L1 Multidimensional KDJLevel: 1
Background
The KDJ oscillator display consists of 3 lines (K, D and J - hence the name of the display) and 2 levels. K and D are the same lines you see when using the stochastic oscillator. The J line in turn represents the deviation of the D value from the K value. The convergence of these lines indicates new trading opportunities. Just like the Stochastic Oscillator, oversold and overbought levels correspond to the times when the trend is likely to reverse.
Function
L1 Multidimensional KDJ utilizes multiple KDJ modeling across multiple time frames. In this instance, it covers three time frames as day, week and month. Although it is named like that, one can deduce and use it in small time frames e.g. 15mins (day), 60mins (week) and 4H (month) because KDJ oscillator is commonly used for small time frames across various markets.
Key Signal
kd --> day K value
kw --> week K value
km --> month K value
dd --> day D value
dw --> week D value
dm --> month D value
divergence --> divergence among day, week, month D values
resonance --> all three time frame D values are in the same direction
Pros and Cons
Pros:
1. Enable multidimensional KDJ,especially D value comparisons
2. divergence and resoanance among different time frame KDJ can be disclosed
Cons:
1. It may satruate for extreme conditions of long and short.
2. Not accurate for long and short entries by resonance effect.
Remarks
Bring about multiple time frames into consideration of KDJ is novel.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
在脚本中搜索"oscillator"
Recursive RsiIntroduction
I have already posted a classic indicator using recursion, it was the stochastic oscillator and recursion helped to get a more predictive and smooth result. Here i will do the same thing with the rsi oscillator but with a different approach. As reminder when using recursion you just use a fraction of the output of a function as input of the same function, i say a fraction because if you feedback the entire output you will just have a periodic function, this is why you average the output with the input.
The Indicator
The indicator will use 50% of the output and 50% of the input, remember that when using feedback always rescale your input, else the effect might be different depending on the market you are in. You can interpret the indicator like a normal rsi except if you plan to use the 80/20 level, depending on length the scale might change, if you need a fixed scale you can always rescale b by using an rsi or stochastic oscillator.
Conclusion
I have presented an rsi oscillator using a different type of recursion structure than the recursive stochastic i posted in the past, the result might be more predictive than the original rsi. Hope you like it and thanks for reading !
BUBD+ - Bats Ultimate Bullish Divergence DetectorBUBD checks for price divergence from oscillators across 6 different oscillators - MACD, CCI (Vol. weighted), RSI, Stochastic RSI, Money Flow and Relative Vigor index. Use it to find good entry spots for longs and also to find downtrend reversals. If this gets popular I will release a Bearish divergence indicator as well.
Please check your stock/crypto across all time frames to get a hint of any developing "Bullish" divergences.
In case you get mixed signals -
Blue - RSI
Purple - RVI
Yellow - CCI
Green - MACD
Lime light green - MFI
Orange - Stoch RSI
Dont get confused by signals appearing on top and bottom all are bullish indicators. If you see a signal go to the respective oscillator to check the developing trend.
Gyspy Bot Trade Engine - V1.2B - Strategy 12-7-25 - SignalLynxGypsy Bot Trade Engine (MK6 V1.2B) - Ultimate Strategy & Backtest
Brought to you by Signal Lynx | Automation for the Night-Shift Nation 🌙
1. Executive Summary & Architecture
Gypsy Bot (MK6 V1.2B) is not merely a strategy; it is a massive, modular Trade Engine built specifically for the TradingView Pine Script environment. While most strategies rely on a single dominant indicator (like an RSI cross or a MACD flip) to generate signals, Gypsy Bot functions as a sophisticated Consensus Algorithm.
The engine calculates data from up to 12 distinct Technical Analysis Modules simultaneously on every bar closing. It aggregates these signals into a "Vote Count" and only executes a trade entry when a user-defined threshold of concurring signals is met. This "Voting System" acts as a noise filter, requiring multiple independent mathematical models—ranging from volume flow and momentum to cyclical harmonics and trend strength—to agree on market direction before capital is committed.
Beyond entries, Gypsy Bot features a proprietary Risk Management suite called the Dump Protection Team (DPT). This logic layer operates independently of the entry modules, specifically scanning for "Moon" (Parabolic) or "Nuke" (Crash) volatility events to force-exit positions, overriding standard stops to preserve capital during Black Swan events.
2. ⚠️ The Philosophy of "Curve Fitting" (Must Read)
One must be careful when applying Gypsy Bot to new pairs or charts.
To be fully transparent: Gypsy Bot is, by definition, a very advanced curve-fitting engine. Because it grants the user granular control over 12 modules, dozens of thresholds, and specific voting requirements, it is extremely easy to "over-fit" the data. You can easily toggle switches until the backtest shows a 100% win rate, only to have the strategy fail immediately in live markets because it was tuned to historical noise rather than market structure.
To use this engine successfully, you must adopt a specific optimization mindset:
Ignore Raw Net Profit: Do not tune for the highest dollar amount. A strategy that makes $1M in the backtest but has a 40% drawdown is useless.
Prioritize Stability: Look for a high Profit Factor (1.5+), a high Percent Profitable, and a smooth equity curve.
Regular Maintenance is Mandatory: Markets shift regimes (e.g., from Bull Trend to Crab Range). Parameters that worked perfectly in 2021 may fail in 2024. Gypsy Bot settings should be reviewed and adjusted at regular intervals (e.g., quarterly) to ensure the voting logic remains aligned with current market volatility.
Timeframe Recommendations:
Gypsy Bot is optimized for High Time Frame (HTF) trend following. It generally produces the most reliable results on charts ranging from 1-Hour to 12-Hours, with the 4-Hour timeframe historically serving as the "sweet spot" for most major cryptocurrency assets.
3. The Voting Mechanism: How Entries Are Generated
The heart of the Gypsy Bot engine is the ActivateOrders input (found in the "Order Signal Modifier" settings).
The engine constantly monitors the output of all enabled Modules.
Long Votes: GoLongCount
Short Votes: GoShortCount
If you have 10 Modules enabled, and you set ActivateOrders to 7:
The engine will ONLY trigger a Buy Entry if 7 or more modules return a valid "Buy" signal on the same closed candle.
If only 6 modules agree, the trade is rejected.
This allows you to mix "Leading" indicators (Oscillators) with "Lagging" indicators (Moving Averages) to create a high-probability entry signal that requires momentum, volume, and trend to all be in alignment.
