The Ultimate Lot Size Calculator Backstory
I created this Pine Script tool to calculate lot sizes with precision. While there are many lot size calculators available on TradingView, I found that most had significant flaws. I started teaching myself Pine Script over three and a half years ago with the sole purpose of building this tool. My first version was messy and lacked accuracy, so I never published it. I wanted it to be better than any other available tool, but my limited knowledge back then held me back.
Recently, I received a request to create a similar tool, as the current options still fail to deliver the precision and reliability traders need. This inspired me to revisit my original idea. With improved skills and a better understanding of Pine Script, I redesigned the tool from scratch, making it as precise, reliable, and efficient as possible.
This tool features built-in error detection to minimize mistakes and ensure accuracy in lot size calculations. I've spent more time on this project than on any other, focusing on delivering a solution that stands out on TradingView. While I plan to add more features based on user feedback, the current version is already a powerful, dependable, and easy-to-use tool for traders who value precision and efficiency in their lot size calculations.
How to use the tool ?
At first it might seem complicated, but it is quite easy to use the tool. There are two modes: auto and manual. By default, the tool is set on manual mode. When you apply the tool on the chart, it will ask you to choose the entry price, then the stop-loss price, and at last the take-profit price. Select all of them one by one. These values can be changed later.
Settings
There are various setting given for making the tool as flexible as possible. Here is the explanation for some of most important settings. Play with them and make yourself comfortable.
General settings
Auto mode : Use this mode if you want the the risk reward to be fixed and stop loss to be based on ATR. However the stop loss can be changed to be based on user input.
Manual mode : Use this mode if you want full control over entry, stop loss and take profit.
Contract Size : The tool works perfectly for all forex pairs including gold and silver but as the contract size is different for different assets it is difficult to add every single asset into the script manually so i have provided this option. In case you want to calculate lot size for a asset other then forex, gold or silver make sure to change this. Contract size = Quantity of the asset in 1 standerd lot.
Account settings
Automatic mode settings and ATR stop settings
Manual mode settings
Table and risk-reward box settings are pretty much self-explanatory i guess.
Error handling
A lot size calculator is a complex program. There are numerous points where it may fail and produce incorrect results. To make it robust and accurate, these issues must be addressed and managed properly, which practically all existing lot size calculator scripts fail to do.
Golden tip
When the symbol is changed it will display a symbol change warning as the entry, stop loss and take profit price won't change.
There are 2 ways to get fix this. Either manually enter all three values which i hate the most or remove the script from the chart and re-apply the script on chart again.
So to re-apply the indicator in most easy way follow the following instructions:
Note : If you encounter any other error then read the instruction to fix it and if it is an unknow error pleas report it to me in comments or DM.
Cari dalam skrip untuk "profit"
Boilerplate Configurable Strategy [Yosiet]This is a Boilerplate Code!
Hello! First of all, let me introduce myself a little bit. I don't come from the world of finance, but from the world of information and communication technologies (ICT) where we specialize in data processing with the aim of automating it and eliminating all human factors and actors in the processes. You could say that I am an algotrader.
That said, in my journey through trading in recent years I have understood that this world is often shown to be incomplete. All those who want to learn about trading only end up learning a small part of what it really entails, they only seek to learn how to read candlesticks. Therefore, I want to share with the entire community a fraction of what I have really understood it to be.
As a computer scientist, the most important thing is the data, it is the raw material of our work and without data you simply cannot do anything. Entropy is simple: Data in -> Data is transformed -> Data out.
The quality of the outgoing data will directly depend on the incoming data, there is no greater mystery or magic in the process. In trading it is no different, because at the end of the day it is nothing more than data. As we often say, if garbage comes in, garbage comes out.
Most people focus on the results only, on the outgoing data, because in the end we all want the same thing, to make easy money. Very few pay attention to the input data, much less to the process.
Now, I am not here to delude you, because there is no bigger lie than easy money, but I am here to give you a boilerplate code that will help you create strategies where you only have to concentrate on the quality of the incoming data.
To the Point
The code is a strategy boilerplate that applies the technique that you decide to customize for the criteria for opening a position. It already has the other factors involved in trading programmed and automated.
1. The Entry
This section of the boilerplate is the one that each individual must customize according to their needs and knowledge. The code is offered with two simple, well-known strategies to exemplify how the code can be reused for your own benefits.
For the purposes of this post on tradingview, I am going to use the simplest of the known strategies in trading for entries: SMA Crossing
// SMA Cross Settings
maFast = ta.sma(close, length)
maSlow = ta.sma(open, length)
The Strategy Properties for all cases published here:
For Stock TSLA H1 From 01/01/2025 To 02/15/2025
For Crypto XMR-USDT 30m From 01/01/2025 To 02/15/2025
For Forex EUR-USD 5m From 01/01/2025 To 02/15/2025
But the goal of this post is not to sell you a dream, else to show you that the same Entry decision works very well for some and does not for others and with this boilerplate code you only have to think of entries, not exits.
2. Schedules, Days, Sessions
As you know, there are an infinite number of markets that are susceptible to the sessions of each country and the news that they announce during those sessions, so the code already offers parameters so that you can condition the days and hours of operation, filter the best time parameters for a specific market and time frame.
3. Data Filtering
The data offered in trading are numerical series presented in vectors on a time axis where an endless number of mathematical equations can be applied to process them, with matrix calculation and non-linear regressions being the best, in my humble opinion.
4. Read Fundamental Macroeconomic Events, News
The boilerplate has integration with the tradingview SDK to detect when news will occur and offers parameters so that you can enable an exclusion time margin to not operate anything during that time window.
