairs and indices by tuning ATR and pivot parameters.
RSI + Elder Bull-Bear pressure RSI + Bull/Bear (Elder-Ray enhanced RSI)
What it is
An extended RSI that overlays Elder-Ray Bull/Bear Power on the same, zero-centered scale. You get classic RSI regime cues plus a live read of buy/sell pressure, with optional smoothing, bands, and right-edge value labels.
Key features
RSI with bands – default bands 30 / 50 / 70 (editable).
Bull/Bear Power (Elder) – ATR-normalized; optional EMA/SMA/RMA/HMA smoothing.
One-pane overlay – RSI and Bull/Bear share a common midline (RSI-50 ↔ panel 0).
Right-edge labels – always visible at the chart’s right margin with adjustable offsets.
How to read it
Cyan line = RSI (normalized)
Above the mid band = bullish regime; below = bearish regime.
Green = Bull Power, Red = Bear Power
Columns/lines above 0 show buy pressure; below 0 show sell pressure.
Smoothing reduces noise; zero-line remains your key reference.
Trade logic (simple playbook)
Entry
BUY (primary):
RSI crosses up through 50 (regime turns bullish), and
Bull (green) crosses up through 0 (buy pressure confirms).
SELL (primary):
RSI crosses down through 50, and
Bear (red) crosses down through 0 (sell pressure confirms).
Alternative momentum entries
Aggressive BUY: Bull (green) pushes above RSI-80 band (strong upside impulse).
Aggressive SELL: Bear (red) pushes below RSI-30 band (strong downside impulse).
Exits / trade management
In a long: consider exiting or tightening stops if Bear (red) dips below the 0 line (rising sell pressure) or RSI loses 50.
In a short: consider exiting or tightening if Bull (green) rises above 0 or RSI reclaims 50.
Tip: “0” on the panel is your pressure zero-line (maps to RSI-50). Most whipsaws happen near this line; smoothing (e.g., EMA 21) helps.
Defaults (on first load)
RSI bands: 30 / 50 / 70 with subtle fills.
Labels: tiny, pushed far right (large offsets).
Bull/Bear smoothing: EMA(21), smoothed line plot mode.
RSI plotted normalized so it overlaps the pressure lines cleanly.
Tighten or loosen the Bull/Bear thresholds (e.g., Bull ≥ +0.5 ATR, Bear ≤ −0.5 ATR) to demand stronger confirmation.
Settings that matter
Smoothing length/type – balances responsiveness vs. noise.
Power/RSI Gain – visual scaling only (doesn’t change logic).
Band placement – keep raw 30/50/80 or switch to “distance from 50” if you prefer symmetric spacing.
Label offsets – move values clear of the last bar/scale clutter.
Good practices
Combine with structure/ATR stops (e.g., 1–1.5× ATR, swing high/low).
In trends, hold while RSI stays above/below 50 and the opposite pressure line doesn’t dominate.
In ranges, favor signals occurring near the mid band and take profits at the opposite band.
Disclaimer: This is a research/visual tool, not financial advice at any kind. Test your rules on multiple markets/timeframes and size positions responsibly.
Option Buying Strategy By Raj PandyaThis strategy is designed for intraday trading on BankNifty using a powerful confluence of trend, structure and momentum. It combines the 9-period Exponential Moving Average (EMA) with Daily Traditional Pivot Points to identify high-probability breakout trades.
A Long (CALL) signal is generated when price crosses and closes above both the 9 EMA and the Daily Pivot Point (PP), confirming upward trend strength. A Short (PUT) signal triggers when price crosses and closes below the 9 EMA and PP, signaling downside momentum. To reduce false signals, the strategy uses RSI with a moving average filter to ensure momentum aligns with price action.
Risk management is built-in with previous candle high/low stop-loss, a fixed 50-point target, and an automatic trailing stop system to protect profits on trending days. This helps capitalize on strong momentum while managing risk effectively.
This strategy works best on the 5-minute timeframe and is optimized for BankNifty futures/options. It aims to capture clean directional moves around key intraday value levels used by institutional traders.
Supertrend Advance Pullback StrategyHandbook for the Supertrend Advance Strategy
1. Introduction
Purpose of the Handbook:
The main purpose of this handbook is to serve as a comprehensive guide for traders and investors who are looking to explore and harness the potential of the Supertrend Advance Strategy. In the rapidly changing financial market, having the right tools and strategies at one's disposal is crucial. Whether you're a beginner hoping to dive into the world of trading or a seasoned investor aiming to optimize and diversify your portfolio, this handbook offers the insights and methodologies you need. By the end of this guide, readers should have a clear understanding of how the Supertrend Advance Strategy works, its benefits, potential pitfalls, and practical application in various trading scenarios.
Overview of the Supertrend Advance Pullback Strategy:
At its core, the Supertrend Advance Strategy is an evolution of the popular Supertrend Indicator. Designed to generate buy and sell signals in trending markets, the Supertrend Indicator has been a favorite tool for many traders around the world. The Advance Strategy, however, builds upon this foundation by introducing enhanced mechanisms, filters, and methodologies to increase precision and reduce false signals.
1. Basic Concept:
The Supertrend Advance Strategy relies on a combination of price action and volatility to determine the potential trend direction. By assessing the average true range (ATR) in conjunction with specific price points, this strategy aims to highlight the potential starting and ending points of market trends.
2. Methodology:
Unlike the traditional Supertrend Indicator, which primarily focuses on closing prices and ATR, the Advance Strategy integrates other critical market variables, such as volume, momentum oscillators, and perhaps even fundamental data, to validate its signals. This multidimensional approach ensures that the generated signals are more reliable and are less prone to market noise.
3. Benefits:
One of the main benefits of the Supertrend Advance Strategy is its ability to filter out false breakouts and minor price fluctuations, which can often lead to premature exits or entries in the market. By waiting for a confluence of factors to align, traders using this advanced strategy can increase their chances of entering or exiting trades at optimal points.
4. Practical Applications:
The Supertrend Advance Strategy can be applied across various timeframes, from intraday trading to swing trading and even long-term investment scenarios. Furthermore, its flexible nature allows it to be tailored to different asset classes, be it stocks, commodities, forex, or cryptocurrencies.
In the subsequent sections of this handbook, we will delve deeper into the intricacies of this strategy, offering step-by-step guidelines on its application, case studies, and tips for maximizing its efficacy in the volatile world of trading.
As you journey through this handbook, we encourage you to approach the Supertrend Advance Strategy with an open mind, testing and tweaking it as per your personal trading style and risk appetite. The ultimate goal is not just to provide you with a new tool but to empower you with a holistic strategy that can enhance your trading endeavors.
2. Getting Started
Navigating the financial markets can be a daunting task without the right tools. This section is dedicated to helping you set up the Supertrend Advance Strategy on one of the most popular charting platforms, TradingView. By following the steps below, you'll be able to integrate this strategy into your charts and start leveraging its insights in no time.
Setting up on TradingView:
TradingView is a web-based platform that offers a wide range of charting tools, social networking, and market data. Before you can apply the Supertrend Advance Strategy, you'll first need a TradingView account. If you haven't set one up yet, here's how:
1. Account Creation:
• Visit TradingView's official website.
• Click on the "Join for free" or "Sign up" button.
• Follow the registration process, providing the necessary details and setting up your login credentials.
2. Navigating the Dashboard:
• Once logged in, you'll be taken to your dashboard. Here, you'll see a variety of tools, including watchlists, alerts, and the main charting window.
• To begin charting, type in the name or ticker of the asset you're interested in the search bar at the top.
3. Configuring Chart Settings:
• Before integrating the Supertrend Advance Strategy, familiarize yourself with the chart settings. This can be accessed by clicking the 'gear' icon on the top right of the chart window.
• Adjust the chart type, time intervals, and other display settings to your preference.
Integrating the Strategy into a Chart:
Now that you're set up on TradingView, it's time to integrate the Supertrend Advance Strategy.
1. Accessing the Pine Script Editor:
• Located at the top-center of your screen, you'll find the "Pine Editor" tab. Click on it.
• This is where custom strategies and indicators are scripted or imported.
2. Loading the Supertrend Advance Strategy Script:
• Depending on whether you have the script or need to find it, there are two paths:
• If you have the script: Copy the Supertrend Advance Strategy script, and then paste it into the Pine Editor.
• If searching for the script: Click on the “Indicators” icon (looks like a flame) at the top of your screen, and then type “Supertrend Advance Strategy” in the search bar. If available, it will show up in the list. Simply click to add it to your chart.
3. Applying the Strategy:
• After pasting or selecting the Supertrend Advance Strategy in the Pine Editor, click on the “Add to Chart” button located at the top of the editor. This will overlay the strategy onto your main chart window.
4. Configuring Strategy Settings:
• Once the strategy is on your chart, you'll notice a small settings ('gear') icon next to its name in the top-left of the chart window. Click on this to access settings.
• Here, you can adjust various parameters of the Supertrend Advance Strategy to better fit your trading style or the specific asset you're analyzing.
5. Interpreting Signals:
• With the strategy applied, you'll now see buy/sell signals represented on your chart. Take time to familiarize yourself with how these look and behave over various timeframes and market conditions.
3. Strategy Overview
What is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is a refined version of the classic Supertrend Indicator, which was developed to aid traders in spotting market trends. The strategy utilizes a combination of data points, including average true range (ATR) and price momentum, to generate buy and sell signals.
In essence, the Supertrend Advance Strategy can be visualized as a line that moves with the price. When the price is above the Supertrend line, it indicates an uptrend and suggests a potential buy position. Conversely, when the price is below the Supertrend line, it hints at a downtrend, suggesting a potential selling point.
Strategy Goals and Objectives:
1. Trend Identification: At the core of the Supertrend Advance Strategy is the goal to efficiently and consistently identify prevailing market trends. By recognizing these trends, traders can position themselves to capitalize on price movements in their favor.
2. Reducing Noise: Financial markets are often inundated with 'noise' - short-term price fluctuations that can mislead traders. The Supertrend Advance Strategy aims to filter out this noise, allowing for clearer decision-making.
3. Enhancing Risk Management: With clear buy and sell signals, traders can set more precise stop-loss and take-profit points. This leads to better risk management and potentially improved profitability.
4. Versatility: While primarily used for trend identification, the strategy can be integrated with other technical tools and indicators to create a comprehensive trading system.
Type of Assets/Markets to Apply the Strategy:
1. Equities: The Supertrend Advance Strategy is highly popular among stock traders. Its ability to capture long-term trends makes it particularly useful for those trading individual stocks or equity indices.
2. Forex: Given the 24-hour nature of the Forex market and its propensity for trends, the Supertrend Advance Strategy is a valuable tool for currency traders.
3. Commodities: Whether it's gold, oil, or agricultural products, commodities often move in extended trends. The strategy can help in identifying and capitalizing on these movements.
4. Cryptocurrencies: The volatile nature of cryptocurrencies means they can have pronounced trends. The Supertrend Advance Strategy can aid crypto traders in navigating these often tumultuous waters.
5. Futures & Options: Traders and investors in derivative markets can utilize the strategy to make more informed decisions about contract entries and exits.
It's important to note that while the Supertrend Advance Strategy can be applied across various assets and markets, its effectiveness might vary based on market conditions, timeframe, and the specific characteristics of the asset in question. As always, it's recommended to use the strategy in conjunction with other analytical tools and to backtest its effectiveness in specific scenarios before committing to trades.
4. Input Settings
Understanding and correctly configuring input settings is crucial for optimizing the Supertrend Advance Strategy for any specific market or asset. These settings, when tweaked correctly, can drastically impact the strategy's performance.
Grouping Inputs:
Before diving into individual input settings, it's important to group similar inputs. Grouping can simplify the user interface, making it easier to adjust settings related to a specific function or indicator.
Strategy Choice:
This input allows traders to select from various strategies that incorporate the Supertrend indicator. Options might include "Supertrend with RSI," "Supertrend with MACD," etc. By choosing a strategy, the associated input settings for that strategy become available.
Supertrend Settings:
1. Multiplier: Typically, a default value of 3 is used. This multiplier is used in the ATR calculation. Increasing it makes the Supertrend line further from prices, while decreasing it brings the line closer.
2. Period: The number of bars used in the ATR calculation. A common default is 7.
EMA Settings (Exponential Moving Average):
1. Period: Defines the number of previous bars used to calculate the EMA. Common periods are 9, 21, 50, and 200.
2. Source: Allows traders to choose which price (Open, Close, High, Low) to use in the EMA calculation.
RSI Settings (Relative Strength Index):
1. Length: Determines how many periods are used for RSI calculation. The standard setting is 14.
2. Overbought Level: The threshold at which the asset is considered overbought, typically set at 70.
3. Oversold Level: The threshold at which the asset is considered oversold, often at 30.
MACD Settings (Moving Average Convergence Divergence):
1. Short Period: The shorter EMA, usually set to 12.
2. Long Period: The longer EMA, commonly set to 26.
3. Signal Period: Defines the EMA of the MACD line, typically set at 9.
CCI Settings (Commodity Channel Index):
1. Period: The number of bars used in the CCI calculation, often set to 20.
2. Overbought Level: Typically set at +100, denoting overbought conditions.
3. Oversold Level: Usually set at -100, indicating oversold conditions.
SL/TP Settings (Stop Loss/Take Profit):
1. SL Multiplier: Defines the multiplier for the average true range (ATR) to set the stop loss.
2. TP Multiplier: Defines the multiplier for the average true range (ATR) to set the take profit.
Filtering Conditions:
This section allows traders to set conditions to filter out certain signals. For example, one might only want to take buy signals when the RSI is below 30, ensuring they buy during oversold conditions.
Trade Direction and Backtest Period:
1. Trade Direction: Allows traders to specify whether they want to take long trades, short trades, or both.
2. Backtest Period: Specifies the time range for backtesting the strategy. Traders can choose from options like 'Last 6 months,' 'Last 1 year,' etc.
It's essential to remember that while default settings are provided for many of these tools, optimal settings can vary based on the market, timeframe, and trading style. Always backtest new settings on historical data to gauge their potential efficacy.
5. Understanding Strategy Conditions
Developing an understanding of the conditions set within a trading strategy is essential for traders to maximize its potential. Here, we delve deep into the logic behind these conditions, using the Supertrend Advance Strategy as our focal point.
Basic Logic Behind Conditions:
Every strategy is built around a set of conditions that provide buy or sell signals. The conditions are based on mathematical or statistical methods and are rooted in the study of historical price data. The fundamental idea is to recognize patterns or behaviors that have been profitable in the past and might be profitable in the future.
Buy and Sell Conditions:
1. Buy Conditions: Usually formulated around bullish signals or indicators suggesting upward price momentum.
2. Sell Conditions: Centered on bearish signals or indicators indicating downward price momentum.
Simple Strategy:
The simple strategy could involve using just the Supertrend indicator. Here:
• Buy: When price closes above the Supertrend line.
• Sell: When price closes below the Supertrend line.
Pullback Strategy:
This strategy capitalizes on price retracements:
• Buy: When the price retraces to the Supertrend line after a bullish signal and is supported by another bullish indicator.
• Sell: When the price retraces to the Supertrend line after a bearish signal and is confirmed by another bearish indicator.
Indicators Used:
EMA (Exponential Moving Average):
• Logic: EMA gives more weight to recent prices, making it more responsive to current price movements. A shorter-period EMA crossing above a longer-period EMA can be a bullish sign, while the opposite is bearish.