4. Technical Deep Dive: The 12 Modules
Gypsy Bot allows you to toggle the following modules On/Off individually to suit the asset you are trading.
Module 1: Modified Slope Angle (MSA)
Logic: Calculates the geometric angle of a moving average relative to the timeline.
Function: It filters out "lazy" trends. A trend is only considered valid if the slope exceeds a specific steepness threshold. This helps avoid entering trades during weak drifts that often precede a reversal.
Module 2: Correlation Trend Indicator (CTI)
Logic: Based on John Ehlers' work, this measures how closely the current price action correlates to a straight line (a perfect trend).
Function: It outputs a confidence score (-1 to 1). Gypsy Bot uses this to ensure that we are not just moving up, but moving up with high statistical correlation, reducing fake-outs.
Module 3: Ehlers Roofing Filter
Logic: A sophisticated spectral filter that combines a High-Pass filter (to remove long-term drift) with a Super Smoother (to remove high-frequency noise).
Function: It attempts to isolate the "Roof" of the price action. It is excellent at catching cyclical turning points before standard moving averages react.
Module 4: Forecast Oscillator
Logic: Uses Linear Regression forecasting to predict where price "should" be relative to where it is.
Function: When the Forecast Oscillator crosses its zero line, it indicates that the regression trend has flipped. We offer both "Aggressive" and "Conservative" calculation modes for this module.
Module 5: Chandelier ATR Stop
Logic: A volatility-based trend follower that hangs a "leash" (ATR multiple) from the highest high (for longs) or lowest low (for shorts).
Function: Used here as an entry filter. If price is above the Chandelier line, the trend is Bullish. It also includes a "Bull/Bear Qualifier" check to ensure structural support.
Module 6: Crypto Market Breadth (CMB)
Logic: This is a macro-filter. It pulls data from multiple major tickers (BTC, ETH, and Perpetual Contracts) across different exchanges.
Function: It calculates a "Market Health" percentage. If Bitcoin is rising but the rest of the market is dumping, this module can veto a trade, ensuring you don't buy into a "fake" rally driven by a single asset.
Module 7: Directional Index Convergence (DIC)
Logic: Analyzes the convergence/divergence between Fast and Slow Directional Movement indices.
Function: Identifies when trend strength is expanding. A buy signal is generated only when the positive directional movement overpowers the negative movement with expanding momentum.
Module 8: Market Thrust Indicator (MTI)
Logic: A volume-weighted breadth indicator. It uses Advance/Decline data and Up/Down Volume data.
Function: This is one of the most powerful modules. It confirms that price movement is supported by actual volume flow. We recommend using the "SSMA" (Super Smoother) MA Type for the cleanest signals on the 4H chart.
Module 9: Simple Ichimoku Cloud
Logic: Traditional Japanese trend analysis using the Tenkan-sen and Kijun-sen.
Function: Checks for a "Kumo Breakout." Price must be fully above the Cloud (for longs) or below it (for shorts). This is a classic "trend confirmation" module.
Module 10: Simple Harmonic Oscillator
Logic: Analyzes the harmonic wave properties of price action to detect cyclical tops and bottoms.
Function: Serves as a counter-trend or early-reversal detector. It tries to identify when a cycle has bottomed out (for buys) or topped out (for sells) before the main trend indicators catch up.
Module 11: HSRS Compression / Super AO
Logic: Two options in one.
HSRS: Hirashima Sugita Resistance Support. Detects volatility compression (squeezes) relative to dynamic support/resistance bands.
Super AO: A combination of the Awesome Oscillator and SuperTrend logic.
Function: Great for catching explosive moves that result from periods of low volatility (consolidation).
Module 12: Fisher Transform (MTF)
Logic: Converts price data into a Gaussian normal distribution.
Function: Identifies extreme price deviations. This module uses Multi-Timeframe (MTF) logic to look at higher-timeframe trends (e.g., looking at the Daily Fisher while trading the 4H chart) to ensure you aren't trading against the major trend.
5. Global Inhibitors (The Veto Power)
Even if 12 out of 12 modules vote "Buy," Gypsy Bot performs a final safety check using Global Inhibitors. If any of these are triggered, the trade is blocked.
Bitcoin Halving Logic:
Hardcoded dates for past and projected future Bitcoin halvings (up to 2040).
Trading is inhibited or restricted during the chaotic weeks immediately surrounding a Halving event to avoid volatility crushes.
Miner Capitulation:
Uses Hash Rate Ribbons (Moving averages of Hash Rate).
If miners are capitulating (Shutting down rigs due to unprofitability), the engine flags a "Bearish" regime and can flip logic to Short-only or flat.
ADX Filter (Flat Market Protocol):
If the Average Directional Index (ADX) is below a specific threshold (e.g., 20), the market is deemed "Flat/Choppy." The bot will refuse to open trend-following trades in a flat market.
CryptoCap Trend:
Checks the total Crypto Market Cap chart. If the broad market is in a downtrend, it can inhibit Long entries on individual altcoins.
6. Risk Management & The Dump Protection Team (DPT)
Gypsy Bot separates "Entry Logic" from "Risk Management Logic."
Dump Protection Team (DPT)
This is a specialized logic branch designed to save the account during Black Swan events.
Nuke Protection: If the DPT detects a volatility signature consistent with a flash crash, it overrides all other logic and forces an immediate exit.
Moon Protection: If a parabolic pump is detected that violates statistical probability (Bollinger deviations), DPT can force a profit take before the inevitable correction.
Advanced Adaptive Trailing Stop (AATS)
Unlike a static trailing stop (e.g., "trail by 5%"), AATS is dynamic.
Penthouse Level: If price is at the top of the HSRS channel (High Volatility), the stop loosens to allow for wicks.
Dungeon Level: If price is compressed at the bottom, the stop tightens to protect capital.
Staged Take Profits
TP1: Scalp a portion (e.g., 10%) to cover fees and secure a win.
TP2: Take the bulk of profit.
TP3: Leave a "Runner" position with a loose trailing stop to catch "Moon" moves.
7. Recommended Setup Guide
When applying Gypsy Bot to a new chart, follow this sequence:
Set Timeframe: 4 Hours (4H).
Reset: Turn OFF Trailing Stop, Stop Loss, and Take Profits. (We want to see raw entry performance first).
Tune DPT: Adjust "Dump/Moon Protection" inputs first. These have the highest impact on net performance.
Tune Module 8 (MTI): This module is a heavy filter. Experiment with the MA Type (SSMA is recommended).
