SFC Bollinger Band and Bandit概述 (Overview)
SFC 布林通道與海盜策略 (SFC Bollinger Band and Bandit Strategy) 是一個基於 Pine Script™ v6 的技術分析指標，結合布林通道 (Bollinger Bands)、移動平均線 (Moving Averages) 以及布林海盜 (Bollinger Bandit) 交易策略，旨在為交易者提供多時間框架的趨勢分析與進出場訊號。該腳本支援風險管理功能，並提供視覺化圖表與交易訊號提示，適用於多種金融市場。
This script, written in Pine Script™ v6, combines Bollinger Bands, Moving Averages, and the Bollinger Bandit strategy to provide traders with multi-timeframe trend analysis and entry/exit signals. It includes risk management features and visualizes data through charts and trading signals, suitable for various financial markets.
功能特點 (Key Features)
布林通道 (Bollinger Bands)
提供可調整的標準差參數 (σ1, σ2)，支援多層布林通道顯示。
進場訊號基於價格穿越布林通道上下軌，並結合連續K線確認機制。
Provides adjustable standard deviation parameters (σ1, σ2) for multi-layer Bollinger Bands display.
Entry signals are based on price crossing the upper/lower bands, combined with a consecutive bar confirmation mechanism.
移動平均線 (Moving Averages)
支援簡單移動平均線 (SMA) 或指數移動平均線 (EMA)，可自訂快、中、慢線週期。
Supports Simple Moving Average (SMA) or Exponential Moving Average (EMA) with customizable fast, medium, and slow line periods.
布林海盜策略 (Bollinger Bandit Strategy)
基於變動率 (ROC) 與布林通道動態止損，提供做多與做空訊號。
包含動態止損均線與平倉天數設定，增強交易靈活性。
Utilizes Rate of Change (ROC) and Bollinger Bands with dynamic stop-loss for long and short signals.
Includes dynamic stop-loss moving average and liquidation days for enhanced trading flexibility.
多時間框架分析 (Multi-Timeframe Analysis)
支援六個時間框架 (5分、15分、1小時、4小時、日線、週線) 的趨勢分析。
通過表格顯示各時間框架的連續上漲/下跌趨勢，輔助交易決策。
Supports trend analysis across six timeframes (5m, 15m, 1h, 4h, daily, weekly).
Displays consecutive up/down trends in a table to aid decision-making.
風險管理 (Risk Management)
提供基於 ATR 或布林通道的停利/停損設定。
自動計算交易手數，根據報價貨幣匯率調整風險敞口。
Offers take-profit/stop-loss settings based on ATR or Bollinger Bands.
Automatically calculates trading lots, adjusting risk exposure based on quote currency exchange rates.
視覺化與提示 (Visualization and Alerts)
繪製布林通道、移動平均線、海盜策略動態止損線及交易訊號。
提供多時間框架趨勢表格、交易手數標籤及浮水印。
支援交易訊號快訊，方便即時監控。
Plots Bollinger Bands, Moving Averages, Bandit strategy stop-loss lines, and trading signals.
Includes multi-timeframe trend tables, trading lot labels, and watermark.
Supports alert conditions for real-time trade monitoring.
使用說明 (Usage Instructions)
設置參數 (Parameter Setup)
布林通道 (Bollinger Bands): 可調整週期 (預設21)、標準差 (σ1=1, σ2=2) 及停利/停損依據 (ATR 或 BAND)。
移動平均線 (Moving Averages): 可選擇顯示快線 (10)、中線 (20)、慢線 (60)，並切換 SMA/EMA。
布林海盜 (Bollinger Bandit): 調整通道週期 (50)、平倉均線週期 (50) 及 ROC 週期 (30)。
時間框架 (Timeframes): 自訂六個時間框架，預設為 5分、15分、1小時、4小時、日線、週線。
Adjust Bollinger Band period (default 21), standard deviations (σ1=1, σ2=2), and take-profit/stop-loss basis (ATR or BAND).
Configure Moving Averages (fast=10, medium=20, slow=60) and toggle SMA/EMA.
Set Bollinger Bandit parameters: channel period (50), liquidation MA period (50), ROC period (30).
Customize six timeframes (default: 5m, 15m, 1h, 4h, daily, weekly).
交易訊號 (Trading Signals)
買入訊號 (Buy): 價格穿越下軌且滿足連續K線條件。
賣出訊號 (Sell): 價格穿越上軌且滿足連續K線條件。
海盜策略訊號: 基於 ROC 與布林通道穿越，結合動態止損。
Buy signal: Price crosses below lower band with consecutive bar confirmation.
Sell signal: Price crosses above upper band with consecutive bar confirmation.
Bandit strategy signals: Based on ROC and band crossings with dynamic stop-loss.
視覺化 (Visualization)
布林通道以不同顏色顯示上下軌與中軌。
移動平均線以快、中、慢線區分顏色。
趨勢表格顯示各時間框架的趨勢狀態 (🔴上漲, 🟢下跌, ⚪中性)。
海盜策略顯示動態止損線與交易狀態。
Bollinger Bands display upper, lower, and middle bands in distinct colors.
Moving Averages use different colors for fast, medium, and slow lines.
Trend table shows timeframe trends (🔴 up, 🟢 down, ⚪ neutral).
Bandit strategy displays dynamic stop-loss and trading status.
In den Scripts nach "roc" suchen
PRO Investing - Apex EnginePRO Investing - Apex Engine
1. Core Concept: Why Does This Indicator Exist?
Traditional momentum oscillators like RSI or Stochastic use a fixed "lookback period" (e.g., 14). This creates a fundamental problem: a 14-period setting that works well in a fast, trending market will generate constant false signals in a slow, choppy market, and vice-versa. The market's character is dynamic, but most tools are static.
The Apex Engine was built to solve this problem. Its primary innovation is a self-optimizing core that continuously adapts to changing market conditions. Instead of relying on one fixed setting, it actively tests three different momentum profiles (Fast, Mid, and Slow) in real-time and selects the one that is most synchronized with the current price action.
This is not just a random combination of indicators; it's a deliberate synthesis designed to create a more robust momentum tool. It combines:
Volatility analysis (ATR) to generate adaptive lookback periods.
Momentum measurement (ROC) to gauge the speed of price changes.
Statistical analysis (Correlation) to validate which momentum measurement is most effective right now.
Classic trend filters (Moving Average, ADX) to ensure signals are only taken in favorable market conditions.
The result is an oscillator that aims to be more responsive in volatile trends and more stable in quiet periods, providing a more intelligent and adaptive signal.
2. How It Works: The Engine's Three-Stage Process
To be transparent, it's important to understand the step-by-step logic the indicator follows on every bar. It's a process of Adapt -> Validate -> Signal.
Stage 1: Adapt (Dynamic Length Calculation)
The engine first measures market volatility using the Average True Range (ATR) relative to its own long-term average. This creates a volatility_factor. In high-volatility environments, this factor causes the base calculation lengths to shorten. In low-volatility, they lengthen. This produces three potential Rate of Change (ROC) lengths: dynamic_fast_len, dynamic_mid_len, and dynamic_slow_len.
Stage 2: Validate (Self-Optimizing Mode Selection)
This is the core of the engine. It calculates the ROC for all three dynamic lengths. To determine which is best, it uses the ta.correlation() function to measure how well each ROC's movement has correlated with the actual bar-to-bar price changes over the "Optimization Lookback" period. The ROC length with the highest correlation score is chosen as the most effective profile for the current moment. This "active" mode is reflected in the oscillator's color and the dashboard.
Stage 3: Signal (Normalized Velocity Oscillator)
The winning ROC series is then normalized into a consistent oscillator (the Velocity line) that ranges from -100 (extreme oversold) to +100 (extreme overbought). This ensures signals are comparable across any asset or timeframe. Signals are only generated when this Velocity line crosses its signal line and the trend filters (explained below) give a green light.
3. How to Use the Indicator: A Practical Guide
Reading the Visuals:
Velocity Line (Blue/Yellow/Pink): The main oscillator line. Its color indicates which mode is active (Fast, Mid, or Slow).
Signal Line (White): A moving average of the Velocity line. Crossovers generate potential signals.
Buy/Sell Triangles (▲ / ▼): These are your primary entry signals. They are intentionally strict and only appear when momentum, trend, and price action align.
Background Color (Green/Red/Gray): This is your trend context.
Green: Bullish trend confirmed (e.g., price above a rising 200 EMA and ADX > 20). Only Buy signals (▲) can appear.
Red: Bearish trend confirmed. Only Sell signals (▼) can appear.
Gray: No clear trend. The market is likely choppy or consolidating. No signals will appear; it is best to stay out.
Trading Strategy Example:
Wait for a colored background. A green or red background indicates the market is in a tradable trend.
Look for a signal. For a green background, wait for a lime Buy triangle (▲) to appear.
Confirm the trade. Before entering, confirm the signal aligns with your own analysis (e.g., support/resistance levels, chart patterns).
Manage the trade. Set a stop-loss according to your risk management rules. An exit can be considered on a fixed target, a trailing stop, or when an opposing signal appears.
4. Settings and Customization
This script is open-source, and its settings are transparent. You are encouraged to understand them.
Synaptic Engine Group:
Volatility Period: The master control for the adaptive engine. Higher values are slower and more stable.
