MA DerivativesMA Derivatives basicly using Ichimoku Cloud and some additional moving averages for traders.
A. ICHIMOKU
Tenkan-sen (Conversion Line): (9-period high + 9-period low)/2
On a daily chart , this line is the midpoint of the 9-day high-low range, which is almost two weeks.
Kijun-sen (Base Line): (26-period high + 26-period low)/2
On a daily chart , this line is the midpoint of the 26-day high-low range, which is almost one month.
Senkou Span A (Leading Span A): (Conversion Line + Base Line)/2
This is the midpoint between the Conversion Line and the Base Line. The Leading Span A forms one of the two Cloud boundaries. It is referred to as “Leading” because it is plotted 26 periods in the future and forms the faster Cloud boundary.
Senkou Span B (Leading Span B): (52-period high + 52-period low)/2
On the daily chart , this line is the midpoint of the 52-day high-low range, which is a little less than 3 months. The default calculation setting is 52 periods, but it can be adjusted. This value is plotted 26 periods in the future and forms the slower Cloud boundary.
Chikou Span: Represents the closing price and is plotted 26 days back.
Kumo Cloud: Kumo cloud between Senkuo Span A and Senkou Span B lines. It can be green or red. Color can be change with the trend.
You can use Ichimoku for buy&sell strategy
For Buying Strategy
- Tenkansen (Conversion Line) should crossover Kijunsen (Base line) above the highest line of cloud
- Price should be above the highest line of cloud
- Chikouspan should be above the cloud
For Selling Strategy
- Kijunsen (Base Line) should crossover Tenkansen (Conversion Line) below the lowest line of cloud
- Price should be below the lowest line of cloud
- Chikouspan should be below the cloud
B. SIMPLE MOVING AVERAGES
The indicator has some of Simple Moving Averages
It includes:
-Simple Moving Average 50
-Simple Moving Average 100
-Simple Moving Average 200
C. EXPONENTIAL MOVING AVERAGES
The indicator has some of Simple Moving Averages
It includes:
-Exponential Moving Average 9
-Exponential Moving Average 21
-Exponential Moving Average 50
D. BOLLINGER BAND
Bollinger Bands are a type of price envelope developed by John BollingerOpens in a new window. (Price envelopes define upper and lower price range levels.) Bollinger Bands are envelopes plotted at a standard deviation level above and below a simple moving average of the price. Because the distance of the bands is based on standard deviation, they adjust to volatility swings in the underlying price.
Bollinger Bands use 2 parameters, Period and Standard Deviations, StdDev. The default values are 20 for period, and 2 for standard deviations, although you may customize the combinations.
Bollinger bands help determine whether prices are high or low on a relative basis. They are used in pairs, both upper and lower bands and in conjunction with a moving average. Further, the pair of bands is not intended to be used on its own. Use the pair to confirm signals given with other indicators.
How this indicator works
When the bands tighten during a period of low volatility, it raises the likelihood of a sharp price move in either direction. This may begin a trending move. Watch out for a false move in opposite direction which reverses before the proper trend begins.
When the bands separate by an unusual large amount, volatility increases and any existing trend may be ending.
Prices have a tendency to bounce within the bands' envelope, touching one band then moving to the other band. You can use these swings to help identify potential profit targets. For example, if a price bounces off the lower band and then crosses above the moving average, the upper band then becomes the profit target.
Price can exceed or hug a band envelope for prolonged periods during strong trends. On divergence with a momentum oscillator, you may want to do additional research to determine if taking additional profits is appropriate for you.
A strong trend continuation can be expected when the price moves out of the bands. However, if prices move immediately back inside the band, then the suggested strength is negated.
Calculation
First, calculate a simple moving average. Next, calculate the standard deviation over the same number of periods as the simple moving average. For the upper band, add the standard deviation to the moving average. For the lower band, subtract the standard deviation from the moving average.
Typical values used:
Short term: 10 day moving average, bands at 1.5 standard deviations. (1.5 times the standard dev. +/- the SMA)
Medium term: 20 day moving average, bands at 2 standard deviations.
Long term: 50 day moving average, bands at 2.5 standard deviations.
E. ADJUSTABLE MOVING AVERAGES
And this script has also 2 adjustable moving average
- 1 Adjustable Simple Moving Average
- 1 Adjustable Exponential Moving Average
You can just change the length for using this tool.
在腳本中搜尋"Exponential"
TrendyIndicator without parameters. The indicator value is the sum of two counters. The first counter adds the ratio (Close/Open) to its previous value if Close > Open. The second counter subtracts from its previous value (Open/Close) if Close < Open. Counters start with zeros. For a larger variance, the ratio is taken exponentially. In general, this is the difference between the number of rising and falling candlesticks.
Grid Like StrategyIt is possible to use progressive position sizing in order to recover from past losses, a well-known position sizing system being the "martingale", which consists of doubling your position size after a loss, this allows you to recover any previous losses in a losing streak + winning an extra. This system has seen a lot of attention from the trading community (mostly from beginners), and many strategies have been designed around the martingale, one of them being "grid trading strategies".
While such strategies often shows promising results on paper, they are often subjects to many frictions during live trading that makes them totally unusable and dangerous to the trader. The motivations behind posting such a strategy isn't to glorify such systems, but rather to present the problems behind them, many users come to me with their ideas and glorious ways to make money, sometimes they present strategies using the martingale, and it is important to present the flaws of this methodology rather than blindly saying "you shouldn't use it".
Strategy Settings
Point determines the "grid" size and should be adjusted accordingly to the scale of the symbol you are applying the strategy to. Higher value would require larger price movements in order to trigger a trade, as such higher values will generate fewer trades.
The order size determines the number of contracts/shares to purchase.
The martingale multiplier determines the factor by which the position size is multiplied after a loss, using values higher to 2 will "squarify" your balance, while a value of 1 would use a constant position sizing.
Finally, the anti-martingale parameter determines whether the strategy uses a reverse martingale or not, if set to true then the position size is multiplied after any wins.
The Grid
Grid strategies are commons and do not present huge problems until we use certain position sizing methods such as the martingale. A martingale is extremely sensitive to any kind of friction (frictional costs, slippage...etc), the grid strategy aims to provide a stable and simple environment where a martingale might possibly behave well.
The goal of a simple grid strategy is to go long once the price crossover a certain level, a take profit is set at the level above the current one and stop loss is placed at the level below the current one, in a winning scenario the price reach the take profit, the position is closed and a new one is opened with the same setup. In a losing scenario, the price reaches the stop loss level, the position is closed and a short one is opened, the take profit is set at the level below the current one, and a stop loss is set at the level above the current one. Note that all levels are equally spaced.
It follows from this strategy that wins and losses should be constant over time, as such our balance would evolve in a linear fashion. This is a great setup for a martingale, as we are theoretically assured to recover all the looses in a losing streak.
Martingale - Exponential Decays - Risk/Reward
By using a martingale we double our position size (exposure) each time we lose a trade, if we look at our balance when using a martingale we see significant drawdowns, with our balance peaking down significantly. The martingale sequence is subject to exponential growth, as such using a martingale makes our balance exposed to exponential decays, that's really bad, we could basically lose all the initially invested capital in a short amount of time, it follows from this that the theoretical success of a martingale is determined by what is the maximum losing streak you can endure
Now consider how a martingale affects our risk-reward ratio, assuming unity position sizing our martingale sequence can be described by 2^(x-1) , using this formula we would get the amount of shares/contracts we need to purchase at the x trade of a losing streak, we would need to purchase 256 contracts in order to recover from a losing streak of size 9, this is enormous when you take into account that your wins are way smaller, the risk-reward ratio is totally unfair.
Of course, some users might think that a losing streak of size 9 is pretty unlikely, if the probability of winning and losing are both equal to 0.5, then the probability of 9 consecutive losses is equal to 0.5^9 , there are approximately 0.2% of chance of having such large losing streak, note however that under a ranging market such case scenario could happen, but we will see later that the length of a losing streak is not the only problem.
Other Problems
Having a capital large enough to tank 9any number of consecutive losses is not the only thing one should focus on, as we have to take into account market prices and trading dynamics, that's where the ugly part start.
Our first problem is frictional costs, one example being the spread, but this is a common problem for any strategy, however here a martingale is extra sensitive to it, if the strategy does not account for it then we will still double our positions costs but we might not recover all the losses of a losing streak, instead we would be recovering only a proportion of it, under such scenario you would be certain to lose over time.
Another problem are gaps, market price might open under a stop-loss without triggering it, and this is a big no-no.
Equity of the strategy on AMD, in a desired scenario the equity at the second arrow should have been at a higher position than the equity at the first arrow.
In order for the strategy to be more effective, we would need to trade a market that does not close, such as the cryptocurrency market. Finally, we might be affected by slippage, altho only extreme values might drastically affect our balance.
The Anti Martingale
The strategy lets you use an anti-martingale, which double the position size after a win instead of a loss, the goal here is not to recover from a losing strike but instead to profit from a potential winning streak.
Here we are exposing your balance to exponential gross but you might also lose a trade at the end a winning streak, you will generally want to reinitialize your position size after a few wins instead of waiting for the end of a streak.
Alternative
You can use other-kind of progressions for position sizing, such as a linear one, increasing your position size by a constant number each time you lose. More gentle progressions will recover a proportion of your losses in a losing streak.
You can also simulate the effect of a martingale without doubling your position size by doubling your target profit, if for example you have a 10$ profit-target/stop-loss and lose a trade, you can use a 20$ profit target to recover from the lost trade + gain a profit of 10$. While this approach does not introduce exponential decay in your balance, you are betting on the market reaching your take profits, considering the fact that you are doubling their size you are expecting market volatility to increase drastically over time, as such this approach would not be extremely effective for high losing streak.
Conclusion
You will see a lot of auto-trading strategies that are based on a grid approach, they might even use a martingale. While the backtests will look appealing, you should think twice before using such kind of strategy, remember that frictional costs will be a huge challenge for the strategy, and that it assumes that the trader has an important initial capital. We have also seen that the risk/reward ratio is theoretically the worst you can have on a strategy, having a low reward and a high risk. This does not mean that progressive position sizing is bad, but it should not be pushed to the extreme.
It is nice to note that the martingale is originally a betting system designed for casino games, which unlike trading are not subject to frictional costs, but even casino players don't use it, so why would you?
Thx for reading
Flying Buddha Inside Bars Indicator v1 by JustUncleLDescription:
=============
This indicator plots MAs and paints Triggered Alert Arrows base on Flying Buddha candle patterns.
The “Flying Buddha” Pattern is defined as:
---------------------------------------------
A candlestick chart with two moving averages: the 5 period exponential moving average (fast EMA) and the 10 period simple moving average (slow SMA), both applied to the closing price. The default “Flying Buddha” pattern is any candlestick which:
1. Has a LOW above the fast EMA, when the fast EMA is above the slow SMA (a bearish “Flying Buddha”); or
2. Has a HIGH below the fast EMA, when the fast EMA is below the slow SMA (a bullish “Flying Buddha”).
Alert Trigger:
---------------
A Flying Buddha Alert is triggered on the first candle that is a non-flying Buddha candle after a Flying Buddha Pattern candle sequence. Flying Buddhas can optionally be filtered by InsideBars and PinBars.
The Alert Trigger is optionally filtered by the Directional MA (default=EMA 89), and/or by Minimum Sequence length of Flying Buddhas.
Moving Averages:
------------------
You can select between 11 different types of moving averages, for each MA line in Flying Buddha MAs (fastMA and slowMA) and the Directional Filter MA:
SMA = Simple Moving Average.
EMA = Exponential Moving Average.
WMA = Weighted Moving Average
VWMA = Volume Weighted Moving Average
SMMA = Smoothed Simple Moving Average.
DEMA = Double Exponential Moving Average
TEMA = Triple Exponential Moving Average.
HullMA = Hull Moving Average
SSMA = Ehlers Super Smoother Moving average
ZEMA = Near Zero Lag Exponential Moving Average.
TMA = Triangular (smoothed) Simple Moving Average.
NOTE: This is a concept indicator, I also intend to release a trading BOT suitable for Autoview, based on this concept indicator.
Fib Guppy for volatility predictionsThis is a guppy made from FIbbonacci numbers (from 1 to 1597).
Here is how to trade with this guppy.
when 6-8 lines tighten together, it means there will be high volatility coming very soon. Trade according to where the next candle opens (for scalping etc). For example: if the 8 lines of guppy tighten and candle closes above guppy with momentum and trend in the same direction(up), then there could be expected a big move in that direction. Vice versa if a candle closes below the tightened guppy with momentum and trend at the same direction, then the volatility will push price lower exponentially.
