Kalkulator pozycji N100This indicator is a real-time position size calculator designed specifically for NASDAQ 100 futures (E-mini NQ and Micro NQ). It works on any timeframe, best on 1-minute charts, and calculates your position size based on candle body (ignoring wicks). This allows you to always see your exact risk and the number of contracts you can take before the candle closes.
อินดิเคเตอร์และกลยุทธ์
MA-Median For Loop | MisinkoMasterThe MA-Median For Loop is a new Trend Following tool that gives the user smooth yet responsive trend signals, allowing you to see clear and accurate trends by combining the Moving Average & Median in a For Loop concept.
How does it work?
1. Select user defined inputs
=> Adjust it to your liking, everyone can set it to their liking.
2. Calculate the MA and the Median
=> Simple, but important
3. Calculate the For Loop
=> For every bar back where the median or ma of that bar is higher than the current median or ma subtract 0.5 from the trend score, and for every bar back where the current median/ma is higher than the previous one add 0.5 to the trend score.
This simple yet effective approach enhances speed, decreases noise, and produces accurate signals everyone can utilize to get an edge in the market
Enjoy G´s
HMA super trade by @arkancapMulti-HMA with five customizable moving averages: visual colors, transparency via picker, flexible line styles, and label/alert for HMA50↔HMA100 crossovers. Lightweight, readable, and ready for trading templates.
Мульти-HMA с пятью настраиваемыми скользящими: визуальные цвета, прозрачность через пикер, гибкие стили линий и метка/алерт для пересечений HMA50↔HMA100. Лёгкий, читабельный и готовый к торговым шаблонам.
Five Hull moving averages that show the trend and indicate key crossovers. Customize colors, thickness, and get accurate alerts. Suitable for scalping and multi-timeframes. Support for filling between moving averages to visually highlight areas of strength or weakness.
Пять Hull-скользящих, которые показывают тренд и подсказывают ключевые пересечения. Настраивай цвета, толщину и получай аккуратные алерты. Подходит для скальпа и мульти-таймфрейма. Поддержка заливки между скользящими для наглядного выделения зон силы или слабости.
DCA Anchor (Weekly/Monthly/N Bars) [CHE] What is Dollar-Cost Averaging (DCA)?
DCA is a position-building method where you invest a fixed amount at fixed intervals (e.g., weekly or monthly) regardless of price. Over time, this:
reduces timing risk (you don’t need to guess tops/bottoms),
smooths entry price by buying more units when price is low and fewer when price is high,
keeps decisions simple and repeatable.
Trade-offs:
You’ll never catch the exact bottom.
In strong uptrends, lump-sum can outperform.
Fees matter if you buy very frequently.
Simple math:
Qty bought at time t = `amount / price_t` (net of fees if fees are not “on top”).
Total qty = sum of all buys.
Average price (cost basis) = `total invested / total qty`.
Equity = `total qty last price`.
P\&L = `equity − total invested` (and `%` = `P&L / total invested`).
DCA Anchor (Weekly/Monthly/N Bars)
Purpose: automate scheduled DCA buys on chart data, optionally add extra buys on drawdowns, track stats, and fire alerts.
Core features
Schedules:
1. Every N bars,
2. Weekly (first bar of a new week),
3. Monthly (first bar of a new month).
A Start time input gates when the logic begins.
Fees model:
Fee on top: you pay `amount + fee` in cash; quantity = `amount / close`.
Fee from amount: fee is deducted from the amount; quantity is smaller, cash outlay equals `amount`.
Optional drawdown buys:
Trigger when `close ≤ avgCost (1 − ddPct/100)`.
Controls: drawdown % threshold, multiplier (extra size vs. base amount), and cooldown in bars.
State & metrics: tracks total invested, total quantity, average price, equity, P\&L (abs/%).
Visuals:
Line plot of Average Price.
Buy labels at execution bars (plan and drawdown).
Compact table (positionable) with key stats (trades, invested, qty, avg price, equity, P\&L).
Alerts:
Plan Buy (Bar Close) and Drawdown Buy (Bar Close) — robust, non-repainting.
Optional Intrabar Preview alerts for early heads-up (can fire before bar close).
