Squeeze mom MTF filtered by Wavetrend with div (Tilt)📋 Description :
This script is based on two famous indicators from @Lazybear : Squeeze Momentum and WaveTrend. fr.tradingview.com
The idea is to use the Wavetrend crossovers and filter them according to the momentum curve.
There is a multi timeframe module with automatic selection of the higher timeframe. The user can also choose his timeframe manually.
There is also a detection of regular and hidden divergences
🛠 Options :
- filtering the cross wave trend according to the momemtum curve
- active or not higher timeframe with automatic or manually timeframe selection
- display or not WaveTrend ans squeeze momentum
- Show a tape that signals when wavetrend is overbought or oversold
- choose colors and apparences
- display a panel for the higher timeframe value
Komut dosyalarını "momentum" için ara
Natural Market River [CC]The Natural Market River was created by Jim Sloman (Ocean Theory pgs 59-62) and this is another momentum indicator that is extremely similar to the previous indicator I published, the Natural Market Mirror . This has almost identical buy and sell signals but different way to handle calculations so I'm going to leave it up to you which one you will prefer. Since this is almost identical, the buy and sell signals work in the same way with both strong signals and normal ones. Buy when the line turns green and sell when it turns red.
Let me know what other indicators you would like to see me publish!
Natural Market Mirror [CC]The Natural Market Mirror was created by Jim Sloman (Ocean Theory pgs 49-57) and this is a continuation of my series from Jim Sloman's indicators. This indicator is also a momentum indicator and is very similar to the previous indicator I published, the Ocean Indicator and of course this indicator is built using ideas from the Ocean indicator. It may just be my opinion but I feel like this indicator provides better buy and sell signals in comparison. I built this using strong buy and sell indicators in addition to normal ones so darker colors are the strong signals and lighter colors are the normal signals. Buy when the line turns green and sell when it turns red.
Let me know what other indicators you would like me to publish!
Market phases 2.0The Market Phase 2.0 indicator is designed to display the following features:
1) The TREND OSCILLATOR : This trend oscillator indicates the trend of the stock/instrument. It is calculated on the basis of number of positive candles or negative candles formed during a specific period.
The oscillator oscillates around the zero horizontal line. The trend is considered bullish if the oscillator value is positive and the trend is considered negative if the oscillator value is negative.
2) The MOMENTUM OSCILLATOR:
The momentum oscillator indicates the short term momentum of the stock/instrument. It is calculated on the rate of change of close price for a specific period in the past.
The Momentum oscillator oscillates around the zero horizontal line. If the momentum oscillator has a positive value, the momentum is considered to be on the bullish side and similarly if the momentum oscillator has a negative value, the momentum is considered to be on the bearish side.
3) The SIGNAL LINE: The signal line is represented by the yellow color line. The Signal line combines the value of the Trend oscillator and the Momentum oscillator. The signal also moves around the zero line. There are two dotted lines above and below the zero line.
When the signal line crosses the upper dotted line, it indicates that the stock/instrument has moved on the upper side too quickly or sharply and the ongoing move may not continue for long. It may also be considered as overbought at that point. A red triangle appears at that point.
Similarly, when the signal line crosses the lower dotted line, it indicates that the stock/instrument has moved on the downside too quickly or sharply and the ongoing down move may not continue for long. It may also be considered as oversold at that point. A green triangle appears at that point.
The values for the look back period of the signal line and the values for the upper range and lower range of the indicator can be changed by going to the settings of the indicator.
***Disclaimer: The market movement depends upon a lot of factors which are beyond the scope of this indicator. Hence the indicator may display results not intended on rare occasions.
Trading in the markets involves involves huge risks and one should always follow his/her own research before taking any trading decisions.
Relative Strength Line by @iArpanKHello Traders!
I'm a Momentum Trader, following the Indian & US markets. Most of us are familiar with the Relative Strength (RS) indicator, popularized by Investor's Business Daily (IBD) and available on their MarketSmith platform. So, here I'm sharing a script that does the same and additionally pops an alert label when the RS line hits a new high (similar to Blue Dot appearance on MarketSmith charts).
User Settings
Inputs tab
Base Symbol : Symbol of the security/index with which you want to compare your current active symbol.
Period : Number of days since which you want to scan for a new high (default is 250 days, which approximately pops alerts for new 52 week high in RS). For example, if you want to look for new 10 days high in RS, set the Period to 10.
Style tab
RS Line : Change color using the palette provided (default is blue).
Alert Label : Show/hide alert labels by checking/unchecking the box. Change color using the palette provided. Change alert label symbol.
Precision : Default is two decimal places. Can be changed as per requirement.
Usage
The indicator consists of two components- the Relative Strength (RS) line & alert labels on new RS highs. Relative strength gives a measure of how the underlying security is performing with respect to a base index or security. For example, how is NSE:DIXON performing w.r.t NSE:NIFTY or how is NASDAQ:AAPL performing w.r.t. the TVC:SPX .
A rising RS line tells us that the underlying entity is outperforming the base entity. Similarly, a declining RS line shows under-performance of the underlying entity. A new high in RS (especially before a new high in price) often gives valuable information about the underlying security's strength w.r.t. the general market, and can tip us off to a possible breakout in the price in near future.
Making RS lists (list of stocks making new high in RS on heavy down days in index) can be very helpful to sort out leaders that are best resisting the decline and are likely to move up aggressively when the market turns favorable.
The concept of RS is extensively used by momentum traders and growth stock traders. When used in conjunction with price & volume action, this can be a very powerful tool in your trading arsenal. You can now easily spot RS trends and new highs visually by simply adding this indicator to your chart!
Conclusion
If you like this script, click on Add to favorite indicators , so that you can easily add this indicator from your favorites tab right away.
Thanks!
MACD Trend Squeezer V2This is a combination of a slightly sped up MACD overlay on top of a modified Bar Trend Squeeze or highly modified Momentum indicator. Helps to see the trend/momentum matched with the characteristics of the MACD and it's historiography. Very user friendly for adjusting color, transparency, depth, lines, size, etc.
MACD is the dark gray line.
Its signal slower line is orange.
Its historiography is the area fill blues and reds
Trend Squeezer / momentum are the Bars in the background.
// Changes from original version \\
Visual depth mostly. Most of the items are adjustable in the settings.
Increased user friendly inputs to adjust colors, lines, data, etc.
(darken / lighten and change background bar colors, increase/decrease line strengths and colors, adjust field data inputs)
The DiamondThe Diamond is a collection of 3 custom oscillators and the RSI. It tries to visualizing how the momentum is increasing and decreasing and gives some buy and sell signals.
Every Line explained:
Orange line: The SMI(Swing Momentum Indicator) it is alternating oscillator between the value -10 and 40 and has its baseline at 10. It showing accumulation and increase of momentum and is used as a trend confirmation
Purple line: The BTD(Buy the Dip) is a modified Version of the SMI. It should be used in Bull or Bearflags to time entries. Also the Horizontal lines can be used as Support or Resistance
Green/Red Band: This one is a custom made stochastic. In its calculation it smoothing Tops/Lows to reduce noise. Also the look is better.