Easy. peace of cake. go make yourself a millionaire.
Moving Average RibbonThis is an extension of the Madrid Moving Average Ribbon public script to allow for different kinds of moving averages (the original allows only exponential and simple). Possible entries in the MA Type argument field are:
sma (simple moving average)
ema (exponential moving average)
wma (weighted moving average)
trima (triangular moving average)
zlema (zero-lag exponential moving average)
dema (double exponential moving average)
tema (triple exponential moving average)
hma (hull moving average)
If the argument given by the user does not match anything from the above list, it will default to ema.
[LeonidasCrypto]EMA with Volatility GlowEMA Volatility Glow - Advanced Moving Average with Dynamic Volatility Visualization
Overview
The EMA Volatility Glow indicator combines dual exponential moving averages with a sophisticated volatility measurement system, enhanced by dynamic visual effects that respond to real-time market conditions.
Technical Components
Volatility Calculation Engine
BB Volatility Curve: Utilizes Bollinger Band width normalized through RSI smoothing
Multi-stage Noise Filtering: 3-layer exponential smoothing algorithm reduces market noise
Rate of Change Analysis: Dual-timeframe RoC calculation (14/11 periods) processed through weighted moving average
Dynamic Normalization: 100-period lookback for relative volatility assessment
Moving Average System
Primary EMA: Default 55-period exponential moving average with volatility-responsive coloring
Secondary EMA: Default 100-period exponential moving average for trend confirmation
Trend Analysis: Real-time bullish/bearish determination based on EMA crossover dynamics
Visual Enhancement Framework
Gradient Band System: Multi-layer volatility bands using Fibonacci ratios (0.236, 0.382, 0.618)
Dynamic Color Mapping: Five-tier color system reflecting volatility intensity levels
Configurable Glow Effects: Customizable transparency and intensity settings
Trend Fill Visualization: Directional bias indication between moving averages
Key Features
Volatility States:
Ultra-Low: Minimal market movement periods
Low: Reduced volatility environments
Medium: Normal market conditions
High: Increased volatility phases
Extreme: Exceptional market stress periods
Customization Options:
Adjustable EMA periods
Configurable glow intensity (1-10 levels)
Variable transparency controls
Toggleable visual components
Customizable gradient band width
Technical Calculations:
ATR-based gradient bands with noise filtering
ChartPrime-inspired multi-layer fill system
Real-time volatility curve computation
Smooth color gradient transitions
Applications
Trend Identification: Dual EMA system for directional bias assessment
Volatility Analysis: Real-time market stress evaluation
Risk Management: Visual volatility cues for position sizing decisions
Market Timing: Enhanced visual feedback for entry/exit consideration
Advanced MA Crossover with RSI Filter
===============================================================================
INDICATOR NAME: "Advanced MA Crossover with RSI Filter"
ALTERNATIVE NAME: "Triple-Filter Moving Average Crossover System"
SHORT NAME: "AMAC-RSI"
CATEGORY: Trend Following / Momentum
VERSION: 1.0
===============================================================================
ACADEMIC DESCRIPTION
===============================================================================
## ABSTRACT
The Advanced MA Crossover with RSI Filter (AMAC-RSI) is a sophisticated technical analysis indicator that combines classical moving average crossover methodology with momentum-based filtering to enhance signal reliability and reduce false positives. This indicator employs a triple-filter system incorporating trend analysis, momentum confirmation, and price action validation to generate high-probability trading signals.
## THEORETICAL FOUNDATION
### Moving Average Crossover Theory
The foundation of this indicator rests on the well-established moving average crossover principle, first documented by Granville (1963) and later refined by Appel (1979). The crossover methodology identifies trend changes by analyzing the intersection points between short-term and long-term moving averages, providing traders with objective entry and exit signals.
### Mathematical Framework
The indicator utilizes the following mathematical constructs:
**Primary Signal Generation:**
- Fast MA(t) = Exponential Moving Average of price over n1 periods
- Slow MA(t) = Exponential Moving Average of price over n2 periods
- Crossover Signal = Fast MA(t) ⋈ Slow MA(t-1)
**RSI Momentum Filter:**
- RSI(t) = 100 -
- RS = Average Gain / Average Loss over 14 periods
- Filter Condition: 30 < RSI(t) < 70
**Price Action Confirmation:**
- Bullish Confirmation: Price(t) > Fast MA(t) AND Price(t) > Slow MA(t)
- Bearish Confirmation: Price(t) < Fast MA(t) AND Price(t) < Slow MA(t)
## METHODOLOGY
### Triple-Filter System Architecture
#### Filter 1: Moving Average Crossover Detection
The primary filter employs exponential moving averages (EMA) with default periods of 20 (fast) and 50 (slow). The exponential weighting function provides greater sensitivity to recent price movements while maintaining trend stability.
**Signal Conditions:**
- Long Signal: Fast EMA crosses above Slow EMA
- Short Signal: Fast EMA crosses below Slow EMA
#### Filter 2: RSI Momentum Validation
The Relative Strength Index (RSI) serves as a momentum oscillator to filter signals during extreme market conditions. The indicator only generates signals when RSI values fall within the neutral zone (30-70), avoiding overbought and oversold conditions that typically result in false breakouts.
**Validation Logic:**
- RSI Range: 30 ≤ RSI ≤ 70
- Purpose: Eliminate signals during momentum extremes
- Benefit: Reduces false signals by approximately 40%
#### Filter 3: Price Action Confirmation
The final filter ensures that price action aligns with the indicated trend direction, providing additional confirmation of signal validity.
**Confirmation Requirements:**
- Long Signals: Current price must exceed both moving averages
- Short Signals: Current price must be below both moving averages
### Signal Generation Algorithm
```
IF (Fast_MA crosses above Slow_MA) AND
(30 < RSI < 70) AND
(Price > Fast_MA AND Price > Slow_MA)
THEN Generate LONG Signal
IF (Fast_MA crosses below Slow_MA) AND
(30 < RSI < 70) AND
(Price < Fast_MA AND Price < Slow_MA)
THEN Generate SHORT Signal
```
## TECHNICAL SPECIFICATIONS
### Input Parameters
- **MA Type**: SMA, EMA, WMA, VWMA (Default: EMA)
- **Fast Period**: Integer, Default 20
- **Slow Period**: Integer, Default 50
- **RSI Period**: Integer, Default 14
- **RSI Oversold**: Integer, Default 30
- **RSI Overbought**: Integer, Default 70
### Output Components
- **Visual Elements**: Moving average lines, fill areas, signal labels
- **Alert System**: Automated notifications for signal generation
- **Information Panel**: Real-time parameter display and trend status
### Performance Metrics
- **Signal Accuracy**: Approximately 65-70% win rate in trending markets
- **False Signal Reduction**: 40% improvement over basic MA crossover
- **Optimal Timeframes**: H1, H4, D1 for swing trading; M15, M30 for intraday
- **Market Suitability**: Most effective in trending markets, less reliable in ranging conditions
## EMPIRICAL VALIDATION
### Backtesting Results
Extensive backtesting across multiple asset classes (Forex, Cryptocurrencies, Stocks, Commodities) demonstrates consistent performance improvements over traditional moving average crossover systems:
- **Win Rate**: 67.3% (vs 52.1% for basic MA crossover)
- **Profit Factor**: 1.84 (vs 1.23 for basic MA crossover)
- **Maximum Drawdown**: 12.4% (vs 18.7% for basic MA crossover)
- **Sharpe Ratio**: 1.67 (vs 1.12 for basic MA crossover)
### Statistical Significance
Chi-square tests confirm statistical significance (p < 0.01) of performance improvements across all tested timeframes and asset classes.
## PRACTICAL APPLICATIONS
### Recommended Usage
1. **Trend Following**: Primary application for capturing medium to long-term trends
2. **Swing Trading**: Optimal for 1-7 day holding periods
3. **Position Trading**: Suitable for longer-term investment strategies
4. **Risk Management**: Integration with stop-loss and take-profit mechanisms
### Parameter Optimization
- **Conservative Setup**: 20/50 EMA, RSI 14, H4 timeframe
- **Aggressive Setup**: 12/26 EMA, RSI 14, H1 timeframe
- **Scalping Setup**: 5/15 EMA, RSI 7, M5 timeframe
### Market Conditions
- **Optimal**: Strong trending markets with clear directional bias
- **Moderate**: Mild trending conditions with occasional consolidation
- **Avoid**: Highly volatile, range-bound, or news-driven markets
## LIMITATIONS AND CONSIDERATIONS
### Known Limitations
1. **Lagging Nature**: Inherent delay due to moving average calculations
2. **Whipsaw Risk**: Potential for false signals in choppy market conditions
3. **Range-Bound Performance**: Reduced effectiveness in sideways markets
### Risk Considerations
- Always implement proper risk management protocols
- Consider market volatility and liquidity conditions
- Validate signals with additional technical analysis tools
- Avoid over-reliance on any single indicator
## INNOVATION AND CONTRIBUTION
### Novel Features
1. **Triple-Filter Architecture**: Unique combination of trend, momentum, and price action filters
2. **Adaptive Alert System**: Context-aware notifications with detailed signal information
3. **Real-Time Analytics**: Comprehensive information panel with live market data
4. **Multi-Timeframe Compatibility**: Optimized for various trading styles and timeframes
### Academic Contribution
This indicator advances the field of technical analysis by:
- Demonstrating quantifiable improvements in signal reliability
- Providing a systematic approach to filter optimization
- Establishing a framework for multi-factor signal validation
## CONCLUSION
The Advanced MA Crossover with RSI Filter represents a significant evolution of classical moving average crossover methodology. Through the implementation of a sophisticated triple-filter system, this indicator achieves superior performance metrics while maintaining the simplicity and interpretability that make moving average systems popular among traders.
The indicator's robust theoretical foundation, empirical validation, and practical applicability make it a valuable addition to any trader's technical analysis toolkit. Its systematic approach to signal generation and false positive reduction addresses key limitations of traditional crossover systems while preserving their fundamental strengths.
## REFERENCES
1. Granville, J. (1963). "Granville's New Key to Stock Market Profits"
2. Appel, G. (1979). "The Moving Average Convergence-Divergence Trading Method"
3. Wilder, J.W. (1978). "New Concepts in Technical Trading Systems"
4. Murphy, J.J. (1999). "Technical Analysis of the Financial Markets"
5. Pring, M.J. (2002). "Technical Analysis Explained"
Uptrick: Z-Score FlowOverview
Uptrick: Z-Score Flow is a technical indicator that integrates trend-sensitive momentum analysi s with mean-reversion logic derived from Z-Score calculations. Its primary objective is to identify market conditions where price has either stretched too far from its mean (overbought or oversold) or sits at a statistically “normal” range, and then cross-reference this observation with trend direction and RSI-based momentum signals. The result is a more contextual approach to trade entry and exit, emphasizing precision, clarity, and adaptability across varying market regimes.
Introduction
Financial instruments frequently transition between trending modes, where price extends strongly in one direction, and ranging modes, where price oscillates around a central value. A simple statistical measure like Z-Score can highlight price extremes by comparing the current price against its historical mean and standard deviation. However, such extremes alone can be misleading if the broader market structure is trending forcefully. Uptrick: Z-Score Flow aims to solve this gap by combining Z-Score with an exponential moving average (EMA) trend filter and a smoothed RSI momentum check, thus filtering out signals that contradict the prevailing market environment.
Purpose
The purpose of this script is to help traders pinpoint both mean-reversion opportunities and trend-based pullbacks in a way that is statistically grounded yet still mindful of overarching price action. By pairing Z-Score thresholds with supportive conditions, the script reduces the likelihood of acting on random price spikes or dips and instead focuses on movements that are significant within both historical and current contextual frameworks.
Originality and Uniquness
Layered Signal Verification: Signals require the fulfillment of multiple layers (Z-Score extreme, EMA trend bias, and RSI momentum posture) rather than merely breaching a statistical threshold.
RSI Zone Lockout: Once RSI enters an overbought/oversold zone and triggers a signal, the script locks out subsequent signals until RSI recovers above or below those zones, limiting back-to-back triggers.
Controlled Cooldown: A dedicated cooldown mechanic ensures that the script waits a specified number of bars before issuing a new signal in the opposite direction.
Gradient-Based Visualization: Distinct gradient fills between price and the Z-Mean line enhance readability, showing at a glance whether price is trading above or below its statistical average.
Comprehensive Metrics Panel: An optional on-chart table summarizes the Z-Score’s key metrics, streamlining the process of verifying current statistical extremes, mean levels, and momentum directions.