How to use it (quick start)
1. Add to chart → Inputs:
Buy frequency: pick Every N bars, Weekly, or Monthly.
Start time: date from which buys may begin.
Buy amount: fixed cash per planned buy.
Fees % and Fee on top? to match your broker/exchange model.
(Optional) Enable drawdown buy, set threshold %, multiplier, and cooldown.
Toggle Show buy labels and Show stats table.
2. Alerts (recommended):
Use “DCA Plan Buy (Bar Close)” and/or “DCA Drawdown Buy (Bar Close)” with Once per bar close.
If you need early signals, enable Intrabar pre-alerts and add the two Intrabar Preview alerts with Once per bar.
3. Interpretation:
The yellow line is your average price.
Green/orange markers show plan buys and drawdown buys.
The table summarizes total trades, invested capital, quantity, average price, current equity, and P\&L.
Practical notes
All executions occur at bar close by default to avoid intrabar repainting.
Weekly/monthly roll depends on the symbol’s exchange calendar.
Backtest realism: no slippage, no partial fills. Fees are modeled as configured.
If you buy very frequently, consider higher “N” or weekly/monthly to keep fees under control.
If you want, I can tailor the defaults (amount, fee model, drawdown rules) to your typical markets and timeframes.
Disclaimer
No indicator guarantees profits. DCA Anchor (Weekly/Monthly/N Bars) is a decision aid; always combine with solid risk management and your own judgment. Backtest, forward test, and size responsibly.
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Enhance your trading precision and confidence 🚀
Best regards
Chervolino
DAILY WYCKOFF ATMWyckoff Confidence Dashboard
A clean, mobile-optimized Wyckoff phase and alignment dashboard built for serious traders.
This tool dynamically detects Accumulation, Distribution, Markup, and Markdown across multiple timeframes (1H/15M) and scores confidence based on:
• HTF trend direction
• Liquidity sweeps
• Fair Value Gap (FVG) presence
• Volume/OBV confirmation
• Multi-timeframe phase/action alignment
Includes smart alerts and a lightweight dashboard interface — no clutter, just actionable structure-based insight.
Great for SMC, Wyckoff, or price-action traders seeking high-confluence entries.
Simplified VMCSimplified VuManChu B — TanTechTrades™
This script is a streamlined version of the popular VuManChu WaveTrend + Divergence indicator. It focuses on the core logic of WaveTrend crosses, divergences, and golden buy signals while keeping visuals clean and lightweight.
🔹 Features
WaveTrend (WT) Oscillator with customizable lengths
Overbought / oversold levels with optional deep oversold threshold
Bullish & Bearish Divergences detected automatically (plotted as circles)
Golden Buy Circles (special oversold + RSI confluence signals)
Buy & Sell crossover circles for WT1 / WT2
Alerts for divergence and golden buy signals
Dark background option for clear contrast
🔹 How It Works
Bullish Divergence: Price makes a lower low, WT makes a higher low
Bearish Divergence: Price makes a higher high, WT makes a lower high
Golden Circle: Oversold bullish divergence + RSI confirmation
Plots crossover signals to highlight potential trend reversals
This version removes unnecessary extras from the original VuManChu script, making it lighter, faster, and focused only on the most powerful signals.
⚠️ Disclaimer: For educational purposes only. Not financial advice.
Custom TP/SL Levels (1%, 2%, 3%)Custom TP/SL Levels (1%, 2%, 3%) — TanTechTrades™
This indicator automatically plots percentage-based take-profit (TP) and stop-loss (SL) levels around the current price, making it easy to visualize risk/reward scenarios for both long and short trades.
🔹 Features
Three configurable TP/SL levels (default: 1%, 2%, 3%)
Separate plotting for long (green = TP, red = SL) and short (blue = TP, purple = SL) setups
Adjustable percentages for flexible strategy testing
Simple visual overlay to assist with trade planning and management
🔹 How It Works
Long setup: SL lines plotted below entry, TP lines above entry
Short setup: SL lines plotted above entry, TP lines below entry
All levels update dynamically as price moves
This tool is useful for traders who want a quick, no-fuss way to manage position exits and visualize multiple TP/SL levels directly on the chart.