5. Direction and Sense
In my experience I have found the peculiarity that the same algorithm works very well for a market in a time frame, but for the same market in another time frame it is only a waste of time and money. So now you can easily decide if you only want to open LONG, SHORT or both side positions and know how effective your strategy really is.
6. Reading the money, THE PURPOSE OF EVERYTHING
The most important section in trading and the reason why many clients usually hire me as a financial programmer, is reading and controlling the money, because in the end everyone wants to win and no one wants to lose. Now they can easily parameterize how the money should flow and this is the genius of this boilerplate, because it is what will really decide if an algorithm (Indicator: A bunch of math equations) for entries will really leave you good money over time.
7. Managing the Risk, The Ego Destroyer
Many trades, little money. Most traders focus on making money and none of them know about statistics and the few who do know something about it, only focus on the winrate. Well, with this code you can unlock what really matters, the true success criteria to be able to live off of trading: Profit Factor, Sortino Ratio, Sharpe Ratio and most importantly, will you really make money?
8. Managing Emotions
Finally, the main reason why many lose money is because they are very bad at managing their emotions, because with this they will no longer need to do so because the boilerplate has already programmed criteria to chase the price in a position, cut losses and maximize profits.
In short, this is a boilerplate code that already has the data processing and data output ready, you only have to worry about the data input.
“And so the trader learned: the greatest edge was not in predicting the storm, but in building a boat that could not sink.”
DISCLAIMER
This post is intended for programmers and quantitative traders who already have a certain level of knowledge and experience. It is not intended to be financial advice or to sell you any money-making script, if you use it, you do so at your own risk.
On-chain Zscore | QuantumResearchQuantumResearch On-chain Zscore Indicator
The On-chain Zscore Indicator by QuantumResearch is a cutting-edge tool designed for traders and analysts who leverage on-chain metrics to assess Bitcoin’s market conditions. This indicator calculates a composite Z-score using three key on-chain metrics: NUPL (Net Unrealized Profit/Loss), SOPR (Spent Output Profit Ratio), and MVRV (Market Value to Realized Value). By normalizing these values through standard deviations, the indicator provides a dynamic, data-driven approach to identifying overbought and oversold conditions, improving market timing and decision-making.
1. Overview
This indicator integrates multiple on-chain metrics to:
Assess Market Cycles – Utilize Z-score normalization to detect potential tops and bottoms.
Smooth Volatility – Apply EMA and standard deviation filtering to refine signals.
Identify Buy & Sell Signals – Use adaptive thresholds to highlight market extremes.
Provide Visual Clarity – Color-coded bar signals and background fills for intuitive analysis.
2. How It Works
A. Z-score Calculation
What is a Z-score? – The Z-score measures how far a data point deviates from its historical mean in terms of standard deviations. This helps in identifying statistical extremes.
Zscore(source,mean,std)=>
zscore = (source-mean)/std
zscore
Standard Deviation Normalization – Each on-chain metric (NUPL, SOPR, MVRV) is individually standardized before being combined into a final score.
B. On-Chain Components
NUPL Z-score – Measures unrealized profits and losses relative to market cycles.
SOPR Z-score – Evaluates profit-taking behavior on spent outputs.
MVRV Z-score – Assesses whether Bitcoin is overvalued or undervalued based on market cap vs. realized cap.
C. Composite On-chain Score
The indicator computes an average Z-score of the three on-chain metrics to create a composite market assessment.
Adaptive thresholds (default: 0.73 for bullish signals, -0.44 for bearish signals) dynamically adjust based on market conditions.
3. Visual Representation
This indicator features color-coded elements and dynamic threshold visualization:
Bar Colors
Green Bars – Bullish conditions when Z-score exceeds the upper threshold.
Red Bars – Bearish conditions when Z-score drops below the lower threshold.
Gray Bars – Neutral market conditions.
Threshold Bands & Background Fill
Upper Band (Overbought) – Default threshold set at 0.73.
Middle Band – Neutral zone at 0.
Lower Band (Oversold) – Default threshold set at -0.44.
4. Customization & Parameters
This indicator is highly configurable, allowing traders to fine-tune settings based on their strategy:
On-Chain Z-score Settings
NUPL Z-score Length – Default: 126 periods
SOPR Z-score Length – Default: 111 periods
MVRV Z-score Length – Default: 111 periods
Signal Thresholds
Upper Threshold (Bullish Zone) – Default: 0.73
Lower Threshold (Bearish Zone) – Default: -0.44
Color & Visual Settings
Choose from eight customizable color modes to suit personal preferences.
5. Trading Applications
The On-chain Zscore Indicator is versatile and can be applied in various market scenarios:
Macro Trend Analysis – Identify long-term market tops and bottoms using normalized on-chain metrics.
Momentum Confirmation – Validate price action trends with SOPR & MVRV behavior.
Market Timing – Use deviation thresholds to enter at historically significant price zones.
Risk Management – Avoid overextended markets by watching for extreme Z-score readings.
6. Final Thoughts
The QuantumResearch On-chain Zscore Indicator provides a unique approach to market evaluation by combining three critical on-chain metrics into a single, normalized score.
By standardizing Bitcoin’s market behavior, this tool helps traders and investors make informed decisions based on historical statistical extremes.
Backtesting and validation are essential before using this indicator in live trading. While it enhances market analysis, it should be used alongside other tools and strategies.
Disclaimer: No indicator can guarantee future performance. Always use appropriate risk management and perform due diligence before trading.