White line: Just a 14-lenght RSI. I use it together with the SMI and BTD to get confirmation
The Indicator is doing best in the crypto market. High market cap Coins/USDT Pairs do better than low market cap and btc pairs. Also it should be only used on timeframes greater than 4h. 6h and daily preferred. On higher time frames you need to adjust the values of the BTD and SMI.
Bearish divergence on both Indicators in a down trending market do give a good short entry.
Bullish divergence on the daily gives good swing entries in a downtrend
Hophop Multiple Timeframe Momentum GridThis indicator is intended to highlight the over bought and over sold momentums for multiple timeframe
As of now it only supports StochRSI and also a variation of it that is more responsive than StochRsi called HophopRsi, I might consider adding more momentum indicators if it is desired
All the needed variables for StochRsi are included as the original indicator, feel free to change them as you normally do on StochRsi
On top of that you can select up to 4 higher timeframe , just make sure that your current timeframe is the smallest one
The top line of the graph shows the current timeframe momentum
1st line = high timeframe 1
2st line = high timeframe 2
3st line = high timeframe 3
4st line = high timeframe 4
Quick demonstration of the usage:
If you benefit from this indicator and you would like to see more of these, please support me by your tips
BTC Tip: 39bwXN1chms1yHskBaYwz76UhDakc7grJ7
LTC Tip: MGD3U9dBCBVctwnoCa1grU8ompxG6hUhMk
ETH Tip: 0xEE9684a5aceE85036527aB48E596DeE4627bD84b
Compare - Oscillator vs BTC momentumI've made a simple indicator to compare the momentum of a trading pair against the momentum of BTC to the dollar. I use it to see how a pair is affected by BTC's momentum... I wouldnt use it to trade off alone, but it can be a useful tool alongside other indicators.
The time range can be adjusted, but I wouldnt reccomend setting it to anything over 12M, or under 1W.... as I'm not sure if it would work.
Any feedback is welcome!
This is an idea I had after looking at a wonderful visualisation made by BarclayJames, link below:
www.tradingview.com
Directional Trend Index (DTI) This technique was described by William Blau in his book "Momentum,
Direction and Divergence" (1995). His book focuses on three key aspects
of trading: momentum, direction and divergence. Blau, who was an electrical
engineer before becoming a trader, thoroughly examines the relationship between
price and momentum in step-by-step examples. From this grounding, he then looks
at the deficiencies in other oscillators and introduces some innovative techniques,
including a fresh twist on Stochastics. On directional issues, he analyzes the
intricacies of ADX and offers a unique approach to help define trending and
non-trending periods.
Directional Trend Index is an indicator similar to DM+ developed by Welles Wilder.
The DM+ (a part of Directional Movement System which includes both DM+ and
DM- indicators) indicator helps determine if a security is "trending." William
Blau added to it a zeroline, relative to which the indicator is deemed positive or
negative. A stable uptrend is a period when the DTI value is positive and rising, a
downtrend when it is negative and falling.
TrendShield Pro | DinkanWorldTrendShield Pro is a powerful price action tool that combines momentum-based trend detection with an ATR-powered trailing stop system. Built using EMA and ATR logic, this indicator helps traders identify real trends, manage dynamic stop-loss levels, and react faster to momentum shifts — all with visual clarity.
🔍 Key Features:
✅ Momentum + Price Action Based Trend Detection
✅ Dynamic ATR Trailing Stop Line
✅ Real-Time Reversal Arrows and Diamond Alerts
✅ Optimized CandleTrack color theme (Green = Demand, Red = Supply)
✅ Fully customizable inputs
🧠 Why Use It?
Capture trends early with momentum-driven logic
Use trailing stops for exit strategy or re-entry zones
Stay on the right side of the market with visual confirmation
⚙️ Inputs:
EMA Period (for directional bias)
ATR Period (for volatility-based trailing stops)
Factor (stop distance control)
⚠️ Disclaimer:
This indicator is for educational and informational purposes only and should not be considered financial advice. Trading involves risk, and past performance does not guarantee future results. Always do your own research and consult with a licensed financial advisor before making any trading decisions. The creator of this script is not responsible for any financial losses incurred through the use of this tool.
TheDevashishratio-MomentumThis custom momentum indicator is inspired by Fibonacci principles but builds a unique sequence with steps of 0.5 (i.e., 0, 0.5, 1, 1.5, 2, ...). Instead of traditional Fibonacci numbers, each step functions as a dynamic lookback period for a momentum calculation. By cycling through these fractional steps, you capture a layered view of price momentum over varying intervals.
The "Fibonacci" Series Used
Sequence:
0, 0.5, 1, 1.5, 2, … up to a user-defined maximum
For trading indicators, lag values (lookback) must be integers, so each step is rounded to the nearest integer and duplicates are removed, resulting in lookbacks:
1, 2, 3, 4, ... N
Indicator Logic
For each selected lookback, the indicator calculates momentum as:
Momentum
n
=
close
−
close
Momentum
n
=close−close
Where:
close = current price
n = integer from your series of
You can combine these momenta for an averaged or weighted momentum profile, displaying the composite as an oscillator.
How To Use
Bullish: Oscillator above zero indicates positive composite momentum.
Bearish: Oscillator below zero indicates negative composite momentum.
Crosses: A cross from below to above zero may signal emerging bullish momentum, and vice versa.
Customization
Adjust max_step to control how many interval lags you want in your composite.
This oscillator averages across many short and mid-term momenta, reducing noise while still being sensitive to changes.
Summary
TheDevashishratio-Momentum offers a fresh momentum oscillator, blending a "Fibonacci-like" progression with technical analysis, and can be easily copy-pasted into TradingView to experiment and refine your edge.
For more on momentum indicator logic or how to use arrays and series in Pine Script, explore TradingView's official documentation and open-source scripts
Step Channel Momentum Trend [ChartPrime]OVERVIEW
Step Channel Momentum Trend is a momentum-based price filtering system that adapts to market structure using pivot levels and ATR volatility. It builds a dynamic channel around a stepwise midline derived from swing highs and lows. The system colors price candles based on whether price remains inside this channel (low momentum) or breaks out (strong directional flow). This allows traders to clearly distinguish ranging conditions from trending ones and take action accordingly.
⯁ STRUCTURAL MIDLNE (STEP CHANNEL CORE)
The midline acts as the backbone of the trend system and is based on structure rather than smoothing.
Calculated as the average of the most recent confirmed Pivot High and Pivot Low.
The result is a step-like horizontal line that only updates when new pivot points are confirmed.
This design avoids lag and makes the line "snap" to recent structural shifts.
It reflects the equilibrium level between recent bullish and bearish control.
This unique step logic creates clear regime shifts and prevents noise from distorting trend interpretation.
⯁ DYNAMIC VOLATILITY BANDS (ATR FILTERING)
To detect momentum strength, the script constructs upper and lower bands using the ATR (Average True Range):
The distance from the midline is determined by ATR × multiplier (default: 200-period ATR × 0.6).