RSI (Relative Strength Index):
• Logic: RSI measures the magnitude of recent price changes to analyze overbought or oversold conditions. Values above 70 are typically considered overbought, and values below 30 are considered oversold.
MACD (Moving Average Convergence Divergence):
• Logic: MACD assesses the relationship between two EMAs of a security’s price. The MACD line crossing above the signal line can be a bullish signal, while crossing below can be bearish.
CCI (Commodity Channel Index):
• Logic: CCI compares a security's average price change with its average price variation. A CCI value above +100 may mean the price is overbought, while below -100 might signify an oversold condition.
And others...
As the strategy expands or contracts, more indicators might be added or removed. The crucial point is to understand the core logic behind each, ensuring they align with the strategy's objectives.
Logic Behind Each Indicator:
1. EMA: Emphasizes recent price movements; provides dynamic support and resistance levels.
2. RSI: Indicates overbought and oversold conditions based on recent price changes.
3. MACD: Showcases momentum and direction of a trend by comparing two EMAs.
4. CCI: Measures the difference between a security's price change and its average price change.
Understanding strategy conditions is not just about knowing when to buy or sell but also about comprehending the underlying market dynamics that those conditions represent. As you familiarize yourself with each condition and indicator, you'll be better prepared to adapt and evolve with the ever-changing financial markets.
6. Trade Execution and Management
Trade execution and management are crucial aspects of any trading strategy. Efficient execution can significantly impact profitability, while effective management can preserve capital during adverse market conditions. In this section, we'll explore the nuances of position entry, exit strategies, and various Stop Loss (SL) and Take Profit (TP) methodologies within the Supertrend Advance Strategy.
Position Entry:
Effective trade entry revolves around:
1. Timing: Enter at a point where the risk-reward ratio is favorable. This often corresponds to confirmatory signals from multiple indicators.
2. Volume Analysis: Ensure there's adequate volume to support the movement. Volume can validate the strength of a signal.
3. Confirmation: Use multiple indicators or chart patterns to confirm the entry point. For instance, a buy signal from the Supertrend indicator can be confirmed with a bullish MACD crossover.
Position Exit Strategies:
A successful exit strategy will lock in profits and minimize losses. Here are some strategies:
1. Fixed Time Exit: Exiting after a predetermined period.
2. Percentage-based Profit Target: Exiting after a certain percentage gain.
3. Indicator-based Exit: Exiting when an indicator gives an opposing signal.
Percentage-based SL/TP:
• Stop Loss (SL): Set a fixed percentage below the entry price to limit potential losses.
• Example: A 2% SL on an entry at $100 would trigger a sell at $98.
• Take Profit (TP): Set a fixed percentage above the entry price to lock in gains.
• Example: A 5% TP on an entry at $100 would trigger a sell at $105.
Supertrend-based SL/TP:
• Stop Loss (SL): Position the SL at the Supertrend line. If the price breaches this line, it could indicate a trend reversal.
• Take Profit (TP): One could set the TP at a point where the Supertrend line flattens or turns, indicating a possible slowdown in momentum.
Swing high/low-based SL/TP:
• Stop Loss (SL): For a long position, set the SL just below the recent swing low. For a short position, set it just above the recent swing high.
• Take Profit (TP): For a long position, set the TP near a recent swing high or resistance. For a short position, near a swing low or support.
And other methods...
1. Trailing Stop Loss: This dynamic SL adjusts with the price movement, locking in profits as the trade moves in your favor.
2. Multiple Take Profits: Divide the position into segments and set multiple TP levels, securing profits in stages.
3. Opposite Signal Exit: Exit when another reliable indicator gives an opposite signal.
Trade execution and management are as much an art as they are a science. They require a blend of analytical skill, discipline, and intuition. Regularly reviewing and refining your strategies, especially in light of changing market conditions, is crucial to maintaining consistent trading performance.
7. Visual Representations
Visual tools are essential for traders, as they simplify complex data into an easily interpretable format. Properly analyzing and understanding the plots on a chart can provide actionable insights and a more intuitive grasp of market conditions. In this section, we’ll delve into various visual representations used in the Supertrend Advance Strategy and their significance.
Understanding Plots on the Chart:
Charts are the primary visual aids for traders. The arrangement of data points, lines, and colors on them tell a story about the market's past, present, and potential future moves.
1. Data Points: These represent individual price actions over a specific timeframe. For instance, a daily chart will have data points showing the opening, closing, high, and low prices for each day.
2. Colors: Used to indicate the nature of price movement. Commonly, green is used for bullish (upward) moves and red for bearish (downward) moves.
Trend Lines:
Trend lines are straight lines drawn on a chart that connect a series of price points. Their significance:
1. Uptrend Line: Drawn along the lows, representing support. A break below might indicate a trend reversal.
2. Downtrend Line: Drawn along the highs, indicating resistance. A break above might suggest the start of a bullish trend.
Filled Areas:
These represent a range between two values on a chart, usually shaded or colored. For instance:
1. Bollinger Bands: The area between the upper and lower band is filled, giving a visual representation of volatility.
2. Volume Profile: Can show a filled area representing the amount of trading activity at different price levels.
Stop Loss and Take Profit Lines:
These are horizontal lines representing pre-determined exit points for trades.
1. Stop Loss Line: Indicates the level at which a trade will be automatically closed to limit losses. Positioned according to the trader's risk tolerance.
2. Take Profit Line: Denotes the target level to lock in profits. Set according to potential resistance (for long trades) or support (for short trades) or other technical factors.
Trailing Stop Lines:
A trailing stop is a dynamic form of stop loss that moves with the price. On a chart:
1. For Long Trades: Starts below the entry price and moves up with the price but remains static if the price falls, ensuring profits are locked in.
2. For Short Trades: Starts above the entry price and moves down with the price but remains static if the price rises.
Visual representations offer traders a clear, organized view of market dynamics. Familiarity with these tools ensures that traders can quickly and accurately interpret chart data, leading to more informed decision-making. Always ensure that the visual aids used resonate with your trading style and strategy for the best results.
8. Backtesting
Backtesting is a fundamental process in strategy development, enabling traders to evaluate the efficacy of their strategy using historical data. It provides a snapshot of how the strategy would have performed in past market conditions, offering insights into its potential strengths and vulnerabilities. In this section, we'll explore the intricacies of setting up and analyzing backtest results and the caveats one must be aware of.
Setting Up Backtest Period:
1. Duration: Determine the timeframe for the backtest. It should be long enough to capture various market conditions (bullish, bearish, sideways). For instance, if you're testing a daily strategy, consider a period of several years.
2. Data Quality: Ensure the data source is reliable, offering high-resolution and clean data. This is vital to get accurate backtest results.
3. Segmentation: Instead of a continuous period, sometimes it's helpful to backtest over distinct market phases, like a particular bear or bull market, to see how the strategy holds up in different environments.
Analyzing Backtest Results:
1. Performance Metrics: Examine metrics like the total return, annualized return, maximum drawdown, Sharpe ratio, and others to gauge the strategy's efficiency.
2. Win Rate: It's the ratio of winning trades to total trades. A high win rate doesn't always signify a good strategy; it should be evaluated in conjunction with other metrics.
3. Risk/Reward: Understand the average profit versus the average loss per trade. A strategy might have a low win rate but still be profitable if the average gain far exceeds the average loss.
4. Drawdown Analysis: Review the periods of losses the strategy could incur and how long it takes, on average, to recover.
9. Tips and Best Practices
Successful trading requires more than just knowing how a strategy works. It necessitates an understanding of when to apply it, how to adjust it to varying market conditions, and the wisdom to recognize and avoid common pitfalls. This section offers insightful tips and best practices to enhance the application of the Supertrend Advance Strategy.
When to Use the Strategy:
1. Market Conditions: Ideally, employ the Supertrend Advance Strategy during trending market conditions. This strategy thrives when there are clear upward or downward trends. It might be less effective during consolidative or sideways markets.
2. News Events: Be cautious around significant news events, as they can cause extreme volatility. It might be wise to avoid trading immediately before and after high-impact news.
3. Liquidity: Ensure you are trading in assets/markets with sufficient liquidity. High liquidity ensures that the price movements are more reflective of genuine market sentiment and not due to thin volume.
Adjusting Settings for Different Markets/Timeframes:
1. Markets: Each market (stocks, forex, commodities) has its own characteristics. It's essential to adjust the strategy's parameters to align with the market's volatility and liquidity.
2. Timeframes: Shorter timeframes (like 1-minute or 5-minute charts) tend to have more noise. You might need to adjust the settings to filter out false signals. Conversely, for longer timeframes (like daily or weekly charts), you might need to be more responsive to genuine trend changes.
3. Customization: Regularly review and tweak the strategy's settings. Periodic adjustments can ensure the strategy remains optimized for the current market conditions.
10. Frequently Asked Questions (FAQs)
Given the complexities and nuances of the Supertrend Advance Strategy, it's only natural for traders, both new and seasoned, to have questions. This section addresses some of the most commonly asked questions regarding the strategy.
1. What exactly is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is an evolved version of the traditional Supertrend indicator. It's designed to provide clearer buy and sell signals by incorporating additional indicators like EMA, RSI, MACD, CCI, etc. The strategy aims to capitalize on market trends while minimizing false signals.
2. Can I use the Supertrend Advance Strategy for all asset types?
Yes, the strategy can be applied to various asset types like stocks, forex, commodities, and cryptocurrencies. However, it's crucial to adjust the settings accordingly to suit the specific characteristics and volatility of each asset type.
3. Is this strategy suitable for day trading?
Absolutely! The Supertrend Advance Strategy can be adjusted to suit various timeframes, making it versatile for both day trading and long-term trading. Remember to fine-tune the settings to align with the timeframe you're trading on.
4. How do I deal with false signals?
No strategy is immune to false signals. However, by combining the Supertrend with other indicators and adhering to strict risk management protocols, you can minimize the impact of false signals. Always use stop-loss orders and consider filtering trades with additional confirmation signals.
5. Do I need any prior trading experience to use this strategy?
While the Supertrend Advance Strategy is designed to be user-friendly, having a foundational understanding of trading and market analysis can greatly enhance your ability to employ the strategy effectively. If you're a beginner, consider pairing the strategy with further education and practice on demo accounts.
6. How often should I review and adjust the strategy settings?
There's no one-size-fits-all answer. Some traders adjust settings weekly, while others might do it monthly. The key is to remain responsive to changing market conditions. Regular backtesting can give insights into potential required adjustments.
7. Can the Supertrend Advance Strategy be automated?
Yes, many traders use algorithmic trading platforms to automate their strategies, including the Supertrend Advance Strategy. However, always monitor automated systems regularly to ensure they're operating as intended.
8. Are there any markets or conditions where the strategy shouldn't be used?
The strategy might generate more false signals in markets that are consolidative or range-bound. During significant news events or times of unexpected high volatility, it's advisable to tread with caution or stay out of the market.
9. How important is backtesting with this strategy?
Backtesting is crucial as it allows traders to understand how the strategy would have performed in the past, offering insights into potential profitability and areas of improvement. Always backtest any new setting or tweak before applying it to live trades.
10. What if the strategy isn't working for me?
No strategy guarantees consistent profits. If it's not working for you, consider reviewing your settings, seeking expert advice, or complementing the Supertrend Advance Strategy with other analysis methods. Remember, continuous learning and adaptation are the keys to trading success.
Other comments
Value of combining several indicators in this script and how they work together
Diversification of Signals: Just as diversifying an investment portfolio can reduce risk, using multiple indicators can offer varied perspectives on potential price movements. Each indicator can capture a different facet of the market, ensuring that traders are not overly reliant on a single data point.
Confirmation & Reduced False Signals: A common challenge with many indicators is the potential for false signals. By requiring confirmation from multiple indicators before acting, the chances of acting on a false signal can be significantly reduced.
Flexibility Across Market Conditions: Different indicators might perform better under different market conditions. For example, while moving averages might excel in trending markets, oscillators like RSI might be more useful during sideways or range-bound conditions. A mashup strategy can potentially adapt better to varying market scenarios.
Comprehensive Analysis: With multiple indicators, traders can gauge trend strength, momentum, volatility, and potential market reversals all at once, providing a holistic view of the market.
How do the different indicators in the Supertrend Advance Strategy work together?
Supertrend: This is primarily a trend-following indicator. It provides traders with buy and sell signals based on the volatility of the price. When combined with other indicators, it can filter out noise and give more weight to strong, confirmed trends.
EMA (Exponential Moving Average): EMA gives more weight to recent price data. It can be used to identify the direction and strength of a trend. When the price is above the EMA, it's generally considered bullish, and vice versa.
RSI (Relative Strength Index): An oscillator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. By cross-referencing with other indicators like EMA or MACD, traders can spot potential reversals or confirmations of a trend.
MACD (Moving Average Convergence Divergence): This indicator identifies changes in the strength, direction, momentum, and duration of a trend in a stock's price. When the MACD line crosses above the signal line, it can be a bullish sign, and when it crosses below, it can be bearish. Pairing MACD with Supertrend can provide dual confirmation of a trend.
CCI (Commodity Channel Index): Initially developed for commodities, CCI can indicate overbought or oversold conditions. It can be used in conjunction with other indicators to determine entry and exit points.
In essence, the synergy of these indicators provides a balanced, comprehensive approach to trading. Each indicator offers its unique lens into market conditions, and when they align, it can be a powerful indication of a trading opportunity. This combination not only reduces the potential drawbacks of each individual indicator but leverages their strengths, aiming for more consistent and informed trading decisions.
Backtesting and Default Settings
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
• Default properties: RSI on (length 14, RSI buy level 50, sell level 50), EMA, RSI, MACD on, type of strategy pullback, SL/TP type: ATR (length 10, factor 3), trade direction both, quantity 5, take profit swing hl 5.1, highest / lowest lookback 2, enable ATR trail (ATR length 10, SL ATR multiplier 1.4, TP multiplier 2.1, lookback = 4, trade direction = both).
Uhl MA System - Strategy AnalysisThe Uhl MA crossover system was specifically designed to provide an adaptive MA crossover system that didn't committed the same errors of more classical MA systems. This crossover system is based on a fast and a slow moving average, with the slow moving average being the corrected moving average (CMA) originally proposed by Andreas Uhl, and the fast moving average being the corrected trend step (CTS) which is also based on the corrected moving average design.
For more information see :
In this post, the performances of this system are analyzed on various markets.
Setup And Rules
The analysis is solely based on the indicator signals, therefore no spread is applied. Constant position sizing is used. The strategy will be backtested on the 15 minute time-frame. The mult setting is discarded, the default setting used for length is 100.
Here are the rules of our strategy :
long: CTS crossover CMA
short: CTS crossunder CMA
Results And Data
EURUSD:
Net Profit: $ 0.08
Total number of trades: 99
Profitability: 35.35 %
Profit Factor: 1.834
Max Drawdown: $ 0.01
EURUSD behaved pretty well, and was most of time showing long term trends without exhibiting particularly tricky structures, the moving averages still did cross during ranging phases, since march 9 we can see a downtrend with more pronounced cyclical variations (retracements) that could potentially lead to loosing trades.
BTCUSD:
Net Profit: $ 4371.57
Total number of trades: 94
Profitability: 32.98 %
Profit Factor: 1.749
Max Drawdown: $ 1409.96
The strategy didn't started well, producing its largest drawdown after only a few trades, the strategy still managed to recover. BTCUSD exhibited a strong downtrend, the strategy profited from that to recover, signals still occurred on ranging phases, and where mostly caused by a short term volatile move, unfortunately the CMA can converge toward ranging/flat price zones where false signals might occur at higher frequency.