ICT NY Kill Zone Auto Trading### **ICT NY Kill Zone Auto Trading Strategy (5-Min Chart)**
#### **Overview:**
This strategy is based on Inner Circle Trader (ICT) concepts, focusing on the **New York Kill Zone**. It is designed for trading GBP/USD exclusively on the **5-minute chart**, automatically entering and exiting trades during the US session.
#### **Key Components:**
1. **Time Filter**
- The strategy only operates during the **New York Kill Zone (9:30 AM - 11:00 AM NY Time)**.
- It ensures execution only on the **5-minute timeframe**.
2. **Fair Value Gaps (FVGs) Detection**
- The script identifies areas where price action left an imbalance, known as Fair Value Gaps (FVGs).
- These gaps indicate potential liquidity zones where price may return before continuing in the original direction.
3. **Order Blocks (OBs) Identification**
- **Bullish Order Block:** Occurs when price forms a strong bullish pattern, suggesting further upside movement.
- **Bearish Order Block:** Identified when a strong bearish formation signals potential downside continuation.
4. **Trade Execution**
- **Long Trade:** Entered when a bullish order block forms within the NY Kill Zone and aligns with an FVG.
- **Short Trade:** Entered when a bearish order block forms within the Kill Zone and aligns with an FVG.
5. **Risk Management**
- **Stop Loss:** Fixed at **30 pips** to limit downside risk.
- **Take Profit:** Set at **60 pips**, providing a **2:1 risk-reward ratio**.
6. **Visual Aids**
- The **Kill Zone is highlighted in blue** to help traders visually confirm the active session.
**Objective:**
This script aims to **capitalize on institutional price movements** within the New York session by leveraging ICT concepts such as FVGs and Order Blocks. By automating trade entries and exits, it eliminates emotions and ensures a disciplined trading approach.
EMA Crossover Backtest [BarScripts]This indicator lets you backtest an EMA crossover strategy with built-in risk management and trade tracking. It simulates long and short trades based on EMA crossovers, allowing you to fine-tune entry conditions, stop-loss placement, and reward/risk settings.
🔹 How It Works:
Long Entry: Fast EMA crosses above Slow EMA, and price closes above Fast EMA.
Short Entry: Fast EMA crosses below Slow EMA, and price closes below Fast EMA.
Stop Loss: Set based on previous bars or a fixed amount.
Take Profit: Adjustable reward/risk ratio.
Higher Timeframe Confluence: Confirms trades based on a larger timeframe.
Trade Hours Filter: Limits trades to specific time windows.
🔹 Key Features:
✅ Shows Entry & Exit Points with visual trade lines.
✅ Customizable EMA Lengths to fit any strategy.
✅ P&L Tracking & Statistics to measure performance.
✅ Position Sizing Options: Fixed position, fixed risk, or percentage of balance.
✅ Commissions Tracking (based on total trades, not contracts).
Use this tool to fine-tune your EMA crossover strategy and see how it performs over time! 🚀
💬 Let me know your feedback—suggest improvements, report issues, or request new features!
[AcerX] Leverage, TP & Optimal TP CalculatorHow It Works
Inputs:
Portfolio Allocation (%): The percentage of your portfolio you're willing to risk on the trade.
Stop Loss (%): The stop loss distance below the entry price.
Taker Fee (%) and Maker Fee (%): The fees applied on entry and exit.
Calculations:
The script calculates the required "raw" leverage to risk 1% of your portfolio.
It floors the computed leverage to an integer ("effectiveLeverage").
If the computed leverage is less than 1, it shows an error message (and suggests the maximum allocation for at least 1× leverage).
Otherwise, it calculates the TP levels for target profits of 1.2%, 1.5%, and 2%, and an "Optimal TP" that nets a 1% profit after fees.
Display:
A table is drawn on the top right corner of your chart displaying the effective leverage, the TP levels, and an error message if applicable.
Simply add this script as a new indicator in TradingView, and adjust the inputs as needed.
Happy trading!
Classic Nacked Z-Score ArbitrageThe “Classic Naked Z-Score Arbitrage” strategy employs a statistical arbitrage model based on the Z-score of the price spread between two assets. This strategy follows the premise of pair trading, where two correlated assets, typically from the same market sector, are traded against each other to profit from relative price movements (Gatev, Goetzmann, & Rouwenhorst, 2006). The approach involves calculating the Z-score of the price spread between two assets to determine market inefficiencies and capitalize on short-term mispricing.
Methodology
Price Spread Calculation:
The strategy calculates the spread between the two selected assets (Asset A and Asset B), typically from different sectors or asset classes, on a daily timeframe.
Statistical Basis – Z-Score:
The Z-score is used as a measure of how far the current price spread deviates from its historical mean, using the standard deviation for normalization.
Trading Logic:
• Long Position:
A long position is initiated when the Z-score exceeds the predefined threshold (e.g., 2.0), indicating that Asset A is undervalued relative to Asset B. This signals an arbitrage opportunity where the trader buys Asset B and sells Asset A.
• Short Position:
A short position is entered when the Z-score falls below the negative threshold, indicating that Asset A is overvalued relative to Asset B. The strategy involves selling Asset B and buying Asset A.
Theoretical Foundation
This strategy is rooted in mean reversion theory, which posits that asset prices tend to return to their long-term average after temporary deviations. This form of arbitrage is widely used in statistical arbitrage and pair trading techniques, where investors seek to exploit short-term price inefficiencies between two assets that historically maintain a stable price relationship (Avery & Sibley, 2020).
Further, the Z-score is an effective tool for identifying significant deviations from the mean, which can be seen as a signal for the potential reversion of the price spread (Braucher, 2015). By capturing these inefficiencies, traders aim to profit from convergence or divergence between correlated assets.
