Machine Learning Breakouts (from Pivots)I developed the 'Machine Learning Breakouts (from Pivots)' indicator to revolutionize the way we detect breakout opportunities and follow trend, harnessing the power of pivot points and machine learning. This tool integrates the k-Nearest Neighbors (k-NN) method with the Euclidean distance algorithm, meticulously analyzing pivot points to accurately forecast multiple breakout paths/zones. "ML Pivots Breakouts" is designed to identify and visually alert traders on bullish breakouts above high lines and bearish breakouts below low lines, offering essential insights for breakout and trend follower traders.
For traders, the instruction is clear: a bullish breakout signal is given when the price crosses above the forecasted high line, indicating potential entry points for long positions. Conversely, a bearish breakout signal is provided when the price breaks below the forecasted low line, suggesting opportunities to enter short positions. This makes the indicator a vital asset for navigating through market volatilities and capitalizing on emerging trends, designed for both long and short strategies and adeptly adapting to market shifts.
In this indicator I operate in a two-dimensional space defined by price and time. The choice of Euclidean distance as the preferred method for this analysis hinges on its simplicity and effectiveness in measuring and predicting straight-line distances between points in this space.
The Machine Learning Breakouts (from Pivots) Indicator calculations have been transitioned to the MLPivotsBreakouts library, simplifying the process of integration. Users can now seamlessly incorporate the "breakouts" function into their scripts to conduct detailed momentum analysis with ease.
Trendfollowing
Ichimoku OscillatorHello All,
This is Ichimoku Oscillator that creates different oscillator layers, calculates the trend and possible entry/exit levels by using Ichimoku Cloud features.
There are four layer:
First layer is the distance between closing price and cloud (min or max, depending on the main trend)
Second layer is the distance between Lagging and Cloud X bars ago (X: the displacement)
Third layer is the distance between Conversion and Base lines
Fourth layer is the distance between both Leadlines
If all layers are visible maning that positive according to the main trend, you can take long/short position and when main trend changed then you should close the position. so it doesn't mean you can take position when main trend changed, you need to wait for all other conditions met (all layers(
there is take profit partially option. if Conversion and base lines cross then you can take profit partially. Optionally you can take profit partially when EMA line crosses Fourth layer.
Optionally ATR (average true range) is used for Conversion and baseline for protection from whipsaws. you can use it to stay on the trend longer time.
I added options to enable/disable the alert and customize alert messages. You can change alert messages as you wish. if you use ' close ' in the alert message then you can get closing price in the alert message when the alert was triggered.
There is an option Bounce Off Support/Resistance , if there is trend and if the price bounce off Support/Resistance zone then a tiny triangle is shown.
There are many other options for coloring, alerts etc.
Some screenshots:
Main trend:
Taking/closing positions:
Example alert messages:
Bounce off:
Colors:
Colors:
Colors:
Non-colored background:
P.S. For a few months I haven't published any new script because of some health issues. hope to be healthy and create new scripts in 2024 :)
Enjoy!
Normalised Gaussian MACD Heikin Ashi [AlgoAlpha]🌟🚀Introducing the Normalised Gaussian MACD Heikin Ashi by AlgoAlpha !
Elevate your trading game with this multipurpose indicator, crafted to pinpoint trend continuation opportunities while highlighting volatility and oversold/overbought conditions. Whether you're embarking on your trading journey or you're a seasoned market navigator, this tool is equipped with intuitive visual cues to amplify your decision-making prowess and enrich your market analysis toolkit. Let's dive into the key features, utilization strategies, and the innovative logic underpinning this indispensable trading asset.
Key Features:
🔧 Enhanced Customization : Tailor your experience with adjustable parameters including Fast Length, Slow Length, Source, Macd Smoothing Length, Signal Smoothing, and more.
🖌️ Visual Enhancements : Opt for Heikin Ashi Candles display and choose to show or hide MACD and Signal lines for a clutter-free chart.
🌈 Color Customization : Personalize your chart with selectable primary and secondary up and down colors to suit your visual preferences.
🔔 Advanced Alert System : Stay ahead with comprehensive alert conditions for market movements, including trend reversals, bullish and bearish swings.
How to Use:
Configure the Inputs : Start by customizing the indicator’s settings to match your trading style. Adjust the length parameters, source selection, and smoothing lengths to fine-tune the indicator’s sensitivity.
Interpret the Candles and Colors : Keep an eye on the Heikin Ashi Candles (if enabled) and the color shifts within the MACD Line Candles and Histogram. These visual cues are pivotal for identifying market trends.
Analyze with Flexibility : Make use of the option to display or hide the MACD and Signal lines based on your analysis requirements. This can help in focusing on the essential information without overcrowding your chart.
Utilize Alerts for Timely Decisions : Leverage the extensive alert system to get notified about potential market movements. These alerts can help you capture the right moment to enter or exit trades.
Basic Logic:
The Normalised Gaussian MACD Heikin Ashi by AlgoAlpha integrates Gaussian filters to elevate the traditional MACD indicator's efficiency, providing a more detailed analysis of market trends and momentum. This sophisticated approach reduces noise and enhances signal speed, which is crucial for identifying momentum trading opportunities.
Gaussian Filter Implementation : The core innovation lies in applying a Gaussian filter to the input price series. This mathematical technique smooths the price data, significantly reducing market noise and making trend signals clearer and more reliable. The Gaussian filter calculates a smoothed value for each data point by weighting nearby data points, with the weights decreasing as the distance from the current data point increases.
Refined MACD Calculation : The Gaussian MACD is derived from the difference between two Gaussian smoothed moving averages (fast and slow), which are then normalized to account for market volatility. This normalization process involves dividing the difference by a measure of market range (such as the high minus the low), and multiplying by a factor (usually 100) to scale the indicator appropriately.
🔑 This script is a versatile tool designed to aid in the identification of momentum and reversals, helping traders to make informed decisions based on technical analysis. Its customization options allow for a tailored analysis experience, fitting the unique needs and strategies of each trader.
Trend Continuation Signals [AlgoAlpha]Introducing the Trend Continuation Signals by AlgoAlpha 🌟🚀
Elevate your trading game with this multipurpose indicator, designed to pinpoint trend continuation opportunities as well as highlight volatility and oversold/overbought conditions. Whether you're a trading novice or a seasoned market veteran, this tool offers intuitive visual cues to boost your decision-making and enhance your market analysis. Let's explore the key features, how to use it effectively, and delve into the operational mechanics that make this tool a game-changer in your trading arsenal:
Key Features:
🔥 Advanced Trend Detection : Leverages the Hull Moving Average (HMA) for superior trend tracking as compared to other MAs, offering unique insights into market momentum.
🌈 Volatility Bands : Implements adjustable bands around the trend line, which evolve with market conditions to highlight potential trading opportunities.
⚡ Trend Continuation Signals : Identifies bullish and bearish continuation signals, equipping you with actionable signals to exploit the prevailing market trend.
🎨 Intuitive Color Coding : Employs a vibrant color scheme to distinguish between uptrends, downtrends, and neutral phases, facilitating easy interpretation of the indicator's insights.
🛠 How to Use "Trend Continuation Signals ":
🔍 Setting Up : Incorporate the indicator onto your chart and customize the indicator to suite your preferences.