Optimization Lookback: How many bars to use for the correlation check.
Switch Sensitivity: A buffer to prevent frantic switching between modes.
Advanced Configuration & Filters Group:
Price Source: The data source for momentum calculation (default close).
Trend Filter MA Type & Length: Define your long-term trend.
Filter by MA Slope: A key feature. If ON, allows for "buy the dip" entries below a rising MA. If OFF, it's stricter, requiring price to be above the MA.
ADX Length & Threshold: Filters out non-trending, choppy markets. Signals will not fire if the ADX is below this threshold.
5. Important Disclaimer
This indicator is a decision-support tool for discretionary traders, not an automated trading system or financial advice. Past performance is not indicative of future results. All trading involves substantial risk. You should always use proper risk management, including setting stop-losses, and never risk more than you are prepared to lose. The signals generated by this script should be used as one component of a broader trading plan.
Money Flow Pulse💸 In markets where volatility is cheap and structure is noisy, what matters most isn’t just the move — it’s the effort behind it. Money Flow Pulse (MFP) offers a compact, color-coded readout of real-time conviction by scoring volume-weighted price action on a five-tier scale. It doesn’t try to predict reversals or validate trends. Instead, it reveals the quality of the move in progress: is it fading , driving , exhausting , or hollow ?
🎨 MFP draws from the traditional Money Flow Index (MFI), a volume-enhanced momentum oscillator, but transforms it into a modular “pressure readout” that fits seamlessly into any structural overlay. Rather than oscillating between extremes with little interpretive guidance, MFP discretizes the flow into clean, color-coded regimes ranging from strong inflow (+2) to strong outflow (–2). The result is a responsive diagnostic layer that complements, rather than competes with, tools like ATR and/or On-Balance Volume.
5️⃣ MFP uses a normalized MFI value smoothed over 13 periods and classified into a 5-tier readout of Volume-Driven Conviction :
🍆 Exhaustion Inflow — usually a top or blowoff; not strength, but overdrive (+2)
🥝 Active Inflow — supportive of trend continuation (+1)
🍋 Neutral — chop, coil, or fakeouts (0)
🍑 Selling Intent — weakening structure, possible fade setups (-1)
🍆 Exhaustion Outflow — often signals forced selling or accumulation traps (-2)
🎭 These tiers are not arbitrary. Each one is tuned to reflect real capital behavior across timeframes. For instance, while +1 may support continuation, +2 often precedes exhaustion — especially on the lower timeframes. Similarly, a –1 reading during a pullback suggests sell-side pressure is building, but a shift to –2 may mean capitulation is already underway. The difference between the two can define whether a move is tradable continuation or strategic exhaustion .
🌊 The MFI ROC (Rate of Change) feature can be toggled to become a volatility-aware pulse monitor beneath the derived MFI tier. Instead of scoring direction or structure, ROC reveals how fast conviction is changing — not just where it’s headed, but how hard it's accelerating or decaying. It measures the raw Δ between the current and previous MFI values, exposing bursts of energy, fading pressure, or transitional churn .
🎢 Visually, ROC appears as a low-opacity area fill, anchored to a shared lemon-yellow zero line. When the green swell rises, buying pressure is accelerating; when the red drops, flow is actively deteriorating. A subtle bump may signal early interest — while a steep wave hints at an emotional overreaction. The ROC value itself provides numeric insight alongside the raw MFI score. A reading of +3.50 implies strong upside momentum in the flow — often supporting trend ignition. A score of –6.00 suggests rapid deceleration or full exhaustion — often preceding reversals or failed breakouts.
・ MFI shows you where the flow is
・ ROC tells you how it’s behaving
😎 This blend reveals not just structure or intent — but also urgency . And in flow-based trading, urgency often precedes outcome.
🧩 Divergence isn’t delay — it’s disagreement . One of the most revealing features of MFP is how it exposes momentum dissonance — situations where price and flow part ways. These divergences often front-run pivots , traps , or velocity stalls . Unlike RSI-style divergence, which whispers of exhaustion, MFI divergence signals a breakdown in conviction. The structure may extend — but the effort isn’t there.
・ Price ▲ MFI ▼ → Effortless Markup : Often signals distribution or a grind into liquidity. Without rising MFI, the rally lacks true flow participation — a warning of fragility.
・ Price ▼ MFI ▲ → Absorption or Early Accumulation : Price breaks down, but money keeps flowing in — a hidden bid. Watch for MFI tier shifts or ROC bursts to confirm a reversal.
🏄♂️ These moments don’t require signal overlays or setup hunting. MFP narrates the imbalance. When price breaks structure but flow does not — or vice versa — you’re not seeing trend, you’re seeing disagreement, and that's where edge begins.
💤 MFP is especially effective on intraday charts where volume dislocations matter most. On the 1H or 15m chart, it helps distinguish between breakouts with conviction versus those lacking flow. On higher timeframes, its resolution softens — it becomes more of a drift indicator than a trigger device. That’s by design: MFP prioritizes pulse, not position. It’s not the fire, it’s the heat.
📎 Use MFP in confluence with structural overlays to validate price behavior. A ribbon expansion with rising MFP is real. A compression breakout without +1 flow is "fishy". Watch how MFP behaves near key zones like anchored VWAP, MAs or accumulation pivots. When MFP rises into a +2 and fails to sustain, the reversal isn’t just technical — it’s flow-based.
🪟 MFP doesn’t speak loudly, but it never whispers without reason. It’s the pulse check before action — the breath of the move before the breakout. While it stays visually minimal on the chart, the true power is in the often overlooked Data Window, where traders can read and interpret the score in real time. Once internalized, these values give structure-aware traders a framework for conviction, continuation, or caution.
🛜 MFP doesn’t chase momentum — it confirms conviction. And in markets defined by noise, that signal isn’t just helpful — it’s foundational.
Fuzzy SMA Trend Analyzer (experimental)[FibonacciFlux]Fuzzy SMA Trend Analyzer (Normalized): Advanced Market Trend Detection Using Fuzzy Logic Theory
Elevate your technical analysis with institutional-grade fuzzy logic implementation
Research Genesis & Conceptual Framework
This indicator represents the culmination of extensive research into applying fuzzy logic theory to financial markets. While traditional technical indicators often produce binary outcomes, market conditions exist on a continuous spectrum. The Fuzzy SMA Trend Analyzer addresses this limitation by implementing a sophisticated fuzzy logic system that captures the nuanced, multi-dimensional nature of market trends.
Core Fuzzy Logic Principles
At the heart of this indicator lies fuzzy logic theory - a mathematical framework designed to handle imprecision and uncertainty:
// Improved fuzzy_triangle function with guard clauses for NA and invalid parameters.
fuzzy_triangle(val, left, center, right) =>
if na(val) or na(left) or na(center) or na(right) or left > center or center > right // Guard checks
0.0
else if left == center and center == right // Crisp set (single point)
val == center ? 1.0 : 0.0
else if left == center // Left-shoulder shape (ramp down from 1 at center to 0 at right)
val >= right ? 0.0 : val <= center ? 1.0 : (right - val) / (right - center)
else if center == right // Right-shoulder shape (ramp up from 0 at left to 1 at center)
val <= left ? 0.0 : val >= center ? 1.0 : (val - left) / (center - left)
else // Standard triangle
math.max(0.0, math.min((val - left) / (center - left), (right - val) / (right - center)))
This implementation of triangular membership functions enables the indicator to transform crisp numerical values into degrees of membership in linguistic variables like "Large Positive" or "Small Negative," creating a more nuanced representation of market conditions.
Dynamic Percentile Normalization
A critical innovation in this indicator is the implementation of percentile-based normalization for SMA deviation:
// ----- Deviation Scale Estimation using Percentile -----
// Calculate the percentile rank of the *absolute* deviation over the lookback period.
// This gives an estimate of the 'typical maximum' deviation magnitude recently.
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
// ----- Normalize the Raw Deviation -----
// Divide the raw deviation by the estimated 'typical max' magnitude.
normalized_diff = raw_diff / diff_abs_percentile
// ----- Clamp the Normalized Deviation -----
normalized_diff_clamped = math.max(-3.0, math.min(3.0, normalized_diff))
This percentile normalization approach creates a self-adapting system that automatically calibrates to different assets and market regimes. Rather than using fixed thresholds, the indicator dynamically adjusts based on recent volatility patterns, significantly enhancing signal quality across diverse market environments.