These bands adjust dynamically to volatility, expanding in high-ATR environments and contracting in calm markets.
The area between upper and lower bands represents a neutral or ranging market state.
Breakouts outside the bands are treated as significant momentum shifts.
This filtering approach ensures that only meaningful breakouts are visually emphasized — not every candle fluctuation.
⯁ MOMENTUM-BASED CANDLE COLORING
The system visually transforms price candles into momentum indicators:
When price (hl2) is above the upper band, candles are green → bullish momentum.
When price is below the lower band, candles are red → bearish momentum.
When price is between the bands, candles are orange → low or no momentum (range).
The candle body, wick, and border are all colored uniformly for visual clarity.
This gives traders instant feedback on when momentum is expanding or fading — ideal for breakout, pullback, or trend-following strategies.
⯁ PIVOT-BASED SWING ANCHORS
Each confirmed pivot is plotted as a label ⬥ directly on the chart:
They also serve as potential manual entry zones, SL/TP anchors, or confirmation points.
⯁ MOMENTUM STATE LABEL
To reinforce the current market mode, a live label is displayed at the most recent candle:
Displays either:
“ Momentum Up ” when price breaks above the upper band.
“ Momentum Down ” when price breaks below the lower band.
“ Range ” when price remains between the bands.
Label color matches the candle color for quick identification.
Automatically updates on each bar close.
This helps discretionary traders filter trades based on market phase.
USAGE
Use the green/red zones to enter with momentum and ride trending moves.
Use the orange zone to stay out or fade ranges.
The step midline can act as a breakout base, pullback anchor, or bias reference.
Combine with other indicators (e.g., order blocks, divergences, or volume) to build high-confluence systems.
CONCLUSION
Step Channel Momentum Trend gives traders a clean, adaptive framework for identifying trend direction, volatility-based breakouts, and ranging environments — all from structural logic and ATR responsiveness. Its stepwise midline provides clarity, while its dynamic color-coded candles make momentum shifts impossible to miss. Whether you’re scalping intraday momentum or managing swing entries, this tool helps you trade with the market’s rhythm — not against it.
Money Flow Pulse💸 In markets where volatility is cheap and structure is noisy, what matters most isn’t just the move — it’s the effort behind it. Money Flow Pulse (MFP) offers a compact, color-coded readout of real-time conviction by scoring volume-weighted price action on a five-tier scale. It doesn’t try to predict reversals or validate trends. Instead, it reveals the quality of the move in progress: is it fading , driving , exhausting , or hollow ?
🎨 MFP draws from the traditional Money Flow Index (MFI), a volume-enhanced momentum oscillator, but transforms it into a modular “pressure readout” that fits seamlessly into any structural overlay. Rather than oscillating between extremes with little interpretive guidance, MFP discretizes the flow into clean, color-coded regimes ranging from strong inflow (+2) to strong outflow (–2). The result is a responsive diagnostic layer that complements, rather than competes with, tools like ATR and/or On-Balance Volume.
5️⃣ MFP uses a normalized MFI value smoothed over 13 periods and classified into a 5-tier readout of Volume-Driven Conviction :
🍆 Exhaustion Inflow — usually a top or blowoff; not strength, but overdrive (+2)
🥝 Active Inflow — supportive of trend continuation (+1)
🍋 Neutral — chop, coil, or fakeouts (0)
🍑 Selling Intent — weakening structure, possible fade setups (-1)
🍆 Exhaustion Outflow — often signals forced selling or accumulation traps (-2)
🎭 These tiers are not arbitrary. Each one is tuned to reflect real capital behavior across timeframes. For instance, while +1 may support continuation, +2 often precedes exhaustion — especially on the lower timeframes. Similarly, a –1 reading during a pullback suggests sell-side pressure is building, but a shift to –2 may mean capitulation is already underway. The difference between the two can define whether a move is tradable continuation or strategic exhaustion .
🌊 The MFI ROC (Rate of Change) feature can be toggled to become a volatility-aware pulse monitor beneath the derived MFI tier. Instead of scoring direction or structure, ROC reveals how fast conviction is changing — not just where it’s headed, but how hard it's accelerating or decaying. It measures the raw Δ between the current and previous MFI values, exposing bursts of energy, fading pressure, or transitional churn .
🎢 Visually, ROC appears as a low-opacity area fill, anchored to a shared lemon-yellow zero line. When the green swell rises, buying pressure is accelerating; when the red drops, flow is actively deteriorating. A subtle bump may signal early interest — while a steep wave hints at an emotional overreaction. The ROC value itself provides numeric insight alongside the raw MFI score. A reading of +3.50 implies strong upside momentum in the flow — often supporting trend ignition. A score of –6.00 suggests rapid deceleration or full exhaustion — often preceding reversals or failed breakouts.
・ MFI shows you where the flow is
・ ROC tells you how it’s behaving
😎 This blend reveals not just structure or intent — but also urgency . And in flow-based trading, urgency often precedes outcome.
🧩 Divergence isn’t delay — it’s disagreement . One of the most revealing features of MFP is how it exposes momentum dissonance — situations where price and flow part ways. These divergences often front-run pivots , traps , or velocity stalls . Unlike RSI-style divergence, which whispers of exhaustion, MFI divergence signals a breakdown in conviction. The structure may extend — but the effort isn’t there.
・ Price ▲ MFI ▼ → Effortless Markup : Often signals distribution or a grind into liquidity. Without rising MFI, the rally lacks true flow participation — a warning of fragility.
・ Price ▼ MFI ▲ → Absorption or Early Accumulation : Price breaks down, but money keeps flowing in — a hidden bid. Watch for MFI tier shifts or ROC bursts to confirm a reversal.
🏄♂️ These moments don’t require signal overlays or setup hunting. MFP narrates the imbalance. When price breaks structure but flow does not — or vice versa — you’re not seeing trend, you’re seeing disagreement, and that's where edge begins.
💤 MFP is especially effective on intraday charts where volume dislocations matter most. On the 1H or 15m chart, it helps distinguish between breakouts with conviction versus those lacking flow. On higher timeframes, its resolution softens — it becomes more of a drift indicator than a trigger device. That’s by design: MFP prioritizes pulse, not position. It’s not the fire, it’s the heat.
📎 Use MFP in confluence with structural overlays to validate price behavior. A ribbon expansion with rising MFP is real. A compression breakout without +1 flow is "fishy". Watch how MFP behaves near key zones like anchored VWAP, MAs or accumulation pivots. When MFP rises into a +2 and fails to sustain, the reversal isn’t just technical — it’s flow-based.
🪟 MFP doesn’t speak loudly, but it never whispers without reason. It’s the pulse check before action — the breath of the move before the breakout. While it stays visually minimal on the chart, the true power is in the often overlooked Data Window, where traders can read and interpret the score in real time. Once internalized, these values give structure-aware traders a framework for conviction, continuation, or caution.
