Moving_AveragesLibrary "Moving_Averages"
This library contains majority important moving average functions with int series support. Which means that they can be used with variable length input. For conventional use, please use tradingview built-in ta functions for moving averages as they are more precise. I'll use functions in this library for my other scripts with dynamic length inputs.
ema(src, len)
Exponential Moving Average (EMA)
Parameters:
src : Source
len : Period
Returns: Exponential Moving Average with Series Int Support (EMA)
alma(src, len, a_offset, a_sigma)
Arnaud Legoux Moving Average (ALMA)
Parameters:
src : Source
len : Period
a_offset : Arnaud Legoux offset
a_sigma : Arnaud Legoux sigma
Returns: Arnaud Legoux Moving Average (ALMA)
covwema(src, len)
Coefficient of Variation Weighted Exponential Moving Average (COVWEMA)
Parameters:
src : Source
len : Period
Returns: Coefficient of Variation Weighted Exponential Moving Average (COVWEMA)
covwma(src, len)
Coefficient of Variation Weighted Moving Average (COVWMA)
Parameters:
src : Source
len : Period
Returns: Coefficient of Variation Weighted Moving Average (COVWMA)
dema(src, len)
DEMA - Double Exponential Moving Average
Parameters:
src : Source
len : Period
Returns: DEMA - Double Exponential Moving Average
edsma(src, len, ssfLength, ssfPoles)
EDSMA - Ehlers Deviation Scaled Moving Average
Parameters:
src : Source
len : Period
ssfLength : EDSMA - Super Smoother Filter Length
ssfPoles : EDSMA - Super Smoother Filter Poles
Returns: Ehlers Deviation Scaled Moving Average (EDSMA)
eframa(src, len, FC, SC)
Ehlrs Modified Fractal Adaptive Moving Average (EFRAMA)
Parameters:
src : Source
len : Period
FC : Lower Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
SC : Upper Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
Returns: Ehlrs Modified Fractal Adaptive Moving Average (EFRAMA)
ehma(src, len)
EHMA - Exponential Hull Moving Average
Parameters:
src : Source
len : Period
Returns: Exponential Hull Moving Average (EHMA)
etma(src, len)
Exponential Triangular Moving Average (ETMA)
Parameters:
src : Source
len : Period
Returns: Exponential Triangular Moving Average (ETMA)
frama(src, len)
Fractal Adaptive Moving Average (FRAMA)
Parameters:
src : Source
len : Period
Returns: Fractal Adaptive Moving Average (FRAMA)
hma(src, len)
HMA - Hull Moving Average
Parameters:
src : Source
len : Period
Returns: Hull Moving Average (HMA)
jma(src, len, jurik_phase, jurik_power)
Jurik Moving Average - JMA
Parameters:
src : Source
len : Period
jurik_phase : Jurik (JMA) Only - Phase
jurik_power : Jurik (JMA) Only - Power
Returns: Jurik Moving Average (JMA)
kama(src, len, k_fastLength, k_slowLength)
Kaufman's Adaptive Moving Average (KAMA)
Parameters:
src : Source
len : Period
k_fastLength : Number of periods for the fastest exponential moving average
k_slowLength : Number of periods for the slowest exponential moving average
Returns: Kaufman's Adaptive Moving Average (KAMA)
kijun(_high, _low, len, kidiv)
Kijun v2
Parameters:
_high : High value of bar
_low : Low value of bar
len : Period
kidiv : Kijun MOD Divider
Returns: Kijun v2
lsma(src, len, offset)
LSMA/LRC - Least Squares Moving Average / Linear Regression Curve
Parameters:
src : Source
len : Period
offset : Offset
Returns: Least Squares Moving Average (LSMA)/ Linear Regression Curve (LRC)
mf(src, len, beta, feedback, z)
MF - Modular Filter
Parameters:
src : Source
len : Period
beta : Modular Filter, General Filter Only - Beta
feedback : Modular Filter Only - Feedback
z : Modular Filter Only - Feedback Weighting
Returns: Modular Filter (MF)
rma(src, len)
RMA - RSI Moving average
Parameters:
src : Source
len : Period
Returns: RSI Moving average (RMA)
sma(src, len)
SMA - Simple Moving Average
Parameters:
src : Source
len : Period
Returns: Simple Moving Average (SMA)
smma(src, len)
Smoothed Moving Average (SMMA)
Parameters:
src : Source
len : Period
Returns: Smoothed Moving Average (SMMA)
stma(src, len)
Simple Triangular Moving Average (STMA)
Parameters:
src : Source
len : Period
Returns: Simple Triangular Moving Average (STMA)
tema(src, len)
TEMA - Triple Exponential Moving Average
Parameters:
src : Source
len : Period
Returns: Triple Exponential Moving Average (TEMA)
thma(src, len)
THMA - Triple Hull Moving Average
Parameters:
src : Source
len : Period
Returns: Triple Hull Moving Average (THMA)
vama(src, len, volatility_lookback)
VAMA - Volatility Adjusted Moving Average
Parameters:
src : Source
len : Period
volatility_lookback : Volatility lookback length
Returns: Volatility Adjusted Moving Average (VAMA)
vidya(src, len)
Variable Index Dynamic Average (VIDYA)
Parameters:
src : Source
len : Period
Returns: Variable Index Dynamic Average (VIDYA)
vwma(src, len)
Volume-Weighted Moving Average (VWMA)
Parameters:
src : Source
len : Period
Returns: Volume-Weighted Moving Average (VWMA)
wma(src, len)
WMA - Weighted Moving Average
Parameters:
src : Source
len : Period
Returns: Weighted Moving Average (WMA)
zema(src, len)
Zero-Lag Exponential Moving Average (ZEMA)
Parameters:
src : Source
len : Period
Returns: Zero-Lag Exponential Moving Average (ZEMA)
zsma(src, len)
Zero-Lag Simple Moving Average (ZSMA)
Parameters:
src : Source
len : Period
Returns: Zero-Lag Simple Moving Average (ZSMA)
evwma(src, len)
EVWMA - Elastic Volume Weighted Moving Average
Parameters:
src : Source
len : Period
Returns: Elastic Volume Weighted Moving Average (EVWMA)
tt3(src, len, a1_t3)
Tillson T3
Parameters:
src : Source
len : Period
a1_t3 : Tillson T3 Volume Factor
Returns: Tillson T3
gma(src, len)
GMA - Geometric Moving Average
Parameters:
src : Source
len : Period
Returns: Geometric Moving Average (GMA)
wwma(src, len)
WWMA - Welles Wilder Moving Average
Parameters:
src : Source
len : Period
Returns: Welles Wilder Moving Average (WWMA)
ama(src, _high, _low, len, ama_f_length, ama_s_length)
AMA - Adjusted Moving Average
Parameters:
src : Source
_high : High value of bar
_low : Low value of bar
len : Period
ama_f_length : Fast EMA Length
ama_s_length : Slow EMA Length
Returns: Adjusted Moving Average (AMA)
cma(src, len)
Corrective Moving average (CMA)
Parameters:
src : Source
len : Period
Returns: Corrective Moving average (CMA)
gmma(src, len)
Geometric Mean Moving Average (GMMA)
Parameters:
src : Source
len : Period
Returns: Geometric Mean Moving Average (GMMA)
ealf(src, len, LAPercLen_, FPerc_)
Ehler's Adaptive Laguerre filter (EALF)
Parameters:
src : Source
len : Period
LAPercLen_ : Median Length
FPerc_ : Median Percentage
Returns: Ehler's Adaptive Laguerre filter (EALF)
elf(src, len, LAPercLen_, FPerc_)
ELF - Ehler's Laguerre filter
Parameters:
src : Source
len : Period
LAPercLen_ : Median Length
FPerc_ : Median Percentage
Returns: Ehler's Laguerre Filter (ELF)
edma(src, len)
Exponentially Deviating Moving Average (MZ EDMA)
Parameters:
src : Source
len : Period
Returns: Exponentially Deviating Moving Average (MZ EDMA)
pnr(src, len, rank_inter_Perc_)
PNR - percentile nearest rank
Parameters:
src : Source
len : Period
rank_inter_Perc_ : Rank and Interpolation Percentage
Returns: Percentile Nearest Rank (PNR)
pli(src, len, rank_inter_Perc_)
PLI - Percentile Linear Interpolation
Parameters:
src : Source
len : Period
rank_inter_Perc_ : Rank and Interpolation Percentage
Returns: Percentile Linear Interpolation (PLI)
rema(src, len)
Range EMA (REMA)
Parameters:
src : Source
len : Period
Returns: Range EMA (REMA)
sw_ma(src, len)
Sine-Weighted Moving Average (SW-MA)
Parameters:
src : Source
len : Period
Returns: Sine-Weighted Moving Average (SW-MA)
vwap(src, len)
Volume Weighted Average Price (VWAP)
Parameters:
src : Source
len : Period
Returns: Volume Weighted Average Price (VWAP)
mama(src, len)
MAMA - MESA Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: MESA Adaptive Moving Average (MAMA)
fama(src, len)
FAMA - Following Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: Following Adaptive Moving Average (FAMA)
hkama(src, len)
HKAMA - Hilbert based Kaufman's Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: Hilbert based Kaufman's Adaptive Moving Average (HKAMA)
Search in scripts for "Exponential Moving Average"
Trend Gradient Moving Average This moving average uses a gradient function which calculates the number of advances/declines of the moving average to change the intensity of the colors, meaning a longer trend in either direction will show a stronger color. You can choose 3 colors to build the gradient: a bullish, bearish & neutral/transition color. The number of steps chosen will change the speed of color change, with a lower number of steps meaning a faster transition and viceversa.
Furthermore, you can choose between many different types of moving averages:
-SMA (Simple Moving Average)
-EMA (Exponential Moving Average)
-RMA (Rolling Moving Average)
-WMA (Weighted Moving Average)
-HMA (Hull Moving Average)
-VWMA (Volume Weighted Moving Average)
-TMA (Triangular Moving Average)
Enjoy!
Erzurum Indicators (By DadashKadir)Erzurum Indicators (By DadashKadir)
An indicator in which you will keep track of the buying and selling movements by adding the movements of the three moving averages together. The parameters were determined as Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA) and Volume Weighted Moving Average (VWMA). Its constant value was taken as WMA. It is used to calculate the averages of 3 - 5 and 7. You can include the standard deviation (STDEV) in these moving averages.
The name of the indicator is taken from our city of Erzurum, the pearl of Eastern Anatolia.
On Balance Volume FieldsThe On Balance Volume (OBV) indicator was developed by Joseph E. Granville and published first in his book "New key to stock market profits" in 1963. It uses volume to determine momentum of an asset. The base concept of OBV is - in simple terms - you take a running total of the volume and either add or subtract the current timeframe volume if the market goes up or down. The simplest use cases only use the line build that way to confirm direction of price, but the possibilities and applications of OBV go far beyond that and are (at least to my knowledge) not found in existing indicators available on this platform.
If you are interested to get a deeper understanding of OBV, I recommend the lecture of the above mentioned book by Granville. All the features described below are taken directly from the book or are inspired by it (deviations will be marked accordingly). If you have no prior experience with OBV, I recommend to start simple and read an easy introduction (e.g. On-Balance Volume (OBV) Definition from Investopedia) and start applying the basic concepts first before heading into the more advanced analysis of OBV fields and trends.
Markets and Timeframes
As the OBV is "just" a momentum indicator, it should be applicable to any market and timeframe.
As a long term investor, my experience is limited to the longer timeframes (primarily daily), which is also how Granville applies it. But that is most likely due to the time it was developed and the lack of lower timeframe data at that point in time. I don't see why it wouldn't be applicable to any timeframe, but cannot speak from experience here so do your own research and let me know. Likewise, I invest in the crypto markets almost exclusively and hence this is where my experience with this indicator comes from.
Feature List
As a general note before starting into the description of the individual features: I use the colors and values of the default settings of the indicator to describe it. The general look and feel obviously can be customized (and I highly recommend doing so, as this is a very visual representation of volume, and it should suit your way of looking at a chart) and I also tried to make the individual features as customizable as possible.
Also, all additions to the OBV itself can be turned off so that you're left with just the OBV line (although if that's what you want, I recommend a version of the indicator with less overhead).
Fields
Fields are defined as successive UPs or DOWNs on the OBV. An UP is any OBV reading above the last high pivot and subsequently a DOWN is any reading below the last low pivot. An UP-field is the time from the first UP after a DOWN-field to the first DOWN (not including). The same goes for a DOWN field but vice versa.
The field serves the same purpose as the OBV itself. To indicate momentum direction. I haven't found much use for the fields themselves other than serving as a more smoothed view on the current momentum. The real power of the fields emerges when starting to determine larger trends of off them (as you will see soon).
Therefor the fields are displayed on the indicator as background colors (UP = green, DOWN = red), but only very faint to not distract too much from the other parts of the indicator.
Major Volume Trend
The major volume trend - from which Granville says, it's the one that tends to precede price - is determined as the succession of the highest highs and lowest lows of UP and DOWN fields. It is represented by the colors of the numbers printed on the highs and lows of the fields.
The trend to be "Rising" is defined as the highest high of an UP field being higher than the highest high of the last UP field and the lowest low of the last DOWN field being higher than the lowest low of the prior DOWN field. And vice versa for a "Falling" trend. If the trend does not have a rising or falling pattern, it is said to be "Doubtful". The colors are indicated as follows:
Rising = green
Falling = red
Doubtful = blue
ZigZag Swing count
The swing count is determined by counting the number of swings within a trend (as described above) and is represented by the numbers above the highs and lows of the fields. It determines the length and thus strength of a trend.
In general there are two ways to determine the count. The first one is by counting the swings between pivots and the second one by counting the swings between highs and lows of fields. This indicator represents the SECOND one as it represents the longer term trend (which I'm more interested in as it denotes a longer term perspective).
However, the ZigZag count has three applications on the OBV. The "simple ZigZag" is a count of three swings which mainly tells you that the shorter term momentum of the market has changed and the current trend is weakening. This doesn't mean it will reverse. A count of three downs is still healthy if it occurs on a strong uptrend (and vice versa) and it should primarily serve as a sign of caution. If the count increases beyond three, the last trend is weakening considerably, and you should probably take action.