Multi-Factor Fuzzy Rule System
The indicator implements a comprehensive fuzzy rule system that evaluates multiple technical factors:
SMA Deviation (Normalized): Measures price displacement from the Simple Moving Average
Rate of Change (ROC): Captures price momentum over a specified period
Relative Strength Index (RSI): Assesses overbought/oversold conditions
These factors are processed through a sophisticated fuzzy inference system with linguistic variables:
// ----- 3.1 Fuzzy Sets for Normalized Deviation -----
diffN_LP := fuzzy_triangle(normalized_diff_clamped, 0.7, 1.5, 3.0) // Large Positive (around/above percentile)
diffN_SP := fuzzy_triangle(normalized_diff_clamped, 0.1, 0.5, 0.9) // Small Positive
diffN_NZ := fuzzy_triangle(normalized_diff_clamped, -0.2, 0.0, 0.2) // Near Zero
diffN_SN := fuzzy_triangle(normalized_diff_clamped, -0.9, -0.5, -0.1) // Small Negative
diffN_LN := fuzzy_triangle(normalized_diff_clamped, -3.0, -1.5, -0.7) // Large Negative (around/below percentile)
// ----- 3.2 Fuzzy Sets for ROC -----
roc_HN := fuzzy_triangle(roc_val, -8.0, -5.0, -2.0)
roc_WN := fuzzy_triangle(roc_val, -3.0, -1.0, -0.1)
roc_NZ := fuzzy_triangle(roc_val, -0.3, 0.0, 0.3)
roc_WP := fuzzy_triangle(roc_val, 0.1, 1.0, 3.0)
roc_HP := fuzzy_triangle(roc_val, 2.0, 5.0, 8.0)
// ----- 3.3 Fuzzy Sets for RSI -----
rsi_L := fuzzy_triangle(rsi_val, 0.0, 25.0, 40.0)
rsi_M := fuzzy_triangle(rsi_val, 35.0, 50.0, 65.0)
rsi_H := fuzzy_triangle(rsi_val, 60.0, 75.0, 100.0)
Advanced Fuzzy Inference Rules
The indicator employs a comprehensive set of fuzzy rules that encode expert knowledge about market behavior:
// --- Fuzzy Rules using Normalized Deviation (diffN_*) ---
cond1 = math.min(diffN_LP, roc_HP, math.max(rsi_M, rsi_H)) // Strong Bullish: Large pos dev, strong pos roc, rsi ok
strength_SB := math.max(strength_SB, cond1)
cond2 = math.min(diffN_SP, roc_WP, rsi_M) // Weak Bullish: Small pos dev, weak pos roc, rsi mid
strength_WB := math.max(strength_WB, cond2)
cond3 = math.min(diffN_SP, roc_NZ, rsi_H) // Weakening Bullish: Small pos dev, flat roc, rsi high
strength_N := math.max(strength_N, cond3 * 0.6) // More neutral
strength_WB := math.max(strength_WB, cond3 * 0.2) // Less weak bullish
This rule system evaluates multiple conditions simultaneously, weighting them by their degree of membership to produce a comprehensive trend assessment. The rules are designed to identify various market conditions including strong trends, weakening trends, potential reversals, and neutral consolidations.
Defuzzification Process
The final step transforms the fuzzy result back into a crisp numerical value representing the overall trend strength:
// --- Step 6: Defuzzification ---
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10 // Use small epsilon instead of != 0.0 for float comparison
fuzzyTrendScore := (strength_SB * STRONG_BULL +
strength_WB * WEAK_BULL +
strength_N * NEUTRAL +
strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1 (strong bearish) to +1 (strong bullish), providing a smooth, continuous evaluation of market conditions that avoids the abrupt signal changes common in traditional indicators.
Advanced Visualization with Rainbow Gradient
The indicator incorporates sophisticated visualization using a rainbow gradient coloring system:
// Normalize score to for gradient function
normalizedScore = na(fuzzyTrendScore) ? 0.5 : math.max(0.0, math.min(1.0, (fuzzyTrendScore + 1) / 2))
// Get the color based on gradient setting and normalized score
final_color = get_gradient(normalizedScore, gradient_type)
This color-coding system provides intuitive visual feedback, with color intensity reflecting trend strength and direction. The gradient can be customized between Red-to-Green or Red-to-Blue configurations based on user preference.
Practical Applications
The Fuzzy SMA Trend Analyzer excels in several key applications:
Trend Identification: Precisely identifies market trend direction and strength with nuanced gradation
Market Regime Detection: Distinguishes between trending markets and consolidation phases
Divergence Analysis: Highlights potential reversals when price action and fuzzy trend score diverge
Filter for Trading Systems: Provides high-quality trend filtering for other trading strategies
Risk Management: Offers early warning of potential trend weakening or reversal
Parameter Customization
The indicator offers extensive customization options:
SMA Length: Adjusts the baseline moving average period
ROC Length: Controls momentum sensitivity
RSI Length: Configures overbought/oversold sensitivity
Normalization Lookback: Determines the adaptive calculation window for percentile normalization
Percentile Rank: Sets the statistical threshold for deviation normalization
Gradient Type: Selects the preferred color scheme for visualization
These parameters enable fine-tuning to specific market conditions, trading styles, and timeframes.
Acknowledgments
The rainbow gradient visualization component draws inspiration from LuxAlgo's "Rainbow Adaptive RSI" (used under CC BY-NC-SA 4.0 license). This implementation of fuzzy logic in technical analysis builds upon Fermi estimation principles to overcome the inherent limitations of crisp binary indicators.
This indicator is shared under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Remember that past performance does not guarantee future results. Always conduct thorough testing before implementing any technical indicator in live trading.
Crypto Divergence from BTCThis script is used to indicate when price action of a crypto coin is diverging significantly from that of BTC.
Explanation of the Script:
Inputs:
roc_length: The period used for calculating the Rate of Change.
ma_length: The period used for the moving average of the ROC.
threshold: The percentage difference that indicates a divergence.
Price Data:
The script retrieves the current asset's price and Bitcoin's price.
ROC Calculation:
The ROC for both the current asset and BTC is calculated based on the defined roc_length.
Moving Averages:
Simple moving averages (SMA) of the ROC values are calculated to smooth out the data.
Divergence Detection:
The indicator checks if the current asset's ROC MA is significantly higher or lower than Bitcoin's ROC MA based on the specified threshold.
Plotting:
The script plots the ROC values and their moving averages.
It also highlights the background in green when a bullish divergence is detected (when the asset is moving up while BTC is lagging) and in red for a bearish divergence.
Leading Indicator by Parag RautBreakdown of the Leading Indicator:
Linear Regression (LRC):
A linear regression line is used to estimate the current trend direction. When the price is above or below the regression line, it indicates whether the price is deviating from its mean, signaling potential reversals.
Rate of Change (ROC):
ROC measures the momentum of the price over a set period. By using thresholds (positive or negative), we predict that the price will continue in the same direction if momentum is strong enough.
Leading Indicator Calculation:
We calculate the difference between the price and the linear regression line. This is normalized using the standard deviation of price over the same period, giving us a leading signal based on price divergence from the mean trend.
The leading indicator is used to forecast changes in price behavior by identifying when the price is either stretched too far from the mean (indicating a potential reversal) or showing strong momentum in a particular direction (predicting trend continuation).
Buy and Sell Signals:
Buy Signal: Generated when ROC is above a threshold and the leading indicator shows the price is above the regression line.
Sell Signal: Generated when ROC is below a negative threshold and the leading indicator shows the price is below the regression line.
Visual Representation:
The indicator oscillates around zero. Values above zero signal potential upward price movements, while values below zero signal potential downward movements.
Background colors highlight potential buy (green) and sell (red) areas based on our conditions.
How It Works as a Leading Indicator:
This indicator attempts to predict price movements before they happen by combining the trend (via linear regression) and momentum (via ROC).
When the price significantly diverges from the trendline and momentum supports a continuation, it signals a potential entry point (either buy or sell).
It is leading in that it anticipates price movement before it becomes fully apparent in the market.
Next Steps:
You can adjust the length of the linear regression and ROC to fine-tune the indicator’s sensitivity to your trading style.
This can be combined with other indicators or used as part of a larger strategy
Moving Average Ratio [InvestorUnknown]Overview
The "Moving Average Ratio" (MAR) indicator is a versatile tool designed for valuation, mean-reversion, and long-term trend analysis. This indicator provides multiple display modes to cater to different analytical needs, allowing traders and investors to gain deeper insights into the market dynamics.
Features
1. Moving Average Ratio (MAR):
Calculates the ratio of the chosen source (close, open, ohlc4, hl2 …) to a longer-term moving average of choice (SMA, EMA, HMA, WMA, DEMA)
Useful for identifying overbought or oversold conditions, aiding in mean-reversion strategies and valuation of assets.
For some high beta asset classes, like cryptocurrencies, you might want to use logarithmic scale for the raw MAR, below you can see the visual difference of using Linear and Logarithmic scale on BTC
2. MAR Z-Score:
Computes the Z-Score of the MAR to standardize the ratio over chosen time period, making it easier to identify extreme values relative to the historical mean.
Helps in detecting significant deviations from the mean, which can indicate potential reversal points and buying/selling opportunities
3. MAR Trend Analysis:
Uses a combination of short-term (default 1, raw MAR) and long-term moving averages of the MAR to identify trend changes.
Provides a visual representation of bullish and bearish trends based on moving average crossings.
Using Logarithmic scale can improve the visuals for some asset classes.
4. MAR Momentum:
Measures the momentum of the MAR by calculating the difference over a specified period.
Useful for detecting changes in the market momentum and potential trend reversals.
5. MAR Rate of Change (ROC):
Calculates the rate of change of the MAR to assess the speed and direction of price movements.
Helps in identifying accelerating or decelerating trends.
MAR Momentum and Rate of Change are very similar, the only difference is that the Momentum is expressed in units of the MAR change and ROC is expressed as % change of MAR over chosen time period.
Customizable Settings
General Settings:
Display Mode: Select the display mode from MAR, MAR Z-Score, MAR Trend, MAR Momentum, or MAR ROC.
Color Bars: Option to color the bars based on the current display mode.