Practical Application
The strategy aligns with the Financial Algorithmic Trading and Market Liquidity analysis, emphasizing the importance of statistical models and efficient execution (Harris, 2024). By utilizing a simple yet effective risk-reward mechanism based on the Z-score, the strategy contributes to the growing body of research on market liquidity, asset correlation, and algorithmic trading.
The integration of transaction costs and slippage ensures that the strategy accounts for practical trading limitations, helping to refine execution in real market conditions. These factors are vital in modern quantitative finance, where liquidity and execution risk can erode profits (Harris, 2024).
References
• Gatev, E., Goetzmann, W. N., & Rouwenhorst, K. G. (2006). Pairs Trading: Performance of a Relative-Value Arbitrage Rule. The Review of Financial Studies, 19(3), 1317-1343.
• Avery, C., & Sibley, D. (2020). Statistical Arbitrage: The Evolution and Practices of Quantitative Trading. Journal of Quantitative Finance, 18(5), 501-523.
• Braucher, J. (2015). Understanding the Z-Score in Trading. Journal of Financial Markets, 12(4), 225-239.
• Harris, L. (2024). Financial Algorithmic Trading and Market Liquidity: A Comprehensive Analysis. Journal of Financial Engineering, 7(1), 18-34.
Daily COC Strategy with SHERLOCK WAVESThis indicator implements a unique trading strategy known as the "Daily COC (Candle Over Candle) Strategy" enhanced with "SHERLOCK WAVES" for pattern recognition. It's designed for traders looking to capitalize on specific candlestick formations with a negative risk-reward ratio, with the aim of achieving a high win rate (over 70%) through numerous trading opportunities, despite each trade having a higher risk relative to the reward.
Key Features:
Pattern Recognition: Identifies a setup based on three consecutive candles - a red candle followed by a shooting star, then an entry candle that does not break below the shooting star's low.
Negative Risk/Reward Trade Selection: Focuses on entries where the potential stop loss is greater than the take profit, banking on a high win rate to offset the individual trade's negative risk-reward ratio.
Visual Signals:
Green Label: Marks potential entry points at the high of the candle before the entry.
Green Dot: Indicates a winning trade closure.
Red Dot: Signals a losing trade closure.
Blue Circle: Warns when the current candle is within 2% of breaking above the previous candle's high, suggesting a potential setup is developing.
Green Circle: Plots the take profit level.
Red Circle: Plots the stop loss level.
Dynamic Statistics: A live updating label showing the number of trades, wins, losses, open trades, current account balance, and win percentage.
Customizable Parameters:
Risk % per Trade: Adjust the percentage of your account balance you're willing to risk on each trade.
Initial Account Balance: Set your starting balance for tracking performance.
Start Date for Strategy: Define when the strategy should start calculating from, allowing for backtesting.
Alerts:
An alert condition is set for when a potential trade setup is developing, helping traders prepare for entries.
Usage Tips:
This strategy is predicated on the idea that a high win rate can compensate for the negative risk-reward ratio of individual trades. It might not suit all market conditions or traders' risk profiles.
Use this strategy in conjunction with other analysis methods to validate trade setups.
Note: Always backtest thoroughly before applying to live markets. Consider this tool as part of a broader trading strategy, not a standalone solution. Monitor your win rate and adjust your risk management accordingly to ensure the strategy remains profitable over time.
This description now correctly explains the purpose behind the negative risk-reward ratio in the context of your trading strategy.
Gold Pro StrategyHere’s the strategy description in a chat format:
---
**Gold (XAU/USD) Trend-Following Strategy**
This **trend-following strategy** is designed for trading gold (XAU/USD) by combining moving averages, MACD momentum indicators, and RSI filters to capture sustained trends while managing volatility risks. The strategy uses volatility-adjusted stops to protect gains and prevent overexposure during erratic price movements. The aim is to take advantage of trending markets by confirming momentum and ensuring entries are not made at extreme levels.
