3_SMA_Strategy_V-Singhal by ParthibIndicator Name: 3_SMA_Strategy_V-Singhal by Parthib
Description:
The 3_SMA_Strategy_V-Singhal by Parthib is a dynamic trend-following strategy that combines three key simple moving averages (SMA) — SMA 20, SMA 50, and SMA 200 — to generate buy and sell signals. This strategy uses these SMAs to capture and follow market trends, helping traders identify optimal entry (buy) and exit (sell) points. Additionally, the strategy highlights the closing price (CP), which plays a critical role in confirming buy and sell signals.
The strategy also features a Second Buy Signal triggered if the price falls more than 10% after an initial buy signal, providing a re-entry opportunity with a different visual highlight for the second buy signal.
Features:
Three Simple Moving Averages (SMA):
SMA 20: Short-term moving average reflecting immediate market trends.
SMA 50: Medium-term moving average showing the prevailing trend.
SMA 200: Long-term moving average that indicates the overall market trend.
Buy Signal (B1):
Triggered when:
SMA 200 > SMA 50 > SMA 20, indicating a bullish market structure.
The closing price is positioned below all three SMAs, confirming a potential upward reversal.
A green label appears at the low of the bar with the text B1-Price, indicating the price at which the buy signal is generated.
Second Buy Signal (B2):
Triggered if the price falls more than 10% after the first buy signal, providing an opportunity to re-enter the market at a potentially better price.
A blue label appears at the low of the bar with the text B2-Price, showing the price at which the second buy opportunity arises.
Sell Signal (S):
Triggered when:
SMA 20 > SMA 50 > SMA 200, indicating a bearish trend.
The closing price (CP) is positioned above all three SMAs, confirming a potential downward movement.
A red label appears at the high of the bar with the text S-Price, showing the price at which the sell signal is triggered.
How It Works:
Buy Conditions:
SMA 200 > SMA 50 > SMA 20: Indicates a bullish market where the long-term trend (SMA 200) is above the medium-term (SMA 50), and the medium-term trend is above the short-term (SMA 20).
Closing price below all three SMAs: Confirms that the price is in a favorable position for a potential upward reversal.
Sell Conditions:
SMA 20 > SMA 50 > SMA 200: This setup indicates a bearish trend.
Closing price above all three SMAs: Confirms that the price is in a favorable position for a potential downward movement.
Second Buy Signal (B2): If the price falls more than 10% after the first buy signal, the strategy triggers a second buy opportunity (B2) at a potentially better price. This helps traders take advantage of pullbacks or corrections after an initial favorable entry.
Labeling System:
B1-Price: The first buy signal label, appearing when the market is bullish and the closing price is below all three SMAs.
B2-Price: The second buy signal label, triggered if the price falls more than 10% after the initial buy signal.
S-Price: The sell signal label, appearing when the market turns bearish and the closing price is above all three SMAs.
How to Use:
Add the Indicator: Add "3_SMA_Strategy_V-Singhal by Parthib" to your chart on TradingView.
Interpret Buy Signals (B1): Look for green labels with the text "B1-Price" when the closing price (CP) is below all three SMAs and the trend is bullish.
Interpret Second Buy Signals (B2): If the price falls more than 10% after the first buy, look for blue labels with "B2-Price" and a re-entry opportunity.
Interpret Sell Signals (S): Look for red labels with the text "S-Price" when the market turns bearish, and the closing price (CP) is above all three SMAs.
Conclusion:
The 3_SMA_Strategy_V-Singhal by Parthib is an efficient and simple trend-following tool for traders looking to make informed buy and sell decisions. By combining the power of three SMAs and the closing price (CP) confirmation, this strategy helps traders to buy when the market shows a strong bullish setup and sell when the trend turns bearish. Additionally, the second buy signal feature ensures that traders don’t miss out on re-entry opportunities after price corrections, giving them a chance to re-enter the market at a favorable price.
Cerca negli script per "bear"
EMA Cloud Matrix with Trend Tablethis script builds upon a standard exponential moving average (ema) by adding volatility-based dynamic bands and persistent trend detection. it also enhances decision-making by including visual indicators (labels and clouds), a multi-timeframe trend table, and optional retest signals. here's an in-depth explanation:
volatility-based bands:
instead of just plotting an ema line, this script creates an upper and lower band around the ema using the average volatility (calculated as the average range of high-low over 100 bars).
the bands represent areas where price is likely to deviate significantly from the ema, signaling potential trend shifts.
persistent trend detection:
a persistent trend variable updates when price crosses above the upper band (bullish trend) or below the lower band (bearish trend). this ensures that the trend state persists until a new cross event occurs.
normal emas don't store such states—they merely provide a lagging representation of price.
visual enhancements:
a color-coded cloud dynamically highlights the area between the ema and the current trend line (upper or lower band), making trend direction clearer.
labels mark significant crossover or crossunder events, serving as potential buy or sell signals.
multi-timeframe trend table:
the table shows the trend direction (buy/sell) for the 15-minute, 4-hour, and daily timeframes, giving a broader perspective for trading decisions.
optional retest signals:
when enabled, it identifies situations where price tests the ema after trending away, providing additional opportunities for entries or exits.
first time ever - why use this and how?
why use this?
this is ideal for traders who:
struggle with trend-following strategies that lack clear entry/exit rules.
want a hybrid system combining ema-based smoothness with volatility-based adaptability.
need to visualize trends in multiple timeframes without switching charts.
how to use this?
buy signal: when the price crosses above the upper band, the trend flips to bullish. you’ll see a green upward arrow (▲) on the chart, indicating a potential long entry.
sell signal: when the price crosses below the lower band, the trend flips to bearish. a blue downward arrow (▼) appears on the chart, signaling a potential short entry.
retest signals (optional): if the price comes back to test the ema during a trend, a retest label can guide you for a secondary entry.
exit based on risk-reward ratio (rr)
this script doesn't explicitly calculate risk-reward ratios (rr), but you can manage exits effectively using the following ideas:
set a defined stop-loss:
if entering on a buy signal (crossover above upper band), place a stop below the ema or the lower band. for short signals, use the upper band as a stop.
this ensures the stop-loss dynamically adjusts with volatility.
use rr to set targets:
decide on a risk-reward ratio like 1:2 or 1:3. for example:
if your stop-loss is 20 points below your entry, set your target 40 or 60 points above for a 1:2 or 1:3 rr.
you can use trailing stops to lock in profits as the trend continues.
exit on opposite signal:
if the trend changes (e.g., price crosses below the lower band in a bullish trade), close the position.
how it gives signals and when to buy or sell
signal logic:
buy signal (bullish crossover):
when the price crosses above the upper band, the script marks it as a bullish trend and plots a green arrow (▲).
sell signal (bearish crossunder):
when the price crosses below the lower band, the script identifies it as a bearish trend and plots a blue arrow (▼).
trend continuation:
the trend state persists until the opposite condition occurs, helping you avoid noise or whipsaws.
multi-timeframe insights:
consult the trend table for confirmation across timeframes. for example:
if the 15-minute and 4-hour timeframes align with a buy trend, it strengthens the case for a long trade.
conflicting signals might suggest waiting for further confirmation.
using retest signals:
during strong trends, price often revisits the ema before resuming. if the optional retest signals are enabled, you’ll see labels at these points. they can be used to:
add to an existing position.
enter a trade if you missed the initial breakout.
key event: price crosses above the upper band
when the price closes above the upper band (ema + volatility buffer), the script identifies a bullish trend.
a green upward arrow (▲) is plotted on the chart, signaling the beginning of a long trend.
visual confirmation:
the cloud between the ema and the trend line (lower band) is filled with a light green color, representing a bullish phase.
the trend table will display "buy" with an upward arrow for the respective timeframe(s).
actionable insight:
entry: take a long position when the green ▲ appears, confirming a bullish crossover.
continuation trades: use the optional retest signals to identify pullbacks to the ema as opportunities to add to the long position.
exit: close the position when a bearish crossunder (sell signal) occurs.
identifying short trends (sell signal)
key event: price crosses below the lower band
when the price closes below the lower band (ema - volatility buffer), the script identifies a bearish trend.
a blue downward arrow (▼) is plotted on the chart, signaling the beginning of a short trend.
visual confirmation:
the cloud between the ema and the trend line (upper band) is filled with a light blue color, representing a bearish phase.
the trend table will display "sell" with a downward arrow for the respective timeframe(s).
actionable insight:
entry: take a short position when the blue ▼ appears, confirming a bearish crossunder.
continuation trades: use the optional retest signals to identify rallies back to the ema as opportunities to add to the short position.
exit: close the position when a bullish crossover (buy signal) occurs.
what makes it different from other ema indicators?
dynamic volatility adaptation:
standard ema indicators only track the average price over a given period, making them susceptible to market noise in highly volatile conditions.
this script uses a volatility buffer (average true range of high-low) to create upper and lower bands around the ema, filtering out insignificant movements and focusing on meaningful breakouts.
persistent trend logic:
unlike traditional emas that simply follow price direction, this script maintains a persistent trend state until a clear crossover or crossunder occurs:
bullish trends persist above the upper band.
bearish trends persist below the lower band.
this minimizes whipsaws in choppy markets.
visual enhancements:
the trend-colored cloud (green for long trends, blue for short trends) helps you quickly identify the market’s state.
labels (▲ and ▼) mark critical entry signals, making it easier to spot potential trades.
multi-timeframe trend confirmation:
the trend table integrates higher and lower timeframes, providing a multi-timeframe perspective:
short-term (15 minutes) for active trading.
medium-term (4 hours) for swing positions.
long-term (daily) for overall trend direction.
optional retest signals:
most ema-based strategies miss the retest phase after a breakout.
this script includes an optional feature to identify pullbacks to the ema during a trend, helping traders enter or add positions at better prices.
all-in-one system:
while traditional ema indicators only show a smoothed average line, this script integrates trend detection, volatility bands, visual aids, and multi-timeframe analysis in a single tool, reducing the need for additional indicators.
summary
this script goes beyond a simple ema by incorporating trend persistence, volatility bands, and multi-timeframe analysis. buy signals occur when price crosses above the upper band, initiating a long trend, while sell signals occur when price crosses below the lower band, initiating a short trend. it stands out due to its ability to adapt to market conditions, provide clear visual cues, and avoid the noise common in standard ema-based systems.
Enhanced RSIEnhanced RSI with Phases, Divergences & Volume Control:
This advanced RSI indicator expands on the traditional Relative Strength Index by introducing dynamic exhaustion phase detection, automatic divergence identification, and volume-based control evaluation. It provides traders with actionable insights into trend momentum, potential reversals, and market dominance.
Key Features:
Dynamic Exhaustion Phases:
Identifies real phases of the RSI based on slope and momentum:
Acceleration: Momentum increasing rapidly (green phase).
Deceleration: Momentum weakening (red phase).
Plateau: Momentum flattening (yellow phase).
Neutral: No significant momentum shift detected.
