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!
Komut dosyalarını "momentum" için ara
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.
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
Volume Based Buy and Sell Momentum by 2tmThis is Volume based Buy and Sell Momentum script.
Basically I'd just adjusted PVI and NVI
But It's easy to understand current Volume trends and Momentums
Thank you and Wish your successful investment.
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
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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.
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.
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.
Uptrick: Universal Market ValuationIntroduction
Uptrick: Universal Market Valuation is created for traders who seek an analytical tool that brings together multiple signals in one place. Whether you focus on intraday scalping or long-term portfolio management, the indicator merges various well-known technical indicators to help gauge potential overvaluation, undervaluation, and trend direction. It is engineered to highlight different market dimensions, from immediate price momentum to extended cyclical trends.
Overview
The indicator categorizes market conditions into short-term, long-term, or a classic Z-Score style reading. Additionally, it draws on a unified trend line for directional bias. By fusing elements from traditionally separate indicators, the indicator aims to reduce “false positives” while giving a multidimensional view of price behavior. The indicator works best on cryptocurrency markets while remaining a universal valuation indicator that performs well across all timeframes. However, on lower timeframes, the Long-Term Combo input may be too long-term, so it's recommended to select the Short-Term Combo in the inputs for better adaptability.
Originality and Value
The Uptrick: Universal Market Valuation indicator is not just a simple combination of existing technical indicators—it introduces a multi-layered, adaptive valuation model that enhances signal clarity, reduces false positives, and provides traders with a more refined assessment of market conditions.
Rather than treating each included indicator as an independent signal, this script normalizes and synthesizes multiple indicators into a unified composite score, ensuring that short-term and long-term momentum, mean reversion, and trend strength are all dynamically weighted based on market behavior. It employs a proprietary weighting system that adjusts how each component contributes to the final valuation output. Instead of static threshold-based signals, the indicator integrates adaptive filtering mechanisms that account for volatility fluctuations, drawdowns, and momentum shifts, ensuring more reliable overbought/oversold readings.
Additionally, the script applies Z-Score-based deviation modeling, which refines price valuation by filtering out extreme readings that are statistically insignificant. This enhances the detection of true overvaluation and undervaluation points by comparing price behavior against a dynamically calculated standard deviation threshold rather than relying solely on traditional fixed oscillator bands. The MVRV-inspired ratio provides a unique valuation layer by incorporating historical fair-value estimations, offering deeper insight into market overextension.
The Universal Trend Line within the indicator is designed to smooth trend direction while maintaining responsiveness to market shifts. Unlike conventional trend indicators that may lag significantly or produce excessive false signals, this trend-following mechanism dynamically adjusts to changing price structures, helping traders confirm directional bias with reduced noise. This approach enables clearer trend recognition and assists in distinguishing between short-lived pullbacks and sustained market movements.
By merging momentum oscillators, trend strength indicators, volume-driven metrics, statistical deviation models, and long-term valuation principles into a single framework, this indicator eliminates the need for juggling multiple individual indicators, helping traders achieve a holistic market perspective while maintaining customization flexibility. The combination of real-time alerts, dynamic color-based valuation visualization, and customizable trend-following modes further enhances usability, making it a comprehensive tool for traders across different timeframes and asset classes.
Inputs and Features
• Calculation Window (Short-Term and Long-Term)
Defines how much historical data the indicator uses to evaluate the market. A smaller window makes the indicator more reactive, benefiting high-frequency traders. A larger window provides a steadier perspective for longer-term holders.
• Smoothing Period (Short-Term and Long-Term)
Controls how much the raw indicator outputs are “smoothed out.” Lower values reveal subtle intraday fluctuations, while higher values aim to present more robust, stable signals.
• Valuation Mechanism (Short Term Combo, Long Term Combo, Classic Z-Score)
Allows you to pick how the indicator evaluates overvaluation or undervaluation. Short Term Combo focuses on rapid oscillations, Long Term Combo assesses market health over more extended periods, and the Classic Z-Score approach highlights statistically unusual price levels.
Short-Term
• Determination Mechanism (Strict or Loose)
Governs the tolerance for labeling a market as overvalued or undervalued. Strict requires stronger confirmation; Loose begins labeling sooner, potentially catching moves earlier but risking more false signals.
Strict
Loose
• Select Color Scheme
Lets you choose the aesthetic style for your charts. Visual clarity can significantly improve reaction time, especially when multiple indicators are combined.