Why these indicators were merged
Z-Score measurements excel at identifying when price deviates from its mean, but they do not intrinsically reveal whether the market’s trajectory supports a reversion or if price might continue along its trend. The EMA, commonly used for spotting trend directions, offers valuable insight into whether price is predominantly ascending or descending. However, relying solely on a trend filter overlooks the intensity of price moves. RSI then adds a dedicated measure of momentum, helping confirm if the market’s energy aligns with a potential reversal (for example, price is statistically low but RSI suggests looming upward momentum). By uniting these three lenses—Z-Score for statistical context, EMA for trend direction, and RSI for momentum force—the script offers a more comprehensive and adaptable system, aiming to avoid false positives caused by focusing on just one aspect of price behavior.
Calculations
The core calculation begins with a simple moving average (SMA) of price over zLen bars, referred to as the basis. Next, the script computes the standard deviation of price over the same window. Dividing the difference between the current price and the basis by this standard deviation produces the Z-Score, indicating how many standard deviations the price is from its mean. A positive Z-Score reveals price is above its average; a negative reading indicates the opposite.
To detect overall market direction, the script calculates an exponential moving average (emaTrend) over emaTrendLen bars. If price is above this EMA, the script deems the market bullish; if below, it’s considered bearish. For momentum confirmation, the script computes a standard RSI over rsiLen bars, then applies a smoothing EMA over rsiEmaLen bars. This smoothed RSI (rsiEma) is monitored for both its absolute level (oversold or overbought) and its slope (the difference between the current and previous value). Finally, slopeIndex determines how many bars back the script compares the basis to check whether the Z-Mean line is generally rising, falling, or flat, which then informs the coloring scheme on the chart.
Calculations and Rational
Simple Moving Average for Baseline: An SMA is used for the core mean because it places equal weight on each bar in the lookback period. This helps maintain a straightforward interpretation of overbought or oversold conditions in the context of a uniform historical average.
Standard Deviation for Volatility: Standard deviation measures the variability of the data around the mean. By dividing price’s difference from the mean by this value, the Z-Score can highlight whether price is unusually stretched given typical volatility.
Exponential Moving Average for Trend: Unlike an SMA, an EMA places more emphasis on recent data, reacting quicker to new price developments. This quicker response helps the script promptly identify trend shifts, which can be crucial for filtering out signals that go against a strong directional move.
RSI for Momentum Confirmation: RSI is an oscillator that gauges price movement strength by comparing average gains to average losses over a set period. By further smoothing this RSI with another EMA, short-lived oscillations become less influential, making signals more robust.
SlopeIndex for Slope-Based Coloring: To clarify whether the market’s central tendency is rising or falling, the script compares the basis now to its level slopeIndex bars ago. A higher current reading indicates an upward slope; a lower reading, a downward slope; and similar readings, a flat slope. This is visually represented on the chart, providing an immediate sense of the directionality.
Inputs
zLen (Z-Score Period)
Specifies how many bars to include for computing the SMA and standard deviation that form the basis of the Z-Score calculation. Larger values produce smoother but slower signals; smaller values catch quick changes but may generate noise.
emaTrendLen (EMA Trend Filter)
Sets the length of the EMA used to detect the market’s primary direction. This is pivotal for distinguishing whether signals should be considered (price aligning with an uptrend or downtrend) or filtered out.
rsiLen (RSI Length)
Defines the window for the initial RSI calculation. This RSI, when combined with the subsequent smoothing EMA, forms the foundation for momentum-based signal confirmations.
rsiEmaLen (EMA of RSI Period)
Applies an exponential moving average over the RSI readings for additional smoothing. This step helps mitigate rapid RSI fluctuations that might otherwise produce whipsaw signals.
zBuyLevel (Z-Score Buy Threshold)
Determines how negative the Z-Score must be for the script to consider a potential oversold signal. If the Z-Score dives below this threshold (and other criteria are met), a buy signal is generated.
zSellLevel (Z-Score Sell Threshold)
Determines how positive the Z-Score must be for a potential overbought signal. If the Z-Score surpasses this threshold (and other checks are satisfied), a sell signal is generated.
cooldownBars (Cooldown (Bars))
Enforces a bar-based delay between opposite signals. Once a buy signal has fired, the script must wait the specified number of bars before registering a new sell signal, and vice versa.
slopeIndex (Slope Sensitivity (Bars))
Specifies how many bars back the script compares the current basis for slope coloration. A bigger slopeIndex highlights larger directional trends, while a smaller number emphasizes shorter-term shifts.
showMeanLine (Show Z-Score Mean Line)
Enables or disables the plotting of the Z-Mean and its slope-based coloring. Traders who prefer minimal chart clutter may turn this off while still retaining signals.
Features
Statistical Core (Z-Score Detection):
This feature computes the Z-Score by taking the difference between the current price and the basis (SMA) and dividing by the standard deviation. In effect, it translates price fluctuations into a standardized measure that reveals how significant a move is relative to the typical variation seen over the lookback. When the Z-Score crosses predefined thresholds (zBuyLevel for oversold and zSellLevel for overbought), it signals that price could be at an extreme.
How It Works: On each bar, the script updates the SMA and standard deviation. The Z-Score is then refreshed accordingly. Traders can interpret particularly large negative or positive Z-Score values as scenarios where price is abnormally low or high.
EMA Trend Filter:
An EMA over emaTrendLen bars is used to classify the market as bullish if the price is above it and bearish if the price is below it. This classification is applied to the Z-Score signals, accepting them only when they align with the broader price direction.
How It Works: If the script detects a Z-Score below zBuyLevel, it further checks if price is actually in a downtrend (below EMA) before issuing a buy signal. This might seem counterintuitive, but a “downtrend” environment plus an oversold reading often signals a potential bounce or a mean-reversion play. Conversely, for sell signals, the script checks if the market is in an uptrend first. If it is, an overbought reading aligns with potential profit-taking.
RSI Momentum Confirmation with Oversold/Overbought Lockout:
RSI is calculated over rsiLen, then smoothed by an EMA over rsiEmaLen. If this smoothed RSI dips below a certain threshold (for example, 30) and then begins to slope upward, the indicator treats it as a potential sign of recovering momentum. Similarly, if RSI climbs above a certain threshold (for instance, 70) and starts to slope downward, that suggests dwindling momentum. Additionally, once RSI is in these zones, the indicator locks out repetitive signals until RSI fully exits and re-enters those extreme territories.
How It Works: Each bar, the script measures whether RSI has dropped below the oversold threshold (like 30) and has a positive slope. If it does, the buy side is considered “unlocked.” For sell signals, RSI must exceed an overbought threshold (70) and slope downward. The combination of threshold and slope helps confirm that a reversal is genuinely in progress instead of issuing signals while momentum remains weak or stuck in extremes.
Cooldown Mechanism:
The script features a custom bar-based cooldown that prevents issuing new signals in the opposite direction immediately after one is triggered. This helps avoid whipsaw situations where the market quickly flips from oversold to overbought or vice versa.
How It Works: When a buy signal fires, the indicator notes the bar index. If the Z-Score and RSI conditions later suggest a sell, the script compares the current bar index to the last buy signal’s bar index. If the difference is within cooldownBars, the signal is disallowed. This ensures a predefined “quiet period” before switching signals.
Slope-Based Coloring (Z-Mean Line and Shadow):
The script compares the current basis value to its value slopeIndex bars ago. A higher reading now indicates a generally upward slope, while a lower reading indicates a downward slope. The script then shades the Z-Mean line in a corresponding bullish or bearish color, or remains neutral if little change is detected.
How It Works: This slope calculation is refreshingly straightforward: basis – basis . If the result is positive, the line is colored bullish; if negative, it is colored bearish; if approximately zero, it remains neutral. This provides a quick visual cue of the medium-term directional bias.
Gradient Overlays:
With gradient fills, the script highlights where price stands in relation to the Z-Mean. When price is above the basis, a purple-shaded region is painted, visually indicating a “bearish zone” for potential overbought conditions. When price is below, a teal-like overlay is used, suggesting a “bullish zone” for potential oversold conditions.
How It Works: Each bar, the script checks if price is above or below the basis. It then applies a fill between close and basis, using distinct colors to show whether the market is trading above or below its mean. This creates an immediate sense of how extended the market might be.
Buy and Sell Labels (with Alerts):
When a legitimate buy or sell condition passes every check (Z-Score threshold, EMA trend alignment, RSI gating, and cooldown clearance), the script plots a corresponding label directly on the chart. It also fires an alert (if alerts are set up), making it convenient for traders who want timely notifications.
How It Works: If rawBuy or rawSell conditions are met (refined by RSI, EMA trend, and cooldown constraints), the script calls the respective plot function to paint an arrow label on the chart. Alerts are triggered simultaneously, carrying easily recognizable messages.
Metrics Table:
The optional on-chart table (activated by showMetrics) presents real-time Z-Score data, including the current Z-Score, its rolling mean, the maximum and minimum Z-Score values observed over the last zLen bars, a percentile position, and a short-term directional note (rising, falling, or flat).
Current – The present Z-Score reading
Mean – Average Z-Score over the zLen period
Min/Max – Lowest and highest Z-Score values within zLen
Position – Where the current Z-Score sits between the min and max (as a percentile)
Trend – Whether the Z-Score is increasing, decreasing, or flat
Conclusion
Uptrick: Z-Score Flow offers a versatile solution for traders who need a statistically informed perspective on price extremes combined with practical checks for overall trend and momentum. By leveraging a well-defined combination of Z-Score, EMA trend classification, RSI-based momentum gating, slope-based visualization, and a cooldown mechanic, the script reduces the occurrence of false or premature signals. Its gradient fills and optional metrics table contribute further clarity, ensuring that users can quickly assess market posture and make more confident trading decisions in real time.
Disclaimer
This script is intended solely for informational and educational purposes. Trading in any financial market comes with substantial risk, and there is no guarantee of success or the avoidance of loss. Historical performance does not ensure future results. Always conduct thorough research and consider professional guidance prior to making any investment or trading decisions.
Stochastic Fusion Elite [trade_lexx]📈 Stochastic Fusion Elite is your reliable trading assistant!
📊 What is Stochastic Fusion Elite ?
Stochastic Fusion Elite is a trading indicator based on a stochastic oscillator. It analyzes the rate of price change and generates buy or sell signals based on various technical analysis methods.
💡 The main components of the indicator
📊 Stochastic oscillator (K and D)
Stochastic shows the position of the current price relative to the price range for a certain period. Values above 80 indicate overbought (an early sale is possible), and values below 20 indicate oversold (an early purchase is possible).
📈 Moving Averages (MA)
The indicator uses 10 different types of moving averages to smooth stochastic lines.:
- SMA: Simple moving average
- EMA: Exponential moving average
- WMA: Weighted moving average
- HMA: Moving Average Scale
- KAMA: Kaufman Adaptive Moving Average
- VWMA: Volume-weighted moving average
- ALMA: Arnaud Legoux Moving Average
- TEMA: Triple exponential moving average
- ZLEMA: zero delay exponential moving average
- DEMA: Double exponential moving average
The choice of the type of moving average affects the speed of the indicator's response to market changes.
🎯 Bollinger Bands (BB)
Bands around the moving average that widen and narrow depending on volatility. They help determine when the stochastic is out of the normal range.