⚠️ Disclaimer: For educational purposes only. Not financial advice.
SSL CHANNEL 2.0SSL Channel + Braid Filter + MFI Alerts (TanTechTrades™)
This indicator combines three confirmation tools — SSL Channel, Braid Filter, and Money Flow Index (MFI) — to generate precise buy/sell alerts.
🔹 Features
SSL Channel: Trend direction based on moving averages of highs and lows
Braid Filter: Confirms trend strength via EMA separation and volatility filter
MFI: Volume-adjusted momentum for validation of long/short entries
Alerts for both long and short signals
Background coloring for visual Braid Filter confirmation
Signal markers on the chart (BUY/SELL labels + colored circles)
🔹 How It Works
Long Signal: SSL bullish crossover + Braid Filter green + MFI above threshold
Short Signal: SSL bearish crossunder + Braid Filter red + MFI below threshold
Plots dynamic trend lines and color-coded backgrounds to reinforce signals visually
This multi-indicator system helps reduce false signals by requiring trend, momentum, and volume confirmation before entries.
⚠️ Disclaimer: Educational purposes only. Not financial advice.
ATR Bands with SL and TPATR Bands with SL and TP (TanTechTrades™)
This indicator uses the Average True Range (ATR) to dynamically calculate stop-loss and take-profit levels around the current price.
🔹 Features
Adjustable ATR period for volatility sensitivity
Separate multipliers for stop-loss and take-profit
Plots long/short SL and TP levels simultaneously
Color-coded bands for quick visual reference (orange = SL, blue = TP)
🔹 How to Use
For long positions: SL is plotted below price, TP above price.
For short positions: SL is plotted above price, TP below price.
The wider the ATR, the further the levels adjust, reflecting higher volatility.
This tool helps traders set volatility-based exits instead of fixed pip/point levels, making risk management more adaptive to market conditions.
⚠️ Disclaimer: For educational purposes only. Not financial advice.
VWAP + Bollinger Bands VWAP + Bollinger Bands (TanTechTrades™)
This indicator combines VWAP (Volume Weighted Average Price) with Bollinger Bands to provide a hybrid view of price action, volume, and volatility.
🔹 VWAP Features
Customizable anchor period (Session, Week, Month, Quarter, Year, etc.)
Option to hide VWAP automatically on daily or higher timeframes
Up to 3 configurable VWAP bands with multipliers
Bands can be calculated using Standard Deviation or Percentage
🔹 Bollinger Bands Features
Adjustable period length and source
Multiple moving average types (SMA, EMA, RMA, WMA, VWMA)
Customizable standard deviation multiplier
Configurable offset for advanced alignment
🔹 Visuals
Central VWAP line with optional surrounding bands
Bollinger Bands with customizable fills
Color-coded regions to highlight volatility expansions and contractions
This tool is designed for traders who want to see how VWAP reacts alongside volatility envelopes, making it easier to identify areas of liquidity, support/resistance, and potential breakouts or reversals.
⚠️ Disclaimer: This script is for educational purposes only. It is not financial advice.
Statistical Mapping [Version 3]Edit Statistical Mapping (ESM) is a statistical technique used mainly in data validation, error detection, and imputation. It’s often applied in official statistics and large surveys. The method works by:
Defining a set of edits (logical or mathematical rules) that data records must satisfy.
Example: Income ≥ 0, Age ≥ 15 if Employment Status = “Employed”.
Identifying inconsistencies in the data when these edits are violated.
Using statistical mapping to correct or impute missing/inconsistent values based on relationships in the dataset.
Ensuring coherence of microdata so that it aligns with macro-level aggregates.
Supporting survey data cleaning, census editing, and economic statistics preparation.
It’s particularly important for official statistics agencies because data collected from respondents often contains errors, missing entries, or contradictions. ESM ensures that the final dataset is internally consistent, reliable, and ready for analysis.
Machine Learning : Neural Network Prediction -EasyNeuro-Machine Learning: Neural Network Prediction
— An indicator that learns and predicts price movements using a neural network —
Overview
The indicator “Machine Learning: Neural Network Prediction” uses price data from the chart and applies a three-layer Feedforward Neural Network (FNN) to estimate future price movements.