• Z-Score Coloring Mode (Heat or Slope)
Determines how the Classic Z-Score line and bars are colored. In Heat mode, the indicator intensifies color as readings move further from a baseline average. Slope mode changes color based on the direction of movement, making turning points more evident.
Classic Z-Score - Heat
Classic Z-Score - Slope
• Trend Following Mode (Short, Long, Extra Long, Filtered Long)
Offers various ways to compute and smooth the universal trend line. Short is more sensitive, Long and Extra Long are meant for extended time horizons, and Filtered Long applies an extra smoothing layer to help you see overarching trends rather than smaller fluctuations.
Short Term
Long Term
Extra Long Term
Filtered Long Term
• Table Display
An optional feature that places a concise summary table on the chart. It shows valuation states, trend direction, volatility condition, and other metrics, letting you observe multi-angle readings at a glance.
• Alerts
Multiple alert triggers can be set up—for crossing into overvaluation zones, for abrupt changes in trend, or for high volatility detection. Traders can stay informed without needing to watch charts continuously.
Why These Indicators Were Merged
• RSI (Relative Strength Index)
RSI is a cornerstone momentum oscillator that interprets speed and change of price movements. It has widespread recognition among traders for detecting potential overbought or oversold conditions. Including RSI provides a tried-and-tested layer of momentum insight.
• Stochastic Oscillator
This oscillator evaluates the closing price relative to its recent price range. Its responsiveness makes it valuable for pinpointing near-term price fluctuations. Where RSI offers a broader momentum picture, Stochastic adds fine-tuned detection of short-lived rallies or pullbacks.
• MFI (Money Flow Index)
MFI assesses buying and selling pressure by incorporating volume data. Many technical tools are purely price-based, but MFI’s volume component helps address questions of liquidity and actual money flow, offering a glimpse of how robust or weak a current move might be.
• CCI (Commodity Channel Index)
CCI shows how far price lies from its statistically “typical” trend. It can spot emerging trends or warn of overextension. Using CCI alongside RSI and Stochastic further refines the valuation layer by capturing price deviation from its underlying trajectory.
• ADX (Average Directional Index)
ADX reveals the strength of a trend but does not specify its direction. This is especially useful in combination with other oscillators that focus on bullish or bearish momentum. ADX can clarify whether a market is truly trending or just moving sideways, lending deeper context to the indicator's broader signals.
• MACD (Moving Average Convergence Divergence)
MACD is known for detecting momentum shifts via the interaction of two moving averages. Its inclusion ensures the indicator can capture transitional phases in market momentum. Where RSI and Stochastic concentrate on shorter-term changes, MACD has a slightly longer horizon for identifying robust directional changes.
• Momentum and ROC (Rate of Change)
Momentum and ROC specifically measure the velocity of price moves. By indicating how quickly (or slowly) price is changing compared to previous bars, they help confirm whether a trend is gathering steam, losing it, or is in a transitional stage.
• MVRV-Inspired Ratio
Drawn loosely from the concept of comparing market value to some underlying historical or fair-value metric, an MVRV-style ratio can help identify if an asset is trading above or below a considered norm. This additional viewpoint on valuation goes beyond simple price-based oscillations.
• Z-Score
Z-Score interprets how many standard deviations current prices deviate from a central mean. This statistical measure is often used to identify extreme conditions—either overly high or abnormally low. Z-Score helps highlight potential mean reversion setups by showing when price strays far from typical levels.
By merging these distinct viewpoints—momentum oscillators, trend strength gauges, volume flow, standard deviation extremes, and fundamental-style valuation measures—the indicator aims to create a well-rounded, carefully balanced final readout. Each component serves a specialized function, and together they can mitigate the weaknesses of a single metric acting alone.
Summary
This indicator simplifies multi-indicator analysis by fusing numerous popular technical signals into one tool. You can switch between short-term and long-term valuation perspectives or adopt a classic Z-Score approach for spotting price extremes. The universal trend line clarifies direction, while user-friendly color schemes, optional tabular summaries, and customizable alerts empower traders to maintain awareness without constantly monitoring every market tick.
Disclaimer
The indicator is made for educational and informational use only, with no claims of guaranteed profitability. Past data patterns, regardless of the indicators used, never ensure future results. Always maintain diligent risk management and consider the broader market context when making trading decisions. This indicator is not personal financial advice, and Uptrick disclaims responsibility for any trading outcomes arising from its use.