Phases are displayed dynamically in a box on the chart.
Automatic Divergence Detection:
Bullish Divergence: Identified when price makes a lower low while RSI makes a higher low.
Bearish Divergence: Identified when price makes a higher high while RSI makes a lower high.
Divergences are marked directly on the RSI chart with labeled circles.
Volume-Based Control Evaluation:
Analyzes price action relative to volume to determine market dominance:
Bulls in Control: Closing price is higher than the opening price.
Bears in Control: Closing price is lower than the opening price.
Neutral: No significant dominance (closing equals opening).
Volume status is displayed alongside the RSI phase in the chart’s top-left box.
Custom RSI Plot:
Includes overbought (70), oversold (30), and neutral (50) levels for easier interpretation of market conditions.
RSI plotted in blue for clarity.
How to Use:
Add to Chart:
Apply this indicator to any chart in TradingView.
Interpret the RSI Phase Box:
Use the RSI phase (Acceleration, Deceleration, Plateau, Neutral) to identify trend momentum.
Combine the phase with the volume status (Bulls or Bears in Control) to confirm market sentiment.
Identify Divergences:
Look for Bullish Divergence (potential upward reversal) or Bearish Divergence (potential downward reversal) marked directly on the RSI chart.
Adjust Settings:
Customize the RSI period, phase sensitivity, and divergence lookback period to fit your trading style.
Disclaimer:
This indicator is a tool to assist with technical analysis. It is not a financial advice or a guarantee of market performance. Always combine this indicator with other methods or strategies for better results.
GMO (Gyroscopic Momentum Oscillator) GMO
Overview
This indicator fuses multiple advanced concepts to give traders a comprehensive view of market momentum, volatility, and potential turning points. It leverages the Gyroscopic Momentum Oscillator (GMO) foundation and layers on IQR-based bands, dynamic ATR-adjusted OB/OS levels, torque filtering, and divergence detection. The outcome is a versatile tool that can assist in identifying both short-term squeezes and long-term reversal zones while detecting subtle shifts in momentum acceleration.
Key Components:
Gyroscopic Momentum Oscillator (GMO) – A physics-inspired metric capturing trend stability and momentum by treating price dynamics as “angle,” “angular velocity,” and “inertia.”
IQR Bands – Highlight statistically typical oscillation ranges, providing insight into short-term squeezes and potential near-term trend shifts.
ATR-Adjusted OB/OS Levels – Dynamic thresholds for overbought/oversold conditions, adapting to volatility, aiding in identifying long-term potential reversal zones.
Torque Filtering & Scaling – Smooths and thresholds torque (the rate of change of momentum) and visually scales it for clarity, indicating sudden force changes that may precede volatility adjustments.
Divergence Detection – Highlights potential reversal cues by comparing oscillator swings against price swings, revealing regular and hidden bullish/bearish divergences.
Conceptual Insights
IQR Bands (Short-Term Squeeze & Trend Direction):
Short-Term Momentum and Squeeze: The IQR (Interquartile Range) bands show where the oscillator tends to “live” statistically. When the GMO line hovers within compressed IQR bands, it can signal a momentum squeeze phase. Exiting these tight ranges often correlates with short-term breakout opportunities.
Trend Reversals: If the oscillator pushes beyond these IQR ranges, it may indicate an emerging short-term trend change. Traders can watch for GMO escaping the IQR “comfort zone” to anticipate a new directional move.
Dynamic OB/OS Levels (Long-Term Reversal Zones):
ATR-Based Adaptive Thresholds: Instead of static overbought/oversold lines, this tool uses ATR to adjust OB/OS boundaries. In calm markets, these lines remain closer to ±90. As volatility rises, they approach ±100, reflecting greater permissible swings.
Long-Term Trend Reversal Potential: If GMO hits these dynamically adjusted OB/OS extremes, it suggests conditions ripe for possible long-term trend reversals. Traders seeking major inflection points may find these adaptive levels more reliable than fixed thresholds.
Torque (Sudden Force & Directional Shifts):
Momentum Acceleration Insight: Torque represents the second derivative of momentum, highlighting how quickly momentum is changing. High positive torque suggests a rapidly strengthening bullish force, while high negative torque warns of sudden bearish pressure.
Early Warning & Stability/Volatility Adjustments: By monitoring torque spikes, traders can anticipate momentum shifts before price fully confirms them. This can signal imminent changes in stability or increased volatility phases.
Indicator Parameters and Usage
GMO-Related Inputs:
lenPivot (Default 100): Length for calculating the pivot line (slow market axis).
lenSmoothAngle (Default 200): Smooths the angle measure, reducing noise.
lenATR (Default 14): ATR period for scaling factor, linking price changes to volatility.
useVolatility (Default true): If true, volatility (ATR) influences inertia, adjusting momentum calculations.
useVolume (Default false): If true, volume affects inertia, adding a liquidity dimension to momentum.
lenVolSmoothing (Default 50): Smooths volume calculations if useVolume is enabled.
lenMomentumSmooth (Default 20): EMA smoothing of GMO for a cleaner oscillator line.
normalizeRange (Default true): Normalizes GMO to a fixed range for consistent interpretation.
lenNorm (Default 100): Length for normalization window, ensuring GMO’s scale adapts to recent extremes.
IQR Bands Settings:
iqrLength (Default 14): Period to compute the oscillator’s statistical IQR.
iqrMult (Default 1.5): Multiplier to define the upper and lower IQR-based bands.
ATR-Adjusted OB/OS Settings:
baseOBLevel (Fixed at 90) and baseOSLevel (Fixed at 90): Base lines for OB/OS.
atrPeriodForOBOS (Default 50): ATR length for adjusting OB/OS thresholds dynamically.
atrScaling (Default 0.2): Controls how strongly volatility affects OB/OS lines.
Torque Filtering & Visualization:
torqueSmoothLength (Default 10): EMA length to smooth raw torque values.
atrPeriodForTorque (Default 14): ATR period to determine torque threshold.
atrTorqueScaling (Default 0.5): Scales ATR for determining torque’s “significant” threshold.
torqueScaleFactor (Default 10.0): Multiplies the torque values for better visual prominence on the chart.
Divergence Inputs:
showDivergences (Default true): Toggles divergence signals.
lbR, lbL (Defaults 5): Pivot lookback periods to identify swing highs and lows.
rangeUpper, rangeLower: Bar constraints to validate potential divergences.
plotBull, plotHiddenBull, plotBear, plotHiddenBear: Toggles for each divergence type.
Visual Elements on the Chart
GMO Line (Blue) & Zero Line (Gray):
GMO line oscillates around zero. Positive territory hints bullish momentum, negative suggests bearish.
IQR Bands (Teal Lines & Yellow Fill):
Upper/lower bands form a statistical “normal range” for GMO. The median line (purple) provides a central reference. Contraction near these bands indicates a short-term squeeze, expansions beyond them can signal emerging short-term trend changes.
Dynamic OB/OS (Red & Green Lines):
Red line near +90 to +100: Overbought zone (dynamic).
Green line near -90 to -100: Oversold zone (dynamic).
Movement into these zones may mark significant, longer-term reversal potential.
Torque Histogram (Colored Bars):
Plotted below GMO. Green bars = torque above positive threshold (bullish acceleration).
Red bars = torque below negative threshold (bearish acceleration).
Gray bars = neutral range.
This provides early warnings of momentum shifts before price responds fully.
Precession (Orange Line):
Scaled for visibility, adds context to long-term angular shifts in the oscillator.
Divergence Signals (Shapes):
Circles and offset lines highlight regular or hidden bullish/bearish divergences, offering potential reversal signals.
Practical Interpretation & Strategy
Short-Term Opportunities (IQR Focus):
If GMO compresses within IQR bands, the market might be “winding up.” A break above/below these bands can signal a short-term trade opportunity.
Long-Term Reversal Zones (Dynamic OB/OS):
When GMO approaches these dynamically adjusted extremes, conditions may be ripe for a major trend shift. This is particularly useful for swing or position traders looking for significant turnarounds.
Monitoring Torque for Acceleration Cues:
Torque spikes can precede price action, serving as an early catalyst signal. If torque turns strongly positive, anticipate bullish acceleration; strongly negative torque may warn of upcoming bearish pressure.
Confirm with Divergences:
Divergences between price and GMO reinforce potential reversal or continuation signals identified by IQR, OB/OS, or torque. Use them to increase confidence in setups.
Tips and Best Practices
Combine with Price & Volume Action:
While the indicator is powerful, always confirm signals with actual price structure, volume patterns, or other trend-following tools.
Adjust Lengths & Periods as Needed:
Shorter lengths = more responsiveness but more noise. Longer lengths = smoother signals but greater lag. Tune parameters to match your trading style and timeframe.
Use ATR and Volume Settings Wisely:
If markets are highly volatile, consider useVolatility to refine momentum readings. If liquidity is key, enable useVolume.
Scaling Torque:
If torque bars are hard to read, increase torqueScaleFactor further. The scaling doesn’t affect logic—only visibility.
Conclusion
The “GMO + IQR Bands + ATR-Adjusted OB/OS + Torque Filtering (Scaled)” indicator presents a holistic framework for understanding market momentum across multiple timescales and conditions. By interpreting short-term squeezes via IQR bands, long-term reversal zones via adaptive OB/OS, and subtle acceleration changes through torque, traders can gain advanced insights into when to anticipate breakouts, manage risk around potential reversals, and fine-tune timing for entries and exits.
This integrated approach helps navigate complex market dynamics, making it a valuable addition to any technical analysis toolkit.
Trend Condition [TradersPro]
OVERVIEW
The Trend Condition Indicator measures the strength of the bullish or bearish trend by using a ribbon pattern of exponential moving averages and scoring system. Trend cycles naturally expand and contract as a normal part of the cycle. It is the rhythm of the market. Perpetual expansion and contraction of trend.
As trend cycles develop the indicator shows a compression of the averages. These compression zones are key locations as trends typically expand from there. The expansion of trend can be up or down.
As the trend advances the ribbon effect of the indicator can be seen as each average expands with the price action. Once they have “fanned” the probability of the current trend slowing is high.
This can be used to recognize a powerful trend may be concluding. Traders can tighten stops, exit positions or utilize other prudent strategies.
CONCEPTS
Each line will display green if it is higher than the prior period and red if it is lower than the prior period. If the average is green it is considered bullish and will score one point in the bullish display. Red lines are considered bearish and will score one point in the bearish display.
The indicator can then be used at a quick glance to see the number of averages that are bullish and the number that are bearish.
A trader may use these on any tradable instrument. They can be helpful in stock portfolio management when used with an index like the S&P 500 to determine the strength of the current market trend. This may affect trade decisions like possession size, stop location and other risk factors.
[AlbaTherium] Volume Venturius Premium Volume Venturius Premium
Introduction
The Volume Venturius Premium is an advanced market analysis tool designed to deeply investigate the behavior of active market participants. By focusing exclusively on executed market orders, Volume Venturius offers traders a unique perspective on buy and sell volumes. Unlike traditional order books that track passive orders, this indicator isolates active orders, shedding light on real market dynamics.