Select Modules: Enable/Disable modules 1-12 based on the asset's personality (Trending vs. Ranging).
Voting Threshold: Adjust ActivateOrders. A lower number = More Trades (Aggressive). A higher number = Fewer, higher conviction trades (Conservative).
Final Polish: Re-enable Stop Losses, Trailing Stops, and Staged Take Profits to smooth the equity curve and define your max risk per trade.
8. Technical Specs
Engine Version: Pine Script V6
Repainting: This strategy uses Closed Candle data for all Risk Management and Entry decisions. This ensures that Backtest results align closely with real-time behavior (no repainting of historical signals).
Alerts: This script generates Strategy alerts. If you require visual-only alerts, see the source code header for instructions on switching to "Study" (Indicator) mode.
Disclaimer:
This script is a complex algorithmic tool for market analysis. Past performance is not indicative of future results. Use this tool to assist your own decision-making, not to replace it.
9. About Signal Lynx
Automation for the Night-Shift Nation 🌙
Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management.
We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to:
Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators
Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend
If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source).
If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
Fair Value Lead-Lag Model [BackQuant]Fair Value Lead-Lag Model
A cross-asset model that estimates where price "should" be relative to a chosen reference series, then tracks the deviation as a normalized oscillator. It helps you answer two questions: 1) is the asset rich or cheap vs its driver, and 2) is the driver leading or lagging price over the next N bars.
Concept in one paragraph
Many assets co-move with a macro or sector driver. Think BTC vs DXY, gold vs real yields, a stock vs its sector ETF. This tool builds a rolling fair value of the charted asset from a reference series and shows how far price is above or below that fair value in standard deviation units. You can shift the reference forward or backward to test who leads whom, then use the deviation and its bands to structure mean-reversion or trend-following ideas.
What the model does
Reference mapping : Pulls a reference symbol at a chosen timeframe, with an optional lead or lag in bars to test causality.
Fair value engine : Converts the reference into a synthetic fair value of the chart using one of four methods:
Ratio : price/ref with a rolling average ratio. Good when the relationship is proportional.
Spread : price minus ref with a rolling average spread. Good when the relationship is additive.
Z-Score : normalizes both series, aligns on standardized units, then re-projects to price space. Good when scale drifts.
Beta-Adjusted : rolling regression style. Uses covariance and variance to compute beta, then builds a fair value = mean(price) + beta * (ref − mean(ref)).
Deviation and bands : Computes a z-scored deviation of price vs fair value and plots sigma bands (±1, ±2, ±3) around the fair value line on the chart.
Correlation context : Shows rolling correlation so you can judge if deviations are meaningful or just noise when co-movement is weak.
Visuals :
Fair value line on price chart with sigma envelopes.
Deviation as a column oscillator and optional line.
Threshold shading beyond user-set upper and lower levels.
Summary table with reference, deviation, status, correlation, and method.
Why this is useful
Mean reversion framework : When correlation is healthy and deviation stretches beyond your sigma threshold, probability favors reversion toward fair value. This is classic pairs logic adapted to a driver and a target.
Trend confirmation : If price rides the fair value line and deviation stays modest while correlation is positive, it supports trend persistence. Pullbacks to negative deviation in an uptrend can be buyable.
Lead-lag discovery : Shift the reference forward by +N bars. If correlation improves, the reference tends to lead. Shift backward for the reverse. Use the best setting for planning early entries or hedges.
Regime detection : Large persistent deviations with falling correlation hint at regime change. The relationship you relied on may be breaking down, so reduce confidence or switch methods.
How to use it step by step
Pick a sensible reference : Choose a macro, index, currency, or sector driver that logically explains the asset’s moves. Example: gold with DXY, a semiconductor stock with SOXX.
Test lead-lag : Nudge Lead/Lag Periods to small positive values like +1 to +5 to see if the reference leads. If correlation improves, keep that offset. If correlation worsens, try a small negative value or zero.
Select a method :
Start with Beta-Adjusted when the relationship is approximately linear with drift.
Use Ratio if the assets usually move in proportional terms.
Use Spread when they trade around a level difference.
Use Z-Score when scales wander or volatility regimes shift.
Tune windows :
Rolling Window controls how quickly fair value adapts. Shorter equals faster but noisier.
Normalization Period controls how deviations are standardized. Longer equals stabler sigma sizing.
Correlation Length controls how co-movement is measured. Keep it near the fair value window.
Trade the edges :
Mean reversion idea : Wait for deviation beyond your Upper or Lower Threshold with positive correlation. Fade back toward fair value. Exit at the fair value line or the next inner sigma band.
Trend idea : In an uptrend, buy pullbacks when deviation dips negative but correlation remains healthy. In a downtrend, sell bounces when deviation spikes positive.
Read the table : Deviation shows how many sigmas you are from fair value. Status tells you overvalued or undervalued. Correlation color hints confidence. Method tells you the projection style used.
Reading the display
Fair value line on price chart: the model’s estimate of where price should trade given the reference, updated each bar.
Sigma bands around fair value: a quick sense of residual volatility. Reversions often target inner bands first.
Deviation oscillator : above zero means rich vs fair value, below zero means cheap. Color bins intensify with distance.
Correlation line (optional): scale is folded to match thresholds. Higher values increase trust in deviations.
Parameter tips
Start with Rolling Window 20 to 30, Normalization Period 100, Correlation Length 50.
Upper and Lower Threshold at ±2.0 are classic. Tighten to ±1.5 for more signals or widen to ±2.5 to focus on outliers.
When correlation drifts below about 0.3, treat deviations with caution. Consider switching method or reference.
If the fair value line whipsaws, increase Rolling Window or move to Beta-Adjusted which tends to be smoother.
Playbook examples
Pairs-style reversion : Asset is +2.3 sigma rich vs reference, correlation 0.65, trend flat. Short the deviation back toward fair value. Cover near the fair value line or +1 sigma.
Pro-trend pullback : Uptrend with correlation 0.7. Deviation dips to −1.2 sigma while price sits near the −1 sigma band. Buy the dip, target the fair value line, trail if the line is rising.
Lead-lag timing : Reference leads by +3 bars with improved correlation. Use reference swings as early cues to anticipate deviation turns on the target.
Caveats
The model assumes a stable relationship over the chosen windows. Structural breaks, policy shocks, and index rebalances can invalidate recent history.
Correlation is descriptive, not causal. A strong correlation does not guarantee future convergence.
Do not force trades when the reference has low liquidity or mismatched hours. Use a reference timeframe that captures real overlap.