BBVOL SwiftEdgeBBVOL SwiftEdge – Precision Scalping with Volume and Trend Filtering
Optimized for scalping and short-term trading on fast-moving markets (e.g., 1-minute charts), BBVOL SwiftEdge combines Bollinger Bands, Heikin Ashi smoothing, volume momentum, and EMA trend alignment to deliver actionable buy/sell signals with visual trend cues. Ideal for forex, crypto, and stocks.
What Makes BBVOL SwiftEdge Unique?
Unlike traditional Bollinger Bands scripts that focus solely on price volatility, BBVOL SwiftEdge enhances signal precision by:
Using Heikin Ashi to filter out noise and confirm trend direction, reducing false signals in choppy markets.
Incorporating volume analysis to ensure signals align with significant buying or selling pressure (customizable thresholds).
Adding an EMA overlay to keep trades in sync with the short-term trend.
Coloring candlesticks (green for bullish, red for bearish, purple for consolidation) to visually highlight market conditions at a glance.
How Does It Work?
Buy Signal: Triggers when price crosses above the lower Bollinger Band, Heikin Ashi shows bullish momentum (close > open), buy volume exceeds your set threshold (default 30%), and price is above the EMA. A green triangle appears below the candle.
Sell Signal: Triggers when price crosses below the upper Bollinger Band, Heikin Ashi turns bearish (close < open), sell volume exceeds the threshold (default 30%), and price is below the EMA. A red triangle appears above the candle.
Trend Visualization: Candles turn green when price is significantly above the Bollinger Bands’ basis (indicating a bullish trend), red when below (bearish trend), or purple when near the basis (consolidation), based on a customizable threshold (default 10% of BB width).
Risk Management: Each signal calculates a stop-loss (10% beyond the opposite band) and take-profit (opposite band), plotted for reference.
How to Use It
Timeframe: Best on 1-minute to 5-minute charts for scalping; test higher timeframes for swing trading.
Markets: Works well in volatile markets like forex pairs (e.g., EUR/USD), crypto (e.g., BTC/USD), or liquid stocks.
Customization: Adjust Bollinger Bands length (default 10), multiplier (default 1.2), volume thresholds (default 30%), EMA length (default 3), and consolidation threshold (default 0.1%) to match your strategy.
Interpretation: Look for green/red triangles as entry signals, confirmed by candle colors. Purple candles suggest caution—wait for a breakout. Use stop-loss/take-profit levels for trade management.
Underlying Concepts
Bollinger Bands: Measures volatility and identifies overbought/oversold zones.
Heikin Ashi: Smooths price action to emphasize trend direction.
Volume Momentum: Calculates cumulative buy/sell volume percentages to confirm market strength (e.g., buyVolPercent = buyVolume / totalVolume * 100).
EMA: A fast-moving average (default length 3) ensures signals align with the immediate trend.
Chart Setup
The chart displays Bollinger Bands (orange), Heikin Ashi close (green circles), EMA (purple), and volume-scaled lines (lime/red). Signals are marked with triangles, and candle colors reflect trend state. Keep the chart clean by focusing on these outputs for clarity.
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.
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✨ 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.
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📊 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.
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👥 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.
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⚙️ 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.
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📌 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.
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📌 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.
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.
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.
Simple Trend Strength & MomentumThis indicator will show a combination of Trend Strength, Volatility using an Adaptive Moving Average (AMA), and Market Momentum.
You can use this indicator to identify trends, volatility, and momentum shifts in real-time, making it an excellent tool for both trend-following and breakout strategies.
The three main features of this indicator are:
Adaptive Moving Average (AMA): Tracks the trend direction with a dynamic smoothing factor that adjusts based on market volatility. The AMA line changes color based on trend strength (green for bullish, red for bearish). I manually compute the Adaptive Moving Average (AMA) using a smoothing factor derived from the market's efficiency ratio. I have used fastLength and slowLength to control the responsiveness of the AMA.
Volatility Bands: Plots upper and lower bands around the AMA line, indicating price volatility. These bands dynamically adjust based on ATR, with a color gradient that changes intensity based on market volatility.
Momentum Circles: Positive momentum (ROC above the threshold) is shown as a green circle below the bar, while negative momentum is marked by a red circle above the bar. This makes it easy to spot momentum shifts.
The green dots in the indicator represent positive momentum. Specifically, they are displayed when the Rate of Change (ROC) of the price exceeds a predefined threshold (set as threshold in the input). This indicates that the market is experiencing upward price movement at a rate faster than the defined threshold.
