Dynamic Momentum Range Index (DMRI)//@version=5
indicator("Dynamic Momentum Range Index (DMRI)", shorttitle="DMRI", overlay=false)
// Inputs
n = input.int(14, title="Momentum Period", minval=1)
atrLength = input.int(14, title="ATR Length", minval=1)
maLength = input.int(20, title="Moving Average Length", minval=1)
// Calculations
pm = close - close // Price Momentum (PM)
atr = ta.atr(atrLength) // Average True Range (ATR)
va = pm / atr // Volatility Adjustment (VA)
// Moving Average and Dynamic Range Factor (DRF)
ma = ta.sma(close, maLength)
drf = math.abs(close - ma) / atr
// Dynamic Momentum Range Index (DMRI)
dmri = va * drf
// Normalization
maxVal = ta.highest(dmri, atrLength)
minVal = ta.lowest(dmri, atrLength)
dmriNormalized = (dmri - minVal) / (maxVal - minVal) * 100
// Zones for Interpretation
bullishZone = 70
bearishZone = 30
// Plotting DMRI
plot(dmriNormalized, title="DMRI", color=color.blue, linewidth=2)
hline(70, "Overbought", color=color.red)
hline(30, "Oversold", color=color.green)
hline(50, "Neutral", color=color.gray)
// Background Coloring
bgcolor(dmriNormalized > bullishZone ? color.new(color.green, 90) : na, title="Bullish Zone Highlight")
bgcolor(dmriNormalized < bearishZone ? color.new(color.red, 90) : na, title="Bearish Zone Highlight")
Momentumindicator
Dynamic Momentum Range Index (DMRI)//@version=5
indicator("Dynamic Momentum Range Index (DMRI)", shorttitle="DMRI", overlay=false)
// Inputs
n = input.int(14, title="Momentum Period", minval=1)
atrLength = input.int(14, title="ATR Length", minval=1)
maLength = input.int(20, title="Moving Average Length", minval=1)
// Calculations
pm = close - close // Price Momentum (PM)
atr = ta.atr(atrLength) // Average True Range (ATR)
va = pm / atr // Volatility Adjustment (VA)
// Moving Average and Dynamic Range Factor (DRF)
ma = ta.sma(close, maLength)
drf = math.abs(close - ma) / atr
// Dynamic Momentum Range Index (DMRI)
dmri = va * drf
// Normalization
maxVal = ta.highest(dmri, atrLength)
minVal = ta.lowest(dmri, atrLength)
dmriNormalized = (dmri - minVal) / (maxVal - minVal) * 100
// Zones for Interpretation
bullishZone = 70
bearishZone = 30
// Plotting DMRI
plot(dmriNormalized, title="DMRI", color=color.blue, linewidth=2)
hline(70, "Overbought", color=color.red)
hline(30, "Oversold", color=color.green)
hline(50, "Neutral", color=color.gray)
// Background Coloring
bgcolor(dmriNormalized > bullishZone ? color.new(color.green, 90) : na, title="Bullish Zone Highlight")
bgcolor(dmriNormalized < bearishZone ? color.new(color.red, 90) : na, title="Bearish Zone Highlight")
Momentum TrackerTo screen for momentum movers, one can filter for stocks that have made a noticeable move over a set period—this initial move defines the momentum or swing move. From this list of candidates, we can create a watchlist by selecting those showing a momentum pause, such as a pullback or consolidation, which later could set up for a continuation.
This Momentum Tracker Indicator serves as a study tool to visualize when stocks historically met these momentum conditions. It marks on the chart where a stock would have appeared on the screener, allowing us to review past momentum patterns and screener requirements.
Indicator Calculation
Bullish Momentum: Price is above the lowest point within the lookback period by the specified threshold percentage.
Bearish Momentum: Price is below the highest point within the lookback period by the specified threshold percentage.
The tool is customizable in terms of lookback period and percentage threshold to accommodate different trading styles and timeframes, allowing us to set criteria that align with specific hold times and momentum requirements.
Salman Indicator: Multi-Purpose Price ActionSalman Indicator: Multi-Purpose Price Action Tool for Pin Bars, Breakouts, and VWAP Anchoring
This indicator provides a comprehensive suite of price action insights, designed for active traders looking to identify key market structures and potential reversals. The script incorporates a Quarterly VWAP for trend bias, marks pin bars for possible reversal points, highlights outside bars for volatility signals, and indicates simple breakouts and pivot-level breaks. Customizable settings allow for flexibility in various trading styles, with default settings optimized for daily charts.
Outside Bars : Represented by an ⤬ symbol on the chart, these indicate bars where the current high is greater than the previous bar’s high, and the low is lower than the previous bar’s low, signaling high volatility and potential market reversals.
Pin Bars : Denoted by a small dot at the top or bottom of a candle’s wick, these are crucial signals of potential reversal areas. Pin bars are identified based on the percentage length of their shadows, with adjustable strictness in settings.
Quarterly VWAP : The light blue line on the chart represents the VWAP (Volume-Weighted Average Price), which is anchored to the Quarterly period by default. The VWAP acts as a directional bias filter, helping you to determine underlying market trends. This period, source, and offset are fully adjustable in the script’s settings.
Simple Breaks : Hollow candles on the chart indicate "simple breaks," defined when the current bar closes above the previous high or below the previous low. This is an effective way to highlight directional momentum in the market.
Bonus Pivot Breaks : The tilde symbol ~ appears when the price closes above or below prior pivot high/low levels, helping traders spot significant breakout or breakdown points relative to recent pivots.
Alerts
Simple Breaks : Alerts you when a breakout occurs beyond the previous bar’s high or low. Pin Bars : Notifies you of potential reversal points as indicated by bullish or bearish pin bars. Outside Bars : Triggers an alert whenever an outside bar is detected, indicating possible volatility changes.
How to Use
VWAP for Trend Bias : Use the Quarterly VWAP line to gauge overall market trend, with settings that allow adjustment to daily, weekly, monthly, or even larger time frames.
Pin Bars for Reversal Potential : Look for the dot markers on candle wicks, where the strictness of the pin bar detection can be adjusted via settings to match your trading preference.
Simple and Pivot Breaks for Momentum : Watch for hollow candles and the tilde symbol ~ as indicators of potential breakout momentum and pivot break levels, respectively.
This script can serve traders on multiple timeframes, from daily to weekly and beyond. The flexible configuration allows for adjustments in VWAP anchoring and pin bar criteria, providing a tailored fit for individual trading strategies.
CMF and Scaled EFI OverlayCMF and Scaled EFI Overlay Indicator
Overview
The CMF and Scaled EFI Overlay indicator combines the Chaikin Money Flow (CMF) and a scaled version of the Elder Force Index (EFI) into a single chart. This allows traders to analyze both indicators simultaneously, facilitating better insights into market momentum and volume dynamics , specifically focusing on buying/selling pressure and momentum , without compromising the integrity of either indicator.