👀 Reading the Signals : Pay attention to the color-coded trend lines and volatility bands. Green indicates an uptrend, red signifies a downtrend, and gray denotes a neutral market condition.
📈 Identifying Entry Points : Look for bullish (▲) and bearish (▼) continuation icons below or above the price bars as signals for potential entry points for long or short positions, respectively.
🔄 Confirmation : Validate your trades with further analysis or other indicators. The Trend Continuation Signals are most effective when complemented by other technical analysis tools or fundamental insights.
📉 Risk Management : Implement stop-loss orders in line with your risk appetite and adjust them based on the volatility bands provided by the indicator to safeguard your investments.
How It Operates:
The essence of the indicator is captured through the hull moving averages for both the primary and secondary lines, set at periods of 93 and 50, respectively, to reflect market trends and pullbacks that trigger the continuation signals every time price recovers from a detected pullback.
Volatility is quantified through the standard deviation of the midline, magnified by a factor, establishing the upper and lower trend band boundaries.
Further volatility bands are plotted around the main volatility band, providing a granular view of market volatility and potential breakout or breakdown zones.
Market trend direction is determined by comparing the HMA line's current position to its previous value, enhanced by the secondary line to identify continuation patterns.
Embrace the power of the Trend Continuation Signals to enhance your trading strategy! It is important to note that all indicators are best used in confluence with other forms of analysis, happy trading! 📊💥
Price SextantThe provided Pine Script™ code is for a technical analysis indicator called "Price Sextant." This indicator helps visualize the price position relative to its linear regression and standard deviation levels. Here's a brief description:
Price Sextant Indicator:
Purpose:
The Price Sextant indicator aims to show the current price's deviation from the linear regression line by dividing the price chart into different zones or sextants.
Components:
Linear Regression: The script calculates a linear regression line based on the closing prices over a specified length (default is 50 bars).
Standard Deviation Sections: It then computes standard deviation levels from the linear regression, creating upper and lower sections around the regression line.
Scoring: Each section is assigned a numerical score, and labels with corresponding scores are displayed on the chart.
Arrow and Midline: An arrow is drawn to indicate the current price's position in relation to the regression line and standard deviation bands. It changes color based in what section it is:
orange section shows a ranging price, below orange section -1 arrow turns red and show down trend and if arrow above +1 section it turns green and show strong up trend of price.
A midline is plotted to mark the position of the linear regression line.
Sextant Description:
In navigation, a sextant is an instrument used to measure the angle between two visible objects.
In the context of this indicator, the term "Sextant" is likely used metaphorically to describe the division of the price chart into six sections or zones based on the linear regression and standard deviation bands.
This indicator can help traders identify potential overbought or oversold conditions, as well as assess the strength and direction of the trend.
Please note that the effectiveness of the indicator depends on various factors, and it's advisable to use it in conjunction with other analysis tools for a comprehensive trading strategy.
Reversal and Breakout Signals [AlgoAlpha]🚀🌟 Introducing the Reversal and Breakout Signals by AlgoAlpha 🌟🚀
This innovative tool is crafted to enhance your chart analysis by identifying potential reversal and breakout opportunities directly on your charts. It's designed with both novice and experienced traders in mind, providing intuitive visual cues for better decision-making. Let's dive into the key features and how it operates:
### Key Features:
🔶 Dynamic Period Settings: Customize the sensitivity of the indicator with user-defined periods for both the indicator and volume strength.
📊 Volume Threshold: Set a threshold to define what constitutes strong volume, enabling the identification of significant market movements.
💡 Trend Coloring: Option to color candles during trends, making it easier to visualize bullish and bearish market conditions.
🌈 Customizable Visuals: Choose your preferred colors for bullish, bearish, and breakout signals, personalizing the chart to your liking.
🚨 Advanced Alert System: Configure alerts for reversal and breakout signals, ensuring you never miss a potential trading opportunity.
### How to Use:
To maximize the effectiveness of the Reversal and Breakout Signals tool, follow these steps:
1. 🔧 Set Up Your Preferences:
- Adjust the Indicator Period and Volume Strength Period to match the timeframe of your trading strategy. This fine-tuning allows the indicator to better align with your specific market analysis needs.
- Define the Strong Volume Threshold to distinguish between ordinary and significant volume movements. This helps in identifying breakout or reversal signals with higher confidence.
2. 🎨 Customize Visuals:
- Choose colors for Bullish , Bearish , and Breakout Signals to visually differentiate between different types of market activities. This customization facilitates quicker decision-making while scanning charts.
3. 🔍 Reversal Signals:
- Bullish Reversal : Look for a triangle below the bar indicating a potential upward movement. It's identified when the price dips below the lower level but closes above it, suggesting a rejection of lower prices.
- Bearish Reversal : A triangle above the bar signals a potential downward movement. This occurs when the price spikes above the upper level but closes below, indicating a rejection of higher prices.
4. 📈 Trend and Breakout Signals:
- Diamonds represent breakout signals. A bullish breakout is marked below the bar when the price closes above the upper level, suggesting strong buying pressure. Conversely, a bearish breakout above the bar indicates strong selling pressure as the price closes below the lower level.
- The tool also features a Trend Tracker that highlights the current market trend using the Hull Moving Average (HMA). This can help you stay aligned with the overall market direction for your trades.
By integrating these steps into your trading strategy, the Reversal and Breakout Signals tool can provide actionable insights to help identify potential entry and exit points, enhancing your trading decisions with visual cues and alerts for market reversals and breakouts.
### How It Works:
The core logic revolves around calculating weighted moving averages of high and low prices over a user-defined period, identifying the highest and lowest points within this period to establish potential breakout or breakdown levels while reducing the amount of noise, hence the use of moving averages.
1. Weighted Moving Averages Calculation:
sh = ta.wma(high, len)
sl = ta.wma(low, len)
h = ta.highest(sh, len)
l = ta.lowest(sl, len)
2. Breakout and Reversal Detection:
The script then employs logic to detect bullish and bearish breakouts and reversals based on the closing price's position relative to these levels, combined with volume analysis to confirm the strength of the move.
if not (h < h or h > h )
hstore := h
if not (l < l or l > l )
lstore := l
bullishbreakout := (breakout or ((breakout or breakout or breakout or breakout ) and candledir == 1)) and strongvol and not (bullishbreakout or bullishbreakout or bullishbreakout )
bearishbreakout := (breakdown or ((breakdown or breakdown or breakdown or breakdown ) and candledir == -1)) and strongvol and not (bearishbreakout or bearishbreakout or bearishbreakout )
3. Visual Indicators and Alerts:
Visual cues such as triangle shapes for reversals and diamonds for breakouts, along with colored bars, make it easy to spot these opportunities. Additionally, alerts can be set up for these events, ensuring traders can react promptly to potential trading setups.
plotshape(bullishrej and not (state ==- 1) ? low * 0.9995 : na, " Bullish Reversal ", shape.triangleup, location.belowbar, color.new(green, 0), size = size.tiny, text = "𝓡", textcolor = color.gray)
plotshape(bearishrej and not (state == 1) ? high * 1.0005 : na, " Bearish Reversal ", shape.triangledown, location.abovebar, color.new(red, 0), size = size.tiny, text = "𝓡", textcolor = color.gray)
plotshape(bullishbreakout ? low * 0.999 : na, " Bullish Breakout ", shape.diamond, location.belowbar, color.new(yellow, 0), size = size.tiny, text = "𝓑", textcolor = color.gray)
plotshape(bearishbreakout ? high * 1.001 : na, " Bearish Breakout ", shape.diamond, location.abovebar, color.new(yellow, 0), size = size.tiny, text = "𝓑", textcolor = color.gray)
This script is a versatile tool designed to aid in the identification of key reversal and breakout points, helping traders to make informed decisions based on technical analysis. Its customization options allow for a tailored analysis experience, fitting the unique needs and strategies of each trader.