Wait for Bar Close: Toggle to wait for the bar to close before updating the MAR value.
MAR Settings:
Length: Period for the moving average calculation.
Source: Data source for the moving average calculation.
Moving Average Type: Select the type of moving average (SMA, EMA, WMA, HMA, DEMA).
Z-Score Settings:
Z-Score Length: Period for the Z-Score calculation.
Trend Analysis Settings:
Moving Average Type: Select the type of moving average for trend analysis (SMA, EMA).
Longer Moving Average: Period for the longer moving average.
Shorter Moving Average: Period for the shorter moving average.
Momentum Settings:
Momentum Length: Period for the momentum calculation.
Rate of Change Settings:
ROC Length: Period for the rate of change calculation.
Calculation and Plotting
Moving Average Ratio (MAR):
Calculates the ratio of the price to the selected moving average type and length.
Plots the MAR with a gradient color based on its Z-Score, aiding in visual identification of extreme values.
// Moving Average Ratio (MAR)
ma_main = switch ma_main_type
"SMA" => ta.sma(src, len)
"EMA" => ta.ema(src, len)
"WMA" => ta.wma(src, len)
"HMA" => ta.hma(src, len)
"DEMA" => ta.dema(src, len)
mar = (waitforclose ? src : src) / ma_main
z_col = color.from_gradient(z, -2.5, 2.5, color.green, color.red)
plot(disp_mode.mar ? mar : na, color = z_col, histbase = 1, style = plot.style_columns)
barcolor(color_bars ? (disp_mode.mar ? (z_col) : na) : na)
MAR Z-Score:
Computes the Z-Score of the MAR and plots it with a color gradient indicating the magnitude of deviation from the mean.
// MAR Z-Score
mean = ta.sma(math.log(mar), z_len)
stdev = ta.stdev(math.log(mar),z_len)
z = (math.log(mar) - mean) / stdev
plot(disp_mode.mar_z ? z : na, color = z_col, histbase = 0, style = plot.style_columns)
plot(disp_mode.mar_z ? 1 : na, color = color.new(color.red,70))
plot(disp_mode.mar_z ? 2 : na, color = color.new(color.red,50))
plot(disp_mode.mar_z ? 3 : na, color = color.new(color.red,30))
plot(disp_mode.mar_z ? -1 : na, color = color.new(color.green,70))
plot(disp_mode.mar_z ? -2 : na, color = color.new(color.green,50))
plot(disp_mode.mar_z ? -3 : na, color = color.new(color.green,30))
barcolor(color_bars ? (disp_mode.mar_z ? (z_col) : na) : na)
MAR Trend:
Plots the MAR along with its short-term and long-term moving averages.
Uses color changes to indicate bullish or bearish trends based on moving average crossings.
// MAR Trend - Moving Average Crossing
mar_ma_long = switch ma_trend_type
"SMA" => ta.sma(mar, len_trend_long)
"EMA" => ta.ema(mar, len_trend_long)
mar_ma_short = switch ma_trend_type
"SMA" => ta.sma(mar, len_trend_short)
"EMA" => ta.ema(mar, len_trend_short)
plot(disp_mode.mar_t ? mar : na, color = mar_ma_long < mar_ma_short ? color.new(color.green,50) : color.new(color.red,50), histbase = 1, style = plot.style_columns)
plot(disp_mode.mar_t ? mar_ma_long : na, color = mar_ma_long < mar_ma_short ? color.green : color.red, linewidth = 4)
plot(disp_mode.mar_t ? mar_ma_short : na, color = mar_ma_long < mar_ma_short ? color.green : color.red, linewidth = 2)
barcolor(color_bars ? (disp_mode.mar_t ? (mar_ma_long < mar_ma_short ? color.green : color.red) : na) : na)
MAR Momentum:
Plots the momentum of the MAR, coloring the bars to indicate increasing or decreasing momentum.
// MAR Momentum
mar_mom = mar - mar
// MAR Momentum
mom_col = mar_mom > 0 ? (mar_mom > mar_mom ? color.new(color.green,0): color.new(color.green,30)) : (mar_mom < mar_mom ? color.new(color.red,0): color.new(color.red,30))
plot(disp_mode.mar_m ? mar_mom : na, color = mom_col, histbase = 0, style = plot.style_columns)
MAR Rate of Change (ROC):
Plots the ROC of the MAR, using color changes to show the direction and strength of the rate of change.
// MAR Rate of Change
mar_roc = ta.roc(mar,len_roc)
// MAR ROC
roc_col = mar_roc > 0 ? (mar_roc > mar_roc ? color.new(color.green,0): color.new(color.green,30)) : (mar_roc < mar_roc ? color.new(color.red,0): color.new(color.red,30))
plot(disp_mode.mar_r ? mar_roc : na, color = roc_col, histbase = 0, style = plot.style_columns)
Summary:
This multi-purpose indicator provides a comprehensive toolset for various trading strategies, including valuation, mean-reversion, and trend analysis. By offering multiple display modes and customizable settings, it allows users to tailor the indicator to their specific analytical needs and market conditions.
Non-Sinusoidal Multi-Layered Moving Average OscillatorThis indicator utilizes multiple moving averages (MAs) of different lengths their difference and its rate of change to provide a comprehensive view of both short-term and long-term market trends. The output signal is characterized by its non-sinusoidal nature, offering distinct advantages in trend analysis and market forecasting.
Combining the difference between two moving averages with the ROC allows to assess not only the direction and strength of the trend but also the momentum behind it. Transforming these signal in to non-sinusoidal output enhances its utility.
The indicator allows traders to select any one or more of seven moving average options. Larger timeframes (e.g., MA89/MA144) provide a broader identification of the overall trend, helping to understand the general market direction. Smaller timeframes (e.g., MA5/MA8) are more sensitive to price changes and can indicate better entry and exit points, aiding in the identification of retracements and pullbacks. By combining multiple timeframes, traders can get a comprehensive view of the market, enabling more precise and informed trading decisions.
Key Features:
Multiple Moving Averages:
The indicator calculates several exponential moving averages (EMAs) based on different lengths: MA5, MA8, MA13, MA21, MA34, MA55, MA89, and MA144.
These MAs are further smoothed using a secondary exponential moving average, with the smoothing length customizable by the user.
Percentage Differences:
The indicator computes the percentage differences between successive MAs (e.g., (MA5 - MA8) / MA8 * 100). These differences highlight the relative movement of prices over different periods, providing insights into market momentum and trend strength.
Short-term MA differences (e.g., MA5/MA8) are more sensitive to recent price changes, making them useful for detecting quick market movements.
Long-term MA differences (e.g., MA89/MA144) smooth out short-term fluctuations, helping to identify major trends.
Rate of Change (ROC):
The indicator applies the Rate of Change (ROC) to the percentage differences of the MAs. ROC measures the speed at which the percentage differences are changing over time, providing an additional layer of trend analysis.
ROC helps in understanding the acceleration or deceleration of market trends, indicating the strength and potential reversals.
Transformations:
The percentage differences undergo a series of mathematical transformations (either inverse hyperbolic sine transformation or inverse fisher transformation) to refine the signal and enhance its interpretability. These transformations include adjustments to stabilize the values and highlight significant movements.
checkbox allows users to select which mathematical transformations to use.
Non-Sinusoidal Nature:
The output signal of this indicator is non-sinusoidal, characterized by abrupt changes and distinct patterns rather than smooth, wave-like oscillations.
The non-sinusoidal signal provides clearer demarcations of trend changes and is more responsive to sudden market shifts.
This nature reduces the lag typically associated with sinusoidal indicators, allowing for more timely and accurate trading decisions.
Customizable Options:
Users can select which MA pairs to include in the analysis using checkboxes. This flexibility allows the indicator to adapt to different trading strategies, whether focused on short-term movements or long-term trends.
Visual Representation:
The indicator plots the transformed values on a separate panel, making it easy for traders to visualize the trends and potential entry or exit points.
Usage Scenarios:
Short-Term Trading: By focusing on shorter MAs (e.g., MA5/MA8), traders can capture quick market movements and identify short-term trends.
Long-Term Analysis: Utilizing longer MAs (e.g., MA89/MA144) helps in identifying major market trends.
Combination of MAs: The ability to mix different MA lengths provides a balanced view, helping traders make decisions based on both immediate price actions and overall market direction.
Practical Benefits:
Early Signal Detection: The sensitivity of short-term MAs provides early signals for potential trend changes, assisting traders in timely decision-making.
Trend Confirmation: Long-term MAs offer stable trend confirmation, reducing the likelihood of false signals in volatile markets.
Noise Reduction: The mathematical transformations and ROC applied to the percentage differences help in filtering out market noise, focusing on meaningful price movements.
Improved Responsiveness: The non-sinusoidal nature of the signal allows the indicator to react more quickly to market changes, providing more accurate and timely trading signals.
Clearer Trend Demarcations: Non-sinusoidal signals make it easier to identify distinct phases of market trends, aiding in better interpretation and decision-making.
Trend, Momentum, Volume Delta Ratings Emoji RatingsThis indicator provides a visual summary of three key market conditions - Trend, Momentum, and Volume Delta - to help traders quickly assess the current state of the market. The goal is to offer a concise, at-a-glance view of these important technical factors.