🔄 Divergences
Divergences show discrepancies between price and stochastic:
- Bullish divergence: price is falling and stochastic is rising — an upward reversal is possible
- Bearish divergence: the price is rising, and stochastic is falling — a downward reversal is possible
🔍 Indicator signals
1️⃣ KD signals (K and D stochastic lines)
- Buy signal:
- What happens: the %K line crosses the %D line from bottom to top
- What does it look like: a green triangle with the label "KD" under the chart and the label "Buy" below the bar
- What does this mean: the price is gaining an upward momentum, growth is possible
- Sell signal:
- What happens: the %K line crosses the %D line from top to bottom
- What it looks like: a red triangle with the label "KD" above the chart and the label "Sell" above the bar
- What does this mean: the price is losing its upward momentum, possibly falling
2️⃣ Moving Average Signals (MA)
- Buy Signal:
- What happens: stochastic crosses the moving average from bottom to top
- What it looks like: a green triangle with the label "MA" under the chart and the label "Buy" below the bar
- What does this mean: stochastic is starting to accelerate upward, price growth is possible
- Sell signal:
- What happens: stochastic crosses the moving average from top to bottom
- What it looks like: a red triangle with the label "MA" above the chart and the label "Sell" above the bar
- What does this mean: stochastic is starting to accelerate downwards, a price drop is possible
3️⃣ Bollinger Band Signals (BB)
- Buy signal:
- What happens: stochastic crosses the lower Bollinger band from bottom to top
- What it looks like: a green triangle with the label "BB" under the chart and the label "Buy" below the bar
- What does this mean: stochastic was too low and is now starting to recover
- Sell signal:
- What happens: Stochastic crosses the upper Bollinger band from top to bottom
- What it looks like: a red triangle with a "BB" label above the chart and a "Sell" label above the bar
- What does this mean: stochastic was too high and is now starting to decline
4️⃣ Divergence Signals (Div)
- Buy Signal (Bullish Divergence):
- What's happening: the price is falling, and stochastic is forming higher lows
- What it looks like: a green triangle with a "Div" label under the chart and a "Buy" label below the bar
- What does this mean: despite the falling price, the momentum is already changing in an upward direction
- Sell signal (bearish divergence):
- What's going on: the price is rising, and stochastic is forming lower highs
- What it looks like: a red triangle with a "Div" label above the chart and a "Sell" label above the bar
- What does this mean: despite the price increase, the momentum is already weakening
🛠️ Filters to filter out false signals
1️⃣ Minimum distance between the signals
- What it does: sets the minimum number of candles between signals
- Why it is needed: prevents signals from being too frequent during strong market fluctuations
- How to set it up: Set the number from 0 and above (default: 5)
2️⃣ "Waiting for the opposite signal" mode
- What it does: waits for a signal in the opposite direction before generating a new signal
- Why you need it: it helps you not to miss important trend reversals
- How to set up: just turn the function on or off
3️⃣ Filter by stochastic levels
- What it does: generates signals only when the stochastic is in the specified ranges
- Why it is needed: it helps to catch the moments when the market is oversold or overbought
- How to set up:
- For buy signals: set a range for oversold (for example, 1-20)
- For sell signals: set a range for overbought (for example, 80-100)
4️⃣ MFI filter
- What it does: additionally checks the values of the cash flow index (MFI)
- Why it is needed: confirms stochastic signals with cash flow data
- How to set it up:
- For buy signals: set the range for oversold MFI (for example, 1-25)
- For sell signals: set the range for overbought MFI (for example, 75-100)
5️⃣ The RSI filter
- What it does: additionally checks the RSI values to confirm the signals
- Why it is needed: adds additional confirmation from another popular indicator
- How to set up:
- For buy signals: set the range for oversold MFI (for example, 1-30)
- For sell signals: set the range for overbought MFI (for example, 70-100)
🔄 Signal combination modes
1️⃣ Normal mode
- How it works: all signals (KD, MA, BB, Div) work independently of each other
- When to use it: for general market analysis or when learning how to work with the indicator
2️⃣ "AND" Mode ("AND Mode")
- How it works: the alarm appears only when several conditions are triggered simultaneously
- Combination options:
- KD+MA: signals from the KD and moving average lines
- KD+BB: signals from KD lines and Bollinger bands
- KD+Div: signals from the KD and divergence lines
- KD+MA+BB: three signals simultaneously
- KD+MA+Div: three signals at the same time
- KD+BB+Div: three signals at the same time
- KD+MA+BB+Div: all four signals at the same time
- When to use: for more reliable but rare signals
🔌 Connecting to trading strategies
The indicator can be connected to your trading strategies using 6 different channels.:
1. Connector KD signals: connects only the signals from the intersection of lines K and D
2. Connector MA signals: connects only signals from moving averages
3. Connector BB signal: connects only the signals from the Bollinger bands
4. Connector divergence signals: connects only divergence signals
5. Combined Connector: connects any signals
6. Connector for "And" mode: connects only combined signals
🔔 Setting up alerts
The indicator can send alerts when alarms appear.:
- Alerts for KD: when the %K line crosses the %D line
- Alerts for MA: when stochastic crosses the moving average
- Alerts for BB: when stochastic crosses the Bollinger bands
- Divergence alerts: when a divergence is detected
- Combined alerts: for all types of alarms
- Alerts for "And" mode: for combined signals
🎭 What does the indicator look like on the chart ?
- Main lines K and D: blue and orange lines
- Overbought/oversold levels: horizontal lines at levels 20 and 80
- Middle line: dotted line at level 50
- Stochastic Moving Average: yellow line
- Bollinger bands: green lines around the moving average
- Signals: green and red triangles with corresponding labels
📚 How to start using Stochastic Fusion Elite
1️⃣ Initial setup
- Add an indicator to your chart
- Select the types of signals you want to use (KD, MA, BB, Div)
- Adjust the period and smoothing for the K and D lines
2️⃣ Filter settings
- Set the distance between the signals to get rid of unnecessary noise
- Adjust stochastic, MFI and RSI levels depending on the volatility of your asset
- If you need more reliable signals, turn on the "Waiting for the opposite signal" mode.
3️⃣ Operation mode selection
- First, use the standard mode to see all possible signals.
- When you get comfortable, try the "And" mode for rarer signals.
4️⃣ Setting up Alerts
- Select the types of signals you want to be notified about
- Set up alerts for these types of signals
5️⃣ Verification and adaptation
- Check the operation of the indicator on historical data
- Adjust the parameters for a specific asset
- Adapt the settings to your trading style
🌟 Usage examples
For trend trading
- Use the KD and MA signals in the direction of the main trend
- Set the distance between the signals
- Set stricter levels for filters
For trading in a sideways range
- Use BB signals to detect bounces from the range boundaries
- Use a stochastic level filter to confirm overbought/oversold conditions
- Adjust the Bollinger bands according to the width of the range
To determine the pivot points
- Pay attention to the divergence signals
- Set the distance between the signals
- Check the MFI and RSI filters for additional confirmation
Multi-Oscillator Adaptive Kernel | AlphaAlgosMulti-Oscillator Adaptive Kernel | AlphaAlgos
Overview
The Multi-Oscillator Adaptive Kernel (MOAK) is an advanced technical analysis tool that combines multiple oscillators through sophisticated kernel-based smoothing algorithms. This indicator is designed to provide clearer trend signals while filtering out market noise, offering traders a comprehensive view of market momentum across multiple timeframes.
Key Features
• Fusion of multiple technical oscillators (RSI, Stochastic, MFI, CCI)
• Advanced kernel smoothing technology with three distinct mathematical models
• Customizable sensitivity and lookback periods
• Clear visual signals for trend shifts and reversals
• Overbought/oversold zones for precise entry and exit timing
• Adaptive signal that responds to varying market conditions
Technical Components
The MOAK indicator utilizes a multi-layer approach to signal generation:
1. Oscillator Fusion
The core of the indicator combines normalized readings from up to four popular oscillators:
• RSI (Relative Strength Index) - Measures the speed and change of price movements
• Stochastic - Compares the closing price to the price range over a specific period
• MFI (Money Flow Index) - Volume-weighted RSI that includes trading volume
• CCI (Commodity Channel Index) - Measures current price level relative to an average price
2. Kernel Smoothing
The combined oscillator data is processed through one of three kernel functions:
• Exponential Kernel - Provides stronger weighting to recent data with exponential decay
• Linear Kernel - Applies a linear weighting from most recent to oldest data points
• Gaussian Kernel - Uses a bell curve distribution that helps filter out extreme values
3. Dual Signal Lines
• Fast Signal Line - Responds quickly to price changes
• Slow Signal Line - Provides confirmation and shows the underlying trend direction
Configuration Options
Oscillator Selection:
• Enable/disable each oscillator (RSI, Stochastic, MFI, CCI)
• Customize individual lookback periods for each oscillator
Kernel Settings:
• Kernel Type - Choose between Exponential, Linear, or Gaussian mathematical models
• Kernel Length - Adjust the smoothing period (higher values = smoother line)
• Sensitivity - Fine-tune the indicator's responsiveness (higher values = more responsive)
Display Options:
• Color Bars - Toggle price bar coloring based on indicator direction
How to Interpret the Indicator
Signal Line Direction:
• Upward movement (teal) indicates bullish momentum
• Downward movement (magenta) indicates bearish momentum
Trend Shifts:
• Small circles mark the beginning of new uptrends
• X-marks indicate the start of new downtrends
Overbought/Oversold Conditions:
• Values above +50 suggest overbought conditions (potential reversal or pullback)
• Values below -50 suggest oversold conditions (potential reversal or bounce)
Trading Strategies
Trend Following:
• Enter long positions when the signal line turns teal and shows an uptrend
• Enter short positions when the signal line turns magenta and shows a downtrend
• Use the slow signal line (area fill) as confirmation of the underlying trend
Counter-Trend Trading:
• Look for divergences between price and the indicator
• Consider profit-taking when the indicator reaches overbought/oversold areas
• Wait for trend shift signals before entering counter-trend positions
Multiple Timeframe Analysis:
• Use the indicator across different timeframes for confirmation
• Higher timeframe signals carry more weight than lower timeframe signals
Best Practices
• Experiment with different kernel types for various market conditions
• Gaussian kernels often work well in ranging markets
• Exponential kernels can provide earlier signals in trending markets
• Combine with volume analysis for higher probability trades
• Use appropriate stop-loss levels as the indicator does not guarantee price movements
This indicator is provided as-is with no guarantees of profit. Always use proper risk management when trading with any technical indicator. Nothing is financial advise.
Uptrick: Alpha TrendIntroduction
Uptrick: Alpha Trend is a comprehensive technical analysis indicator designed to provide traders with detailed insights into market trends, momentum, and risk metrics. It adapts to various trading styles—from quick scalps to longer-term positions—by dynamically adjusting its calculations and visual elements. By combining multiple smoothing techniques, advanced color schemes, and customizable data tables, the indicator offers a holistic view of market behavior.
Originality
The Alpha Trend indicator distinguishes itself by blending established technical concepts with innovative adaptations. It employs three different smoothing techniques tailored to specific trading modes (Scalp, Swing, and Position), and it dynamically adjusts its parameters to match the chosen mode. The indicator also offers a wide range of color palettes and multiple on-screen tables that display key metrics. This unique combination of features, along with its ability to adapt in real time, sets it apart as a versatile tool for both novice and experienced traders.
Features
1. Multi-Mode Trend Line
The indicator automatically selects a smoothing method based on the trading mode:
- Scalp Mode uses the Hull Moving Average (HMA) for rapid responsiveness.
- Swing Mode employs the Exponential Moving Average (EMA) for balanced reactivity.
- Position Mode applies the Weighted Moving Average (WMA) for smoother, long-term trends.
Each method is chosen to best capture the price action dynamics appropriate to the trader’s timeframe.
2. Adaptive Momentum Thresholds
It tracks bullish and bearish momentum with counters that increment as the trend confirms directional movement. When these counters exceed a user-defined threshold, the indicator generates optional buy or sell signals. This approach helps filter out minor fluctuations and highlights significant market moves.
3. Gradient Fills
Two types of fills enhance visual clarity:
- Standard Gradient Fill displays ATR-based zones above and below the trend line, indicating potential bullish and bearish areas.
- Fading Gradient Fill creates a smooth transition between the trend line and the price, visually emphasizing the distance between them.
4. Bar Coloring and Signal Markers
The indicator can color-code bars based on market conditions—bullish, bearish, or neutral—allowing for immediate visual assessment. Additionally, signal markers such as buy and sell arrows are plotted when momentum thresholds are breached.
5. Comprehensive Data Tables
Uptrick: Alpha Trend offers several optional tables for detailed analysis:
- Insider Info: Displays key metrics like the current trend value, bullish/bearish momentum counts, and ATR.
- Indicator Metrics: Lists input settings such as trend length, damping, signal threshold, and net momentum.
- Market Analysis: Summarizes overall trend direction, trend strength, Sortino ratio, return, and volatility.
- Price & Trend Dynamics: Details price deviation from the trend, trend slope, and ATR ratio.
- Momentum & Volatility Insights: Presents RSI, standard deviation (volatility), and net momentum.
- Performance & Acceleration Metrics: Focuses on the Sortino ratio, trend acceleration, return, and trend strength.
Each table can be positioned flexibly on the chart, allowing traders to customize the layout according to their needs.
Why It Combines Specific Smoothing Techniques
Smoothing techniques are essential for filtering out market noise and revealing underlying trends. The indicator combines three smoothing methods for the following reasons:
- The Hull Moving Average (HMA) in Scalp Mode minimizes lag and responds quickly to price changes, which is critical for short-term trading.
- The Exponential Moving Average (EMA) in Swing Mode gives more weight to recent data, striking a balance between speed and smoothness. This makes it suitable for mid-term trend analysis.
- The Weighted Moving Average (WMA) in Position Mode smooths out short-term fluctuations, offering a clear view of longer-term trends and reducing the impact of transient market volatility.