Bottom line
This tool turns a loose cross-asset intuition into a quantified, visual fair value map. It gives you a consistent way to find rich or cheap conditions, time mean-reversion toward a statistically grounded target, and confirm or fade trends when the driver agrees.
Money Flow | Lyro RSMoney Flow | Lyro RS
The Money Flow is a momentum and volume-driven oscillator designed to highlight market strength, exhaustion, and potential reversal points. By combining smoothed Money Flow Index readings with volatility, momentum, and RVI-based logic, it offers traders a deeper perspective on money inflow/outflow, divergences, and overbought/oversold dynamics.
Key Features
Smoothed Money Flow Line
EMA-smoothed calculation of the MFI for noise reduction.
Clear thresholds for overbought and oversold zones.
Normalized Histogram
Histogram plots show bullish/bearish money flow pressure.
Color-coded cross logic for quick trend assessment.
Relative Volatility Index (RVI) Signals
Detects overbought and oversold conditions using volatility-adjusted RVI.
Plots ▲ and ▼ markers at exhaustion points.
Momentum Strength Gauge
Calculates normalized momentum strength from ROC and volume activity.
Displays percentage scale of current momentum force.
Divergence Detection
Bullish divergence: Price makes lower lows while money flow makes higher lows.
Bearish divergence: Price makes higher highs while money flow makes lower highs.
Plotted as diamond markers on the oscillator.
Signal Dashboard (Table Overlay)
Displays real-time status of Money Flow signals, volatility, and momentum.
Color-coded readouts for instant clarity (Long/Short/Neutral + Momentum Bias).
How It Works
Money Flow Calculation – Applies EMA smoothing to MFI values.
Normalization – Scales oscillator between relative high/low values.
Trend & Signals – Generates bullish/bearish signals based on midline and histogram cross logic.
RVI Integration – Confirms momentum exhaustion with overbought/oversold markers.
Divergences – Identifies hidden market imbalances between price and money flow.
Practical Use
Trend Confirmation – Use midline crossovers with histogram direction for money flow bias.
Overbought/Oversold Reversals – Watch RVI ▲/▼ markers for exhaustion setups.
Momentum Tracking – Monitor momentum percentage to gauge strength of current trend.
Divergence Alerts – Spot early reversal opportunities when money flow diverges from price action.
Customization
Adjust length, smoothing, and thresholds for different markets.
Enable/disable divergence detection as needed.
Personalize visuals and dashboard display for cleaner charts.
⚠️ Disclaimer
This indicator is a tool for technical analysis and does not provide guaranteed results. It should be used alongside other methods and proper risk management. The creator is not responsible for financial decisions made using this script.
Confluence StackPlease read the instructions below. The code was mostly written using AI so may contain errors. Happy trading all and good luck. ATB Richard
INTENDED USE
This indicator is designed for technical traders who want to move beyond simple buy/sell signals and gain a deeper understanding of the underlying market dynamics. It is ideal for trend followers, swing traders, and anyone looking to confirm the quality of a trend.
WHO IS THIS FOR?
Traders who want to differentiate between strong, sustainable trends and weak, unreliable moves.
Analysts looking to identify high-conviction setups backed by multiple factors (e.g., momentum confirmed by volume).
Discretionary traders who need a quick, visual tool to gauge market sentiment and avoid choppy conditions.
WHY USE IT?
Traditional indicators often give conflicting signals. The Confluence Stack solves this by aggregating multiple perspectives into one clear visual. It helps you answer not just "Is the market going up?" but "WHY is it going up, and how strong is the conviction?". This allows for more informed decision-making and helps filter out low-probability trades.
DISCLAIMER AND LICENSE
This script is for educational purposes only and is not a recommendation to buy or sell any financial instrument. All trading and investment decisions are the sole responsibility of the user. Trading involves significant risk.
This source code is subject to the terms of the Mozilla Public License 2.0 at www.mozilla.org
HOW TO USE THIS INDICATOR
This indicator is designed to show the 'character' of a market move by grouping signals into distinct categories. Instead of seeing many individual signals, you see the strength of the underlying forces driving the price.
1. READ THE HEIGHT (Strength of Confluence)
The total height of the stack shows the strength of agreement. A tall stack means many signals are aligned, indicating a high-conviction move. A short stack means weak agreement and a choppy, indecisive market.
2. READ THE COLOR (Character of the Move)
The colors tell you WHY the market is moving.
BLUE (Momentum): A stack of mostly blue shades indicates a trend driven by pure momentum. This is the 'speed' of the market.
RSI (Relative Strength Index): Measures the magnitude of recent price gains versus losses. A smooth measure of trend strength.
Stochastic Oscillator: Measures the current closing price's position within the recent high-low range. More sensitive to immediate price action.
CCI (Commodity Channel Index): Measures the price's deviation from its moving average. Excels at identifying cyclical turns.
MACD (Moving Average Convergence Divergence): A trend-following momentum indicator showing the relationship between two moving averages. Excellent for identifying the start and end of trends.
YELLOW (Volume): The appearance of yellow shades confirms the move is supported by high market participation. This is the 'fuel' for the trend.
Volume Ratio: A custom signal that triggers when buy or sell volume is unusually high compared to its recent average.
CRV (Candle Range Volume): A custom signal that looks for candles with significant price range and volume.
OBV (On-Balance Volume): A cumulative indicator that adds volume on up days and subtracts it on down days. It shows the long-term flow of money.
FUCHSIA (Volatility): A fuchsia block signals a volatility breakout. This adds a sense of urgency and confirms the price is moving with exceptional force.
Bollinger Bands: A signal triggers when the price closes outside of the upper or lower standard deviation bands.
ORANGE (Price Action): An orange block is a pure price structure signal. It's a raw statement of intent from the market.
Price Gap: A signal that triggers when there's a gap up or gap down between candles.
3. READ THE TRANSITION (Shift in Sentiment)
The most important signal from the stacks is the flip from one side of the zero line to the other.
Flipping from Negative to Positive: A bearish stack disappears and is replaced by a bullish stack. This indicates market sentiment is shifting from bearish to bullish.
Flipping from Positive to Negative: A bullish stack disappears and is replaced by a bearish stack. This warns of a potential top or the start of a new downtrend.
4. FILTER FOR NOISE (Plot Threshold)
In choppy markets, the stack can flicker with low signal counts (e.g., +1 or -1). To focus only on high-conviction moves, go to the indicator settings and increase the "Plot Threshold". A setting of 2 or 3 will hide all stacks that don't have at least 2 or 3 agreeing signals, effectively filtering out market noise and keeping your chart clean.