Trend (HMA): The indicator uses a Hull Moving Average (HMA) to assess the overall trend direction. If the current price is above the HMA, the trend is considered "Good" or bullish (represented by a 😀 emoji). If the price is below the HMA, the trend is "Bad" or bearish (🤮). If the price is equal to the HMA, the trend is considered "Neutral" (😐).
Momentum (ROC): The Rate of Change (ROC) is used to measure the momentum of the market. A positive ROC indicates "Good" or bullish momentum (😀), a negative ROC indicates "Bad" or bearish momentum (🤮), and a zero ROC is considered "Neutral" (😐).
Volume Delta: The indicator calculates the difference between the current trading volume and a simple moving average of the volume (Volume Delta). If the Volume Delta is above a user-defined threshold, it is considered "Good" or bullish (😀). If the Volume Delta is below the negative of the threshold, it is "Bad" or bearish (🤮). Values within the threshold are considered "Neutral" (😐).
The indicator displays these three ratings in a compact table format in the top-right corner of the chart. The table uses color-coding to quickly convey the overall market conditions - green for "Good", red for "Bad", and gray for "Neutral".
This indicator can be useful for traders who want a concise, at-a-glance view of the current market trend, momentum, and volume activity. By combining these three technical factors, traders can get a more well-rounded understanding of the market conditions and potentially identify opportunities or areas of concern more easily.
The user can customize the indicator by adjusting the lengths of the HMA, ROC, and Volume moving average, as well as the Volume Delta threshold. The colors used in the table can also be customized to suit the trader's preferences.
VIX Dashboard [NariCapitalTrading]Overview
This VIX Dashboard is designed to provide traders with a quick visual reference into the current volatility and trend direction of the market as measured by CBOE VIX. It uses statistical measures and indicators including Rate of Change (ROC), Average True Range (ATR), and simple moving averages (SMA) to analyze the VIX.
Components
ATR Period : The ATR Period is used to calculate the Average True Range. The default period set is 24.
Trend Period : This period is used for the Simple Moving Average (SMA) to determine the trend direction. The default is set to 48.
Speed Up/Down Thresholds : These thresholds are used to determine significant increases or decreases in the VIX’s rate of change, signaling potential market volatility spikes or drops. These are customizable in the input section.
VIX Data : The script fetches the closing price of the VIX from a specified source (CBOE:VIX) with a 60-minute interval.
Rate of Change (ROC) : The ROC measures the percentage change in price from one period to the next. The script uses a default period of 20. The period can be customized in the input section.
VIX ATR : This is the Average True Range of the VIX, indicating the daily volatility level.
Trend Direction : Determined by comparing the VIX data with its SMA, indicating if the trend is up, down, or neutral. The trend direction can be customized in the input section.
Dashboard Display : The script creates a table on the chart that dynamically updates with the VIX ROC, ATR, trend direction, and speed.
Calculations
VIX ROC : Calculated as * 100
VIX ATR : ATR is calculated using the 'atrPeriod' and is a measure of volatility.
Trend Direction : Compared against the SMA over 'trendPeriod'.
Trader Interpretation
High ROC Value : Indicates increasing volatility, which could signal a market turn or increased uncertainty.
High ATR Value : Suggests high volatility, often seen in turbulent market conditions.
Trend Direction : Helps in understanding the overall market sentiment and trend.
Speed Indicators : “Mooning” suggests rapid increase in volatility, whereas “Cratering” indicates a rapid decrease.
The interpretation of these indicators should be combined with other market analysis tools for best results.
Golden Transform The Golden Transform Oscillator contains multiple technical indicators and conditions for making buy and sell decisions. Here's a breakdown of its components and what it's trying to achieve:
Strategy Setup:
The GT is designed to be plotted on the chart without overlaying other indicators.
Rate of Change (ROC) Calculation:
The Rate of Change (ROC) indicator is calculated with a specified period ("Rate of Change Length").
The ROC measures the percentage change in price over the specified period.
Hull Modified TRIX Calculation:
The Hull Modified TRIX indicator is calculated with a specified period ("Hull TRIX Length").
The Hull MA (Moving Average) formula, a modified WMA, is used to calculate a modified TRIX indicator, which is a momentum oscillator.
Hull MA Calculation:
A Hull Moving Average (Hull MA) is calculated as an entry filter.
Fisher Transform Calculation:
The Fisher Transform indicator is calculated to serve as a preemptive exit filter.
It involves mathematical transformations of price data to create an oscillator that can help identify potential reversals. The Fisher Transform is further smoothed using a Hull Moving Average (HMA).
Conditions and Signals:
Long conditions are determined based on crossovers between ROC and TRIX, as well as price relative the the MA. Short conditions are inversed.
Exit Conditions:
Exit conditions are defined for both long and short positions.
For long positions, the strategy exits if ROC crosses under TRIX, or if the smoothed Fisher Transform crosses above a threshold and declines. Once again, short conditions are the inverse.
Visualization and Plotting:
The script uses background colors for entry and shapes for exits to highlight different levels and conditions for the ROC/TRIX correlation.
It plots the Fisher Transform values and a lag trigger on the chart.
Overall, this script is a complex algorithm that combines multiple technical indicators and conditions to generate trading signals and manage positions in the financial markets. It aims to identify potential entry and exit points based on the interplay of the mentioned indicators and conditions.
TradeVision Pro - Multi-Factor Analysis System═══════════════════════════════════════════════════════════════════
TRADEVISION PRO - MULTI-FACTOR ANALYSIS SYSTEM
Created by Zakaria Safri
═══════════════════════════════════════════════════════════════════
A comprehensive technical analysis tool combining multiple factors for
signal generation, trend analysis, and dynamic risk management visualization.
Designed for educational purposes to study multi-factor convergence trading
strategies across all markets and timeframes.
⚠️ IMPORTANT DISCLAIMER:
This indicator is provided for EDUCATIONAL and INFORMATIONAL purposes only.
It does NOT constitute financial advice, investment advice, or trading advice.
Past performance does not guarantee future results. Trading involves
substantial risk of loss. Always do your own research and consult a
financial advisor before making trading decisions.
🎯 KEY FEATURES
═══════════════════════════════════════════════════════════════════
✅ MULTI-FACTOR SIGNAL GENERATION
• Price Volume Trend (PVT) analysis
• Rate of Change (ROC) momentum confirmation
• Volume-Weighted Moving Average (VWMA) trend filter
• Simple Moving Average (SMA) price smoothing
• Signals only when all factors align
✅ DYNAMIC RISK VISUALIZATION (Educational Only)
• ATR-based stop loss calculation
• Risk-reward based take profit levels (1-5 targets)
• Visual lines and labels showing entry, SL, and TPs
• Automatically adapts to market volatility
• ⚠️ VISUAL REFERENCE ONLY - Does not execute trades
✅ SUPPORT & RESISTANCE DETECTION
• Automatic pivot-based level identification
• Red dashed lines for resistance zones
• Green dashed lines for support areas
• Helps identify key price levels
✅ VWMA TREND BANDS
• Volume-weighted moving average with standard deviation
• Color-changing bands (Green = Uptrend, Red = Downtrend)
• Filled band area for easy visualization
• Volume-confirmed trend strength
✅ TREND DETECTION SYSTEM
• Counting-based trend confirmation
• Three states: Up Trend, Down Trend, Ranging
• Requires threshold of consecutive bars
• Independent trend validation
✅ PRICE RANGE VISUALIZATION
• High/Low range lines showing market structure
• Filled area highlighting price volatility
• Helps identify breakout zones
✅ COMPREHENSIVE INFO TABLE
• Real-time trend status
• Last signal type (BUY/SELL)
• Entry price display
• Stop loss level
• All active take profit levels
• Clean, professional layout
✅ OPTIONAL FEATURES
• Bar coloring by trend direction
• Customizable alert notifications
• Toggle visibility for all components
• Fully configurable parameters
📊 HOW IT WORKS
═══════════════════════════════════════════════════════════════════
SIGNAL METHODOLOGY:
BUY SIGNAL generates when ALL conditions are met:
• Smoothed price > Moving Average (upward price trend)
• PVT > PVT Average (volume supporting uptrend)
• ROC > 0 (positive momentum)
• Close > VWMA (above volume-weighted average)
SELL SIGNAL generates when ALL conditions are met:
• Smoothed price < Moving Average (downward price trend)
• PVT < PVT Average (volume supporting downtrend)
• ROC < 0 (negative momentum)
• Close < VWMA (below volume-weighted average)
This multi-factor approach filters out weak signals and waits for
strong convergence before generating alerts.
RISK CALCULATION:
Stop Loss = Entry ± (ATR × SL Multiplier)
• Uses Average True Range for volatility measurement
• Automatically adjusts to market conditions
Take Profit Levels = Entry ± (Risk Distance × TP Multiplier × Level)
• Risk Distance = |Entry - Stop Loss|
• Creates risk-reward based targets
• Example: TP Multiplier 1.0 = 1:1, 2:2, 3:3 risk-reward
⚠️ NOTE: All risk levels are VISUAL REFERENCES for educational study.
They do not execute trades automatically.