🛜 MFP doesn’t chase momentum — it confirms conviction. And in markets defined by noise, that signal isn’t just helpful — it’s foundational.
Stochastic Order Flow Momentum [ScorsoneEnterprises]This indicator implements a stochastic model of order flow using the Ornstein-Uhlenbeck (OU) process, combined with a Kalman filter to smooth momentum signals. It is designed to capture the dynamic momentum of volume delta, representing the net buying or selling pressure per bar, and highlight potential shifts in market direction. The volume delta data is sourced from TradingView’s built-in functionality:
www.tradingview.com
For a deeper dive into stochastic processes like the Ornstein-Uhlenbeck model in financial contexts, see these research articles: arxiv.org and arxiv.org
The SOFM tool aims to reveal the momentum and acceleration of order flow, modeled as a mean-reverting stochastic process. In markets, order flow often oscillates around a baseline, with bursts of buying or selling pressure that eventually fade—similar to how physical systems return to equilibrium. The OU process captures this behavior, while the Kalman filter refines the signal by filtering noise. Parameters theta (mean reversion rate), mu (mean level), and sigma (volatility) are estimated by minimizing a squared-error objective function using gradient descent, ensuring adaptability to real-time market conditions.
How It Works
The script combines a stochastic model with signal processing. Here’s a breakdown of the key components, including the OU equation and supporting functions.
// Ornstein-Uhlenbeck model for volume delta
ou_model(params, v_t, lkb) =>
theta = clamp(array.get(params, 0), 0.01, 1.0)
mu = clamp(array.get(params, 1), -100.0, 100.0)
sigma = clamp(array.get(params, 2), 0.01, 100.0)
error = 0.0
v_pred = array.new(lkb, 0.0)
array.set(v_pred, 0, array.get(v_t, 0))
for i = 1 to lkb - 1
v_prev = array.get(v_pred, i - 1)
v_curr = array.get(v_t, i)
// Discretized OU: v_t = v_{t-1} + theta * (mu - v_{t-1}) + sigma * noise
v_next = v_prev + theta * (mu - v_prev)
array.set(v_pred, i, v_next)
v_curr_clean = na(v_curr) ? 0 : v_curr
v_pred_clean = na(v_next) ? 0 : v_next
error := error + math.pow(v_curr_clean - v_pred_clean, 2)
error
The ou_model function implements a discretized Ornstein-Uhlenbeck process:
v_t = v_{t-1} + theta (mu - v_{t-1})
The model predicts volume delta (v_t) based on its previous value, adjusted by the mean-reverting term theta (mu - v_{t-1}), with sigma representing the volatility of random shocks (approximated in the Kalman filter).
Parameters Explained
The parameters theta, mu, and sigma represent distinct aspects of order flow dynamics:
Theta:
Definition: The mean reversion rate, controlling how quickly volume delta returns to its mean (mu). Constrained between 0.01 and 1.0 (e.g., clamp(array.get(params, 0), 0.01, 1.0)).
Interpretation: A higher theta indicates faster reversion (short-lived momentum), while a lower theta suggests persistent trends. Initial value is 0.1 in init_params.
In the Code: In ou_model, theta scales the pull toward \mu, influencing the predicted v_t.
Mu:
Definition: The long-term mean of volume delta, representing the equilibrium level of net buying/selling pressure. Constrained between -100.0 and 100.0 (e.g., clamp(array.get(params, 1), -100.0, 100.0)).
Interpretation: A positive mu suggests a bullish bias, while a negative mu indicates bearish pressure. Initial value is 0.0 in init_params.
In the Code: In ou_model, mu is the target level that v_t reverts to over time.
Sigma:
Definition: The volatility of volume delta, capturing the magnitude of random fluctuations. Constrained between 0.01 and 100.0 (e.g., clamp(array.get(params, 2), 0.01, 100.0)).
Interpretation: A higher sigma reflects choppier, noisier order flow, while a lower sigma indicates smoother behavior. Initial value is 0.1 in init_params.
In the Code: In the Kalman filter, sigma contributes to the error term, adjusting the smoothing process.
Summary:
theta: Speed of mean reversion (how fast momentum fades).
mu: Baseline order flow level (bullish or bearish bias).
sigma: Noise level (variability in order flow).
Other Parts of the Script
Clamp
A utility function to constrain parameters, preventing extreme values that could destabilize the model.
ObjectiveFunc
Defines the objective function (sum of squared errors) to minimize during parameter optimization. It compares the OU model’s predicted volume delta to observed data, returning a float to be minimized.
How It Works: Calls ou_model to generate predictions, computes the squared error for each timestep, and sums it. Used in optimization to assess parameter fit.
FiniteDifferenceGradient
Calculates the gradient of the objective function using finite differences. Think of it as finding the "slope" of the error surface for each parameter. It nudges each parameter (theta, mu, sigma) by a small amount (epsilon) and measures the change in error, returning an array of gradients.
Minimize
Performs gradient descent to optimize parameters. It iteratively adjusts theta, mu, and sigma by stepping down the "hill" of the error surface, using the gradients from FiniteDifferenceGradient. Stops when the gradient norm falls below a tolerance (0.001) or after 20 iterations.
Kalman Filter
Smooths the OU-modeled volume delta to extract momentum. It uses the optimized theta, mu, and sigma to predict the next state, then corrects it with observed data via the Kalman gain. The result is a cleaner momentum signal.
Applied
After initializing parameters (theta = 0.1, mu = 0.0, sigma = 0.1), the script optimizes them using volume delta data over the lookback period. The optimized parameters feed into the Kalman filter, producing a smoothed momentum array. The average momentum and its rate of change (acceleration) are calculated, though only momentum is plotted by default.
A rising momentum suggests increasing buying or selling pressure, while a flattening or reversing momentum indicates fading activity. Acceleration (not plotted here) could highlight rapid shifts.
Tool Examples
The SOFM indicator provides a dynamic view of order flow momentum, useful for spotting directional shifts or consolidation.
Low Time Frame Example: On a 5-minute chart of SEED_ALEXDRAYM_SHORTINTEREST2:NQ , a rising momentum above zero with a lookback of 5 might signal building buying pressure, while a drop below zero suggests selling dominance. Crossings of the zero line can mark transitions, though the focus is on trend strength rather than frequent crossovers.
High Time Frame Example: On a daily chart of NYSE:VST , a sustained positive momentum could confirm a bullish trend, while a sharp decline might warn of exhaustion. The mean-reverting nature of the OU process helps filter out noise on longer scales. It doesn’t make the most sense to use this on a high timeframe with what our data is.
Choppy Markets: When momentum oscillates near zero, it signals indecision or low conviction, helping traders avoid whipsaws. Larger deviations from zero suggest stronger directional moves to act on, this is on $STT.
Inputs
Lookback: Users can set the lookback period (default 5) to adjust the sensitivity of the OU model and Kalman filter. Shorter lookbacks react faster but may be noisier; longer lookbacks smooth more but lag slightly.