How it works:
Rate of Change (ROC) measures the percentage change in price over a specified period (in this case, 14 periods).
When the ROC is greater than the set threshold (1.5 by default), a green circle (dot) is plotted below the price bar to signal that there is significant positive momentum.
This can be seen as an indicator of bullish momentum, where price is increasing at a relatively fast pace compared to previous periods.
The green dots help you spot when the price is moving upward rapidly, potentially signaling a good time to enter a long position or watch for further price action.
NOTE: It is vice versa for red dots.
MAG 7 - Weighted Multi-Symbol Momentum + ExtrasOverview
This indicator aggregates the percentage change of multiple symbols into a single “weighted momentum” value. You can set individual weights to emphasize or de-emphasize particular stocks. The script plots two key items:
The default tickers in the script are:
AAPL (Apple)
AMZN (Amazon)
NVDA (NVIDIA)
MSFT (Microsoft)
GOOGL (Alphabet/Google)
TSLA (Tesla)
META (Meta Platforms/Facebook)
Raw Weighted Momentum (Histogram):
Each bar represents the combined (weighted) percentage change across your chosen symbols for that bar.
Bars are colored green if the momentum is above zero, or red if below zero.
Smoothed Momentum (Yellow Line):
An Exponential Moving Average (EMA) of the raw momentum for a smoother trend view.
Helps visualize when short-term momentum is accelerating or decelerating relative to its average.
Features
Symbol Inputs: Up to seven user-defined tickers, with weights for each symbol.
Smoothing Period: Set a custom lookback length to calculate the EMA (or switch to SMA in the code if you prefer).
Table Display: A built-in table in the top-right corner lists each symbol’s real-time percentage change, plus the total weighted momentum.
Alerts:
Configure alerts for when the weighted momentum crosses above or below user-defined thresholds.
Helps you catch major shifts in sentiment across multiple symbols.
How To Use
Select Symbols & Weights: In the indicator’s settings, specify the tickers you want to monitor and their corresponding weights. Weights default to 1 (equal weighting).
Watch the Bars vs. Zero:
Bars above zero mean a positive weighted momentum (the basket is collectively moving up).
Bars below zero mean negative weighted momentum (the basket is collectively under pressure).
Check the Yellow Line: The EMA of momentum.
If the bars consistently stay above the line, short-term momentum is stronger than its recent average.
If the bars dip below the line, momentum is weakening relative to its average.
Review the Table: Quick snapshot of each symbol’s daily percentage change plus the total basket momentum, all color-coded red or green.
Caution & Tips
This indicator measures rate of change, not absolute price levels. A rising momentum can still be part of a larger downtrend.
Always combine momentum readings with other technical and/or fundamental signals for confirmation.
For better reliability, experiment with different smoothing lengths to suit your trading style (shorter for scalping, longer for swing or positional approaches).
Multi-Feature IndicatorThe Multi-Feature Indicator combines three popular technical analysis tools — RSI, Moving Averages (MA), and MACD — into a single indicator to provide unified buy and sell signals. This script is designed for traders who want to filter out noise and focus on signals confirmed by multiple criteria.
Features:
RSI (Relative Strength Index):
Measures momentum and identifies overbought (70) and oversold (30) conditions.
A signal is triggered when RSI crosses these thresholds.
Moving Averages (MA):
Uses a short-term moving average (default: 9 periods) and a long-term moving average (default: 21 periods).
Buy signals occur when the short-term MA crosses above the long-term MA, indicating an uptrend.
Sell signals occur when the short-term MA crosses below the long-term MA, indicating a downtrend.
MACD (Moving Average Convergence Divergence):
A trend-following momentum indicator that shows the relationship between two moving averages of an asset's price.
Signals are based on the crossover of the MACD line and its signal line.
Unified Buy and Sell Signals:
Buy Signal: Triggered when:
RSI crosses above 30 (leaving oversold territory).
Short-term MA crosses above the long-term MA.
MACD line crosses above the signal line.
Sell Signal: Triggered when:
RSI crosses below 70 (leaving overbought territory).
Short-term MA crosses below the long-term MA.
MACD line crosses below the signal line.
Visualization:
The indicator plots the short-term and long-term moving averages on the price chart.
Green "BUY" labels appear below price bars when all buy conditions are met.
Red "SELL" labels appear above price bars when all sell conditions are met.