Purpose
Chaikin Money Flow (CMF): Measures buying and selling pressure by evaluating price and volume over a specified period. It indicates accumulation (buying pressure) when values are positive and distribution (selling pressure) when values are negative.
Elder Force Index (EFI): Combines price changes and volume to assess the momentum behind market moves. Positive values indicate upward momentum (prices rising with strong volume), while negative values indicate downward momentum (prices falling with strong volume).
By scaling the EFI to match the amplitude of the CMF, this indicator enables a direct comparison between pressure and momentum , preserving their shapes and zero crossings. Traders can observe the relationship between price movements, volume, and momentum more effectively, aiding in decision-making.
Understanding Pressure vs. Momentum
Chaikin Money Flow (CMF):
- Indicates the level of demand (buying pressure) or supply (selling pressure) in the market based on volume and price movements.
- Accumulation: When institutional or large investors are buying significant amounts of an asset, leading to an increase in buying pressure.
- Distribution: When these investors are selling off their holdings, increasing selling pressure.
Elder Force Index (EFI):
- Measures the strength and speed of price movements, indicating how forceful the current trend is.
- Positive Momentum: Prices are rising quickly, indicating a strong uptrend.
- Negative Momentum: Prices are falling rapidly, indicating a strong downtrend.
Understanding the difference between pressure and momentum is crucial. For example, a market may exhibit strong buying pressure (positive CMF) but weak momentum (low EFI), suggesting accumulation without significant price movement yet.
Features
Overlay of CMF and Scaled EFI: Both indicators are plotted on the same chart for easy comparison of pressure and momentum dynamics.
Customizable Parameters: Adjust lengths for CMF and EFI calculations and fine-tune the scaling factor for optimal alignment.
Preserved Indicator Integrity: The scaling method preserves the shape and zero crossings of the EFI, ensuring accurate analysis.
How It Works
CMF Calculation:
- Calculates the Money Flow Multiplier (MFM) and Money Flow Volume (MFV) to assess buying and selling pressure.
- CMF is computed by summing the MFV over the specified length and dividing by the sum of volume over the same period:
CMF = (Sum of MFV over n periods) / (Sum of Volume over n periods)
EFI Calculation:
- Calculates the EFI using the Exponential Moving Average (EMA) of the price change multiplied by volume:
EFI = EMA(n, Change in Close * Volume)
Scaling the EFI:
- The EFI is scaled by multiplying it with a user-defined scaling factor to match the CMF's amplitude.
Plotting:
- Both the CMF and the scaled EFI are plotted on the same chart.
- A zero line is included for reference, aiding in identifying crossovers and divergences.
Indicator Settings
Inputs
CMF Length (`cmf_length`):
- Default: 20
- Description: The number of periods over which the CMF is calculated. A higher value smooths the indicator but may delay signals.
EFI Length (`efi_length`):
- Default: 13
- Description: The EMA length for the EFI calculation. Adjusting this value affects the sensitivity of the EFI to price changes.
EFI Scaling Factor (`efi_scaling_factor`):
- Default: 0.000001
- Description: A constant used to scale the EFI to match the CMF's amplitude. Fine-tuning this value ensures the indicators align visually.
How to Adjust the EFI Scaling Factor
Start with the Default Value:
- Begin with the default scaling factor of `0.000001`.
Visual Inspection:
- Observe the plotted indicators. If the EFI appears too large or small compared to the CMF, proceed to adjust the scaling factor.
Fine-Tune the Scaling Factor:
- Increase or decrease the scaling factor incrementally (e.g., `0.000005`, `0.00001`, `0.00005`) until the amplitudes of the CMF and EFI visually align.
- The optimal scaling factor may vary depending on the asset and timeframe.
Verify Alignment:
- Ensure that the scaled EFI preserves the shape and zero crossings of the original EFI.
- Overlay the original EFI (if desired) to confirm alignment.
How to Use the Indicator
Analyze Buying/Selling Pressure and Momentum:
- Positive CMF (>0): Indicates accumulation (buying pressure).
- Negative CMF (<0): Indicates distribution (selling pressure).
- Positive EFI: Indicates positive momentum (prices rising with strong volume).
- Negative EFI: Indicates negative momentum (prices falling with strong volume).
Look for Indicator Alignment:
- Both CMF and EFI Positive:
- Suggests strong bullish conditions with both buying pressure and upward momentum.
- Both CMF and EFI Negative:
- Indicates strong bearish conditions with selling pressure and downward momentum.
Identify Divergences:
- CMF Positive, EFI Negative:
- Buying pressure exists, but momentum is negative; potential for a bullish reversal if momentum shifts.
- CMF Negative, EFI Positive:
- Selling pressure exists despite rising prices; caution advised as it may indicate a potential bearish reversal.
Confirm Signals with Other Analysis:
- Use this indicator in conjunction with other technical analysis tools (e.g., trend lines, support/resistance levels) to confirm trading decisions.
Example Usage
Scenario 1: Bullish Alignment
- CMF Positive: Indicates accumulation (buying pressure).
- EFI Positive and Increasing: Shows strengthening upward momentum.
- Interpretation:
- Strong bullish signal suggesting that buyers are active, and the price is likely to continue rising.
- Action:
- Consider entering a long position or adding to existing ones.
Scenario 2: Bearish Divergence
- CMF Negative: Indicates distribution (selling pressure).
- EFI Positive but Decreasing: Momentum is positive but weakening.
- Interpretation:
- Potential bearish reversal; price may be rising but underlying selling pressure suggests caution.
- Action:
- Be cautious with long positions; consider tightening stop-losses or preparing for a possible trend reversal.
Tips
Adjust for Different Assets:
- The optimal scaling factor may differ across assets due to varying price and volume characteristics.
- Always adjust the scaling factor when analyzing a new asset.
Monitor Indicator Crossovers:
- Crossings above or below the zero line can signal potential trend changes.
Watch for Divergences:
- Divergences between the CMF and EFI can provide early warning signs of trend reversals.
Combine with Other Indicators:
- Enhance your analysis by combining this overlay with other indicators like moving averages, RSI, or Ichimoku Cloud.
Limitations
Scaling Factor Sensitivity:
- An incorrect scaling factor may misalign the indicators, leading to inaccurate interpretations.
- Regular adjustments may be necessary when switching between different assets or timeframes.
Not a Standalone Indicator:
- Should be used as part of a comprehensive trading strategy.
- Always consider other market factors and indicators before making trading decisions.
Disclaimer
No Guarantee of Performance:
- Past performance is not indicative of future results.
- Trading involves risk, and losses can exceed deposits.
Use at Your Own Risk:
- This indicator is provided for educational purposes.