Key Features
Normally, training and inference with neural networks require advanced programming languages that support machine learning frameworks (such as TensorFlow or PyTorch) as well as high-performance hardware with GPUs. However, this indicator independently implements the neural network mechanism within TradingView’s Pine Script environment, enabling real-time training and prediction directly on the chart.
Since Pine Script does not support matrix operations, the backpropagation algorithm—necessary for neural network training—has been implemented entirely through scalar operations. This unique approach makes the creation of such a groundbreaking indicator possible.
Significance of Neural Networks
Neural networks are a core machine learning method, forming the foundation of today’s widely used generative AI systems, such as OpenAI’s GPT and Google’s Gemini. The feedforward neural network adopted in this indicator is the most classical architecture among neural networks. One key advantage of neural networks is their ability to perform nonlinear predictions.
All conventional indicators—such as moving averages and oscillators like RSI—are essentially linear predictors. Linear prediction inherently lags behind past price fluctuations. In contrast, nonlinear prediction makes it theoretically possible to dynamically anticipate future price movements based on past patterns. This offers a significant benefit for using neural networks as prediction tools among the multitude of available indicators.
Moreover, neural networks excel at pattern recognition. Since technical analysis is largely based on recognizing market patterns, this makes neural networks a highly compatible approach.
Structure of the Indicator
This indicator is based on a three-layer feedforward neural network (FNN). Every time a new candlestick forms, the model samples random past data and performs online learning using stochastic gradient descent (SGD).
SGD is known as a more versatile learning method compared to standard gradient descent, particularly effective for uncertain datasets like financial market price data. Considering Pine Script’s computational constraints, SGD is a practical choice since it can learn effectively from small amounts of data. Because online learning is performed with each new candlestick, the indicator becomes a little “smarter” over time.
Adjustable Parameters
Learning Rate
Specifies how much the network’s parameters are updated per training step. Values between 0.0001 and 0.001 are recommended. Too high causes divergence and unstable predictions, while too low prevents sufficient learning.
Iterations per Online Learning Step
Specifies how many training iterations occur with each new candlestick. More iterations improve accuracy but may cause timeouts if excessive.
Seed
Random seed for initializing parameters. Changing the seed may alter performance.
Architecture Settings
Number of nodes in input and hidden layers:
Increasing input layer nodes allows predictions based on longer historical periods. Increasing hidden layer nodes increases the network’s interpretive capacity, enabling more flexible nonlinear predictions. However, more nodes increase computational cost exponentially, risking timeouts and overfitting.
Hidden layer activation function (ReLU / Sigmoid / Tanh):
Sigmoid:
Classical function, outputs between 0–1, approximates a normal distribution.
Tanh:
Similar to Sigmoid but outputs between -1 and 1, centered around 0, often more accurate.
ReLU:
Simple function (outputs input if ≥ 0, else 0), efficient and widely effective.
Input Features (selectable and combinable)
RoC (Rate of Change):
Measures relative price change over a period. Useful for predicting movement direction.
RSI (Relative Strength Index):
Oscillator showing how much price has risen/fallen within a period. Widely used to anticipate direction and momentum.
Stdev (Standard Deviation, volatility):
Measures price variability. Useful for volatility prediction, though not directional.
Optionally, input data can be smoothed to stabilize predictions.
Other Parameters
Data Sampling Window:
Period from which random samples are drawn for SGD.
Prediction Smoothing Period:
Smooths predictions to reduce spikes, especially when RoC is used.
Prediction MA Period:
Moving average applied to smoothed predictions.
Visualization Features
The internal state of the neural network is displayed in a table at the upper-right of the chart:
Network architecture:
Displays the structure of input, hidden, and output layers.
Node activations:
Shows how input, hidden, and output node values dynamically change with market conditions.
This design allows traders to intuitively understand the inner workings of the neural network, which is often treated as a black box.
Glossary of Terms
Feature:
Input variables fed to the model (RoC/RSI/Stdev).
Node/Unit:
Smallest computational element in a layer.