MVRV Z-Score [AlgoAlpha]Introducing the ∑ MVRV Z-Score by AlgoAlpha, a dynamic and sophisticated tool designed for traders seeking to gain an edge in INDEX:BTCUSD analysis. This script employs advanced statistical techniques on Bitcoin On-Chain data to offer a deeper understanding of market conditions, focusing on valuation extremes and momentum trends. Let's explore the features and functionalities that make this tool a valuable addition to your trading arsenal.
Key Features:
🔶 Adjustable Parameters: Customize the Z score lookback length, moving average lookback length, and choose from six moving average types, tailoring the analysis to your trading style.
🔶 Heiken Ashi Compatibility: Incorporate Heiken Ashi plots to visualize market trends, adding a layer of clarity to your technical analysis.
🔶 Divergence Alerts: Detect significant bullish and bearish divergences, allowing for timely identification of potential market reversals.
🔶 Configurable Alerts: Set alerts for overbought, oversold, and divergence conditions, ensuring you never miss an opportunity.
How to Use:
1. ➡️ Parameter Selection: Start by configuring the Z-Score and moving average settings according to your analysis needs. This includes selecting the lookback period and the type of moving average.
2. ➡️ Visualization Options: Choose to enable Heiken Ashi plots for an alternative view of the Z-Score, which can help in identifying trend directions more clearly.
3. ➡️ Monitor for Signals: Keep an eye out for divergence signals and overbought/oversold conditions as potential indicators for entering or exiting trades.
4. ➡️ Alert Setup: Configure alerts based on your selected parameters to receive notifications for important market movements and conditions.
How It Works:
The core of this tool is the Z-Score calculation, which assesses the standard deviation of the current market value from its mean, highlighting overvalued or undervalued market conditions. Here's a brief overview of the script's operational mechanics:
1. 📊 Calculating the Z-Score: The script first calculates the mean over a user-defined lookback period of the MVRV ratio, then it computes the Z-Score to identify deviations from the average.
meanValue = ta.sma(marketValue, zScoreLookback)
zScoreValue = (marketValue - meanValue) / ta.stdev(marketValue, zScoreLookback)
2. 📈 Applying a Moving Average: To smooth the Z-Score data and make trends more discernible, a moving average is applied. Users can choose from several types, such as SMA, EMA, or HMA, based on their preference.
3. 🔄 Heiken Ashi Visualization: For those opting for a more intuitive trend analysis, Heiken Ashi plots can be enabled, transforming the Z-Score data into candlestick charts that simplify trend identification.
4. 🔍 Identifying Divergences: The script is equipped to spot divergences between the market price action and the Z-Score, signaling potential bullish or bearish market reversals.
oscHigherLow = haClose > ta.valuewhen(findPivotLow, haClose , 1) and isInRange(findPivotLow )
priceLowerLow = low < ta.valuewhen(findPivotLow, low , 1)
bullishCondition = enablePlotBullish and priceLowerLow and oscHigherLow and findPivotLow
5. 🚨 Configurable Alerts: Lastly, the script allows for the setting of customizable alerts based on the Z-Score, moving averages, and identified divergences, enabling traders to react promptly to market changes.
The ∑ MVRV Z-Score by AlgoAlpha is an essential tool for traders looking to analyze and interpret market dynamics through a quantitatively rigorous lens. Whether you're focused on identifying market extremes or tracking trend momentum, this script offers the insights needed to support informed trading decisions. 🌟📊💡
SuperTrend Fisher [AlgoAlpha]🚀🌟 Introducing the "Super Fisher" by AlgoAlpha, a sophisticated and versatile tool crafted for the discerning trader. This innovative indicator merges the precision of the Fisher Transform with the adaptability of the SuperTrend methodology, offering a fresh perspective on market analysis. 📈🔍
Key Features:
🔶 Customizable Settings: Tailor the indicator to your trading style with adjustable inputs like "Fair-value Period" and "EMA Length". Choose your preferred "Up Color" and "Down Color" for a personalized visual experience.
🔶 Advanced Fisher Transform: At the heart of this tool is the Fisher Transform, an algorithm renowned for pinpointing potential price reversals by normalizing asset prices.
🔶 Integrated SuperTrend Functionality: This feature adds a layer of trend analysis, using the refined Fisher Transform values to generate dynamic, trend-following signals.
🔶 Enhanced Visualization: Clearly distinguishable bullish and bearish market phases, thanks to the color-coded plots of Fisher Transform and SuperTrend values.
🔶 Overbought/Oversold Levels: Visual plots and fills for these levels provide additional insights into market extremities.
🔶 Configurable Alerts: Stay informed with alerts for critical market movements like crossing the zero line or the SuperTrend.
Logic:
The "Super Fisher" operates on a sophisticated algorithm:
1. Fisher Transform Calculation: It starts by calculating the Detrended Price Oscillator (DPO) and its standard deviation. These values are then transformed using the Fisher Transform formula, which is subsequently smoothed with a Hull Moving Average.
2. SuperTrend Integration: The SuperTrend function employs the Fisher Transform values to create a dynamic trend-following tool. It calculates upper and lower bands and determines which one to use for market direction based on whether the fisher is above or below the bands, offering an insightful view of the price trend.
3. Overbought/Oversold Identification: The tool plots specific levels to indicate overbought and oversold conditions, aiding in the identification of potential reversal points.
Here's a closer look at the core calculations:
Calculates the Fisher Transform:
value = 0.0
value := round_(.66 * ((src - low_) / (high_ - low_) - .5) + .67 * nz(value ))
fish1 = 0.0
fish1 := .5 * math.log((1 + value) / (1 - value)) + .5 * nz(fish1 )
fish1 := ta.hma(fish1, l)
Calculates the SuperTrend:
supertrend(factor, atrPeriod, srcc) =>
src = srcc
atr = atrr(srcc, atrPeriod)
upperBand = src + factor * atr
lowerBand = src - factor * atr
prevLowerBand = nz(lowerBand )
prevUpperBand = nz(upperBand )
lowerBand := lowerBand > prevLowerBand or srcc < prevLowerBand ? lowerBand : prevLowerBand
upperBand := upperBand < prevUpperBand or srcc > prevUpperBand ? upperBand : prevUpperBand
int direction = na
float superTrend = na
prevSuperTrend = superTrend
if na(atr )
direction := 1
else if prevSuperTrend == prevUpperBand
direction := srcc > upperBand ? -1 : 1
else
direction := srcc < lowerBand ? 1 : -1
superTrend := direction == -1 ? lowerBand : upperBand
How to Use:
📊 To maximize the potential of the "Super Fisher", follow these steps:
1. Customize Settings: Adjust the inputs to match your trading preferences. This includes setting the periods for the Fisher Transform and SuperTrend, as well as choosing colors for better visualization.