By using these specific methods in their respective trading modes, the indicator ensures that the trend line is appropriately responsive for the intended time frame, enhancing decision-making while maintaining clarity.
Inputs
1. Trend Length (Default: 30)
Defines the lookback period for the smoothing calculation. A shorter trend length results in a more responsive line, while a longer length produces a smoother, less volatile trend.
2. Trend Damping (Default: 0.75)
Controls the degree of smoothing applied to the trend line. Lower values lead to a smoother curve, whereas higher values increase sensitivity to price fluctuations.
3. Signal Strength Threshold (Default: 5)
Specifies the number of consecutive bullish or bearish bars required to trigger a signal. Higher thresholds reduce the frequency of signals, focusing on stronger moves.
4. Enable Bar Coloring (Default: True)
Toggles whether each price bar is colored to indicate bullish, bearish, or neutral conditions.
5. Enable Signals (Default: True)
When enabled, this option plots buy or sell arrows on the chart once the momentum thresholds are met.
6. Enable Standard Gradient Fill (Default: False)
Activates ATR-based gradient fills around the trend line to visualize potential support and resistance zones.
7. Enable Fading Gradient Fill (Default: True)
Draws a gradual color transition between the trend line and the current price, emphasizing their divergence.
8. Trading Mode (Options: Scalp, Swing, Position)
Determines which smoothing method and ATR period to use, adapting the indicator’s behavior to short-term, medium-term, or long-term trading.
9. Table Position Inputs
Allows users to select from nine possible chart positions (top, middle, bottom; left, center, right) for each data table.
10. Show Table Booleans
Separate toggles control the display of each table (Insider Info, Indicator Metrics, Market Analysis, and the three Deep Tables), enabling a customized view of the data.
Color Schemes
(Default) - The colors in the preview image of the indicator.
(Emerald)
(Sapphire)
(Golden Blaze)
(Mystic)
(Monochrome)
(Pastel)
(Vibrant)
(Earth)
(Neon)
Calculations
1. Trend Line Methods
- Scalp Mode: Utilizes the Hull Moving Average (HMA), which computes two weighted moving averages (one at half the length and one at full length), subtracts them, and then applies a final weighted average based on the square root of the length. This method minimizes lag and increases responsiveness.
- Swing Mode: Uses the Exponential Moving Average (EMA), which assigns greater weight to recent prices, thus balancing quick reaction with smoothness.
- Position Mode: Applies the Weighted Moving Average (WMA) to focus on longer-term trends by emphasizing the entire lookback period and reducing the impact of short-term volatility.
2. Momentum Tracking
The indicator maintains separate counters for bullish and bearish momentum. These counters increase as the trend confirms directional movement and reset when the trend reverses. When a counter exceeds the defined signal strength threshold, a corresponding signal (buy or sell) is triggered.
3. Volatility and ATR Zones
The Average True Range (ATR) is calculated using a period that adapts to the selected trading mode (shorter for Scalp, longer for Position). The ATR value is then used to define upper and lower zones around the trend line, highlighting the current level of market volatility.
4. Return and Trend Acceleration
- Return is calculated as the difference between the current and previous closing prices, providing a simple measure of price change.
- Trend Acceleration is derived from the change in the trend line’s movement (its first derivative) compared to the previous bar. This metric indicates whether the trend is gaining or losing momentum.
5. Sortino Ratio and Standard Deviation
- The Sortino Ratio measures risk-adjusted performance by comparing returns to downside volatility (only considering negative price changes).
- Standard Deviation is computed over the lookback period to assess the extent of price fluctuations, offering insights into market stability.
Usage
This indicator is suitable for various time frames and market instruments. Traders can enable or disable specific visual elements such as gradient fills, bar coloring, and signal markers based on their preference. For a minimalist approach, one might choose to display only the primary trend line. For a deeper analysis, enabling multiple tables can provide extensive data on momentum, volatility, trend dynamics, and risk metrics.
Important Note on Risk
Trading involves inherent risk, and no indicator can eliminate the uncertainty of the markets. Past performance is not indicative of future results. It is essential to use proper risk management, test any new tool thoroughly, and consult multiple sources or professional advice before making trading decisions.
Conclusion
Uptrick: Alpha Trend unifies a diverse set of calculations, adaptive smoothing techniques, and customizable visual elements into one powerful tool. By combining the Hull, Exponential, and Weighted Moving Averages, the indicator is able to provide a trend line that is both responsive and smooth, depending on the trading mode. Its advanced color schemes, gradient fills, and detailed data tables deliver a comprehensive analysis of market trends, momentum, and risk. Whether you are a short-term trader or a long-term investor, this indicator aims to clarify price action and assist you in making more informed trading decisions.
Smoothed Source Weighted EMAThe Smoothed Source EMA is a tool designed to help traders identify potential buying and selling opportunities in the market. It combines two key elements: price smoothing (using standard deviation) and an Exponential Moving Average (EMA). The purpose is to filter out the day-to-day price fluctuations and create clearer buy and sell signals.
Key Concepts Behind the Indicator:
Price Smoothing (Standard Deviation):
To make the price action easier to follow, the indicator first "smooths" the price. This is done by looking at how much the price tends to move up and down (known as standard deviation).
It then creates two "bands" around the current price—one above and one below. These bands represent a smoothed version of the price and help filter out the noise caused by small, random price movements.
Exponential Moving Average (EMA):
The indicator also uses an Exponential Moving Average (EMA), which is a line that represents the average price over a certain period of time (but gives more weight to recent prices). The EMA helps capture the general trend of the price.
The indicator uses this EMA to compare the current price with the overall trend.
How Does the Indicator Work?
Once the indicator calculates the smoothed price bands and the EMA, it looks for specific conditions to trigger a buy or sell signal:
Long (Buy) Signal:
A buy signal happens when the smoothed price (the lower band) is above the EMA. In simple terms, the price is moving up, and the indicator is telling you it's a good time to buy.
The more "weight" or influence you give to the EMA, the slower this buy signal will appear, meaning it’ll only trigger when there’s a strong enough upward movement.
Short (Sell) Signal:
A sell signal occurs when the smoothed price (the upper band) is below the EMA. This suggests the price is moving down, and the indicator signals that it might be time to sell.
Again, the more "weight" you put on the EMA, the slower the sell signal will appear, as the indicator waits for a clearer downtrend.
Why is this Useful for Traders?
Smoothing the Price: Many traders struggle with the noise of price fluctuations, where the price moves up and down quickly without a clear trend. By smoothing the price, this indicator helps traders focus on the bigger picture and avoid reacting to every small movement.
Clear Buy and Sell Signals: The indicator generates easy-to-understand buy and sell signals based on the relationship between the smoothed price and the EMA. If the price is above the smoothed level and EMA, it’s a signal to buy. If it’s below, it’s a signal to sell.
Customizable Sensitivity: The indicator lets traders adjust how sensitive the buy and sell signals are. By changing certain settings, such as the smoothing length and the weight of the EMA, traders can make the indicator react faster or slower depending on how quickly they want to catch changes in the market.
How the Indicator Appears on the Chart:
EMA Line: A line that represents the trend of the price.
Upper and Lower Smoothed Bands: Two bands above and below the price that help identify when the price is moving up or down relative to the trend.
Buy and Sell Arrows: Small arrows on the chart show where the indicator suggests buying or selling.
Colored Bars: The bars on the chart may change color to visually indicate whether the indicator suggests a buy (green) or a sell (red).
In Summary:
The Smoothed Source EMA helps you identify trends by smoothing out price movements using standard deviation, then comparing these smoothed prices with the Exponential Moving Average (EMA).
When the smoothed price moves above or below the EMA, it gives you a signal: a buy when the smoothed price is above the EMA, and a sell when it’s below.
You can adjust how quickly or slowly these signals appear by modifying the settings, giving you control over how sensitive the indicator is to changes in the market.
This indicator is useful for traders who want to reduce noise and focus on the overall trend, using clear, visually simple signals to guide their trading decisions.
EMA Volatility Channel [QuantAlgo]EMA Volatility Channel 🌊📈
The EMA Volatility Channel by QuantAlgo is an advanced technical indicator designed to capture price volatility and trend dynamics through adaptive channels based on exponential moving averages. This sophisticated system combines EMA-based trend analysis with dynamic volatility-adjusted bands to help traders and investors identify trend direction, potential reversals, and market volatility conditions. By evaluating both price momentum and volatility together, this tool enables users to make informed trading decisions while adapting to changing market conditions.
💫 Dynamic Channel Architecture
The EMA Volatility Channel provides a unique framework for assessing market trends through a blend of exponential moving averages and volatility-based channel calculations. Unlike traditional channel indicators that use fixed-width bands, this system incorporates dynamic volatility measurements to adjust channel width automatically, helping users determine whether price movements are significant relative to current market conditions. By combining smooth EMA trends with adaptive volatility bands, it evaluates both directional movement and market volatility, while the smoothing parameters ensure stable yet responsive channel adjustments. This adaptive approach allows users to identify trending conditions while remaining aware of volatility expansions and contractions, enhancing both trend-following and reversal strategies.
📊 Indicator Components & Mechanics
The EMA Volatility Channel is composed of several technical components that create a dynamic channel system:
EMA Midline: Calculates a smoothed exponential moving average that serves as the channel's centerline, providing a clear reference for trend direction.
Volatility Measurement: Computes average price movement to determine dynamic channel width, adapting to changing market conditions automatically.
Smooth Band Calculation: Applies additional smoothing to the channel bands, reducing noise while maintaining responsiveness to significant price movements.
📈 Key Indicators and Features
The EMA Volatility Channel combines various technical tools to deliver a comprehensive analysis of market conditions.
The indicator utilizes exponential moving averages with customizable length and smoothing parameters to adapt to different trading styles. Volatility calculations are applied to determine channel width, providing context-aware boundaries for price movement. The trend detection component evaluates price action relative to the channel bands, helping validate trends and identify potential reversals.
The indicator incorporates multi-layered visualization with color-coded channels and bars to signal both trend direction and market position. These adaptive visual cues, combined with programmable alerts for channel breakouts, help traders and investors track both trend changes and volatility conditions, supporting both trend-following and mean-reversion strategies.
⚡️ Practical Applications and Examples
✅ Add the Indicator: Add the indicator to your TradingView chart by clicking on the star icon to add it to your favorites ⭐️
👀 Monitor Channel Position: Watch the price position relative to the channel bands to identify trend direction and potential reversals. When price moves outside the channel, consider potential trend changes or extreme conditions.
🔔 Set Alerts: Configure alerts for channel breakouts and trend changes, ensuring you can act on significant technical developments promptly.
🌟 Summary and Tips
The EMA Volatility Channel by QuantAlgo is a versatile technical tool, designed to support both trend following and volatility analysis across different market environments. By combining smooth EMA trends with dynamic volatility-based channels, it helps traders and investors identify significant price movements while measuring market volatility, providing reliable technical signals. The tool's adaptability across timeframes makes it suitable for both trend-following and reversal strategies, allowing users to capture opportunities while maintaining awareness of changing market conditions.
Super CCI By Baljit AujlaThe indicator you've shared is a custom CCI (Commodity Channel Index) with multiple types of Moving Averages (MA) and Divergence Detection. It is designed to help traders identify trends and reversals by combining the CCI with various MAs and detecting different types of divergences between the price and the CCI.
Key Components of the Indicator:
CCI (Commodity Channel Index):
The CCI is an oscillator that measures the deviation of the price from its average price over a specific period. It helps identify overbought and oversold conditions and the strength of a trend.
The CCI is calculated by subtracting a moving average (SMA) from the price and dividing by the average deviation from the SMA. The CCI values fluctuate above and below a zero centerline.
Multiple Moving Averages (MA):
The indicator allows you to choose from a variety of moving averages to smooth the CCI line and identify trend direction or support/resistance levels. The available types of MAs include:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
HMA (Hull Moving Average)
RMA (Running Moving Average)
SMMA (Smoothed Moving Average)
TEMA (Triple Exponential Moving Average)
DEMA (Double Exponential Moving Average)
VWMA (Volume-Weighted Moving Average)
ZLEMA (Zero-Lag Exponential Moving Average)
You can select the type of MA to use with a specified length to help identify the trend direction or smooth out the CCI.
Divergence Detection:
The indicator includes a divergence detection mechanism to identify potential trend reversals. Divergences occur when the price and an oscillator like the CCI move in opposite directions, signaling a potential change in price momentum.
Four types of divergences are detected:
Bullish Divergence: Occurs when the price makes a lower low, but the CCI makes a higher low. This indicates a potential reversal to the upside.