AMD:
Net Profit: $ 16.09
Total number of trades: 95
Profitability: 29.47 %
Profit Factor: 1.288
Max Drawdown: $ 20.11
On AMD the strategy started relatively well with a raising balance, then the balance quickly fallen, this downtrend in the balance lasted quite some time (almost 48 trades), the strategy finally recovered in Nov 2019 and the balance made a new highest high at the end of February. AMD had numerous trends during the backtesting period, yet results are poor.
AAPL:
Net Profit: $ -28.17
Total number of trades: 89
Profitability: 28.09 %
Profit Factor: 0.894
Max Drawdown: $ 63.21
AAPL show the poorest results so far, with a stationary balance around the initial capital (in short the evolution of the balance is not showing any particular trend and oscillate around the initial capital value).
AAPL had some significant retracements in its up-trend, which triggered some trades (of course), and the ranging period from Jan 24 to Feb 13 heavily damaged the strategy performance, generating 6 significant loosing trades. AAPL show the worst results so far, mostly due by ranging phases.
Conclusions
The Uhl MA crossover system strategy has been tested and based on the results don't show particularly interesting performances, and might even be outperformed by simpler MA systems that prove to be more robust against ranging markets. The total number of executed trades are on average 94, and the profitability is on average 31%. The strategy might prove more interesting if we can correct the behavior of the CMA, who sometimes converged toward ranging/flat markets.
Golden Cross 50/200Simplicity characterizes each of my trading systems and methods. On this occasion, I present a trend-following strategy with simple rules and high profitability.
System Rules:
-Long entries when the 50 EMA crosses above the 200 EMA.
-Stop Loss (SL) placed at the low of 15 candles prior to the entry candle.
-Take Profit (TP) triggered when the 50 EMA crosses below the 200 EMA.
As with any trend-following system, we sacrifice win rate for profitability, and of course, we will focus on traditional markets with a consistent trend-following nature over time.
Recommended Markets and Timeframes:
BTCUSDT H6
August 17, 2017 - October 20, 2025 Total trades: 30
Profitability: +1,682.99%
Win rate: 40%
Outperforms Buy & Hold
BTCUSDT H4
August 17, 2017 - October 20, 2025 Total trades: 42
Profitability: +12,213.49% (high and stable performance curve)
Win rate: 40%
Outperforms Buy & Hold
BTCUSDT H2
August 17, 2017 - October 20, 2025 Total trades: 95
Profitability: +2,363.80%
Win rate: 24.21%
Matches Buy & Hold
BTCUSDT H1
August 17, 2017 - October 20, 2025 Total trades: 203
Profitability: +1,045% (stable performance curve)
Win rate: 25.62%
BTCUSDT 30M
August 17, 2017 - October 20, 2025 Total trades: 393
Profitability: +4,205.51% (high and stable performance curve)
Win rate: 27.74%
Outperforms Buy & Hold
BTCUSDT 15M
August 17, 2017 - October 20, 2025 Total trades: 821
Profitability: +1,311.97%
Win rate: 23.14%
Timeframes such as Daily, 12-hour, 8-hour, and even 5-minute charts are profitable with this system, so feel free to experiment.
Other markets and timeframes to observe include:
-XAUUSD (H1, H4, H6, H8, Daily)
-SPX (Daily: +21,302% profitability since 1871 in 40 trades)
-Tesla (H1, H2, H4, H6, especially M30 and M15)
-Apple (M5, M15, M30, H1, H2, H4…)
-Warner Bros (M5, M15, M30…)
-GOOGL (M5, M15, M30, H1, H2, H4, H6…)
-AMZN (M5, M15, M30, H2, H4, H6…)
-META (M5, M15, M30, H1, H2, H4…)
-NVDA (M5, M15, M30, H1, H2, H4…)
This system not only generates significant profitability but also performs very well in traditional markets, even on lower timeframes like 5-minute charts. In many cases, the returns far exceed Buy & Hold.
I hope this strategy is useful to you. Follow my Spanish-speaking profile if you want to see my market analyses, and send me your good vibes!
Backtesting & Trading Engine [PineCoders]The PineCoders Backtesting and Trading Engine is a sophisticated framework with hybrid code that can run as a study to generate alerts for automated or discretionary trading while simultaneously providing backtest results. It can also easily be converted to a TradingView strategy in order to run TV backtesting. The Engine comes with many built-in strats for entries, filters, stops and exits, but you can also add you own.
If, like any self-respecting strategy modeler should, you spend a reasonable amount of time constantly researching new strategies and tinkering, our hope is that the Engine will become your inseparable go-to tool to test the validity of your creations, as once your tests are conclusive, you will be able to run this code as a study to generate the alerts required to put it in real-world use, whether for discretionary trading or to interface with an execution bot/app. You may also find the backtesting results the Engine produces in study mode enough for your needs and spend most of your time there, only occasionally converting to strategy mode in order to backtest using TV backtesting.
As you will quickly grasp when you bring up this script’s Settings, this is a complex tool. While you will be able to see results very quickly by just putting it on a chart and using its built-in strategies, in order to reap the full benefits of the PineCoders Engine, you will need to invest the time required to understand the subtleties involved in putting all its potential into play.
Disclaimer: use the Engine at your own risk.
Before we delve in more detail, here’s a bird’s eye view of the Engine’s features:
More than 40 built-in strategies,
Customizable components,
Coupling with your own external indicator,
Simple conversion from Study to Strategy modes,
Post-Exit analysis to search for alternate trade outcomes,
Use of the Data Window to show detailed bar by bar trade information and global statistics, including some not provided by TV backtesting,
Plotting of reminders and generation of alerts on in-trade events.
By combining your own strats to the built-in strats supplied with the Engine, and then tuning the numerous options and parameters in the Inputs dialog box, you will be able to play what-if scenarios from an infinite number of permutations.
USE CASES
You have written an indicator that provides an entry strat but it’s missing other components like a filter and a stop strategy. You add a plot in your indicator that respects the Engine’s External Signal Protocol, connect it to the Engine by simply selecting your indicator’s plot name in the Engine’s Settings/Inputs and then run tests on different combinations of entry stops, in-trade stops and profit taking strats to find out which one produces the best results with your entry strat.
You are building a complex strategy that you will want to run as an indicator generating alerts to be sent to a third-party execution bot. You insert your code in the Engine’s modules and leverage its trade management code to quickly move your strategy into production.
You have many different filters and want to explore results using them separately or in combination. Integrate the filter code in the Engine and run through different permutations or hook up your filtering through the external input and control your filter combos from your indicator.
You are tweaking the parameters of your entry, filter or stop strat. You integrate it in the Engine and evaluate its performance using the Engine’s statistics.
You always wondered what results a random entry strat would yield on your markets. You use the Engine’s built-in random entry strat and test it using different combinations of filters, stop and exit strats.
You want to evaluate the impact of fees and slippage on your strategy. You use the Engine’s inputs to play with different values and get immediate feedback in the detailed numbers provided in the Data Window.
You just want to inspect the individual trades your strategy generates. You include it in the Engine and then inspect trades visually on your charts, looking at the numbers in the Data Window as you move your cursor around.
You have never written a production-grade strategy and you want to learn how. Inspect the code in the Engine; you will find essential components typical of what is being used in actual trading systems.
You have run your system for a while and have compiled actual slippage information and your broker/exchange has updated his fees schedule. You enter the information in the Engine and run it on your markets to see the impact this has on your results.
FEATURES
Before going into the detail of the Inputs and the Data Window numbers, here’s a more detailed overview of the Engine’s features.
Built-in strats
The engine comes with more than 40 pre-coded strategies for the following standard system components:
Entries,
Filters,
Entry stops,
2 stage in-trade stops with kick-in rules,
Pyramiding rules,
Hard exits.
While some of the filter and stop strats provided may be useful in production-quality systems, you will not devise crazy profit-generating systems using only the entry strats supplied; that part is still up to you, as will be finding the elusive combination of components that makes winning systems. The Engine will, however, provide you with a solid foundation where all the trade management nitty-gritty is handled for you. By binding your custom strats to the Engine, you will be able to build reliable systems of the best quality currently allowed on the TV platform.
On-chart trade information
As you move over the bars in a trade, you will see trade numbers in the Data Window change at each bar. The engine calculates the P&L at every bar, including slippage and fees that would be incurred were the trade exited at that bar’s close. If the trade includes pyramided entries, those will be taken into account as well, although for those, final fees and slippage are only calculated at the trade’s exit.
You can also see on-chart markers for the entry level, stop positions, in-trade special events and entries/exits (you will want to disable these when using the Engine in strategy mode to see TV backtesting results).
Customization
You can couple your own strats to the Engine in two ways:
1. By inserting your own code in the Engine’s different modules. The modular design should enable you to do so with minimal effort by following the instructions in the code.
2. By linking an external indicator to the engine. After making the proper selections in the engine’s Settings and providing values respecting the engine’s protocol, your external indicator can, when the Engine is used in Indicator mode only:
Tell the engine when to enter long or short trades, but let the engine’s in-trade stop and exit strats manage the exits,
Signal both entries and exits,
Provide an entry stop along with your entry signal,
Filter other entry signals generated by any of the engine’s entry strats.
Conversion from strategy to study
TradingView strategies are required to backtest using the TradingView backtesting feature, but if you want to generate alerts with your script, whether for automated trading or just to trigger alerts that you will use in discretionary trading, your code has to run as a study since, for the time being, strategies can’t generate alerts. From hereon we will use indicator as a synonym for study.
Unless you want to maintain two code bases, you will need hybrid code that easily flips between strategy and indicator modes, and your code will need to restrict its use of strategy() calls and their arguments if it’s going to be able to run both as an indicator and a strategy using the same trade logic. That’s one of the benefits of using this Engine. Once you will have entered your own strats in the Engine, it will be a matter of commenting/uncommenting only four lines of code to flip between indicator and strategy modes in a matter of seconds.
Additionally, even when running in Indicator mode, the Engine will still provide you with precious numbers on your individual trades and global results, some of which are not available with normal TradingView backtesting.
Post-Exit Analysis for alternate outcomes (PEA)
While typical backtesting shows results of trade outcomes, PEA focuses on what could have happened after the exit. The intention is to help traders get an idea of the opportunity/risk in the bars following the trade in order to evaluate if their exit strategies are too aggressive or conservative.
After a trade is exited, the Engine’s PEA module continues analyzing outcomes for a user-defined quantity of bars. It identifies the maximum opportunity and risk available in that space, and calculates the drawdown required to reach the highest opportunity level post-exit, while recording the number of bars to that point.
Typically, if you can’t find opportunity greater than 1X past your trade using a few different reasonable lengths of PEA, your strategy is doing pretty good at capturing opportunity. Remember that 100% of opportunity is never capturable. If, however, PEA was finding post-trade maximum opportunity of 3 or 4X with average drawdowns of 0.3 to those areas, this could be a clue revealing your system is exiting trades prematurely. To analyze PEA numbers, you can uncomment complete sets of plots in the Plot module to reveal detailed global and individual PEA numbers.
Statistics
The Engine provides stats on your trades that TV backtesting does not provide, such as:
Average Profitability Per Trade (APPT), aka statistical expectancy, a crucial value.
APPT per bar,
Average stop size,
Traded volume .
It also shows you on a trade-by-trade basis, on-going individual trade results and data.
In-trade events
In-trade events can plot reminders and trigger alerts when they occur. The built-in events are:
Price approaching stop,
Possible tops/bottoms,
Large stop movement (for discretionary trading where stop is moved manually),
Large price movements.
Slippage and Fees
Even when running in indicator mode, the Engine allows for slippage and fees to be included in the logic and test results.
Alerts
The alert creation mechanism allows you to configure alerts on any combination of the normal or pyramided entries, exits and in-trade events.
Backtesting results
A few words on the numbers calculated in the Engine. Priority is given to numbers not shown in TV backtesting, as you can readily convert the script to a strategy if you need them.
We have chosen to focus on numbers expressing results relative to X (the trade’s risk) rather than in absolute currency numbers or in other more conventional but less useful ways. For example, most of the individual trade results are not shown in percentages, as this unit of measure is often less meaningful than those expressed in units of risk (X). A trade that closes with a +25% result, for example, is a poor outcome if it was entered with a -50% stop. Expressed in X, this trade’s P&L becomes 0.5, which provides much better insight into the trade’s outcome. A trade that closes with a P&L of +2X has earned twice the risk incurred upon entry, which would represent a pre-trade risk:reward ratio of 2.
The way to go about it when you think in X’s and that you adopt the sound risk management policy to risk a fixed percentage of your account on each trade is to equate a currency value to a unit of X. E.g. your account is 10K USD and you decide you will risk a maximum of 1% of it on each trade. That means your unit of X for each trade is worth 100 USD. If your APPT is 2X, this means every time you risk 100 USD in a trade, you can expect to make, on average, 200 USD.
By presenting results this way, we hope that the Engine’s statistics will appeal to those cognisant of sound risk management strategies, while gently leading traders who aren’t, towards them.
We trade to turn in tangible profits of course, so at some point currency must come into play. Accordingly, some values such as equity, P&L, slippage and fees are expressed in currency.
Many of the usual numbers shown in TV backtests are nonetheless available, but they have been commented out in the Engine’s Plot module.
Position sizing and risk management
All good system designers understand that optimal risk management is at the very heart of all winning strategies. The risk in a trade is defined by the fraction of current equity represented by the amplitude of the stop, so in order to manage risk optimally on each trade, position size should adjust to the stop’s amplitude. Systems that enter trades with a fixed stop amplitude can get away with calculating position size as a fixed percentage of current equity. In the context of a test run where equity varies, what represents a fixed amount of risk translates into different currency values.
Dynamically adjusting position size throughout a system’s life is optimal in many ways. First, as position sizing will vary with current equity, it reproduces a behavioral pattern common to experienced traders, who will dial down risk when confronted to poor performance and increase it when performance improves. Second, limiting risk confers more predictability to statistical test results. Third, position sizing isn’t just about managing risk, it’s also about maximizing opportunity. By using the maximum leverage (no reference to trading on margin here) into the trade that your risk management strategy allows, a dynamic position size allows you to capture maximal opportunity.
To calculate position sizes using the fixed risk method, we use the following formula: Position = Account * MaxRisk% / Stop% [, which calculates a position size taking into account the trade’s entry stop so that if the trade is stopped out, 100 USD will be lost. For someone who manages risk this way, common instructions to invest a certain percentage of your account in a position are simply worthless, as they do not take into account the risk incurred in the trade.
The Engine lets you select either the fixed risk or fixed percentage of equity position sizing methods. The closest thing to dynamic position sizing that can currently be done with alerts is to use a bot that allows syntax to specify position size as a percentage of equity which, while being dynamic in the sense that it will adapt to current equity when the trade is entered, does not allow us to modulate position size using the stop’s amplitude. Changes to alerts are on the way which should solve this problem.
In order for you to simulate performance with the constraint of fixed position sizing, the Engine also offers a third, less preferable option, where position size is defined as a fixed percentage of initial capital so that it is constant throughout the test and will thus represent a varying proportion of current equity.