2. Analyze the Market: Observe the Fisher Transform and SuperTrend plots to gauge market direction. Pay special attention to color changes, as they indicate shifts in market sentiment.
3. Identify Extremes: Use the overbought and oversold plots to understand potential reversal points.
4. Set Alerts: Utilize the alert functionality to stay informed about significant market movements, ensuring you never miss an opportunity.
🔥 In summary the "Super Fisher" is a comprehensive market analysis tool designed to enhance your trading insights and decision-making process. 📉🌟🚨
Enhanced Candle Sticks [AlgoAlpha]🚀🌟 Introducing the Enhanced Candle Sticks by AlgoAlpha, a Pine Script tool designed to provide traders with an enhanced view of market dynamics through candlestick analysis. This script aims to visualise if price has hit the high or low of the candle first, aiding in back-testing, and to identify smaller trends using market structure.📊🔍
Key Features:
Timeframe Flexibility: Users can select their desired timeframe for analysis, offering a range of options from M15 to H12. This flexibility allows for detailed and specific timeframe analysis.
Micro Trend Identification: The script includes an option to enable 'MicroTrends', giving traders insights into smaller movements and trends within the larger market context.
Customizable Visuals: Traders can customize the colors of bullish and bearish candlesticks, enhancing visual clarity and personalizing the chart to their preferences.
State Tracking: The script tracks the 'state' of the market on lower timeframes to detect if the high or the low was formed first.
Warning System: When the selected timeframe does not match the chart timeframe, the script generates a warning, ensuring accurate analysis and preventing potential misinterpretations.
Usages:
Enhanced Back-testing: Users can now get a more accurate interpretation of the candlesticks by know if the high or the low came first (denoted with ⩚ or ⩛), especially in scenarios where the high and the low of the larger timeframe candle is touching both the take-profit and stop-loss levels.
Squeeze Analysis: Users can identify squeezes in price when the microtrend shows both an uptrend and a downtrend, possibly giving more insight into the market.
Lower Timeframe Market Structure Analysis: Microtrends form when the low of the candle is consecutively increasing and the high is consecutively falling, which means on a lower timeframe, price is forming higher lows or lower highs.
Basic Logic Explanation:
- The script starts by setting up the necessary parameters and importing the required library. Users can customize the timeframe, colors, and whether to enable micro trends and candlestick plotting.
- It then calculates the lower timeframe (1/12th of the current timeframe) for more detailed analysis. The `minutes` function helps in converting the selected timeframe into minutes.
- The script tracks new bars and calculates the highest and lowest values within an hour, using `ta.highestSince` and `ta.lowestSince`.
- It determines the market 'state' by checking if the current high is breaking the previous high and if the current low is breaking the previous low on lower timeframes to determine if the high or the low was formed first.
- The script uses the `plotchar` and `plotcandle` functions to visually represent these trends and states on the chart. This visual representation is key for quick and effective analysis.
Alerts:
Alerts can be set for microtrend formations:
This script is a valuable tool for traders looking to deepen their market analysis with enhanced candlestick visualization and micro trend tracking. 📈🔶💡
Standardized Orderflow [AlgoAlpha]Introducing the Standardized Orderflow indicator by AlgoAlpha. This innovative tool is designed to enhance your trading strategy by providing a detailed analysis of order flow and velocity. Perfect for traders who seek a deeper insight into market dynamics, it's packed with features that cater to various trading styles. 🚀📊
Key Features:
📈 Order Flow Analysis: At its core, the indicator analyzes order flow, distinguishing between bullish and bearish volume within a specified period. It uses a unique standard deviation calculation for normalization, offering a clear view of market sentiment.
🔄 Smoothing Options: Users can opt for a smoothed representation of order flow, using a Hull Moving Average (HMA) for a more refined analysis.
🌪️ Velocity Tracking: The indicator tracks the velocity of order flow changes, providing insights into the market's momentum.
🎨 Customizable Display: Tailor the display mode to focus on either order flow, order velocity, or both, depending on your analysis needs.
🔔 Alerts for Critical Events: Set up alerts for crucial market events like crossover/crossunder of the zero line and overbought/oversold conditions.
How to Use:
1. Setup: Easily configure the indicator to match your trading strategy with customizable input parameters such as order flow period, smoothing length, and moving average types.
2. Interpretation: Watch for bullish and bearish columns in the order flow chart, utilize the Heiken Ashi RSI candle calculation, and look our for reversal notations for additional market insights.
3. Alerts: Stay informed with real-time alerts for key market events.
Code Explanation:
- Order Flow Calculation:
The core of the indicator is the calculation of order flow, which is the sum of volumes for bullish or bearish price movements. This is followed by normalization using standard deviation.
orderFlow = math.sum(close > close ? volume : (close < close ? -volume : 0), orderFlowWindow)
orderFlow := useSmoothing ? ta.hma(orderFlow, smoothingLength) : orderFlow
stdDev = ta.stdev(orderFlow, 45) * 1
normalizedOrderFlow = orderFlow/(stdDev + stdDev)
- Velocity Calculation:
The velocity of order flow changes is calculated using moving averages, providing a dynamic view of market momentum.
velocityDiff = ma((normalizedOrderFlow - ma(normalizedOrderFlow, velocitySignalLength, maTypeInput)) * 10, velocityCalcLength, maTypeInput)
- Display Options:
Users can choose their preferred display mode, focusing on either order flow, order velocity, or both.
orderFlowDisplayCond = displayMode != "Order Velocity" ? display.all : display.none
wideDisplayCond = displayMode != "Order Flow" ? display.all : display.none
- Reversal Indicators and Divergences:
The indicator also includes plots for potential bullish and bearish reversals, as well as regular and hidden divergences, adding depth to your market analysis.
bullishReversalCond = reversalType == "Order Flow" ? ta.crossover(normalizedOrderFlow, -1.5) : (reversalType == "Order Velocity" ? ta.crossover(velocityDiff, -4) : (ta.crossover(velocityDiff, -4) or ta.crossover(normalizedOrderFlow, -1.5)) )
bearishReversalCond = reversalType == "Order Flow" ? ta.crossunder(normalizedOrderFlow, 1.5) : (reversalType == "Order Velocity" ? ta.crossunder(velocityDiff, 4) : (ta.crossunder(velocityDiff, 4) or ta.crossunder(normalizedOrderFlow, 1.5)) )
In summary, the Standardized Orderflow indicator by AlgoAlpha is a versatile tool for traders aiming to enhance their market analysis. Whether you're focused on short-term momentum or long-term trends, this indicator provides valuable insights into market dynamics. 🌟📉📈
Standardized Median Proximity [AlgoAlpha]Introducing the Standardized Median Proximity by AlgoAlpha 🚀📊 – a dynamic tool designed to enhance your trading strategy by analyzing price fluctuations relative to the median value. This indicator is built to provide clear visual cues on the price deviation from its median, allowing for a nuanced understanding of market trends and potential reversals.