5. CUSTOMIZE YOUR SIGNALS (Enable/Disable)
This indicator is fully customizable. In the settings, you can enable or disable each of the 9 indicators individually. For example, if you are a pure momentum trader, you could disable all Volume, Volatility, and Price Action signals to focus only on the blue stacks. Tailor it to fit your specific trading style.
EXAMPLE INTERPRETATIONS
Strong, Confirmed Trend: A tall stack of mostly blue (Momentum) and yellow (Volume) indicates a high-quality trend backed by both speed and market participation.
Momentum-Only Trend: A tall stack of only blue is a strong momentum move, but the lack of yellow (Volume) is a warning that the move may lack the "fuel" to be sustained.
Choppy/Indecisive Market: A short, mixed-color stack flickering around the zero line means the market is choppy with no clear conviction. It's often best to stay out.
Volatility Breakout: A new stack that appears suddenly with a fuchsia (Bollinger Bands) block on its first bar suggests a volatility-driven breakout is initiating.
Exhaustion Move: An orange (Price Gap) block appearing at the peak of a tall, long-standing stack can signal an exhaustion gap, potentially marking the end of the trend.
Weakening Conviction (Divergence): If price makes a new high but the positive stack is visibly shorter than the stack at the previous price high, it suggests underlying conviction is weakening.
TZanalyserTZanalyser (Trend Zone Monitor With Trend Strength, Volume Focus And -Events Markers)
Before I used TrendZones to manage my portfolio I used Fibonacci Zone Oscillator as my favorite in the sub panel, accompanied with another subpanel indicator which I never published called IncliValue and also REVE Cohorts.
TZanalyser inherits Ideas and code from all three of them: The visual and the idea of using a channel as the basis for an oscillator depicted as a histogram, is taken from the FibZone Oscillator. The idea of providing a number to evaluate the trend is taken from IncliValue. The idea to create a horizontal line which indicates high and low volume focus completed with markers for volume events, is taken from REVE-cohorts.
These ideas are combined in one sleek visual called TZanalyser. TZ stand for TrendZones, because the histogram is based on it.
The histogram.
Depicted is the distance of the price from COG as percent. The distance between Upper Curve and Lower Curve is used as 100%. The values may reach between 300 and -300. The colors indicate in which zone the candle lives, blue in the blue zone, green in the green zone etc. Despite the absence of a gray zone, there are gray bars. These depict candles that wrap around COG. Because hl2 is used as price, some gray bars point up and others down. The orange and red bars point down because the orange and red downtrend zones are below COG.
Use of the histogram.
Sometimes I need to create a list of stocks which are in uptrend in monthly, weekly and daily charts from the stocks I follow in my universe. This job is done fast and easy by looking at the last bar of the histogram. The histogram also gives a quick evaluation of how the stock fared in the past.
The number.
Suppose I need to allocate some money to another stock, selected a few, looked into news and gurus and they look equally good. Then it is nice to be able to find out which has the best charts. Which one has the strongest uptrend. For this purpose this number can be consulted, because it indicates somehow the strength of the trend. It is an integer between 20 and -20, the closer to 20 the stronger the uptrend, closer to -20 indicates a stronger downtrend. The color of the background is the same as the last column of the histogram.
Volume focus and events
The horizontal lines depict volume focus, the line below the focus that comes with the uptrend columns pointing up, the one above the focus for the downtrend columns pointing down. Thes line have tree colors: maroon for high volume focus, green for normal volume and gray for low volume situations. Between the lines and the histogram triangles appear at volume events, a green triangle when the candle comes with high volume, i.e. 120-200 percent of normal, maroon when extreme volume, i.e. more than 200 percent of normal.
The direction of these triangles is that of the histogram, i.e. when the price is higher, direction is up and vice versa.
Take care and have fun.
Flux Capacitor (FC)# Flux Capacitor
**A volume-weighted, outlier-resistant momentum oscillator designed to expose hidden directional pressure from institutional participants.**
---
### Why "Flux Capacitor"?
The name pays homage to the fictional energy core in *Back to the Future* — an invisible engine that powers movement. Similarly, this indicator detects whether price movement is being powered by real market participation (volume) or if it's coasting without conviction.
---
### Methodology
The Flux Capacitor fuses three statistical layers:
- **Normalized Momentum**: `(Close – Open) / ATR`
Controls for raw price size and volatility.
- **Volume Scaling**:
Amplifies the effect of price moves that occur with elevated volume.
- **Robust Normalization**:
- *Winsorization* caps outlier spikes.
- *MAD-Z scoring* normalizes the signal across assets (crypto, futures, stocks).
- This produces consistent scaling across timeframes and symbols.
The result is a smooth oscillator that reliably indicates **liquidity-backed momentum** — not just price movement.
---
### Signal Events
- **Divergence (D)**: Price makes higher highs or lower lows, but Flux does not.
- **Absorption (A)**: Candle shows high volume and small body, while Flux opposes the candle direction — indicates smart money stepping in.
- **Compression (◆)**: High volume with low momentum — potential breakout zone.
- **Zero-Cross**: Indicates directional regime flip.
- **Flux Acceleration**: Histogram shows pressure rate of change.
- **Regime Background**: Color fades with weakening trend conviction.
All signals are color-coded and visually compact for easy pattern recognition.
---
### Interpreting Divergence & Absorption Correctly
Signal strength improves significantly when it appears **in the correct zone**:
#### Divergence:
| Signal | Zone | Meaning | Strength |
|--------|------------|------------------------------------------|--------------|
| Green D | Below 0 | Bullish reversal forming in weakness | **Strong** |
| Green D | Above 0 | Bullish, but less convincing | Moderate |
| Red D | Above 0 | Bearish reversal forming in strength | **Strong** |
| Red D | Below 0 | Bearish continuation — low warning value | Weak |
#### Absorption:
| Signal | Zone | Meaning | Strength |
|--------|------------|-----------------------------------------|--------------|
| Green A | Below 0 | Buyers absorbing panic-selling | **Strong** |
| Green A | Above 0 | Support continuation | Moderate |
| Red A | Above 0 | Sellers absorbing FOMO buying | **Strong** |
| Red A | Below 0 | Trend continuation — not actionable | Weak |
Look for **absorption or divergence signals in “enemy territory”** for the most actionable entries.