Let’s recap. The three position sizing methods the Engine offers are:
1. By specifying the maximum percentage of risk to incur on your remaining equity, so the Engine will dynamically adjust position size for each trade so that, combining the stop’s amplitude with position size will yield a fixed percentage of risk incurred on current equity,
2. By specifying a fixed percentage of remaining equity. Note that unless your system has a fixed stop at entry, this method will not provide maximal risk control, as risk will vary with the amplitude of the stop for every trade. This method, as the first, does however have the advantage of automatically adjusting position size to equity. It is the Engine’s default method because it has an equivalent in TV backtesting, so when flipping between indicator and strategy mode, test results will more or less correspond.
3. By specifying a fixed percentage of the Initial Capital. While this is the least preferable method, it nonetheless reflects the reality confronted by most system designers on TradingView today. In this case, risk varies both because the fixed position size in initial capital currency represents a varying percentage of remaining equity, and because the trade’s stop amplitude may vary, adding another variability vector to risk.
Note that the Engine cannot display equity results for strategies entering trades for a fixed amount of shares/contracts at a variable price.
SETTINGS/INPUTS
Because the initial text first published with a script cannot be edited later and because there are just too many options, the Engine’s Inputs will not be covered in minute detail, as they will most certainly evolve. We will go over them with broad strokes; you should be able to figure the rest out. If you have questions, just ask them here or in the PineCoders Telegram group.
Display
The display header’s checkbox does nothing.
For the moment, only one exit strategy uses a take profit level, so only that one will show information when checking “Show Take Profit Level”.
Entries
You can activate two simultaneous entry strats, each selected from the same set of strats contained in the Engine. If you select two and they fire simultaneously, the main strat’s signal will be used.
The random strat in each list uses a different seed, so you will get different results from each.
The “Filter transitions” and “Filter states” strats delegate signal generation to the selected filter(s). “Filter transitions” signals will only fire when the filter transitions into bull/bear state, so after a trade is stopped out, the next entry may take some time to trigger if the filter’s state does not change quickly. When you choose “Filter states”, then a new trade will be entered immediately after an exit in the direction the filter allows.
If you select “External Indicator”, your indicator will need to generate a +2/-2 (or a positive/negative stop value) to enter a long/short position, providing the selected filters allow for it. If you wish to use the Engine’s capacity to also derive the entry stop level from your indicator’s signal, then you must explicitly choose this option in the Entry Stops section.
Filters
You can activate as many filters as you wish; they are additive. The “Maximum stop allowed on entry” is an important component of proper risk management. If your system has an average 3% stop size and you need to trade using fixed position sizes because of alert/execution bot limitations, you must use this filter because if your system was to enter a trade with a 15% stop, that trade would incur 5 times the normal risk, and its result would account for an abnormally high proportion in your system’s performance.
Remember that any filter can also be used as an entry signal, either when it changes states, or whenever no trade is active and the filter is in a bull or bear mode.
Entry Stops
An entry stop must be selected in the Engine, as it requires a stop level before the in-trade stop is calculated. Until the selected in-trade stop strat generates a stop that comes closer to price than the entry stop (or respects another one of the in-trade stops kick in strats), the entry stop level is used.
It is here that you must select “External Indicator” if your indicator supplies a +price/-price value to be used as the entry stop. A +price is expected for a long entry and a -price value will enter a short with a stop at price. Note that the price is the absolute price, not an offset to the current price level.
In-Trade Stops
The Engine comes with many built-in in-trade stop strats. Note that some of them share the “Length” and “Multiple” field, so when you swap between them, be sure that the length and multiple in use correspond to what you want for that stop strat. Suggested defaults appear with the name of each strat in the dropdown.
In addition to the strat you wish to use, you must also determine when it kicks in to replace the initial entry’s stop, which is determined using different strats. For strats where you can define a positive or negative multiple of X, percentage or fixed value for a kick-in strat, a positive value is above the trade’s entry fill and a negative one below. A value of zero represents breakeven.
Pyramiding
What you specify in this section are the rules that allow pyramiding to happen. By themselves, these rules will not generate pyramiding entries. For those to happen, entry signals must be issued by one of the active entry strats, and conform to the pyramiding rules which act as a filter for them. The “Filter must allow entry” selection must be chosen if you want the usual system’s filters to act as additional filtering criteria for your pyramided entries.
Hard Exits
You can choose from a variety of hard exit strats. Hard exits are exit strategies which signal trade exits on specific events, as opposed to price breaching a stop level in In-Trade Stops strategies. They are self-explanatory. The last one labelled When Take Profit Level (multiple of X) is reached is the only one that uses a level, but contrary to stops, it is above price and while it is relative because it is expressed as a multiple of X, it does not move during the trade. This is the level called Take Profit that is show when the “Show Take Profit Level” checkbox is checked in the Display section.
While stops focus on managing risk, hard exit strategies try to put the emphasis on capturing opportunity.
Slippage
You can define it as a percentage or a fixed value, with different settings for entries and exits. The entry and exit markers on the chart show the impact of slippage on the entry price (the fill).
Fees
Fees, whether expressed as a percentage of position size in and out of the trade or as a fixed value per in and out, are in the same units of currency as the capital defined in the Position Sizing section. Fees being deducted from your Capital, they do not have an impact on the chart marker positions.
In-Trade Events
These events will only trigger during trades. They can be helpful to act as reminders for traders using the Engine as assistance to discretionary trading.
Post-Exit Analysis
It is normally on. Some of its results will show in the Global Numbers section of the Data Window. Only a few of the statistics generated are shown; many more are available, but commented out in the Plot module.
Date Range Filtering
Note that you don’t have to change the dates to enable/diable filtering. When you are done with a specific date range, just uncheck “Date Range Filtering” to disable date filtering.
Alert Triggers
Each selection corresponds to one condition. Conditions can be combined into a single alert as you please. Just be sure you have selected the ones you want to trigger the alert before you create the alert. For example, if you trade in both directions and you want a single alert to trigger on both types of exits, you must select both “Long Exit” and “Short Exit” before creating your alert.
Once the alert is triggered, these settings no longer have relevance as they have been saved with the alert.
When viewing charts where an alert has just triggered, if your alert triggers on more than one condition, you will need the appropriate markers active on your chart to figure out which condition triggered the alert, since plotting of markers is independent of alert management.
Position sizing
You have 3 options to determine position size:
1. Proportional to Stop -> Variable, with a cap on size.
2. Percentage of equity -> Variable.
3. Percentage of Initial Capital -> Fixed.
External Indicator
This is where you connect your indicator’s plot that will generate the signals the Engine will act upon. Remember this only works in Indicator mode.
DATA WINDOW INFORMATION
The top part of the window contains global numbers while the individual trade information appears in the bottom part. The different types of units used to express values are:
curr: denotes the currency used in the Position Sizing section of Inputs for the Initial Capital value.
quote: denotes quote currency, i.e. the value the instrument is expressed in, or the right side of the market pair (USD in EURUSD ).
X: the stop’s amplitude, itself expressed in quote currency, which we use to express a trade’s P&L, so that a trade with P&L=2X has made twice the stop’s amplitude in profit. This is sometimes referred to as R, since it represents one unit of risk. It is also the unit of measure used in the APPT, which denotes expected reward per unit of risk.
X%: is also the stop’s amplitude, but expressed as a percentage of the Entry Fill.
The numbers appearing in the Data Window are all prefixed:
“ALL:” the number is the average for all first entries and pyramided entries.
”1ST:” the number is for first entries only.
”PYR:” the number is for pyramided entries only.
”PEA:” the number is for Post-Exit Analyses
Global Numbers
Numbers in this section represent the results of all trades up to the cursor on the chart.
Average Profitability Per Trade (X): This value is the most important gauge of your strat’s worthiness. It represents the returns that can be expected from your strat for each unit of risk incurred. E.g.: your APPT is 2.0, thus for every unit of currency you invest in a trade, you can on average expect to obtain 2 after the trade. APPT is also referred to as “statistical expectancy”. If it is negative, your strategy is losing, even if your win rate is very good (it means your winning trades aren’t winning enough, or your losing trades lose too much, or both). Its counterpart in currency is also shown, as is the APPT/bar, which can be a useful gauge in deciding between rivalling systems.
Profit Factor: Gross of winning trades/Gross of losing trades. Strategy is profitable when >1. Not as useful as the APPT because it doesn’t take into account the win rate and the average win/loss per trade. It is calculated from the total winning/losing results of this particular backtest and has less predictive value than the APPT. A good profit factor together with a poor APPT means you just found a chart where your system outperformed. Relying too much on the profit factor is a bit like a poker player who would think going all in with two’s against aces is optimal because he just won a hand that way.
Win Rate: Percentage of winning trades out of all trades. Taken alone, it doesn’t have much to do with strategy profitability. You can have a win rate of 99% but if that one trade in 100 ruins you because of poor risk management, 99% doesn’t look so good anymore. This number speaks more of the system’s profile than its worthiness. Still, it can be useful to gauge if the system fits your personality. It can also be useful to traders intending to sell their systems, as low win rate systems are more difficult to sell and require more handholding of worried customers.
Equity (curr): This the sum of initial capital and the P&L of your system’s trades, including fees and slippage.
Return on Capital is the equivalent of TV’s Net Profit figure, i.e. the variation on your initial capital.
Maximum drawdown is the maximal drawdown from the highest equity point until the drop . There is also a close to close (meaning it doesn’t take into account in-trade variations) maximum drawdown value commented out in the code.
The next values are self-explanatory, until:
PYR: Avg Profitability Per Entry (X): this is the APPT for all pyramided entries.
PEA: Avg Max Opp . Available (X): the average maximal opportunity found in the Post-Exit Analyses.
PEA: Avg Drawdown to Max Opp . (X): this represents the maximum drawdown (incurred from the close at the beginning of the PEA analysis) required to reach the maximal opportunity point.
Trade Information
Numbers in this section concern only the current trade under the cursor. Most of them are self-explanatory. Use the description’s prefix to determine what the values applies to.
PYR: Avg Profitability Per Entry (X): While this value includes the impact of all current pyramided entries (and only those) and updates when you move your cursor around, P&L only reflects fees at the trade’s last bar.
PEA: Max Opp . Available (X): It’s the most profitable close reached post-trade, measured from the trade’s Exit Fill, expressed in the X value of the trade the PEA follows.
PEA: Drawdown to Max Opp . (X): This is the maximum drawdown from the trade’s Exit Fill that needs to be sustained in order to reach the maximum opportunity point, also expressed in X. Note that PEA numbers do not include slippage and fees.
EXTERNAL SIGNAL PROTOCOL
Only one external indicator can be connected to a script; in order to leverage its use to the fullest, the engine provides options to use it as either an entry signal, an entry/exit signal or a filter. When used as an entry signal, you can also use the signal to provide the entry’s stop. Here’s how this works:
For filter state: supply +1 for bull (long entries allowed), -1 for bear (short entries allowed).
For entry signals: supply +2 for long, -2 for short.
For exit signals: supply +3 for exit from long, -3 for exit from short.
To send an entry stop level with an entry signal: Send positive stop level for long entry (e.g. 103.33 to enter a long with a stop at 103.33), negative stop level for short entry (e.g. -103.33 to enter a short with a stop at 103.33). If you use this feature, your indicator will have to check for exact stop levels of 1.0, 2.0 or 3.0 and their negative counterparts, and fudge them with a tick in order to avoid confusion with other signals in the protocol.
Remember that mere generation of the values by your indicator will have no effect until you explicitly allow their use in the appropriate sections of the Engine’s Settings/Inputs.
An example of a script issuing a signal for the Engine is published by PineCoders.
RECOMMENDATIONS TO ASPIRING SYSTEM DESIGNERS
Stick to higher timeframes. On progressively lower timeframes, margins decrease and fees and slippage take a proportionally larger portion of profits, to the point where they can very easily turn a profitable strategy into a losing one. Additionally, your margin for error shrinks as the equilibrium of your system’s profitability becomes more fragile with the tight numbers involved in the shorter time frames. Avoid <1H time frames.
Know and calculate fees and slippage. To avoid market shock, backtest using conservative fees and slippage parameters. Systems rarely show unexpectedly good returns when they are confronted to the markets, so put all chances on your side by being outrageously conservative—or a the very least, realistic. Test results that do not include fees and slippage are worthless. Slippage is there for a reason, and that’s because our interventions in the market change the market. It is easier to find alpha in illiquid markets such as cryptos because not many large players participate in them. If your backtesting results are based on moving large positions and you don’t also add the inevitable slippage that will occur when you enter/exit thin markets, your backtesting will produce unrealistic results. Even if you do include large slippage in your settings, the Engine can only do so much as it will not let slippage push fills past the high or low of the entry bar, but the gap may be much larger in illiquid markets.
Never test and optimize your system on the same dataset , as that is the perfect recipe for overfitting or data dredging, which is trying to find one precise set of rules/parameters that works only on one dataset. These setups are the most fragile and often get destroyed when they meet the real world.
Try to find datasets yielding more than 100 trades. Less than that and results are not as reliable.
Consider all backtesting results with suspicion. If you never entertained sceptic tendencies, now is the time to begin. If your backtest results look really good, assume they are flawed, either because of your methodology, the data you’re using or the software doing the testing. Always assume the worse and learn proper backtesting techniques such as monte carlo simulations and walk forward analysis to avoid the traps and biases that unchecked greed will set for you. If you are not familiar with concepts such as survivor bias, lookahead bias and confirmation bias, learn about them.
Stick to simple bars or candles when designing systems. Other types of bars often do not yield reliable results, whether by design (Heikin Ashi) or because of the way they are implemented on TV (Renko bars).
Know that you don’t know and use that knowledge to learn more about systems and how to properly test them, about your biases, and about yourself.
Manage risk first , then capture opportunity.
Respect the inherent uncertainty of the future. Cleanse yourself of the sad arrogance and unchecked greed common to newcomers to trading. Strive for rationality. Respect the fact that while backtest results may look promising, there is no guarantee they will repeat in the future (there is actually a high probability they won’t!), because the future is fundamentally unknowable. If you develop a system that looks promising, don’t oversell it to others whose greed may lead them to entertain unreasonable expectations.
Have a plan. Understand what king of trading system you are trying to build. Have a clear picture or where entries, exits and other important levels will be in the sort of trade you are trying to create with your system. This stated direction will help you discard more efficiently many of the inevitably useless ideas that will pop up during system design.
Be wary of complexity. Experienced systems engineers understand how rapidly complexity builds when you assemble components together—however simple each one may be. The more complex your system, the more difficult it will be to manage.
Play! . Allow yourself time to play around when you design your systems. While much comes about from working with a purpose, great ideas sometimes come out of just trying things with no set goal, when you are stuck and don’t know how to move ahead. Have fun!
@LucF
NOTES
While the engine’s code can supply multiple consecutive entries of longs or shorts in order to scale positions (pyramid), all exits currently assume the execution bot will exit the totality of the position. No partial exits are currently possible with the Engine.
Because the Engine is literally crippled by the limitations on the number of plots a script can output on TV; it can only show a fraction of all the information it calculates in the Data Window. You will find in the Plot Module vast amounts of commented out lines that you can activate if you also disable an equivalent number of other plots. This may be useful to explore certain characteristics of your system in more detail.
When backtesting using the TV backtesting feature, you will need to provide the strategy parameters you wish to use through either Settings/Properties or by changing the default values in the code’s header. These values are defined in variables and used not only in the strategy() statement, but also as defaults in the Engine’s relevant Inputs.