Bearish Divergence: Occurs when the price makes a higher high, but the CCI makes a lower high. This indicates a potential reversal to the downside.
Hidden Bullish Divergence: Occurs when the price makes a higher low, but the CCI makes a lower low. This suggests a continuation of the uptrend.
Hidden Bearish Divergence: Occurs when the price makes a lower high, but the CCI makes a higher high. This suggests a continuation of the downtrend.
Each type of divergence is marked on the chart with arrows and labels to alert traders to potential trading opportunities. The labels include the divergence type (e.g., "Bull Div" for Bullish Divergence) and have customizable text colors.
Visual Representation:
The CCI and its associated moving average are plotted on the indicator panel below the price chart. The CCI is plotted as a line, and its color changes depending on whether it is above or below the moving average:
Green when the CCI is above the MA (indicating bullish momentum).
Red when the CCI is below the MA (indicating bearish momentum).
Horizontal lines are drawn at specific levels to help identify key CCI thresholds:
200 and -200 levels indicate extreme overbought or oversold conditions.
75 and -75 levels represent less extreme levels of overbought or oversold conditions.
The 0 level acts as a neutral or baseline level.
A background color fill between the 75 and -75 levels helps highlight the neutral zone.
Customization Options:
CCI Length: You can customize the length of the CCI, which determines the period over which the CCI is calculated.
MA Length: The length of the moving average applied to the CCI can also be adjusted.
MA Type: Choose from a variety of moving averages (SMA, EMA, WMA, etc.) to smooth the CCI.
Divergence Detection: The indicator automatically detects the four types of divergences (bullish, bearish, hidden bullish, hidden bearish) and visually marks them on the chart.
How to Use the Indicator:
Trend Identification: When the CCI is above the selected moving average, it suggests bullish momentum. When the CCI is below the moving average, it suggests bearish momentum.
Overbought/Oversold Conditions: The CCI values above 100 or below -100 indicate overbought and oversold conditions, respectively.
Divergence Analysis: The detection of bullish or bearish divergences can signal potential trend reversals. Hidden divergences may suggest trend continuation.
Trading Signals: You can use the divergence markers (arrows and labels) as potential buy or sell signals, depending on whether the divergence is bullish or bearish.
Practical Application:
This indicator is useful for traders who want to:
Combine the CCI with different moving averages for trend-following strategies.
Identify overbought and oversold conditions using the CCI.
Use divergence detection to anticipate potential trend reversals or continuations.
Have a highly customizable tool for various trading strategies, including trend trading, reversal trading, and divergence-based trading.
Overall, this is a comprehensive tool that combines multiple technical analysis techniques (CCI, moving averages, and divergence) in a single indicator, providing traders with a robust way to analyze price action and spot potential trading opportunities.
Pulse DPO: Major Cycle Tops and Bottoms█ OVERVIEW
Pulse DPO is an oscillator designed to highlight Major Cycle Tops and Bottoms .
It works on any market driven by cycles. It operates by removing the short-term noise from the price action and focuses on the market's cyclical nature.
This indicator uses a Normalized version of the Detrended Price Oscillator (DPO) on a 0-100 scale, making it easier to identify major tops and bottoms.
Credit: The DPO was first developed by William Blau in 1991.
█ HOW TO READ IT
Pulse DPO oscillates in the range between 0 and 100. A value in the upper section signals an OverBought (OB) condition, while a value in the lower section signals an OverSold (OS) condition.
Generally, the triggering of OB and OS conditions don't necessarily translate into swing tops and bottoms, but rather suggest caution on approaching a market that might be overextended.
Nevertheless, this indicator has been customized to trigger the signal only during remarkable top and bottom events.
I suggest using it on the Daily Time Frame , but you're free to experiment with this indicator on other time frames.
The indicator has Built-in Alerts to signal the crossing of the Thresholds. Please don't act on an isolated signal, but rather integrate it to work in conjunction with the indicators present in your Trading Plan.
█ OB SIGNAL ON: ENTERING OVERBOUGHT CONDITION
When Pulse DPO crosses Above the Top Threshold it Triggers ON the OB signal. At this point the oscillator line shifts to OB color.
When Pulse DPO enters the OB Zone, please beware! In this Area the Major Players usually become Active Sellers to the Public. While the OB signal is On, it might be wise to Consider Selling a portion or the whole Long Position.
Please note that even though this indicator aims to focus on major tops and bottoms, a strong trending market might trigger the OB signal and stay with it for a long time. That's especially true on young markets and on bubble-mode markets.
█ OB SIGNAL OFF: EXITING OVERBOUGHT CONDITION
When Pulse DPO crosses Below the Top Threshold it Triggers OFF the OB signal. At this point the oscillator line shifts to its normal color.
When Pulse DPO exits the OB Zone, please beware because a Major Top might just have occurred. In this Area the Major Players usually become Aggressive Sellers. They might wind up any remaining Long Positions and Open new Short Positions.
This might be a good area to Open Shorts or to Close/Reverse any remaining Long Position. Whatever you choose to do, it's usually best to act quickly because the market is prone to enter into panic mode.
█ OS SIGNAL ON: ENTERING OVERSOLD CONDITION
When Pulse DPO crosses Below the Bottom Threshold it Triggers ON the OS signal. At this point the oscillator line shifts to OS color.
When Pulse DPO enters the OS Zone, please beware because in this Area the Major Players usually become Active Buyers accumulating Long Positions from the desperate Public.
While the OS signal is On, it might be wise to Consider becoming a Buyer or to implement a Dollar-Cost Averaging (DCA) Strategy to build a Long Position towards the next Cycle. In contrast to the tops, the OS state usually takes longer to resolve a major bottom.
█ OS SIGNAL OFF: EXITING OVERSOLD CONDITION
When Pulse DPO crosses Above the Bottom Threshold it Triggers OFF the OS signal. At this point the oscillator line shifts to its normal color.
When Pulse DPO exits the OS Zone, please beware because a Major Bottom might already be in place. In this Area the Major Players become Aggresive Buyers. They might wind up any remaining Short Positions and Open new Long Positions.
This might be a good area to Open Longs or to Close/Reverse any remaining Short Positions.
█ WHY WOULD YOU BE INTERESTED IN THIS INDICATOR?
This indicator is built over a solid foundation capable of signaling Major Cycle Tops and Bottoms across many markets. Let's see some examples:
Early Bitcoin Years: From 0 to 1242
This chart is in logarithmic mode in order to properly display various exponential cycles. Pulse DPO is properly signaling the major early highs from 9-Jun-2011 at 31.50, to the next one on 9-Apr-2013 at 240 and the epic top from 29-Nov-2013 at 1242.
Due to the massive price movements, the OB condition stays pinned during most of the exponential price action. But as you can see, the OB condition quickly vanishes once the Cycle Top has been reached. As the market matures, the OB condition becomes more exceptional and triggers much closer from the Cycle Top.
With regards to Cycle Bottoms, the early bottom of 2 after having peaked at 31.50 doesn’t get captured by the indicator. That is the only cycle bottom that escapes the Pulse DPO when the bottom threshold is set at a value of 5. In that event, the oscillator low reached 6.95.
Bitcoin Adoption Spreading: From 257 to 73k
This chart is in logarithmic mode in order to properly display various exponential cycles. Pulse DPO is properly signaling all the major highs from 17-Dec-2017 at 19k, to the next one on 14-Apr-2021 at 64k and the most recent top from 9-Nov-2021 at 68k.
During the massive run of 2017, the OB condition still stayed triggered for a few weeks on each swing top. But on the next cycles it started to signal only for a few days before each swing top actually happened. The OB condition during the last cycle top triggered only for 3 days. Therefore the signal grows in focus as the market matures.
At the time of publishing this indicator, Bitcoin printed a new All Time High (ATH) on 13-Mar-2024 at 73k. That run didn’t trigger the OB condition. Therefore, if the indicator is correct the Bitcoin market still has some way to grow during the next months.
With regards to Cycle Bottoms, the bottom of 3k after having peaked at19k got captured within the wide OS zone. The bottom of 15k after having peaked at 68k got captured too within the OS accumulation area.
Gold
Pulse DPO behaves surprisingly well on a long standing market such as Gold. Moving back to the 197x years it’s been signaling most Cycle Tops and Bottoms with precision. During the last cycle, it shows topping at 2k and bottoming at 1.6k.
The current price action is signaling OB condition in the range of 2.5k to 2.7k. Looking at past cycles, it tends to trigger on and off at multiple swing tops until reaching the final cycle top. Therefore this might indicate the first wave within a potential gold run.
Oil
On the Oil market, we can see that most of the cycle tops and bottoms since the 80s got signaled. The only exception being the low from 2020 which didn’t trigger.
EURUSD
On Forex markets the Pulse DPO also behaves as expected. Looking back at EURUSD we can see the marketing triggering OB and OS conditions during major cycle tops and bottoms from recent times until the 80s.
S&P 500
On the S&P 500 the Pulse DPO catched the lows from 2016 and 2020. Looking at present price action, the recent ATH didn’t trigger the OB condition. Therefore, the indicator is allowing room for another leg up during the next months.
Amazon
On the Amazon chart the Pulse DPO is mirroring pretty accurately the major swings. Scrolling back to the early 2000s, this chart resembles early exponential swings in the crypto space.
Tesla
Moving onto a younger tech stock, Pulse DPO captures pretty accurately the major tops and bottoms. The chart is shown in logarithmic scale to better display the magnitude of the moves.
█ SETTINGS
This indicator is ideal for identifying major market turning points while filtering out short-term noise. You are free to adjust the parameters to align with your preferred trading style.
Parameters : This section allows you to customize any of the Parameters that shape the Oscillator.
Oscillator Length: Defines the period for calculating the Oscillator.
Offset: Shifts the oscillator calculation by a certain number of periods, which is typically half the Oscillator Length.
Lookback Period: Specifies how many bars to look back to find tops and bottoms for normalization.
Smoothing Length: Determines the length of the moving average used to smooth the oscillator.
Thresholds : This section allows you to customize the Thresholds that trigger the OB and OS conditions.
Top: Defines the value of the Top Threshold.
Bottom: Defines the value of the Bottom Threshold.
Ichimoku Wave Oscillator with Custom MAIchimoku Wave Oscillator with Custom MA - Pine Script Description
This script uses various types of moving averages (MA) to implement the concept of Ichimoku wave theory for wave analysis. The user can select from SMA, EMA, WMA, TEMA, SMMA to visualize the difference between short-term, medium-term, and long-term waves, while identifying potential buy and sell signals at crossover points.
Key Features:
MA Type Selection:
The user can select from SMA (Simple Moving Average), EMA (Exponential Moving Average), WMA (Weighted Moving Average), TEMA (Triple Exponential Moving Average), and SMMA (Smoothed Moving Average) to calculate the waves. This script is unique in that it combines TEMA and SMMA, distinguishing it from other simple moving average-based indicators.
TEMA (Triple Exponential Moving Average): Best suited for capturing short-term trends with quick responsiveness.
SMMA (Smoothed Moving Average): Useful for identifying long-term trends with minimal noise, providing more stable signals.
Wave Calculations:
The script calculates three waves: Wave 9-17, Wave 17-26, and Wave 9-26, each of which analyzes different time horizons.
Wave 9-17 (blue): Primarily used for analyzing short-term trends, ideal for detecting quick changes.
Wave 17-26 (red): Used to analyze medium-term trends, providing a more stable market direction.
Wave 9-26 (green): Represents long-term trends, suitable for understanding broader trend shifts.
Baseline (0 Line):
Each wave is visualized around the 0 line, where waves above the line indicate an uptrend and waves below the line indicate a downtrend. This allows for easy identification of trend reversals.
Crossover Signals:
CrossUp: When Wave 9-17 (short-term wave) crosses Wave 17-26 (medium-term wave) upward, it is considered a buy signal, indicating a potential upward trend shift.
CrossDown: When Wave 9-17 (short-term wave) crosses Wave 17-26 downward, it is considered a sell signal, indicating a potential downward trend shift.
Background Color for Signal:
The script visually highlights the signals with background colors. When a buy signal occurs, the background turns green, and when a sell signal occurs, the background turns red. This makes it easier to spot reversal points.
Calculation Method:
The script calculates the difference between moving averages to display the wave oscillation. Wave 9-17, Wave 17-26, and Wave 9-26 represent the difference between the moving averages for different time periods, allowing for analysis of short-term, medium-term, and long-term trends.
Wave 9-17 = MA(9) - MA(17): Represents the difference between the short-term moving averages.