---
### Reducing Visual Footprint
If your chart shows a long line of numbers across the top of the Flux Capacitor pane (e.g. "FC 14 20 9 ... Bottom Right"), it’s due to TradingView’s *status line input display*.
**To fix this**:
Right-click the indicator pane → **Settings** → **Status Line** tab → uncheck “Show Indicator Arguments”.
This frees up vertical space so top-edge signals (like red `D` or yellow `◆`) remain visible and unobstructed.
---
### Features
- Original MAD-Z based momentum design
- True volume-based divergence and absorption logic
- Built-in alerts for all signal types
- Works across timeframes (1-min to weekly)
- Minimalist, responsive layout
- 25+ customizable parameters
- No future leaks, no repainting
---
### Usage Scenarios
- **Trend confirmation**: Flux > 0 confirms bullish trend strength
- **Reversal detection**: Divergence or absorption in opposite territory = high-probability reversal
- **Breakout anticipation**: Compression signal inside range often precedes directional move
- **Momentum shifts**: Watch for zero-crosses + flux acceleration spikes
---
### ⚠ Visual Note for BTC, ETH, Crude Oil & Futures
These high-priced or rapidly accelerating instruments can visually compress any linear oscillator. You may notice the Flux Capacitor’s line appears "flat" or muted on these assets — especially over long lookbacks.
> **This does not affect signal validity.** Divergence, absorption, and compression triggers still fire based on underlying logic — only the line’s amplitude appears reduced due to scaling constraints.
---
### Disclaimer
This indicator is for educational purposes only. It is not trading advice. Past results do not guarantee future performance. Use in combination with your own risk management and analysis.
Multiple Values TableThis Pine Script indicator, named "Multiple Values Table," provides a comprehensive view of various technical indicators in a tabular format directly on your trading chart. It allows traders to quickly assess multiple metrics without switching between different charts or panels.
Key Features:
Table Position and Size:
Users can choose the position of the table on the chart (e.g., top left, top right).
The size of the table can be adjusted (e.g., tiny, small, normal, large).
Moving Averages:
Calculates the 5-day Exponential Moving Average (5DEMA) using daily data.
Calculates the 5-week and 20-week EMAs (5WEMA and 20WEMA) using weekly data.
Indicates whether the current price is above or below these moving averages in percentage terms.
Drawdown and Williams VIX Fix:
Computes the drawdown from the 365-day high to the current close.
Calculates the Williams VIX Fix (WVF), which measures the volatility of the asset.
Shows both the current WVF and a 2% drawdown level.
Relative Strength Index (RSI):
Displays the current RSI and compares it to the RSI from 14 days ago.
Indicates whether the RSI is increasing, decreasing, or flat.
Stochastic RSI:
Computes the Stochastic RSI and compares it to the value from 14 days ago.
Indicates whether the Stochastic RSI is increasing, decreasing, or flat.
Normalized MACD (NMACD):
Calculates the Normalized MACD values.
Indicates whether the MACD is increasing, decreasing, or flat.
Awesome Oscillator (AO):
Calculates the AO on a daily timeframe.
Indicates whether the AO is increasing, decreasing, or flat.
Volume Analysis:
Displays the average volume over the last 22 days.
Shows the current day's volume as a percentage of the average volume.
Percentile Calculations:
Calculates the current percentile rank of the WVF and ATH over specified periods.
Indicates the percentile rank of the current volume percentage over the past period.
Table Display:
All these values are presented in a neatly formatted table.
The table updates dynamically with the latest data.
Example Use Cases:
Comprehensive Market Analysis: Quickly assess multiple indicators at a glance.
Trend and Momentum Analysis: Identify trends and momentum changes based on various moving averages and oscillators.
Volatility and Drawdown Monitoring: Track volatility and drawdown levels to manage risk effectively.
This script offers a powerful tool for traders who want to have a holistic view of various technical indicators in one place. It provides flexibility in customization and a user-friendly interface to enhance your trading experience.
Stochastic Vix Fix SVIX (Tartigradia)The Stochastic Vix or Stochastic VixFix (SVIX), just like the Williams VixFix, is a realized volatility indicator, and can help in finding market bottoms as well as tops without requiring bollinger bands or any other construct, as the SVIX is bounded between 0-100 which allows for an objective thresholding regardless of the past.
Mathematically, SVIX is the complement of the original Stochastic Oscillator, with such a simple transform reproducing Williams' VixFix and the VIX index signals of high volatility and hence of market bottoms quite accurately but within a bounded 0-100 range. Having a predefined range allows to find markets bottoms without needing to compare to past prices using a bollinger band (Chris Moody on TradingView) nor a moving average (Hesta 2015), as a simple threshold condition (by default above 80) is sufficient to reliably signal interesting entry points at bottoming prices.
Having a predefined range allows to find markets bottoms without needing to compare to past prices using a bollinger band (Chris Moody on TradingView) nor a moving average (Hesta 2015), as a simple threshold condition (by default above 80) is sufficient to reliably signal interesting entry points at bottoming prices.
Indeed, as Williams describes in his paper, markets tend to find the lowest prices during times of highest volatility, which usually accompany times of highest fear.
Although the VixFix originally only indicates market bottoms, the Stochastic VixFix can also indicate good times to exit, when SVIX is at a low value (default: below 20), but just like the original VixFix and VIX index, exit signals are as usual much less reliable than long entries signals, because: 1) mature markets such as SP500 tend to increase over the long term, 2) when market fall, retail traders panic and hence volatility skyrockets and bottom is more reliably signalled, but at market tops, no one is panicking, price action only loses momentum because of liquidity drying up.
Compared to Hesta 2015 strategy of using a moving average over Williams' VixFix to generate entry signals, SVIX generates much fewer false positives during ranging markets, which drastically reduce Hesta 2015 strategy profitability as this incurs quite a lot of losses.
This indicator goes further than the original SVIX, by restoring the smoothed D and second-level smoothed D2 oscillators from the original Stochastic Oscillator, and use a 14-period ZLMA instead of the original 20-period SMA, to generate smoother yet responsive signals compared to using just the raw SVIX (by default, this is disabled, as the original raw SVIX is used to produce more entry signals).
Usage:
Set the timescale to daily or weekly preferably, to reduce false positives.
When the background is highlighted in green or when the highlight disappears, it is usually a good time to enter a long position.
Red background highlighting can be enabled to signal good exit zones, but these generate a lot of false positives.
To further reduce false positives, the SVIX_MA can be used to generate signals instead of the raw SVIX.