---
**Key Components**
1. **Trend Identification**
- **50 vs 200 EMA Crossover**
- **Bullish Trend:** 50 EMA crosses above 200 EMA, and the price closes above the 200 EMA
- **Bearish Trend:** 50 EMA crosses below 200 EMA, and the price closes below the 200 EMA
2. **Momentum Confirmation**
- **MACD (12,26,9)**
- **Buy Signal:** MACD line crosses above the signal line
- **Sell Signal:** MACD line crosses below the signal line
- **RSI (14 Period)**
- **Bullish Zone:** RSI between 50-70 to avoid overbought conditions
- **Bearish Zone:** RSI between 30-50 to avoid oversold conditions
3. **Entry Criteria**
- **Long Entry:** Bullish trend, MACD bullish crossover, and RSI between 50-70
- **Short Entry:** Bearish trend, MACD bearish crossover, and RSI between 30-50
4. **Exit & Risk Management**
- **ATR Trailing Stops (14 Period):**
- Initial Stop: 3x ATR from entry price
- Trailing Stop: Adjusts to lock in profits as price moves favorably
- **Position Sizing:** 100% of equity per trade (high-risk strategy)
---
**Key Logic Flow**
1. **Trend Filter:** Use the 50/200 EMA relationship to define the market's direction
2. **Momentum Confirmation:** Confirm trend momentum with MACD crossovers
3. **RSI Validation:** Ensure RSI is within non-extreme ranges before entering trades
4. **Volatility-Based Risk Management:** Use ATR stops to manage market volatility
---
**Visual Cues**
- **Blue Line:** 50 EMA
- **Red Line:** 200 EMA
- **Green Triangles:** Long entry signals
- **Red Triangles:** Short entry signals
---
**Strengths**
- **Clear Trend Focus:** Avoids counter-trend trades
- **RSI Filter:** Prevents entering overbought or oversold conditions
- **ATR Stops:** Adapts to gold’s inherent volatility
- **Simple Rules:** Easy to follow with minimal inputs
---
**Weaknesses & Risks**
- **Infrequent Signals:** 50/200 EMA crossovers are rare
- **Potential Missed Opportunities:** Strict RSI criteria may miss some valid trends
- **Aggressive Position Sizing:** 100% equity allocation can lead to large drawdowns
- **No Profit Targets:** Relies on trailing stops rather than defined exit targets
---
**Performance Profile**
| Metric | Expected Range |
|----------------------|---------------------|
| Annual Trades | 4-8 |
| Win Rate | 55-65% |
| Max Drawdown | 25-35% |
| Profit Factor | 1.8-2.5 |
---
**Optimization Recommendations**
1. **Increase Trade Frequency**
Adjust the EMAs to shorter periods:
- `emaFastLen = input.int(30, "Fast EMA")`
- `emaSlowLen = input.int(150, "Slow EMA")`
2. **Relax RSI Filters**
Adjust the RSI range to:
- `rsiBullish = rsi > 45 and rsi < 75`
- `rsiBearish = rsi < 55 and rsi > 25`
3. **Add Profit Targets**
Introduce a profit target at 1.5% above entry:
```pine
strategy.exit("Long Exit", "Long",
stop=longStopPrice,
profit=close*1.015, // 1.5% target
trail_offset=trailOffset)
```
4. **Reduce Position Sizing**
Risk a smaller percentage per trade:
- `default_qty_value=25`
---
**Best Use Case**
This strategy excels in **strong trending markets** such as gold rallies during economic or geopolitical crises. However, during sideways or choppy market conditions, the strategy might require manual intervention to avoid false signals. Additionally, integrating fundamental analysis—like monitoring USD weakness or geopolitical risks—can enhance its effectiveness.
---
This strategy offers a balanced approach for trading gold, combining trend-following principles with risk management tailored to the volatility of the market.
Trend & ADX by Gideon for Indian MarketsThis indicator is designed to help traders **identify strong trends** using the **Kalman Filter** and **ADX** (Average Directional Index). It provides **Buy/Sell signals** based on trend direction and ADX strength. I wanted to create something for Indian markets since there are not much available.
In a nut-shell:
✅ **Buy when the Kalman Filter turns green, and ADX is strong.
❌ **Sell when the Kalman Filter turns red, and ADX is strong.
📌 **Ignore signals if ADX is weak (below threshold).
📊 Use on 5-minute timeframes for intraday trading.
------------------------------------------------------------------------
1. Understanding the Indicator Components**
- **Green Line:** Indicates an **uptrend**.
- **Red Line:** Indicates a **downtrend**.
- The **line color change** signals a potential **trend reversal**.
**ADX Strength Filter**
- The **ADX (orange line)** measures trend strength.
- The **blue horizontal line** marks the **ADX threshold** (default: 20).
- A **Buy/Sell signal is only valid if ADX is above the threshold**, ensuring a strong trend.
**Buy & Sell Signals**
- **Buy Signal (Green Up Arrow)**
- Appears **one candle before** the Kalman line turns green.
- ADX must be **above the threshold** (default: 20).
- Suggests entering a **long position**.
- **Sell Signal (Red Down Arrow)**
- Appears **one candle before** the Kalman line turns red.
- ADX must be **above the threshold** (default: 20).
- Suggests entering a **short position**.
2. Best Settings for 5-Minute Timeframe**
For day trading on the **5-minute chart**, the following settings work best:
- **Kalman Filter Length:** `50`
- **Process Noise (Q):** `0.1`
- **Measurement Noise (R):** `0.01`
- **ADX Length:** `14`
- **ADX Threshold:** `20`
- **(Increase to 25-30 for more reliable signals in volatile markets)**
3. How to Trade with This Indicator**
**Entry Rules**
✅ **Buy Entry**
- Wait for a **green arrow (Buy Signal).
- Kalman Line must **turn green**.
- ADX must be **above the threshold** (strong trend confirmed).
- Enter a **long position** on the next candle.
❌ **Sell Entry**
- Wait for a **red arrow (Sell Signal).
- Kalman Line must **turn red**.
- ADX must be **above the threshold** (strong trend confirmed).
- Enter a **short position** on the next candle.
**Exit & Risk Management**
📌 **Stop Loss**:
- Place stop-loss **below the previous swing low** (for buys) or **above the previous swing high** (for sells).
📌 **Take Profit:
- Use a **Risk:Reward Ratio of 1:2 or 1:3.
- Exit when the **Kalman Filter color changes** (opposite trend signal).
📌 **Avoid Weak Trends**:
- **No trades when ADX is below the threshold** (low trend strength).
4. Additional Tips
- Works best on **liquid assets** like **Bank Nifty, Nifty 50, and large-cap stocks**.
- **Avoid ranging markets** with low ADX values (<20).
- Use alongside **volume analysis and support/resistance levels** for confirmation.
- Experiment with **ADX Threshold (increase for stronger signals, decrease for more trades).**
Best of Luck traders ! 🚀
Johnny's Machine Learning Moving Average (MLMA) w/ Trend Alerts📖 Overview
Johnny's Machine Learning Moving Average (MLMA) w/ Trend Alerts is a powerful adaptive moving average indicator designed to capture market trends dynamically. Unlike traditional moving averages (e.g., SMA, EMA, WMA), this indicator incorporates volatility-based trend detection, Bollinger Bands, ADX, and RSI, offering a comprehensive view of market conditions.