- The author is not responsible for any financial losses incurred while using this indicator.
Code Summary
//@version=5
indicator(title="CMF and Scaled EFI Overlay", shorttitle="CMF & Scaled EFI", overlay=false)
cmf_length = input.int(20, minval=1, title="CMF Length")
efi_length = input.int(13, minval=1, title="EFI Length")
efi_scaling_factor = input.float(0.000001, title="EFI Scaling Factor", minval=0.0, step=0.000001)
// --- CMF Calculation ---
ad = high != low ? ((2 * close - low - high) / (high - low)) * volume : 0
mf = math.sum(ad, cmf_length) / math.sum(volume, cmf_length)
// --- EFI Calculation ---
efi_raw = ta.ema(ta.change(close) * volume, efi_length)
// --- Scale EFI ---
efi_scaled = efi_raw * efi_scaling_factor
// --- Plotting ---
plot(mf, color=color.green, title="CMF", linewidth=2)
plot(efi_scaled, color=color.red, title="EFI (Scaled)", linewidth=2)
hline(0, color=color.gray, title="Zero Line", linestyle=hline.style_dashed)
- Lines 4-6: Define input parameters for CMF length, EFI length, and EFI scaling factor.
- Lines 9-11: Calculate the CMF.
- Lines 14-16: Calculate the EFI.
- Line 19: Scale the EFI by the scaling factor.
- Lines 22-24: Plot the CMF, scaled EFI, and zero line.
Feedback and Support
Suggestions: If you have ideas for improvements or additional features, please share your feedback.
Support: For assistance or questions regarding this indicator, feel free to contact the author through TradingView.
---
By combining the CMF and scaled EFI into a single overlay, this indicator provides a powerful tool for traders to analyze market dynamics more comprehensively. Adjust the parameters to suit your trading style, and always practice sound risk management.
GAP Momentum Oscillator
This function calculates GAP Momentum, a measure of momentum based on the gaps between opening and closing prices over several periods.
Gaps are calculated for defined periods (here, by default, 14 periods). It determines :
UpGaps: the sum of positive gaps, i.e. openings that are higher than the previous period's close.
DnGaps: the sum of negative gaps, i.e. openings below the previous period's close.
It then calculates the GAP Momentum as the ratio between the sum of the up gaps and the sum of the down gaps, multiplied by 100. If the total of the down gaps is zero, the ratio takes a default value of 1 to avoid division by zero.
Advanced Stochastic ForLoopAdvanced Stochastic ForLoop
OVERVIEW
Advanced Stochastic ForLoop is an improved version of Stochastic it is designed to calculate an array of values 1 or -1 depending if soruce for calculations is above or below basis.
It takes avereage of values over a range of lengths, providing trend signals smothed based on various moving averages in order to get rid of noise.
It offers flexibility with different signal modes and visual customizations.
TYPE OF SIGNALS
-FAST (MA > MA or MA > 0.99)
-SLOW (MA > 0)
-THRESHOLD CROSSING (set by user treshold for both directions)
-FAST THRESHOLD (when theres an change in signal by set margin e.g 0.4 -> 0.2 means bearsih when FT is set to 0.1, when MA is > 0.99 it will signal bullish, when MA < -0.99 it will signal bearish)
Generaly Lime color of line indicates Bullish, Fuchsia indicates Bearish.
This colors are not set in stone so you can change them in settings.
Alerts included when line color is:
-Bullish Trend, line color is lime
-Bearish Trend, line color is fuchsia
Credit
Idea for this script was from one of indicators created by www.tradingview.com
Warning
This indicator can be really noisy depending on the settings, signal mode so it should be used preferably as a part of an strategy not as a stand alone indicator
Remember the lower the timeframe you use the more noise there is.
No single indicator should be used alone when making investment decisions.
Relative Strength and MomentumRelative Strength and Momentum Indicator
Unlock deeper market insights with the Relative Strength and Momentum Indicator—a powerful tool designed to help traders and investors identify the strongest stocks and sectors based on relative performance. This custom indicator displays essential information on relative strength and momentum for up to 15 different symbols, compared against a benchmark index, all within a clear and organized table format.
Key Features:
1. Customizable Inputs: Choose up to 15 symbols to compare, along with a benchmark index, allowing you to tailor the indicator to your trading strategy. The 'Lookback Period' input defines how many weeks of data are analyzed for relative strength and momentum.
2. Relative Strength Calculation: For each selected symbol, the indicator calculates the Relative Strength (RS) against the chosen benchmark. This RS is further refined using an exponential moving average (EMA) to smooth the results, providing a more stable trend overview.
3. Momentum Analysis: Momentum is determined by analyzing the rate of change in relative strength. The indicator calculates a momentum rank for each symbol, based on its relative strength’s improvement or deterioration.
4. Percentile Ranking System: Each symbol is assigned a percentile rank (from 1 to 100) based on its relative strength compared to the others. Similarly, momentum rankings are also assigned from 1 to 100, offering a clear understanding of which assets are outperforming or underperforming.
5. Visual Indicators:
a. Green: Signals improving or stable relative strength and momentum.
b. Red: Indicates declining relative strength or momentum.
c. Aqua: Highlights symbols performing well on both relative strength and momentum—ideal candidates for further analysis.
6. Two Clear Tables:
a. Relative Strength Rank Table: Displays weekly rankings of relative strength for each symbol.
b. Momentum Table: Shows momentum trends, helping you identify which symbols are gaining or losing strength.
7. Color-Coded for Easy Analysis: The tables are color-coded to make analysis quick and straightforward. A green color means the symbol is performing well in terms of relative strength or momentum, while red indicates weaker performance. Aqua marks symbols that are excelling in both areas.
Use Case:
a. Sector Comparison: Identify which sectors or indexes are showing both relative strength and momentum to pick high-potential stocks. This allows you to align with broader market trends for improved trade entries.
b. Stock Selection: Quickly compare symbols within the same sector to find the stronger performers.
Intramarket Difference Index StrategyHi Traders !!
The IDI Strategy:
In layman’s terms this strategy compares two indicators across markets and exploits their differences.
note: it is best the two markets are correlated as then we know we are trading a short to long term deviation from both markets' general trend with the assumption both markets will trend again sometime in the future thereby exhausting our trading opportunity.
📍 Import Notes:
This Strategy calculates trade position size independently (i.e. risk per trade is controlled in the user inputs tab), this means that the ‘Order size’ input in the ‘Properties’ tab will have no effect on the strategy. Why ? because this allows us to define custom position size algorithms which we can use to improve our risk management and equity growth over time. Here we have the option to have fixed quantity or fixed percentage of equity ATR (Average True Range) based stops in addition to the turtle trading position size algorithm.
‘Pyramiding’ does not work for this strategy’, similar to the order size input togeling this input will have no effect on the strategy as the strategy explicitly defines the maximum order size to be 1.