If you want to test using pyramiding, then both the strategy’s Setting/Properties and the Engine’s Settings/Inputs need to allow pyramiding.
If you find any bugs in the Engine, please let us know.
THANKS
To @glaz for allowing the use of his unpublished MA Squize in the filters.
To @everget for his Chandelier stop code, which is also used as a filter in the Engine.
To @RicardoSantos for his pseudo-random generator, and because it’s from him that I first read in the Pine chat about the idea of using an external indicator as input into another. In the PineCoders group, @theheirophant then mentioned the idea of using it as a buy/sell signal and @simpelyfe showed a piece of code implementing the idea. That’s the tortuous story behind the use of the external indicator in the Engine.
To @admin for the Volatility stop’s original code and for the donchian function lifted from Ichimoku .
To @BobHoward21 for the v3 version of Volatility Stop .
To @scarf and @midtownsk8rguy for the color tuning.
To many other scripters who provided encouragement and suggestions for improvement during the long process of writing and testing this piece of code.
To J. Welles Wilder Jr. for ATR, used extensively throughout the Engine.
To TradingView for graciously making an account available to PineCoders.
And finally, to all fellow PineCoders for the constant intellectual stimulation; it is a privilege to share ideas with you all. The Engine is for all TradingView PineCoders, of course—but especially for you.
Look first. Then leap.
Great Expectations [LucF]Great Expectations helps traders answer the question: What is possible? It is a powerful question, yet exploration of the unknown always entails risk. A more complete set of questions better suited to traders could be:
What opportunity exists from any given point on a chart?
What portion of this opportunity can be realistically captured?
What risk will be incurred in trying to do so, and how long will it take?
Great Expectations is the result of an exploration of these questions. It is a trade simulator that generates visual and quantitative information to help strategy modelers visually identify and analyse areas of optimal expectation on charts, whether they are designing automated or discretionary strategies.
WARNING: Great Expectations is NOT an indicator that helps determine the current state of a market. It works by looking at points in the past from which the future is already known. It uses one definition of repainting extensively (i.e. it goes back in the past to print information that could not have been know at the time). Repainting understood that way is in fact almost all the indicator does! —albeit for what I hope is a noble cause. The indicator is of no use whatsoever in analyzing markets in real-time. If you do not understand what it does, please stay away!
This is an indicator—not a strategy that uses TradingView’s backtesting engine. It works by simulating trades, not unlike a backtest, but with the crucial difference that it assumes a trade (either long or short) is entered on all bars in the historic sample. It walks forward from each bar and determines possible outcomes, gathering individual trade statistics that in turn generate precious global statistics from all outcomes tested on the chart.
Great Expectations provides numbers summarizing trade results on all simulations run from the chart. Those numbers cannot be compared to backtest-produced numbers since all non-filtered bars are examined, even if an entry was taken on the bar immediately preceding the current one, which never happens in a backtest. This peculiarity does NOT invalidate Great Expectations calculations; it just entails that results be considered under a different light. Provided they are evaluated within the indicator’s context, they can be useful—sometimes even more than backtesting results, e.g. in evaluating the impact of parameter-fitting or variations in entry, exit or filtering strats.
Traders and strategy modelers are creatures of hope often suffering from blurred vision; my hope is that Great Expectations will help them appraise the validity of their setup and strat intuitions in a realistic fashion, preventing confirmation bias from obstructing perspective—and great expectations from turning into financial great deceptions.
USE CASES
You’ve identified what looks like a promising setup on other indicators. You load Great Expectations on the chart and evaluate if its high-expectation areas match locations where your setup’s conditions occur. Unless today is your lucky day, chances are the indicator will help you realize your setup is not as promising as you had hoped.
You want to get a rough estimate of the optimal trade duration for a chart and you don’t mind using the entry and exit strategies provided with the indicator. You use the trade length readouts of the indicator.
You’re experimenting with a new stop strategy and want to know how long it will keep you in trades, on average. You integrate your stop strategy in the indicator’s code and look at the average trade length it produces and the TST ratio to evaluate its performance.
You have put together your own entry and exit criteria and are looking for a filter that will help you improve backtesting results. You visually ascertain the suitability of your filter by looking at its results on the charts with great Expectations, to see if your filter is choosing its areas correctly.
You have a strategy that shows backtested trades on your chart. Great Expectations can help you evaluate how well your strategy is benefitting from high-opportunity areas while avoiding poor expectation spots.
You want more complete statistics on your set of strategies than what backtesting will provide. You use Great Expectations, knowing that it tests all bars in the sample that correspond to your criteria, as opposed to backtesting results which are limited to a subset of all possible entries.
You want to fool your friends into thinking you’ve designed the holy grail of indicators, something that identifies optimal opportunities on any chart; you show them the P&L cloud.
FEATURES
For one trade
At any given point on the chart, assuming a trade is entered there, Great Expectations shows you information specific to that trade simulation both on the chart and in the Data Window.
The chart can display:
the P & L Cloud which shows whether the trade ended profitably or not, and by how much,
the Opportunity & Risk Cloud which the maximum opportunity and risk the simulation encountered. When superimposed over the P & L cloud, you will see what I call the managed opportunity and risk, i.e the portion of maximum opportunity that was captured and the portion of the maximum risk that was incurred,
the target and if it was reached,
a background that uses a gradient to show different levels of trade length, P&L or how frequently the target was reached during simulation.
The Data Window displays more than 40 values on individual trades and global results. For any given trade you will know:
Entry/Exit levels, including slippage impact,
It’s outcome and duration,
P/L achieved,
The fraction of the maximum opportunity/risk managed by the trade.
For all trades
After going through all the possible trades on the chart, the indicator will provide you with a rare view of all outcomes expressed with the P&L cloud, which allows us to instantly see the most/least profitable areas of a chart using trade data as support, while also showing its relationship with the opportunity/risk encountered during the simulation. The difference between the two clouds is the managed opportunity and risk.
The Data Window will present you with numbers which we will go through later. Some of them are: average stop size, P/L, win rate, % opportunity managed, trade lengths for different types of trade outcomes and the TST (Target:Stop Travel) ratio.
Let’s see Great Expectations in action… and remember to open your Data Window!
INPUTS
Trade direction : You must first choose if you wish to look at long or short trades. Because of the way the indicator works and the amount of visual information on the chart, it is only practical to look at one type of trades at a time. The default is Longs.
Maximum trade Length (MaxL) : This is the maximum walk forward distance the simulator will go in analyzing outcomes from any given point in the past. It also determines the size of the dead zone among the chart’s last bars. A red background line identifies the beginning of the dead zone for which not enough bars have elapsed to analyze outcomes for the maximum trade length defined. If an ATR-based entry stop is used, that length is added to the wait time before beginning simulations, so that the first entry starts with a clean ATR value. On a sample of around 16000 bars, my tests show that the indicator runs into server errors at lengths of around 290, i.e. having completed ~4,6M simulation loop iterations. That is way too high a length anyways; 100 will usually be amply enough to ring out all the possibilities out of a simulation, and on shorter time frames, 30 can be enough. While making it unduly small will prevent simulations of expressing the market’s potential, the less you use, the faster the indicator will run. The default is 40.
Unrealized P&L base at End of Trade (EOT) : When a simulation ends and the trade is still open, we calculate unrealized P&L from an exit order executed from either the last in-trade stop on the previous bar, or the close of the last bar. You can readily see the impact of this selection on the chart, with the P&L cloud. The default is on the close.
Display : The check box besides the title does nothing.
Show target : Shows a green line displaying the trade’s target expressed as a multiple of X, i.e. the amplitude of the entry stop. I call this value “X” and use it as a unit to express profit and loss on a trade (some call it “R”). The line is highlighted for trades where the close reached the target during the trade, whether the trade ended in profit or loss. This is also where you specify the multiple of X you wish to use in calculating targets. The multiple is used even if targets are not displayed.
Show P&L Cloud : The cloud allows traders to see right away the profitable areas of the chart. The only line printed with the cloud is the “end of trade line” (EOT). The EOT line is the only way one can see the level where a trade ended on the chart (in the Data Window you can see it as the “Exit Fill” value). The EOT level for the trade determines if the trade ended in a profit or a loss. Its value represents one of the following:
- fill from order executed at close of bar where stop is breached during trade (which produces “Realized P/L”),
- simulation of a fill pseudo-fill at the user-defined EOT level (last close or stop level) if the trade runs its course through MaxL bars without getting stopped (producing Unrealized P/L).
The EOT line and the cloud fill print in green when the trade’s outcome is profitable and in red when it is not. If the trade was closed after breaching the stop, the line appears brighter.
Show Opportunity&Risk Cloud : Displays the maximum opportunity/risk that was present during the trade, i.e. the maximum and minimum prices reached.
Background Color Scheme : Allows you to choose between 3 different color schemes for the background gradients, to accommodate different types of chart background/candles. Select “None” if you don’t want a background.
Background source : Determines what value will be used to generate the different intensities of the gradient. You can choose trade length (brighter is shorter), Trade P&L (brighter is higher) or the number of times the target was reached during simulation (brighter is higher). The default is Trade Length.
Entry strat : The check box besides the title does nothing. The default strat is All bars, meaning a trade will be simulated from all bars not excluded by the filters where a MaxL bars future exists. For fun, I’ve included a pseudo-random entry strat (an indirect way of changing the seed is to vary the starting date of the simulation).
Show Filter State : Displays areas where the combination of filters you have selected are allowing entries. Filtering occurs as per your selection(s), whether the state is displayed or not. The effect of multiple selections is additive. The filters are:
1. Bar direction: Longs will only be entered if close>open and vice versa.
2. Rising Volume: Applies to both long and shorts.
3. Rising/falling MA of the length you choose over the number of bars you choose.
4. Custom indicator: You can feed your own filtering signal through this from another indicator. It must produce a signal of 1 to allow long entries and 0 to allow shorts.
Show Entry Stops :
1. Multiple of user-defined length ATR.
2. Fixed percentage.
3. Fixed value.
All entry stops are calculated using the entry fill price as a reference. The fill price is calculated from the current bar’s open, to which slippage is added if configured. This simulates the case where the strategy issued the entry signal on the previous bar for it to be executed at the next bar’s open.
The entry stop remains active until the in-trade stop becomes the more aggressive of the two stops. From then on, the entry stop will be ignored, unless a bar close breaches the in-trade stop, in which case the stop will be reset with a new entry stop and the process repeats.
Show In-trade stops : Displays in bright red the selected in-trade stop (be sure to read the note in this section about them).
1. ATR multiple: added/subtracted from the average of the two previous bars minimum/maximum of open/close.
2. A trailing stop with a deviation expressed as a multiple of entry stop (X).
3. A fixed percentage trailing stop.
Trailing stops deviations are measured from the highest/lowest high/low reached during the trade.
Note: There is a twist with the in-trade stops. It’s that for any given bar, its in-trade stop can hold multiple values, as each successive pass of the advancing simulation loops goes over it from a different entry points. What is printed is the stop from the loop that ended on that bar, which may have nothing to do with other instances of the trade’s in-trade stop for the same bar when visited from other starting points in previous simulations. There is just no practical way to print all stop values that were used for any given bar. While the printed entry stops are the actual ones used on each bar, the in-trade stops shown are merely the last instance used among many.
Include Slippage : if checked, slippage will be added/subtracted from order price to yield the fill price. Slippage is in percentage. If you choose to include slippage in the simulations, remember to adjust it by considering the liquidity of the markets and the time frame you’ll be analyzing.
Include Fees : if checked, fees will be subtracted/added to both realized an unrealized trade profits/losses. Fees are in percentage. The default fees work well for crypto markets but will need adjusting for others—especially in Forex. Remember to modify them accordingly as they can have a major impact on results. Both fees and slippage are included to remind us of their importance, even if the global numbers produced by the indicator are not representative of a real trading scenario composed of sequential trades.
Date Range filtering : the usual. Just note that the checkbox has to be selected for date filtering to activate.
DATA WINDOW
Most of the information produced by this indicator is made available in the Data Window, which you bring up by using the icon below the Watchlist and Alerts buttons at the right of the TV UI. Here’s what’s there.
Some of the information presented in the Data Window is standard trade data; other values are not so standard; e. g. the notions of managed opportunity and risk and Target:Stop Travel ratio. The interplay between all the values provided by Great Expectations is inherently complex, even for a static set of entry/filter/exit strats. During the constant updating which the habitual process of progressive refinement in building strategies that is the lot of strategy modelers entails, another level of complexity is no doubt added to the analysis of this indicator’s values. While I don’t want to sound like Wolfram presenting A New Kind of Science , I do believe that if you are a serious strategy modeler and spend the time required to get used to using all the information this indicator makes available, you may find it useful.
Trade Information
Entry Order : This is the open of the bar where simulation starts. We suppose that an entry signal was generated at the previous bar.
Entry Fill (including slip.) : The actual entry price, including slippage. This is the base price from which other values will be calculated.
Exit Order : When a stop is breached, an exit order is executed from the close of the bar that breached the stop. While there is no “In-trade stop” value included in the Data Window (other than the End of trade Stop previously discussed), this “Exit Order” value is how we can know the level where the trade was stopped during the simulation. The “Trade Length” value will then show the bar where the stop was breached.
Exit Fill (including slip.) : When the exit order is simulated, slippage is added to the order level to create the fill.
Chart: Target : This is the target calculated at the beginning of the simulation. This value also appear on the chart in teal. It is controlled by the multiple of X defined under the “Show Target” checkbox in the Inputs.
Chart: Entry Stop : This value also appears on the chart (the red dots under points where a trade was simulated). Its value is controlled by the Entry Strat chosen in the Inputs.
X (% Fill, including Fees) and X (currency) : This is the stop’s amplitude (Entry Fill – Entry Stop) + Fees. It represents the risk incurred upon entry and will be used to express P&L. We will show R expressed in both a percentage of the Entry Fill level (this value), and currency (the next value). This value represents the risk in the risk:reward ratio and is considered to be a unit of 1 so that RR can be expressed as a single value (i.e. “2” actually meaning “1:2”).
Trade Length : If trade was stopped, it’s the number of bars elapsed until then. The trade is then considered “Closed”. If the trade ends without being stopped (there is no profit-taking strat implemented, so the stop is the only exit strat), then the trade is “Open”, the length is MaxL and it will show in orange. Otherwise the value will print in green/red to reflect if the trade is winning/losing.
P&L (X) : The P&L of the trade, expressed as a multiple of X, which takes into account fees paid at entry and exit. Given our default target setting at 2 units of “X”, a trade that closes at its target will have produced a P&L of +2.0, i.e. twice the value of X (not counting fees paid at exit ). A trade that gets stopped late 50% further that the entry stop’s level will produce a P&L of -1.5X.
P&L (currency, including Fees) : same value as above, but expressed in currency.
Target first reached at bar : If price closed above the target during the trade (even if it occurs after the trade was stopped), this will show when. This value will be used in calculating our TST ratio.
Times Stop/Target reached in sim. : Includes all occurrences during the complete simulation loop.
Opportunity (X) : The highest/lowest price reached during a simulation, i.e. the maximum opportunity encountered, whether the trade was previously stopped or not, expressed as a multiple of X.
Risk (X) : The lowest/highest price reached during a simulation, i.e. the maximum risk encountered, whether the trade was previously stopped or not, expressed as a multiple of X.
Risk:Opportunity : The greater this ratio, the greater Opportunity is, compared to Risk.