Chapter 1: Understanding Market Participants
1.1 Categories of Market Participants
Market participants can be classified into several categories based on their:
Size : The volume of trades executed.
Influence : Their ability to initiate bull or bear campaigns.
Strategy : The trading methods employed, such as scalping, swing trading, or high-frequency trading.
Objectives : Whether their focus is on speculation, hedging, or arbitrage.
Time Horizon : Short-term versus long-term goals.
Behavioral Patterns : Their reaction to liquidity levels or price movements.
1.2 Objectives of Market Participants
Each category pursues specific objectives, such as profit-making or risk management. Regulatory reports like the Commitment of Traders (COT) provide weekly insights into the positions and intentions of major players.
Chapter 2: The Philosophy of Volume Analysis
2.1 Active Orders vs. Passive Orders
Unlike passive orders waiting to be filled at specific prices, active orders directly impact market prices. By focusing on these executed orders, Volume Venturius Premium provides traders with actionable insights into market trends and momentum.
2.2 Wyckoff’s Market Dynamics
According to Wyckoff, markets operate in two primary phases:
Manipulation: Where large participants accumulate or distribute positions to prepare for a move.
Expansion: The phase where price trends begin to unfold, either in a bullish or bearish direction.
Wyckoff’s theory emphasizes understanding how major players manipulate the market to identify accumulation or distribution zones. Volume Venturius Premium aids in pinpointing these manipulative actions by analyzing volume and order flow data.
Chapter 3: The Secrets of Order Flow and Volume
3.1 Unveiling Market Control
By studying the positioning and execution volumes of large players, traders can discern who holds control in the market. Volume Venturius Premium identifies the balance of power and tracks shifts that signal potential trend reversals.
3.2 Behavioral Patterns in Volume
Key metrics tracked by Volume Venturius Premium include:
Volume Clusters : Areas of concentrated buying or selling activity.
Directional Bias : Whether market participants are net buyers or sellers.
Momentum Shifts : Changes in execution speed and volume that may precede major moves.
3.2.1 Volume Clusters, Directional Bias and Directional Bias: Areas of Concentrated Buying or Selling Activity
Volume clusters play a crucial role in understanding market dynamics by highlighting areas where aggressive buying or selling activity is most concentrated. These clusters often serve as key decision zones, providing insights into potential reversals, breakouts, or continuations. To better visualize and interpret these zones, a distinct color-coding system has been implemented. Each color represents a specific market condition or level of activity, allowing for a more intuitive analysis of volume behavior and its influence on price movement.
Below is a detailed explanation of the color logic used to represent these clusters and their significance within the trading framework.
Color Interpretation and Meaning :
Extra Extreme Zones
These zones highlight areas where clusters of aggressive buyers or sellers are most heavily concentrated. They represent critical levels for identifying potential reversals or strong continuations.
Bright Red (#ff003c) : Represents extra-extreme sell zones, where aggressive sellers dominate.
Meaning: Indicates extreme selling pressure, often signaling potential exhaustion of sellers.
Bright Blue (#001eff) : Represents extra-extreme buy zones, where aggressive buyers are most active.
Meaning: Shows extreme buying pressure, possibly marking a saturation point for buyers.
Main Zones
These zones help identify key levels based on volume activity and well-defined clusters.
Dark Red (#d60033) : Represents strong selling pressure.
Orange (#ff8000) : Indicates significant selling pressure that begins to fade.
Yellow (#ffff00) : Represents moderate selling pressure, signaling a potential slowdown.
White (#ffffff) : Marks transition zones, which are interesting entry points for potential reversals or continuations.
Transition Zones (Frontier Zones)
These zones indicate intermediate movements and potential shifts in momentum.
Transparent Black (#000000, 50) : Represents transition areas, where the market tests boundaries between buyers and sellers.
Meaning: These are critical decision points.
Neutral Zone (Sea Zone)- Trend Zones
These zones represent more balanced market activity, where neither buyers nor sellers dominate clearly.
Transparent Green (#00e040, 25) : Indicates slight bullish activity in a neutral zone.
Transparent Red (#e01a00, 25) : Indicates slight bearish activity in a neutral zone.
This color logic allows you to pinpoint areas where volume clusters show a clear dominance, exhaustion, or optimal entry opportunities.
3.3 Divergences Between Price and Volume
Divergences between price and volume are critical for identifying key shifts in market sentiment. Volume Venturius Premium distinguishes two main types of divergences: Lack of Participation and Absorption, each offering valuable signals for potential reversals or continuations.
Lack of Participation
This divergence occurs when price movements are not supported by corresponding volume dynamics, signaling a reduction in activity from significant market participants.
1. Bullish Lack of Participation:
Characteristics : Price is making lower lows, but volume is making higher lows.
This indicates waning selling pressure as prices drop.
Inference : A potential bullish reversal may occur. Traders could consider looking for opportunities to go long.
2.Bearish Lack of Participation:
Characteristics : Price is making higher highs, but volume is making lower highs. This suggests diminishing buying pressure even as prices rise.
Inference : A potential bearish reversal might follow. Traders might position to go short.
Absorption
Absorption occurs when larger market participants neutralize the pressure from smaller participants, often leading to significant market moves.
1.Bullish Absorption:
Characteristics : Price is making higher bottoms, but volume is making lower bottoms.
This reflects sellers being trapped as their selling efforts are absorbed by larger buyers.
Inference : A potential upward breakout is likely. Traders may look for opportunities to go long.
2.Bearish Absorption:
Characteristics : Price is making lower tops, but volume is making higher tops. This indicates buyers being trapped as larger sellers absorb their buying activity.
Inference : A downward breakout is probable. Traders may consider positioning to go short.
Chapter 4: Practical Application and Trading Strategies
4.1 Leveraging Active Order Insights
Learn how to use Volume Venturius Premium to detect hidden accumulation or distribution phases. Strategies include identifying spikes in active volume that signal institutional participation.
4.2 Confirming Bull and Bear Campaigns
Gain confidence in detecting the early stages of bullish or bearish campaigns by analyzing the interplay between active orders and volume flow.
Chapter 5: Real-World Examples
5.1 Analyzing Market Manipulation
See how Volume Venturius Premium can reveal manipulation tactics employed by large players to trigger liquidity events.
5.2 Spotting Trends with Active Orders
Real-life scenarios demonstrate how the tool can be used to identify and ride the market’s dominant trend.
Conclusion
The Volume Venturius Premium is an indispensable tool for traders who seek to understand the underlying mechanics of market movement. By focusing on active order flows and drawing on Wyckoff’s principles, it provides unique insights into market manipulation and expansion phases. Whether you’re an intraday trader or a long-term strategist, this tool empowers you to anticipate market shifts and trade with confidence.
Stay tuned for updates as we continue to refine Volume Venturius Premium to further enhance your trading journey.
FVG Chain (Consecutive Fair Value Gaps / Imbalances)This indicator detects fair value gaps that are created out of the touch of older fair value gaps, hence creating an "FVG chain".
It counts +1 for the chain whenever a new price leg's FVG is touched.
You can use the current FVG Chain count, as well as the high, low, and price leg high/low of the current FVG as input source in external indicators. Check the data window to see the plot values.
How FVGs are detected:
Bullish: The low of the current confirmed bar is above the high of 2 bars back.
Bearish: The high of the current confirmed bar is below the low of 2 bars back.
A bullish FVG chain is broken if:
The current FVG's price leg low is broken.
The previous bar closed below the FVG, and the current confirmed bar closed below the previous bar.
A bearish FVG chain is broken if:
The current FVG's price leg high is broken.
The previous bar closed above the FVG, and the current confirmed bar closed above the previous bar.
Daily Directional Bias Indicator (S&P 500)This indicator is designed to help you be on the right side of the trade.
Most traders who struggle to know which way price may move are only looking at part of the picture. This Directional Bias Indicator uses both the Accumulation/Distribution Line and VIX for directional confirmation.
The Accumulation/Distribution Line
The Accumulation/Distribution (ACC) line helps us gauge market momentum by showing the cumulative flow of money into or out of an asset. When the ACC line is rising, it suggests that buying pressure is dominating, indicating a bullish market. Conversely, when the ACC line is falling, it suggests that selling pressure is stronger, indicating a bearish market. By comparing the ACC line with the VWAP, traders can see if the price is moving in line with the overall market sentiment. If the ACC line is above the VWAP, it suggests the market is in a bullish phase; if it's below, it indicates a bearish phase.
The VIX
The VIX (Volatility Index) is often referred to as the "fear gauge" of the market. When the VIX is rising, it typically signals increased market fear and higher volatility, which can be a sign of bearish market conditions. Conversely, when the VIX is falling, it suggests lower volatility and a more stable, bullish market. Using the VIX with the VWAP helps us confirm market direction, particularly in relation to the S&P 500.
VWAP
For both the ACC Line and VIX, we use a VWAP line to gauge whether the ACC line or the VIX is above or below the average. When the ACC line is above the VWAP, we view it as a sign that price will go up. However, because the VIX has an inverse relationship, when the VIX falls below the VWAP, we take that as a sign to go long.
How to use
The yellow line represents the ACC Line.
The red line represents the VWAP based on the ACC line.
The triangles at the bottom simply show when the ACC line is above or below the VWAP.
The triangles at the top show whether the VIX is bullish or bearish.
If both triangles (top or bottom) are bullish, this confirms that the price of an asset like the S&P 500 will likely go up. If both triangles are pointing down, it suggests that price will fall.
As always, test for yourself.
Happy trading!
Weis Wave Max█ Overview
Weis Wave Max is the result of my weis wave study.
David Weis said,
"Trading with the Weis Wave involves changes in behavior associated with springs, upthrusts, tests of breakouts/breakdowns, and effort vs reward. The most common setup is the low-volume pullback after a bullish/bearish change in behavior."
THE STOCK MARKET UPDATE (February 24, 2013)
I inspired from his sentences and made this script.
Its Main feature is to identify the largest wave in Weis wave and advantageous trading opportunities.
█ Features
This indicator includes several features related to the Weis Wave Method.
They help you analyze which is more bullish or bearish.
Highlight Max Wave Value (single direction)
Highlight Abnormal Max Wave Value (both directions)
Support and Resistance zone
Signals and Setups
█ Usage
Weis wave indicator displays cumulative volume for each wave.
Wave volume is effective when analyzing volume from VSA (Volume Spread Analysis) perspective.
The basic idea of Weis wave is large wave volume hint trend direction. This helps identify proper entry point.
This indicator highlights max wave volume and displays the signal and then proper Risk Reward Ratio entry frame.
I defined Change in Behavior as max wave volume (single direction).
Pullback is next wave that does not exceed the starting point of CiB wave (LH sell entry, HL buy entry).
Change in Behavior Signal ○ appears when pullback is determined.