This strategy is not perfect, and as of writing of this post I have not traded this algo.
Always take your time to backtests and debug the strategy.
🔷 The IDI Strategy:
By default this strategy pulls data from your current TV chart and then compares it to the base market, be default BINANCE:BTCUSD . The strategy pulls SMA and RSI data from either market (we call this the difference data), standardizes the data (solving the different unit problem across markets) such that it is comparable and then differentiates the data, calling the result of this transformation and difference the Intramarket Difference (ID). The formula for the the ID is
ID = market1_diff_data - market2_diff_data (1)
Where
market(i)_diff_data = diff_data / ATR(j)_market(i)^0.5,
where i = {1, 2} and j = the natural numbers excluding 0
Formula (1) interpretation is the following
When ID > 0: this means the current market outperforms the base market
When ID = 0: Markets are at long run equilibrium
When ID < 0: this means the current market underperforms the base market
To form the strategy we define one of two strategy type’s which are Trend and Mean Revesion respectively.
🔸 Trend Case:
Given the ‘‘Strategy Type’’ is equal to TREND we define a threshold for which if the ID crosses over we go long and if the ID crosses under the negative of the threshold we go short.
The motivating idea is that the ID is an indicator of the two symbols being out of sync, and given we know volatility clustering, momentum and mean reversion of anomalies to be a stylised fact of financial data we can construct a trading premise. Let's first talk more about this premise.
For some markets (cryptocurrency markets - synthetic symbols in TV) the stylised fact of momentum is true, this means that higher momentum is followed by higher momentum, and given we know momentum to be a vector quantity (with magnitude and direction) this momentum can be both positive and negative i.e. when the ID crosses above some threshold we make an assumption it will continue in that direction for some time before executing back to its long run equilibrium of 0 which is a reasonable assumption to make if the market are correlated. For example for the BTCUSD - ETHUSD pair, if the ID > +threshold (inputs for MA and RSI based ID thresholds are found under the ‘‘INTRAMARKET DIFFERENCE INDEX’’ group’), ETHUSD outperforms BTCUSD, we assume the momentum to continue so we go long ETHUSD.
In the standard case we would exit the market when the IDI returns to its long run equilibrium of 0 (for the positive case the ID may return to 0 because ETH’s difference data may have decreased or BTC’s difference data may have increased). However in this strategy we will not define this as our exit condition, why ?
This is because we want to ‘‘let our winners run’’, to achieve this we define a trailing Donchian Channel stop loss (along with a fixed ATR based stop as our volatility proxy). If we were too use the 0 exit the strategy may print a buy signal (ID > +threshold in the simple case, market regimes may be used), return to 0 and then print another buy signal, and this process can loop may times, this high trade frequency means we fail capture the entire market move lowering our profit, furthermore on lower time frames this high trade frequencies mean we pay more transaction costs (due to price slippage, commission and big-ask spread) which means less profit.
By capturing the sum of many momentum moves we are essentially following the trend hence the trend following strategy type.
Here we also print the IDI (with default strategy settings with the MA difference type), we can see that by letting our winners run we may catch many valid momentum moves, that results in a larger final pnl that if we would otherwise exit based on the equilibrium condition(Valid trades are denoted by solid green and red arrows respectively and all other valid trades which occur within the original signal are light green and red small arrows).
another example...
Note: if you would like to plot the IDI separately copy and paste the following code in a new Pine Script indicator template.
indicator("IDI")
// INTRAMARKET INDEX
var string g_idi = "intramarket diffirence index"
ui_index_1 = input.symbol("BINANCE:BTCUSD", title = "Base market", group = g_idi)
// ui_index_2 = input.symbol("BINANCE:ETHUSD", title = "Quote Market", group = g_idi)
type = input.string("MA", title = "Differrencing Series", options = , group = g_idi)
ui_ma_lkb = input.int(24, title = "lookback of ma and volatility scaling constant", group = g_idi)
ui_rsi_lkb = input.int(14, title = "Lookback of RSI", group = g_idi)
ui_atr_lkb = input.int(300, title = "ATR lookback - Normalising value", group = g_idi)
ui_ma_threshold = input.float(5, title = "Threshold of Upward/Downward Trend (MA)", group = g_idi)
ui_rsi_threshold = input.float(20, title = "Threshold of Upward/Downward Trend (RSI)", group = g_idi)
//>>+----------------------------------------------------------------+}
// CUSTOM FUNCTIONS |
//<<+----------------------------------------------------------------+{
// construct UDT (User defined type) containing the IDI (Intramarket Difference Index) source values
// UDT will hold many variables / functions grouped under the UDT
type functions
float Close // close price
float ma // ma of symbol
float rsi // rsi of the asset
float atr // atr of the asset
// the security data
getUDTdata(symbol, malookback, rsilookback, atrlookback) =>
indexHighTF = barstate.isrealtime ? 1 : 0
= request.security(symbol, timeframe = timeframe.period,
expression = [close , // Instentiate UDT variables
ta.sma(close, malookback) ,
ta.rsi(close, rsilookback) ,
ta.atr(atrlookback) ])
data = functions.new(close_, ma_, rsi_, atr_)
data
// Intramerket Difference Index
idi(type, symbol1, malookback, rsilookback, atrlookback, mathreshold, rsithreshold) =>
threshold = float(na)
index1 = getUDTdata(symbol1, malookback, rsilookback, atrlookback)
index2 = getUDTdata(syminfo.tickerid, malookback, rsilookback, atrlookback)
// declare difference variables for both base and quote symbols, conditional on which difference type is selected
var diffindex1 = 0.0, var diffindex2 = 0.0,
// declare Intramarket Difference Index based on series type, note
// if > 0, index 2 outpreforms index 1, buy index 2 (momentum based) until equalibrium
// if < 0, index 2 underpreforms index 1, sell index 1 (momentum based) until equalibrium
// for idi to be valid both series must be stationary and normalised so both series hae he same scale
intramarket_difference = 0.0
if type == "MA"
threshold := mathreshold
diffindex1 := (index1.Close - index1.ma) / math.pow(index1.atr*malookback, 0.5)
diffindex2 := (index2.Close - index2.ma) / math.pow(index2.atr*malookback, 0.5)
intramarket_difference := diffindex2 - diffindex1
else if type == "RSI"
threshold := rsilookback
diffindex1 := index1.rsi
diffindex2 := index2.rsi
intramarket_difference := diffindex2 - diffindex1
//>>+----------------------------------------------------------------+}
// STRATEGY FUNCTIONS CALLS |
//<<+----------------------------------------------------------------+{
// plot the intramarket difference
= idi(type,
ui_index_1,
ui_ma_lkb,
ui_rsi_lkb,
ui_atr_lkb,
ui_ma_threshold,
ui_rsi_threshold)
//>>+----------------------------------------------------------------+}
plot(intramarket_difference, color = color.orange)
hline(type == "MA" ? ui_ma_threshold : ui_rsi_threshold, color = color.green)
hline(type == "MA" ? -ui_ma_threshold : -ui_rsi_threshold, color = color.red)
hline(0)
Note it is possible that after printing a buy the strategy then prints many sell signals before returning to a buy, which again has the same implication (less profit. Potentially because we exit early only for price to continue upwards hence missing the larger "trend"). The image below showcases this cenario and again, by allowing our winner to run we may capture more profit (theoretically).