Parameters:
RSI Length: Default is 14. This controls the sensitivity of the RSI.
Short MA Length: Default is 9. This determines the short-term trend.
Long MA Length: Default is 21. This determines the long-term trend.
Use Case:
The Multi-Feature Indicator is ideal for traders seeking higher confirmation before entering or exiting trades. By combining momentum (RSI), trend (MA), and momentum shifts (MACD), it reduces false signals and enhances decision-making.
How to Use:
Apply the indicator to your chart in TradingView.
Look for "BUY" or "SELL" signals, which appear when all conditions align.
Use this tool in conjunction with other analysis techniques for best results.
Note:
The default settings are suitable for many assets, but you may need to adjust them for different timeframes or market conditions.
This indicator is meant to assist in trading decisions and should not be used as the sole basis for trading.
NASI +The NASI + indicator is an advanced adaptation of the classic McClellan Oscillator, a tool widely used to gauge market breadth. It calculates the McClellan Oscillator by measuring the difference between the 19-day and 39-day EMAs of net advancing issues, which are optionally adjusted to account for the relative strength of advancing vs. declining stocks.
To enhance this analysis, NASI + applies the Relative Strength Index (RSI) to the cumulative McClellan Oscillator values, generating a unique momentum-based view of market breadth. Additionally, two extra EMAs—a 10-day and a 4-day EMA—are applied to the RSI, providing further refinement to signals for overbought and oversold conditions.
With NASI +, users benefit from:
-A deeper analysis of market momentum through cumulative breadth data.
-Enhanced sensitivity to trend shifts with the applied RSI and dual EMAs.
-Clear visual cues for overbought and oversold conditions, aiding in intuitive signal identification.
DeNoised Momentum [OmegaTools]The DeNoised Momentum by OmegaTools is a versatile tool designed to help traders evaluate momentum, acceleration, and noise-reduction levels in price movements. Using advanced mathematical smoothing techniques, this script provides a "de-noised" view of momentum by applying filters to reduce market noise. This helps traders gain insights into the strength and direction of price trends without the distractions of market volatility. Key components include a DeNoised Moving Average (MA), a Momentum line, and Acceleration bars to identify trend shifts more clearly.
Features:
- Momentum Line: Measures the percentage change of the de-noised source price over a specified look-back period, providing insights into trend direction.
- Acceleration (Ret) Bars: Visualizes the rate of change of the source price, helping traders identify momentum shifts.
- Normal and DeNoised Moving Averages: Two moving averages, one based on close price (Normal MA) and the other on de-noised data (DeNoised MA), enable a comparison of smoothed trends versus typical price movements.
- DeNoised Price Data Plot: Displays the current de-noised price, color-coded to indicate the relationship between the Normal and DeNoised MAs, which highlights bullish or bearish conditions.
Script Inputs:
- Length (lnt): Sets the period for calculations (default: 21). It influences the sensitivity of the momentum and moving averages. Higher values will smooth the indicator further, while lower values increase sensitivity to price changes.
The Length does not change the formula of the DeNoised Price Data, it only affects the indicators calculated on it.
Indicator Components:
1. Momentum (Blue/Red Line):
- Calculated using the log of the percentage change over the specified period.
- Blue color indicates positive momentum; red indicates negative momentum.
2. Acceleration (Gray Columns):
- Measures the short-term rate of change in momentum, shown as semi-transparent gray columns.
3. Moving Averages:
- Normal MA (Purple): A standard simple moving average (SMA) based on the close price over the selected period.
- DeNoised MA (Gray): An SMA of the de-noised source, reducing the effect of market noise.
4. DeNoised Price Data:
- Represented as colored circles, with blue indicating that the Normal MA is above the DeNoised MA (bullish) and red indicating the opposite (bearish).
Usage Guide:
1. Trend Identification:
- Use the Momentum line to assess overall trend direction. Positive values indicate upward momentum, while negative values signal downward momentum.
- Compare the Normal and DeNoised MAs: when the Normal MA is above the DeNoised MA, it indicates a bullish trend, and vice versa for bearish trends.
2. Entry and Exit Signals:
- A change in the Momentum line's color from blue to red (or vice versa) may indicate potential entry or exit points.
- Observe the DeNoised Price Data circles for early signs of a trend reversal based on the interaction between the Normal and DeNoised MAs.