The second count to look out for is five swings - the "compound ZigZag". If this goes hand in hand with breaking a major support/resistance on the OBV it can offer a buying/selling opportunity in the direction of the trend. Otherwise, there's a good chance that this is a reversal signal.
The third count is nine. To quote Granville directly: "there is a very strong tendency FOR MAJOR REVERSAL OF REND AFTER THE NINTH SWING" (emphasis by the author). This is something I look out for and get cautious about, although I have found signal to be weak in an overextended market. I have observed counts of 10 and even 12 which did not result in a major reversal and the market trended further after a short period of time. This is still a major sign of caution and should not be taken lightly.
Moving average
Although Granville talks only briefly about averages and the only mention of a specific one is the 10MA, I found moving averages to be a very valuable addition to my analysis of the OBV movements.
The indicator uses three Exponential Moving Averages. A long term one to determine the general direction and two short term ones to determine the momentum of the trend. Especially for the latter two, keep in mind that those are very indirect as they are indicators of an indicator anyway and I they should not necessarily be used as support or resistance (although that might sometimes be helpful). I recommend paying most attention to the longterm average as I've found it to be very accurate when determining the longterm trend of a market (even better than the same indicator on the price).
If the OBV is above the long term average, the space between OBV and average is filled green and filled red if below. The colors and defaults for the averages are:
long term, 144EMA, green
short term 1, 21EMA, blue
short term 2, 55EMA, red
Divergences
This is a very rudimentary adaption of the standard TradingView "Divergence Indicator". I find it helpful to have these on the radar, but do not actively use them (as in having a strategy based on OBV/price divergence). This is something that I would eventually pick up in a later version of the indicator if there is any demand for it, or I find the time to look into strategies based on this.
Comparison line
A small but very helpful addition to the indicator is a horizontal line that traces the current OBV value in real time, which makes it very easy to compare the current value of the OBV to historic values (which is a study I can highly recommend).
Trend Reversal Indicator (EMA of slopes)Good morning Traders
Inspirated by lukescream EMA-slope strategy, today I want to share with you this simple indicator whose possible use-case would be for detecting in advance possible trend reversals, specially on higher timeframes.
Once that you've chosen the desired source (RSI, EMA or Stochastic k or d), the indicator will calculate its "slope" approximating its first order derivative by the division between the last variation of the series and its last value.
You can see the slope as a white line by enabling the relative checkmark (it's disabled by default since it simply messes up the the graph)
Then, the slope itself becomes the source for two exponential moving averages: the fast one (in blue) has a period of 20 while the slow one (in red, it becomes similiar to a horizontal line actually) has a period of 500
Why the slope? Since all the sources mentioned before are directly or indirectly calculated on the price action, a more aggressiveness in the price movement would be translated into a more (positive/negative) steepness of those indicator (of course this effect would be far more evident if the indicators are calculated on low periods, but really low periods could compromise the consistency of the signals).
In this way, the slope would mirror the decisiveness of price movements and a comparison between two averages calculated from it (the first one based on more recent values, the second one that conisders also older values) could tell you in advance what direction the market is possibly about to take
The usage is simple: once that the fast moving average crosses upward the slow one, this could be a sign of potential trend reversal from bearish to bullish. On the contrary, if the fast EMA crosses downward the slow one, this could be a sign of potential trend reversal from bullish to bearish.
What I suggest you is to integrate this indicator with Exponential Moving Averages plotted on the price candles, in order to have a general bias for opening long or short positions, and with an oscillator as well such as the Stochastisc RSI in order to detect the overbought/oversold zones for opening/closing positions at the right moment.
Happy Trading!
Dazzling BoltsThis is three moving average based strategy focused on trend-following. Targets and stops are set based on ATR. Following image pictures the strategy with all mas plotted:
Buying conditions are:
►A smoothened moving average (red) is above the exponential moving average (yellow)
►An exponential moving average is above simple moving average (black)
►Low five candles ago was still above the exponential moving average
►Low two candles ago reached below the exponential moving average
►Close of the previous candle was above the exponential moving average
►Ema force is disabled or exponential moving average set candles ago (orange) is still above simple moving average now.
If these conditions are met, Dazzling Bolts will always give you a signal. However, it holds only one position at a time and it will not buy again until it is closed or exited.
There are two ways exiting may happen. Smoothened moving average crosses below simple moving average or it reaches value based on your settings of average true range and its multiplier.
Settings 10/76/200/true/50/true/true/5/5 shows perfect results on EURUSD 15m chart but it does not guarantee the results. It is only 62 trades which is barely a useful statistical source. It is also highly optimized which means its settings filters out bad trades that may be bad only because of randomnation rather than set market behaviour. You need to test it on 200 trades + before using.
Moving averages (EMA & SMA) by magariMoving averages (EMA & SMA)
The script contains moving averages:
- Exponential Moving Averages: EMA20, EMA50, EMA100, EMA200
- Simple Moving Averages: SMA50, SMA100 & SMA200.
You can display all of them in one chart and they count as one indicator (perfect for non pro users) switch each of them on or off and change their colors and line widths.
Uptrick: Volume Weighted BandsIntroduction
This indicator, Uptrick: Volume Weighted Bands, overlays dynamic, volume-informed trend channels directly on the chart. By fusing price and volume data through volume-weighted and exponential moving averages, the script forms a core trend line with adaptive bandwidth controlled by volatility. It is designed to help traders identify trend direction, breakout entries, and extended conditions that may warrant take-profits or pullback re-entries.
Overview
The Volume Weighted Bands system is built around a trend line calculated by averaging a Volume Weighted Moving Average (VWMA) and an Exponential Moving Average (EMA), both over a configurable lookback period. This hybrid trend baseline is then smoothed further and expanded into dynamic upper and lower bands using an Average True Range (ATR) multiplier. These bands adapt with market volatility and shift color based on prevailing price action, helping traders quickly identify bullish, bearish, or neutral conditions.
Originality and Unique Features
This script introduces originality by blending both price and volume in the core trend calculation, a technique that is more responsive than traditional moving average bands. Its multi-mode visualization (cloud, single-band, or line-only), combined with selective buy/sell signals, makes it flexible for discretionary and algorithmic strategies alike. Optional modules for take-profit signals based on z-score deviation and RSI slope, as well as buy-back detection logic with cooldown filters, offer practical tools for managing trades beyond simple entries.
Explanation of Inputs
Every user input in this script is included to give the trader control over behavior and visual presentation:
Trend Length (len): Defines the lookback window for both the VWMA and EMA, controlling the sensitivity of the core trend baseline. A lower value makes the bands more reactive, while a higher value smooths out short-term noise.
Extra Smoothing (smoothLen): Applies an additional EMA to the blended VWMA/EMA average. This second-level smoothing ensures the central trend line reacts gradually to shifts in price.
Band Width (ATR Multiplier) (bandMult): Multiplies the ATR to create the width of the upper and lower bands around the trend line. Larger values widen the bands, capturing more volatility, while smaller values narrow them.
ATR Length (atrLen): Sets the length of the ATR used in calculating band width and signal offsets. Longer values produce smoother band boundaries.
Show Buy/Sell Signals (showSignals): Toggles the primary crossover/crossunder entry signals, which are labeled when the close crosses the upper or lower band.
Visual Mode (visualMode): Allows selection between three display modes:
--> Cloud: Shows both bands and the central trend line with a shaded background.
--> Single Band: Displays only the active (upper or lower) band depending on trend state, with gradient fill to price.
--> Line Only: Shows only the trend line for a minimal visual profile.
Take Profit Signals (enableTP): Enables a z-score-based profit-taking signal system. Signals occur when price deviates significantly from the trend line and RSI confirms exhaustion.
TP Z-Score Threshold (tpThreshold): Sets the z-score deviation required to trigger a take-profit signal. Higher values reduce the frequency of signals, focusing on more extreme moves.
Re-Entries (enableBuyBack): Enables logic to signal when price reverts into the band after an initial breakout, suggesting a possible re-entry or pullback setup.
Buy Back Cooldown (bars) (buyBackCooldown): Defines a minimum bar count before a new buy-back signal is allowed, preventing rapid retriggering in choppy conditions.
Buy Offset and Sell Offset: Hidden inputs used to vertically adjust the placement of the Buy ("𝓤𝓹") and Sell ("𝓓𝓸𝔀𝓷") labels relative to the bands. These use ATR units to maintain proportionality across different instruments and timeframes.
Take-Profit Signal Module
The take-profit module uses a z-score of the distance between price and the trend line to detect extended conditions. In bullish trends, a signal appears when price is well above the band and RSI indicates exhaustion; the opposite applies for bearish conditions. A boolean flag is used to prevent retriggering until RSI resets. These signals are plotted with minimalist “X” markers near recent highs or lows, based on whether the market is extended upward or downward.
Re-Entry Logic
The re-entry system identifies instances where price momentarily dips or spikes into the opposite band but closes back inside, implying a continuation of the prevailing trend. This module can be particularly useful for traders managing entries after brief pullbacks. A built-in cooldown period helps filter out noise and prevents signal overloading during fast markets. Visual markers are shown as upward or downward arrows near the relevant candle wicks.
How to Use This Indicator
The basic usage of this indicator follows a directional, signal-driven approach. When a buy signal appears, it suggests entering a long position. The recommended stop loss placement is below the lower band, allowing for some breathing space to accommodate natural volatility. As the position progresses, take partial profits—typically 10% to 15% of the position—each time a take-profit signal (marked with an "X") is shown on the chart.
An optional feature is the buy-back signal, which can be used to re-enter after partial exits or missed entries. Utilizing this can help reduce losses during false breakouts or trend reversals by scaling in more gradually. However, it also means that in strong, clean trends, the full position may not be captured from the start, potentially reducing the total return. It is up to the trader to decide whether to enter fully on the initial signal or incrementally using buy-backs.
When a sell signal appears, the strategy advises fully exiting any long positions and immediately switching to a short position. The short trade follows the same logic: place your stop loss above the upper band with some margin, and again, take partial profits at each take-profit signal.
Visual Presentation and Signal Labels
All signals are plotted with clean, minimal labels that avoid clutter, and are color-coded using a custom palette designed to remain clear across light and dark chart themes. Bullish trends are marked in teal and bearish trends in magenta. Candles and wicks are also colored accordingly to align price action with the detected trend state. Buy and sell entries are marked with "𝓤𝓹" and "𝓓𝓸𝔀𝓷" labels.
Summary
In summary, the Uptrick: Volume Weighted Bands indicator provides a versatile, visually adaptive trend and volatility tool that can serve multiple styles of trading. Through its integration of price, volume, and volatility, along with modular take-profit and buy-back signaling, it aims to provide actionable structure across a range of market conditions.
Disclaimer
This indicator is for educational purposes only. Trading involves risk, and past performance does not guarantee future results. Always test strategies before applying them in live markets.
PRO Scalper(EN)
## What it is
**PRO Scalper** is an intraday price–action and liquidity map that helps you see where the market is likely to move **now**, not just where it has been.
It combines five building blocks that professional scalpers often watch together:
1. **Session Volume-Weighted Average Price (VWAP)** — the intraday “fair value” anchor.
2. **Opening Range** — the first minutes of the session that set the day’s balance.
3. **Trend filter** — higher-timeframe bias using **Exponential Moving Averages (EMA)** and optional **Average Directional Index (ADX)** strength.
4. **Two independent Supply/Demand zone engines** — zones are drawn from confirmed swing pivots, with midlines and **touch counters**.
5. **Order-flow style visuals**:
* **Delta bubbles** (green/red circles) show where buying or selling pressure was unusually strong, using a safe **delta proxy** (no external feeds).
* **Liquidity densities** (subtle rectangular bands) highlight clusters of large activity that often act as magnets or barriers and disappear when “eaten” by strong moves.
This mix gives you a **complete intraday picture**: the mean (VWAP), the day’s initial balance (Opening Range), the higher-timeframe push (trend filter), the nearby fuel or brakes (zones), and the live pressure points (bubbles and densities).
---
## Why these components
* **VWAP** tracks where the bulk of traded value sits. Price tends to rotate around it or accelerate away from it — a perfect compass for scalps.
* **Opening Range** frames the early auction. Many intraday breaks, fades and retests start at its boundaries.
* **EMA bias + ADX strength** separates trending conditions from chop, so you can keep only the zones that agree with the bigger push.
* **Pivot-based zones (two pairs at once)** are simple, objective and fast. Midlines help with confirmations; touch counters quantify how many times the zone was tested.
* **Bubbles and densities** add the “effort” layer: where the push appeared and where liquidity is concentrated. You see **where** a move is likely to continue or fail.
Together they reduce ambiguity: **context + level + effort** — all on one screen.
---
## How it works (plain language)
* **VWAP** resets each day and is calculated as the cumulative sum of typical price multiplied by volume divided by total volume.
* **Opening Range** is either automatic (a multiple of your chart timeframe) or a manual number of minutes. While it is forming, the highest high and lowest low are captured and plotted as the range.
* **Trend filter**
* **EMA Fast** and **EMA Slow** define directional bias.
* **ADX (optional)** adds “trend strength”: only when the Average Directional Index is above the chosen threshold do we treat the move as strong. You can source this from a higher timeframe.
* **Zones**
* There are **two independent pairs** of pivots at the same time (for example 10-left 10-right and 5-left 5-right).
* Each detected pivot creates a **Supply** (from a swing high) or **Demand** (from a swing low) box. Box depth = **zone depth × Average True Range** for adaptive sizing; the boxes **extend forward**.
* Midline (optional dashed line inside the box) is the “balance” of the zone.
* **“Only in trend”** mode can hide boxes that go against the higher-timeframe bias.
* The **touch counter** increases when price revisits the box. Labels show the pair name and the number of touches.
* **Bubbles**
* A safe **delta proxy** measures bar pressure (for example, range-weighted close vs open).
* A **quantile filter** shows only unusually large pressure: choose lookback and percentile, and the script draws a circle sized by intensity (green = bullish pressure, red = bearish).
* **Densities**
* The script marks heavy activity clusters as **subtle bands** around price (depth = fraction of Average True Range).
* If price **breaks** a density with volume above its moving average, the band **disappears** (“eaten”), which often precedes continuation.