Activation Function:
Nonlinear function applied to node outputs (ReLU/Sigmoid/Tanh).
MSE (Mean Squared Error):
Loss function using average squared errors.
Gradient Descent (GD/SGD):
Optimization method that gradually adjusts weights in the direction that reduces loss.
Online Learning:
Training method where the model updates sequentially with each new data point.
Smart Money Price Action ProSmart Money Price Action Pro - Smart Money and Price Action Dynamic Toolkit
The Smart Money Price Action Pro is designed to bring together multiple layers of market analysis into a single, cohesive framework, combining trend identification and consolidation detection in an actionable format. While individual indicators can provide useful insights, they often work in isolation. This toolkit integrates market flow detection, range analytics, and adaptive visualization into one system, allowing traders to see the bigger picture without piecing together multiple disconnected tools.
Building on principles from institutional trading behaviors, the toolkit gives traders a clearer picture of where “smart money” may be entering or exiting the market. Its design emphasizes confluence: signals from multiple independent modules overlap to create higher conviction setups, offering a structured edge when planning entries, exits, and risk levels.
At its core, the toolkit addresses the duality of market conditions: trending versus ranging. By offering a combination of trend-following signals and contrarian insights, it helps traders operate with a deeper understanding of market structure. While it provides actionable signals and visual guidance, it is intended as an assistive system, helping traders make more informed decisions rather than serving as a single source of truth.
Key Modules
1. Smart Money Signal Module
The Smart Money Signal Module identifies potential institutional activity by analyzing price swings and momentum shifts. Using configurable swing detection, it highlights potential reversal or continuation zones, expressed as adaptive zones around key market levels.
Signals are augmented with trend-colored candle overlays, offering immediate guidance on market bias. Bullish and bearish zones are clearly marked, while continuation and reversal markers help distinguish between trend shifts and market noise.
At its core, the engine applies swing detection combined with a sensitivity filter to track directional momentum across recent bars. This allows it to pinpoint bullish pivots (where downside momentum fades and strength returns) and bearish pivots (where upside momentum collapses). Once a pivot is confirmed, the system draws flow lines that map the breakout and classify it as either continuation or reversal, depending on broader market bias.
Momentum zones are then plotted to show areas where buyers stepped in with strength or sellers forced price lower. These levels extend forward dynamically, shifting in real time as new data forms. Zones change color the moment they break, visually confirming whether market structure has held or failed. Gradient shading highlights periods of extreme pressure, giving traders a clear visual of when momentum surges into overbought or oversold territory.
Instead of simply showing trend direction, this module also maps accumulation and distribution zones tied to institutional flows. When combined with the Range Module, these zones become more meaningful — for example, when institutional accumulation aligns with a breakout from consolidation.
Practical Use: Traders can use these signals to align trades with institutional flows. For example, entering a long position near a bullish accumulation zone or managing risk when bearish distribution areas form. By combining these insights with higher timeframe analysis, traders can filter out false signals and improve decision-making.
2. Range Detection Module
The Range Detection engine continuously monitors price action to flag when markets transition into consolidation phases. Ranges are defined not just by flat price action, but by a measurable contraction in volatility, repeated touches of boundary levels, and the clustering of traded volume around a central equilibrium point.
Once a valid range is identified, the system assigns a compression strength score (0–100). This score reflects how cleanly defined and structurally sound the consolidation is—higher scores indicate tighter boundaries and stronger evidence of accumulation or distribution.
Breakout tendencies are modeled dynamically. The system updates a forward-looking bias by incorporating:
Boundary time distribution – how often price presses against upper vs. lower edges
Historical breakout patterns – probability benchmarks derived from structurally similar ranges
Volume skew – whether traded volume leans toward buyers or sellers inside the range
Momentum alignment – auxiliary filters such as slope-based oscillators that indicate when energy is building for a directional move
The result is a live breakout forecast that evolves bar by bar as the range matures. Each active range carries a visual strength meter plotted above the consolidation zone, quantifying both compression and breakout potential in real time.
The module also supports range memory, preserving completed consolidations even after a breakout. This allows traders to review the prior structure for post-analysis or to track whether price respects the boundaries of the old range as support or resistance going forward.