3. Volatility and Noise Reduction:
- By utilizing the DeNoised MA and de-noised price data, this indicator helps filter out minor fluctuations and focus on larger price movements, improving decision-making in volatile markets.
Burst PowerThe Burst Power indicator is to be used for Indian markets where most stocks have a maximum price band limit of 20%.
This indicator is intended to identify stocks with high potential for significant price movements. By analysing historical price action over a user-defined lookback period, it calculates a Burst Power score that reflects the stock's propensity for rapid and substantial moves. This can be helpful for stock selection in strategies involving momentum bursts, swing trading, or identifying stocks with explosive potential.
Key Components
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Significant Move Counts:
5% Moves: Counts the number of days within the lookback period where the stock had a positive close-to-close move between 5% and 10%.
10% Moves: Counts the number of days with a positive close-to-close move between 10% and 19%.
19% Moves: Counts the number of days with a positive close-to-close move of 19% or more.
Maximum Price Move (%):
Identifies the largest positive close-to-close percentage move within the lookback period, along with the date it occurred.
Burst Power Score:
A composite score calculated using the counts of significant moves: Burst Power =(Count5%/5) +(Count10%/2) + (Count19%/0.5)
The score is then rounded to the nearest whole number.
A higher Burst Power score indicates a higher frequency of significant price bursts.
Visual Indicators:
Table Display: Presents all the calculated data in a customisable table on the chart.
Markers on Chart: Plots markers on the chart where significant moves occurred, aiding visual analysis.
Using the Lookback Period
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The lookback period determines how much historical data the indicator analyses. Users can select from predefined options:
3 Months
6 Months
1 Year
3 Years
5 Years
A shorter lookback period focuses on recent price action, which may be more relevant for short-term trading strategies. A longer lookback period provides a broader historical context, useful for identifying long-term patterns and behaviors.
Interpreting the Burst Power Score
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High Burst Power Score (≥15):
Indicates the stock frequently experiences significant price moves.
Suitable for traders seeking quick momentum bursts and swing trading opportunities.
Stocks with high scores may be more volatile but offer potential for rapid gains.
Moderate Burst Power Score (10 to 14):
Suggests occasional significant price movements.
May suit traders looking for a balance between volatility and stability.
Low Burst Power Score (<10):
Reflects fewer significant price bursts.
Stocks are more likely to exhibit longer, sustainable, but slower price trends.
May be preferred by traders focusing on steady growth or longer-term investments.
Note: Trading involves uncertainties, and the Burst Power score should be considered as one of many factors in a comprehensive trading strategy. It is essential to incorporate broader market analysis and risk management practices.
Customisation Options
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The indicator offers several customisation settings to tailor the display and functionality to individual preferences:
Display Mode:
Full Mode: Shows the detailed table with all components, including significant move counts, maximum price move, and the Burst Power score.
Mini Mode: Displays only the Burst Power score and its corresponding indicator (green, orange, or red circle).
Show Latest Date Column:
Toggle the display of the "Latest Date" column in the table, which shows the most recent occurrence of each significant move category.
Theme (Dark Mode):
Switch between Dark Mode and Light Mode for better visual integration with your chart's color scheme.
Table Position and Size:
Position: Place the table at various locations on the chart (top, middle, bottom; left, center, right).
Size: Adjust the table's text size (tiny, small, normal, large, huge, auto) for optimal readability.
Header Size: Customise the font size of the table headers (Small, Medium, Large).
Color Settings:
Disable Colors in Table: Option to display the table without background colors, which can be useful for printing or if colors are distracting.
Bullish Closing Filter:
Another customisation here is to count a move only when the closing for the day is strong. For this, we have an additional filter to see if close is within the chosen % of the range of the day. Closing within the top 1/3, for instance, indicates a way more bullish day tha, say, closing within the bottom 25%.
Move Markers on chart:
The indicator also marks out days with significant moves. You can choose to hide or show the markers on the candles/bars.
Practical Applications
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Momentum Trading: High Burst Power scores can help identify stocks that are likely to experience rapid price movements, suitable for momentum traders.
Swing Trading: Traders looking for short- to medium-term opportunities may focus on stocks with moderate to high Burst Power scores.
Positional Trading: Lower Burst Power scores may indicate steadier stocks that are less prone to volatility, aligning with long-term investment strategies.
Risk Management: Understanding a stock's propensity for significant moves can aid in setting appropriate stop-loss and take-profit levels.