Change in Behavior Setup (Entry frame) appears when condition of Min/Max Pullback is met and follow through wave breaks end point of CiB wave.
This indicator has many other features and they can also help a user identify potential levels of trade entry and which is more bullish or bearish.
In the screenshot below we can see wave volume zones as support and resistance levels. SOT and large wave volume /delta price (yellow colored wave text frame) hint stopping action.
█ Settings
Explains the main settings.
-- General --
Wave size : Allows the User to select wave size from ① Fixed or ② ATR. ② ATR is Factor x ATR(Length).
Display : Allows the User to select how many wave text and zigzag appear.
-- Wave Type --
Wave type : Allows the User to select from Volume or Volume and Time.
Wave Volume / delta price : Displays Wave Volume / delta price.
Simplified value : Allows the User to select wave text display style from ① Divisor or ② Normalized. Normalized use SMA.
Decimal : Allows the User to select the decimal point in the Wave text.
-- Highlight Abnormal Wave --
Highlight Max Wave value (single direction) : Adds marks to the Wave text to highlight the max wave value.
Lookback : Allows the User to select how many waves search for the max wave value.
Highlight Abnormal Wave value (both directions) : Changes wave text size, color or frame color to highlight the abnormal wave value.
Lookback : Allows the User to select SMA length to decide average wave value.
Large/Small factor : Allows the User to select the threshold large wave value and small wave value. Average wave value is 1.
delta price : Highlights large delta price by large wave text size, small by small text size.
Wave Volume : Highlights large wave volume by yellow colored wave text, small by gray colored.
Wave Volume / delta price : highlights large Wave Volume / delta price by yellow colored wave text frame, small by gray colored.
-- Support and Resistance --
Single side Max Wave Volume / delta price : Draws dashed border box from end point of Max wave volume / delta price level.
Single side Max Wave Volume : Draws solid border box from start point of Max wave volume level.
Bias Wave Volume : Draws solid border box from start point of bias wave volume level.
-- Signals --
Bias (Wave Volume / delta price) : Displays Bias mark when large difference in wave volume / delta price before and after.
Ratio : Decides the threshold of become large difference.
3Decrease : Displays 3D mark when a continuous decrease in wave volume.
Shortening Of the Thrust : Displays SOT mark when a continuous decrease in delta price.
Change in Behavior and Pullback : Displays CiB mark when single side max wave volume and pullback.
-- Setups --
Change in Behavior and Pullback and Breakout : Displays entry frame when change in behavior and pullback and then breakout.
Min / Max Pullback : Decides the threshold of min / max pullback.
If you need more information, please read the indicator's tooltip.
█ Conclusion
Weis Wave is powerful interpretation of volume and its tell us potential trend change and entry point which can't find without weis wave.
It's not the holy grail, but improve your chart reading skills and help you trade rationally (at least from VSA perspective).
Simple Decesion Matrix Classification Algorithm [SS]Hello everyone,
It has been a while since I posted an indicator, so thought I would share this project I did for fun.
This indicator is an attempt to develop a pseudo Random Forest classification decision matrix model for Pinescript.
This is not a full, robust Random Forest model by any stretch of the imagination, but it is a good way to showcase how decision matrices can be applied to trading and within Pinescript.
As to not market this as something it is not, I am simply calling it the "Simple Decision Matrix Classification Algorithm". However, I have stolen most of the aspects of this machine learning algo from concepts of Random Forest modelling.
How it works:
With models like Support Vector Machines (SVM), Random Forest (RF) and Gradient Boosted Machine Learning (GBM), which are commonly used in Machine Learning Classification Tasks (MLCTs), this model operates similarity to the basic concepts shared amongst those modelling types. While it is not very similar to SVM, it is very similar to RF and GBM, in that it uses a "voting" system.
What do I mean by voting system?
How most classification MLAs work is by feeding an input dataset to an algorithm. The algorithm sorts this data, categorizes it, then introduces something called a confusion matrix (essentially sorting the data in no apparently order as to prevent over-fitting and introduce "confusion" to the algorithm to ensure that it is not just following a trend).
From there, the data is called upon based on current data inputs (so say we are using RSI and Z-Score, the current RSI and Z-Score is compared against other RSI's and Z-Scores that the model has saved). The model will process this information and each "tree" or "node" will vote. Then a cumulative overall vote is casted.
How does this MLA work?
This model accepts 2 independent variables. In order to keep things simple, this model was kept as a three node model. This means that there are 3 separate votes that go in to get the result. A vote is casted for each of the two independent variables and then a cumulative vote is casted for the overall verdict (the result of the model's prediction).
The model actually displays this system diagrammatically and it will likely be easier to understand if we look at the diagram to ground the example:
In the diagram, at the very top we have the classification variable that we are trying to predict. In this case, we are trying to predict whether there will be a breakout/breakdown outside of the normal ATR range (this is either yes or no question, hence a classification task).
So the question forms the basis of the input. The model will track at which points the ATR range is exceeded to the upside or downside, as well as the other variables that we wish to use to predict these exceedences. The ATR range forms the basis of all the data flowing into the model.
Then, at the second level, you will see we are using Z-Score and RSI to predict these breaks. The circle will change colour according to "feature importance". Feature importance basically just means that the indicator has a strong impact on the outcome. The stronger the importance, the more green it will be, the weaker, the more red it will be.
We can see both RSI and Z-Score are green and thus we can say they are strong options for predicting a breakout/breakdown.
So then we move down to the actual voting mechanisms. You will see the 2 pink boxes. These are the first lines of voting. What is happening here is the model is identifying the instances that are most similar and whether the classification task we have assigned (remember out ATR exceedance classifier) was either true or false based on RSI and Z-Score.
These are our 2 nodes. They both cast an individual vote. You will see in this case, both cast a vote of 1. The options are either 1 or 0. A vote of 1 means "Yes" or "Breakout likely".
However, this is not the only voting the model does. The model does one final vote based on the 2 votes. This is shown in the purple box. We can see the final vote and result at the end with the orange circle. It is 1 which means a range exceedance is anticipated and the most likely outcome.
The Data Table Component
The model has many moving parts. I have tried to represent the pivotal functions diagrammatically, but some other important aspects and background information must be obtained from the companion data table.
If we bring back our diagram from above:
We can see the data table to the left.
The data table contains 2 sections, one for each independent variable. In this case, our independent variables are RSI and Z-Score.
The data table will provide you with specifics about the independent variables, as well as about the model accuracy and outcome.
If we take a look at the first row, it simply indicates which independent variable it is looking at. If we go down to the next row where it reads "Weighted Impact", we can see a corresponding percent. The "weighted impact" is the amount of representation each independent variable has within the voting scheme. So in this case, we can see its pretty equal, 45% and 55%, This tells us that there is a slight higher representation of z-score than RSI but nothing to worry about.
If there was a major over-respresentation of greater than 30 or 40%, then the model would risk being skewed and voting too heavily in favour of 1 variable over the other.
If we move down from there we will see the next row reads "independent accuracy". The voting of each independent variable's accuracy is considered separately. This is one way we can determine feature importance, by seeing how well one feature augments the accuracy. In this case, we can see that RSI has the greatest importance, with an accuracy of around 87% at predicting breakouts. That makes sense as RSI is a momentum based oscillator.
Then if we move down one more, we will see what each independent feature (node) has voted for. In this case, both RSI and Z-Score voted for 1 (Breakout in our case).
You can weigh these in collaboration, but its always important to look at the final verdict of the model, which if we move down, we can see the "Model prediction" which is "Bullish".
If you are using the ATR breakout, the model cannot distinguish between "Bullish" or "Bearish", must that a "Breakout" is likely, either bearish or bullish. However, for the other classification tasks this model can do, the results are either Bullish or Bearish.
Using the Function:
Okay so now that all that technical stuff is out of the way, let's get into using the function. First of all this function innately provides you with 3 possible classification tasks. These include:
1. Predicting Red or Green Candle
2. Predicting Bullish / Bearish ATR
3. Predicting a Breakout from the ATR range
The possible independent variables include:
1. Stochastics,
2. MFI,
3. RSI,
4. Z-Score,
5. EMAs,
6. SMAs,
7. Volume
The model can only accept 2 independent variables, to operate within the computation time limits for pine execution.
Let's quickly go over what the numbers in the diagram mean:
The numbers being pointed at with the yellow arrows represent the cases the model is sorting and voting on. These are the most identical cases and are serving as the voting foundation for the model.
The numbers being pointed at with the pink candle is the voting results.
Extrapolating the functions (For Pine Developers:
So this is more of a feature application, so feel free to customize it to your liking and add additional inputs. But here are some key important considerations if you wish to apply this within your own code:
1. This is a BINARY classification task. The prediction must either be 0 or 1.
2. The function consists of 3 separate functions, the 2 first functions serve to build the confusion matrix and then the final "random_forest" function serves to perform the computations. You will need all 3 functions for implementation.
3. The model can only accept 2 independent variables.
I believe that is the function. Hopefully this wasn't too confusing, it is very statsy, but its a fun function for me! I use Random Forest excessively in R and always like to try to convert R things to Pinescript.
Hope you enjoy!
Safe trades everyone!
ADX and DI Trend meter and status table IndicatorThis ADX (Average Directional Index) and DI (Directional Indicator) indicator helps identify:
Trend Direction & Strength:
LONG: +DI above -DI with ADX > 20
SHORT: -DI above +DI with ADX > 20
RANGE: ADX < 20 indicates choppy/sideways market
Trading Signals:
Bullish: +DI crosses above -DI (green triangle)
Bearish: -DI crosses below +DI (red triangle)
ADX Strength Levels:
Strong: ADX ≥ 50
Moderate: ADX 30-49
Weak: ADX 20-29
No Trend: ADX < 20
Best Uses:
Trend confirmation before entering trades
Identifying ranging vs trending markets
Exit signal when trend weakens
Works well on multiple timeframes
Most effective in combination with other indicators
The table displays current trend direction and ADX strength in real-time
Wick Length Display + Alert conditionsDescription of the Wick Length Display (Advanced) script
Originality and purpose of the script
The Wick Length Display (Advanced) script is an innovative tool for traders who want to gain detailed insights into the length of candle wicks. It stands out for its versatility and user-friendly customization options. It combines precise technical calculations with visual representation to provide important information about market movements and dynamics right on the chart.
Functionality
The script calculates and displays the length of the upper and lower wicks of each candle on the chart. It also provides additional visual cues such as:
• “Bull pressure”: When green candles do not have upper wicks, this indicates strong buying pressure.
• “Bear pressure”: When red candles do not have lower wicks, this indicates strong selling pressure.
• Threshold conditions: Only displays wicks that exceed a certain threshold (optional).
• Display in pips: Allows you to display wick lengths in pips, which is useful for forex traders.
How it works
The script analyzes each candle using the following calculations:
1. Wick length calculation:
◦ Upper wick length = High - (top of the body)
◦ Lower wick length = (bottom of the body) - Low
2. Display conditions:
◦ It distinguishes between bullish and bearish candles.