This should be clear...
🔸 Mean Reversion Case:
We stated prior that mean reversion of anomalies is an standerdies fact of financial data, how can we exploit this ?
We exploit this by normalizing the ID by applying the Ehlers fisher transformation. The transformed data is then assumed to be approximately normally distributed. To form the strategy we employ the same logic as for the z score, if the FT normalized ID > 2.5 (< -2.5) we buy (short). Our exit conditions remain unchanged (fixed ATR stop and trailing Donchian Trailing stop)
🔷 Position Sizing:
If ‘‘Fixed Risk From Initial Balance’’ is toggled true this means we risk a fixed percentage of our initial balance, if false we risk a fixed percentage of our equity (current balance).
Note we also employ a volatility adjusted position sizing formula, the turtle training method which is defined as follows.
Turtle position size = (1/ r * ATR * DV) * C
Where,
r = risk factor coefficient (default is 20)
ATR(j) = risk proxy, over j times steps
DV = Dollar Volatility, where DV = (1/Asset Price) * Capital at Risk
🔷 Risk Management:
Correct money management means we can limit risk and increase reward (theoretically). Here we employ
Max loss and gain per day
Max loss per trade
Max number of consecutive losing trades until trade skip
To read more see the tooltips (info circle).
🔷 Take Profit:
By defualt the script uses a Donchain Channel as a trailing stop and take profit, In addition to this the script defines a fixed ATR stop losses (by defualt, this covers cases where the DC range may be to wide making a fixed ATR stop usefull), ATR take profits however are defined but optional.
ATR SL and TP defined for all trades
🔷 Hurst Regime (Regime Filter):
The Hurst Exponent (H) aims to segment the market into three different states, Trending (H > 0.5), Random Geometric Brownian Motion (H = 0.5) and Mean Reverting / Contrarian (H < 0.5). In my interpretation this can be used as a trend filter that eliminates market noise.
We utilize the trending and mean reverting based states, as extra conditions required for valid trades for both strategy types respectively, in the process increasing our trade entry quality.
🔷 Example model Architecture:
Here is an example of one configuration of this strategy, combining all aspects discussed in this post.
Future Updates
- Automation integration (next update)
Aggressor Volume ImbalanceAggressor volume imbalance represents the ratio between market aggressor buy volume (market buy orders) and market aggressor sell volume (market sell orders). This ratio enables traders to evaluate the interest of market aggressors and whether aggressive market activity favours the price's direction.
Analysing aggressor volume is critical in understanding market sentiment and aids in identifying shifts in momentum and potential exhaustion points in the market. When the aggressor buy volume significantly exceeds the sell volume, it typically indicates strong buying interest, driving prices higher if the offer-side liquidity cannot contain it, and vice versa.
How it Works
The imbalance ratio is calculated as follows, according to the selected session timeframe (see settings):
imbalance := ((buyVolumeAccumulator - sellVolumeAccumulator)
/ (buyVolumeAccumulator + sellVolumeAccumulator)) * 100
Aggressive Volume Imbalance uses lower timeframe historical data to calculate Historical Aggressor Volume Imbalances, while live data is used for live aggressor volume imbalances.
How to Use It
You can set the indicator to use any historical data timeframe you prefer. However, it is highly recommended to use lower timeframes (e.g., 1 second), as the lower the timeframe, the more granular the data.
The indicator resets to 0% whenever a new session timeframe begins (e.g., a new day) and calculates new values for the rest of the session. This can be configured in the settings.
Dynamic Momentum GaugeOverview
The Dynamic Momentum Gauge is an indicator designed to provide information and insights into the trend and momentum of a financial asset. While this indicator is not directional , it helps you know when there will be a trend, big move, or when momentum will have a run, and when you should take profits.
How It Works
This indicator calculates momentum and then removes the negative values to focus instead on when the big trend could likely happen and when it could end, or when you should enter a trade based on momentum or exit. Traders can basically use this indicator to time their market entries or exits, and align their strategies with momentum dynamics.
How To Use
As previously mentioned, this is not a directional indicator but more like a timing indicator. This indicator helps you find when the trend moves, and big moves in the markets will occur and its possibly best to exit the trades. For example, if you decide to enter a long trade if the Dynamic Momentum Gauge value is at an extreme low and another momentum indicator that you use has conditions that you would consider to long with, then this indicator is basically telling you that there isn't more space for the momentum to squeeze any longer, can only really expand from that point or stay where it currently is, but this is also a mean reverting process so it does tend to go back up from the low point.
Settings:
Length: This is the length of the momentum, by default its at 100.
Normalization Length: Length of the Normalization which ensures the the values fall within a consistent range.
Bubble Risk IndicatorThe Bubble Risk Indicator is a sophisticated tool designed to assess the potential risk level of a trading instrument by measuring its deviation from a 20-week Simple Moving Average (SMA). This dynamic indicator visually represents the deviation with a color-changing line, indicating the degree of risk based on the distance from the SMA.
🔷 Calculation
The indicator calculates the deviation from the 20-week SMA and expresses it as a percentage extension:
20-Week SMA : Averages the closing prices over the past 20 periods, providing a consistent measure of the long-term trend.
Deviation Percentage : Measures the percentage difference between the current closing price and the 20-week SMA.
🔷 Color Coding
The line changes color based on the deviation level to represent different risk levels. Users can customize these colors as per their preferences. However, the following are the default recommended settings:
Extreme Low Risk (Below 0) : Blue
Low Risk (Below 0) : Light Blue
Low Risk (Above 0) : Light Purple
Medium Risk : Orange
High Risk : Red
Colors transition smoothly to reflect the increasing or decreasing risk based on the deviation from the SMA.
🔷 Customization
Users have the flexibility to change the colors representing each risk level through the indicator settings. While the default colors are recommended for a standard view, users comfortable with custom color schemes can adjust according to their preference.
🔷 Usage
This indicator is beneficial for gauging the relative risk associated with current price movements compared to a historical average. It's most effective when used in conjunction with other technical analysis tools and market knowledge.
🔷 Limitations
While the Bubble Risk Indicator provides valuable insights, it should form part of a broader trading strategy. It assesses risk levels based on historical data and does not predict future market directions.