⚙️ SETTINGS GUIDE
═══════════════════════════════════════════════════════════════════
SIGNAL SETTINGS:
• Signal Length (14): Main calculation period for averages
• Smooth Length (8): Price data smoothing period
• PVT Length (14): Price Volume Trend calculation period
• ROC Length (9): Rate of Change momentum period
RISK MANAGEMENT (Visual Only):
• ATR Length (14): Volatility measurement lookback
• SL Multiplier (2.2): Stop loss distance (× ATR)
• TP Multiplier (1.0): Risk-reward ratio per TP level
• TP Levels (1-5): Number of take profit targets to display
• Show TP/SL Lines: Toggle visual reference lines
SUPPORT & RESISTANCE:
• Pivot Lookback (10): Sensitivity for S/R detection
• Show SR: Toggle support/resistance lines
VWMA BANDS:
• VWMA Length (20): Volume-weighted average period
• Show Bands: Toggle band visibility
TREND DETECTION:
• Trend Threshold (5): Consecutive bars required for trend
PRICE LINES:
• Period (20): High/low calculation lookback
• Show: Toggle price range visualization
DISPLAY OPTIONS:
• Signals: Show/hide BUY/SELL labels
• Table: Show/hide information panel
• Color Bars: Enable trend-based bar coloring
ALERTS:
• Enable: Activate alert notifications for signals
💡 USAGE INSTRUCTIONS
═══════════════════════════════════════════════════════════════════
RECOMMENDED APPROACH:
• Works on all timeframes (1m to Monthly)
• Suitable for all markets (Stocks, Forex, Crypto, etc.)
• Best used with additional analysis and confirmation
• Always practice proper risk management
ENTRY STRATEGY:
1. Wait for BUY or SELL signal to appear
2. Check trend table for trend confirmation
3. Verify VWMA band color matches signal direction
4. Look for nearby support/resistance confluence
5. Consider entering on next candle open
6. Use visual SL level for risk management
EXIT STRATEGY:
1. Use TP levels as potential exit zones
2. Consider scaling out at multiple TP levels
3. Exit on opposite signal
4. Adjust stops as trade progresses
5. Account for spread and slippage
TREND TRADING:
• "Up Trend" → Focus on BUY signals
• "Down Trend" → Focus on SELL signals
• "Ranging" → Wait for clear trend or use range strategies
🎨 VISUAL ELEMENTS
═══════════════════════════════════════════════════════════════════
• GREEN VWMA BANDS → Bullish trend indication
• RED VWMA BANDS → Bearish trend indication
• ORANGE DASHED LINE → Entry price reference
• RED SOLID LINE → Stop loss level
• GREEN DOTTED LINES → Take profit targets
• RED DASHED LINES → Resistance levels
• GREEN DASHED LINES → Support levels
• GREY FILLED AREA → Price high/low range
• GREEN BUY LABEL → Long signal
• RED SELL LABEL → Short signal
• BLUE INFO TABLE → Current trade details
• GREEN/RED BARS → Trend direction (optional)
⚠️ IMPORTANT NOTES
═══════════════════════════════════════════════════════════════════
RISK WARNING:
• Trading involves substantial risk of loss
• You can lose more than your initial investment
• Past performance does not guarantee future results
• No indicator is 100% accurate
• Always use proper position sizing
• Never risk more than you can afford to lose
EDUCATIONAL PURPOSE:
• This tool is for learning and research
• Not a complete trading system
• Should be combined with other analysis
• Requires interpretation and context
• Test thoroughly before live use
• Consider consulting a financial advisor
TECHNICAL LIMITATIONS:
• Signals lag price action (all indicators lag)
• False signals occur in choppy markets
• Works better in trending conditions
• Support/resistance levels are approximate
• TP/SL levels are suggestions, not guarantees
📚 METHODOLOGY
═══════════════════════════════════════════════════════════════════
This indicator combines established technical analysis concepts:
• Price Volume Trend (PVT): Volume-weighted price momentum
• Rate of Change (ROC): Momentum measurement
• Volume-Weighted Moving Average (VWMA): Trend identification
• Average True Range (ATR): Volatility measurement (J. Welles Wilder)
• Pivot Points: Support/resistance detection
All methods are based on publicly available technical analysis
principles. No proprietary or "secret" algorithms are used.
⚖️ FULL DISCLAIMER
═══════════════════════════════════════════════════════════════════
LIABILITY:
The creator (Zakaria Safri) assumes NO liability for:
• Trading losses or damages of any kind
• Loss of capital or profits
• Incorrect signal interpretation
• Technical issues, bugs, or errors
• Any consequences of using this tool
USER RESPONSIBILITY:
By using this indicator, you acknowledge that:
• You are solely responsible for your trading decisions
• You understand the substantial risks involved
• You will not hold the creator liable for losses
• You will conduct your own research and analysis
• You may consult a licensed financial professional
• You are using this tool entirely at your own risk
AS-IS PROVISION:
This indicator is provided "AS IS" without warranty of any kind,
express or implied, including but not limited to warranties of
merchantability, fitness for a particular purpose, or non-infringement.
The creator is not a registered investment advisor, financial planner,
or broker-dealer. This tool is not approved or endorsed by any
financial authority.
📞 ABOUT THE CREATOR
═══════════════════════════════════════════════════════════════════
Created by: Zakaria Safri
Specialization: Technical analysis indicator development
Focus: Multi-factor analysis, risk visualization, trend detection
This is an educational tool designed to demonstrate technical
analysis concepts and multi-factor signal generation methods.
📋 VERSION INFO
═══════════════════════════════════════════════════════════════════
Version: 1.0
Platform: TradingView Pine Script v5
License: Mozilla Public License 2.0
Creator: Zakaria Safri
Year: 2024
═══════════════════════════════════════════════════════════════════
Study Carefully, Trade Wisely, Manage Risk Properly
TradeVision Pro - Educational Trading Tool
Created by Zakaria Safri
═══════════════════════════════════════════════════════════════════
Multi Momentum 10/21/42/63 — Histogram + 2xSMAMY MM INDICATOR INDIRED BY KARADI
It averages four rate-of-change snapshots of price, all anchored at today’s close.
If “Show as %” is on, the value is multiplied by 100.
Each term is a simple momentum/ROC over a different lookback.
Combining 10, 21, 42, 63 bars blends short, medium, and intermediate horizons into one number.
Positive MM → average upward pressure across those horizons; negative MM → average downward pressure.
Why those lengths?
They roughly stack into ~2× progression (10→21≈2×10, 21→42=2×21, 63≈1.5×42). That creates a “multi-scale” momentum that’s less noisy than a single fast ROC but more responsive than a long ROC alone.
How to read the panel
Gray histogram = raw Multi-Momentum value each bar.
SMA Fast/Slow lines (defaults 12 & 26 over the MM values) = smoothing of the histogram to show the trend of momentum itself.
Typical signals
Zero-line context:
Above 0 → bullish momentum regime on average.
Below 0 → bearish regime.
Crosses of SMA Fast & Slow: momentum trend shifts (fast above slow = improving momentum; fast below slow = deteriorating).
Histogram vs SMA lines: widening distance suggests strengthening momentum; narrowing suggests momentum is fading.
Divergences: price makes a new high/low but MM doesn’t → potential exhaustion.
Compared to a classic ROC
A single ROC(20) is very sensitive to that one window.
MM averages several windows, smoothing idiosyncrasies (e.g., a one-off spike 21 bars ago) and reducing “lookback luck.”
Settings & customization
Lookbacks (10/21/42/63): you can tweak for your asset/timeframe; the idea is to mix short→medium horizons.
Percent vs raw ratio: percent is easier to compare across symbols.
SMA lengths: shorter = more reactive but choppier; longer = smoother but slower.
Practical tips
Use regime + signal: trade longs primarily when MM>0 and fast SMA>slow SMA; consider shorts when MM<0 and fast
Small-Cap — Sell Every Spike (Rendon1) Small-Cap — Sell Every Spike v6 — Strict, No Look-Ahead
Educational use only. This is not financial advice or a signal service.
This strategy targets low/ mid-float runners (≤ ~20M) that make parabolic spikes. It shorts qualified spikes and scales out into flushes. Logic is deliberately simple and transparent to avoid curve-fit.
What the strategy does
Detects a parabolic up move using:
Fast ROC over N bars
Big range vs ATR
Volume spike vs SMA
Fresh higher high (no stale spikes)
Enters short at bar close when conditions are met (no same-bar fills).
Manages exits with ATR targets and optional % covers.
Tracks float rotation intraday (manual float input) and blocks trades above a hard limit.
Draws daily spike-high resistance from confirmed daily bars (no repaint / no look-ahead).
Timeframes & market
Designed for 1–5 minute charts.
Intended for US small-caps; turn Premarket on.
Works intraday; avoid illiquid tickers or names with constant halts.
Entry, Exit, Risk (short side)
Entry: parabolic spike (ROC + Range≥ATR×K + Vol≥SMA×K, new HH).
Optional confirmations (OFF by default to “sell every spike”): upper-wick and VWAP cross-down.
Stop: ATR stop above entry (default 1.2× ATR).
Targets: TP1 = 1.0× ATR, TP2 = 2.0× ATR + optional 10/20/30% covers.
Safety: skip trades if RVOL is low or Float Rotation exceeds your limit (default warn 5×, hard 7×).
Inputs (Balanced defaults)
Price band: $2–$10
Float Shares: set per ticker (from Finviz).