---
## How to use — practical playbooks
> Recommended chart: crypto or index futures, one to five minutes. Use **one hour** or **fifteen minutes** for the higher-timeframe bias.
### 1) Trend pullback scalp (continuation)
1. Enable **Only in trend** zones.
2. In an uptrend: wait for a pullback into a **Demand** zone that overlaps with VWAP or sits just below the Opening Range midpoint.
3. Look for **green bubbles** near the zone’s bottom or a fresh **density** under price.
4. Enter on a candle closing **back above the zone midline**.
5. Stop-loss: below the bottom of the zone or a small multiple of Average True Range.
6. Targets: previous swing high, Opening Range high, fixed risk multiples, or VWAP.
Mirror the logic for downtrends using Supply zones, red bubbles and densities above price.
### 2) Reversion with liquidity sweep (fade)
1. Bias neutral or countertrend allowed.
2. Price **wicks through** a zone boundary (or an Opening Range line) and **closes back inside** the zone.
3. The bubble color often flips (absorption).
4. Enter toward the **inside** of the zone; stop beyond the sweep wick; first target = zone midline, second = opposite side of the zone or VWAP.
### 3) Opening Range break and retest
1. Wait for the Opening Range to complete.
2. A break with a large bubble suggests intent.
3. Look for a **retest** into a nearby zone aligned with VWAP.
4. Trade continuation toward the next zone or the session extremes.
### 4) Density “eaten” continuation
1. When a density band **disappears** on high volume, it often means the resting liquidity was consumed.
2. Trade in the direction of the break, toward the nearest opposing zone.
---
## Settings — quick guide
**Core**
* *ATR Length* — used for zone and density depths.
* *Show VWAP / Show Opening Range*.
* *Opening Range*: Auto (multiple of timeframe minutes) or Manual minutes.
**Trend Filter**
* *Mode*: Off, EMA only, or EMA with ADX strength.
* *Use higher timeframe* and its value.
* *EMA Fast / EMA Slow*, *ADX Length*, *ADX threshold*.
* *Plot EMA filter* to display the moving averages.
**Zones (two pairs)**
* *Pivot A Left / Right* and *Pivot B Left / Right*.
* *Zone depth × ATR*, *Extend bars*.
* *Show zone midline*, *Only in trend zones*.
* Labels automatically show the touch counters.
**Bubbles**
* *Show Bubbles*.
* *Quantile lookback* and *Quantile percent* (higher percent = stricter filter, fewer bubbles).
**Densities**
* *Metric*: absolute delta proxy or raw volume.
* *Quantile lookback / percent*.
* *Depth × ATR*, *Extend bars*, *Merge distance* (in ATR),
* *Break condition*: volume moving average length and multiplier,
* *Midline for densities* (optional dashed line).
---
## Tips and risk management
* This script **does not use external order-flow feeds**. Delta is a **proxy** suitable for TradingView; tune quantiles per symbol and timeframe.
* Do not trade every bubble. Combine **context (trend + VWAP + Opening Range)** with **level (zone)** and **effort (bubble/density)**.
* Set stop-losses beyond the zone or at a fraction of Average True Range. Predefine risk per trade.
* Backtest your rules with a strategy script before using real funds.
* Markets differ. Parameters that work on Bitcoin may not transfer to low-liquidity altcoins or stocks.
* Nothing here is financial advice. Scalping is high-risk; slippage and over-trading can quickly damage your account.
---
## What makes PRO Scalper unique
* Two **independent** zone engines run in parallel, so you can see both **larger structure** and **fine intraday levels** at the same time.
* Clean **“only in trend” rendering** — zones and midlines against the bias can be hidden, reducing clutter and hesitation.
* **Touch counters** convert “feel” into numbers.
* **Self-contained order-flow visuals** (bubbles and densities) that require no extra data sources.
* Careful defaults: subtle colors for densities, clearer zones, and responsive auto Opening Range.
---
(RU)
## Что это такое
**PRO Scalper** — это индикатор для внутридневной торговли, который показывает **контекст и ликвидность прямо сейчас**.
Он объединяет пять модулей, которыми профессиональные скальперы пользуются вместе:
1. **VWAP** — средневзвешенная по объему цена за сессию, «справедливая стоимость» дня.
2. **Opening Range** — первая часть сессии, задающая баланс дня.
3. **Фильтр тренда** — направление старшего таймфрейма по **экспоненциальным средним** и при желании по силе тренда **Average Directional Index**.
4. **Две независимые системы зон спроса/предложения** — зоны строятся от подтвержденных экстремумов (пивотов), имеют **среднюю линию** и **счетчик касаний**.
5. **Визуализация «ордер-флоу»**:
* **Пузыри дельты** (зеленые/красные круги) — места повышенного покупательного/продажного давления, рассчитанные через безопасный **прокси-дельты**.
* **Плотности ликвидности** (ненавязчивые прямоугольные ленты) — скопления объема, которые нередко притягивают цену или удерживают ее и исчезают, когда «разъедаются» сильным движением.
Итог — **полная картинка момента**: среднее (VWAP), баланс дня (Opening Range), старшая сила (фильтр тренда), ближайшие уровни топлива/тормозов (зоны), текущие точки усилия (пузыри и плотности).
---
## Почему именно эти элементы
* **VWAP** показывает, где сосредоточена стоимость; цена либо вращается вокруг него, либо быстро уходит — идеальный ориентир скальпера.
* **Opening Range** фиксирует ранний аукцион — от его границ часто начинаются пробои, возвраты и ретесты.
* **EMA + ADX** отделяют тренд от «пилы», позволяя оставлять на графике только зоны по направлению старшего таймфрейма.
* **Зоны от пивотов** просты, объективны и быстры; средняя линия помогает подтверждать разворот, счетчик касаний переводит субъективность в цифры.
* **Пузыри и плотности** добавляют слой «усилия»: где именно возник толчок и где сконцентрирована ликвидность.
Комбинация **контекста + уровня + усилия** уменьшает двусмысленность и ускоряет принятие решения.
---
## Как это работает (простыми словами)
* **VWAP** каждый день стартует заново: сумма «типичной цены × объем» делится на суммарный объем.
* **Opening Range** — автоматический (кратный минутам вашего таймфрейма) или вручную заданный период; пока он формируется, фиксируются максимум и минимум.
* **Фильтр тренда**
* Две экспоненциальные средние задают направление.
* **ADX** (по желанию) добавляет «силу». Источник можно взять со старшего таймфрейма.
* **Зоны**
* Одновременно работает **две пары** пивотов (например 10-лево 10-право и 5-лево 5-право).
* От пивота строится зона **предложения** (от максимума) или **спроса** (от минимума). Глубина зоны = **коэффициент × Average True Range**; зона тянется вперед.
* Внутри рисуется **средняя линия** (по желанию).
* Режим **«только по тренду»** скрывает зоны против старшего направления.
* **Счетчик касаний** увеличивается, когда цена снова входит в зону; подпись показывает пару и количество касаний.
* **Пузыри**
* Используется безопасный **прокси-дельты** — измерение «напряжения» внутри свечи.
* Через **квантильный фильтр** выводятся только необычно сильные места: настраиваются окно и процент квантиля; размер кружка — сила, цвет: зеленый покупатели, красный продавцы.
* **Плотности**
* Крупные активности отмечаются **ненавязчивыми прямоугольниками** (глубина — доля Average True Range).
* Если плотность **пробивается** объемом выше среднего, она **исчезает** — часто это предвещает продолжение.
---
## Как пользоваться — практические схемы
> Рекомендация: крипто или фьючерсы, таймфрейм 1–5 минут. Для старшего фильтра удобно взять **1 час** или **15 минут**.
### 1) Скальп на откат по тренду
1. Включите **«только по тренду»**.
2. В восходящем тренде дождитесь отката в **зону спроса**, желательно рядом с **VWAP** или серединой **Opening Range**.
3. Подтверждение — **зеленые пузыри** у нижней границы зоны или свежая **плотность** под ценой.
4. Вход после закрытия свечи **выше средней линии** зоны.
5. Стоп-лосс: за нижнюю границу зоны или небольшой множитель Average True Range.
6. Цели: предыдущий максимум, верх Opening Range, фиксированные R-множители, либо VWAP.
Для нисходящего тренда зеркально: зоны предложения, красные пузыри и плотности над ценой.
### 2) Контрдвижение с «выбиванием ликвидности»
1. Нейтральный или контртрендовый режим.
2. Цена **выносит хвостом** границу зоны (или линию Opening Range) и **закрывается обратно внутри**.
3. Цвет пузыря часто меняется (поглощение).
4. Вход внутрь зоны; стоп — за хвост выбивания; цели: средняя линия, противоположная граница зоны или VWAP.
### 3) Пробой Opening Range + ретест
1. Дождитесь завершения диапазона.
2. Сильный пробой с крупным пузырем — признак намерения.
3. Ищите **ретест** в зоне по тренду рядом с линией диапазона и VWAP.
4. Торгуйте продолжение к следующей зоне.
### 4) Продолжение после «съеденной» плотности
1. Когда прямоугольник плотности **исчезает** на повышенном объеме, это значит, что ликвидность поглощена.
2. Торгуйте в сторону пробоя к ближайшей противоположной зоне.
---
## Настройки — краткая шпаргалка
**Core**
— Длина Average True Range (для размеров зон и плотностей).
— Включение VWAP и Opening Range.
— Длина Opening Range: автоматическая (кратная минутам ТФ) или ручная.
**Trend Filter**
— Режим: выкл., только средние, либо средние + ADX.
— Источник со старшего таймфрейма и его значение.
— Длины средних, длина ADX и порог силы.
— Показать/скрыть линий средних.
**Zones (две пары одновременно)**
— Пара A: лев/прав; Пара B: лев/прав.
— Глубина зоны × Average True Range, продление по барам.
— Средняя линия, режим **«только по тренду»**.
— Подписи со счетчиком касаний.
**Bubbles**
— Вкл./выкл., окно поиска и процент квантиля (чем выше процент — тем реже пузыри).
**Densities**
— Метрика: абсолютная прокси-дельты или чистый объем.
— Окно/квантиль, глубина × Average True Range, продление,
— Порог объединения (в Average True Range),
— Условие «разъедания» по объему,
— Средняя линия плотности (по желанию).
---
## Советы и риски
* Индикатор **не использует внешние потоки ордер-флоу**. Дельта — **прокси**, подходящая для TradingView; подбирайте квантили под инструмент и таймфрейм.
* Не торгуйте каждый пузырь. Склейте **контекст (тренд + VWAP + Opening Range)** с **уровнем (зона)** и **усилием (пузырь/плотность)**.
* Стоп-лосс — за границей зоны или по Average True Range. Риск на сделку задавайте заранее.
* Перед реальными деньгами протестируйте правила в стратегии.
* Разные рынки ведут себя по-разному; настройки из Биткоина могут не подойти малоликвидным альткоинам или акциям.
* Это не инвестиционная рекомендация. Скальпинг — высокий риск; проскальзывание и переизбыток сделок быстро наносят ущерб капиталу.
---
## Чем уникален PRO Scalper
* Две **одновременные** системы зон показывают и **крупную структуру**, и **точные локальные уровни**.
* Режим **«только по тренду»** чистит экран от лишних уровней и ускоряет решение.
* **Счетчики касаний** дают количественную опору.
* **Самодостаточные визуализации усилия** (пузыри и плотности) — без сторонних источников данных.
* Аккуратная цветовая схема: плотности — мягко, зоны — ясно; Opening Range — адаптивный.
Пусть он станет вашей «картой местности» для быстрых и дисциплинированных решений внутри дня.
Momentum Moving Averages | MisinkoMasterThe Momentum Moving Averages (MMA) indicator blends multiple moving averages into a single momentum-scoring framework, helping traders identify whether market conditions are favoring upside momentum or downside momentum.
By comparing faster, more adaptive moving averages (DEMA, TEMA, ALMA, HMA) against a baseline EMA, the MMA produces a cumulative score that reflects the prevailing strength and direction of the trend.
🔎 Methodology
Moving Averages Used
EMA (Exponential Moving Average) → Baseline reference.
DEMA (Double Exponential Moving Average) → Reacts faster than EMA.
TEMA (Triple Exponential Moving Average) → Even faster, reduces lag further.
ALMA (Arnaud Legoux Moving Average) → Smooth but adaptive, with adjustable σ and offset.
HMA (Hull Moving Average) → Very responsive, reduces lag, ideal for momentum shifts.
Scoring System
Each comparison is made against the EMA baseline:
If another MA is above EMA → +1 point.
If another MA is below EMA → -1 point.
The total score reflects overall momentum:
Positive score → Bullish bias.
Negative score → Bearish bias.
Trend Logic
Bullish Signal → When the score crosses above 0.1.
Bearish Signal → When the score crosses below -0.1.
Neutral or sideways trends are identified when the score remains between thresholds.
📈 Visualization
All five moving averages are plotted on the chart.
Colors adapt to the current score:
Cyan (Bullish bias) → Positive momentum.
Magenta (Bearish bias) → Negative momentum.
Overlapping fills between MAs highlight zones of convergence/divergence, making momentum shifts visually clear.
⚡ Features
Adjustable length parameter for all MAs.
Adjustable ALMA parameters (sigma and offset).
Cumulative momentum score system to filter false signals.
Works across all markets (crypto, forex, stocks, indices).
Overlay design for direct chart integration.
✅ Use Cases
Trend Confirmation → Ensure alignment with market momentum.
Momentum Shifts → Spot when faster MAs consistently outperform the baseline EMA.
Entry & Exit Filter → Avoid trades when the score is neutral or indecisive.
Divergence Visualizer → Filled zones make it easier to see when MAs begin separating or converging.
Low History Required → Unlike most For Loops, this script does not require that much history, making it less lagging and more responsive
⚠️ Limitations
Works best in trending conditions; performance decreases in sideways/choppy ranges.
Sensitivity of signals depends on chosen length and ALMA settings.
Should not be used as a standalone buy/sell system—combine with volume, structure, or higher timeframe analysis.