The user can also specify the timeframe they want the volume delta from. There is a default way to lower and expand the time frame based on the one we are looking at, but users have the flexibility.
No indicator is 100% accurate, and SOFM is no exception. It’s an estimation tool, blending stochastic modeling with signal processing to provide a leading view of order flow momentum. Use it alongside price action, support/resistance, and your own discretion for best results. I encourage comments and constructive criticism.
JW Momentum IndicatorJW Momentum Indicator
This indicator provides clear and actionable buy/sell signals based on a combination of volume-enhanced momentum, divergence detection, and volatility adjustment. It's designed to identify potential trend reversals and momentum shifts with a focus on high-probability setups.
Key Features:
Volume-Enhanced Momentum: The indicator calculates a custom oscillator that combines momentum with volume, giving more weight to momentum when volume is significant. This helps to identify strong momentum moves.
Divergence Detection: It detects bullish and bearish divergences using pivot highs and lows, highlighting potential trend reversals.
Volatility-Adjusted Signals: The indicator adjusts signal sensitivity based on the Average True Range (ATR), making it more reliable in varying market conditions.
Clear Visuals: Buy and sell signals are clearly indicated with up and down triangles, while divergences are highlighted with distinct labels.
How to Use:
Buy Signals: Look for green up triangles or bullish divergence labels.
Sell Signals: Look for red down triangles or bearish divergence labels.
Oscillator and Thresholds: Use the plotted oscillator and thresholds to confirm signal strength.
Parameters:
Momentum Period: Adjusts the length of the momentum calculation.
Volume Average Period: Adjusts the length of the volume average calculation.
Volatility Period: Adjusts the length of the ATR calculation.
Volatility Multiplier: Adjusts the sensitivity of the volatility-adjusted signals.
Disclaimer:
This indicator is for informational purposes only and should not be considered financial advice. Always conduct 1 thorough research and use appropriate risk management techniques when trading.
TMO (True Momentum Oscillator)TMO ((T)rue (M)omentum (O)scilator)
Created by Mobius V01.05.2018 TOS Convert to TV using Claude 3.7 and ChatGPT 03 Mini :
TMO calculates momentum using the delta of price. Giving a much better picture of trend, tend reversals and divergence than momentum oscillators using price.
True Momentum Oscillator (TMO)
The True Momentum Oscillator (TMO) is a momentum-based technical indicator designed to identify trend direction, trend strength, and potential reversal points in the market. It's particularly useful for spotting overbought and oversold conditions, aiding traders in timing their entries and exits.
How it Works:
The TMO calculates market momentum by analyzing recent price action:
Momentum Calculation:
For a user-defined length (e.g., 14 bars), TMO compares the current closing price to past open prices. It assigns:
+1 if the current close is greater than the open price of the past bar (indicating bullish momentum).
-1 if it's less (indicating bearish momentum).
0 if there's no change.
The sum of these scores gives a raw momentum measure.
EMA Smoothing:
To reduce noise and false signals, this raw momentum is smoothed using Exponential Moving Averages (EMAs):
First, the raw data is smoothed by an EMA over a short calculation period (default: 5).
Then, it undergoes additional smoothing through another EMA (default: 3 bars), creating the primary "Main" line of the indicator.
Lastly, a "Signal" line is derived by applying another EMA (also default: 3 bars) to the main line, adding further refinement.
Trend Identification:
The indicator plots two lines:
Main Line: Indicates current momentum strength and direction.
Signal Line: Acts as a reference line, similar to a moving average crossover system.
When the Main line crosses above the Signal line, it suggests strengthening bullish momentum. Conversely, when the Main line crosses below the Signal line, it indicates increasing bearish momentum.
Overbought/Oversold Levels:
The indicator identifies key levels based on the chosen length parameter:
Overbought zone (positive threshold): Suggests the market might be overheated, and a potential bearish reversal or pullback could occur.
Oversold zone (negative threshold): Suggests the market might be excessively bearish, signaling a potential bullish reversal.
Clouds visually mark these overbought/oversold areas, making it easy to see potential reversal zones.
Trading Applications:
Trend-following: Traders can enter positions based on crossovers of the Main and Signal lines.
Reversals: The overbought and oversold areas highlight high-probability reversal points.
Momentum confirmation: Use TMO to confirm price action or other technical signals, improving trade accuracy and timing.
The True Momentum Oscillator provides clarity in identifying momentum shifts, making it a valuable addition to various trading strategies.
Bollinger Momentum Deviation | QuantEdgeBIntroducing Bollinger Momentum Deviation (BMD) by QuantEdgeB
🛠️ Overview
Bollinger Momentum Deviation (BMD) is a trend-following momentum indicator designed to identify strong price movements while also detecting overbought and oversold conditions in ranging markets.
By normalizing a simple moving average (SMA) with standard deviation, BMD captures momentum shifts, helping traders make data-driven entries and exits. In trending conditions, it acts as a momentum confirmation tool, while in ranging markets, it highlights mean-reversion opportunities for profit-taking or re-accumulation.
BMD combines the best of both worlds—a robust trend-following framework with an integrated volatility-based overbought/oversold detection system.
____
✨ Key Features
🔹 Momentum & Trend-Following Core
Built upon a normalized SMA with standard deviation filtering, BMD efficiently tracks price movements while reducing lag.
🔹 Overbought/Oversold Market Detection
By dynamically adjusting its thresholds based on standard deviation, it identifies high-probability reversion zones in sideways markets.
🔹 Adaptive Normalization Mechanism
Ensures consistent signal reliability across different assets and timeframes by standardizing momentum fluctuations.
🔹 Customizable Visual & Signal Settings
Includes multiple color modes, extra plots, and trend labels, making it easy to align with different trading styles.
____
📊 How It Works
1️⃣ Normalized Momentum Calculation
BMD computes a normalized momentum score using a simple moving average (SMA) combined with a standard deviation (SD) filter to create dynamic upper and lower bands. The final momentum score is derived by normalizing the price within this volatility-adjusted range. This normalization makes momentum readings comparable across different price levels and timeframes.
2️⃣ Standard Deviation Filtering
Unlike traditional approaches where standard deviation is derived from price as is the first SD, BMDs second SD is driven from the normalized momentum oscillator itself. This allows for a volatility-adjusted smoothing mechanism that adapts to momentum shifts rather than raw price fluctuations. This ensures that the trend signals remain dynamic and responsive, filtering out short-term noise while keeping the core momentum structure intact. By applying standard deviation directly to the oscillator, BMD achieves a self-regulating feedback loop, improving accuracy in both trending and range-bound conditions.
3️⃣ Signal Generation
✅ Long Signal → Upper BMD SD > Long Threshold (83)
❌ Short Signal → Lower BMD SD < Short Threshold (60)
📌 Additional Features:
- Overbought Zone → Values above 130 indicate price extension.
- Oversold Zone → Values below -10 suggest potential accumulation.
- Momentum Labels → Optional "Long" and "Short" markers for clear trade identification.
____
👥 Who Should Use It?