The MLMA is "machine learning-inspired" because it adapts dynamically to market conditions using ATR-based windowing and integrates multiple trend strength indicators (ADX, RSI, and volatility bands) to provide an intelligent moving average calculation that learns from recent price action rather than being static.
🛠 How It Works
1️⃣ Adaptive Moving Average Selection
The MLMA automatically selects one of four different moving averages:
📊 EMA (Exponential Moving Average) – Reacts quickly to price changes.
🔵 HMA (Hull Moving Average) – Smooth and fast, reducing lag.
🟡 WMA (Weighted Moving Average) – Gives recent prices more importance.
🔴 VWAP (Volume Weighted Average Price) – Accounts for volume impact.
The user can select which moving average type to use, making the indicator customizable based on their strategy.
2️⃣ Dynamic Trend Detection
ATR-Based Adaptive Window 📏
The Average True Range (ATR) determines the window size dynamically.
When volatility is high, the moving average window expands, making the MLMA more stable.
When volatility is low, the window shrinks, making the MLMA more responsive.
Trend Strength Filters 📊
ADX (Average Directional Index) > 25 → Indicates a strong trend.
RSI (Relative Strength Index) > 70 or < 30 → Identifies overbought/oversold conditions.
Price Position Relative to Upper/Lower Bands → Determines bullish vs. bearish momentum.
3️⃣ Volatility Bands & Dynamic Support/Resistance
Bollinger Bands (BB) 📉
Uses standard deviation-based bands around the MLMA to detect overbought and oversold zones.
Upper Band = Resistance, Lower Band = Support.
Helps traders identify breakout potential.
Adaptive Trend Bands 🔵🔴
The MLMA has built-in trend envelopes.
When price breaks the upper band, bullish momentum is confirmed.
When price breaks the lower band, bearish momentum is confirmed.
4️⃣ Visual Enhancements
Dynamic Gradient Fills 🌈
The trend strength (ADX-based) determines the gradient intensity.
Stronger trends = More vivid colors.
Weaker trends = Lighter colors.
Trend Reversal Arrows 🔄
🔼 Green Up Arrow: Bullish reversal signal.
🔽 Red Down Arrow: Bearish reversal signal.
Trend Table Overlay 🖥
Displays ADX, RSI, and Trend State dynamically on the chart.
📢 Trading Signals & How to Use It
1️⃣ Bullish Signals 📈
✅ Conditions for a Long (Buy) Trade:
The MLMA crosses above the lower band.
The ADX is above 25 (confirming trend strength).
RSI is above 55, indicating positive momentum.
Green trend reversal arrow appears (confirmation of a bullish reversal).
🔹 How to Trade It:
Enter a long trade when the MLMA turns bullish.
Set stop-loss below the lower Bollinger Band.
Target previous resistance levels or use the upper band as take-profit.
2️⃣ Bearish Signals 📉
✅ Conditions for a Short (Sell) Trade:
The MLMA crosses below the upper band.
The ADX is above 25 (confirming trend strength).
RSI is below 45, indicating bearish pressure.
Red trend reversal arrow appears (confirmation of a bearish reversal).
🔹 How to Trade It:
Enter a short trade when the MLMA turns bearish.
Set stop-loss above the upper Bollinger Band.
Target the lower band as take-profit.
💡 What Makes This a Machine Learning Moving Average?
📍 1️⃣ Adaptive & Self-Tuning
Unlike static moving averages that rely on fixed parameters, this MLMA automatically adjusts its sensitivity to market conditions using:
ATR-based dynamic windowing 📏 (Expands/contracts based on volatility).
Adaptive smoothing using EMA, HMA, WMA, or VWAP 📊.
Multi-indicator confirmation (ADX, RSI, Volatility Bands) 🏆.
📍 2️⃣ Intelligent Trend Confirmation
The MLMA "learns" from recent price movements instead of blindly following a fixed-length average.
It incorporates ADX & RSI trend filtering to reduce noise & false signals.
📍 3️⃣ Dynamic Color-Coding for Trend Strength
Strong trends trigger more vivid colors, mimicking confidence levels in machine learning models.
Weaker trends appear faded, suggesting uncertainty.
🎯 Why Use the MLMA?
✅ Pros
✔ Combines multiple trend indicators (MA, ADX, RSI, BB).
✔ Automatically adjusts to market conditions.
✔ Filters out weak trends, making it more reliable.
✔ Visually intuitive (gradient colors & reversal arrows).
✔ Works across all timeframes and assets.
⚠️ Cons
❌ Not a standalone strategy → Best used with volume confirmation or candlestick analysis.
❌ Can lag slightly in fast-moving markets (due to smoothing).
Auto-Adjusting Kalman Filter by TenozenNew year, new indicator! Auto-Adjusting Kalman Filter is an indicator designed to provide an adaptive approach to trend analysis. Using the Kalman Filter (a recursive algorithm used in signal processing), this algo dynamically adjusts to market conditions, offering traders a reliable way to identify trends and manage risk! In other words, it's a remaster of my previous indicator, Kalman Filter by Tenozen.
What's the difference with the previous indicator (Kalman Filter by Tenozen)?
The indicator adjusts its parameters (Q and R) in real-time using the Average True Range (ATR) as a measure of market volatility. This ensures the filter remains responsive during high-volatility periods and smooth during low-volatility conditions, optimizing its performance across different market environments.