Tzotchev Trend Measure [EdgeTools]Are you still measuring trend strength with moving averages? Here is a better variant at scientific level:
Tzotchev Trend Measure: A Statistical Approach to Trend Following
The Tzotchev Trend Measure represents a sophisticated advancement in quantitative trend analysis, moving beyond traditional moving average-based indicators toward a statistically rigorous framework for measuring trend strength. This indicator implements the methodology developed by Tzotchev et al. (2015) in their seminal J.P. Morgan research paper "Designing robust trend-following system: Behind the scenes of trend-following," which introduced a probabilistic approach to trend measurement that has since become a cornerstone of institutional trading strategies.
Mathematical Foundation and Statistical Theory
The core innovation of the Tzotchev Trend Measure lies in its transformation of price momentum into a probability-based metric through the application of statistical hypothesis testing principles. The indicator employs the fundamental formula ST = 2 × Φ(√T × r̄T / σ̂T) - 1, where ST represents the trend strength score bounded between -1 and +1, Φ(x) denotes the normal cumulative distribution function, T represents the lookback period in trading days, r̄T is the average logarithmic return over the specified period, and σ̂T represents the estimated daily return volatility.
This formulation transforms what is essentially a t-statistic into a probabilistic trend measure, testing the null hypothesis that the mean return equals zero against the alternative hypothesis of non-zero mean return. The use of logarithmic returns rather than simple returns provides several statistical advantages, including symmetry properties where log(P₁/P₀) = -log(P₀/P₁), additivity characteristics that allow for proper compounding analysis, and improved validity of normal distribution assumptions that underpin the statistical framework.
The implementation utilizes the Abramowitz and Stegun (1964) approximation for the normal cumulative distribution function, achieving accuracy within ±1.5 × 10⁻⁷ for all input values. This approximation employs Horner's method for polynomial evaluation to ensure numerical stability, particularly important when processing large datasets or extreme market conditions.
Comparative Analysis with Traditional Trend Measurement Methods
The Tzotchev Trend Measure demonstrates significant theoretical and empirical advantages over conventional trend analysis techniques. Traditional moving average-based systems, including simple moving averages (SMA), exponential moving averages (EMA), and their derivatives such as MACD, suffer from several fundamental limitations that the Tzotchev methodology addresses systematically.
Moving average systems exhibit inherent lag bias, as documented by Kaufman (2013) in "Trading Systems and Methods," where he demonstrates that moving averages inevitably lag price movements by approximately half their period length. This lag creates delayed signal generation that reduces profitability in trending markets and increases false signal frequency during consolidation periods. In contrast, the Tzotchev measure eliminates lag bias by directly analyzing the statistical properties of return distributions rather than smoothing price levels.
The volatility normalization inherent in the Tzotchev formula addresses a critical weakness in traditional momentum indicators. As shown by Bollinger (2001) in "Bollinger on Bollinger Bands," momentum oscillators like RSI and Stochastic fail to account for changing volatility regimes, leading to inconsistent signal interpretation across different market conditions. The Tzotchev measure's incorporation of return volatility in the denominator ensures that trend strength assessments remain consistent regardless of the underlying volatility environment.
Empirical studies by Hurst, Ooi, and Pedersen (2013) in "Demystifying Managed Futures" demonstrate that traditional trend-following indicators suffer from significant drawdowns during whipsaw markets, with Sharpe ratios frequently below 0.5 during challenging periods. The authors attribute these poor performance characteristics to the binary nature of most trend signals and their inability to quantify signal confidence. The Tzotchev measure addresses this limitation by providing continuous probability-based outputs that allow for more sophisticated risk management and position sizing strategies.
The statistical foundation of the Tzotchev approach provides superior robustness compared to technical indicators that lack theoretical grounding. Fama and French (1988) in "Permanent and Temporary Components of Stock Prices" established that price movements contain both permanent and temporary components, with traditional moving averages unable to distinguish between these elements effectively. The Tzotchev methodology's hypothesis testing framework specifically tests for the presence of permanent trend components while filtering out temporary noise, providing a more theoretically sound approach to trend identification.
Research by Moskowitz, Ooi, and Pedersen (2012) in "Time Series Momentum in the Cross Section of Asset Returns" found that traditional momentum indicators exhibit significant variation in effectiveness across asset classes and time periods. Their study of multiple asset classes over decades revealed that simple price-based momentum measures often fail to capture persistent trends in fixed income and commodity markets. The Tzotchev measure's normalization by volatility and its probabilistic interpretation provide consistent performance across diverse asset classes, as demonstrated in the original J.P. Morgan research.
Comparative performance studies conducted by AQR Capital Management (Asness, Moskowitz, and Pedersen, 2013) in "Value and Momentum Everywhere" show that volatility-adjusted momentum measures significantly outperform traditional price momentum across international equity, bond, commodity, and currency markets. The study documents Sharpe ratio improvements of 0.2 to 0.4 when incorporating volatility normalization, consistent with the theoretical advantages of the Tzotchev approach.
The regime detection capabilities of the Tzotchev measure provide additional advantages over binary trend classification systems. Research by Ang and Bekaert (2002) in "Regime Switches in Interest Rates" demonstrates that financial markets exhibit distinct regime characteristics that traditional indicators fail to capture adequately. The Tzotchev measure's five-tier classification system (Strong Bull, Weak Bull, Neutral, Weak Bear, Strong Bear) provides more nuanced market state identification than simple trend/no-trend binary systems.
Statistical testing by Jegadeesh and Titman (2001) in "Profitability of Momentum Strategies" revealed that traditional momentum indicators suffer from significant parameter instability, with optimal lookback periods varying substantially across market conditions and asset classes. The Tzotchev measure's statistical framework provides more stable parameter selection through its grounding in hypothesis testing theory, reducing the need for frequent parameter optimization that can lead to overfitting.
Advanced Noise Filtering and Market Regime Detection
A significant enhancement over the original Tzotchev methodology is the incorporation of a multi-factor noise filtering system designed to reduce false signals during sideways market conditions. The filtering mechanism employs four distinct approaches: adaptive thresholding based on current market regime strength, volatility-based filtering utilizing ATR percentile analysis, trend strength confirmation through momentum alignment, and a comprehensive multi-factor approach that combines all methodologies.
The adaptive filtering system analyzes market microstructure through price change relative to average true range, calculates volatility percentiles over rolling windows, and assesses trend alignment across multiple timeframes using exponential moving averages of varying periods. This approach addresses one of the primary limitations identified in traditional trend-following systems, namely their tendency to generate excessive false signals during periods of low volatility or sideways price action.
The regime detection component classifies market conditions into five distinct categories: Strong Bull (ST > 0.3), Weak Bull (0.1 < ST ≤ 0.3), Neutral (-0.1 ≤ ST ≤ 0.1), Weak Bear (-0.3 ≤ ST < -0.1), and Strong Bear (ST < -0.3). This classification system provides traders with clear, quantitative definitions of market regimes that can inform position sizing, risk management, and strategy selection decisions.
Professional Implementation and Trading Applications
The indicator incorporates three distinct trading profiles designed to accommodate different investment approaches and risk tolerances. The Conservative profile employs longer lookback periods (63 days), higher signal thresholds (0.2), and reduced filter sensitivity (0.5) to minimize false signals and focus on major trend changes. The Balanced profile utilizes standard academic parameters with moderate settings across all dimensions. The Aggressive profile implements shorter lookback periods (14 days), lower signal thresholds (-0.1), and increased filter sensitivity (1.5) to capture shorter-term trend movements.
Signal generation occurs through threshold crossover analysis, where long signals are generated when the trend measure crosses above the specified threshold and short signals when it crosses below. The implementation includes sophisticated signal confirmation mechanisms that consider trend alignment across multiple timeframes and momentum strength percentiles to reduce the likelihood of false breakouts.
The alert system provides real-time notifications for trend threshold crossovers, strong regime changes, and signal generation events, with configurable frequency controls to prevent notification spam. Alert messages are standardized to ensure consistency across different market conditions and timeframes.
Performance Optimization and Computational Efficiency
The implementation incorporates several performance optimization features designed to handle large datasets efficiently. The maximum bars back parameter allows users to control historical calculation depth, with default settings optimized for most trading applications while providing flexibility for extended historical analysis. The system includes automatic performance monitoring that generates warnings when computational limits are approached.
Error handling mechanisms protect against division by zero conditions, infinite values, and other numerical instabilities that can occur during extreme market conditions. The finite value checking system ensures data integrity throughout the calculation process, with fallback mechanisms that maintain indicator functionality even when encountering corrupted or missing price data.
Timeframe validation provides warnings when the indicator is applied to unsuitable timeframes, as the Tzotchev methodology was specifically designed for daily and higher timeframe analysis. This validation helps prevent misapplication of the indicator in contexts where its statistical assumptions may not hold.
Visual Design and User Interface
The indicator features eight professional color schemes designed for different trading environments and user preferences. The EdgeTools theme provides an institutional blue and steel color palette suitable for professional trading environments. The Gold theme offers warm colors optimized for commodities trading. The Behavioral theme incorporates psychology-based color contrasts that align with behavioral finance principles. The Quant theme provides neutral colors suitable for analytical applications.
Additional specialized themes include Ocean, Fire, Matrix, and Arctic variations, each optimized for specific visual preferences and trading contexts. All color schemes include automatic dark and light mode optimization to ensure optimal readability across different chart backgrounds and trading platforms.
The information table provides real-time display of key metrics including current trend measure value, market regime classification, signal strength, Z-score, average returns, volatility measures, filter threshold levels, and filter effectiveness percentages. This comprehensive dashboard allows traders to monitor all relevant indicator components simultaneously.
Theoretical Implications and Research Context
The Tzotchev Trend Measure addresses several theoretical limitations inherent in traditional technical analysis approaches. Unlike moving average-based systems that rely on price level comparisons, this methodology grounds trend analysis in statistical hypothesis testing, providing a more robust theoretical foundation for trading decisions.
The probabilistic interpretation of trend strength offers significant advantages over binary trend classification systems. Rather than simply indicating whether a trend exists, the measure quantifies the statistical confidence level associated with the trend assessment, allowing for more nuanced risk management and position sizing decisions.
The incorporation of volatility normalization addresses the well-documented problem of volatility clustering in financial time series, ensuring that trend strength assessments remain consistent across different market volatility regimes. This normalization is particularly important for portfolio management applications where consistent risk metrics across different assets and time periods are essential.
Practical Applications and Trading Strategy Integration
The Tzotchev Trend Measure can be effectively integrated into various trading strategies and portfolio management frameworks. For trend-following strategies, the indicator provides clear entry and exit signals with quantified confidence levels. For mean reversion strategies, extreme readings can signal potential turning points. For portfolio allocation, the regime classification system can inform dynamic asset allocation decisions.
The indicator's statistical foundation makes it particularly suitable for quantitative trading strategies where systematic, rules-based approaches are preferred over discretionary decision-making. The standardized output range facilitates easy integration with position sizing algorithms and risk management systems.
Risk management applications benefit from the indicator's ability to quantify trend strength and provide early warning signals of potential trend changes. The multi-timeframe analysis capability allows for the construction of robust risk management frameworks that consider both short-term tactical and long-term strategic market conditions.
Implementation Guide and Parameter Configuration
The practical application of the Tzotchev Trend Measure requires careful parameter configuration to optimize performance for specific trading objectives and market conditions. This section provides comprehensive guidance for parameter selection and indicator customization.
Core Calculation Parameters
The Lookback Period parameter controls the statistical window used for trend calculation and represents the most critical setting for the indicator. Default values range from 14 to 63 trading days, with shorter periods (14-21 days) providing more sensitive trend detection suitable for short-term trading strategies, while longer periods (42-63 days) offer more stable trend identification appropriate for position trading and long-term investment strategies. The parameter directly influences the statistical significance of trend measurements, with longer periods requiring stronger underlying trends to generate significant signals but providing greater reliability in trend identification.
The Price Source parameter determines which price series is used for return calculations. The default close price provides standard trend analysis, while alternative selections such as high-low midpoint ((high + low) / 2) can reduce noise in volatile markets, and volume-weighted average price (VWAP) offers superior trend identification in institutional trading environments where volume concentration matters significantly.
The Signal Threshold parameter establishes the minimum trend strength required for signal generation, with values ranging from -0.5 to 0.5. Conservative threshold settings (0.2 to 0.3) reduce false signals but may miss early trend opportunities, while aggressive settings (-0.1 to 0.1) provide earlier signal generation at the cost of increased false positive rates. The optimal threshold depends on the trader's risk tolerance and the volatility characteristics of the traded instrument.
Trading Profile Configuration
The Trading Profile system provides pre-configured parameter sets optimized for different trading approaches. The Conservative profile employs a 63-day lookback period with a 0.2 signal threshold and 0.5 noise sensitivity, designed for long-term position traders seeking high-probability trend signals with minimal false positives. The Balanced profile uses a 21-day lookback with 0.05 signal threshold and 1.0 noise sensitivity, suitable for swing traders requiring moderate signal frequency with acceptable noise levels. The Aggressive profile implements a 14-day lookback with -0.1 signal threshold and 1.5 noise sensitivity, optimized for day traders and scalpers requiring frequent signal generation despite higher noise levels.
Advanced Noise Filtering System
The noise filtering mechanism addresses the challenge of false signals during sideways market conditions through four distinct methodologies. The Adaptive filter adjusts thresholds based on current trend strength, increasing sensitivity during strong trending periods while raising thresholds during consolidation phases. The Volatility-based filter utilizes Average True Range (ATR) percentile analysis to suppress signals during abnormally volatile conditions that typically generate false trend indications.
The Trend Strength filter requires alignment between multiple momentum indicators before confirming signals, reducing the probability of false breakouts from consolidation patterns. The Multi-factor approach combines all filtering methodologies using weighted scoring to provide the most robust noise reduction while maintaining signal responsiveness during genuine trend initiations.
The Noise Sensitivity parameter controls the aggressiveness of the filtering system, with lower values (0.5-1.0) providing conservative filtering suitable for volatile instruments, while higher values (1.5-2.0) allow more signals through but may increase false positive rates during choppy market conditions.
Visual Customization and Display Options
The Color Scheme parameter offers eight professional visualization options designed for different analytical preferences and market conditions. The EdgeTools scheme provides high contrast visualization optimized for trend strength differentiation, while the Gold scheme offers warm tones suitable for commodity analysis. The Behavioral scheme uses psychological color associations to enhance decision-making speed, and the Quant scheme provides neutral colors appropriate for quantitative analysis environments.