◦ It checks if the calculated wicks exceed the defined thresholds before displaying them.
3. Dynamic labels:
◦ Labels are placed above or below the respective candles.
◦ Size, color and type of labels are fully customizable.
4. Limitation of labels:
◦ To ensure clarity, a maximum number of labels is defined.
Usage
1. Customization:
◦ Open the script in the Pine Script Editor in TradingView.
◦ Use the input options to customize parameters such as color selection, label size, thresholds and other details according to your requirements.
2. Enable thresholds:
◦ Enable thresholds to show labels only for relevant wicks (default is 6).
◦ Define the minimum wick lengths for bullish (green) and bearish (red) candles.
3. Show in pips:
◦ Enable the “Show wick length in pips” option to show the results in pips (especially suitable for Forex).
4. Edit pressure labels:
◦ Turn the “Bull Pressure” and “Bear Pressure” features on or off depending on your analysis settings.
Concepts behind the calculations
• Technical market analysis: Wick lengths can indicate buying or selling pressure and provide important information on market psychology.
• Thresholds and filtering: The script uses thresholds to avoid visual overload and highlight only essential data.
• Label display: Dynamic labels improve chart readability and give the user instant feedback on market developments.
Usage
This script is great for:
• Intraday trading: Analyzing short-term movements using wick lengths.
• Forex trading: Tracking market momentum using the pip indicator.
• Swing trading: Identifying buying or selling pressure in key markets.
• Visual support: Ideal for traders who prefer a graphical display.
Description of the Wick Length Display (Advanced) script
Originality and purpose of the script
The Wick Length Display (Advanced) script is an innovative tool for traders who want to gain detailed insights into the length of candle wicks. It stands out for its versatility and user-friendly customization options. It combines precise technical calculations with visual representation to provide important information about market movements and dynamics right on the chart.
Functionality
The script calculates and displays the length of the upper and lower wicks of each candle on the chart. It also provides additional visual cues such as:
• “Bull pressure”: When green candles do not have upper wicks, this indicates strong buying pressure.
• “Bear pressure”: When red candles do not have lower wicks, this indicates strong selling pressure.
• Threshold conditions: Only displays wicks that exceed a certain threshold (optional).
• Display in pips: Allows you to display wick lengths in pips, which is useful for forex traders.
How it works
The script analyzes each candle using the following calculations:
1. Wick length calculation:
◦ Upper wick length = High - (top of the body)
◦ Lower wick length = (bottom of the body) - Low
2. Display conditions:
◦ It distinguishes between bullish and bearish candles.
◦ It checks if the calculated wicks exceed the defined thresholds before displaying them.
3. Dynamic labels:
◦ Labels are placed above or below the respective candles.
◦ Size, color and type of labels are fully customizable.
4. Limitation of labels
Alert conditions:
Alerts are triggered when the wick length of a bullish or bearish candle exceeds the defined thresholds.
Alert function:
alert() is used to issue messages with a frequency of once per candle when the conditions are met.
How to set up alerts
Save the script and add it to your chart.
Open the alert settings in TradingView.
Select the script's custom message as a trigger.
Adjust the frequency and notification type (popup, email, etc.).
Now you have a powerful tool with visual analysis and alert function!
Prometheus Markov ChainThe Prometheus Markov Chain Indicator is a custom-built tool designed to predict potential future price movements using a Markov Chain approach. A Markov Chain is a statistical model that assumes the probability of moving to a future state depends solely on the current state. In this indicator, states represent price movement classifications—bullish, bearish, or neutral—and are determined based on historical price changes (percentage returns). The indicator builds a transition matrix to calculate probabilities of transitioning from one state to another, enabling traders to identify patterns and forecast likely price actions.
Core Functionality and Transition Matrix
The transition matrix is the backbone of the Markov Chain. It captures the frequency of transitions between states in the historical price data and normalizes these counts into probabilities. For example, if the price was in a bearish state and transitioned to a bullish state 3 out of 10 times, the probability of transitioning from bearish to bullish would be 0.3. The matrix is created dynamically using the stateFunc function to classify states, which can use either dynamic thresholds (highest and lowest returns over a lookback period) or a user-defined percent return threshold. Below is the snippet that updates the transition matrix:
transitionMatrix = matrix.new(dimension, dimension, 0.0)
for i = 0 to array.size(vec) - 2
fromState = array.get(vec, i)
toState = array.get(vec, i + 1)
transitionMatrix.set(fromState, toState, transitionMatrix.get(fromState, toState) + 1)
for i = 0 to dimension - 1
rowSum = 0.0
for j = 0 to dimension - 1
rowSum += transitionMatrix.get(i, j)
for j = 0 to dimension - 1
prob = transitionMatrix.get(i, j) / rowSum
transitionMatrix.set(i, j, prob)
This snippet iterates through historical price movements, counts state transitions, and then normalizes each row of the matrix so that the sum of probabilities for all possible transitions from a given state equals 1.
How the Indicator Predicts Future States
After constructing the transition matrix, the indicator calculates the current state of the price based on the latest percentage return and then uses the matrix to compute probabilities for transitioning to other states. The state with the highest probability is predicted as the next state, which is displayed on the chart using color-coded labels: green for bullish and red for bearish. The following snippet demonstrates how the current state and predictions are calculated:
current_chng = (close - close ) / close
var int current_state = na
if not use_custom_thresh
highest_chng = ta.highest(current_chng, int(size) * 2)
lowest_chng = ta.lowest(current_chng, int(size) * 2)
current_state := stateFunc(current_chng, highest_chng, lowest_chng)
else
current_state := stateFunc(current_chng, custom_thresh)
predicted_probs = array.new(dimension, 0.0)
for j = 0 to dimension - 1
array.set(predicted_probs, j, transitionMatrix.get(current_state, j))
The indicator evaluates which state has the highest transition probability (highest_prob) and places corresponding labels on the chart. For example, if the next state is predicted to be bullish, a green "Bullish" label is placed below the current bar. This predictive functionality helps traders anticipate potential reversals or continuations in price trends based on historical behavior patterns.
Usage:
Here we see the indicator at work on $PLTR. The states predicted are bullish then bearish. In this example we then see price move in a way that verifies those predictions.
On this 4 Hour NASDAQ:AMZN chart we see predictions play out in a short trade style. States quickly move from one to another but not without giving traders a way to take advantage.
This is the perspective we aim to provide. We encourage traders to not follow indicators blindly. No indicator is 100% accurate. This one can give you a different perspective market state. We encourage any comments about desired updates or criticism!
Super CCI By Baljit AujlaThe indicator you've shared is a custom CCI (Commodity Channel Index) with multiple types of Moving Averages (MA) and Divergence Detection. It is designed to help traders identify trends and reversals by combining the CCI with various MAs and detecting different types of divergences between the price and the CCI.
Key Components of the Indicator:
CCI (Commodity Channel Index):
The CCI is an oscillator that measures the deviation of the price from its average price over a specific period. It helps identify overbought and oversold conditions and the strength of a trend.
The CCI is calculated by subtracting a moving average (SMA) from the price and dividing by the average deviation from the SMA. The CCI values fluctuate above and below a zero centerline.
Multiple Moving Averages (MA):
The indicator allows you to choose from a variety of moving averages to smooth the CCI line and identify trend direction or support/resistance levels. The available types of MAs include:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
HMA (Hull Moving Average)
RMA (Running Moving Average)
SMMA (Smoothed Moving Average)
TEMA (Triple Exponential Moving Average)
DEMA (Double Exponential Moving Average)
VWMA (Volume-Weighted Moving Average)
ZLEMA (Zero-Lag Exponential Moving Average)
You can select the type of MA to use with a specified length to help identify the trend direction or smooth out the CCI.
Divergence Detection:
The indicator includes a divergence detection mechanism to identify potential trend reversals. Divergences occur when the price and an oscillator like the CCI move in opposite directions, signaling a potential change in price momentum.
Four types of divergences are detected:
Bullish Divergence: Occurs when the price makes a lower low, but the CCI makes a higher low. This indicates a potential reversal to the upside.
Bearish Divergence: Occurs when the price makes a higher high, but the CCI makes a lower high. This indicates a potential reversal to the downside.
Hidden Bullish Divergence: Occurs when the price makes a higher low, but the CCI makes a lower low. This suggests a continuation of the uptrend.
Hidden Bearish Divergence: Occurs when the price makes a lower high, but the CCI makes a higher high. This suggests a continuation of the downtrend.
Each type of divergence is marked on the chart with arrows and labels to alert traders to potential trading opportunities. The labels include the divergence type (e.g., "Bull Div" for Bullish Divergence) and have customizable text colors.
Visual Representation:
The CCI and its associated moving average are plotted on the indicator panel below the price chart. The CCI is plotted as a line, and its color changes depending on whether it is above or below the moving average:
Green when the CCI is above the MA (indicating bullish momentum).
Red when the CCI is below the MA (indicating bearish momentum).
Horizontal lines are drawn at specific levels to help identify key CCI thresholds:
200 and -200 levels indicate extreme overbought or oversold conditions.
75 and -75 levels represent less extreme levels of overbought or oversold conditions.
The 0 level acts as a neutral or baseline level.
A background color fill between the 75 and -75 levels helps highlight the neutral zone.
Customization Options:
CCI Length: You can customize the length of the CCI, which determines the period over which the CCI is calculated.
MA Length: The length of the moving average applied to the CCI can also be adjusted.
MA Type: Choose from a variety of moving averages (SMA, EMA, WMA, etc.) to smooth the CCI.
Divergence Detection: The indicator automatically detects the four types of divergences (bullish, bearish, hidden bullish, hidden bearish) and visually marks them on the chart.
How to Use the Indicator:
Trend Identification: When the CCI is above the selected moving average, it suggests bullish momentum. When the CCI is below the moving average, it suggests bearish momentum.
Overbought/Oversold Conditions: The CCI values above 100 or below -100 indicate overbought and oversold conditions, respectively.
Divergence Analysis: The detection of bullish or bearish divergences can signal potential trend reversals. Hidden divergences may suggest trend continuation.
Trading Signals: You can use the divergence markers (arrows and labels) as potential buy or sell signals, depending on whether the divergence is bullish or bearish.
Practical Application:
This indicator is useful for traders who want to:
Combine the CCI with different moving averages for trend-following strategies.
Identify overbought and oversold conditions using the CCI.
Use divergence detection to anticipate potential trend reversals or continuations.
Have a highly customizable tool for various trading strategies, including trend trading, reversal trading, and divergence-based trading.
Overall, this is a comprehensive tool that combines multiple technical analysis techniques (CCI, moving averages, and divergence) in a single indicator, providing traders with a robust way to analyze price action and spot potential trading opportunities.