Managed Opportunity (%) : The portion of Opportunity that was captured by the highest/low stop position, even if it occurred after a previous stop closed the trade.
Managed Risk (%) : The portion of risk that was protected by the lowest/highest stop position, even if it occurred after a previous stop closed the trade. When this value is greater than 100%, it means the trade’s stop is protecting more than the maximum risk, which is frequent. You will, however, never see close to those values for the Managed Opportunity value, since the stop would have to be higher than the Maximum opportunity. It is much easier to alleviate the risk than it is to lock in profits.
Managed Risk:Opportunity : The ratio of the two preceding values.
Managed Opp. vs. Risk : The Managed Opportunity minus the Managed Risk. When it is negative, which is most often is, it means your strat is protecting a greater portion of the risk than it captures opportunity.
Global Numbers
Win Rate(%) : Percentage of winning trades over all entries. Open trades are considered winning if their last stop/close (as per user selection) locks in profits.
Avg X%, Avg X (currency) : Averages of previously described values:.
Avg Profitability/Trade (APPT) : This measures expectation using: Average Profitability Per Trade = (Probability of Win × Average Win) − (Probability of Loss × Average Loss) . It quantifies the average expectation/trade, which RR alone can’t do, as the probabilities of each outcome (win/lose) must also be used to calculate expectancy. The APPT combine the RR with the win rate to yield the true expectancy of a strategy. In my usual way of expressing risk with X, APPT is the equivalent of the average P&L per trade expressed in X. An APPT of -1.5 means that we lose on average 1.5X/trade.
Equity (X), Equity (currency) : The cumulative result of all trade outcomes, expressed as a multiple of X. Multiplied by the Average X in currency, this yields the Equity in currency.
Risk:Opportunity, Managed Risk:Opportunity, Managed Opp. vs. Risk : The global values of the ones previously described.
Avg Trade Length (TL) : One of the most important values derived by going through all the simulations. Again, it is composed of either the length of stopped trades, or MaxL when the trade isn’t stopped (open). This value can help systems modelers shape the characteristics of the components they use to build their strategies.
Avg Closed Win TL and Avg Closed Lose TL : The average lengths of winning/losing trades that were stopped.
Target reached? Avg bars to Stop and Target reached? Avg bars to Target : For the trades where the target was reached at some point in the simulation, the number of bars to the first point where the stop was breached and where the target was reached, respectively. These two values are used to calculate the next value.
TST (Target:Stop Travel Ratio) : This tracks the ratio between the two preceding values (Bars to first stop/Bars to first target), but only for trades where the target was reached somewhere in the loop. A ratio of 2 means targets are reached twice as fast as stops.
The next values of this section are counts or percentages and are self-explanatory.
Chart Plots
Contains chart plots of values already describes.
NOTES
Optimization/Overfitting: There is a fine line between optimizing and overfitting. Tools like this indicator can lead unsuspecting modelers down a path of overfitting that often turns strategies into over-specialized beasts that do not perform elegantly when confronted to the real-world. Proven testing strategies like walk forward analysis will go a long way in helping modelers alleviate this risk.
Input tuning: Because the results generated by the indicator will vary with the parameters used in the active entry, filtering and exit strats, it’s important to realize that although it may be fun at first, just slapping the default settings on a chart and time frame will not yield optimal nor reliable results. While using ATR as often as possible (as I do in this indicator) is a good way to make strat parametrization adaptable, it is not a foolproof solution.
There is no data for the last MaxL bars of the chart, since not enough trade future has elapsed to run a simulation from MaxL bars back.
Modifying the code: I have tried to structure the code modularly, even if that entails a larger code base, so that you can adapt it to your needs. I’ve included a few token components in each of the placeholders designed for entry strategies, filters, entry stops and in-trade stops. This will hopefully make it easier to add your own. In the same spirit, I have also commented liberally.
You will find in the code many instances of standard trade management tasks that can be lifted to code TV strategies where, as I do in mine, you manage everything yourself and don’t rely on built-in Pine strategy functions to act on your trades.
Enjoy!
THANKS
To @scarf who showed me how plotchar() could be used to plot values without ruining scale.
To @glaz for the suggestion to include a Chandelier stop strat; I will.
To @simpelyfe for the idea of using an indicator input for the filters (if some day TV lets us use more than one, it will be useful in other modules of the indicator).
To @RicardoSantos for the random generator used in the random entry strat.
To all scripters publishing open source on TradingView; their code is the best way to learn.
To my trading buddies Irving and Bruno; who showed me way back how pro traders get it done.
Hellenic EMA Matrix - Α Ω PremiumHellenic EMA Matrix - Alpha Omega Premium
Complete User Guide
Table of Contents
Introduction
Indicator Philosophy
Mathematical Constants
EMA Types
Settings
Trading Signals
Visualization
Usage Strategies
FAQ
Introduction
Hellenic EMA Matrix is a premium indicator based on mathematical constants of nature: Phi (Phi - Golden Ratio), Pi (Pi), e (Euler's number). The indicator uses these universal constants to create dynamic EMAs that adapt to the natural rhythms of the market.
Key Features:
6 EMA types based on mathematical constants
Premium visualization with Neon Glow and Gradient Clouds
Automatic Fast/Mid/Slow EMA sorting
STRONG signals for powerful trends
Pulsing Ribbon Bar for instant trend assessment
Works on all timeframes (M1 - MN)
Indicator Philosophy
Why Mathematical Constants?
Traditional EMAs use arbitrary periods (9, 21, 50, 200). Hellenic Matrix goes further, using universal mathematical constants found in nature:
Phi (1.618) - Golden Ratio: galaxy spirals, seashells, human body proportions
Pi (3.14159) - Pi: circles, waves, cycles
e (2.71828) - Natural logarithm base: exponential growth, radioactive decay
Markets are also a natural system composed of millions of participants. Using mathematical constants allows tuning into the natural rhythms of market cycles.
Mathematical Constants
Phi (Phi) - Golden Ratio
Phi = 1.618033988749895
Properties:
Phi² = Phi + 1 = 2.618
Phi³ = 4.236
Phi⁴ = 6.854
Application: Ideal for trending movements and Fibonacci corrections
Pi (Pi) - Pi Number
Pi = 3.141592653589793
Properties:
2Pi = 6.283 (full circle)
3Pi = 9.425
4Pi = 12.566
Application: Excellent for cyclical markets and wave structures
e (Euler) - Euler's Number
e = 2.718281828459045
Properties:
e² = 7.389
e³ = 20.085
e⁴ = 54.598
Application: Suitable for exponential movements and volatile markets
EMA Types
1. Phi (Phi) - Golden Ratio EMA
Description: EMA based on the golden ratio
Period Formula:
Period = Phi^n × Base Multiplier
Parameters:
Phi Power Level (1-8): Power of Phi
Phi¹ = 1.618 → ~16 period (with Base=10)
Phi² = 2.618 → ~26 period
Phi³ = 4.236 → ~42 period (recommended)
Phi⁴ = 6.854 → ~69 period
Recommendations:
Phi² or Phi³ for day trading
Phi⁴ or Phi⁵ for swing trading
Works excellently as Fast EMA
2. Pi (Pi) - Circular EMA
Description: EMA based on Pi for cyclical movements
Period Formula:
Period = Pi × Multiple × Base Multiplier
Parameters:
Pi Multiple (1-10): Pi multiplier
1Pi = 3.14 → ~31 period (with Base=10)
2Pi = 6.28 → ~63 period (recommended)
3Pi = 9.42 → ~94 period
Recommendations:
2Pi ideal as Mid or Slow EMA
Excellently identifies cycles and waves
Use on volatile markets (crypto, forex)
3. e (Euler) - Natural EMA
Description: EMA based on natural logarithm
Period Formula:
Period = e^n × Base Multiplier
Parameters:
e Power Level (1-6): Power of e
e¹ = 2.718 → ~27 period (with Base=10)
e² = 7.389 → ~74 period (recommended)
e³ = 20.085 → ~201 period
Recommendations:
e² works excellently as Slow EMA
Ideal for stocks and indices
Filters noise well on lower timeframes
4. Delta (Delta) - Adaptive EMA
Description: Adaptive EMA that changes period based on volatility
Period Formula:
Period = Base Period × (1 + (Volatility - 1) × Factor)
Parameters:
Delta Base Period (5-200): Base period (default 20)
Delta Volatility Sensitivity (0.5-5.0): Volatility sensitivity (default 2.0)
How it works:
During low volatility → period decreases → EMA reacts faster
During high volatility → period increases → EMA smooths noise
Recommendations:
Works excellently on news and sharp movements
Use as Fast EMA for quick adaptation
Sensitivity 2.0-3.0 for crypto, 1.0-2.0 for stocks
5. Sigma (Sigma) - Composite EMA
Description: Composite EMA combining multiple active EMAs
Composition Methods:
Weighted Average (default):
Sigma = (Phi + Pi + e + Delta) / 4
Simple average of all active EMAs
Geometric Mean:
Sigma = fourth_root(Phi × Pi × e × Delta)
Geometric mean (more conservative)
Harmonic Mean:
Sigma = 4 / (1/Phi + 1/Pi + 1/e + 1/Delta)
Harmonic mean (more weight to smaller values)
Recommendations:
Enable for additional confirmation
Use as Mid EMA
Weighted Average - most universal method
6. Lambda (Lambda) - Wave EMA
Description: Wave EMA with sinusoidal period modulation
Period Formula:
Period = Base Period × (1 + Amplitude × sin(2Pi × bar / Frequency))
Parameters:
Lambda Base Period (10-200): Base period
Lambda Wave Amplitude (0.1-2.0): Wave amplitude
Lambda Wave Frequency (10-200): Wave frequency in bars
How it works:
Period pulsates sinusoidally
Creates wave effect following market cycles
Recommendations:
Experimental EMA for advanced users
Works well on cyclical markets
Frequency = 50 for day trading, 100+ for swing
Settings
Matrix Core Settings
Base Multiplier (1-100)
Multiplies all EMA periods
Base = 1: Very fast EMAs (Phi³ = 4, 2Pi = 6, e² = 7)
Base = 10: Standard (Phi³ = 42, 2Pi = 63, e² = 74)
Base = 20: Slow EMAs (Phi³ = 85, 2Pi = 126, e² = 148)
Recommendations by timeframe:
M1-M5: Base = 5-10
M15-H1: Base = 10-15 (recommended)
H4-D1: Base = 15-25
W1-MN: Base = 25-50
Matrix Source
Data source selection for EMA calculation:
close - closing price (standard)
open - opening price
high - high
low - low
hl2 - (high + low) / 2
hlc3 - (high + low + close) / 3
ohlc4 - (open + high + low + close) / 4
When to change:
hlc3 or ohlc4 for smoother signals
high for aggressive longs
low for aggressive shorts
Manual EMA Selection
Critically important setting! Determines which EMAs are used for signal generation.
Use Manual Fast/Slow/Mid Selection
Enabled (default): You select EMAs manually
Disabled: Automatic selection by periods
Fast EMA
Fast EMA - reacts first to price changes
Recommendations:
Phi Golden (recommended) - universal choice
Delta Adaptive - for volatile markets
Must be fastest (smallest period)
Slow EMA
Slow EMA - determines main trend
Recommendations:
Pi Circular (recommended) - excellent trend filter
e Natural - for smoother trend
Must be slowest (largest period)
Mid EMA
Mid EMA - additional signal filter
Recommendations:
e Natural (recommended) - excellent middle level
Pi Circular - alternative
None - for more frequent signals (only 2 EMAs)
IMPORTANT: The indicator automatically sorts selected EMAs by their actual periods:
Fast = EMA with smallest period
Mid = EMA with middle period
Slow = EMA with largest period
Therefore, you can select any combination - the indicator will arrange them correctly!