✅ Trend Traders & Momentum Followers → Use BMD as a confirmation tool for strong directional trends.
✅ Range & Mean Reversion Traders → Identify reversal opportunities at extreme BMD levels.
✅ Swing & Position Traders → Utilize normalized momentum shifts for data-driven entries & exits.
✅ Systematic & Quant Traders → Implement BMD within algorithmic frameworks for adaptive market detection.
____
⚙️ Customization & Default Settings
🔧 Key Custom Inputs:
- Base Length (Default: 40) → Defines the SMA calculation period.
- Standard Deviation Length (Default: 50) → Controls the volatility filter strength.
- SD Multiplier (Default: 0-7) → Adjusts the sensitivity of the momentum filter.
- Long Threshold (Default: 83) → Above this level, momentum is bullish.
- Short Threshold (Default: 60) → Below this level, momentum weakens.
- Visual Customizations → Multiple color themes, extra plots, and trend labels available.
🚀 By default, BMD is optimized for trend-following and momentum filtering while remaining adaptable to various trading strategies.
____
📌 How to Use Bollinger Momentum Deviation (BMD) in Trading
1️⃣ Trend-Following Strategy (Momentum Confirmation)
✔ Enter long positions when BMD crosses above the long threshold (83), confirming upward momentum.
✔ Enter short positions when BMD crosses below the short threshold (60), confirming downward momentum.
✔ Stay in trades as long as BMD remains in trend direction, filtering out noise.
2️⃣ Mean Reversion Strategy (Overbought/Oversold Conditions)
✔ Take profits or hedge when BMD crosses above 130 (overbought).
✔ Re-accumulate positions when BMD drops below -10 (oversold).
📌 Why?
- In trending markets, follow BMD’s momentum confirmation.
- In ranging markets, use BMD’s normalized bands to buy at deep discounts and sell into strength.
_____
📌 Conclusion
Bollinger Momentum Deviation (BMD) is a versatile momentum indicator that combines trend-following mechanics with volatility-adjusted mean reversion zones. By normalizing SMA-based momentum shifts, BMD ensures robust signal reliability across different assets and timeframes.
🔹 Key Takeaways:
1️⃣ Momentum Confirmation & Trend Detection – Captures directional strength with dynamic filtering.
2️⃣ Overbought/Oversold Conditions – Identifies reversal opportunities in sideways markets.
3️⃣ Adaptive & Customizable – Works across different timeframes and trading styles.
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Balance Price Range (BPR) IndicatorOverview
The BPR with Directional Momentum-Filtered Breakouts indicator is designed to identify Balanced Price Ranges (BPR) and d etect high-probability breakouts and breakdowns with directional momentum confirmation . By leveraging historical BPR structures, EMA-based momentum filtering , and a trade cooldown mechanism , this script provides a structured approach to identifying potential trading opportunities while reducing false signals.
This invite-only indicator is ideal for traders who seek precise breakout confirmation, reduced noise, and trend-following logic while maintaining flexibility through adjustable parameters.
How It Works
The script follows a multi-step breakout detection process by integrating multiple key technical components:
1. Balanced Price Range (BPR) Detection:
• A Balanced Candle is identified when the price remains within a specific percentage of its range midpoint.
• These BPR zones represent areas of equilibrium , where a breakout or breakdown is likely to occur.
• The script historically tracks BPR levels across the entire chart to monitor price action around key areas.
2. Momentum-Filtered Breakout & Breakdown Logic:
• Bullish Breakout: Occurs when the price breaks above the historical BPR high with bullish momentum.
• Bearish Breakdown: Occurs when the price breaks below the historical BPR low with bearish momentum.
• Momentum Confirmation: Each breakout requires a strong directional move, measured against the Exponential Moving Average (EMA) .
• Only confirmed breakouts are marked, reducing the likelihood of false signals in choppy markets.
3. Candle-Based Background Visualization:
• Grey Background: Represents a Balanced Price Range (BPR), indicating potential breakout zones.
• Green Background: Indicates a Bullish Breakout when the price successfully breaks and holds above the BPR high.
• Red Background: Indicates a Bearish Breakdown when the price drops below the BPR low.
4. Trade Cooldown Mechanism:
• Prevents consecutive signals from triggering too frequently.
• Default cooldown period: 5 bars (adjustable).
• Ensures that trades are not clustered, improving signal quality.
5. EMA for Trend Direction & Confirmation:
• A 20-period EMA (default, adjustable) is used to confirm trade direction.
• Breakouts above the EMA align with uptrend continuation.
• Breakdowns below the EMA align with downtrend momentum.
Key Features
✔️ Historical BPR Detection – Tracks past BPR levels across the entire chart for structured breakout zones.
✔️ Momentum-Based Breakouts – Ensures breakouts are confirmed by directional price movement before generating signals.
✔️ Candle-Based Background Logic – Subtle candle highlights rather than full background fills, for better chart clarity.
✔️ Trade Cooldown Period – Prevents consecutive buy/sell signals within a defined period, improving signal efficiency.
✔️ Dynamic EMA Confirmation – Ensures trades align with the overall trend, reducing counter-trend trades.
✔️ Customizable Inputs – Adjust breakout thresholds, EMA length, and cooldown periods as per trading style.
✔️ Works Across Multiple Timeframes – Can be applied to intraday, swing, and positional trading strategies.
How to Use
1. Look for Balanced Price Ranges ( BPR )
• These zones highlight equilibrium areas where price is likely to break out.
• Grey-shaded candles indicate potential breakout zones.
2. Monitor for Bullish or Bearish Breakouts
• A green candle background signals a bullish breakout above BPR.
• A red candle background signals a bearish breakdown below BPR.
• The EMA filter helps confirm whether the breakout aligns with the prevailing trend.
3. Follow the Cooldown Logic
• After a breakout signal, wait for the cooldown period before another trade is allowed.
• This helps filter out noisy price action and prevents excessive trading.
4. Use Alongside Other Indicators
• Works well with volume analysis, support/resistance levels, and price action strategies.
• Can be combined with other momentum indicators for further trade confirmation.
Why This Combination?
Unlike generic breakout indicators, this script uniquely combines:
• BPR historical structures for defining potential breakout zones.
• Momentum-based breakout filtering using EMA confirmation.
• Trade cooldown logic to avoid excessive trading signals.
• Subtle candle-based highlights instead of cluttered full-background fills.
This structured approach makes the indicator more robust, adaptive, and reliable in different market conditions.
Why It’s Worth Using?
🔹 Avoid False Breakouts: Built-in momentum confirmation prevents weak or fake breakouts.
🔹 Clean Visualization: No excessive overlays—just precise, meaningful background coloring for breakouts.
🔹 Works in Any Market: Use on stocks, crypto, forex, indices, and commodities across different timeframes.
🔹 User-Friendly & Customizable: Fine-tune parameters to match individual trading styles.
⚠️ Note: This is an Invite-Only script. Access is granted to selected users.
✅ If you find it useful, consider incorporating it into your trend-following & breakout trading strategies.