Adaptive bollinger bands cloud v1 trend & trade signalsadaptive bollinger bands cloud:
the script extends the concept of bollinger bands by creating a "cloud" between the upper and lower bands. this cloud visually represents market conditions, with its color dynamically adjusting based on trend strength and volatility.
the gradient fill between the bands changes according to the deviation of the price from its basis, offering a visual cue for trend momentum.
trend detection logic:
a trend variable determines whether the price is in a bullish, bearish, or neutral state. if the price is above the upper band and the basis, the trend is marked bullish. if it's below the lower band and the basis, the trend is bearish. otherwise, it's neutral.
this trend logic is further enhanced with visual markers like arrows to indicate potential trend reversals.
extended take-profit bands:
additional upper and lower bands are calculated using a higher multiplier. these extended bands help identify potential take-profit levels, signaling when the price may have reached an overextended state.
gradient calculation:
the script computes a gradient based on the deviation of the price from its basis and normalizes it over a lookback period. this normalized gradient is smoothed to reflect volatility intensity and used to color the cloud dynamically.
signal generation:
buy and sell signals are generated based on crossovers of the trend variable. for instance, when the trend shifts from negative to positive, it signals a bullish opportunity. conversely, a shift from positive to negative indicates bearish conditions.
take-profit markers ("x") are plotted when the price crosses the extended bands, suggesting potential exit points.
trade entry tracking:
the script includes a table to display real-time entry signals and prices for long (buy) or short (sell) trades. this feature helps traders keep track of signals without needing to reference the chart visually.
customizable inputs:
users can adjust the bb period, multiplier, and colors to suit their trading preferences. this flexibility allows for tuning the indicator based on different market conditions or asset classes.
overall, the indicator blends traditional bollinger bands with innovative visualization, trend identification, and trading signals to enhance decision-making.
how to use this indicator
trend detection:
watch for arrows indicating trend shifts:
an upward arrow (green) signals a bullish trend; consider buying or entering a long position.
a downward arrow (red) signals a bearish trend; consider selling or entering a short position.
use the gradient-colored cloud to assess trend strength:
bright and strong colors indicate significant momentum.
fading colors suggest weakening trends or consolidation.
entry signals:
refer to the table in the top-right corner of the chart for real-time buy or sell entry signals.
when a "buy" signal is displayed with the price, it suggests a potential entry point for a long trade.
when a "sell" signal is displayed, consider shorting or exiting long positions.
take-profit signals:
look for the "x" markers near the extended bands (upper1 and lower1):
an "x" above the price suggests taking profit on long positions.
an "x" below the price suggests taking profit on short positions.
background gradient analysis:
observe the dynamic background color:
a strong purple gradient indicates significant price movement or volatility.
a lighter gradient suggests reduced momentum, signaling caution or a potential reversal.
alerts for automation:
set alerts using the predefined conditions:
bullish trend start, bearish trend start, and take-profit levels can be used to automate notifications for trade actions.
why to use this indicator
enhanced decision-making:
the adaptive cloud and gradient provide visual insights into trend strength and volatility, allowing traders to assess market conditions at a glance.
precise signals:
the indicator uses crossover logic and extended bollinger bands to generate clear buy, sell, and take-profit signals, reducing guesswork.
trend confirmation:
combining the bollinger bands with the trend variable ensures that traders only act on confirmed market trends rather than noise.
dynamic volatility assessment:
the normalized gradient calculation highlights periods of high or low volatility, helping traders adjust their strategies accordingly.
customizable settings:
adjustable parameters (period, multiplier, colors) allow the indicator to fit various markets, timeframes, and trading styles.
all-in-one tool:
integrates trend detection, entry signals, and take-profit levels into a single indicator, minimizing the need for multiple tools.
this indicator is especially useful for traders seeking a balance between simplicity and precision, whether scalping, day trading, or swing trading. it not only identifies trends but also highlights actionable entry and exit points, making it a versatile addition to any trading strategy.
Indicator DashboardThis script creates an 'Indicator Dashboard' designed to assist you in analyzing financial markets and making informed decisions. The indicator provides a summary of current market conditions by presenting various technical analysis indicators in a table format. The dashboard evaluates popular indicators such as Moving Averages, RSI, MACD, and Stochastic RSI. Below, we'll explain each part of this script in detail and its purpose:
### Overview of Indicators
1. **Moving Averages (MA)**:
- This indicator calculates Simple Moving Averages (“SMA”) for 5, 14, 20, 50, 100, and 200 periods. These averages provide a visual summary of price movements. Depending on whether the price is above or below the moving average, it determines the market direction as either “Bullish” or “Bearish.”
2. **RSI (Relative Strength Index)**:
- The RSI helps identify overbought or oversold market conditions. Here, the RSI is calculated for a 14-period window, and this value is displayed in the table. Additionally, the 14-period moving average of the RSI is also included.
3. **MACD (Moving Average Convergence Divergence)**:
- The MACD indicator is used to determine trend strength and potential reversals. This script calculates the MACD line, signal line, and histogram. The MACD condition (“Bullish,” “Bearish,” or “Neutral”) is displayed alongside the MACD and signal line values.
4. **Stochastic RSI**:
- Stochastic RSI is used to identify momentum changes in the market. The %K and %D lines are calculated to determine the market condition (“Bullish” or “Bearish”), which is displayed along with the calculated values for %K and %D.
### Table Layout and Presentation
The dashboard is presented in a vertical table format in the top-right corner of the chart. The table contains two columns: “Indicator” and “Status,” summarizing the condition of each technical indicator.
- **Indicator Column**: Lists each of the indicators being tracked, such as SMA values, RSI, MACD, etc.
- **Status Column**: Displays the current status of each indicator, such as “Bullish,” “Bearish,” or specific values like the RSI or MACD.
The table also includes rounded indicator values for easier interpretation. This helps traders quickly assess market conditions and make informed decisions based on multiple indicators presented in a single location.
### Detailed Indicator Status Calculations
1. **SMA Status**: For each moving average (5, 14, 20, 50, 100, 200), the script checks if the current price is above or below the SMA. The status is determined as “Bullish” if the price is above the SMA and “Bearish” if below, with the value of the SMA also displayed.
2. **RSI and RSI Average**: The RSI value for a 14-period is displayed along with its 14-period SMA, which provides an average reading of the RSI to smooth out volatility.
3. **MACD Indicator**: The MACD line, signal line, and histogram are calculated using standard parameters (12, 26, 9). The status is shown as “Bullish” when the MACD line is above the signal line, and “Bearish” when it is below. The exact values for the MACD line, signal line, and histogram are also included.
4. **Stochastic RSI**: The %K and %D lines of the Stochastic RSI are used to determine the trend condition. If %K is greater than %D, the condition is “Bullish,” otherwise it is “Bearish.” The actual values of %K and %D are also displayed.
### Conclusion
The 'Indicator Dashboard' provides a comprehensive overview of multiple technical indicators in a single, easy-to-read table. This allows traders to quickly gauge market conditions and make more informed decisions. By consolidating key indicators like Moving Averages, RSI, MACD, and Stochastic RSI into one dashboard, it saves time and enhances the efficiency of technical analysis.
This script is particularly useful for traders who prefer a clean and organized overview of their favorite indicators without needing to plot each one individually on the chart. Instead, all the crucial information is available at a glance in a consolidated format.
Trend Speed Analyzer (Zeiierman)█ Overview
The Trend Speed Analyzer by Zeiierman is designed to measure the strength and speed of market trends, providing traders with actionable insights into momentum dynamics. By combining a dynamic moving average with wave and speed analysis, it visually highlights shifts in trend direction, market strength, and potential reversals. This tool is ideal for identifying breakout opportunities, gauging trend consistency, and understanding the dominance of bullish or bearish forces over various timeframes.
█ How It Works
The indicator employs a Dynamic Moving Average (DMA) enhanced with an Accelerator Factor, allowing it to adapt dynamically to market conditions. The DMA is responsive to price changes, making it suitable for both long-term trends and short-term momentum analysis.
Key components include:
Trend Speed Analysis: Measures the speed of market movements, highlighting momentum shifts with visual cues.
Wave Analysis: Tracks bullish and bearish wave sizes to determine market strength and bias.
Normalized Speed Values: Ensures consistency across different market conditions by adjusting for volatility.
⚪ Average Wave and Max Wave
These metrics analyze the size of bullish and bearish waves over a specified Lookback Period:
Average Wave: This represents the mean size of bullish and bearish movements, helping traders gauge overall market strength.
Max Wave: Highlights the largest movements within the period, identifying peak momentum during trend surges.
⚪ Current Wave Ratio
This feature compares the current wave's size against historical data:
Average Wave Ratio: Indicates if the current momentum exceeds historical averages. A value above 1 suggests the trend is gaining strength.
Max Wave Ratio: Shows whether the current wave surpasses previous peak movements, signaling potential breakouts or trend accelerations.
⚪ Dominance
Dominance metrics reveal whether bulls or bears have controlled the market during the Lookback Period:
Average Dominance: Compares the net difference between average bullish and bearish wave sizes.
Max Dominance: Highlights which side had the stronger individual waves, indicating key power shifts in market dynamics.
Positive values suggest bullish dominance, while negative values point to bearish control. This helps traders confirm trend direction or anticipate reversals.
█ How to Use
Identify Trends: Leverage the color-coded candlesticks and dynamic trend line to assess the overall market direction with clarity.
Monitor Momentum: Use the Trend Speed histogram to track changes in momentum, identifying periods of acceleration or deceleration.
Analyze Waves: Compare the sizes of bullish and bearish waves to identify the prevailing market bias and detect potential shifts in sentiment. Additionally, fluctuations in Current Wave ratio values should be monitored as early indicators of possible trend reversals.
Evaluate Dominance: Utilize dominance metrics to confirm the strength and direction of the current trend.
█ Settings
Maximum Length: Sets the smoothing of the trend line.
Accelerator Multiplier: Adjusts sensitivity to price changes.
Lookback Period: Defines the range for wave calculations.
Enable Table: Displays statistical metrics for in-depth analysis.
Enable Candles: Activates color-coded candlesticks.
Collection Period: Normalizes trend speed values for better accuracy.
Start Date: Limits calculations to a specific timeframe.
Timer Option: Choose between using all available data or starting from a custom date.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Adaptive DEMA Momentum Oscillator (ADMO)Overview:
The Adaptive DEMA Momentum Oscillator (ADMO) is an open-source technical analysis tool developed to measure market momentum using a Double Exponential Moving Average (DEMA) and adaptive standard deviation. By dynamically combining price deviation from the moving average with normalized standard deviation, ADMO provides traders with a powerful way to interpret market conditions.
Key Features:
Double Exponential Moving Average (DEMA):
The core calculation of the indicator is based on DEMA, which is known for being more responsive to price changes compared to traditional moving averages. This makes the ADMO capable of capturing trend momentum effectively.
Standard Deviation Integration:
A normalized standard deviation is used to adaptively weight the oscillator. This makes the indicator more sensitive to market volatility, enhancing responsiveness during high volatility and reducing sensitivity during calmer periods.