The Ocean, Fire, Matrix, and Arctic schemes offer additional aesthetic options while maintaining analytical functionality. Each scheme includes optimized colors for both light and dark chart backgrounds, ensuring visibility across different trading platform configurations.
The Show Glow Effects parameter enhances plot visibility through multiple layered lines with progressive transparency, particularly useful when analyzing multiple timeframes simultaneously or when working with dense price data that might obscure trend signals.
Performance Optimization Settings
The Maximum Bars Back parameter controls the historical data depth available for calculations, with values ranging from 5,000 to 50,000 bars. Higher values enable analysis of longer-term trend patterns but may impact indicator loading speed on slower systems or when applied to multiple instruments simultaneously. The optimal setting depends on the intended analysis timeframe and available computational resources.
The Calculate on Every Tick parameter determines whether the indicator updates with every price change or only at bar close. Real-time calculation provides immediate signal updates suitable for scalping and day trading strategies, while bar-close calculation reduces computational overhead and eliminates signal flickering during bar formation, preferred for swing trading and position management applications.
Alert System Configuration
The Alert Frequency parameter controls notification generation, with options for all signals, bar close only, or once per bar. High-frequency trading strategies benefit from all signals mode, while position traders typically prefer bar close alerts to avoid premature position entries based on intrabar fluctuations.
The alert system generates four distinct notification types: Long Signal alerts when the trend measure crosses above the positive signal threshold, Short Signal alerts for negative threshold crossings, Bull Regime alerts when entering strong bullish conditions, and Bear Regime alerts for strong bearish regime identification.
Table Display and Information Management
The information table provides real-time statistical metrics including current trend value, regime classification, signal status, and filter effectiveness measurements. The table position can be customized for optimal screen real estate utilization, and individual metrics can be toggled based on analytical requirements.
The Language parameter supports both English and German display options for international users, while maintaining consistent calculation methodology regardless of display language selection.
Risk Management Integration
Effective risk management integration requires coordination between the trend measure signals and position sizing algorithms. Strong trend readings (above 0.5 or below -0.5) support larger position sizes due to higher probability of trend continuation, while neutral readings (between -0.2 and 0.2) suggest reduced position sizes or range-trading strategies.
The regime classification system provides additional risk management context, with Strong Bull and Strong Bear regimes supporting trend-following strategies, while Neutral regimes indicate potential for mean reversion approaches. The filter effectiveness metric helps traders assess current market conditions and adjust strategy parameters accordingly.
Timeframe Considerations and Multi-Timeframe Analysis
The indicator's effectiveness varies across different timeframes, with higher timeframes (daily, weekly) providing more reliable trend identification but slower signal generation, while lower timeframes (hourly, 15-minute) offer faster signals with increased noise levels. Multi-timeframe analysis combining trend alignment across multiple periods significantly improves signal quality and reduces false positive rates.
For optimal results, traders should consider trend alignment between the primary trading timeframe and at least one higher timeframe before entering positions. Divergences between timeframes often signal potential trend reversals or consolidation periods requiring strategy adjustment.
Conclusion
The Tzotchev Trend Measure represents a significant advancement in technical analysis methodology, combining rigorous statistical foundations with practical trading applications. Its implementation of the J.P. Morgan research methodology provides institutional-quality trend analysis capabilities previously available only to sophisticated quantitative trading firms.
The comprehensive parameter configuration options enable customization for diverse trading styles and market conditions, while the advanced noise filtering and regime detection capabilities provide superior signal quality compared to traditional trend-following indicators. Proper parameter selection and understanding of the indicator's statistical foundation are essential for achieving optimal trading results and effective risk management.
References
Abramowitz, M. and Stegun, I.A. (1964). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Washington: National Bureau of Standards.
Ang, A. and Bekaert, G. (2002). Regime Switches in Interest Rates. Journal of Business and Economic Statistics, 20(2), 163-182.
Asness, C.S., Moskowitz, T.J., and Pedersen, L.H. (2013). Value and Momentum Everywhere. Journal of Finance, 68(3), 929-985.
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Fama, E.F. and French, K.R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Hurst, B., Ooi, Y.H., and Pedersen, L.H. (2013). Demystifying Managed Futures. Journal of Investment Management, 11(3), 42-58.
Jegadeesh, N. and Titman, S. (2001). Profitability of Momentum Strategies: An Evaluation of Alternative Explanations. Journal of Finance, 56(2), 699-720.
Kaufman, P.J. (2013). Trading Systems and Methods. 5th Edition. Hoboken: John Wiley & Sons.
Moskowitz, T.J., Ooi, Y.H., and Pedersen, L.H. (2012). Time Series Momentum. Journal of Financial Economics, 104(2), 228-250.
Tzotchev, D., Lo, A.W., and Hasanhodzic, J. (2015). Designing robust trend-following system: Behind the scenes of trend-following. J.P. Morgan Quantitative Research, Asset Management Division.
T-Virus Sentiment [hapharmonic]🧬 T-Virus Sentiment: Visualize the Market's DNA
Remember the iconic T-Virus vial from the first Resident Evil? That powerful, swirling helix of potential has always fascinated me. It sparked an idea: what if we could visualize the market's underlying health in a similar way? What if we could capture the "genetic code" of market sentiment and contain it within a dynamic, 3D indicator? This project is the result of that idea, brought to life with Pine Script.
The indicator's main goal is to measure the strength and direction of market sentiment by analyzing the "genetic code" of price action through a variety of trusted indicators. The result is displayed as a liquid level within a DNA helix, a bubble density representing buying pressure, and a T-Virus mascot that reflects the overall mood.
🧐 Core Concept: How It Works
The primary output of the indicator is the "Active %" gauge you see on the right side of the vial. This percentage represents the overall sentiment score, calculated as an average from 7 different technical analysis tools. Each tool is analyzed on every bar and assigned a score from 1 (strong bearish pressure) to 5 (strong bullish potential).
In this indicator, we re-imagine market dynamics through the lens of a viral outbreak. A strong bear market is like a virus taking hold, pulling all technical signals down into a state of weakness. Conversely, a powerful bull market is like an antiviral serum ; positive signals rise and spread toward the top of the vial, indicating that the system is being injected with strength.
This is not just another line on a chart. It's a comprehensive sentiment dashboard designed to give an immediate, at-a-glance understanding of the confluence between 7 classic technical indicators. The incredible 3D model of the vial itself was inspired by a design concept found here .
⚛️ The 4 Core Elements of T-Virus Sentiment
These four elements work in harmony to give a complete, multi-faceted picture of market sentiment. Each component tells a different part of the story.
The Virus Mascot: An instant emotional cue. This character provides the quickest possible read on the overall market mood, combining sentiment with volume pressure.
The Antiviral Serum Level: The main quantitative output. This is the liquid level in the DNA helix and the percentage gauge on the right, representing the average sentiment score from all 7 indicators.
Buy Pressure & Bubble Density: This visualizes volume flow. The density of bubbles represents the intensity of accumulation (buying) versus distribution (selling). It's the "power" behind the move.
The Signal Distribution: This shows the confluence (or dispersion) of sentiment. Are all signals bullish and clustered at the top, or are they scattered, indicating a conflicted market? The position of the indicator labels is crucial, as each is assigned to one of five distinct zones:
Base Bottom: The market is at its weakest. Signals here suggest strong bearish control and distribution.
Lower Zone: The market is still bearish, but signals may be showing early signs of accumulation or bottoming.
Neutral Core (Center): A state of balance or sideways consolidation. The market is waiting for a new direction.
Upper Zone: Bullish momentum is becoming clear. Signals are strengthening and showing bullish control.
Top Cap: The market is "heating up" with strong bullish sentiment, potentially nearing overbought conditions.
🐂🐻 The Virus Mascot: The At-a-Glance Indicator
This character acts as a shortcut to confirm market health. It combines the sentiment score with volume, preventing false confidence in a low-volume rally.
Its state is determined by a dual-check: the overall "Antiviral Serum Level" and the "Buy Pressure" must both be above 50%.
Green & Smiling: The 'all clear' signal. This means that not only is the overall technical sentiment bullish, but it's also being supported by real buying pressure. This is a sign of a healthy bull market.
Red & Angry: A warning sign. This appears if either the sentiment is weak, or a bullish sentiment is not being confirmed by buying volume. The latter could indicate a potential "bull trap" or an exhaustive move.
This mascot can be disabled from the settings page under "Virus Mascot Styling" if a cleaner look is preferred.
🫧 Bubble Density: Gauging Buy vs. Sell Pressure
The bubbles visualize the battle between buyers and sellers. There are two modes to control how this is calculated:
Mode 1: Visible Range (The 'Big Picture' View)
This default mode is best for getting a broad, contextual understanding of the current session. It dynamically analyzes the volume of every single candlestick currently visible on the screen to calculate the buy/sell pressure ratio. It answers the question: "Over the entire period I'm looking at, who is in control?" As you zoom in or out, the calculation adapts.
Mode 2: Custom Lookback (The 'Precision' View)
This mode is for traders who need to analyze short-term pressure. You can define a fixed number of recent bars to analyze, which is perfect for scalping or understanding the volume dynamics leading into a key level. It answers the question: "What is happening right now ?" In the example above, a lookback of 2 focuses only on the most recent action, clearly showing intense, immediate selling pressure (few bubbles) and a corresponding drop in the sentiment score to 29%.
ℹ️ Interactive Tooltips: Dive Deeper
We believe in transparency, not 'black box' indicators. This feature transforms the indicator from a visual aid into an active learning tool.
Simply hover the mouse over any indicator label (like EMA, OBV, etc.) to get a detailed tooltip. It will explain the specific data points and thresholds that signal met to be placed in its current zone. This helps build trust in the signals and allows users to fine-tune the indicator settings to better match their own trading style.
🎯 The Scoring Logic Breakdown
The "Antiviral Serum Level" gauge is the average score from 7 technical analysis tools. Each is graded on a 5-point scale (1=Strong Bearish to 5=Strong Bullish). Here’s a detailed, transparent look at how each "gene" is evaluated:
Relative Strength Index (RSI)
Measures momentum and overbought/oversold conditions.
Group 1 (Strong Bearish): RSI > 80 (Extreme Overbought)
Group 2 (Bearish): 70 < RSI ≤ 80 (Overbought)
Group 3 (Neutral): 30 ≤ RSI ≤ 70
Group 4 (Bullish): 20 ≤ RSI < 30 (Oversold)
Group 5 (Strong Bullish): RSI < 20 (Extreme Oversold)
Exponential Moving Averages (EMA)
Evaluates the trend's strength and structure based on the alignment of multiple EMAs (9, 21, 50, 100, 200, 250).
Group 1 (Strong Bearish): A perfect bearish sequence (9 < 21 < 50 < ...)
Group 2 (Bearish Transition): Early signs of a potential reversal (e.g., 9 > 21 but still below 50)
Group 3 (Neutral / Mixed): MAs are intertwined or showing a partial bullish sequence.
Group 4 (Bullish): A strong bullish sequence is forming (e.g., 9 > 21 > 50 > 100)
Group 5 (Strong Bullish): A perfect bullish sequence (9 > 21 > 50 > 100 > 200 > 250)
Moving Average Convergence Divergence (MACD)
Analyzes the relationship between two moving averages to gauge momentum.
Group 1 (Strong Bearish): MACD & Histogram are negative and momentum is falling.
Group 2 (Weakening Bearish): MACD is negative but the histogram is rising or positive.
Group 3 (Neutral / Crossover): A crossover event is occurring near the zero line.
Group 4 (Bullish): MACD & Histogram are positive.
Group 5 (Strong Bullish): MACD & Histogram are positive, rising strongly, and accelerating.
Average Directional Index (ADX)
Measures trend strength, not direction. The score is based on both ADX value and the dominance of DI+ vs DI-.
Group 1 (Bearish / No Trend): ADX < 20 and DI- is dominant.
Group 2 (Developing Bearish Trend): 20 ≤ ADX < 25 and DI- is dominant.
Group 3 (Neutral / Indecision): Trend is weak or DI+ and DI- are nearly equal.
Group 4 (Developing Bullish Trend): 25 ≤ ADX ≤ 40 and DI+ is dominant.
Group 5 (Strong Bullish Trend): ADX > 40 and DI+ is dominant.
Ichimoku Cloud (IKH)
A comprehensive indicator that defines support/resistance, momentum, and trend direction.
Group 1 (Strong Bearish): Price is below the Kumo, Tenkan < Kijun, and Chikou is below price.
Group 2 (Bearish): Price is inside or below the Kumo, with mixed secondary signals.
Group 3 (Neutral / Ranging): Price is inside the Kumo, often with a Tenkan/Kijun cross.
Group 4 (Bullish): Price is above the Kumo with strong primary signals.
Group 5 (Strong Bullish): All signals are aligned bullishly: price above Kumo, bullish Tenkan/Kijun cross, bullish future Kumo, and Chikou above price.
Bollinger Bands (BB)
Measures volatility and relative price levels.
Group 1 (Strong Bearish): Price is below the lower band.
Group 2 (Bearish Territory): Price is between the lower band and the basis line.
Group 3 (Neutral): Price is hovering around the basis line.
Group 4 (Bullish Territory): Price is between the basis line and the upper band.
Group 5 (Strong Bullish): Price is above the upper band.
On-Balance Volume (OBV)
Uses volume flow to predict price changes. The score is based on OBV's trend and its position relative to its moving average.
Group 1 (Strong Bearish): OBV is below its MA and falling.
Group 2 (Weakening Bearish): OBV is below its MA but showing signs of rising.
Group 3 (Neutral): OBV is very close to its MA.
Group 4 (Bullish): OBV is above its MA and rising.
Group 5 (Strong Bullish): OBV is above its MA, rising strongly, and showing signs of a volume spike.
🧭 How to Use the T-Virus Sentiment Indicator
IMPORTANT: This indicator is a sentiment dashboard , not a direct buy/sell signal generator. Its strength lies in showing confluence and providing a quick, holistic view of the market's technical health.
Confirmation Tool: Use the "Active %" gauge to confirm a trade setup from your primary strategy. For example, if you see a bullish chart pattern, a high and rising sentiment score can add confidence to your trade.