🔍 Key Features:
1. 📈 Median Tracking: At the core of this indicator is the calculation of the median price over a specified lookback period. By evaluating the current price against this median, the indicator provides a sense of whether the price is trending above or below its recent median value.
medianValue = ta.median(priceSource, lookbackLength)
2. 🌡️ Normalization of Price Deviation: The deviation of the price from the median is normalized using standard deviation, ensuring that the indicator's readings are consistent and comparable across different time frames and instruments.
standardDeviation = ta.stdev(priceDeviation, 45)
normalizedValue = priceDeviation / (standardDeviation + standardDeviation)
3. 📌 Boundary Calculations: The indicator sets upper and lower boundaries based on the normalized values, helping to identify overbought and oversold conditions.
upperBoundary = ta.ema(positiveValues, lookbackLength) + ta.stdev(positiveValues, lookbackLength) * stdDevMultiplier
lowerBoundary = ta.ema(negativeValues, lookbackLength) - ta.stdev(negativeValues, lookbackLength) * stdDevMultiplier
4. 🎨 Visual Appeal and Clarity: With carefully chosen colors, the plots provide an intuitive and clear representation of market states. Rising trends are indicated in a shade of green, while falling trends are shown in red.
5. 🚨 Alert Conditions: Stay ahead of market movements with customizable alerts for trend shifts and impulse signals, enabling timely decisions.
alertcondition(ta.crossover(normalizedValue, 0), "Bullish Trend Shift", "Median Proximity Crossover Zero Line")
🔧 How to Use:
- 🎯 Set your preferred lookback lengths and standard deviation multipliers to tailor the indicator to your trading style.
- 💹 Utilize the boundary plots to understand potential overbought or oversold conditions.
- 📈 Analyze the color-coded column plots for quick insights into the market's direction relative to the median.
- ⏰ Set alerts to notify you of significant trend changes or conditions that match your trading criteria.
Basic Logic Explained:
- The indicator first calculates the median of the selected price source over your chosen lookback period. This median serves as a baseline for measuring price deviation.
- It then standardizes this deviation by dividing it by the standard deviation of the price deviation over a 45-period lookback, creating a normalized value.
- Upper and lower boundaries are computed using the exponential moving average (EMA) and standard deviation of these normalized values, adjusted by your selected multiplier.
- Finally, color-coded plots provide a visual representation of these calculations, offering at-a-glance insights into market conditions.
Remember, while this tool offers valuable insights, it's crucial to use it as part of a comprehensive trading strategy, complemented by other analysis and indicators. Happy trading!
🚀
Trend Change IndicatorThe Trend Change Indicator is an all-in-one, user-friendly trend-following tool designed to identify bullish and bearish trends in asset prices. It features adjustable input values and a built-in alert system that promptly notifies investors of potential shifts in both short-term and long-term price trends. This alert system is crucial for helping less active investors correctly position themselves ahead of major trend shifts and assists in risk management after a trend is established. It's important to note that this indicator is most effective with assets that historically exhibit strong trends.
At the heart of this tool is the interaction between the 30-day and 60-day Exponential Moving Averages (EMA). A bullish trend is indicated in green when the 30-day EMA is above the 60-day EMA, while a bearish trend is signaled in red when the 30-day EMA is below the 60-day EMA. The appearance of gray alerts users to potential shifts in the current trend as the EMAs converge, falling below the Average True Range (ATR) safety margin. This analysis is conducted across both hourly and daily timeframes, with the 4-hour timeframe providing early signals for daily trend changes. The band visually represents the interaction between the daily EMAs and is also displayed in the second row of the table, with the first row showing the same EMA interaction on the 4-hour timeframe.
This indicator also includes a 140-day (20-week) Simple Moving Average (SMA), visually represented by a line with predictive dots. This feature significantly enhances the investor's ability to understand long-term trends in asset prices, offering forward-looking insights by projecting the SMA value 10 days into the future. The value of this forecast lies in interpreting the slope of the dots; upward trending dots suggest a bullish underlying trend, while downward trending dots indicate a bearish trend. Generally, prices above the SMA signal bullishness, and prices below indicate bearishness.
In summary, the Trend Change Indicator is a comprehensive solution for identifying price trends and managing risk. Its intuitive, color-coded design makes it an indispensable tool for traders and investors who aim to be well-positioned ahead of trend shifts and manage risk once a trend has been established. While it has proven historically valuable in trending markets such as cryptocurrencies, tech stocks, and commodities, it is advisable to use this indicator in conjunction with other technical analysis tools for a more comprehensive and well-rounded decision-making process.
Volume-Trend Sentiment (VTS) [AlgoAlpha]Introducing the Volume-Trend Sentiment by AlgoAlpha, a unique tool designed for traders who seek a deeper understanding of market sentiment through volume analysis. This innovative indicator offers a comprehensive view of market dynamics, blending volume trends with price action to provide an insightful perspective on market sentiment. 🚀📊
Key Features:
1. 🌟 Dual Trend Analysis: This indicator combines the concepts of price movement and volume, offering a multi-dimensional view of market sentiment. By analyzing the relationship between the closing and opening prices relative to volume, it provides a nuanced understanding of market dynamics.
2. 🎨 Customizable Settings: Flexibility is at the core of this indicator. Users can adjust various parameters such as the length of the volume trend, standard deviation, and SMA length, ensuring a tailored experience to match individual trading strategies.
3. 🌈 Visual Appeal: With options to display noise, the main plot, and background colors, the indicator is not only informative but also visually engaging. Users can choose their preferred colors for up and down movements, making the analysis more intuitive.
4. ⚠️ Alerts for Key Movements: Stay ahead of market changes with built-in alert conditions. These alerts notify traders when the Volume-Trend Sentiment crosses above or below the midline, signaling potential shifts in market momentum.
How It Works:
The core of the indicator is the calculation of the Volume-Trend Sentiment (VTS). It is computed by subtracting a double-smoothed Exponential Moving Average (EMA) of the price-volume ratio from a single EMA of the same ratio. This method highlights the trend in volume relative to price changes.
volumeTrend = ta.ema((close - open) / volume, volumeTrendLength) - ta.ema(ta.ema((close - open) / volume, volumeTrendLength), volumeTrendLength)
To manage volatility and noise in the volume trend, the indicator employs a standard deviation calculation and a Simple Moving Average (SMA). This smoothing process helps in identifying the true underlying trend by filtering out extreme fluctuations.
standardDeviation = ta.stdev(volumeTrend, standardDeviationLength) * 1
smoothedVolumeTrend = ta.sma(volumeTrend / (standardDeviation + standardDeviation), smaLength)
A unique feature is the dynamic background color, which changes based on the sentiment level. This visual cue instantly communicates the market's bullish or bearish sentiment, enhancing the decision-making process.
getColor(volumeTrendValue) =>
sentimentLevel = math.abs(volumeTrendValue * 10)
baseTransparency = 60 // Base transparency level
colorTransparency = math.max(90 - sentimentLevel * 5, baseTransparency)
volumeTrendValue > 0 ? color.new(upColor, colorTransparency) : color.new(downColor, colorTransparency)
bgcolor(showBackgroundColor ? getColor(smoothedVolumeTrend) : na)
In summary, the Volume-Trend Sentiment by AlgoAlpha is a comprehensive tool that enhances market analysis through a unique blend of volume and price trends. Whether you're a seasoned trader or just starting out, this indicator offers valuable insights into market sentiment and helps in making informed trading decisions. 📈📉🔍🌐
Median Proximity Percentile [AlgoAlpha]📊🚀 Introducing the "Median Proximity Percentile" by AlgoAlpha, a dynamic and sophisticated trading indicator designed to enhance your market analysis! This tool efficiently tracks median price proximity over a specified lookback period and finds it's percentile between 2 dynamic standard deviation bands, offering valuable insights for traders looking to make informed decisions.