The filter resets on a user-defined timeframe, aligning its calculations with dominant trends and reducing sensitivity to short-term noise. This helps maintain consistency with the broader market structure.
A confidence metric, derived from the deviation of price from the Kalman filter line (measured in ATR multiples), is visualized as a heatmap:
Green : Bullish confidence (higher values indicate stronger trends).
Red : Bearish confidence (higher values indicate stronger trends).
Gray : Neutral zone (low confidence, suggesting caution).
This provides a clear, objective measure of trend strength.
How it works?
The Kalman Filter estimates the "true" price by filtering out market noise. It operates in two steps, that is, prediction and update. Prediction is about projection the current state (price) forward. Update is about adjusting the prediction based on the latest price data. The filter's parameters (Q and R) are scaled using normalized ATR, ensuring adaptibility to changing market conditions. So it means that, Q (Process Noise) increases during high volatility, making the filter more responsive to price changes and R (Measurement Noise) increases during low volatility, smoothing out the filter to avoid overreacting to minor fluctuations. Also, the trend confidence is calculated based on the deviation of price from the Kalman filter line, measured in ATR multiples, this provides a quantifiable measure of trend strength, helping traders assess market conditions objectively.
How to use?
Use the Kalman Filter line to identify the prevailing trend direction. Trade in alignment with the filter's slope for higher-probability setups.
Look for pullbacks toward the Kalman Filter line during strong trends (high confidence zones)
Utilize the dynamic stop-loss and take-profit levels to manage risk and lock in profits
Confidence Heatmap provides an objective measure of market sentiment, helping traders avoid low-confidence (neutral) zones and focus on high-probability opportunities
Guess that's it! I hope this indicator helps! Let me know if you guys got some feedback! Ciao!
IU Range Trading StrategyIU Range Trading Strategy
The IU Range Trading Strategy is designed to identify range-bound markets and take trades based on defined price ranges. This strategy uses a combination of price ranges and ATR (Average True Range) to filter entry conditions and incorporates a trailing stop-loss mechanism for better trade management.
User Inputs:
- Range Length: Defines the number of bars to calculate the highest and lowest price range (default: 10).
- ATR Length: Sets the length of the ATR calculation (default: 14).
- ATR Stop-Loss Factor: Determines the multiplier for the ATR-based stop-loss (default: 2.00).
Entry Conditions:
1. A range is identified when the difference between the highest and lowest prices over the selected range is less than or equal to 1.75 times the ATR.
2. Once a valid range is formed:
- A long trade is triggered at the range high.
- A short trade is triggered at the range low.
Exit Conditions:
1. Trailing Stop-Loss:
- The stop-loss adjusts dynamically using ATR targets.
- The strategy locks in profits as the trade moves in your favor.
2. The stop-loss and take-profit levels are visually plotted for transparency and easier decision-making.
Features:
- Automated box creation to visualize the trading range.
- Supports one position at a time, canceling opposite-side entries.
- ATR-based trailing stop-loss for effective risk management.
- Clear visual representation of stop-loss and take-profit levels with colored bands.
This strategy works best in markets with defined ranges and can help traders identify breakout opportunities when the price exits the range.
Adaptive Fractal Grid Scalping StrategyThis Pine Script v6 component implements an "Adaptive Fractal Grid Scalping Strategy" with an added volatility threshold feature.
Here's how it works:
Fractal Break Detection: Uses ta.pivothigh and ta.pivotlow to identify local highs and lows.
Volatility Clustering: Measures volatility using the Average True Range (ATR).
Adaptive Grid Levels: Dynamically adjusts grid levels based on ATR and user-defined multipliers.
Directional Bias Filter: Uses a Simple Moving Average (SMA) to determine trend direction.
Volatility Threshold: Introduces a new input to specify a minimum ATR value required to activate the strategy.
Trade Execution Logic: Places limit orders at grid levels based on trend direction and fractal levels, but only when ATR exceeds the volatility threshold.
Profit-Taking and Stop-Loss: Implements profit-taking at grid levels and a trailing stop-loss based on ATR.
How to Use
Inputs: Customize the ATR length, SMA length, grid multipliers, trailing stop multiplier, and volatility threshold through the input settings.
Visuals: The script plots fractal points and grid levels on the chart for easy visualization.
Trade Signals: The strategy automatically places buy/sell orders based on the detected fractals, trend direction, and volatility threshold.
Profit and Risk Management: The script includes logic for taking profits and setting stop-loss levels to manage trades effectively.
This strategy is designed to capitalize on micro-movements during high volatility and avoid overtrading during low-volatility trends. Adjust the input parameters to suit your trading style and market conditions.
Fibonacci Trend [ChartPrime]Fibonacci Trend Indicator
This powerful indicator leverages supertrend analysis to detect market direction while overlaying dynamic Fibonacci levels to highlight potential support, resistance, and optimal trend entry zones. With its straightforward design, it is perfect for traders looking to simplify their workflow and enhance decision-making.
⯁ KEY FEATURES AND HOW TO USE
⯌ Supertrend Trend Identification :
The indicator uses a supertrend algorithm to identify market direction. It displays purple for downtrends and green for uptrends, ensuring quick and clear trend analysis.
⯌ Fibonacci Levels for Current Swings :
Automatically calculates Fibonacci retracement levels (0.236, 0.382, 0.618, 0.786) for the current swing leg.
- These levels act as key zones for potential support, resistance, and trend continuation.
- The high and low swing points are labeled with exact prices, ensuring clarity.
- If the swing range is insufficient (less than five times ATR), Fibonacci levels are not displayed, avoiding irrelevant data.