Oscillator Representation:
The final oscillator value is derived from the combination of the DEMA-based Z-score and the normalized standard deviation. This final value is visualized as a color-coded histogram, reflecting bullish or bearish momentum.
Color-Coded Histogram:
Bullish Momentum: Values above zero are colored using a customizable bullish color (default: light green).
Bearish Momentum: Values below zero are colored using a customizable bearish color (default: red).
How It Works:
Inputs:
DEMA Length: Defines the period used for calculating the Double Exponential Moving Average. It can be adjusted from 1 to 200 to suit different trading styles.
Standard Deviation Length: Sets the lookback period for standard deviation calculations, which influences the responsiveness of the oscillator.
Standard Deviation Weight (StdDev Weight): Controls the weight given to the normalized standard deviation, allowing customization of the oscillator's sensitivity to volatility.
Calculation Steps:
Double Exponential Moving Average Calculation:
The DEMA is calculated using two exponential moving averages, which helps in reducing lag compared to a simple moving average.
Z-score Calculation:
The Z-score is derived by comparing the difference between the DEMA and its smoothed average (LSMA) to the standard deviation. This indicates how far the current value is from the mean in units of standard deviation.
Normalized Standard Deviation:
The standard deviation is normalized by subtracting the mean standard deviation and dividing by the standard deviation of the values. This helps to make the oscillator adaptive to recent changes in volatility.
Final Oscillator Value:
The final value is calculated by multiplying the Z-score with a factor based on the normalized standard deviation, resulting in a momentum indicator that adapts to different market conditions.
Visualization:
Histogram: The oscillator is plotted as a histogram, with color-coded bars showing the strength and direction of market momentum.
Positive (bullish) values are shown in green, indicating upward momentum.
Negative (bearish) values are shown in red, indicating downward momentum.
Zero Line: A zero line is plotted to provide a reference point, helping users quickly determine whether the current momentum is bullish or bearish.
Example Use Cases:
Momentum Identification:
ADMO helps identify the current market momentum by dynamically adapting to changes in market volatility. When the histogram is above zero and green, it indicates bullish conditions, whereas values below zero and red suggest bearish momentum.
Volatility-Adjusted Signals:
The normalized standard deviation weighting allows the ADMO to provide more reliable signals during different market conditions. This makes it particularly useful for traders who want to be responsive to market volatility while avoiding false signals.
Trend Confirmation and Divergence:
ADMO can be used to confirm the strength of a trend or identify potential divergences between price and momentum. This helps traders spot potential reversal points or continuation signals.
Summary:
The Adaptive DEMA Momentum Oscillator (ADMO) offers a unique approach by combining momentum analysis with adaptive standard deviation. The integration of DEMA makes it responsive to price changes, while the standard deviation adjustment helps it stay relevant in both high and low volatility environments. It's a versatile tool for traders who need an adaptive, momentum-based approach to technical analysis.
Feel free to explore the code and adapt it to your trading strategy. The open-source nature of this tool allows you to adjust the settings and visualize the output to fit your personal trading preferences.
Wick Trend Analysis with Supertrend and RSI -AYNETScientific Explanation
1. Wick Trend Analysis
Upper and Lower Wicks:
Calculated based on the difference between the high or low price and the candlestick body (open and close).
The trend of these wick lengths is derived using the Simple Moving Average (SMA) over the defined trend_length period.
Trend Direction:
Positive change (ta.change > 0) indicates an increasing trend.
Negative change (ta.change < 0) indicates a decreasing trend.
2. Supertrend Indicator
ATR Bands:
The Supertrend uses the Average True Range (ATR) to calculate dynamic upper and lower bands:
upper_band
=
hl2
+
(
supertrend_atr_multiplier
×
ATR
)
upper_band=hl2+(supertrend_atr_multiplier×ATR)
lower_band
=
hl2
−
(
supertrend_atr_multiplier
×
ATR
)
lower_band=hl2−(supertrend_atr_multiplier×ATR)
Trend Detection:
If the price is above the upper band, the Supertrend moves to the lower band.
If the price is below the lower band, the Supertrend moves to the upper band.
The Supertrend helps identify the prevailing market trend.
3. RSI (Relative Strength Index)
The RSI measures the momentum of price changes and ranges between 0 and 100:
Overbought Zone (Above 70): Indicates that the price may be overextended and due for a pullback.
Oversold Zone (Below 30): Indicates that the price may be undervalued and due for a reversal.
Visualization Features
Wick Trend Lines:
Upper wick trend (green) and lower wick trend (red) show the relative strength of price rejection on both sides.
Wick Trend Area:
The area between the upper and lower wick trends is filled dynamically:
Green: Upper wick trend is stronger.
Red: Lower wick trend is stronger.
Supertrend Line:
Displays the Supertrend as a blue line to highlight the market's directional bias.
RSI:
Plots the RSI line, with horizontal dotted lines marking the overbought (70) and oversold (30) levels.
Applications
Trend Confirmation:
Use the Supertrend and wick trends together to confirm the market's directional bias.
For example, a rising lower wick trend with a bullish Supertrend suggests strong bullish sentiment.
Momentum Analysis:
Combine the RSI with wick trends to assess the strength of price movements.
For example, if the RSI is oversold and the lower wick trend is increasing, it may signal a potential reversal.
Signal Generation:
Generate entry signals when all three indicators align:
Bullish Signal:
Lower wick trend increasing.
Supertrend bullish.
RSI rising from oversold.
Bearish Signal:
Upper wick trend increasing.
Supertrend bearish.
RSI falling from overbought.
Future Improvements
Alert System:
Add alerts for alignment of Supertrend, RSI, and wick trends:
pinescript
Kodu kopyala
alertcondition(upper_trend_direction == 1 and supertrend < close and rsi > 50, title="Bullish Signal", message="Bullish alignment detected.")
alertcondition(lower_trend_direction == 1 and supertrend > close and rsi < 50, title="Bearish Signal", message="Bearish alignment detected.")
Custom Thresholds:
Add thresholds for wick lengths and RSI levels to filter weak signals.
Multiple Timeframes:
Incorporate multi-timeframe analysis for more robust signal generation.
Conclusion
This script combines wick trends, Supertrend, and RSI to create a comprehensive framework for analyzing market sentiment and detecting potential trading opportunities. By visualizing trends, market bias, and momentum, traders can make more informed decisions and reduce reliance on single-indicator strategies.
EMA 50 + 200 Trend Signal TableEMA 50 + 200 Trend Signal Table (ETT)
This indicator provides a multi-timeframe trend signal table based on the 50-period and 200-period Exponential Moving Averages (EMAs). It visually plots the EMA 50 and EMA 200 on the chart, along with a customizable, compact table that indicates the trend direction across multiple timeframes. This tool is useful for traders looking to quickly identify market trends and momentum on various timeframes.
How It Works
- EMA Trend Analysis: The script compares the EMA 50 and EMA 200 values to determine the trend. When EMA 50 is above EMA 200, the trend is considered Bullish; if EMA 50 is below EMA 200, the trend is Bearish. If EMA 200 data is unavailable (e.g., on very short timeframes), the trend status will display as Neutral.
- Multi-Timeframe Trend Signals: The table displays the trend signals across five user-defined timeframes, updating in real time. Each timeframe row shows either Bullish, Bearish, or Neutral, with colors customizable to your preference.
Features
- EMA 50 and EMA 200 Visualization: Plots EMA 50 and EMA 200 lines directly on the chart. Users can customize the color and line thickness for each EMA to fit their charting style.
- Trend Signal Table: A table positioned on the chart (with options for positioning in the corners) shows the trend direction for the selected timeframes.
Bullish Trend: Highlighted in green (default) with 50% opacity.
Bearish Trend: Highlighted in red (default) with 50% opacity.
Neutral Trend: Highlighted in gray (default) with 50% opacity.
- Customizable Table Appearance: Allows users to select the position of the table (top-right, top-left, bottom-right, or bottom-left) and choose between compact sizes (Extra Small, Small, Normal).
- Adjustable Colors: Users can specify custom colors for each trend status (Bullish, Bearish, Neutral) as well as for the text and table border colors.
Inputs and Customizations
- Timeframes: Choose up to five different timeframes for trend analysis.
- EMA Colors and Line Widths: Customize the color and line width of EMA 50 and EMA 200 plotted on the chart.
- Table Settings: Control the position, size, and color options of the trend signal table for improved visibility and integration with your chart layout.
Use Case This indicator is ideal for traders who employ a multi-timeframe approach to confirm trends and filter entries. By monitoring the relative positions of EMA 50 and EMA 200 across various timeframes, traders can get a quick snapshot of trend strength and direction, aiding in informed trading decisions.
Exposure Oscillator (Cumulative 0 to ±100%)
Exposure Oscillator (Cumulative 0 to ±100%)
This Pine Script indicator plots an "Exposure Oscillator" on the chart, which tracks the cumulative market exposure from a range of technical buy and sell signals. The exposure is measured on a scale from -100% (maximum short exposure) to +100% (maximum long exposure), helping traders assess the strength of their position in the market. It provides an intuitive visual cue to aid decision-making for trend-following strategies.
Buy Signals (Increase Exposure Score by +10%)
Buy Signal 1 (Cross Above 21 EMA):
This signal is triggered when the price crosses above the 21-period Exponential Moving Average (EMA), where the current bar closes above the EMA21, and the previous bar closed below the EMA21. This indicates a potential upward price movement as the market shifts into a bullish trend.
buySignal1 = ta.crossover(close, ema21)
Buy Signal 2 (Trending Above 21 EMA):
This signal is triggered when the price closes above the 21-period EMA for each of the last 5 bars, indicating a sustained bullish trend. It confirms that the price is consistently above the EMA21 for a significant period.
buySignal2 = ta.barssince(close <= ema21) > 5
Buy Signal 3 (Living Above 21 EMA):
This signal is triggered when the price has closed above the 21-period EMA for each of the last 15 bars, demonstrating a strong, prolonged uptrend.
buySignal3 = ta.barssince(close <= ema21) > 15
Buy Signal 4 (Cross Above 50 SMA):
This signal is triggered when the price crosses above the 50-period Simple Moving Average (SMA), where the current bar closes above the 50 SMA, and the previous bar closed below it. It indicates a shift toward bullish momentum.
buySignal4 = ta.crossover(close, sma50)
Buy Signal 5 (Cross Above 200 SMA):
This signal is triggered when the price crosses above the 200-period Simple Moving Average (SMA), where the current bar closes above the 200 SMA, and the previous bar closed below it. This suggests a long-term bullish trend.
buySignal5 = ta.crossover(close, sma200)
Buy Signal 6 (Low Above 50 SMA):
This signal is true when the lowest price of the current bar is above the 50-period SMA, indicating strong bullish pressure as the price maintains itself above the moving average.
buySignal6 = low > sma50
Buy Signal 7 (Accumulation Day):
An accumulation day occurs when the closing price is in the upper half of the daily range (greater than 50%) and the volume is larger than the previous bar's volume, suggesting buying pressure and accumulation.