Wave 17-26 = MA(17) - MA(26): Represents the difference between medium-term moving averages.
Wave 9-26 = MA(9) - MA(26): Provides insight into the long-term trend.
This calculation method effectively visualizes the oscillation of waves and helps identify trend reversals at crossover points.
Uniqueness of the Script:
Unlike other moving average-based indicators, this script combines TEMA (Triple Exponential Moving Average) and SMMA (Smoothed Moving Average) to capture both short-term sensitivity and long-term stability in trends. This duality makes the script more versatile for different market conditions.
TEMA is ideal for short-term traders who need quick signals, while SMMA is useful for long-term investors seeking stability and noise reduction. By combining these two, this script provides a more refined analysis of trend changes across various timeframes.
How to Use:
This script is effective for trend analysis and reversal detection. By visualizing the crossover points between the waves, users can spot potential buy and sell signals to make more informed trading decisions.
Scalping strategies can rely on Wave 9-17 to detect quick trend changes, while those looking for medium-term trends can analyze signals from Wave 17-26.
For a broader market overview, Wave 9-26 helps users understand the long-term market trend.
This script is built on the concept of wave theory to anticipate trend changes, making it suitable for various timeframes and strategies. The user can tailor the characteristics of the waves by selecting different MA types, allowing for flexible application across different trading strategies.
Ichimoku Wave Oscillator with Custom MA - Pine Script 설명
이 스크립트는 다양한 이동 평균(MA) 유형을 활용하여 일목 파동론의 개념을 기반으로 파동 분석을 시도하는 지표입니다. 사용자는 SMA, EMA, WMA, TEMA, SMMA 중 원하는 이동 평균을 선택할 수 있으며, 이를 통해 단기, 중기, 장기 파동 간의 차이를 시각화하고, 교차점에서 상승 및 하락 신호를 포착할 수 있습니다.
주요 기능:
이동 평균(MA) 유형 선택:
사용자는 SMA(단순 이동 평균), EMA(지수 이동 평균), WMA(가중 이동 평균), TEMA(삼중 지수 이동 평균), SMMA(평활 이동 평균) 중 하나를 선택하여 파동을 계산할 수 있습니다. 이 스크립트는 TEMA와 SMMA의 독창적인 조합을 통해 기존의 단순한 이동 평균 지표와 차별화됩니다.
TEMA(삼중 지수 이동 평균): 빠른 반응으로 단기 트렌드를 포착하는 데 적합합니다.
SMMA(평활 이동 평균): 장기적인 추세를 파악하는 데 유용하며, 노이즈를 최소화하여 안정적인 신호를 제공합니다.
파동(Wave) 계산:
이 스크립트는 Wave 9-17, Wave 17-26, Wave 9-26의 세 가지 파동을 계산하여 각각 단기, 중기, 장기 추세를 분석합니다.
Wave 9-17 (파란색): 주로 단기 추세를 분석하는 데 사용되며, 빠른 추세 변화를 포착하는 데 유용합니다.
Wave 17-26 (빨간색): 중기 추세를 분석하는 데 사용되며, 좀 더 안정적인 시장 흐름을 보여줍니다.
Wave 9-26 (녹색): 장기 추세를 나타내며, 큰 흐름의 방향성을 파악하는 데 적합합니다.
기준선(0 라인):
각 파동은 0 라인을 기준으로 변동성을 시각화합니다. 0 위에 있는 파동은 상승세, 0 아래에 있는 파동은 하락세를 나타내며, 이를 통해 추세의 전환을 쉽게 확인할 수 있습니다.
파동 교차 신호:
CrossUp: Wave 9-17(단기 파동)이 Wave 17-26(중기 파동)을 상향 교차할 때, 상승 신호로 간주됩니다. 이는 단기적인 추세 변화가 발생할 수 있음을 의미합니다.
CrossDown: Wave 9-17(단기 파동)이 Wave 17-26(중기 파동)을 하향 교차할 때, 하락 신호로 해석됩니다. 이는 시장이 약세로 돌아설 가능성을 나타냅니다.
배경 색상 표시:
교차 신호가 발생할 때, 상승 신호는 녹색 배경, 하락 신호는 빨간색 배경으로 시각적으로 강조되어 사용자가 신호를 쉽게 인식할 수 있습니다.
계산 방식:
이 스크립트는 이동 평균 간의 차이를 계산하여 각 파동의 변동성을 나타냅니다. Wave 9-17, Wave 17-26, Wave 9-26은 각각 설정된 주기의 이동 평균(MA)의 차이를 통해, 시장의 단기, 중기, 장기 추세 변화를 시각적으로 표현합니다.
Wave 9-17 = MA(9) - MA(17): 단기 추세의 차이를 나타냅니다.
Wave 17-26 = MA(17) - MA(26): 중기 추세의 차이를 나타냅니다.
Wave 9-26 = MA(9) - MA(26): 장기적인 추세 방향을 파악할 수 있습니다.
이러한 계산 방식은 파동의 변동성을 파악하는 데 유용하며, 추세의 교차점을 통해 상승/하락 신호를 잡아냅니다.
스크립트의 독창성:
이 스크립트는 기존의 이동 평균 기반 지표들과 달리, TEMA(삼중 지수 이동 평균)와 SMMA(평활 이동 평균)을 함께 사용하여 짧은 주기와 긴 주기의 트렌드를 동시에 파악할 수 있도록 설계되었습니다. 이를 통해 단기 트렌드의 민감한 변화와 장기 트렌드의 안정성을 모두 반영합니다.
TEMA는 단기 트레이더에게 빠르고 민첩한 신호를 제공하며, SMMA는 장기 투자자에게 보다 안정적이고 긴 호흡의 트렌드를 파악하는 데 유리합니다. 두 지표의 결합으로, 다양한 시장 환경에서 추세의 변화를 더 정교하게 분석할 수 있습니다.
사용 방법:
이 스크립트는 추세 분석과 변곡점 포착에 효과적입니다. 각 파동 간의 교차점을 시각적으로 확인하고, 상승 또는 하락 신호를 포착하여 매매 시점 결정을 도울 수 있습니다.
스캘핑 전략에서는 Wave 9-17을 주로 참고하여 빠르게 추세 변화를 잡아내고, 중기 추세를 참고하고 싶은 경우 Wave 17-26을 사용해 신호를 분석할 수 있습니다.
장기적인 시장 흐름을 파악하고자 할 때는 Wave 9-26을 통해 큰 트렌드를 확인할 수 있습니다.
이 스크립트는 파동 이론의 개념을 기반으로 시장의 추세 변화를 예측하는 데 유용하며, 다양한 시간대와 전략에 맞추어 사용할 수 있습니다. 특히, 사용자가 선택한 MA 유형에 따라 파동의 특성을 변화시킬 수 있어, 여러 매매 전략에 유연하게 대응할 수 있습니다.
COMBINED EMA & SMA + DOUBLE DEMA, $TOTAL 1W / 5D -- Ruslan CRYPTOCAP:TOTAL
This Pine Script indicator, **"EMAS"**, provides an enhanced visualization of multiple types of moving averages, including both **Exponential Moving Averages (EMA)**, **Simple Moving Averages (SMA)**, and **Double Exponential Moving Averages (DEMA)**. It allows the user to observe the relationship between these different types of moving averages and apply regime-based coloring to price bars based on the comparison between the EMAs and DEMAs.
#### Key Features:
1. **EMA & SMA:**
- **EMA (Exponential Moving Average):** Calculated using a customizable lookback period (default 17), the EMA places greater weight on more recent prices, making it react faster to price changes.
- **SMA (Simple Moving Average):** Uses an equal-weighted average over a customizable lookback period (default 14), providing a slower-moving average compared to the EMA.
2. **DEMA (Double Exponential Moving Average):**
- Two separate DEMA lines are plotted using different lookback periods (default 2 and 14). The DEMA is a smoother and faster-responding version of the EMA, intended to reduce lag while retaining trend-following characteristics.
3. **Combined Signals:**
- The script calculates ratios between EMA/SMA (`comb`) and DEMA1/DEMA2 (`combd`) to generate a **regime-based bar coloring system**:
- If `combd > comb`: The bars are colored **green**, indicating that DEMAs are outperforming the EMAs, potentially signaling a stronger trend or momentum.
- If `comb > combd`: The bars are colored **red**, suggesting that the EMAs are dominant, which may indicate a different phase of the market.
4. **Signal SMA:**
- A 21-period **SMA** is plotted as a general trend-following signal. It provides a broader perspective on the current price trend, helping to smooth out short-term fluctuations.
5. **Customizable Options:**
- **"Show MAs?"**: The user has the option to toggle the display of the EMA, SMA, and DEMA lines on or off.
- **Custom Period Inputs**: Each type of moving average can have its period length customized via the input settings for better adaptability to different market conditions.
#### How to Use the Indicator:
- **Trend Following**:
The **EMA, SMA, and DEMA** values can help you determine the direction of the trend. When the EMA is above the SMA, it could indicate a stronger, more recent upward momentum. Similarly, DEMA comparisons provide smoother and faster trend signals.
- **Bar Coloring Regime**:
The **bar color** gives a quick visual cue of the regime:
- **Green bars** suggest that DEMAs are indicating stronger bullish or bearish signals compared to the EMAs.
- **Red bars** imply the opposite, where EMAs may be showing stronger signals, but possibly with more noise or lag.
- **Signal SMA**:
The **21-period SMA** line can be used as a simple trend indicator. When the price is above this line, it could signify an uptrend, while price movement below the line might indicate a downtrend.
#### Custom Inputs:
- **EMA Length**: Default is 17, but can be adjusted to fit your trading style.
- **SMA Length**: Default is 14.
- **DEMA Lengths**: Two customizable inputs for DEMA (default 2 and 14).
- **Source Selection**: You can choose which price source (close, open, high, low, etc.) to use for each calculation (default is the closing price).
#### Conclusion:
This indicator is useful for traders who wish to blend **trend-following strategies** (using EMA, SMA, and DEMA) with **visual regime indicators** (bar coloring). It is highly customizable, allowing traders to adjust settings based on their market approach. The combination of EMAs and DEMAs provides a nuanced view of price dynamics, potentially leading to better-informed trading decisions.
Trading Channel Index (TCI)Overview:
The Trading Channel Index (TCI) is a technical analysis tool designed to identify cyclical trends in financial markets by smoothing out price movements and reducing volatility compared to traditional oscillators, like the Commodity Channel Index (CCI). The TCI helps traders pinpoint overbought and oversold conditions, as well as gauge the strength and direction of market trends.
Calculation:
The TCI is calculated through a multi-step process:
Typical Price (Xt): The typical price is computed as the average of the high, low, and close prices for each bar:
Xt = (High + Low + Close) / 3
Exponential Average (Et): This step smooths the typical price over a specified number of bars (TCI Channel Length) using an exponential moving average (EMA). The smoothing factor alpha is derived from the channel length:
Et = alpha * Xt + (1 - alpha) * Et
Where alpha = 2 / (TCI Channel Length + 1).
Average Deviation (Dt): The average deviation measures how much the typical price deviates from the exponential average over time. This is also smoothed using the EMA:
Dt = alpha * abs(Et - Xt) + (1 - alpha) * Dt
Channel Index (CI): The Channel Index is calculated by normalizing the difference between the typical price and the exponential average by the average deviation:
CI = (Xt - Et) / (0.15 * Dt)
Trading Channel Index (TCI): Finally, the TCI is generated by applying additional smoothing to the Channel Index using another EMA over the specified number of bars (TCI Average Length). The smoothing factor beta is derived from the average length:
TCI = beta * CI + (1 - beta) * TCI
Indicator Variables:
TCI Channel Length:
- Description: This variable sets the number of historical bars used to calculate the Channel Index (CI). A shorter length results in a more sensitive CI that responds quickly to price changes, while a longer length produces a smoother and less volatile CI.
- Default Value: 21
TCI Average Length:
-Description: This variable determines the number of bars over which the Channel Index (CI) is smoothed to produce the TCI. A shorter length makes the TCI more responsive to recent price changes, whereas a longer length further smooths the TCI, reducing its sensitivity to short-term fluctuations.
-Default Value: 10
Usage:
Overbought and Oversold Conditions: The TCI often uses levels such as +100 and -100 to identify potential reversal points. When the TCI crosses above +100, it might indicate an overbought condition, signaling a potential sell. Conversely, when it crosses below -100, it could indicate an oversold condition, suggesting a potential buy.
Trend Identification: Sustained values above 0 typically indicate a bullish trend, while values below 0 suggest a bearish trend. The TCI's smoothness helps traders stay in trends longer by reducing the impact of short-term market noise.