🚀 Optimize your trading with structured breakout detection! 🚀
Blockchain Fundamentals: Liquidity Cycle MomentumLiquidity Cycle Momentum Indicator
Overview:
This indicator analyzes global liquidity trends by calculating a unique Liquidity Index and measuring its year-over-year (YoY) percentage change. It then applies a momentum oscillator to the YoY change, providing insights into the cyclical momentum of liquidity. The indicator incorporates a limited historical data workaround to ensure accurate calculations even when the chart’s history is short.
Features Breakdown:
1. Limited Historical Data Workaround
Function: The limit(length) function adjusts the lookback period when there isn’t enough historical data (i.e., near the beginning of the chart), ensuring that calculations do not break due to insufficient data.
2. Global Liquidity Calculation
Data Sources:
TVC:CN10Y (10-year yield from China)
TVC:DXY (US Dollar Index)
ECONOMICS:USCBBS (US Central Bank Balance Sheet)
FRED:JPNASSETS (Japanese assets)
ECONOMICS:CNCBBS (Chinese Central Bank Balance Sheet)
FRED:ECBASSETSW (ECB assets)
Calculation Methodology:
A ratio is computed (cn10y / dxy) to adjust for currency influences.
The Liquidity Index is then derived by multiplying this ratio with the sum of the other liquidity components.
3. Year-over-Year (YoY) Percent Change
Computation:
The indicator determines the number of bars that approximately represent one year.
It then compares the current Liquidity Index to its value one year ago, calculating the YoY percentage change.
4. Momentum Oscillator on YoY Change
Oscillator Components:
1. Calculated using the Chande Momentum Oscillator (CMO) applied to the YoY percent change with a user-defined momentum length.
2. A weighted moving average (WMA) that smooths the momentum signal.
3. Overbought and Oversold zones
Signal Generation:
Buy Signal: Triggered when the momentum crosses upward from an oversold condition, suggesting a potential upward shift in liquidity momentum.
Sell Signal: Triggered when crosses below an overbought condition, indicating potential downward momentum.
State Management:
The indicator maintains a state variable to avoid repeated signals, ensuring that a new buy or sell signal is only generated when there’s a clear change in momentum.
5. Visual Presentation and Alerts
Plots:
The oscillator value and signalline are plotted for visual analysis.
Overbought and oversold levels are marked with dashed horizontal lines.
Signal Markers:
Buy and sell signals are marked with green and maroon circles, respectively.
Background Coloration:
Optionally, the chart’s background bars are colored (yellow for buy signals and fuchsia for sell signals) to enhance visual cues when signals are triggered.
Conclusion
In summary, the Liquidity Cycle Momentum Indicator provides a robust framework to analyze liquidity trends by combining global liquidity data, YoY changes, and momentum oscillation. This makes it an effective tool for traders and analysts looking to identify cyclical shifts in liquidity conditions and potential turning points in the market.
Cluster Reversal Zones📌 Cluster Reversal Zones – Smart Market Turning Point Detector
📌 Category : Public (Restricted/Closed-Source) Indicator
📌 Designed for : Traders looking for high-accuracy reversal zones based on price clustering & liquidity shifts.
🔍 Overview
The Cluster Reversal Zones Indicator is an advanced market reversal detection tool that helps traders identify key turning points using a combination of price clustering, order flow analysis, and liquidity tracking. Instead of relying on static support and resistance levels, this tool dynamically adjusts to live market conditions, ensuring traders get the most accurate reversal signals possible.
📊 Core Features:
✅ Real-Time Reversal Zone Mapping – Detects high-probability market turning points using price clustering & order flow imbalance.
✅ Liquidity-Based Support/Resistance Detection – Identifies strong rejection zones based on real-time liquidity shifts.
✅ Order Flow Sensitivity for Smart Filtering – Filters out weak reversals by detecting real market participation behind price movements.
✅ Momentum Divergence for Confirmation – Aligns reversal zones with momentum divergences to increase accuracy.
✅ Adaptive Risk Management System – Adjusts risk parameters dynamically based on volatility and trend state.
🔒 Justification for Mashup
The Cluster Reversal Zones Indicator contains custom-built methodologies that extend beyond traditional support/resistance indicators:
✔ Smart Price Clustering Algorithm: Instead of plotting fixed support/resistance lines, this system analyzes historical price clustering to detect active reversal areas.
✔ Order Flow Delta & Liquidity Shift Sensitivity: The tool tracks real-time order flow data, identifying price zones with the highest accumulation or distribution levels.
✔ Momentum-Based Reversal Validation: Unlike traditional indicators, this tool requires a momentum shift confirmation before validating a potential reversal.
✔ Adaptive Reversal Filtering Mechanism: Uses a combination of historical confluence detection + live market validation to improve accuracy.
🛠️ How to Use:
• Works well for reversal traders, scalpers, and swing traders seeking precise turning points.
• Best combined with VWAP, Market Profile, and Delta Volume indicators for confirmation.
• Suitable for Forex, Indices, Commodities, Crypto, and Stock markets.
🚨 Important Note:
For educational & analytical purposes only.
[COG] Adaptive Squeeze Intensity 📊 Adaptive Squeeze Intensity (ASI) Indicator
🎯 Overview
The Adaptive Squeeze Intensity (ASI) indicator is an advanced technical analysis tool that combines the power of volatility compression analysis with momentum, volume, and trend confirmation to identify high-probability trading opportunities. It quantifies the degree of price compression using a sophisticated scoring system and provides clear entry signals for both long and short positions.