Momentum & Trend Gauge: A consistently high score (e.g., > 75%) suggests strong, established bullish momentum. A consistently low score (< 25%) suggests strong bearish control. A score hovering around 50% often indicates a ranging or indecisive market.
Divergence & Warning System: Pay attention to divergences. If the price is making new highs but the sentiment score is failing to follow or is actively decreasing, it could be an early warning sign that the underlying momentum is weakening.
⚙️ Settings & Customization
The indicator is highly customizable to fit any trading style.
Position & Anchor: Control where the vial appears on the chart.
Styling (Vial, Helix, etc.): Nearly every visual element can be color-customized.
Signals: This is where the real power is. All underlying indicator parameters (RSI length, MACD settings, etc.) can be fine-tuned to match a personal strategy. The text labels can also be disabled if the chart feels cluttered.
Enjoy visualizing the market's DNA with the T-Virus Sentiment indicator
Dr Avinash Talele momentum indicaterTrend and Volatility Metrics
EMA10, EMA20, EMA50:
Show the percentage distance of the current price from the 10, 20, and 50-period Exponential Moving Averages.
Positive values indicate the price is above the moving average (bullish momentum).
Negative values indicate the price is below the moving average (bearish or corrective phase).
Use: Helps traders spot if a stock is extended or pulling back to support.
RVol (Relative Volume):
Compares current volume to the 20-day average.
Positive values mean higher-than-average trading activity (potential institutional interest).
Negative values mean lower activity (less conviction).
Use: High RVol often precedes strong moves.
ADR (Average Daily Range):
Shows the average daily price movement as a percentage.
Use: Higher ADR = more volatility = more trading opportunities.
50D Avg. Vol & 50D Avg. Vol ₹:
The 50-day average volume (in millions) and value traded (in crores).
Use: Confirms liquidity and suitability for larger trades.
ROC (Rate of Change) Section
1W, 1M, 3M, 6M, 12M:
Show the percentage price change over the last 1 week, 1 month, 3 months, 6 months, and 12 months.
Positive values (green) = uptrend, Negative values (red) = downtrend.
Use: Quickly see if the stock is gaining or losing momentum over different timeframes.
Momentum Section
1M, 3M, 6M:
Show the percentage gain from the lowest price in the last 1, 3, and 6 months.
Use: Measures how much the stock has bounced from recent lows, helping find strong rebounds or new leaders.
52-Week High/Low Section
From 52WH / From 52WL:
Show how far the current price is from its 52-week high and low, as a percentage.
Closer to 52WH = strong uptrend; Closer to 52WL = possible value or turnaround setup.
Use: Helps traders identify stocks breaking out to new highs or rebounding off lows.
U/D Ratio
U/D Ratio:
The ratio of up-volume to down-volume over the last 50 days.
Above 1 = more buying volume (bullish), Below 1 = more selling volume (bearish).
Use: Confirms accumulation or distribution.
How This Table Helps Analysts and Traders
Instant Trend Assessment:
With EMA distances and ROC, analysts can instantly see if the stock is trending, consolidating, or reversing.
Momentum Confirmation:
ROC and Momentum sections highlight stocks with strong recent moves, ideal for momentum and breakout traders.
Liquidity and Volatility Check:
Volume and ADR ensure the stock is tradable and has enough price movement to justify a trade.
Relative Positioning:
52-week high/low stats show whether the stock is near breakout levels or potential reversal zones.
Volume Confirmation:
RVol and U/D ratio help confirm if moves are backed by real buying/selling interest.
Actionable Insights:
By combining these metrics, traders can filter for stocks with strong trends, robust momentum, and institutional backing—ideal for swing, position, or even intraday trading.
SL - 4 EMAs, 2 SMAs & Crossover SignalsThis TradingView Pine Script code is built for day traders, especially those trading crypto on a 1‑hour chart. In simple words, the script does the following:
Calculates Moving Averages:
It computes four exponential moving averages (EMAs) and two simple moving averages (SMAs) based on the closing price (or any price you select). Each moving average uses a different time period that you can adjust.
Plots Them on Your Chart:
The EMAs and SMAs are drawn on your chart in different colors and line thicknesses. This helps you quickly see the short-term and long-term trends.
Generates Buy and Sell Signals:
Buy Signal: When the fastest EMA (for example, a 10-period EMA) crosses above a slightly slower EMA (like a 21-period EMA) and the four EMAs are in a bullish order (meaning the fastest is above the next ones), the script will show a "BUY" label on the chart.
Sell Signal: When the fastest EMA crosses below the second fastest EMA and the four EMAs are lined up in a bearish order (the fastest is below the others), it displays a "SELL" label.
In essence, the code is designed to help you spot potential entry and exit points based on the relationships between multiple moving averages, which work as trend indicators. This makes it easier to decide when to trade on your 1‑hour crypto chart.
TTM Squeeze Momentum MTF [Cometreon]TTM Squeeze Momentum MTF combines the core logic of both the Squeeze Momentum by LazyBear and the TTM Squeeze by John Carter into a single, unified indicator. It offers a complete system to analyze the phase, direction, and strength of market movements.
Unlike the original versions, this indicator allows you to choose how to calculate the trend, select from 15 different types of moving averages, customize every parameter, and adapt the visual style to your trading preferences.
If you are looking for a powerful, flexible and highly configurable tool, this is the perfect choice for you.
🔷 New Features and Improvements
🟩 Unified System: Trend Detection + Visual Style
You can decide which logic to use for the trend via the "Show TTM Squeeze Trend" input:
✅ Enabled → Trend calculated using TTM Squeeze
❌ Disabled → Trend based on Squeeze Momentum
You can also customize the visual style of the indicator:
✅ Enable "Show Histogram" for a visual mode using Histogram, Area, or Column
❌ Disable it to display the classic LazyBear-style line
Everything updates automatically and dynamically based on your selection.
🟩 Full Customization
Every base parameter of the original indicator is now fully configurable: lengths, sources, moving average types, and more.
You can finally adapt the squeeze logic to your strategy — not the other way around.
🟩 Multi-MA Engine
Choose from 15 different Moving Averages for each part of the calculation:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
RMA (Smoothed Moving Average)
HMA (Hull Moving Average)
JMA (Jurik Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
LSMA (Least Squares Moving Average)
VWMA (Volume-Weighted Moving Average)
SMMA (Smoothed Moving Average)
KAMA (Kaufman’s Adaptive Moving Average)
ALMA (Arnaud Legoux Moving Average)
FRAMA (Fractal Adaptive Moving Average)
VIDYA (Variable Index Dynamic Average)
🟩 Dynamic Signal Line
Apply a moving average to the momentum for real-time cross signals, with full control over its length and type.
🟩 Multi-Timeframe & Multi-Ticker Support
You're no longer limited to the chart's current timeframe or ticker. Apply the squeeze to any symbol or timeframe without repainting.
🔷 Technical Details and Customizable Inputs
This indicator offers a fully modular structure with configurable parameters for every component:
1️⃣ Squeeze Momentum Settings – Choose the source, length, and type of moving average used to calculate the base momentum.
2️⃣ Trend Mode Selector – Toggle "Show TTM Squeeze Trend" to select the trend logic displayed on the chart:
✅ Enabled – Shows the trend based on TTM Squeeze (Bollinger Bands inside/outside Keltner Channel)
❌ Disabled – Displays the trend based on Squeeze Momentum logic
🔁 The moving average type for the Keltner Channel is handled automatically, so you don't need to select it manually, even if the custom input is disabled.
3️⃣ Signal Line – Toggle the Signal Line on the Squeeze Momentum. Select its length and MA type to generate visual cross signals.
4️⃣ Bollinger Bands – Configure the length, multiplier, source, and MA type used in the bands.
5️⃣ Keltner Channel – Adjust the length, multiplier, source, and MA type. You can also enable or disable the True Range option.
6️⃣ Advanced MA Parameters – Customize the parameters for advanced MAs (JMA, ALMA, FRAMA, VIDYA), including Phase, Power, Offset, Sigma, and Shift values.
7️⃣ Ticker & Input Source – Select the ticker and manage inputs for alternative chart types like Renko, Kagi, Line Break, and Point & Figure.
8️⃣ Style Settings – Choose how the squeeze is displayed:
Enable "Show Histogram" for Histogram, Area, or Column style
Disable it to show the classic LazyBear-style line
Use Reverse Color to invert line colors
Toggle Show Label to highlight Signal Line cross signals
Customize trend colors to suit your preferences
9️⃣ Multi-Timeframe Options - Timeframe – Use the squeeze on higher timeframes for stronger confirmation
🔟 Wait for Timeframe Closes -
✅ Enabled – Prevents multiple signals within the same candle
❌ Disabled – Displays the indicator smoothly without delay
🔧 Default Settings Reference
To replicate the default settings of the original indicators as they appear when first applied to the chart, use the following configurations:
🟩 TTM Squeeze (John Carter Style)
Squeeze
Length: 20
MA Type: SMA
Show TTM Squeeze Trend: Enabled
Bollinger Bands
Length: 20
Multiplier: 2.0
MA Type: SMA
Keltner Channel
Length: 20
Multiplier: 1.0
Use True Range: ON
MA Type: EMA
Style
Show Histogram: Enabled
Reverse Color: Enabled
🟩 Squeeze Momentum (LazyBear Style)
Squeeze
Length: 10
MA Type: SMA
Show TTM Squeeze Trend: Disabled
Bollinger Bands
Length: 20
Multiplier: 1.5
MA Type: SMA
Keltner Channel
Length: 10
Multiplier: 1.5
Use True Range: ON
MA Type: SMA
Style
Show Histogram: Disabled
Reverse Color: Disabled
⚠️ These values are intended as a starting point. The Cometreon indicator lets you fully customize every input to fit your trading style.
🔷 How to Use Squeeze Momentum Pro
🔍 Identifying Trends
Squeeze Momentum Pro supports two different methods for identifying the trend visually, each based on a distinct logic:
Squeeze Momentum Trend (LazyBear-style):
Displays 3 states based on the position of the Bollinger Bands relative to the Keltner Channel:
🔵 Blue = No Squeeze (BB outside KC and KC outside BB)
⚪️ White = Squeeze Active (BB fully inside KC)
⚫️ Gray = Neutral state (none of the above)
TTM Squeeze Trend (John Carter-style):
Calculates the difference in width between the Bollinger Bands and the Keltner Channel:
🟩 Green = BB width is greater than KC → potential expansion phase
🟥 Red = BB are tighter than KC → possible compression or pre-breakout
📈 Interpreting Signals
Depending on the active configuration, the indicator can provide various signals, including:
Trend color → Reflects the current compression/expansion state (based on selected mode)
Momentum value (above or below 0) → May indicate directional pressure
Signal Line cross → Can highlight momentum shifts
Color change in the momentum → May suggest a potential trend reversal
🛠 Integration with Other Tools
Squeeze Momentum Pro works well alongside other indicators to strengthen market context:
✅ Volume Profile / OBV – Helps confirm accumulation or distribution during squeezes
✅ RSI – Useful to detect divergence between momentum and price
✅ Moving Averages – Ideal for defining primary trend direction and filtering signals
☄️ If you find this indicator useful, leave a Boost to support its development!
Every piece of feedback helps improve the tool and deliver an even better trading experience.
🔥 Share your ideas or feature requests in the comments!
Combo Gama Exposure + EMA + SMA 1.0Gamma Exposure (GEX) for the CBOE Volatility Index ( TVC:VIX ) is an estimate of how much option sellers need to hedge for every 1% change in the underlying asset's price. It's also known as Gamma Levels.
How is GEX calculated?
GEX is calculated based on a 1% move of the underlying security
It's calculated and updated throughout the day
It's based on market positioning and open interest
These regions are important because they show the regions where players can act more aggressively to defend their positions. When inserting the indicator on the chart, a popup will open requesting the GEX levels (Put wall, Vix Call Wall 0DTE, etc.)
In addition, 3 moving averages will be inserted into the chart. A 9-period exponential moving average, a 20-period arithmetic moving average, and a 200-period arithmetic moving average. These moving averages aim to indicate the possible trend of the asset, where pullbacks in these averages can signal a possible entry in favor of the trend.
[blackcat] L1 Small Wave Operation L1 Small Wave Operation
Overview
Are you looking to catch those elusive small waves in the market? Look no further than " L1 Small Wave Operation." This script offers a unique way to identify potential buying opportunities by analyzing price movements, volume changes, and trend directions. With customizable inputs and clear visual indicators, it’s designed to help traders spot favorable entry points with precision.
Features
Dynamic Signal Identification: Automatically detects two types of buy signals labeled "S" and "B."
Adaptable Parameters: Allows users to adjust low period, high period, EMA periods, SMA period, and various threshold values to fine-tune the strategy.
Visual Clarity: Plots K and D lines along with four distinct threshold levels for easy visualization.
Condition-Based Signals: Uses multiple conditions including volume increases, price actions, and crossover events to confirm signals.
How It Works
Calculate Percent Range: Determines where the current closing price lies within the recent low and high range.
Compute Moving Averages: Calculates Exponential Moving Average (EMA) and Simple Moving Average (SMA) of the percent range.
Define Conditions: Checks for bullish or strong bullish patterns, uptrends, and specific crossover events between K and D lines.
Generate Signals: Marks potential buying opportunities when predetermined conditions are met.
How To Use
Add this script to your TradingView chart.
Adjust the input parameters according to your preferred settings.
Monitor the plotted lines and look for "S" and "B" labels indicating buy signals.
Consider incorporating these signals into a broader trading strategy that includes risk management techniques.
What Makes It Special
Flexibility: Users can easily modify parameters to adapt the script to different markets or personal preferences.
Automation: Saves time by automatically scanning for trade setups based on predefined rules.
Comprehensive Analysis: Combines multiple factors like volume, price action, and moving averages to provide reliable signals.
Limitations
Past performance does not guarantee future results.
Market conditions can vary, affecting signal reliability.
Not suitable for very short-term trades without additional refinements.
Notes
Always perform backtesting on historical data before implementing live trades.
Understand the underlying logic of the script to avoid misinterpretation of signals.
Regularly review and adjust parameters based on changing market dynamics.
DAILY Supertrend + EMA Crossover with RSI FilterThis strategy is a technical trading approach that combines multiple indicators—Supertrend, Exponential Moving Averages (EMAs), and the Relative Strength Index (RSI)—to identify and manage trades.