🌟 Key Features:
Color-Coded Visuals: Easily interpret market trends with color-coded plots indicating bullish or bearish signals.
Flexibility: Customize the indicator with your preferred price source and lookback lengths to suit your trading strategy.
Advanced Alert System: Stay ahead with customizable alerts for key trend shifts and market conditions.
🔍 Deep Dive into the Code:
Choose your preferred price data source and define lookback lengths for median and EMA calculations. priceSource = input.source(close, "Source") and lookbackLength = input.int(21, minval = 1, title = "Lookback Length")
Calculate median value, price deviation, and normalized value to analyze market position relative to the median. medianValue = ta.median(priceSource, lookbackLength)
Determine upper and lower boundaries based on standard deviation and EMA. upperBoundary = ta.ema(positiveValues, lookbackLength) + ta.stdev(positiveValues, lookbackLength) * stdDevMultiplier
lowerBoundary = ta.ema(negativeValues, lookbackLength) - ta.stdev(negativeValues, lookbackLength) * stdDevMultiplier
Compute the percentile value to track market position within these boundaries. percentileValue = 100 * (normalizedValue - lowerBoundary)/(upperBoundary - lowerBoundary) - 50
Enhance your analysis with Hull Moving Average (HMA) for smoother trend identification. emaValue = ta.hma(percentileValue, emaLookbackLength)
Visualize trends with color-coded plots and characters for easy interpretation. plotColor = percentileValue > 0 ? colorUp : percentileValue < 0 ? colorDown : na
Set up advanced alerts to stay informed about significant market movements. // Alerts
alertcondition(ta.crossover(emaValue, 0), "Bullish Trend Shift", "Median Proximity Percentile Crossover Zero Line")
alertcondition(ta.crossunder(emaValue, 0), "Bearish Trend Shift", "Median Proximity Percentile Crossunder Zero Line")
alertcondition(ta.crossunder(emaValue,emaValue ) and emaValue > 90, "Bearish Reversal", "Median Proximity Percentile Bearish Reversal")
alertcondition(ta.crossunder(emaValue ,emaValue) and emaValue < -90, "Bullish Reversal", "Median Proximity Percentile Bullish Reversal")
🚨 Remember, the "Median Proximity Percentile " is a tool to aid your analysis. It’s essential to combine it with other analysis techniques and market understanding for best results. Happy trading! 📈📉
ATR TrendTL;DR - An average true range (ATR) based trend
ATR trend uses a (customizable) ATR calculation and highest high & lowest low prices to calculate the actual trend. Basically it determines the trend direction by using highest high & lowest low and calculates (depending on the determined direction) the ATR trend by using a ATR based calculation and comparison method.
The indicator will draw one trendline by default. It is also possible to draw a second trendline which shows a 'negative trend'. This trendline is calculated the same way the primary trendline is calculated but uses a negative (-1 by default) value for the ATR calculation. This trendline can be used to detect early trend changes and/or micro trends.
How to use:
Due to its ATR nature the ATR trend will show trend changes by changing the trendline direction. This means that when the price crosses the trendline it does not automatically mean a trend change. However using the 'negative trend' option ATR trend can show early trend changes and therefore good entry points.
Some notes:
- A (confirmed) trend change is shown by a changing color and/or moving trendline (up/down)
- Unlike other indicators the 'time period' value is not the primary adjustment setting. This value is only used to calculate highest high & lowest low values and has medium impact on trend calculation. The primary adjustment setting is 'ATR weight'
- Every settings has a tooltip with further explanation
- I added additional color coding which uses a different color when the trend attempts to change but the trend change isn't confirmed (yet)
- Default values work fine (at least in my back testing) but the recommendation is to adjust the settings (especially ATR weight) to your trading style
- You can further finetune this indicator by using custom moving average types for the ATR calculation (like linear regression or Hull moving average)
- Both trendlines can be used to determine future support and resistance zones
- ATR trend can be used as a stop loss finder
- Alerts are using buy/sell signals
- You can use fancy color filling ;)
Happy trading!
Daniel
Momentum Bias Index [AlgoAlpha]Description:
The Momentum Bias Index by AlgoAlpha is designed to provide traders with a powerful tool for assessing market momentum bias. The indicator calculates the positive and negative bias of momentum to gauge which one is greater to determine the trend.
Key Features:
Comprehensive Momentum Analysis: The script aims to detect momentum-trend bias, typically when in an uptrend, the momentum oscillator will oscillate around the zero line but will have stronger positive values than negative values, similarly for a downtrend the momentum will have stronger negative values. This script aims to quantify this phenomenon.
Overlay Mode: Traders can choose to overlay the indicator on the price chart for a clear visual representation of market momentum.
Take-profit Signals: The indicator includes signals to lock in profits, they appear as labels in overlay mode and as crosses when overlay mode is off.
Impulse Boundary: The script includes an impulse boundary, the impulse boundary is a threshold to visualize significant spikes in momentum.
Standard Deviation Multiplier: Users can adjust the standard deviation multiplier to increase the noise tolerance of the impulse boundary.
Bias Length Control: Traders can customize the length for evaluating bias, enabling them to fine-tune the indicator according to their trading preferences. A higher length will give a longer-term bias in trend.
BTC Supply in Profits and Losses (BTCSPL) [AlgoAlpha]Description:
🚨The BTC Supply in Profits and Losses (BTCSPL) indicator, developed by AlgoAlpha, offers traders insights into the distribution of INDEX:BTCUSD addresses between profits and losses based on INDEX:BTCUSD on-chain data.
Features:
🔶Alpha Decay Adjustment: The indicator provides the option to adjust the data against Alpha Decay, this compensates for the reduction in clarity of the signal over time.
🔶Rolling Change Display: The indicator enables the display of the rolling change in the distribution of Bitcoin addresses between profits and losses, aiding in identifying shifts in market sentiment.
🔶BTCSPL Value Score: The indicator optionally displays a value score ranging from -1 to 1, traders can use this to carry out strategic dollar cost averaging and reverse dollar cost averaging based on the implied value of bitcoin.
🔶Reversal Signals: The indicator gives long-term reversal signals denoted as "▲" and "▼" for the price of bitcoin based on oversold and overbought conditions of the BTCSPL.
🔶Moving Average Visualization: Traders can choose to display a moving average line, allowing for better trend identification.
How to Use ☝️ (summary):
Alpha Decay Adjustment: Toggle this option to enable or disable Alpha Decay adjustment for a normalized representation of the data.
Moving Average: Toggle this option to show or hide the moving average line, helping traders identify trends.
Short-Term Trend: Enable this option to display the short-term trend based on the Aroon indicator.
Rolling Change: Choose this option to visualize the rolling change in the distribution between profits and losses.
BTCSPL Value Score: Activate this option to show the BTCSPL value score, ranging from -1 to 1, 1 implies that bitcoin is extremely cheap(buy) and -1 implies bitcoin is extremely expensive(sell).
Reversal Signals: Gives binary buy and sell signals for the long term
Volume Exhaustion [AlgoAlpha]Introducing the Volume Exhaustion by AlgoAlpha, is an innovative tool that aims to identify potential exhaustion or peaks in trading volume , which can be a key indicator for reversals or continuations in market trends 🔶.