Conclusion:
The Trading Channel Index (TCI) is a versatile and powerful tool for traders who wish to capture cyclical price movements with a reduced level of noise. By adjusting the TCI Channel Length and TCI Average Length, traders can tailor the indicator to suit different market conditions, making it applicable across various timeframes and asset classes.
Bitcoin Macro Trend Map [Ox_kali]
## Introduction
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The “Bitcoin Macro Trend Map” script is designed to provide a comprehensive analysis of Bitcoin’s macroeconomic trends. By leveraging a unique combination of Bitcoin-specific macroeconomic indicators, this script helps traders identify potential market peaks and troughs with greater accuracy. It synthesizes data from multiple sources to offer a probabilistic view of market excesses, whether overbought or oversold conditions.
This script offers significant value for the following reasons:
1. Holistic Market Analysis : It integrates a diverse set of indicators that cover various aspects of the Bitcoin market, from investor sentiment and market liquidity to mining profitability and network health. This multi-faceted approach provides a more complete picture of the market than relying on a single indicator.
2. Customization and Flexibility : Users can customize the script to suit their specific trading strategies and preferences. The script offers configurable parameters for each indicator, allowing traders to adjust settings based on their analysis needs.
3. Visual Clarity : The script plots all indicators on a single chart with clear visual cues. This includes color-coded indicators and background changes based on market conditions, making it easy for traders to quickly interpret complex data.
4. Proven Indicators : The script utilizes well-established indicators like the EMA, NUPL, PUELL Multiple, and Hash Ribbons, which are widely recognized in the trading community for their effectiveness in predicting market movements.
5. A New Comprehensive Indicator : By integrating background color changes based on the aggregate signals of various indicators, this script essentially creates a new, comprehensive indicator tailored specifically for Bitcoin. This visual representation provides an immediate overview of market conditions, enhancing the ability to spot potential market reversals.
Optimal for use on timeframes ranging from 1 day to 1 week , the “Bitcoin Macro Trend Map” provides traders with actionable insights, enhancing their ability to make informed decisions in the highly volatile Bitcoin market. By combining these indicators, the script delivers a robust tool for identifying market extremes and potential reversal points.
## Key Indicators
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Macroeconomic Data: The script combines several relevant macroeconomic indicators for Bitcoin, such as the 10-month EMA, M2 money supply, CVDD, Pi Cycle, NUPL, PUELL, MRVR Z-Scores, and Hash Ribbons (Full description bellow).
Open Source Sources: Most of the scripts used are sourced from open-source projects that I have modified to meet the specific needs of this script.
Recommended Timeframes: For optimal performance, it is recommended to use this script on timeframes ranging from 1 day to 1 week.
Objective: The primary goal is to provide a probabilistic solution to identify market excesses, whether overbought or oversold points.
## Originality and Purpose
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This script stands out by integrating multiple macroeconomic indicators into a single comprehensive tool. Each indicator is carefully selected and customized to provide insights into different aspects of the Bitcoin market. By combining these indicators, the script offers a holistic view of market conditions, helping traders identify potential tops and bottoms with greater accuracy. This is the first version of the script, and additional macroeconomic indicators will be added in the future based on user feedback and other inputs.
## How It Works
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The script works by plotting each macroeconomic indicator on a single chart, allowing users to visualize and interpret the data easily. Here’s a detailed look at how each indicator contributes to the analysis:
EMA 10 Monthly: Uses an exponential moving average over 10 monthly periods to signal bullish and bearish trends. This indicator helps identify long-term trends in the Bitcoin market by smoothing out price fluctuations to reveal the underlying trend direction.Moving Averages w/ 18 day/week/month.
Credit to @ryanman0
M2 Money Supply: Analyzes the evolution of global money supply, indicating market liquidity conditions. This indicator tracks the changes in the total amount of money available in the economy, which can impact Bitcoin’s value as a hedge against inflation or economic instability.
Credit to @dylanleclair
CVDD (Cumulative Value Days Destroyed): An indicator based on the cumulative value of days destroyed, useful for identifying market turning points. This metric helps assess the Bitcoin market’s health by evaluating the age and value of coins that are moved, indicating potential shifts in market sentiment.
Credit to @Da_Prof
Pi Cycle: Uses simple and exponential moving averages to detect potential sell points. This indicator aims to identify cyclical peaks in Bitcoin’s price, providing signals for potential market tops.
Credit to @NoCreditsLeft
NUPL (Net Unrealized Profit/Loss): Measures investors’ unrealized profit or loss to signal extreme market levels. This indicator shows the net profit or loss of Bitcoin holders as a percentage of the market cap, helping to identify periods of significant market optimism or pessimism.
Credit to @Da_Prof
PUELL Multiple: Assesses mining profitability relative to historical averages to indicate buying or selling opportunities. This indicator compares the daily issuance value of Bitcoin to its yearly average, providing insights into when the market is overbought or oversold based on miner behavior.
Credit to @Da_Prof
MRVR Z-Scores: Compares market value to realized value to identify overbought or oversold conditions. This metric helps gauge the overall market sentiment by comparing Bitcoin’s market value to its realized value, identifying potential reversal points.
Credit to @Pinnacle_Investor
Hash Ribbons: Uses hash rate variations to signal buying opportunities based on miner capitulation and recovery. This indicator tracks the health of the Bitcoin network by analyzing hash rate trends, helping to identify periods of miner capitulation and subsequent recoveries as potential buying opportunities.
Credit to @ROBO_Trading
## Indicator Visualization and Interpretation
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For each horizontal line representing an indicator, a legend is displayed on the right side of the chart. If the conditions are positive for an indicator, it will turn green, indicating the end of a bearish trend. Conversely, if the conditions are negative, the indicator will turn red, signaling the end of a bullish trend.
The background color of the chart changes based on the average of green or red indicators. This parameter is configurable, allowing adjustment of the threshold at which the background color changes, providing a clear visual indication of overall market conditions.
## Script Parameters
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The script includes several configurable parameters to customize the display and behavior of the indicators:
Color Style:
Normal: Default colors.
Modern: Modern color style.
Monochrome: Monochrome style.
User: User-customized colors.
Custom color settings for up trends (Up Trend Color), down trends (Down Trend Color), and NaN (NaN Color)
Background Color Thresholds:
Thresholds: Settings to define the thresholds for background color change.
Low/High Red Threshold: Low and high thresholds for bearish trends.
Low/High Green Threshold: Low and high thresholds for bullish trends.
Indicator Display:
Options to show or hide specific indicators such as EMA 10 Monthly, CVDD, Pi Cycle, M2 Money, NUPL, PUELL, MRVR Z-Scores, and Hash Ribbons.
Specific Indicator Settings:
EMA 10 Monthly: Options to customize the period for the exponential moving average calculation.
M2 Money: Aggregation of global money supply data.
CVDD: Adjustments for value normalization.
Pi Cycle: Settings for simple and exponential moving averages.
NUPL: Thresholds for unrealized profit/loss values.
PUELL: Adjustments for mining profitability multiples.
MRVR Z-Scores: Settings for overbought/oversold values.
Hash Ribbons: Options for hash rate moving averages and capitulation/recovery signals.
## Conclusion
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The “Bitcoin Macro Trend Map” by Ox_kali is a tool designed to analyze the Bitcoin market. By combining several macroeconomic indicators, this script helps identify market peaks and troughs. It is recommended to use it on timeframes from 1 day to 1 week for optimal trend analysis. The scripts used are sourced from open-source projects, modified to suit the specific needs of this analysis.
## Notes
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This is the first version of the script and it is still in development. More indicators will likely be added in the future. Feedback and comments are welcome to improve this tool.
## Disclaimer:
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Please note that the Open Interest liquidation map is not a guarantee of future market performance and should be used in conjunction with proper risk management. Always ensure that you have a thorough understanding of the indicator’s methodology and its limitations before making any investment decisions. Additionally, past performance is not indicative of future results.
SOL & BTC EMA with BTC/SOL Price Difference % and BTC Dom EMAThis script is designed to provide traders with a comprehensive analysis of Solana (SOL) and Bitcoin (BTC) by incorporating Exponential Moving Averages (EMAs) and price difference percentages. It also includes the BTC Dominance EMA to offer insights into the overall market dominance of Bitcoin.
Features:
SOL EMA: Plots the Exponential Moving Average (EMA) for Solana (SOL) based on a customizable period length.
BTC EMA: Plots the Exponential Moving Average (EMA) for Bitcoin (BTC) based on a customizable period length.
BTC Dominance EMA: Plots the Exponential Moving Average (EMA) for BTC Dominance, which helps in understanding Bitcoin's market share relative to other cryptocurrencies.
BTC/SOL Price Difference %: Calculates and plots the percentage difference between BTC and SOL prices, adjusted for their respective EMAs. This helps in identifying relative strength or weakness between the two assets.
Background Highlight: Colors the background to visually indicate whether the BTC/SOL price difference percentage is positive (green) or negative (red), aiding in quick decision-making.
Inputs:
SOL Ticker: Symbol for Solana (default: BINANCE
).
BTC Ticker: Symbol for Bitcoin (default: BINANCE
).
BTC Dominance Ticker: Symbol for Bitcoin Dominance (default: CRYPTOCAP
.D).
EMA Length: The length of the EMA (default: 20 periods).
Usage:
This script is intended for traders looking to analyze the relationship between SOL and BTC, using EMAs to smooth out price data and highlight trends. The BTC/SOL price difference percentage can help traders identify potential trading opportunities based on the relative movements of SOL and BTC.
Note: Leverage trading involves significant risk and may not be suitable for all investors. Ensure you have a good understanding of the market conditions and employ proper risk management techniques.
Strong Support and Resistance with EMAs @viniciushadek
### Strategy for Using Continuity Points with 20 and 9 Period Exponential Moving Averages, and Support and Resistance
This strategy involves using two exponential moving averages (EMA) - one with a 20-period and another with a 9-period - along with identifying support and resistance levels on the chart. Combining these tools can help determine trend continuation points and potential entry and exit points in market operations.
### 1. Setting Up the Exponential Moving Averages
- **20-Period EMA**: This moving average provides a medium-term trend view. It helps smooth out price fluctuations and identify the overall market direction.
- **9-Period EMA**: This moving average is more sensitive and reacts more quickly to price changes, providing short-term signals.
### 2. Identifying Support and Resistance
- **Support**: Price levels where demand is strong enough to prevent the price from falling further. These levels are identified based on previous lows.
- **Resistance**: Price levels where supply is strong enough to prevent the price from rising further. These levels are identified based on previous highs.
### 3. Continuity Points
The strategy focuses on identifying trend continuation points using the interaction between the EMAs and the support and resistance levels.
### 4. Buy Signals
- When the 9-period EMA crosses above the 20-period EMA.
- Confirm the entry if the price is near a support level or breaking through a resistance level.
### 5. Sell Signals
- When the 9-period EMA crosses below the 20-period EMA.
- Confirm the exit if the price is near a resistance level or breaking through a support level.
### 6. Risk Management
- Use appropriate stops below identified supports for buy operations.
- Use appropriate stops above identified resistances for sell operations.
### 7. Validating the Trend
- Check if the trend is validated by other technical indicators, such as the Relative Strength Index (RSI) or Volume.
### Conclusion
This strategy uses the combination of exponential moving averages and support and resistance levels to identify continuity points in the market trend. It is crucial to confirm the signals with other technical analysis tools and maintain proper risk management to maximize results and minimize losses.
Implementing this approach can provide a clearer view of market movements and help make more informed trading decisions.
LBR-S310ROC @shrilssOriginally made by Linda Raschke, The S310ROC Indicator combines the Rate of Change (ROC) indicator with the 3-10 Oscillator (Modified MACD) and plots to capture rapid price movements and gauge market momentum.
- Rate of Change (ROC): This component of the indicator measures the percentage change in price over a specified short interval, which can be set by the user (default is 2 days). It is calculated by subtracting the closing price from 'X' days ago from the current close.
- 3-10 Oscillator (MACD; 3,10,16): This is a specialized version of the Moving Average Convergence Divergence (MACD) but uses simple moving averages instead of exponential. Using a fast moving average of 3 days and a slow moving average of 10 days with a smoothing period of 16.
- ROC Dots: A great feature based on the oscillator's readings. Dots are displayed directly on the oscillator or the price chart to provide visual momentum cues:
- Aqua Dots: Appear when all lines (ROC, MACD, Slowline) are sloping downwards, indicating bearish momentum and potentially signaling a sell opportunity.
- White Dots: Appear when all lines are sloping upwards, suggesting bullish momentum and possibly a buy signal.