RVOL(50) ≥ 1.5×
ROC(5) ≥ 1.0%, Range ≥ 1.6× ATR, Vol ≥ 1.8× SMA
Cooldown: 10 bars; Max trades/day: 6
Optional: Require wick (≥35%) and/or Require VWAP cross-down.
Presets suggestion:
• Balanced (defaults above)
• Safer: wick+VWAP ON, Range≥1.8×, trades/day 3–4
• Micro-float (<5M): ROC 1.4–1.8%, Range≥1.9–2.2×, Vol≥2.2×, RVOL≥2.0, wick 40–50%
No look-ahead / repaint notes
Daily spike-highs use request.security(..., lookahead_off) and shifted → only closed daily bars.
Orders arm next bar after entry; entries execute at bar close.
VWAP/ATR/ROC/Vol/RVOL are computed on the chart timeframe (no HTF peeking).
How to use
Build a watchlist: Float <20M, RelVol >2, Today +20% (Finviz).
Open 1–5m chart, enter Float Shares for the ticker.
Start with Balanced, flip to Safer on halty/SSR names or repeated VWAP reclaims.
Scale out into flushes; respect the stop and rotation guard.
Limitations & risk
Backtests on small-caps can be optimistic due to slippage, spreads, halts, SSR, and limited premarket data. Always use conservative sizing. Low-float stocks can squeeze violently.
Alerts
Parabolic UP (candidate short)
SHORT Armed (conditions met; entry at bar close)
JHW Volume Based Buy and Sell MomentumThe JHW Volume-Based Buy and Sell Momentum indicator is a custom momentum oscillator designed to capture market sentiment based on volume dynamics and price rate of change (ROC). It aims to identify bullish or bearish momentum by analyzing how price reacts to increasing or decreasing trading volume.
Core Logic:
The indicator calculates the Rate of Change (ROC) of the closing price.
It then accumulates this ROC separately based on whether the current volume is lower or higher than the previous bar:
If volume decreases, the ROC is added to a "negative volume index" accumulator.
If volume increases, the ROC is added to a "positive volume index" accumulator.
These two accumulators are combined to form a net momentum line.
Smoothing:
A Simple Moving Average (SMA) is applied to both accumulators over a user-defined period (default: 25 bars).
The sum of these smoothed values forms the signal line.
Visualization:
The indicator plots:
The net momentum line (yellow).
The smoothed signal line (blue).
The area between the two lines is filled with color:
Yellow when momentum is above the signal (bullish).
Blue when momentum is below the signal (bearish).
Bar colors are also adjusted to reflect the current momentum state.
Use Case:
This indicator helps traders:
Detect volume-driven momentum shifts.
Identify potential buy or sell zones based on volume behavior.
Confirm trends or spot early reversals.
Trend Surge with Pullback FilterTrend Surge with Pullback Filter
Overview
Trend Surge with Pullback Filter is a price action-based strategy designed to enter strong trends not at the breakout, but at the first controlled pullback after a surge. It filters out noise by requiring momentum confirmation and low volatility conditions, aiming for better entry prices and reduced risk exposure.
How It Works
A strong upward trend is identified when the Rate of Change (ROC) exceeds a defined percentage (e.g., 2%).
Instead of jumping into the trend immediately, the strategy waits for a pullback: the price must drop at least 1% below its recent high (over the past 3 candles).
A low volatility environment is also required for entry — measured using ATR being below its 20-period average multiplied by a safety factor.
If all three conditions are met (trend + pullback + quiet volatility), the system enters a long position.
The trade is managed using a dynamic ATR-based stop-loss and a take-profit at 2x ATR.
An automatic exit occurs after 30 bars if neither SL nor TP is hit.
Key Features
- Momentum-triggered trend detection via ROC
- Smart pullback filter avoids overbought entries
- Volatility-based filter to eliminate noise and choppy conditions
- Dynamic risk-reward ratio with ATR-driven exit logic
- Time-limited exposure using bar-based exit
Parameter Explanation
ROC Length (10): Looks for short-term price surges
ROC Threshold (2.0%): Trend is considered valid if price increased more than 2%
Pullback Lookback (3): Checks last 3 candles for price retracement
Minimum Pullback % (1.0%): Entry only if price pulled back at least 1%
ATR Length (14): Measures current volatility
Low Volatility Multiplier (1.2): ATR must be below this multiple of its 20-period average
Risk-Reward (2.0): Target is set at 2x the stop-loss distance
Max Bars (30): Trade is closed automatically after 30 bars
Originality Statement
This strategy doesn’t enter at the trend start, unlike many momentum bots. Instead, it waits for the first market hesitation — a minor pullback under low volatility — before entering. This logic mimics how real traders often wait for a better entry after a breakout, avoiding emotional overbought buys. The combined use of ROC, dynamic pullback detection, and ATR-based environment filters makes it both practical and original for real-world trading.
Disclaimer
This strategy is intended for educational and research purposes. Backtest thoroughly and understand the logic before using with real capital.
Trend Analysis with Volatility and MomentumVolatility and Momentum Trend Analyzer
The Volatility and Momentum Trend Analyzer is a multi-faceted TradingView indicator designed to provide a comprehensive analysis of market trends, volatility, and momentum. It incorporates key features to identify trend direction (uptrend, downtrend, or sideways), visualize weekly support and resistance levels, and offer a detailed assessment of market strength and activity. Below is a breakdown of its functionality:
1. Input Parameters
The indicator provides customizable settings for precision and adaptability:
Volatility Lookback Period: Configurable period (default: 14) for calculating Average True Range (ATR), which measures market volatility.
Momentum Lookback Period: Configurable period (default: 14) for calculating the Rate of Change (ROC), which measures the speed and strength of price movements.
Support/Resistance Lookback Period: Configurable period (default: 7 weeks) to determine critical support and resistance levels based on weekly high and low prices.
2. Volatility Analysis (ATR)
The Average True Range (ATR) is calculated to quantify the market's volatility:
What It Does: ATR measures the average range of price movement over the specified lookback period.
Visualization: Plotted as a purple line in a separate panel below the price chart, with values amplified (multiplied by 10) for better visibility.
3. Momentum Analysis (ROC)
The Rate of Change (ROC) evaluates the momentum of price movements:
What It Does: ROC calculates the percentage change in closing prices over the specified lookback period, indicating the strength and direction of market moves.
Visualization: Plotted as a yellow line in a separate panel below the price chart, with values amplified (multiplied by 10) for better visibility.
4. Trend Detection
The indicator identifies the current market trend based on momentum and the position of the price relative to its moving average:
Uptrend: Occurs when momentum is positive, and the closing price is above the simple moving average (SMA) of the specified lookback period.
Downtrend: Occurs when momentum is negative, and the closing price is below the SMA.
Sideways Trend: Occurs when neither of the above conditions is met.
Visualization: The background of the price chart changes color to reflect the detected trend:
Green: Uptrend.
Red: Downtrend.
Gray: Sideways trend.
5. Weekly Support and Resistance
Critical levels are calculated based on weekly high and low prices:
Support: The lowest price observed over the last specified number of weeks.
Resistance: The highest price observed over the last specified number of weeks.
Visualization:
Blue Line: Indicates the support level.
Orange Line: Indicates the resistance level.
Both lines are displayed on the main price chart, dynamically updating as new data becomes available.
6. Alerts
The indicator provides configurable alerts for trend changes, helping traders stay informed without constant monitoring:
Uptrend Alert: Notifies when the market enters an uptrend.
Downtrend Alert: Notifies when the market enters a downtrend.
Sideways Alert: Notifies when the market moves sideways.
7. Key Use Cases
Trend Following: Identify and follow the dominant trend to capitalize on sustained price movements.
Volatility Assessment: Measure market activity to determine potential breakouts or quiet consolidation phases.
Support and Resistance: Highlight key levels where price is likely to react, assisting in decision-making for entries, exits, or stop-loss placement.
Momentum Tracking: Gauge the strength and speed of price moves to validate trends or anticipate reversals.
8. Visualization Summary
Main Chart:
Background color-coded for trend direction (green, red, gray).
Blue and orange lines for weekly support and resistance.
Lower Panels:
Purple line for volatility (ATR).
Yellow line for momentum (ROC).
Percentile Momentum IndicatorInput Parameters:
lengthPercentile: Defines the period used to calculate the percentile values (default: 30).
lengthMomentum: Defines the period for calculating the Rate of Change (ROC) momentum (default: 10).
Core Logic:
Rate of Change (ROC): The script calculates the ROC of the closing price over the specified period (lengthMomentum).
Percentile Calculations: The script calculates two key percentiles:
percentile_upper (80th percentile of the high prices)
percentile_lower (20th percentile of the low prices)
Percentile Average: An average of the upper and lower percentiles is calculated (avg_percentile).
Trade Signals:
Buy Signal: Triggered when the ROC is positive, the close is above the percentile_lower, and the close is above the avg_percentile.
Sell Signal: Triggered when the ROC is negative, the close is below the percentile_upper, and the close is below the avg_percentile.
Trade State Management:
The script uses a binary state: 1 for long (buy) and -1 for short (sell).
The trade state is updated based on buy or sell signals.
Bar Coloring:
Bars are colored dynamically based on the trade state:
Green for long (buy signal).
Red for short (sell signal).
The same color is applied to the percentile and average percentile lines for visual consistency.