Key Features:
Signal Plotting : A special feature is the plotting of 'Release' signals, marked by orange diamonds, indicating points where the exhaustion index crosses under its previous value and is above a certain boundary. This could signify critical market points 🚨.
Calculation Length Customization : Users can adjust the calculation and Signal lengths to suit their trading style, allowing for flexibility in analysis over different time periods. ☝️
len = input(50, "Calculation Length")
len2 = input(8, "Signal Length")
Visual Appeal : The script offers customizable colors (col for the indicator and col1 for the background) enhancing the visual clarity and user experience 💡.
col = input.color(color.white, "Indicator Color")
col1 = input.color(color.gray, "Background Color")
Advanced Volume Processing : At its core, the script utilizes a combination of Hull Moving Average (HMA) and Exponential Moving Average (EMA) applied to the volume data. This sophisticated approach helps in smoothing out the volume data and reducing lag.
sv = ta.hma(volume, len)
ssv = ta.hma(sv, len)
Volume Exhaustion Detection : The script calculates the difference between the volume and its smoothed version, normalizing this value to create an exhaustion index (fff). Positive values of this index suggest potential volume exhaustion.
f = sv-ssv
ff = (f) / (ta.ema(ta.highest(f, len) - ta.lowest(f, len), len)) * 100
fff = ff > 0 ? ff : 0
Boundary and Zero Line : The script includes a boundary line (boundary) and a zero line (zero), with the area between them filled for enhanced visual interpretation. This helps in assessing the relative position of the exhaustion index.
Customizable Background : The script colors the background of the chart for better readability and to distinguish the indicator’s area clearly.
Overall, Volume Exhaustion is designed for traders who focus on volume analysis. It provides a unique perspective on volume trends and potential exhaustion points, which can be crucial for making informed trading decisions. This script is a valuable addition for traders looking to enhance their trading experience with advanced volume analysis tools.
Adaptive Trend Finder (log)In the dynamic landscape of financial markets, the Adaptive Trend Finder (log) stands out as an example of precision and professionalism. This advanced tool, equipped with a unique feature, offers traders a sophisticated approach to market trend analysis: the choice between automatic detection of the long-term or short-term trend channel.
Key Features:
1. Choice Between Long-Term or Short-Term Trend Channel Detection: Positioned first, this distinctive feature of the Adaptive Trend Finder (log) allows traders to customize their analysis by choosing between the automatic detection of the long-term or short-term trend channel. This increased flexibility adapts to individual trading preferences and changing market conditions.
2. Autonomous Trend Channel Detection: Leveraging the robust statistical measure of the Pearson coefficient, the Adaptive Trend Finder (log) excels in autonomously locating the optimal trend channel. This data-driven approach ensures objective trend analysis, reducing subjective biases, and enhancing overall precision.
3. Precision of Logarithmic Scale: A distinctive characteristic of our indicator is its strategic use of the logarithmic scale for regression channels. This approach enables nuanced analysis of linear regression channels, capturing the subtleties of trends while accommodating variations in the amplitude of price movements.
4. Length and Strength Visualization: Traders gain a comprehensive view of the selected trend channel, with the revelation of its length and quantification of trend strength. These dual pieces of information empower traders to make informed decisions, providing insights into both the direction and intensity of the prevailing trend.
In the demanding universe of financial markets, the Adaptive Trend Finder (log) asserts itself as an essential tool for traders, offering an unparalleled combination of precision, professionalism, and customization. Highlighting the choice between automatic detection of the long-term or short-term trend channel in the first position, this indicator uniquely caters to the specific needs of each trader, ensuring informed decision-making in an ever-evolving financial environment.
Triple Confirmation Kernel Regression Overlay [QuantraSystems]Kernel Regression Oscillator - Overlay
Introduction
The Kernel Regression Oscillator (ᏦᏒᎧ) represents an advanced tool for traders looking to capitalize on market trends.
This Indicator is valuable in identifying and confirming trend directions, as well as probabilistic and dynamic oversold and overbought zones.
It achieves this through a unique composite approach using three distinct Kernel Regressions combined in an Oscillator.
The additional Chart Overlay Indicator adds confidence to the signal.
Which is this Indicator.
This methodology helps the trader to significantly reduce false signals and offers a more reliable indication of market movements than more widely used indicators can.
Legend
The upper section is the Overlay. It features the Signal Wave to display the current trend.
Its Overbought and Oversold zones start at 50% and end at 100% of the selected Standard Deviation (default σ = 3), which can indicate extremely rare situations which can lead to either a softening momentum in the trend or even a mean reversion situation.
The lower one is the Base Chart.
The Indicator is linked here
It features the Kernel Regression Oscillator to display a composite of three distinct regressions, also displaying current trend.
Its Overbought and Oversold zones start at 50% and end at 100% of the selected Standard Deviation (default σ = 2), which can indicate extremely rare situations.
Case Study
To effectively utilize the ᏦᏒᎧ, traders should use both the additional Overlay and the Base
Chart at the same time. Then focus on capturing the confluence in signals, for example:
If the 𝓢𝓲𝓰𝓷𝓪𝓵 𝓦𝓪𝓿𝓮 on the Overlay and the ᏦᏒᎧ on the Base Chart both reside near the extreme of an Oversold zone the probability is higher than normal that momentum in trend may soften or the token may even experience a reversion soon.
If a bar is characterized by an Oversold Shading in both the Overlay and the Base Chart, then the probability is very high to experience a reversion soon.
In this case the trader may want to look for appropriate entries into a long position, as displayed here.
If a bar is characterized by an Overbought Shading in either Overlay or Base Chart, then the probability is high for momentum weakening or a mean reversion.
In this case the trade may have taken profit and closed his long position, as displayed here.
Please note that we always advise to find more confluence by additional indicators.
Recommended Settings
Swing Trading (1D chart)
Overlay
Bandwith: 45
Width: 2
SD Lookback: 150
SD Multiplier: 2
Base Chart
Bandwith: 45
SD Lookback: 150
SD Multiplier: 2
Fast-paced, Scalping (4min chart)
Overlay
Bandwith: 75
Width: 2
SD Lookback: 150
SD Multiplier: 3
Base Chart
Bandwith: 45
SD Lookback: 150
SD Multiplier: 2
Notes
The Kernel Regression Oscillator on the Base Chart is also sensitive to divergences if that is something you are keen on using.
For maximum confluence, it is recommended to use the indicator both as a chart overlay and in its Base Chart.
Please pay attention to shaded areas with Standard Deviation settings of 2 or 3 at their outer borders, and consider action only with high confidence when both parts of the indicator align on the same signal.
This tool shows its best performance on timeframes lower than 4 hours.
Traders are encouraged to test and determine the most suitable settings for their specific trading strategies and timeframes.
The trend following functionality is indicated through the "𝓢𝓲𝓰𝓷𝓪𝓵 𝓦𝓪𝓿𝓮" Line, with optional "Up" and "Down" arrows to denote trend directions only (toggle “Show Trend Signals”).
Methodology
The Kernel Regression Oscillator takes three distinct kernel regression functions,
used at similar weight, in order to calculate a balanced and smooth composite of the regressions. Part of it are:
The Epanechnikov Kernel Regression: Known for its efficiency in smoothing data by assigning less weight to data points further away from the target point than closer data points, effectively reducing variance.