For more information on Williams' Vix Fix, which is a strategy published under public domain:
The VIX Fix, Larry Williams, Active Trader magazine, December 2007, web.archive.org
Fixing the VIX: An Indicator to Beat Fear, Amber Hestla-Barnhart, Journal of Technical Analysis, March 13, 2015, ssrn.com
For more information on the Stochastic Vix Fix (SVIX), published under Creative Commons:
Replicating the CBOE VIX using a synthetic volatility index trading algorithm, Dayne Cary and Gary van Vuuren, Cogent Economics & Finance, Volume 7, 2019, Issue 1, doi.org
Note: strangely, in the paper, the authors failed to mention that the SVIX is the complement of the original Stochastic Oscillator, instead reproducing just the original equation. The correct equation for the SVIX was retroengineered by comparing charts they published in the paper with charts generated by this pinescript indicator.
For a more complete indicator, see:
Dynamic Zone Range on PDFMA [Loxx]Dynamic Zone Range on PDFMA is a Probability Density Function Moving Average oscillator with Dynamic Zones.
What is Probability Density Function?
Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included
4 signal types
Bar coloring
Alerts
Channels fill
Smoke And MirrorsSmoke And Mirrors is an indicator combining few simple but often used indicators to a delightfully visual presentation. Smoke And Mirrors features a generic SMA from where it derives BBands and a Standard Deviation band, and in it's default configuration offers a small timescale Average True Range and also matches the generic SMA against VWAP in an oscillatory fashion. And that's not all! It also has very unique voodoo on top of it all, charting the distance between open and close and the distance between high and low based on the average of open, close, high and low. It's pretty intuitive and while the settings have numerous variables to tweak, they're mostly related to how the colors are displayed so you can set it up to match your current charts colors. The default settings are meant for charts with a normal change of around 1 unit, so if you're charting something that's in it's tens of thousands and varies daily by a 1000 or more, you might want to tone the "rate-of-change" numbers down to all the way to 1. Other than that, it's recommended that you play around with the numbers a little bit so that you know which band represents which indicator.
Don't hesitate to use any or all parts of the indicator in your own scripts! There's a handy hsva function that yields rgb color with transparency based on hue(0-360), saturation (0-1), value (0-1) and alpha (0-1) and plenty of examples on how to utilize it.
[blackcat] L2 Improved Jeffrey Owen Cyclical SystemLevel: 2
Background
In Jeffrey Owen Katz's article "Trading stocks with a cyclical system" he introduces the Stock Rhythm System. I found the central part is quite similar to KDJ indicator and I use my own KDJ algo to enhance its performance.
Function
Jeffrey Owen Katz has a customized stochastic indicator. I used it as the engine of my own KDJ trading system. My KDJ oscillator display consists of 3 lines (K, D and J - hence the name of the display) and 2 levels. K and D are the same lines you see when using the stochastic oscillator. The J line in turn represents the deviation of the D value from the K value. The convergence of these lines indicates new trading opportunities. Just like the Stochastic Oscillator, oversold and overbought levels correspond to the times when the trend is likely to reverse. Just as the Stochastic, the KDJ has the K & D lines, plus the J. This last one represents the divergence from the K-line. When all three converge, it usually signals a possible trend forming. Labels and alerts are added for long and short entries.
Key Signal
KVal --> K.
DVal --> D.
JVal --> J.
Remarks
This is a Level 2 free and open source indicator.
Feedbacks are appreciated.
Awesome Oscillator & MACD Cross TacticOscillator for Tradingview based on MACD and Awesome Oscillator. This oscillator is designed to identify potential local growth or decline in prices as part of a trend movement.
For some ridiculous reason I am not allowed to attach screenshots of graphs and links on TradingView, so I hope that you will find my detailed instructions on my github page: github.com/samgozman/AO-MACD-cross-tradingview
Hybrid Overbought/Oversold Detector + Put/Call SignalsThere are many indicators of overbought/oversold conditions out there. Some of more common ones are:
- Bollinger Bands %B
- Money Flow Index (MFI)
- Relative Strength Index (RSI)
- Stochastic
This script uses a combination of these 4 oscillators to confirm overbought/oversold and filter the signals of market reverse which could be used for trading binary options.
You may select which oscillators you want to apply and of course change the source, the length of the calculations and the overbought/oversold levels.
Also the script will draw a combined graph which is the average of the selected oscillators in the options.
Send me your ideas!
Combo Backtest 123 Reversal & ECO Strategy This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
We call this one the ECO for short, but it will be listed on the indicator list
at W. Blau’s Ergodic Candlestick Oscillator. The ECO is a momentum indicator.
It is based on candlestick bars, and takes into account the size and direction
of the candlestick "body". We have found it to be a very good momentum indicator,
and especially smooth, because it is unaffected by gaps in price, unlike many other
momentum indicators.
We like to use this indicator as an additional trend confirmation tool, or as an
alternate trend definition tool, in place of a weekly indicator. The simplest way
of using the indicator is simply to define the trend based on which side of the "0"
line the indicator is located on. If the indicator is above "0", then the trend is up.
If the indicator is below "0" then the trend is down. You can add an additional
qualifier by noting the "slope" of the indicator, and the crossing points of the slow
and fast lines. Some like to use the slope alone to define trend direction. If the
lines are sloping upward, the trend is up. Alternately, if the lines are sloping
downward, the trend is down. In this view, the point where the lines "cross" is the
point where the trend changes.
When the ECO is below the "0" line, the trend is down, and we are qualified only to
sell on new short signals from the Hi-Lo Activator. In other words, when the ECO is
above 0, we are not allowed to take short signals, and when the ECO is below 0, we
are not allowed to take long signals.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Strategy 123 Reversal & ECO This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
We call this one the ECO for short, but it will be listed on the indicator list
at W. Blau’s Ergodic Candlestick Oscillator. The ECO is a momentum indicator.
It is based on candlestick bars, and takes into account the size and direction
of the candlestick "body". We have found it to be a very good momentum indicator,
and especially smooth, because it is unaffected by gaps in price, unlike many other
momentum indicators.
We like to use this indicator as an additional trend confirmation tool, or as an
alternate trend definition tool, in place of a weekly indicator. The simplest way
of using the indicator is simply to define the trend based on which side of the "0"
line the indicator is located on. If the indicator is above "0", then the trend is up.