Premium Visualization
Neon Glow
Enable Neon Glow for EMAs - adds glowing effect around EMA lines
Glow Strength:
Light - subtle glow
Medium (recommended) - optimal balance
Strong - bright glow (may be too bright)
Effect: 2 glow layers around each EMA for 3D effect
Gradient Clouds
Enable Gradient Clouds - fills space between EMAs with gradient
Parameters:
Cloud Transparency (85-98): Cloud transparency
95-97 (recommended)
Higher = more transparent
Dynamic Cloud Intensity - automatically changes transparency based on EMA distance
Cloud Colors:
Phi-Pi Cloud:
Blue - when Pi above Phi (bullish)
Gold - when Phi above Pi (bearish)
Pi-e Cloud:
Green - when e above Pi (bullish)
Blue - when Pi above e (bearish)
2 layers for volumetric effect
Pulsing Ribbon Bar
Enable Pulsing Indicator Bar - pulsing strip at bottom/top of chart
Parameters:
Ribbon Position: Top / Bottom (recommended)
Pulse Speed: Slow / Medium (recommended) / Fast
Symbols and colors:
Green filled square - STRONG BULLISH
Pink filled square - STRONG BEARISH
Blue hollow square - Bullish (regular)
Red hollow square - Bearish (regular)
Purple rectangle - Neutral
Effect: Pulsation with sinusoid for living market feel
Signal Bar Highlights
Enable Signal Bar Highlights - highlights bars with signals
Parameters:
Highlight Transparency (88-96): Highlight transparency
Highlight Style:
Light Fill (recommended) - bar background fill
Thin Line - bar outline only
Highlights:
Golden Cross - green
Death Cross - pink
STRONG BUY - green
STRONG SELL - pink
Show Greek Labels
Shows Greek alphabet letters on last bar:
Phi - Phi EMA (gold)
Pi - Pi EMA (blue)
e - Euler EMA (green)
Delta - Delta EMA (purple)
Sigma - Sigma EMA (pink)
When to use: For education or presentations
Show Old Background
Old background style (not recommended):
Green background - STRONG BULLISH
Pink background - STRONG BEARISH
Blue background - Bullish
Red background - Bearish
Not recommended - use new Gradient Clouds and Pulsing Bar
Info Table
Show Info Table - table with indicator information
Parameters:
Position: Top Left / Top Right (recommended) / Bottom Left / Bottom Right
Size: Tiny / Small (recommended) / Normal / Large
Table contents:
EMA list - periods and current values of all active EMAs
Effects - active visual effects
TREND - current trend state:
STRONG UP - strong bullish
STRONG DOWN - strong bearish
Bullish - regular bullish
Bearish - regular bearish
Neutral - neutral
Momentum % - percentage deviation of price from Fast EMA
Setup - current Fast/Slow/Mid configuration
Trading Signals
Show Golden/Death Cross
Golden Cross - Fast EMA crosses Slow EMA from below (bullish signal) Death Cross - Fast EMA crosses Slow EMA from above (bearish signal)
Symbols:
Yellow dot "GC" below - Golden Cross
Dark red dot "DC" above - Death Cross
Show STRONG Signals
STRONG BUY and STRONG SELL - the most powerful indicator signals
Conditions for STRONG BULLISH:
EMA Alignment: Fast > Mid > Slow (all EMAs aligned)
Trend: Fast > Slow (clear uptrend)
Distance: EMAs separated by minimum 0.15%
Price Position: Price above Fast EMA
Fast Slope: Fast EMA rising
Slow Slope: Slow EMA rising
Mid Trending: Mid EMA also rising (if enabled)
Conditions for STRONG BEARISH:
Same but in reverse
Visual display:
Green label "STRONG BUY" below bar
Pink label "STRONG SELL" above bar
Difference from Golden/Death Cross:
Golden/Death Cross = crossing moment (1 bar)
STRONG signal = sustained trend (lasts several bars)
IMPORTANT: After fixes, STRONG signals now:
Work on all timeframes (M1 to MN)
Don't break on small retracements
Work with any Fast/Mid/Slow combination
Automatically adapt thanks to EMA sorting
Show Stop Loss/Take Profit
Automatic SL/TP level calculation on STRONG signal
Parameters:
Stop Loss (ATR) (0.5-5.0): ATR multiplier for stop loss
1.5 (recommended) - standard
1.0 - tight stop
2.0-3.0 - wide stop
Take Profit R:R (1.0-5.0): Risk/reward ratio
2.0 (recommended) - standard (risk 1.5 ATR, profit 3.0 ATR)
1.5 - conservative
3.0-5.0 - aggressive
Formulas:
LONG:
Stop Loss = Entry - (ATR × Stop Loss ATR)
Take Profit = Entry + (ATR × Stop Loss ATR × Take Profit R:R)
SHORT:
Stop Loss = Entry + (ATR × Stop Loss ATR)
Take Profit = Entry - (ATR × Stop Loss ATR × Take Profit R:R)
Visualization:
Red X - Stop Loss
Green X - Take Profit
Levels remain active while STRONG signal persists
Trading Signals
Signal Types
1. Golden Cross
Description: Fast EMA crosses Slow EMA from below
Signal: Beginning of bullish trend
How to trade:
ENTRY: On bar close with Golden Cross
STOP: Below local low or below Slow EMA
TARGET: Next resistance level or 2:1 R:R
Strengths:
Simple and clear
Works well on trending markets
Clear entry point
Weaknesses:
Lags (signal after movement starts)
Many false signals in ranging markets
May be late on fast moves
Optimal timeframes: H1, H4, D1
2. Death Cross
Description: Fast EMA crosses Slow EMA from above
Signal: Beginning of bearish trend
How to trade:
ENTRY: On bar close with Death Cross
STOP: Above local high or above Slow EMA
TARGET: Next support level or 2:1 R:R
Application: Mirror of Golden Cross
3. STRONG BUY
Description: All EMAs aligned + trend + all EMAs rising
Signal: Powerful bullish trend
How to trade:
ENTRY: On bar close with STRONG BUY or on pullback to Fast EMA
STOP: Below Fast EMA or automatic SL (if enabled)
TARGET: Automatic TP (if enabled) or by levels
TRAILING: Follow Fast EMA
Entry strategies:
Aggressive: Enter immediately on signal
Conservative: Wait for pullback to Fast EMA, then enter on bounce
Pyramiding: Add positions on pullbacks to Mid EMA
Position management:
Hold while STRONG signal active
Exit on STRONG SELL or Death Cross appearance
Move stop behind Fast EMA
Strengths:
Most reliable indicator signal
Doesn't break on pullbacks
Catches large moves
Works on all timeframes
Weaknesses:
Appears less frequently than other signals
Requires confirmation (multiple conditions)
Optimal timeframes: All (M5 - D1)
4. STRONG SELL
Description: All EMAs aligned down + downtrend + all EMAs falling
Signal: Powerful bearish trend
How to trade: Mirror of STRONG BUY
Visual Signals
Pulsing Ribbon Bar
Quick market assessment at a glance:
Symbol Color State
Filled square Green STRONG BULLISH
Filled square Pink STRONG BEARISH
Hollow square Blue Bullish
Hollow square Red Bearish
Rectangle Purple Neutral
Pulsation: Sinusoidal, creates living effect
Signal Bar Highlights
Bars with signals are highlighted:
Green highlight: STRONG BUY or Golden Cross
Pink highlight: STRONG SELL or Death Cross
Gradient Clouds
Colored space between EMAs shows trend strength:
Wide clouds - strong trend
Narrow clouds - weak trend or consolidation
Color change - trend change
Info Table
Quick reference in corner:
TREND: Current state (STRONG UP, Bullish, Neutral, Bearish, STRONG DOWN)
Momentum %: Movement strength
Effects: Active visual effects
Setup: Fast/Slow/Mid configuration
Usage Strategies
Strategy 1: "Golden Trailing"
Idea: Follow STRONG signals using Fast EMA as trailing stop
Settings:
Fast: Phi Golden (Phi³)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base Multiplier: 10
Timeframe: H1, H4
Entry rules:
Wait for STRONG BUY
Enter on bar close or on pullback to Fast EMA
Stop below Fast EMA
Management:
Hold position while STRONG signal active
Move stop behind Fast EMA daily
Exit on STRONG SELL or Death Cross
Take Profit:
Partially close at +2R
Trail remainder until exit signal
For whom: Swing traders, trend followers
Pros:
Catches large moves
Simple rules
Emotionally comfortable
Cons:
Requires patience
Possible extended drawdowns on pullbacks
Strategy 2: "Scalping Bounces"
Idea: Scalp bounces from Fast EMA during STRONG trend
Settings:
Fast: Delta Adaptive (Base 15, Sensitivity 2.0)
Mid: Phi Golden (Phi²)
Slow: Pi Circular (2Pi)
Base Multiplier: 5
Timeframe: M5, M15
Entry rules:
STRONG signal must be active
Wait for price pullback to Fast EMA
Enter on bounce (candle closes above/below Fast EMA)
Stop behind local extreme (15-20 pips)
Take Profit:
+1.5R or to Mid EMA
Or to next level
For whom: Active day traders
Pros:
Many signals
Clear entry point
Quick profits
Cons:
Requires constant monitoring
Not all bounces work
Requires discipline for frequent trading
Strategy 3: "Triple Filter"
Idea: Enter only when all 3 EMAs and price perfectly aligned
Settings:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (3Pi)
Base Multiplier: 15
Timeframe: H4, D1
Entry rules (LONG):
STRONG BUY active
Price above all three EMAs
Fast > Mid > Slow (all aligned)
All EMAs rising (slope up)
Gradient Clouds wide and bright
Entry:
On bar close meeting all conditions
Or on next pullback to Fast EMA
Stop:
Below Mid EMA or -1.5 ATR
Take Profit:
First target: +3R
Second target: next major level
Trailing: Mid EMA
For whom: Conservative swing traders, investors
Pros:
Very reliable signals
Minimum false entries
Large profit potential
Cons:
Rare signals (2-5 per month)
Requires patience
Strategy 4: "Adaptive Scalper"
Idea: Use only Delta Adaptive EMA for quick volatility reaction
Settings:
Fast: Delta Adaptive (Base 10, Sensitivity 3.0)
Mid: None
Slow: Delta Adaptive (Base 30, Sensitivity 2.0)
Base Multiplier: 3
Timeframe: M1, M5
Feature: Two different Delta EMAs with different settings
Entry rules:
Golden Cross between two Delta EMAs
Both Delta EMAs must be rising/falling
Enter on next bar
Stop:
10-15 pips or below Slow Delta EMA
Take Profit:
+1R to +2R
Or Death Cross
For whom: Scalpers on cryptocurrencies and forex
Pros:
Instant volatility adaptation
Many signals on volatile markets
Quick results
Cons:
Much noise on calm markets
Requires fast execution
High commissions may eat profits
Strategy 5: "Cyclical Trader"
Idea: Use Pi and Lambda for trading cyclical markets
Settings:
Fast: Pi Circular (1Pi)
Mid: Lambda Wave (Base 30, Amplitude 0.5, Frequency 50)
Slow: Pi Circular (3Pi)
Base Multiplier: 10
Timeframe: H1, H4
Entry rules:
STRONG signal active
Lambda Wave EMA synchronized with trend
Enter on bounce from Lambda Wave
For whom: Traders of cyclical assets (some altcoins, commodities)
Pros:
Catches cyclical movements
Lambda Wave provides additional entry points
Cons:
More complex to configure
Not for all markets
Lambda Wave may give false signals
Strategy 6: "Multi-Timeframe Confirmation"
Idea: Use multiple timeframes for confirmation
Scheme:
Higher TF (D1): Determine trend direction (STRONG signal)
Middle TF (H4): Wait for STRONG signal in same direction
Lower TF (M15): Look for entry point (Golden Cross or bounce from Fast EMA)
Settings for all TFs:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base Multiplier: 10
Rules:
All 3 TFs must show one trend
Entry on lower TF
Stop by lower TF
Target by higher TF
For whom: Serious traders and investors
Pros:
Maximum reliability
Large profit targets
Minimum false signals
Cons:
Rare setups
Requires analysis of multiple charts
Experience needed
Practical Tips
DOs
Use STRONG signals as primary - they're most reliable
Let signals develop - don't exit on first pullback
Use trailing stop - follow Fast EMA
Combine with levels - S/R, Fibonacci, volumes
Test on demo before real
Adjust Base Multiplier for your timeframe
Enable visual effects - they help see the picture
Use Info Table - quick situation assessment
Watch Pulsing Bar - instant state indicator
Trust auto-sorting of Fast/Mid/Slow
DON'Ts
Don't trade against STRONG signal - trend is your friend
Don't ignore Mid EMA - it adds reliability
Don't use too small Base Multiplier on higher TFs
Don't enter on Golden Cross in range - check for trend
Don't change settings during open position
Don't forget risk management - 1-2% per trade
Don't trade all signals in row - choose best ones
Don't use indicator in isolation - combine with Price Action
Don't set too tight stops - let trade breathe
Don't over-optimize - simplicity = reliability
Optimal Settings by Asset
US Stocks (SPY, AAPL, TSLA)
Recommendation:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base: 10-15
Timeframe: H4, D1
Features:
Use on daily for swing
STRONG signals very reliable
Works well on trending stocks
Forex (EUR/USD, GBP/USD)
Recommendation:
Fast: Delta Adaptive (Base 15, Sens 2.0)
Mid: Phi Golden (Phi²)
Slow: Pi Circular (2Pi)
Base: 8-12
Timeframe: M15, H1, H4
Features:
Delta Adaptive works excellently on news
Many signals on M15-H1
Consider spreads
Cryptocurrencies (BTC, ETH, altcoins)
Recommendation:
Fast: Delta Adaptive (Base 10, Sens 3.0)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base: 5-10
Timeframe: M5, M15, H1
Features:
High volatility - adaptation needed
STRONG signals can last days
Be careful with scalping on M1-M5
Commodities (Gold, Oil)
Recommendation:
Fast: Pi Circular (1Pi)
Mid: Phi Golden (Phi³)
Slow: Pi Circular (3Pi)
Base: 12-18
Timeframe: H4, D1
Features:
Pi works excellently on cyclical commodities
Gold responds especially well to Phi
Oil volatile - use wide stops
Indices (S&P500, Nasdaq, DAX)
Recommendation:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base: 15-20
Timeframe: H4, D1, W1
Features:
Very trending instruments
STRONG signals last weeks
Good for position trading
Alerts
The indicator supports 6 alert types:
1. Golden Cross
Message: "Hellenic Matrix: GOLDEN CROSS - Fast EMA crossed above Slow EMA - Bullish trend starting!"
When: Fast EMA crosses Slow EMA from below
2. Death Cross
Message: "Hellenic Matrix: DEATH CROSS - Fast EMA crossed below Slow EMA - Bearish trend starting!"
When: Fast EMA crosses Slow EMA from above
3. STRONG BULLISH
Message: "Hellenic Matrix: STRONG BULLISH SIGNAL - All EMAs aligned for powerful uptrend!"
When: All conditions for STRONG BUY met (first bar)
4. STRONG BEARISH
Message: "Hellenic Matrix: STRONG BEARISH SIGNAL - All EMAs aligned for powerful downtrend!"
When: All conditions for STRONG SELL met (first bar)
5. Bullish Ribbon
Message: "Hellenic Matrix: BULLISH RIBBON - EMAs aligned for uptrend"
When: EMAs aligned bullish + price above Fast EMA (less strict condition)
6. Bearish Ribbon
Message: "Hellenic Matrix: BEARISH RIBBON - EMAs aligned for downtrend"
When: EMAs aligned bearish + price below Fast EMA (less strict condition)
How to Set Up Alerts:
Open indicator on chart
Click on three dots next to indicator name
Select "Create Alert"
In "Condition" field select needed alert:
Golden Cross
Death Cross
STRONG BULLISH
STRONG BEARISH
Bullish Ribbon
Bearish Ribbon
Configure notification method:
Pop-up in browser
Email
SMS (in Premium accounts)
Push notifications in mobile app
Webhook (for automation)
Select frequency:
Once Per Bar Close (recommended) - once on bar close
Once Per Bar - during bar formation
Only Once - only first time
Click "Create"
Tip: Create separate alerts for different timeframes and instruments
FAQ
1. Why don't STRONG signals appear?
Possible reasons:
Incorrect Fast/Mid/Slow order
Solution: Indicator automatically sorts EMAs by periods, but ensure selected EMAs have different periods
Base Multiplier too large
Solution: Reduce Base to 5-10 on lower timeframes
Market in range
Solution: STRONG signals appear only in trends - this is normal
Too strict EMA settings
Solution: Try classic combination: Phi³ / Pi×2 / e² with Base=10
Mid EMA too close to Fast or Slow
Solution: Select Mid EMA with period between Fast and Slow
2. How often should STRONG signals appear?
Normal frequency:
M1-M5: 5-15 signals per day (very active markets)
M15-H1: 2-8 signals per day
H4: 3-10 signals per week
D1: 2-5 signals per month
W1: 2-6 signals per year
If too many signals - market very volatile or Base too small
If too few signals - market in range or Base too large
4. What are the best settings for beginners?
Universal "out of the box" settings:
Matrix Core:
Base Multiplier: 10
Source: close
Phi Golden: Enabled, Power = 3
Pi Circular: Enabled, Multiple = 2
e Natural: Enabled, Power = 2
Delta Adaptive: Enabled, Base = 20, Sensitivity = 2.0
Manual Selection:
Fast: Phi Golden
Mid: e Natural
Slow: Pi Circular
Visualization:
Gradient Clouds: ON
Neon Glow: ON (Medium)
Pulsing Bar: ON (Medium)
Signal Highlights: ON (Light Fill)
Table: ON (Top Right, Small)
Signals:
Golden/Death Cross: ON
STRONG Signals: ON
Stop Loss: OFF (while learning)
Timeframe for learning: H1 or H4
5. Can I use only one EMA?
No, minimum 2 EMAs (Fast and Slow) for signal generation.
Mid EMA is optional:
With Mid EMA = more reliable but rarer signals
Without Mid EMA = more signals but less strict filtering
Recommendation: Start with 3 EMAs (Fast/Mid/Slow), then experiment
6. Does the indicator work on cryptocurrencies?
Yes, works excellently! Especially good on:
Bitcoin (BTC)
Ethereum (ETH)
Major altcoins (SOL, BNB, XRP)
Recommended settings for crypto:
Fast: Delta Adaptive (Base 10-15, Sensitivity 2.5-3.0)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base: 5-10
Timeframe: M15, H1, H4
Crypto market features:
High volatility → use Delta Adaptive
24/7 trading → set alerts
Sharp movements → wide stops
7. Can I trade only with this indicator?
Technically yes, but NOT recommended.