⯌ Extended Fibonacci Levels :
User-defined extensions project Fibonacci levels into the future, aiding traders in planning price targets or projecting key zones.
⯌ Optimal Trend Entry Zone :
A filled area between 0.618 and 0.786 levels visually highlights the optimal entry zone for trend continuation. This allows traders to refine their entry points during pullbacks.
⯌ Diagonal Trend Line :
A dashed diagonal line connects the swing high and low, visually confirming the range and trend strength of the current swing.
⯌ Visual Labels for Fibonacci Levels :
Each Fibonacci level is marked with a label displaying its value for quick reference.
⯁ HOW TRADERS CAN POTENTIALLY USE THIS TOOL
Fibonacci Retracements:
Use the Fibonacci retracement levels to find key support or resistance zones where the price may pull back before continuing its trend.
Example: Enter long trades when the price retraces to 0.618–0.786 levels in an uptrend.
Fibonacci Extensions:
Use Fibonacci extensions to project future price targets based on the current trend's swing leg. Levels like 127.2% and 161.8% are commonly used as profit-taking zones.
Reversal Identification:
Spot potential reversals by monitoring price reactions at key Fibonacci retracement levels (e.g., 0.236 or 0.382) or the swing high/low.
Optimal Trend Entries:
The filled zone between 0.618 and 0.786 is a statistically strong area for entering a position in the direction of the trend.
Example: Enter long positions during retracements to this range in an uptrend.
Risk Management:
Set stop-losses below key Fibonacci levels or the swing low/high, and take profits at extension levels, enhancing your trade management strategies.
⯁ CONCLUSION
The Fibonacci Trend Indicator is a straightforward yet effective tool for identifying trends and key Fibonacci levels. It simplifies analysis by integrating supertrend-based trend identification with Fibonacci retracements, extensions, and optimal entry zones. Whether you're a beginner or experienced trader, this indicator is an essential addition to your toolkit for trend trading, reversal spotting, and risk management.
ICT Digital open Daily DividersDescription for "ICT Digital Open Daily Dividers" TradingView Indicator
Overview
The "ICT Digital Open Daily Dividers" is a versatile and comprehensive TradingView Pine Script indicator designed for traders who utilize Institutional Order Flow methodologies, particularly in ICT (Inner Circle Trader) trading. This indicator provides a structured visual framework to assist traders in identifying key daily market sessions, critical opening prices, and distinguishing different trading days, especially focusing on the Sunday open, which is a crucial element in the ICT trading strategy.
Core Functionalities
Daily Vertical Lines: The script plots vertical lines at the start of each trading day, which helps to demarcate daily trading sessions. These lines are customizable, allowing traders to choose their color, style (solid, dashed, or dotted), and width. This feature helps in visually segmenting each trading day, making it easier to analyze daily price action patterns.
Sunday Open Differentiation: Unlike many other daily divider indicators, this script uniquely provides the option to highlight the Sunday open at 6 PM EST with distinct lines. This feature is especially valuable for ICT traders who consider the Sunday open as a critical reference point for weekly analysis. The color, style, and width of the Sunday open lines can be set separately, providing a clear visual distinction from regular weekday separators.
12 AM Open Toggle: For markets that are influenced by midnight opens, the indicator includes an option to shift the daily open line to 12 AM instead of the default 6 PM. This flexibility allows traders to adapt the indicator to different market dynamics or trading strategies.
Timezone Customization: The indicator allows traders to set the timezone for the open lines, ensuring that the vertical lines align accurately with the trader’s specific market hours, whether they follow New York time or any other timezone.
Session Time Filters: The script can hide or show specific trading session markers, such as the New York session open and close, which are pivotal for ICT traders. These markers help in focusing on the most active and liquid trading times.
Customizable Style Settings: The script includes comprehensive styling options for the plotted lines and session markers, allowing traders to personalize their charts to suit their visual preferences and improve clarity.
Day of the Week Labels: The indicator can plot labels for each day of the week, providing a quick reference to the day’s price action. This feature is particularly useful in reviewing weekly trading patterns and performance.
Use in ICT Trading
In ICT trading, the concept of the "open" is fundamental. The "ICT Digital Open Daily Dividers" indicator serves multiple purposes:
Market Structure Identification: By clearly marking daily opens, traders can easily identify market structure changes such as breakouts, retracements, or consolidations around these key levels.
Reference Points: The Sunday open is often a key level in ICT analysis, serving as a benchmark for assessing market direction for the upcoming week. This indicator’s ability to plot Sunday opens separately makes it uniquely suited for ICT strategies.
Time-based Analysis: ICT methodology often involves analyzing the market at specific times of the day. This indicator supports such analysis by marking significant session opens and closes.
Uniqueness and Advantages
The "ICT Digital Open Daily Dividers" stands out from other similar indicators due to its specialized features:
Sunday Open Highlighting: Few indicators offer the capability to specifically mark the Sunday open with distinct styling options.
Flexibility in Time Adjustments: With options to adjust the open time to either 6 PM or 12 AM, this indicator caters to a broader range of trading strategies and market conditions.
Enhanced Visualization: The wide range of customization options ensures that traders can tailor the indicator to their specific needs, enhancing the usability and visual clarity of their charts.
Compliance with TradingView's Pine Script Community Guidelines
The description adheres to TradingView's guidelines by being comprehensive, clear, and informative. It highlights the utility of the script, its unique features, and its application in trading strategies without making exaggerated claims about performance or profitability. The detailed customization options and unique functionalities are emphasized to differentiate this script from other standard daily divider indicators.