Practical Use : Traders can use these ranges to anticipate breakout direction or step aside when conditions are unclear. A tight consolidation near a bullish zone, for instance, often signals a potential long opportunity, while overlapping bearish flows warn of false breakouts.
Integrated Workflow
The strength of the toolkit lies in its synergy. Each module is effective on its own, but the real advantage comes when their signals align.
A typical workflow may include:
Assessing the market trend using the Smart Money Signal Module and its trend-colored overlays
Identifying consolidation and breakout zones with the Range Detection Module
Watching for confluences: institutional accumulation aligning with range compression, or dashboard bias matching local setups
Executing trades with structured confidence, using these layered confirmations rather than relying on a single trigger
This integrated workflow streamlines decision-making and avoids the conflicting signals that can occur when combining unrelated indicators.
Additional Features
Adaptive Visualization : Dynamic zones and trend overlays adjust to volatility, keeping charts clear and focused
Analytics Dashboard : A compact summary panel shows active zones, bullish vs bearish flow counts, and current bias, giving context at a glance
Instead of simply adding more signals, the dashboard provides a meta-layer of analysis — context, bias, and flow strength — helping traders manage risk and stay aligned with broader market conditions.
Use Cases
Trend Confluence : Entering trades in line with prevailing smart money flows while filtering out counter-trend setups
Breakout Trading : Using the Range Detection Module to anticipate breakout zones and confirming direction with institutional flow signals
Contrarian Reversal Trades : Targeting accumulation/distribution zones where both modules indicate potential reversals
Each use case demonstrates how layered confluence creates clarity and conviction, making the toolkit a strong complement to other forms of technical analysis.
Conclusion
The Smart Money Signals Toolkit simplifies complex market analysis into actionable, visually intuitive insights. While standalone indicators provide value, this toolkit goes further by combining smart money flows, range detection, adaptive zones, and dashboard analytics into one cohesive system.
It doesn’t just generate buy/sell markers — it shows why a setup matters, where it is occurring, and how it aligns with broader conditions. This allows traders to operate with greater clarity, structure, and discipline.
Risk Disclaimer : This toolkit and its features are for educational and informational purposes only. Past performance does not guarantee future results. All suggested use cases are theoretical and should be applied with proper risk management.
Double Median ATR Bands | MisinkoMasterThe Double Median ATR Bands is a version of the SuperTrend that is designed to be smoother, more accurate while maintaining a good speed by combining the HMA smoothing technique and the median source.
How does it work?
Very simple!
1. Get user defined inputs:
=> Set them up however you want, for the result you want!
2. Calculate the Median of the source and the ATR
=> Very simple
3. Smooth the median with √length (for example if median length = 9, it would be smoothed over the length of 3 since 3x3 = 9)
4. Add ATR bands like so:
Upper = median + (atr*multiplier)
Lower = median - (atr*multiplier)
Trend Logic:
Source crossing over the upper band = uptrend
Source crossing below the lower band = downtrend
Enjoy G´s!
Futures Multi-Asset Open Distance Table## Multi-Asset Open Distance Table - Quick Description
This Pine Script indicator displays a **real-time table** that tracks how far **three user-selected assets** are from their key opening price levels.
**What it shows:**
- **Three customizable assets** (default: NQ!, ES!, YM!)
- **Distance from 3 key opens** for each asset:
- **1800 ET Open** (Electronic trading session start)
- **0930 ET Open** (Regular market hours start)
- **Weekly Open** (Beginning of trading week)
**Visual features:**
- **Percentage changes** from each open level
- **Color coding**: Green for gains above opens, red for losses below opens
- **Direction arrows**: ▲ (above), ▼ (below), ■ (unchanged)
- **Customizable table position** and size
**Perfect for:**
- **Intraday traders** monitoring key session levels
- **Multi-timeframe analysis** across different market opens
- **Quick reference** to see which assets are performing relative to major opening levels
- **Session-based trading strategies** using 6PM and 9:30AM opens
The table updates in real-time and provides an at-a-glance view of where your chosen assets stand relative to these critical price reference points throughout the trading day.