Best approach - combine with:
Price Action - support/resistance levels, candle patterns
Volume - movement strength confirmation
Fibonacci - retracement and extension levels
RSI/MACD - divergences and overbought/oversold
Fundamental analysis - news, company reports
Hellenic Matrix:
Excellently determines trend and its strength
Provides clear entry/exit points
Doesn't consider fundamentals
Doesn't see major levels
8. Why do Gradient Clouds change color?
Color depends on EMA order:
Phi-Pi Cloud:
Blue - Pi EMA above Phi EMA (bullish alignment)
Gold - Phi EMA above Pi EMA (bearish alignment)
Pi-e Cloud:
Green - e EMA above Pi EMA (bullish alignment)
Blue - Pi EMA above e EMA (bearish alignment)
Color change = EMA order change = possible trend change
9. What is Momentum % in the table?
Momentum % = percentage deviation of price from Fast EMA
Formula:
Momentum = ((Close - Fast EMA) / Fast EMA) × 100
Interpretation:
+0.5% to +2% - normal bullish momentum
+2% to +5% - strong bullish momentum
+5% and above - overheating (correction possible)
-0.5% to -2% - normal bearish momentum
-2% to -5% - strong bearish momentum
-5% and below - oversold (bounce possible)
Usage:
Monitor momentum during STRONG signals
Large momentum = don't enter (wait for pullback)
Small momentum = good entry point
10. How to configure for scalping?
Settings for scalping (M1-M5):
Base Multiplier: 3-5
Source: close or hlc3 (smoother)
Fast: Delta Adaptive (Base 8-12, Sensitivity 3.0)
Mid: None (for more signals)
Slow: Phi Golden (Phi²) or Pi Circular (1Pi)
Visualization:
- Gradient Clouds: ON (helps see strength)
- Neon Glow: OFF (doesn't clutter chart)
- Pulsing Bar: ON (quick assessment)
- Signal Highlights: ON
Signals:
- Golden/Death Cross: ON
- STRONG Signals: ON
- Stop Loss: ON (1.0-1.5 ATR, R:R 1.5-2.0)
Scalping rules:
Trade only STRONG signals
Enter on bounce from Fast EMA
Tight stops (10-20 pips)
Quick take profit (+1R to +2R)
Don't hold through news
11. How to configure for long-term investing?
Settings for investing (D1-W1):
Base Multiplier: 20-30
Source: close
Fast: Phi Golden (Phi³ or Phi⁴)
Mid: e Natural (e²)
Slow: Pi Circular (3Pi or 4Pi)
Visualization:
- Gradient Clouds: ON
- Neon Glow: ON (Medium)
- Everything else - to taste
Signals:
- Golden/Death Cross: ON
- STRONG Signals: ON
- Stop Loss: OFF (use percentage stop)
Investing rules:
Enter only on STRONG signals
Hold while STRONG active (weeks/months)
Stop below Slow EMA or -10%
Take profit: by company targets or +50-100%
Ignore short-term pullbacks
12. What if indicator slows down chart?
Indicator is optimized, but if it slows:
Disable unnecessary visual effects:
Neon Glow: OFF (saves 8 plots)
Gradient Clouds: ON but low quality
Lambda Wave EMA: OFF (if not using)
Reduce number of active EMAs:
Sigma Composite: OFF
Lambda Wave: OFF
Leave only Phi, Pi, e, Delta
Simplify settings:
Pulsing Bar: OFF
Greek Labels: OFF
Info Table: smaller size
13. Can I use on different timeframes simultaneously?
Yes! Multi-timeframe analysis is very powerful:
Classic scheme:
Higher TF (D1, W1) - determine global trend
Wait for STRONG signal
This is our trading direction
Middle TF (H4, H1) - look for confirmation
STRONG signal in same direction
Precise entry zone
Lower TF (M15, M5) - entry point
Golden Cross or bounce from Fast EMA
Precise stop loss
Example:
W1: STRONG BUY active (global uptrend)
H4: STRONG BUY appeared (confirmation)
M15: Wait for Golden Cross or bounce from Fast EMA → ENTRY
Advantages:
Maximum reliability
Clear timeframe hierarchy
Large targets
14. How does indicator work on news?
Delta Adaptive EMA adapts excellently to news:
Before news:
Low volatility → Delta EMA becomes fast → pulls to price
During news:
Sharp volatility spike → Delta EMA slows → filters noise
After news:
Volatility normalizes → Delta EMA returns to normal
Recommendations:
Don't trade at news release moment (spreads widen)
Wait for STRONG signal after news (2-5 bars)
Use Delta Adaptive as Fast EMA for quick reaction
Widen stops by 50-100% during important news
Advanced Techniques
Technique 1: "Divergences with EMA"
Idea: Look for discrepancies between price and Fast EMA
Bullish divergence:
Price makes lower low
Fast EMA makes higher low
= Possible reversal up
Bearish divergence:
Price makes higher high
Fast EMA makes lower high
= Possible reversal down
How to trade:
Find divergence
Wait for STRONG signal in divergence direction
Enter on confirmation
Technique 2: "EMA Tunnel"
Idea: Use space between Fast and Slow EMA as "tunnel"
Rules:
Wide tunnel - strong trend, hold position
Narrow tunnel - weak trend or consolidation, caution
Tunnel narrowing - trend weakening, prepare to exit
Tunnel widening - trend strengthening, can add
Visually: Gradient Clouds show this automatically!
Trading:
Enter on STRONG signal (tunnel starts widening)
Hold while tunnel wide
Exit when tunnel starts narrowing
Technique 3: "Wave Analysis with Lambda"
Idea: Lambda Wave EMA creates sinusoid matching market cycles
Setup:
Lambda Base Period: 30
Lambda Wave Amplitude: 0.5
Lambda Wave Frequency: 50 (adjusted to asset cycle)
How to find correct Frequency:
Look at historical cycles (distance between local highs)
Average distance = your Frequency
Example: if highs every 40-60 bars, set Frequency = 50
Trading:
Enter when Lambda Wave at bottom of sinusoid (growth potential)
Exit when Lambda Wave at top (fall potential)
Combine with STRONG signals
Technique 4: "Cluster Analysis"
Idea: When all EMAs gather in narrow cluster = powerful breakout soon
Cluster signs:
All EMAs (Phi, Pi, e, Delta) within 0.5-1% of each other
Gradient Clouds almost invisible
Price jumping around all EMAs
Trading:
Identify cluster (all EMAs close)
Determine breakout direction (where more volume, higher TFs direction)
Wait for breakout and STRONG signal
Enter on confirmation
Target = cluster size × 3-5
This is very powerful technique for big moves!
Technique 5: "Sigma as Dynamic Level"
Idea: Sigma Composite EMA = average of all EMAs = magnetic level
Usage:
Enable Sigma Composite (Weighted Average)
Sigma works as dynamic support/resistance
Price often returns to Sigma before trend continuation
Trading:
In trend: Enter on bounces from Sigma
In range: Fade moves from Sigma (trade return to Sigma)
On breakout: Sigma becomes support/resistance
Risk Management
Basic Rules
1. Position Size
Conservative: 1% of capital per trade
Moderate: 2% of capital per trade (recommended)
Aggressive: 3-5% (only for experienced)
Calculation formula:
Lot Size = (Capital × Risk%) / (Stop in pips × Pip value)
2. Risk/Reward Ratio
Minimum: 1:1.5
Standard: 1:2 (recommended)
Optimal: 1:3
Aggressive: 1:5+
3. Maximum Drawdown
Daily: -3% to -5%
Weekly: -7% to -10%
Monthly: -15% to -20%
Upon reaching limit → STOP trading until end of period
Position Management Strategies
1. Fixed Stop
Method:
Stop below/above Fast EMA or local extreme
DON'T move stop against position
Can move to breakeven
For whom: Beginners, conservative traders
2. Trailing by Fast EMA
Method:
Each day (or bar) move stop to Fast EMA level
Position closes when price breaks Fast EMA
Advantages:
Stay in trend as long as possible
Automatically exit on reversal
For whom: Trend followers, swing traders
3. Partial Exit
Method:
50% of position close at +2R
50% hold with trailing by Mid EMA or Slow EMA
Advantages:
Lock profit
Leave position for big move
Psychologically comfortable
For whom: Universal method (recommended)
4. Pyramiding
Method:
First entry on STRONG signal (50% of planned position)
Add 25% on pullback to Fast EMA
Add another 25% on pullback to Mid EMA
Overall stop below Slow EMA
Advantages:
Average entry price
Reduce risk
Increase profit in strong trends
Caution:
Works only in trends
In range leads to losses
For whom: Experienced traders
Trading Psychology
Correct Mindset
1. Indicator is a tool, not holy grail
Indicator shows probability, not guarantee
There will be losing trades - this is normal
Important is series statistics, not one trade
2. Trust the system
If STRONG signal appeared - enter
Don't search for "perfect" moment
Follow trading plan
3. Patience
STRONG signals don't appear every day
Better miss signal than enter against trend
Quality over quantity
4. Discipline
Always set stop loss
Don't move stop against position
Don't increase risk after losses
Beginner Mistakes
1. "I know better than indicator"
Indicator says STRONG BUY, but you think "too high, will wait for pullback"
Result: miss profitable move
Solution: Trust signals or don't use indicator
2. "Will reverse now for sure"
Trading against STRONG trend
Result: stops, stops, stops
Solution: Trend is your friend, trade with trend
3. "Will hold a bit more"
Don't exit when STRONG signal disappears
Greed eats profit
Solution: If signal gone - exit!
4. "I'll recover"
After losses double risk
Result: huge losses
Solution: Fixed % risk ALWAYS
5. "I don't like this signal"
Skip signals because of "feeling"
Result: inconsistency, no statistics
Solution: Trade ALL signals or clearly define filters
Trading Journal
What to Record
For each trade:
1. Entry/exit date and time
2. Instrument and timeframe
3. Signal type
Golden Cross
STRONG BUY
STRONG SELL
Death Cross
4. Indicator settings
Fast/Mid/Slow EMA
Base Multiplier
Other parameters
5. Chart screenshot
Entry moment
Exit moment
6. Trade parameters
Position size
Stop loss
Take Profit
R:R
7. Result
Profit/Loss in $
Profit/Loss in %
Profit/Loss in R
8. Notes
What was right
What was wrong
Emotions during trade
Lessons
Journal Analysis
Analyze weekly:
1. Win Rate
Win Rate = (Profitable trades / All trades) × 100%
Good: 50-60%
Excellent: 60-70%
Exceptional: 70%+
2. Average R
Average R = Sum of all R / Number of trades
Good: +0.5R
Excellent: +1.0R
Exceptional: +1.5R+
3. Profit Factor
Profit Factor = Total profit / Total losses
Good: 1.5+
Excellent: 2.0+
Exceptional: 3.0+
4. Maximum Drawdown
Track consecutive losses
If more than 5 in row - stop, check system
5. Best/Worst Trades
What was common in best trades? (do more)
What was common in worst trades? (avoid)
Pre-Trade Checklist
Technical Analysis
STRONG signal active (BUY or SELL)
All EMAs properly aligned (Fast > Mid > Slow or reverse)
Price on correct side of Fast EMA
Gradient Clouds confirm trend
Pulsing Bar shows STRONG state
Momentum % in normal range (not overheated)
No close strong levels against direction
Higher timeframe doesn't contradict
Risk Management
Position size calculated (1-2% risk)
Stop loss set
Take profit calculated (minimum 1:2)
R:R satisfactory
Daily/weekly risk limit not exceeded
No other open correlated positions
Fundamental Analysis
No important news in coming hours
Market session appropriate (liquidity)
No contradicting fundamentals
Understand why asset is moving
Psychology
Calm and thinking clearly
No emotions from previous trades
Ready to accept loss at stop
Following trading plan
Not revenging market for past losses
If at least one point is NO - think twice before entering!
Learning Roadmap
Week 1: Familiarization
Goals:
Install and configure indicator
Study all EMA types
Understand visualization
Tasks:
Add indicator to chart
Test all Fast/Mid/Slow settings
Play with Base Multiplier on different timeframes
Observe Gradient Clouds and Pulsing Bar
Study Info Table
Result: Comfort with indicator interface
Week 2: Signals
Goals:
Learn to recognize all signal types
Understand difference between Golden Cross and STRONG
Tasks:
Find 10 Golden Cross examples in history
Find 10 STRONG BUY examples in history
Compare their results (which worked better)
Set up alerts
Get 5 real alerts
Result: Understanding signals
Week 3: Demo Trading
Goals:
Start trading signals on demo account
Gather statistics
Tasks:
Open demo account
Trade ONLY STRONG signals
Keep journal (minimum 20 trades)
Don't change indicator settings
Strictly follow stop losses
Result: 20+ documented trades
Week 4: Analysis
Goals:
Analyze demo trading results
Optimize approach
Tasks:
Calculate win rate and average R
Find patterns in profitable trades
Find patterns in losing trades
Adjust approach (not indicator!)
Write trading plan
Result: Trading plan on 1 page
Month 2: Improvement
Goals:
Deepen understanding
Add additional techniques
Tasks:
Study multi-timeframe analysis
Test combinations with Price Action
Try advanced techniques (divergences, tunnels)
Continue demo trading (minimum 50 trades)
Achieve stable profitability on demo
Result: Win rate 55%+ and Profit Factor 1.5+
Month 3: Real Trading
Goals:
Transition to real account
Maintain discipline
Tasks:
Open small real account
Trade minimum lots
Strictly follow trading plan
DON'T increase risk
Focus on process, not profit
Result: Psychological comfort on real
Month 4+: Scaling
Goals:
Increase account
Become consistently profitable
Tasks:
With 60%+ win rate can increase risk to 2%
Upon doubling account can add capital
Continue keeping journal
Periodically review and improve strategy
Share experience with community
Result: Stable profitability month after month
Additional Resources
Recommended Reading
Technical Analysis:
"Technical Analysis of Financial Markets" - John Murphy
"Trading in the Zone" - Mark Douglas (psychology)
"Market Wizards" - Jack Schwager (trader interviews)
EMA and Moving Averages:
"Moving Averages 101" - Steve Burns
Articles on Investopedia about EMA
Risk Management:
"The Mathematics of Money Management" - Ralph Vince
"Trade Your Way to Financial Freedom" - Van K. Tharp
Trading Journals:
Edgewonk (paid, very powerful)
Tradervue (free version + premium)
Excel/Google Sheets (free)
Screeners:
TradingView Stock Screener
Finviz (stocks)
CoinMarketCap (crypto)
Conclusion
Hellenic EMA Matrix is a powerful tool based on universal mathematical constants of nature. The indicator combines:
Mathematical elegance - Phi, Pi, e instead of arbitrary numbers
Premium visualization - Neon Glow, Gradient Clouds, Pulsing Bar
Reliable signals - STRONG BUY/SELL work on all timeframes
Flexibility - 6 EMA types, adaptation to any trading style
Automation - auto-sorting EMAs, SL/TP calculation, alerts
Key Success Principles:
Simplicity - start with basic settings (Phi/Pi/e, Base=10)
Discipline - follow STRONG signals strictly
Patience - wait for quality setups
Risk Management - 1-2% per trade, ALWAYS
Journal - document every trade
Learning - constantly improve skills
Remember:
Indicator shows probability, not guarantee
Important is series statistics, not one trade
Psychology more important than technique
Quality more important than quantity
Process more important than result
Acknowledgments
Thank you for using Hellenic EMA Matrix - Alpha Omega Premium!
The indicator was created with love for mathematics, markets, and beautiful visualization.
Wishing you profitable trading!
Guide Version: 1.0
Date: 2025
Compatibility: Pine Script v6, TradingView
"In the simplicity of mathematical constants lies the complexity of market movements"