If the indicator is below "0" then the trend is down. You can add an additional
qualifier by noting the "slope" of the indicator, and the crossing points of the slow
and fast lines. Some like to use the slope alone to define trend direction. If the
lines are sloping upward, the trend is up. Alternately, if the lines are sloping
downward, the trend is down. In this view, the point where the lines "cross" is the
point where the trend changes.
When the ECO is below the "0" line, the trend is down, and we are qualified only to
sell on new short signals from the Hi-Lo Activator. In other words, when the ECO is
above 0, we are not allowed to take short signals, and when the ECO is below 0, we
are not allowed to take long signals.
WARNING:
- For purpose educate only
- This script to change bars colors.
Stochastic Direction StrategyThis is a simple strategy based on the Stochastic Oscillator: stockcharts com/school/doku.php?id=chart_school:technical_indicators:stochastic_oscillator_fast_slow_and_full
Its purpose is to gradually build a position in a trending market (as of June 26th 2016 in most cryptocurrencies).
Inputs:
- direction (long/short)
- overbought/oversold
- close positions (yes/no to only increase positions)
Outputs:
- buy/sell/close signals plotted on a chart below
This script can easily be used as a TradingView study (for alerts) and a strategy (for backtesting). See the comments in the code.
I have added additional alert conditions to be used easily together with a trading bot reading the signals
Yet obviously you can also do manual trading on each alert.
Minimal Godmode 2.1// Acknowledgments:
// Original Godmode Authors:
// @Legion, @LazyBear, @Ni6HTH4wK, @xSilas
// Drop a line if you use or modify this code.
// Godmode 3.1.4: @SNOW_CITY
// Godmode 3.2: @sco77m4r7in and @oh92
// Godmode3.2+LSMA: @scilentor
// Godmode 4.0.0-4.0.1: @chrysopoetics
// Jurik Moving Average: @everget
// Constance Brown Composite Index RSI: @LazyBear
// Wavetrend Oscillator: @fskrypt
// TTM Squeeze: @Greeny
// True TSI/RSI: @cI8DH and @chrysopoetics
// Laguerre RSI (Self-Adjusting Alpha with Fractals Energy): @everget
// RSI Shaded: @mortdiggiddy
// Minimal Godmode v2.0:
// 6 BTC pairs/exchanges (instead of 11) to reduce loading time from the pinescript security() function
// Volume Composite for engine calculation
// TTM Squeeze on Wavetrend Signal
// Constance Brown Composite Index RSI (CBCI)
// TrueTSI (Godmode 4.0.0 implementation)
// Laguerre RSI (LRSI)
// Minimal Godmode v2.1:
// Removed TTM Squeeze and Volume Composite
// EMA for Wavetrend Signal
// Multi-exchange for BTC no longer the default
// mg engine toggle for CBCI, Laguerre RSI, and TTSI
// Wavetrend Histogram component toggle
True Balance of powerThis is an improvement of the script published by LazyBear,
The improvements are:
1. it includes gaps because it uses true range in stead of the current bar,
2. it has been turned into a percent oscillator as the basic algorithm belongs in the family of stochastic oscillators.
Unlike the usual stochatics I refrained from over the top averaging and smoothing, nor did I attempt a signal line. There’s no need to make a mock MACD.
The indicator should be interpreted as a stochastics, the difference between Stochs and MACD is that stochs report inclinations, i.e. in which direction the market is edging, while MACD reports movements, in which direction the market is moving. Stochs are an early indicator, MACD is lagging. The emoline is a 30 period linear regression, I use linear regressions because these have no lagging, react immidiately to changes, I use a 30 period version because that is not so nervous. You might say that an MA gives an average while a linear regression gives an ‘over all’ of the periods.
The back ground color is red when the emoline is below zero, that is where the market ‘looks down’, white where the market ‘looks up’. This doesn’t mean that the market will actually go down or up, it may allways change its mind.
Have fun and take care, Eykpunter.
Z-Score Momentum | MisinkoMasterThe Z-Score Momentum is a new trend analysis indicator designed to catch reversals, and shifts in trends by comparing the "positive" and "negative" momentum by using the Z-Score.
This approach helps traders and investors get unique insight into the market of not just Crypto, but any market.
A deeper dive into the indicator
First, I want to cover the "Why?", as I believe it will ease of the part of the calculation to make it easier to understand, as by then you will understand how it fits the puzzle.
I had an attempt to create a momentum oscillator that would catch reversals and provide high tier accuracy while maintaining the main part => the speed.
I thought back to many concepts, divergences between averages?
- Did not work
Maybe a MACD rework?
- Did not work with what I tried :(
So I thought about statistics, Standard Deviation, Z-Score, Sharpe/Sortino/Omega ratio...
Wait, was that the Z-Score? I only tried the For Loop version of it :O
So on my way back from school I formulated a concept (originaly not like this but to that later) that would attempt to use the Z-Score as an accurate momentum oscillator.
Many ideas were falling out of the blue, but not many worked.
After almost giving up on this, and going to go back to developing my strategies, I tried one last thing:
What if we use divergences in the average, formulated like a Z-score?
Surprise-surprise, it worked!
Now to explain what I have been so passionately yapping about, and to connect the pieces of the puzzle once and for all:
The indicator compares the "strength" of the bullish/bearish factors (could be said differently, but this is my "speach bubble", and I think this describes it the best)
What could we use for the "bullish/bearish" factors?
How about high & low?
I mean, these are by definitions the highest and lowest points in price, which I decided to interpret as: The highest the bull & bear "factors" achieved that bar.
The problem here is comparison, I mean high will ALWAYS > low, unless the asset decided to unplug itself and stop moving, but otherwise that would be unfair.
Now if I use my Z-score, it will get higher while low is going up, which is the opposite of what I want, the bearish "factor" is weaker while we go up!
So I sat on my ret*rded a*s for 25 minutes, completly ignoring the fact the number "-1" exists.
Surprise surprise, multiplying the Z-Score of the low by -1 did what I wanted!
Now it reversed itself (magically). Now while the low keeps going down, the bear factor increases, and while it goes up the bear factor lowers.
This was btw still too noisy, so instead of the classic formula:
a = current value
b = average value
c = standard deviation of a
Z = (a-b)/c
I used:
a = average value over n/2 period
b = average value over n period
c = standard deviation of a
Z = (a-b)/c
And then compared the Z-Score of High to the Z-Score of Low by basic subtraction, which gives us final result and shows us the strength of trend, the direction of the trend, and possibly more, which I may have not found.
As always, this script is open source, so make sure to play around with it, you may uncover the treasure that I did not :)
Enjoy Gs!