🔷 Conclusion
The Bubble Risk Indicator offers a nuanced and visually intuitive way to understand market risk levels, providing traders with an additional tool for informed decision-making.
🔷 Risk Disclaimer
Trading involves significant risk and is not suitable for every investor. The value of investments can fluctuate. Past performance is not indicative of future results. Always consider your circumstances and seek independent advice before making financial decisions. This indicator is provided for informational purposes only and is not intended as financial advice.
Logical Trading Indicator V.1Features of the Logical Trading Indicator V.1
ATR-Based Trailing Stop Loss
The Logical Trading Indicator V.1 utilizes the Average True Range (ATR) to implement a dynamic trailing stop loss. You can customize the sensitivity of your alerts by adjusting the ATR Multiple and ATR Period settings.
Higher ATR Multiple values create wider stops, while lower values result in tighter stops. This feature ensures that your trades are protected against adverse price movements. For best practice, use higher values on higher timeframes and lower values on lower term timeframes.
Bollinger Bands
The Logical Trading Indicator V.1 includes Bollinger Bands, which can be customized to use either a Simple Moving Average (SMA) or an Exponential Moving Average (EMA) as the basis.
You can adjust the length and standard deviation multiplier of the Bollinger Bands to fine-tune your strategy. The color of the basis line changes to green when price is above and red when price is below the line to represent the trend.
The bands show a range vs a single band that also represents when the price is in overbought and oversold ranges similar to an RSI. These bands also control the take profit signals.
You also have the ability to change the band colors as well as toggle them off, which only affects the view, they are still active which will still fire the take profit signals.
Momentum Indicator
Our indicator offers a momentum filter option that highlights market momentum directly on the candlesticks, identifying periods of bullish, bearish, or consolidation phases. You can enable or disable this filter as needed, providing valuable insights into market conditions.
By default, you will see the candlestick colors represent the momentum direction as green or red, and consolidation periods as white, but the filter on the BUY and SELL signals is not active. The view options and filter can be toggled on and off in the settings.
Buy and Sell Signals
The Logical Trading Indicator V.1 generates buy and sell signals based on a combination of ATR-based filtering, Bollinger Band basis crossover, and optional momentum conditions if selected in the settings. These signals help you make informed decisions about when to enter or exit a trade. You can also enable a consolidation filter to stay out of trades during tight ranges.
Basically a BUY signal fires when the price closes above the basis line, and the price meets or exceeds the ATR multiple from the previous candle length, which is also editable in the settings.
If the momentum filter is engaged, it will not fire BUY signals when in consolidation periods. It works just the opposite for SELL signals.
Take Profit Signals
We've integrated a Take Profit feature that helps you identify points to exit your trades with profits. The indicator marks Long Take Profit when prices close below the upper zone line of the Bollinger Bands after the previous candle closes inside the band, suggesting an optimal point to exit a long trade or consider a short position.
Conversely, Short Take Profit signals appear when prices close above the lower zone after the previous candle closes inside of it, indicating the right time to exit a short trade or contemplate a long position.
Alerts for Informed Trading
The Logical Trading Indicator V.1 comes equipped with alert conditions for buy signals, sell signals, take profit points, and more. Receive real-time notifications to your preferred devices or platforms to stay updated on market movements and trading opportunities.
PhantomFlow TrendDetectorThe TrendDetector calculates waves on the chart using the built-in ZigZag indicator and detects a trend change after the last high/low update occurs in a minimum sequence of non-updated highs/lows. This assumes a continuation of the trend for the subsequent update of the remaining high/low.
For trend determination:
When you see a pink or light yellow trend color, it means that a new trend may potentially be emerging right now, and you can join it almost at the beginning. So, if you see patterns from your trading system aligning with the TrendDetector indicator and they have the same direction, it further increases the likelihood of your plan working out.
In the case where the trend phase has a red or green color, it may indicate that the primary market impulse has already occurred, and therefore, joining the trend at this time may not be advisable.
For trade entry:
Additionally, you can use the indicator specifically for entering the market using market orders. Depending on the timeframe (the smaller the timeframe, the more confirmation candles are needed), you can open a trade when one trend replaces another at the close, for example, the second candle in the case of a 10-minute timeframe. Stop-loss can be placed under the signal candle, a local peak, or a reversal trend valley, a global peak, or a reversal trend valley. In the example above, the second option was used.
Settings
You cannot technically adjust anything in this indicator because all the logic is hardcoded. However, for a better chart visualization, after adding it to the chart, click on the three dots next to the indicator name, select "Visual order," and then "Bring to front".
Momentum Memory Indicator
The Momentum Memory Indicator (MMI) is a custom tool designed to predict future price movements based on the historical momentum of an asset. By calculating the Rate of Change (ROC) and then averaging it over a specified "memory" period, the MMI provides a prediction that reflects both recent and slightly older momentum data. The prediction is visualized as a histogram, with colors indicating the direction of the momentum.
**Parameters:**
1. **Rate of Change Period (ROC Period):** This parameter sets the period for the Rate of Change calculation, which measures the momentum of the asset. The default value is 14.
2. **Memory Period:** This parameter determines the period over which the average momentum is calculated. By considering momentum over this "memory" period, the indicator aims to provide a more stable and reliable prediction. The default value is 5.
**Logic:**
1. **Rate of Change (Momentum):** The ROC is calculated based on the asset's closing prices over the specified ROC period. It provides a measure of how much the price has changed over that period, indicating momentum.
2. **Average Momentum:** The average momentum is calculated by taking a simple moving average (SMA) of the ROC values over the memory period. This smoothens out the momentum data and provides a more stable value for prediction.
3. **Prediction:** The prediction is calculated by adjusting the current closing price based on the average momentum. This gives an estimate of where the price might be in the next period, assuming the momentum continues.
4. **Prediction Color:** The color of the prediction histogram is determined by the direction of the average momentum. A positive momentum results in a green histogram, while a negative momentum results in a red histogram.
**Plots:**
1. **Prediction (Histogram):** Represents the predicted price movement based on the average momentum. The direction and magnitude of the histogram bars provide insights into the expected price change. The color of the bars (green or red) indicates the direction of the momentum.
ATR + Momentum Shifts w/Take ProfitThis script is a technical analysis indicator designed to assist in identifying potential entry points and setting take profit levels in trading. It combines the Average True Range (ATR) indicator, momentum shifts, and customizable take profit levels to provide insights into potential market movements.
Differences from Currently Published Ones:
This script is unique due to its use of a combination of elements:
ATR and Momentum: The script combines the ATR indicator to provide dynamic support and resistance levels with the momentum indicator to identify shifts in the underlying momentum.
Customizable Take Profit Levels: It offers the ability to set take profit levels based on customizable multipliers of the ATR, helping traders manage potential profits.