The Wave Kernel Regression: Similarly assigning weight to the data points based on distance, it captures repetitive and thus wave-like patterns within the data to smoothen out and reduce the effect of underlying cyclical trends.
The Logistic Kernel Regression: This uses the logistic function in order to assign weights by probability distribution on the distance between data points and target points. It thus avoids both bias and variance to a certain level.
kernel(source, bandwidth, kernel_type) =>
switch kernel_type
"Epanechnikov" => math.abs(source) <= 1 ? 0.75 * (1 - math.pow(source, 2)) : 0.0
"Logistic" => 1/math.exp(source + 2 + math.exp(-source))
"Wave" => math.abs(source) <= 1 ? (1 - math.abs(source)) * math.cos(math.pi * source) : 0.
kernelRegression(src, bandwidth, kernel_type) =>
sumWeightedY = 0.
sumKernels = 0.
for i = 0 to bandwidth - 1
base = i*i/math.pow(bandwidth, 2)
kernel = kernel(base, 1, kernel_type)
sumWeightedY += kernel * src
sumKernels += kernel
(src - sumWeightedY/sumKernels)/src
// Triple Confirmations
Ep = kernelRegression(source, bandwidth, 'Epanechnikov' )
Lo = kernelRegression(source, bandwidth, 'Logistic' )
Wa = kernelRegression(source, bandwidth, 'Wave' )
By combining these regressions in an unbiased average, we follow our principle of achieving confluence for a signal or a decision, by stacking several edges to increase the probability that we are correct.
// Average
AV = math.avg(Ep, Lo, Wa)
The Standard Deviation bands take defined parameters from the user, in this case sigma of ideally between 2 to 3,
to help the indicator detect extremely improbable conditions and thus take an inversely probable signal from it to forward to the user.
The parameter settings and also the visualizations allow for ample customizations by the trader. The indicator comes with default and recommended settings.
For questions or recommendations, please feel free to seek contact in the comments.
Liquidity Weighted Moving Averages [AlgoAlpha]Description:
The Liquidity Weighted Moving Averages by AlgoAlpha is a unique approach to identifying underlying trends in the market by looking at candle bars with the highest level of liquidity. This script offers a modified version of the classical MA crossover indicator that aims to be less noisy by using liquidity to determine the true fair value of price and where it should place more emphasis on when calculating the average.
Rationale:
It is common knowledge that liquidity makes it harder for market participants to move the price of assets, using this logic, we can determine the coincident liquidity of each bar by looking at the volume divided by the distance between the opening and closing price of that bar. If there is a higher volume but the opening and closing prices are near each other, this means that there was a high level of liquidity in that bar. We then use standard deviations to filter out high spikes of liquidity and record the closing prices on those bars. An average is then applied to these recorded prices only instead of taking the average of every single bar to avoid including outliers in the data processing.
Key features:
Customizable:
Fast Length - the period of the fast-moving average
Slow Length - the period of the slow-moving average
Outlier Threshold Length - the period of the outlier processing algorithm to detect spikes in liquidity
Significant Noise reduction from outliers:
Amazing Oscillator (AO) [Algoalpha]Description:
Introducing the Amazing Oscillator indicator by Algoalpha, a versatile tool designed to help traders identify potential trend shifts and market turning points. This indicator combines the power of the Awesome Oscillator (AO) and the Relative Strength Index (RSI) to create a new indicator that provides valuable insights into market momentum and potential trade opportunities.
Key Features:
Customizable Parameters: The indicator allows you to customize the period of the RSI calculations to fine-tune the indicator's responsiveness.
Visual Clarity: The indicator uses user-defined colors to visually represent upward and downward movements. You can select your preferred colors for both bullish and bearish signals, making it easy to spot potential trade setups.
AO and RSI Integration: The script combines the AO and RSI indicators to provide a comprehensive view of market conditions. The RSI is applied to the AO, which results in a standardized as well as a less noisy version of the Awesome Oscillator. This makes the indicator capable of pointing out overbought or oversold conditions as well as giving fewer false signals
Signal Plots: The indicator plots key levels on the chart, including the RSI threshold(Shifted down by 50) at 30 and -30. These levels are often used by traders to identify potential trend reversal points.
Signal Alerts: For added convenience, the indicator includes "x" markers to signal potential buy (green "x") and sell (red "x") opportunities based on RSI crossovers with the -30 and 30 levels. These alerts can help traders quickly identify potential entry and exit points.
Trend Flow Profile [AlgoAlpha]Description:
The "Trend Flow Profile" indicator is a powerful tool designed to analyze and interpret the underlying trends and reversals in a financial market. It combines the concepts of Order Flow and Rate of Change (ROC) to provide valuable insights into market dynamics, momentum, and potential trade opportunities. By integrating these two components, the indicator offers a comprehensive view of market sentiment and price movements, facilitating informed trading decisions.
Rationale:
The combination of Order Flow and ROC in the "Trend Flow Profile" indicator stems from the recognition that both factors play critical roles in understanding market behavior. Order Flow represents the net buying or selling pressure in the market, while ROC measures the rate at which prices change. By merging these elements, the indicator captures the interplay between market participants' actions and the momentum of price movements, enabling traders to identify trends, spot reversals, and gauge the strength of price acceleration or deceleration.
Calculation:
The Order Flow component is computed by summing the volume when prices move up and subtracting the volume when prices move down. This cumulative measure reflects the overall order imbalance in the market, providing insights into the dominant buying or selling pressure.
The ROC component calculates the percentage change in price over a given period. It compares the current price to a previous price and expresses the change as a percentage. This measurement indicates the velocity and direction of price movement, allowing traders to assess the market's momentum.
How to Use It?
The "Trend Flow Profile" indicator offers valuable information to traders for making informed trading decisions. It enables the identification of underlying trends and potential reversals, providing a comprehensive view of market sentiment and momentum. Here are some key ways to utilize the indicator:
Spotting Trends: The indicator helps identify the prevailing market trend, whether bullish or bearish. A consistent positive (green) histogram indicates a strong uptrend, while a consistent negative (red) histogram suggests a robust downtrend.
Reversal Signals: Reversal patterns can be identified when the histogram changes color, transitioning from positive to negative (or vice versa). These reversals can signify potential turning points in the market, highlighting opportunities for counter-trend trades.
Momentum Assessment: By observing the width and intensity of the histogram, traders can assess the acceleration or deceleration of price momentum. A wider histogram suggests strong momentum, while a narrower histogram indicates a potential slowdown.
Utility:
The "Trend Flow Profile" indicator serves as a valuable tool for traders, providing several benefits. Traders can easily identify the prevailing market trend, enabling them to align their trading strategies with the dominant direction of the market. The indicator also helps spot potential reversals, allowing traders to anticipate market turning points and capture counter-trend opportunities. Additionally, the green and red histogram colors provide visual cues to determine the optimal duration of a long or short position. Following the green histogram signals when in a long position and the red histogram signals when in a short position can assist traders in managing their trades effectively. Moreover, the width and intensity of the histogram offer insights into the acceleration or deceleration of momentum. Traders can gauge the strength of price movements and adjust their trading strategies accordingly. By leveraging the "Trend Flow Profile" indicator, traders gain a comprehensive understanding of market dynamics, which enhances their decision-making and improves their overall trading outcomes.