⭐ Key Features
- 📈 Comprehensive squeeze intensity scoring system (0-100)
- 📏 Multiple Keltner Channel compression zones
- 📊 Volume analysis integration
- 🎯 EMA-based trend confirmation
- 🎨 Proximity-based entry validation
- 📱 Visual status monitoring
- 🎨 Customizable color schemes
- ⚡ Clear entry signals with directional indicators
🔧 Components
1. 📐 Squeeze Intensity Score (0-100)
The indicator calculates a total squeeze intensity score based on four components:
- 📊 Band Convergence (0-40 points): Measures the relationship between Bollinger Bands and Keltner Channels
- 📍 Price Position (0-20 points): Evaluates price location relative to the base channels
- 📈 Volume Intensity (0-20 points): Analyzes volume patterns and thresholds
- ⚡ Momentum (0-20 points): Assesses price momentum and direction
2. 🎨 Compression Zones
Visual representation of squeeze intensity levels:
- 🔴 Extreme Squeeze (80-100): Red zone
- 🟠 Strong Squeeze (60-80): Orange zone
- 🟡 Moderate Squeeze (40-60): Yellow zone
- 🟢 Light Squeeze (20-40): Green zone
- ⚪ No Squeeze (0-20): Base zone
3. 🎯 Entry Signals
The indicator generates entry signals based on:
- ✨ Squeeze release confirmation
- ➡️ Momentum direction
- 📊 Candlestick pattern confirmation
- 📈 Optional EMA trend alignment
- 🎯 Customizable EMA proximity validation
⚙️ Settings
🔧 Main Settings
- Base Length: Determines the calculation period for main indicators
- BB Multiplier: Sets the Bollinger Bands deviation multiplier
- Keltner Channel Multipliers: Three separate multipliers for different compression zones
📈 Trend Confirmation
- Four customizable EMA periods (default: 21, 34, 55, 89)
- Optional trend requirement for entry signals
- Adjustable EMA proximity threshold
📊 Volume Analysis
- Customizable volume MA length
- Adjustable volume threshold for signal confirmation
- Option to enable/disable volume analysis
🎨 Visualization
- Customizable bullish/bearish colors
- Optional intensity zones display
- Status monitor with real-time score and state information
- Clear entry arrows and background highlights
💻 Technical Code Breakdown
1. Core Calculations
// Base calculations for EMAs
ema_1 = ta.ema(close, ema_length_1)
ema_2 = ta.ema(close, ema_length_2)
ema_3 = ta.ema(close, ema_length_3)
ema_4 = ta.ema(close, ema_length_4)
// Proximity calculation for entry validation
ema_prox_raw = math.abs(close - ema_1) / ema_1 * 100
is_close_to_ema_long = close > ema_1 and ema_prox_raw <= prox_percent
```
### 2. Squeeze Detection System
```pine
// Bollinger Bands setup
BB_basis = ta.sma(close, length)
BB_dev = ta.stdev(close, length)
BB_upper = BB_basis + BB_mult * BB_dev
BB_lower = BB_basis - BB_mult * BB_dev
// Keltner Channels setup
KC_basis = ta.sma(close, length)
KC_range = ta.sma(ta.tr, length)
KC_upper_high = KC_basis + KC_range * KC_mult_high
KC_lower_high = KC_basis - KC_range * KC_mult_high
```
### 3. Scoring System Implementation
```pine
// Band Convergence Score
band_ratio = BB_width / KC_width
convergence_score = math.max(0, 40 * (1 - band_ratio))
// Price Position Score
price_range = math.abs(close - KC_basis) / (KC_upper_low - KC_lower_low)
position_score = 20 * (1 - price_range)
// Final Score Calculation
squeeze_score = convergence_score + position_score + vol_score + mom_score
```
### 4. Signal Generation
```pine
// Entry Signal Logic
long_signal = squeeze_release and
is_momentum_positive and
(not use_ema_trend or (bullish_trend and is_close_to_ema_long)) and
is_bullish_candle
short_signal = squeeze_release and
is_momentum_negative and
(not use_ema_trend or (bearish_trend and is_close_to_ema_short)) and
is_bearish_candle
```
📈 Trading Signals
🚀 Long Entry Conditions
- Squeeze release detected
- Positive momentum
- Bullish candlestick
- Price above relevant EMAs (if enabled)
- Within EMA proximity threshold (if enabled)
- Sufficient volume confirmation (if enabled)
🔻 Short Entry Conditions
- Squeeze release detected
- Negative momentum
- Bearish candlestick
- Price below relevant EMAs (if enabled)
- Within EMA proximity threshold (if enabled)
- Sufficient volume confirmation (if enabled)
⚠️ Alert Conditions
- 🔔 Extreme squeeze level reached (score crosses above 80)
- 🚀 Long squeeze release signal
- 🔻 Short squeeze release signal
💡 Tips for Usage
1. 📱 Use the status monitor to track real-time squeeze intensity and state
2. 🎨 Pay attention to the color gradient for trend direction and strength
3. ⏰ Consider using multiple timeframes for confirmation
4. ⚙️ Adjust EMA and proximity settings based on your trading style
5. 📊 Use volume analysis for additional confirmation in liquid markets
📝 Notes
- 🔧 The indicator combines multiple technical analysis concepts for robust signal generation
- 📈 Suitable for all tradable markets and timeframes
- ⭐ Best results typically achieved in trending markets with clear volatility cycles
- 🎯 Consider using in conjunction with other technical analysis tools for confirmation
⚠️ Disclaimer
This technical indicator is designed to assist in analysis but should not be considered as financial advice. Always perform your own analysis and risk management when trading.
Multi-Timeframe Technical IndicatorThis Multi-Timeframe Technical Indicator is designed for use in financial markets to assist traders in evaluating various key technical indicators across multiple timeframes. The indicator displays a table that includes the values of Moving Averages (MA), Relative Strength Index (RSI), Momentum, and VWAP for a range of timeframes, allowing for the evaluation of trends in real-time.
Key Features:
Multiple Timeframes: The indicator supports timeframes ranging from as low as 1 minute up to 1 month. By tracking indicators on multiple timeframes, traders can make better-informed decisions based on trends across different periods (e.g., short-term vs. long-term trends).
Technical Indicators:
Moving Average (MA): The MA provides insight into the trend direction of the asset's price. It can be configured as Simple Moving Average (SMA), Exponential Moving Average (EMA), or Weighted Moving Average (WMA).
Relative Strength Index (RSI): A momentum oscillator that measures the speed and change of price movements. RSI values below 50 suggest an upward trend, while values above 50 indicate a downward trend.
Momentum: Measures the rate of change of an asset's price, highlighting whether the price is increasing or decreasing.
VWAP (Volume Weighted Average Price): Reflects the average price of the asset weighted by its trading volume. Traders use this value to gauge the fair value of an asset.
Trend Indicators: The table dynamically displays trend arrows (↑ or ↓) based on the comparison of each indicator's value to the previous timeframe’s value. This allows users to identify the prevailing market sentiment or trend at a glance.
Visualization: The data is presented in an easy-to-read table format, where each value is accompanied by color-coded indicators (e.g., green for bullish trends, red for bearish trends). This provides a clear and visually accessible way to interpret complex market conditions.
Use Cases:
Day Trading: Helps day traders assess the momentum and strength of a price move on short-term timeframes like 1-minute, 5-minute, and 15-minute intervals.
Swing Trading: Provides insights into medium-term trends using 1-hour, 4-hour, and daily data points.
Long-Term Analysis: Useful for traders and investors looking to gauge the overall health of an asset over weeks or months, analyzing the 1-week and 1-month indicators.
Limitations and Risks:
As with all technical indicators, it is important to remember that the Multi-Timeframe Technical Indicator is not foolproof. While technical analysis offers valuable insights, it does not guarantee success and can lead to losses. Traders should always use a combination of different methods (technical and fundamental) and consult with financial advisors before making trading decisions.
The indicator operates as a tool for analysis but should not be the sole basis for trading decisions. According to Elder (1993), no indicator is perfect, and it is crucial to combine multiple factors when assessing market conditions. Additionally, Murphy (1999) emphasized the importance of understanding the limitations of indicators, as they are based on historical price movements and may not always predict future trends accurately.
References:
Elder, A. (1993). Trading for a Living. Wiley.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance.
This Multi-Timeframe Technical Indicator is built to provide real-time, comprehensive data for informed decision-making, and is best used in conjunction with other analysis methods to manage risk effectively.