How to Use:
ATR Bands: The script plots upper and lower ATR bands as potential dynamic support and resistance levels.
Shift Arrows: Arrows are plotted below bars for potential long entry opportunities (green triangle) and above bars for potential short entry opportunities (yellow triangle).
Take Profit Levels: The script also plots take profit levels both above and below the source price based on the ATR multipliers set in the inputs.
Markets and Conditions:
This script can be used across various financial markets, including stocks, forex, commodities, and cryptocurrencies. It's most effective in trending markets where momentum shifts can signal potential reversals or continuation of trends. Traders should consider the following conditions:
Trend Confirmation: Look for momentum shifts in the direction of the prevailing trend for higher probability setups.
Volatility: Higher volatility can amplify ATR movements and subsequently affect the placement of ATR bands and take profit levels.
Risk Management: Always implement proper risk management strategies to protect your capital.
Additional Considerations:
Customization: Traders can adjust input parameters like ATR length, momentum length, and take profit multipliers to match their trading style and market conditions.
Combining with Other Indicators: Consider using this indicator in conjunction with other technical indicators or chart patterns for confirmation.
Standardized MACD Heikin-Ashi TransformedThe Standardized MACD Heikin-Ashi Transformed (St. MACD) is an advanced indicator designed to overcome the limitations of the traditional MACD. It offers a more robust and standardized measure of momentum, making it comparable across different timeframes and securities. By incorporating the Heikin-Ashi transformation, the St. MACD provides a smoother visualization of trends and potential reversals, enhancing its utility for traders seeking a clearer view of the underlying market direction.
Methodology:
The calculation of St. MACD begins with the traditional MACD, which computes the difference between two exponential moving averages (EMAs) of the price. To address the issue of non-comparability across assets, the St. MACD normalizes its values using the exponential average of the price's height. This normalization process ensures that the indicator's readings are not influenced by the absolute price levels, allowing for objective and quantitatively defined comparisons of momentum strength.
Furthermore, St. MACD utilizes the Heikin-Ashi transformation, which involves deriving candles from the price data. These Heikin-Ashi candles provide a smoother representation of trends and help filter out noise in the market. A predictive curve of Heikin-Ashi candles within the St. MACD turns blue or red, indicating the prevailing trend direction. This feature enables traders to easily identify trend shifts and make better informed trading decisions.
Advantages:
St. MACD offers several key advantages over the traditional MACD-
Standardization: By normalizing the indicator's values, St. MACD becomes comparable across different assets and timeframes. This makes it a valuable tool for traders analyzing various markets and seeking consistent momentum measurements.
Heikin-Ashi Transformation: The integration of the Heikin-Ashi transformation smoothes out the indicator's fluctuations and enhances trend visibility. Traders can more easily identify trends and potential reversal points, improving their market analysis.
Quantifiable Momentum: St. MACD's key levels represent the strength of momentum, providing traders with a quantifiable framework to gauge the intensity of market movements. This feature helps identify periods of increased or decreased momentum.
Utility:
The St. MACD indicator offers versatile utility for traders-
Trend Identification: Traders can use the color-coded predictive curve of Heikin-Ashi candles to swiftly determine the prevailing trend direction. This aids in identifying potential entry and exit points in the market.
Reversal Signals: Colored extremes within the St. MACD signal potential price reversals, alerting traders to potential turning points in the market. This assists in making timely decisions during market inflection points.
Overbought/Oversold Conditions: The histogram version of St. MACD can be used in conjunction with the bands to detect short-term overbought or oversold market conditions, allowing traders to adjust their strategies accordingly.
In conclusion, this tool addresses the limitations of the traditional MACD by providing a standardized and comparable momentum indicator. Its incorporation of the Heikin-Ashi transformation enhances trend visibility and assists traders in making more informed decisions. With its quantifiable momentum measurements and various utility features, the St. MACD is a valuable tool for traders seeking a clearer and more objective view of market trends and reversals.
Key Features:
Display Modes: MACD, Histogram or Hybrid
Reversion Triangles by adjustable thresholds
Bar Coloring Methods: MidLine, Candles, Signal Cross, Extremities, Reversions
Example Charts:
-Traditional limitations-
-Comparisons across time and securities-
-Showcase-
See Also:
-Other Heikin-Ashi Transforms-
Momentum Oscillator, Divergences & Signals [TrendAlpha]The "Momentum, Real Time Divergences & Signals " indicator is designed to provide traders with insights into market momentum, identify potential divergences, and generate buy and sell signals. It offers a comprehensive set of features to assist traders in making informed trading decisions.
The indicator starts by calculating the momentum oscillator based on user-defined parameters.
- Traders can adjust the "Length" parameter to customize the sensitivity of the oscillator. The default value is set to 7, but it can be modified according to individual preferences.
- The "Source" parameter allows traders to select the input source for the oscillator calculation, with the default being the closing price of the asset.
- Traders have the option to display divergence lines by switching on the "Show Lines" parameter. This feature helps identify potential divergences between the oscillator and the price.
The oscillator is calculated using a two-step process. First, a smoothing function is applied to the source data using the "sma" (simple moving average) function. Then, the rate of change is computed over the specified length using the "mom" (momentum) function. Positive oscillator values indicate upward momentum, while negative values indicate downward momentum.
The indicator also generates buy and sell signals by identifying bullish and bearish divergences. A bullish divergence occurs when the oscillator is negative and crosses above zero, while a bearish divergence occurs when the oscillator is positive and crosses below zero. The indicator checks for specific conditions to confirm the divergences, such as comparing the current oscillator value with the previous value and validating the corresponding price action.
When a bullish or bearish divergence is detected, the indicator plots circles to highlight these signals on the chart. A green circle indicates a bullish signal, suggesting a potential buying opportunity, while a red circle indicates a bearish signal, suggesting a potential selling opportunity. In addition to circles, the indicator also displays labels to provide further clarity on the signals. A "Buy" label is shown for bullish signals, and a "Sell" label is shown for bearish signals.
To visually represent the divergences, the indicator plots lines connecting the corresponding points on the oscillator. A green line is drawn for bullish divergences, while a red line is drawn for bearish divergences. Traders can easily observe the divergence patterns and their relationships with the price action, aiding them in making trading decisions.
- The indicator also includes alert conditions for both bullish and bearish divergences. Traders can set up alerts to receive notifications when potential divergences occur, allowing them to take timely action.
ATR Momentum [QuantVue]ATR Momentum is a dynamic technical analysis tool designed to assess the momentum of a securities price movement. It utilizes the comparison between a faster short-term Average True Range (ATR) and a slower long-term ATR to determine whether momentum is increasing or decreasing.
This indicator visually represents the momentum relationship by plotting both ATR values as lines on a chart and applying color fill between the lines based on if momentum is increasing or decreasing.