Disclaimer: Trading involves significant risk, and past performance is not indicative of future results. The Burst Power indicator is intended for educational purposes and should not be construed as financial advice. Always conduct thorough research and consult with a qualified financial professional before making investment decisions.
Price-Shift Oscillator (PSO)The PSOscillator calculates an oscillator value based on price movements over a specific period. Oscillators like this one are typically used to identify momentum shifts, and trend direction. Here's a breakdown of how the logic behind it works:
Key Concepts for Beginners:
Oscillators:
In this case, the PSOscillator helps indicate whether the market momentum is positive (price might rise) or negative (price might fall).
Input Parameters:
oscPeriod: This is the number of bars (or candles) used to calculate the oscillator. It affects how sensitive the oscillator is to price changes. A lower period makes it more sensitive to short-term movements, while a higher period smoothens it out.
smaPeriod: This is a simple moving average (SMA) applied to the oscillator for additional smoothing, further reducing noise.
Calculation Logic:
The JpOscillator uses recent price data to calculate its value. Specifically, it looks at the closing prices of the current and previous bars (candles). periods ago).
This calculation aims to identify how much recent price action is deviating from past price behavior.
Essentially, it tells us whether the current price is higher or lower relative to the past, and how the trend is evolving over recent periods.
Smoothing:
After calculating the oscillator values, we apply optional smoothing to make it less "jumpy." This is useful in reducing the noise caused by small, insignificant price movements.
The sma_from_array function averages out the recent oscillator values to make the signal smoother, depending on the oscPeriod.
Oscillator Levels:
Above Zero:
If the oscillator is above 0, it means the price is gaining momentum upwards (bullish signal), which is why we color the histogram green.
Below Zero: If the oscillator is below 0, it indicates downward momentum (bearish signal), which is why we color the histogram red.
You can think of the zero line as a "neutral zone." Crossing above it means momentum is shifting to the upside, and crossing below it means momentum is shifting to the downside.
Histogram Plotting:
The values of the oscillator are plotted as a histogram (bars). The color changes based on whether the oscillator is above or below zero (green for positive and red for negative momentum).
The moving average (SMA) of the oscillator is plotted as a line to help identify trends over time.
Using two different coloring methods for a histogram in a trading strategy can provide a trader with distinct, layered information about market conditions, trends, and momentum shifts. Each coloring method can highlight different aspects of the price action or the oscillator behavior. Here’s how a trader might use both methods to their advantage:
ETHUSDT Daily
1. Color Based on Oscillator Position Relative to Zero
This method colors the histogram green when the oscillator value is above zero and red when it's below zero. This coloring strategy is straightforward and helps a trader quickly identify whether the market's momentum is generally bullish or bearish.
Advantages:
Trend Confirmation: When the oscillator remains above zero and green, it can confirm a bullish trend, and vice versa for a bearish trend with red colors below zero.
Quick Visual Reference: Easy to see at a glance, helping in fast decision-making processes.
2. Color Based on the Change of the Oscillator
This method changes the color based on whether the oscillator is increasing or decreasing compared to its previous value. For instance, a darker shade of green might be used if the oscillator value is rising from one period to the next, indicating increasing bullish momentum, and a darker red if declining, indicating increasing bearish momentum.
Advantages:
Momentum Insight: This coloring method gives insights into the strength of the movement. An oscillator that is increasing (even below zero) might suggest a weakening of a bearish trend or the start of a bullish reversal.
Detecting Reversals: Seeing the oscillator rise from negative to less negative or drop from positive to less positive can alert traders to potential early reversals before they cross the zero line.
Strategic Use in Trading:
A trader can use these two methods together by applying a multi-layered approach to analyze the oscillator:
Overall Trend Assessment:
Above Zero (Green): Considered bullish; look for buy opportunities, especially if the color gets brighter (indicating strengthening).
Below Zero (Red): Considered bearish; look for sell opportunities, especially if the color gets darker (indicating strengthening).
Short-Term Momentum and Entries:
Brightening Green: Could indicate a good time to enter or add to long positions as bullish momentum increases.
Darkening Red: Could indicate a good time to enter or add to short positions as bearish momentum increases.
Lightening Color: If red starts to lighten (become less intense), it might suggest a bearish trend is losing steam, which could be an exit signal for shorts or an early warning for a potential long setup.
Risk Management:
Switch in Color Intensity: A sudden change in color intensity can be used as a trigger for tightening stops or taking partial profits, helping manage risk by responding to changes in market momentum.