Core Components:
1. Exponential Moving Averages (EMAs):
Two EMAs, one with a shorter period (fast) and one with a longer period (slow), are calculated. The idea is to spot when the faster EMA crosses above or below the slower EMA. A fast EMA crossing above the slow EMA often suggests upward momentum, while crossing below suggests downward momentum.
2. Supertrend Indicator:
The Supertrend uses Average True Range (ATR) to establish dynamic support and resistance lines. These lines shift above or below price depending on the prevailing trend. When price is above the Supertrend line, the trend is considered bullish; when below, it’s considered bearish. This helps ensure that the strategy trades only in the direction of the overall trend rather than against it.
3. RSI Filter:
The RSI measures momentum. It helps avoid buying into markets that are already overbought or selling into markets that are oversold. For example, when going long (buying), the strategy only proceeds if the RSI is not too high, and when going short (selling), it only proceeds if the RSI is not too low. This filter is meant to improve the quality of the trades by reducing the chance of entering right before a reversal.
4. Time Filters:
The strategy only triggers entries during user-specified date and time ranges. This is useful if one wants to limit trading activity to certain trading sessions or periods with higher market liquidity.
5. Risk Management via ATR-based Stops and Targets:
Both stop loss and take profit levels are set as multiples of the ATR. ATR measures volatility, so when volatility is higher, both stops and profit targets adjust to give the trade more breathing room. Conversely, when volatility is low, stops and targets tighten. This dynamic approach helps maintain consistent risk management regardless of market conditions.
Overall Logic Flow:
- First, the market conditions are analyzed through EMAs, Supertrend, and RSI.
- When a buy (long) condition is met—meaning the fast EMA crosses above the slow EMA, the trend is bullish according to Supertrend, and RSI is below the specified “overbought” threshold—the strategy initiates or adds to a long position.
- Similarly, when a sell (short) condition is met—meaning the fast EMA crosses below the slow EMA, the trend is bearish, and RSI is above the specified “oversold” threshold—it initiates or adds to a short position.
- Each position is protected by an automatically calculated stop loss and a take profit level based on ATR multiples.
Intended Result:
By blending trend detection, momentum filtering, and volatility-adjusted risk management, the strategy aims to capture moves in the primary trend direction while avoiding entries at excessively stretched prices. Allowing multiple entries can potentially amplify gains in strong trends but also increases exposure, which traders should consider in their risk management approach.
In essence, this strategy tries to ride established trends as indicated by the Supertrend and EMAs, filter out poor-quality entries using RSI, and dynamically manage trade risk through ATR-based stops and targets.
WhalenatorThis custom TradingView indicator combines multiple analytic techniques to help identify potential market trends, areas of support and resistance, and zones of heightened trading activity. It incorporates a SuperTrend-like line based on ATR, Keltner Channels for volatility-based price envelopes, and dynamic order blocks derived from significant volume and pivot points. Additionally, it highlights “whale” activities—periods of exceptionally large volume—along with an estimated volume profile level and approximate bid/ask volume distribution. Together, these features aim to offer traders a more comprehensive view of price structure, volatility, and institutional participation.
This custom TradingView indicator integrates multiple trading concepts into a single, visually descriptive tool. Its primary goal is to help traders identify directional bias, volatility levels, significant volume events, and potential support/resistance zones on a price chart. Below are the main components and their functionalities:
SuperTrend-Like Line (Trend Bias):
At the core of the indicator is a trend-following line inspired by the SuperTrend concept, which uses Average True Range (ATR) to adaptively set trailing stop levels. By comparing price to these levels, the line attempts to indicate when the market is in an uptrend (price above the line) or a downtrend (price below the line). The shifting levels can provide a dynamic sense of direction and help traders stay with the predominant trend until it shifts.
Keltner Channels (Volatility and Range):
Keltner Channels, based on an exponential moving average and Average True Range, form volatility-based envelopes around price. They help traders visualize whether price is extended (touching or moving outside the upper/lower band) or trading within a stable range. This can be useful in identifying low-volatility consolidations and high-volatility breakouts.
Dynamic Order Blocks (Approximations of Supply/Demand Zones):
By detecting pivot highs and lows under conditions of significant volume, the indicator approximates "order blocks." Order blocks are areas where institutional buying or selling may have occurred, potentially acting as future support or resistance zones. Although these approximations are not perfect, they offer a visual cue to areas on the chart where price might react strongly if revisited.
Volume Profile Proxy and Whale Detection:
The indicator highlights price levels associated with recent maximum volume activity, providing a rough "volume profile" reference. Such levels often become key points of price interaction.
"Whale" detection logic attempts to identify bars where exceptionally large volume occurs (beyond a defined threshold). By tracking these "whale bars," traders can infer where heavy participation—often from large traders or institutions—may influence market direction or create zones of interest.
Approximate Bid/Ask Volume and Dollar Volume Tracking:
The script estimates whether volume within each bar leans more towards the bid or the ask side, aiming to understand which participant (buyers or sellers) might have been more aggressive. Additionally, it calculates dollar volume (close price multiplied by volume) and provides an average to gauge the relative participation strength over time.
Labeling and Visual Aids:
Dynamic labels display Whale Frequency (the ratio of bars with exceptionally large volume), average dollar volume, and approximate ask/bid volume metrics. This gives traders at-a-glance insights into current market conditions, participation, and sentiment.
Strengths:
Multifaceted Analysis:
By combining trend, volatility, volume, and order block logic in one place, the indicator saves chart space and simplifies the analytical process. Traders gain a holistic view without flipping between multiple separate tools.
Adaptable to Market Conditions:
The use of ATR and Keltner Channels adapts to changing volatility conditions. The SuperTrend-like line helps keep traders aligned with the prevailing trend, avoiding constant whipsaws in choppy markets.
Volume-Based Insights:
Integrating whale detection and a crude volume profile proxy helps traders understand where large players might be interacting. This perspective can highlight critical levels that might not be evident from price action alone.
Convenient Visual Cues and Labels:
The indicator provides quick reference points and textual information about the underlying volume dynamics, making decision-making potentially faster and more informed.
Weaknesses:
Heuristic and Approximate Nature:
Many of the indicator’s features, like the "order blocks," "whale detection," and the approximate bid/ask volume, rely on heuristics and assumptions that may not always be accurate. Without actual Level II data or true volume profiles, the insights are best considered as supplementary, not definitive signals.
Lagging Components:
Indicators that rely on past data, like ATR-based trends or moving averages for Keltner Channels, inherently lag behind price. This can cause delayed signals, particularly in fast-moving markets, potentially missing some early opportunities or late in confirming market reversals.
No Guaranteed Predictive Power:
As with any technical tool, it does not forecast the future with certainty. Strong volume at a certain level or a bullish SuperTrend reading does not guarantee price will continue in that direction. Market conditions can change unexpectedly, and false signals will occur.
Complexity and Overreliance Risk:
With multiple signals combined, there’s a risk of information overload. Traders might feel compelled to rely too heavily on this one tool. Without complementary analysis (fundamentals, news, or additional technical confirmation), overreliance on the indicator could lead to misguided trades.
Conclusion:
This integrated indicator offers a comprehensive visual guide to market structure, volatility, and activity. Its strength lies in providing a multi-dimensional viewpoint in a single tool. However, traders should remain aware of its approximations, inherent lags, and the potential for conflicting signals. Sound risk management, position sizing, and the use of complementary analysis methods remain essential for trading success.
Risks Associated with Trading:
No indicator can guarantee profitable trades or accurately predict future price movements. Market conditions are inherently unpredictable, and reliance on any single tool or combination of tools carries the risk of financial loss. Traders should practice sound risk management, including the use of stop losses and position sizing, and should not trade with funds they cannot afford to lose. Ultimately, decisions should be guided by a thorough trading plan and possibly supplemented with other forms of market analysis or professional advice.
Risks and Important Considerations:
• Not a Standalone Tool:
• This indicator should not be used in isolation. It is essential to incorporate additional technical analysis tools, fundamental analysis, and market context when making trading decisions.
• Relying solely on this indicator may lead to incomplete assessments of market conditions.
• Market Volatility and False Signals:
• Financial markets can be highly volatile, and indicators based on historical data may not accurately predict future movements.
• The indicator may produce false signals due to sudden market changes, low liquidity, or atypical trading activity.
• Risk Management:
• Always employ robust risk management strategies, including setting stop-loss orders, diversifying your portfolio, and not over-leveraging positions.
• Understand that no indicator guarantees success, and losses are a natural part of trading.
• Emotional Discipline:
• Avoid making impulsive decisions based on indicator signals alone.
• Emotional trading can lead to significant financial losses; maintain discipline and adhere to a well-thought-out trading plan.
• Continuous Learning and Adaptation:
• Stay informed about market news, economic indicators, and global events that may impact trading conditions.
• Continuously evaluate and adjust your trading strategies as market dynamics evolve.
• Consultation with Professionals:
• Consider seeking advice from financial advisors or professional traders to understand better how this indicator can fit into your overall trading strategy.
• Professional guidance can provide personalized insights based on your financial goals and risk tolerance.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research and consult with a licensed financial professional before making any trading decisions.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data and possibly paper trading before applying them in live trading scenarios.
Enhanced Buy/Sell Pressure, Volume, and Trend Bar analysisEnhanced Buy/Sell Pressure, Volume, and Trend Bar Analysis Indicator
Overview
This indicator is designed to help traders identify buy and sell pressure, volume changes, and overall trend direction in the market. It combines multiple concepts like price action, volume, and trend analysis, candlestick anaysis to provide a comprehensive view of market dynamics. The visual elements are intuitive, making it suitable for traders at different levels. This indicator works together with Enhanced Pressure MTF Screener which is a screener based of this indicator to make it easier to see Bullish/Bearish pressures and trend across multiple timeframes.
Image below: is the Enhanced Buy/Sell Pressure, Volume, and Trend Bar Analysis with the Enhanced Pressure MTF Screener indicator both active together.
Key Features
1.Buy/Sell Pressure Identification
Buy Pressure: Calculated based on price movement where the close price is higher than the opening price.
Sell Pressure: Calculated when the closing price is equal to or lower than the opening price.These pressures help you understand whether buyers or sellers are more dominant for each bar.
2.Volume Analysis
Normalized Volume: Volume data is normalized, making it easier to compare volume levels over different periods.
Volume Histogram: The volume is also presented as a histogram for easy visualization, showing whether the current volume is higher or lower compared to the average.
3.Simplified Coloring Option
You can choose to simplify the coloring of bars to reflect the dominant pressure: green for bullish pressure and red for bearish pressure. This makes it visually easier to identify who is in control. When simplified coloring is disabled, the bars' colors will represent the combined effect of buy and sell pressure.
4.Heikin-Ashi Candles for Pressure Calculation
The indicator includes an option to use Heikin-Ashi candles instead of traditional candles to calculate buy and sell pressure. Heikin-Ashi candles are known for smoothing out price action and providing a clearer trend representation.
5.Trend Background Coloring
This feature uses exponential moving averages (EMAs) to determine the trend:
Short-Term EMA vs. Long-Term EMA: When the short-term EMA is above the long-term EMA, the trend is considered bullish, and vice versa.
The background color changes based on the identified trend: green for an uptrend and red for a downtrend. This feature helps visualize the overall market direction at a glance.
6.Signals for Key Price Actions
The indicator plots various symbols to signal important price movements:
Bullish Close (▲): Indicates a strong upward movement where the close price crosses above the open.
Bearish Close (▼): Indicates a downward movement where the close price falls below the open.
Higher High (•): Highlights new highs compared to previous bars, useful for confirming an uptrend.
Lower Low (•): Highlights lower lows compared to previous bars, which can indicate a downtrend or bearish pressure.
Calculations Explained
1.Buy and Sell Pressure Calculation
The buy pressure is determined by the price range (high - low) if the closing price is above the opening price, indicating an increase in value.
The sell pressure is similarly calculated when the closing price is equal to or below the opening price.
The indicator uses the Average True Range (ATR) for normalization. Normalizing helps you compare pressure across different periods, regardless of market volatility.
2.Volume Normalization
Volume Normalization: To make volume comparable across different periods, the indicator normalizes it using the Simple Moving Average (SMA) of volume over a user-defined length.
Volume Histogram: The histogram provides a clear representation of volume changes compared to the average, making it easier to spot unusual activity that may indicate market shifts.
3.Combined Pressure Calculation
The indicator calculates a combined pressure value by subtracting sell pressure from buy pressure.
When combined pressure is positive, buying is dominant, and when negative, selling is dominant. This helps in visually understanding the ongoing momentum.
4.Trend Calculation
The indicator uses two EMAs to determine the trend:
Short-Term EMA (default 14-period) to capture recent price movements.
Long-Term EMA (default 50-period) to provide a broader trend perspective.
By comparing these EMAs on a higher timeframe, the indicator can identify whether the trend is up or down, making it easier for traders to align their trades with the larger market movement.
Inputs and Customization
The indicator provides several options for customization, allowing you to adjust it to your preferences:
SMA Length: Determines the lookback period for moving averages and volume normalization. A longer length provides more smoothing, whereas a shorter length makes the indicator more responsive.
Buy/Sell/Volume Colors: Customize the colors used to represent buying, selling, and volume to suit your preferences.
Heikin Ashi Option: Toggle between using Heikin Ashi or traditional OHLC (Open-High-Low-Close) candles for pressure calculations.
Trend Timeframe and EMA Periods: You can choose different timeframes and EMA periods for trend analysis to suit your trading strategy.
How to Use This Indicator
Identifying Market Momentum: Use the buy/sell pressure columns to see which side (buyers or sellers) is in control. Positive pressure combined with green color indicates strong buying, while red indicates selling.
Volume Confirmation: Check the volume area plot and histogram. High volume coupled with strong pressure is a sign of conviction, meaning the current move has backing from market participants.
Trend Identification: The trend background color helps identify the overall trend direction. Trade in the direction of the trend (e.g., take long positions during a green background).
Signal Indicators: The plotted symbols like "Bullish Close" and "Bearish Close" provide visual signals of key price actions, useful for timing entry or exit points.
Practical use Example
Scenario: The market is consolidating, and you see alternating green and red bars.