When the short-term ATR is greater than the long-term ATR, representing increasing momentum, the area between them is filled with green.
Conversely, when the short-term ATR is less than the long-term ATR line, the area between them is filled with red. This red fill indicates decreasing momentum.
Don't hesitate to reach out with any questions or concerns.
We hope you enjoy!
Cheers.
ADX Momentum Shaded CandlesDescription:
The "ADX Momentum Shaded Candles" indicator (ADXMSC) is an overlay indicator that enhances candlestick charts by adding shading based on the momentum derived from the Average Directional Index (ADX). This indicator provides visual cues about the strength of bullish and bearish momentum by adjusting the transparency of the candlesticks.
How it Works:
The indicator utilizes the ADX indicator to calculate the values of +DI (Directional Indicator Plus) and -DI (Directional Indicator Minus) based on user-defined parameters. It then determines the transparency levels for the bullish and bearish candlesticks based on the calculated values of +DI and -DI. Higher values of +DI or -DI result in lower transparency levels, while lower values increase transparency.
Transparency Calculation:
The transparency of the bullish and bearish candlesticks is adjusted based on the values of +DI and -DI, which reflect the momentum of the price movement. Transparency is inversely proportional to these values, with higher values resulting in lower transparency. To calculate transparency, the indicator uses the formula 100 minus the value of +DI or -DI multiplied by 2. This ensures that higher values of +DI or -DI produce more opaque candlesticks.
Usage:
To effectively use the "ADX Momentum Shaded Candles" indicator (ADXMSC), follow these steps:
1. Apply the indicator to your chart by adding it from the available indicators.
2. Observe the candlesticks on the chart:
- Bullish candlesticks are represented by the original bullish color with adjusted transparency.
- Bearish candlesticks are represented by the original bearish color with adjusted transparency.
3. Analyze the transparency levels of the candlesticks to assess the strength of bullish and bearish momentum. Less transparent candlesticks indicate stronger momentum, while more transparent ones suggest weaker momentum.
4. Combine the visual information from the shaded candlesticks with other technical analysis tools, such as support and resistance levels, trend lines, or oscillators, to confirm potential trade opportunities.
5. Customize the indicator's parameters, such as the ADX length and smoothing, to suit your trading preferences.
6. Implement appropriate risk management strategies, including setting stop-loss orders and position sizing, to manage your trades effectively and protect your capital.
Histogram Momentum Shaded CandlesDescription:
The Histogram Momentum Shaded Candles indicator (HMSC) is a powerful technical analysis tool that combines the concepts of the MACD (Moving Average Convergence Divergence) indicator and shaded candlestick visualization. It provides insights into momentum and trend strength by representing the MACD histogram as shaded candles on the chart.
How it Works:
The HMSC indicator calculates the MACD (Moving Average Convergence Divergence) using user-defined parameters such as the fast length, slow length, source, signal smoothing, and moving average types. It then calculates the MACD histogram by subtracting the signal line from the MACD line. The indicator transforms the histogram values into transparency levels for the shaded candles, representing bullish and bearish momentum.
Usage:
To effectively utilize the Histogram Momentum Shaded Candles indicator, follow these steps:
1. Apply the HMSC indicator to your chart by adding it from the available indicators.
2. Customize the MACD settings such as the fast length, slow length, source, signal smoothing, and moving average types according to your trading preferences.
3. Observe the shaded candles plotted on the chart:
- Bullish shaded candles (green by default) indicate positive momentum and potential buying pressure.
- Bearish shaded candles (red by default) indicate negative momentum and potential selling pressure.
4. Assess the intensity of the shaded candles:
5. Shading intensity is determined by the magnitude of the MACD histogram, with higher values resulting in more opaque candles.
6. The shading intensity reflects the strength of momentum and can help identify significant shifts in price action.
7. Combine the analysis of shaded candles with traditional candlestick patterns, trend lines, support and resistance levels, and other technical indicators to validate potential trade setups.
8. Implement appropriate risk management strategies, including setting stop-loss orders and position sizing, to manage your trades effectively and protect your capital.
Colorful Moving Averageswhat is Colorful Moving Averages?
This indicator allows you to use your favorite moving averages in their advanced form.
what it does?
It gives you easy access to the following information with a single indicator: the direction and momentum of the price,
rate of change of momentum (acceleration),
time-dependent change in momentum,
and all the other information a moving average provides.
it paints the selected moving average type according to the momentum it has, and also shows the momentum and acceleration values in a table. colors are interpreted as follows: the color of the moving average is red, the momentum is negative; A green color means the momentum is positive, and a yellow color means the momentum is 0. As the momentum changes, the moving average takes on different shades of these 3 colors. how it actually works can be easily understood at a glance.
"Δ" sign indicates momentum compressed between 100 and -100.
"Γ" sign indicates the momentum of the momentum, that is the acceleration. its values are compressed between 100 and -100.
how it does it?
it uses this formulas:
how to use it?
First, select the moving average type you want to use. then set the length and source. Now, with a single indicator, you can observe both the distance of the price from the mean, its instantaneous momentum relative to the last candle by looking at the symbol "Δ", the current change of momentum by looking at the symbol "Γ", and the time-dependent change in its momentum by looking at the colors. you can also see the maximum and minimum points where the momentum is equal to 0.
Multi indicators tableThis is a comprehensive trading tool that presents an overview of the market in a tabular format. It consists of five distinct categories of trading indicators : Volatility, Trend, Momentum, Reversal, and Volume. Each category includes a series of indicators that are widely used in the trading communauty.
The Volatility category includes the Average True Range (ATR) and Bollinger Bands indicators. The Trend category comprises the Average Directional Index (ADX), four Exponential Moving Averages (EMAs), Aroon, Parabolic SAR, and the Supertrend. The Momentum category includes the Stochastic Relative Strength Index (StochRSI), Money Flow Index (MFI), Williams %R, Relative Strength Index (RSI), and Commodity Channel Index (CCI). The Reversal category includes Parabolic SAR, Moving Average Convergence Divergence (MACD), and PP Supertrend. Finally, the Volume category includes the Volume Exponential Moving Average (EMA) indicator.
The indicators states are easily readable, the indicator case is colored based on his actual state. A bullish color (green by default), a bearish color (red by default),
a very bullish color (dark green by default), a very bearish color (dark red by default) and a neutral color (gray by default) displayed when the indicator doesn't give us a clear signal. Some indicators do not have a very bullish or very bearish state. Concerning volatility indicators, the bullish color indicates high volatility, the bearish color indicates low volatility, and the neutral color indicates normal volatility.
Most of the indicators displayed in the table are customizable, and traders can choose to hide the categories they don't want to use. The Indicator provides a quick and easily readable view on the market and allows traders to reduce the number of indicators on their chart making it lighter and more readable.