buySignal7 = (close - low) / (high - low) > 0.5 and volume > volume
Buy Signal 8 (Higher High):
This signal occurs when the current bar’s high exceeds the highest high of the previous 14 bars, indicating a breakout or strong upward momentum.
buySignal8 = high > ta.highest(high, 14)
Buy Signal 9 (Key Reversal Bar):
This signal is generated when the stock opens below the low of the previous bar but rallies to close above the previous bar’s high, signaling a potential reversal from bearish to bullish.
buySignal9 = open < low and close > high
Buy Signal 10 (Distribution Day Fall Off):
This signal is triggered when a distribution day (a day with high volume and a close near the low of the range) "falls off" the rolling 25-bar period, indicating the end of a bearish trend or selling pressure.
buySignal10 = ta.barssince(close < sma50 and close < sma50) > 25
Sell Signals (Decrease Exposure Score by -10%)
Sell Signal 1 (Cross Below 21 EMA):
This signal is triggered when the price crosses below the 21-period Exponential Moving Average (EMA), where the current bar closes below the EMA21, and the previous bar closed above it. It suggests that the market may be shifting from a bullish trend to a bearish trend.
sellSignal1 = ta.crossunder(close, ema21)
Sell Signal 2 (Trending Below 21 EMA):
This signal is triggered when the price closes below the 21-period EMA for each of the last 5 bars, indicating a sustained bearish trend.
sellSignal2 = ta.barssince(close >= ema21) > 5
Sell Signal 3 (Living Below 21 EMA):
This signal is triggered when the price has closed below the 21-period EMA for each of the last 15 bars, suggesting a strong downtrend.
sellSignal3 = ta.barssince(close >= ema21) > 15
Sell Signal 4 (Cross Below 50 SMA):
This signal is triggered when the price crosses below the 50-period Simple Moving Average (SMA), where the current bar closes below the 50 SMA, and the previous bar closed above it. It indicates the start of a bearish trend.
sellSignal4 = ta.crossunder(close, sma50)
Sell Signal 5 (Cross Below 200 SMA):
This signal is triggered when the price crosses below the 200-period Simple Moving Average (SMA), where the current bar closes below the 200 SMA, and the previous bar closed above it. It indicates a long-term bearish trend.
sellSignal5 = ta.crossunder(close, sma200)
Sell Signal 6 (High Below 50 SMA):
This signal is true when the highest price of the current bar is below the 50-period SMA, indicating weak bullishness or a potential bearish reversal.
sellSignal6 = high < sma50
Sell Signal 7 (Distribution Day):
A distribution day is identified when the closing range of a bar is less than 50% and the volume is larger than the previous bar's volume, suggesting that selling pressure is increasing.
sellSignal7 = (close - low) / (high - low) < 0.5 and volume > volume
Sell Signal 8 (Lower Low):
This signal occurs when the current bar's low is less than the lowest low of the previous 14 bars, indicating a breakdown or strong downward momentum.
sellSignal8 = low < ta.lowest(low, 14)
Sell Signal 9 (Downside Reversal Bar):
A downside reversal bar occurs when the stock opens above the previous bar's high but falls to close below the previous bar’s low, signaling a reversal from bullish to bearish.
sellSignal9 = open > high and close < low
Sell Signal 10 (Distribution Cluster):
This signal is triggered when a distribution day occurs three times in the rolling 7-bar period, indicating significant selling pressure.
sellSignal10 = ta.valuewhen((close < low) and volume > volume , 1, 7) >= 3
Theme Mode:
Users can select the theme mode (Auto, Dark, or Light) to match the chart's background or to manually choose a light or dark theme for the oscillator's appearance.
Exposure Score Calculation: The script calculates a cumulative exposure score based on a series of buy and sell signals.
Buy signals increase the exposure score, while sell signals decrease it. Each signal impacts the score by ±10%.
Signal Conditions: The buy and sell signals are derived from multiple conditions, including crossovers with moving averages (EMA21, SMA50, SMA200), trend behavior, and price/volume analysis.
Oscillator Visualization: The exposure score is visualized as a line on the chart, changing color based on whether the exposure is positive (long position) or negative (short position). It is limited to the range of -100% to +100%.
Position Type: The indicator also indicates the position type based on the exposure score, labeling it as "Long," "Short," or "Neutral."
Horizontal Lines: Reference lines at 0%, 100%, and -100% visually mark neutral, increasing long, and increasing short exposure levels.
Exposure Table: A table displays the current exposure level (in percentage) and position type ("Long," "Short," or "Neutral"), updated dynamically based on the oscillator’s value.
Inputs:
Theme Mode: Choose "Auto" to use the default chart theme, or manually select "Dark" or "Light."
Usage:
This oscillator is designed to help traders track market sentiment, gauge exposure levels, and manage risk. It can be used for long-term trend-following strategies or short-term trades based on moving average crossovers and volume analysis.
The oscillator operates in conjunction with the chart’s price action and provides a visual representation of the market’s current trend strength and exposure.
Important Considerations:
Risk Management: While the exposure score provides valuable insight, it should be combined with other risk management tools and analysis for optimal trading decisions.
Signal Sensitivity: The accuracy and effectiveness of the signals depend on market conditions and may require adjustments based on the user’s trading strategy or timeframe.
Disclaimer:
This script is for educational purposes only. Trading involves significant risk, and users should carefully evaluate all market conditions and apply appropriate risk management strategies before using this tool in live trading environments.
Inversion Fair Value Gap Oscillator | Flux Charts💎 GENERAL OVERVIEW
Introducing the new Inversion Fair Value Gap Oscillator (IFVG Oscillator) indicator! This unique indicator identifies and tracks Inversion Fair Value Gaps (IFVGs) in price action, presenting them in an oscillator format to reveal market momentum based on IFVG strength. It highlights bullish and bearish IFVGs while enabling traders to adjust detection sensitivity and apply volume and ATR-based filters for more precise setups. For more information about the process, check the "📌 HOW DOES IT WORK" section.
Features of the new IFVG Oscillator:
Fully Customizable FVG & IFVG Detection
An Oscillator Approach To IFVGs
Divergence Markers For Potential Reversals
Alerts For Divergence Labels
Customizable Styling
📌 HOW DOES IT WORK?
Fair Value Gaps are price gaps within bars that indicate inefficiencies, often filled as the market retraces. An Inversion Fair Value Gap is created in the opposite direction once a FVG gets invalidated. The IFVG Oscillator scans historical bars to identify these gaps, then filters them based on ATR or volume. Each IFVG is marked as bullish or bearish according to the opposite direction of the original FVG that got invalidated.
An oscillator is calculated using recent IFVGs with this formula :
1. The Oscillator starts as 0.
2. When a new IFVG Appears, it contributes (IFVG Width / ATR) to the oscillator of the corresponding type.
3. Each confirmed bar, the oscillator is recalculated as OSC = OSC * (1 - Decay Coefficient)
The oscillator aggregates and decays past IFVGs, allowing recent IFVG activity to dominate the signal. This approach emphasizes current market momentum, with oscillations moving bullish or bearish based on IFVG intensity. Divergences are marked where IFVG oscillations suggest potential reversals. Bullish Divergence conditions are as follows :
1. The current candlestick low must be the lowest of last 25 bars.
2. Net Oscillator (Shown in gray line by default) must be > 0.
3. The current Bullish IFVG Oscillator value should be no more than 0.1 below the highest value from the last 25 bars.
Traders can use divergence signals to get an idea of potential reversals, and use the Net IFVG Oscillator as a trend following marker.
🚩 UNIQUENESS
The Inversion Fair Value Gap Oscillator stands out by converting IFVG activity into an oscillator format, providing a momentum-based visualization of IFVGs that reveals market sentiment dynamically. Unlike traditional indicators that statically mark IFVG zones, the oscillator decays older IFVGs over time, showing only the most recent, relevant activity. This approach allows for real-time insight into market conditions and potential reversals based on oscillating IFVG strength, making it both intuitive and powerful for momentum trading.
Another unique feature is the combination of customizable ATR and volume filters, letting traders adapt the indicator to match their strategy and market type. You can also set-up alerts for bullish & bearish divergences.
⚙️ SETTINGS
1. General Configuration
Decay Coefficient -> The decay coefficient for oscillators. Increasing this setting will result in oscillators giving the weight to recent IFVGs, while decreasing it will distribute the weight equally to the past and recent IFVGs.
2. Fair Value Gaps
Zone Invalidation -> Select between Wick & Close price for FVG Zone Invalidation.
Zone Filtering -> With "Average Range" selected, algorithm will find FVG zones in comparison with average range of last bars in the chart. With the "Volume Threshold" option, you may select a Volume Threshold % to spot FVGs with a larger total volume than average.
FVG Detection -> With the "Same Type" option, all 3 bars that formed the FVG should be the same type. (Bullish / Bearish). If the "All" option is selected, bar types may vary between Bullish / Bearish.
Detection Sensitivity -> You may select between Low, Normal or High FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
3. Inversion Fair Value Gaps
Zone Invalidation -> Select between Wick & Close price for IFVG Zone Invalidation.
4. Style
Divergence Labels On -> You can switch divergence labels to show up on the chart or the oscillator plot.
Arshtiq - Multi-Timeframe Trend StrategyMulti-Timeframe Setup:
The script uses two distinct timeframes: a higher (daily) timeframe for identifying the trend and a lower (hourly) timeframe for making trades. This combination allows the script to follow the larger trend while timing entries and exits with more precision on a shorter timeframe.
Moving Averages Calculation:
higher_ma: The 20-period Simple Moving Average (SMA) calculated based on the daily timeframe. This average gives a sense of the larger trend direction.
lower_ma: The 20-period SMA calculated on the hourly (current) timeframe, providing a dynamic level for detecting entry and exit points within the broader trend.
Trend Identification:
Bullish Trend: The script determines that a bullish trend is present if the current price is above the daily moving average (higher_ma).
Bearish Trend: Similarly, a bearish trend is identified when the current price is below this daily moving average.
Trade Signals:
Buy Signal: A buy signal is generated when the price on the hourly chart crosses above the hourly 20-period MA, but only if the higher (daily) timeframe trend is bullish. This ensures that buy trades align with the larger upward trend.
Sell Signal: A sell signal is generated when the price on the hourly chart crosses below the hourly 20-period MA, but only if the daily trend is bearish. This ensures that sell trades are consistent with the broader downtrend.
Plotting and Visual Cues:
Higher Timeframe MA: The daily 20-period moving average is plotted in red to help visualize the long-term trend.
Buy and Sell Signals: Buy signals appear as green labels below the price bars with the text "BUY," while sell signals appear as red labels above the bars with the text "SELL."
Background Coloring: The background changes color based on the identified trend for easier trend recognition:
Green (with transparency) when the daily trend is bullish.
Red (with transparency) when the daily trend is bearish.