Action: Wait for a consistent sequence of green bars (buy pressure) along with a green background (uptrend) to consider going long, although you can go long without having a green background, the background adds confirmation layer.
Scenario: The market has several bearish closes (red ▼ symbols) accompanied by increasing volume.
Action: This could indicate strong selling pressure. If the background also turns red, it might be a good time to exit long positions or consider shorting.
Higher timeframe pressure and volume: Another way to use the indicator is to check buy/sell volume and pressure of the higher timeframe say weekly or daily or any timeframe you consider higher, once you’ve identified or feel confident in which direction the bar is going along with the full picture of trend, you can go to the lower timeframe and wait for it to sync with the higher timeframe to consider a long or a short. It is also easier to see when markets sync up by also applying the Enhanced Pressure MTF Screener which works in companion to this indicator.
Visual Cues and Interpretation
Combined Pressure Plot: The green and red column plot at the bottom of the chart represents the dominance between buying and selling. Tall green bars signify strong buying, while tall red bars indicate selling dominance.
Trend Background: Helps visualize the overall direction without manually drawing trend lines. When the background turns green, it generally indicates that the shorter-term moving average has crossed above the longer-term average—a sign of a bullish trend.
To Summarize shortly
The Enhanced Buy/Sell Pressure, Volume, and Trend Bar Analysis Indicator is an advanced but simple tool designed to help traders visually understand market dynamics. It combines different aspects of market analysis of candle pressure from buyers and sellers, volume confirmation, and trend identification into a single view, which can assist both new and experienced traders in making informed trading decisions.
This indicator:
Saves time by simplifying market analysis.
Provides clear visual cues for buy/sell pressure, volume, and trend.
Offers customizable settings to suit individual trading styles.
Always, I am happy to share my creations with you all for free. If you guys have cool ideas you would like to share, or suggestions for improvements the comment is below and I hope this overview gave an idea of how to use the indicator :D
LiquidityFlow Dominance+Alerts (btc.d, T3, Stables)LiquidityFlow Dominance+Alerts: Overview & Usage Guide
Overview
The LiquidityFlow Dominance+Alerts indicator provides a dynamic view of liquidity flow across Bitcoin, Altcoins, and Stablecoins, helping track liquidity shifts and identify market sentiment. By integrating moving averages, custom alerts, and thresholds for extreme outliers, this indicator helps to anticipate bullish and bearish shifts in liquidity and alert market tops and bottoms.
Key features include:
1. Liquidity Flow Monitoring : Track liquidity flow across Bitcoin (BTC), Altcoins (TOTAL3), and Stablecoins (USDT, USDC, DAI).
2. Custom Alerts : Set alerts for key liquidity shifts and extreme conditions in Stablecoin dominance, both with static and moving average (MA)-based calculations.
3. Moving Averages : Use Simple, Exponential, or Weighted Moving Averages to smooth out market data for more reliable signals.
4. Outlier Detection : Identify potential tops and bottoms using thresholds for Stablecoin dominance, with alerts for extreme movements.
Functionality
Data Inputs and Key Metrics
- Symbols Monitored:
- Bitcoin Dominance (BTC.D)
- Altcoin Market Cap (TOTAL3)
- Stablecoins (USDT.D, USDC.D, DAI.D)
- Liquidity Flow Conditions:
- Track percentage changes in dominance across sectors to detect liquidity flow into Bitcoin, Altcoins, or Stablecoins.
- Custom Metrics:
- Liquidity Flow Index: BTC Dominance minus Stablecoin Dominance.
- Liquidity Flow Ratio: BTC Dominance divided by the combined dominance of Stablecoins and Altcoins.
Moving Average Integration
- Select from SMA, EMA, or WMA to apply moving averages to the dominance metrics. Moving averages help smooth out short-term volatility and provide more consistent signals.
- Moving averages are applied to each sector (BTC, Altcoins, and Stablecoins) and compared to their previous period values to determine shifts in liquidity.
Alerts and Thresholds
- % Change Lookback Period: Adjust the lookback period to align with the timeframe of your chart. Shorter timeframes may require a lower lookback period, while higher timeframes may benefit from longer periods.
- Stables Bull/Bear % for Alerts: Set a threshold for when Stablecoin dominance becomes a bullish or bearish signal relative to BTC and Altcoins. A higher threshold may be used in volatile markets to filter out noise.
- Extreme Outliers Detection: Use the **Stables Up/Down Extreme Threshold** to identify potential market tops or bottoms when Stablecoin dominance deviates significantly from historical trends. The **Extreme Lookback Period** controls the time window for detecting these anomalies.
How to Use the Indicator
Adjusting the % Change Lookback Period
- The `% Change Lookback Period` should be adjusted based on your chart’s timeframe. For example, a shorter period (e.g., 7) works well for intraday charts, while longer periods (e.g., 14) might be more suitable for daily or weekly charts.
Setting Thresholds for Alerts
- Stables Bull/Bear % for Alerts: Adjust this setting to define when Stablecoin dominance triggers bullish or bearish alerts. A value like 1% could be a good starting point for most market conditions but can be fine-tuned based on volatility.
- Extreme Lookback Period: Define the lookback period for detecting extreme moves in Stablecoin dominance. This will help identify major tops and bottoms in the market. For shorter-term trades, consider using a shorter extreme lookback (e.g., 7-10 periods).
Alerts for Liquidity Shifts
- The indicator supports alerts for key liquidity shifts, which are useful for staying ahead of market movements. Alerts can be set to notify you when liquidity moves into:
- Bitcoin: Indicating a potential bullish trend for Bitcoin.
- Altcoins: Signaling altcoins are bullish.
- Stablecoins: Suggesting a risk-off environment or market correction.
Extreme Alerts for Stables
- Extreme Up/Down Alerts: These are triggered when Stablecoin dominance crosses extreme thresholds. For example, if Stablecoin dominance rises more than 14% over a set period, it could signal a market top, while a significant drop could indicate a market bottom.
Moving Average Calculations
- In addition to static percentage changes, moving averages can be applied to smooth out dominance values. The type and length of the moving average can be customized:
- SMA (Simple Moving Average): Best for smoothing out volatility in a linear way.
- EMA (Exponential Moving Average): More responsive to recent data, making it useful in faster markets.
- WMA (Weighted Moving Average): Emphasizes more recent data, but less reactive than the EMA.
Additional Usage Tips:
- Background Colors: The indicator visually highlights the dominant liquidity flow:
- Orange: Liquidity is shifting toward Bitcoin.
- Aqua: Liquidity is flowing into Altcoins.
- Red: Liquidity is moving into Stablecoins.
Multi-Factor StrategyThis trading strategy combines multiple technical indicators to create a systematic approach for entering and exiting trades. The goal is to capture trends by aligning several key indicators to confirm the direction and strength of a potential trade. Below is a detailed description of how the strategy works:
Indicators Used
MACD (Moving Average Convergence Divergence):
MACD Line: The difference between the 12-period and 26-period Exponential Moving Averages (EMAs).
Signal Line: A 9-period EMA of the MACD line.
Usage: The strategy looks for crossovers between the MACD line and the Signal line as entry signals. A bullish crossover (MACD line crossing above the Signal line) indicates a potential upward movement, while a bearish crossover (MACD line crossing below the Signal line) signals a potential downward movement.
RSI (Relative Strength Index):
Usage: RSI is used to gauge the momentum of the price movement. The strategy uses specific thresholds: below 70 for long positions to avoid overbought conditions and above 30 for short positions to avoid oversold conditions.
ATR (Average True Range):
Usage: ATR measures market volatility and is used to set dynamic stop-loss and take-profit levels. A stop loss is set at 2 times the ATR, and a take profit at 3 times the ATR, ensuring that risk is managed relative to market conditions.
Simple Moving Averages (SMA):
50-day SMA: A short-term trend indicator.
200-day SMA: A long-term trend indicator.
Usage: The strategy uses the relationship between the 50-day and 200-day SMAs to determine the overall market trend. Long positions are taken when the price is above the 50-day SMA and the 50-day SMA is above the 200-day SMA, indicating an uptrend. Conversely, short positions are taken when the price is below the 50-day SMA and the 50-day SMA is below the 200-day SMA, indicating a downtrend.
Entry Conditions
Long Position:
-MACD Crossover: The MACD line crosses above the Signal line.
-RSI Confirmation: RSI is below 70, ensuring the asset is not overbought.
-SMA Confirmation: The price is above the 50-day SMA, and the 50-day SMA is above the 200-day SMA, indicating a strong uptrend.
Short Position:
MACD Crossunder: The MACD line crosses below the Signal line.
RSI Confirmation: RSI is above 30, ensuring the asset is not oversold.
SMA Confirmation: The price is below the 50-day SMA, and the 50-day SMA is below the 200-day SMA, indicating a strong downtrend.
Opposite conditions for shorts
Exit Strategy
Stop Loss: Set at 2 times the ATR from the entry price. This dynamically adjusts to market volatility, allowing for wider stops in volatile markets and tighter stops in calmer markets.
Take Profit: Set at 3 times the ATR from the entry price. This ensures a favorable risk-reward ratio of 1:1.5, aiming for higher rewards on successful trades.
Visualization
SMAs: The 50-day and 200-day SMAs are plotted on the chart to visualize the trend direction.
MACD Crossovers: Bullish and bearish MACD crossovers are highlighted on the chart to identify potential entry points.
Summary
This strategy is designed to align multiple indicators to increase the probability of successful trades by confirming trends and momentum before entering a position. It systematically manages risk with ATR-based stop loss and take profit levels, ensuring that trades are exited based on market conditions rather than arbitrary points. The combination of trend indicators (SMAs) with momentum and volatility indicators (MACD, RSI, ATR) creates a robust approach to trading in various market environments.
Trend Strength with Volatility and Volume [ST]Trend Strength with Volatility and Volume
Description in English:
This indicator combines market volatility and trading volume to measure the current trend strength. It helps identify when the trend is gaining or losing momentum.
Detailed Explanation:
Configuration:
Length: This input defines the period over which the moving average is calculated. The default value is 14.
MA Type: This input allows you to choose between a Simple Moving Average (SMA) and an Exponential Moving Average (EMA).
Volatility Length: This input defines the period over which the ATR (Average True Range) is calculated. The default value is 14.
Volume Length: This input defines the period over which the moving average of volume is calculated. The default value is 14.
Trend Strength Calculation:
Moving Average (MA): The script calculates the moving average of the closing price based on the selected type (SMA or EMA) and period.
Volatility (ATR): The ATR is used to measure market volatility over the specified period.
Volume MA: The script calculates the moving average of the trading volume based on the selected type (SMA or EMA) and period.
Trend Strength: The trend strength is calculated as the difference between the closing price and the moving average, divided by the volatility, and multiplied by the volume normalized by its moving average.
Plotting:
The trend strength is plotted as a line chart. Positive values indicate a strong upward trend, while negative values indicate a strong downward trend.
A horizontal line is added at the zero level to help identify the neutral point.
Indicator Benefits:
Trend Identification: Helps traders identify the strength of the current trend by combining price, volatility, and volume.
Visual Cues: Provides clear visual signals for trend strength, aiding in making informed trading decisions.
Customizable Parameters: Allows traders to adjust the length of the moving averages, ATR, and volume to suit different trading strategies and market conditions.
Justification of Component Combination:
Combining price, volatility, and volume provides a comprehensive measure of trend strength. This combination enhances the trader's ability to make informed decisions based on multiple market factors.
How Components Work Together:
The script calculates the moving average of the closing price and trading volume.
It measures market volatility using the ATR.
The trend strength is calculated by combining these components, providing a robust measure of the current trend's strength.
Título: Força da Tendência com Volatilidade e Volume
Descrição em Português:
Este indicador combina a volatilidade do mercado, medida pelo ATR (Average True Range), e o volume de negociações para medir a força da tendência atual. Ele ajuda a identificar quando a tendência está ganhando ou perdendo força.
Explicação Detalhada:
Configuração:
Comprimento: Este parâmetro define o período para o cálculo da média móvel. O valor padrão é 14.
Tipo de MA: Este parâmetro permite escolher entre uma Média Móvel Simples (SMA) e uma Média Móvel Exponencial (EMA).
Comprimento da Volatilidade: Este parâmetro define o período para o cálculo do ATR (Average True Range). O valor padrão é 14.
Comprimento do Volume: Este parâmetro define o período para o cálculo da média móvel do volume. O valor padrão é 14.
Cálculo da Força da Tendência:
Média Móvel (MA): O indicador calcula a média móvel do preço de fechamento com base no tipo selecionado (SMA ou EMA) e período.
Volatilidade (ATR): O ATR é usado para medir a volatilidade do mercado ao longo do período especificado.
Média Móvel do Volume: O indicador calcula a média móvel do volume de negociação com base no tipo selecionado (SMA ou EMA) e período.
Força da Tendência: A força da tendência é calculada como a diferença entre o preço de fechamento e a média móvel, dividida pela volatilidade e multiplicada pelo volume normalizado pela sua média móvel.
Plotagem:
A força da tendência é plotada como um gráfico de linhas. Valores positivos indicam uma forte tendência de alta, enquanto valores negativos indicam uma forte tendência de baixa.
Uma linha horizontal é adicionada no nível zero para ajudar a identificar o ponto neutro.
Benefícios do Indicador:
Identificação de Tendências: Este indicador ajuda os traders a identificar a força da tendência atual, combinando preço, volatilidade e volume.
Sinais Visuais Claros: Fornece sinais visuais claros para a força da tendência, facilitando a tomada de decisões informadas.
Parâmetros Personalizáveis: Os traders podem ajustar o comprimento das médias móveis, ATR e volume para se adequar a diferentes estratégias de negociação e condições de mercado.
Justificação da Combinação de Componentes:
A combinação de preço, volatilidade e volume fornece uma medida abrangente da força da tendência.
Isso melhora a capacidade dos traders de tomar decisões informadas com base em múltiplos fatores do mercado.
Como os Componentes Funcionam Juntos:
O indicador calcula a média móvel do preço de fechamento e do volume de negociação.
Mede a volatilidade do mercado usando o ATR.
A força da tendência é calculada combinando esses componentes, fornecendo uma medida robusta da força da tendência atual.