Momentum Memory Indicator
The Momentum Memory Indicator (MMI) is a custom tool designed to predict future price movements based on the historical momentum of an asset. By calculating the Rate of Change (ROC) and then averaging it over a specified "memory" period, the MMI provides a prediction that reflects both recent and slightly older momentum data. The prediction is visualized as a histogram, with colors indicating the direction of the momentum.
**Parameters:**
1. **Rate of Change Period (ROC Period):** This parameter sets the period for the Rate of Change calculation, which measures the momentum of the asset. The default value is 14.
2. **Memory Period:** This parameter determines the period over which the average momentum is calculated. By considering momentum over this "memory" period, the indicator aims to provide a more stable and reliable prediction. The default value is 5.
**Logic:**
1. **Rate of Change (Momentum):** The ROC is calculated based on the asset's closing prices over the specified ROC period. It provides a measure of how much the price has changed over that period, indicating momentum.
2. **Average Momentum:** The average momentum is calculated by taking a simple moving average (SMA) of the ROC values over the memory period. This smoothens out the momentum data and provides a more stable value for prediction.
3. **Prediction:** The prediction is calculated by adjusting the current closing price based on the average momentum. This gives an estimate of where the price might be in the next period, assuming the momentum continues.
4. **Prediction Color:** The color of the prediction histogram is determined by the direction of the average momentum. A positive momentum results in a green histogram, while a negative momentum results in a red histogram.
**Plots:**
1. **Prediction (Histogram):** Represents the predicted price movement based on the average momentum. The direction and magnitude of the histogram bars provide insights into the expected price change. The color of the bars (green or red) indicates the direction of the momentum.
D-BoT Alpha ReversalsHello traders, today I'm going to share with you a strategy that I use very frequently. I wanted to share this strategy that I use in my manual trades by translating it into code. I'm sharing it with you with completely open source code.
RSI of ROC: The indicator initially calculates RSI (Relative Strength Index) on ROC (Rate of Change). This is a method that tracks the rate of price change (ROC) over a certain period and applies it to the RSI calculation.
Adaptive RSI: The code then calculates the RSI for all periods between the minimum and maximum RSI lengths. It takes the average of these calculations and names it as avg_rsi66. In addition, it checks whether each RSI value exceeds the determined overbought and oversold limits.
Signal Triggers: If both RSI of ROC and avg_rsi66 are above or below the specified overbought or oversold levels and the difference between these two values is less than the specified threshold value (Extremities Sensitivity), a signal is triggered. In addition, the color of the bar is also checked: An overbought (sell) signal is triggered for a red bar and an oversold (buy) signal is triggered for a green bar.
Signal Visualization: Signals are shown on the chart at appropriate places with "Sell" or "Buy" shapes. Also, each of these conditions is defined as an alert condition.
The general purpose of this indicator is to determine the turning points of the market. Overbought and oversold signals are based on the idea that the price may turn from these areas. That is, a "Sell" signal indicates a turning point where the price may start to fall, while a "Buy" signal indicates a turning point where the price may start to rise.
These types of indicators usually have some weak points:
False Signals: Like any kind of technical analysis indicator, this indicator can also give false signals. That is, you may get a "Buy" or "Sell" signal but the price may not move in the expected direction.
Market Conditions: This indicator may perform better under certain market conditions. For example, a trend-following indicator usually works well in trending markets, but can be misleading in range-bound markets. This indicator too can perform better or worse in a particular market situation.
Parameter Selection: The choice of the parameters of the indicator (ROC and RSI lengths, overbought/oversold levels, etc.) can significantly affect the quality of the indicator signals. Parameters should be optimized for various assets and time frames.
In conclusion, it would be better to use this indicator not as a standalone trading system, but in conjunction with other technical analysis tools or fundamental analysis. Also, it is always beneficial to test a new trading strategy on past data or on a demo account before trading with real money."
Stay tuned for more of my original strategies :)
Happy trading...
Fundamental Value and Dividend Growth InvestingThis script is an original implementation of a Fundamental Value and Dividend Growth Investing Strategy for traders who want to incorporate these concepts in their trading decisions. The script uses technical indicators to determine buy and sell signals based on a set of criteria.
To use the script, traders can input various parameters, such as the length of the simple moving averages (SMA), the rate of change (ROC) length, and the dividend yield. The script calculates the SMA for the long and short periods, the ROC, and the dividend.
The buy signal is triggered when the current closing price is greater than the short-term SMA, the short-term SMA crosses above the long-term SMA, the ROC is positive, and the closing price is greater than the dividend. The sell signal is triggered when the current closing price is less than the long-term SMA, the long-term SMA crosses above the short-term SMA, and the ROC is negative.
The script plots the signals and the indicators, such as the SMA200, the SMS50, the dividend, and the ROC. The script also includes alert conditions for the buy and sell signals.
The concept underlying the calculations of this script is the Fundamental Value and Dividend Growth Investing Strategy. This strategy aims to identify stocks that are trading below their intrinsic value and have a history of increasing dividends. The SMA and ROC indicators help identify the trends in the stock price, while the dividend yield helps identify stocks with a history of dividend growth.
Overall, this script offers traders an original and useful tool for incorporating Fundamental Value and Dividend Growth Investing Strategy into their trading decisions.
KST con HMA---------- ENGLISH DESCRIPTION ----------
The indicator created is called "KST with HMA" and is used to measure the impulse of an asset's price.
The code begins by defining four variables representing ROC (Rate of Change) period lengths for calculating the KST (Know Sure Thing) and a variable for the length of the HMA (Hull Moving Average).
Next, an HMA function is defined to calculate the Hull Moving Average, a type of weighted moving average that adjusts for price volatility.
ROC values are then calculated for the four periods defined above and KST values are calculated as a weighted sum of the ROC values. These values are then normalized with the HMA and the standard deviation of the HMA is calculated. The normalized value is finally plotted with three different color lines: black for values greater than 1, red for values less than -1, and green for values between -1 and 1.
Finally, a black dashed line is plotted to represent the zero line. The green line indicates a phase of market uncertainty or lateralization, while the indicator can be used to identify buy points above zero and sell points below zero.
---------- ITALIAN DESCRIPTION ----------
L'indicatore creato è chiamato "KST con HMA" e viene utilizzato per misurare l'impulso del prezzo di un asset.
Il codice inizia definendo quattro variabili che rappresentano le lunghezze dei periodi di ROC (Rate of Change) per il calcolo del KST (Know Sure Thing) e una variabile per la lunghezza dell'HMA (Hull Moving Average).
Successivamente viene definita una funzione HMA per il calcolo della Hull Moving Average, un tipo di media mobile ponderata che si adatta alla volatilità del prezzo.
Vengono poi calcolati i valori ROC per i quattro periodi definiti in precedenza e calcolati i valori KST come somma ponderata dei valori ROC. Questi valori vengono poi normalizzati con l'HMA e viene calcolata la deviazione standard dell'HMA. Il valore normalizzato viene infine plottato con tre diverse linee di colore: nero per valori superiori a 1, rosso per valori inferiori a -1 e verde per valori tra -1 e 1.
Infine, viene plottata una linea tratteggiata nera per rappresentare la linea zero. La linea verde indica una fase di incertezza o lateralizzazione del mercato, mentre l'indicatore può essere utilizzato per individuare punti di acquisto sopra lo zero e di vendita al di sotto dello zero.
Jdawg Sentiment Momentum Oscillator EnhancedThe Jdawg Sentiment Momentum Oscillator Enhanced (JSMO_E) is a versatile technical analysis indicator designed to provide traders with insights into potential trend changes and overbought or oversold market conditions. JSMO_E combines the principles of the Relative Strength Index (RSI), the Simple Moving Average (SMA), and the Rate of Change (ROC) to create a comprehensive tool for assessing market sentiment and momentum.
The uniqueness of JSMO_E lies in its ability to integrate the RSI, SMA of RSI, and ROC of RSI, while also allowing users to customize the weight of the ROC component. This combination of features is not commonly found in other indicators, which increases its distinctiveness.
To effectively use JSMO_E, follow these steps:
Apply the JSMO_E indicator to the price chart of the asset you are analyzing.
Observe the plotted JSMO_E line in relation to the zero line, overbought, and oversold levels.
When the JSMO_E line crosses above the zero line, it may signal the beginning of an uptrend or bullish momentum. Conversely, when the JSMO_E line crosses below the zero line, it may indicate the start of a downtrend or bearish momentum.
Overbought and oversold levels, marked by the red and green dashed lines, respectively, can serve as a warning that a trend reversal may be imminent. When the JSMO_E line reaches or surpasses the overbought level, it might indicate that the asset is overvalued and could experience a price decline. Conversely, when the JSMO_E line reaches or goes below the oversold level, it can signal that the asset is undervalued and may experience a price increase.
Adjust the input parameters (RSI Period, SMA Period, ROC Period, and ROC Weight) as needed to optimize the indicator for the specific market and time frame you are analyzing.
The JSMO_E indicator is suitable for various markets, including stocks, forex, commodities, and cryptocurrencies. However, its effectiveness may vary depending on the market conditions and time frames used. It is recommended to use JSMO_E in conjunction with other technical analysis tools and methods to confirm potential trade setups and improve overall trading performance. Always conduct thorough backtesting and forward-testing before employing any indicator in a live trading environment.
