Adaptive Trend Classification: Moving Averages [InvestorUnknown]Adaptive Trend Classification: Moving Averages
Overview
The Adaptive Trend Classification (ATC) Moving Averages indicator is a robust and adaptable investing tool designed to provide dynamic signals based on various types of moving averages and their lengths. This indicator incorporates multiple layers of adaptability to enhance its effectiveness in various market conditions.
Key Features
Adaptability of Moving Average Types and Lengths: The indicator utilizes different types of moving averages (EMA, HMA, WMA, DEMA, LSMA, KAMA) with customizable lengths to adjust to market conditions.
Dynamic Weighting Based on Performance: ] Weights are assigned to each moving average based on the equity they generate, with considerations for a cutout period and decay rate to manage (reduce) the influence of past performances.
Exponential Growth Adjustment: The influence of recent performance is enhanced through an adjustable exponential growth factor, ensuring that more recent data has a greater impact on the signal.
Calibration Mode: Allows users to fine-tune the indicator settings for specific signal periods and backtesting, ensuring optimized performance.
Visualization Options: Multiple customization options for plotting moving averages, color bars, and signal arrows, enhancing the clarity of the visual output.
Alerts: Configurable alert settings to notify users based on specific moving average crossovers or the average signal.
User Inputs
Adaptability Settings
λ (Lambda): Specifies the growth rate for exponential growth calculations.
Decay (%): Determines the rate of depreciation applied to the equity over time.
CutOut Period: Sets the period after which equity calculations start, allowing for a focus on specific time ranges.
Robustness Lengths: Defines the range of robustness for equity calculation with options for Narrow, Medium, or Wide adjustments.
Long/Short Threshold: Sets thresholds for long and short signals.
Calculation Source: The data source used for calculations (e.g., close price).
Moving Averages Settings
Lengths and Weights: Allows customization of lengths and initial weights for each moving average type (EMA, HMA, WMA, DEMA, LSMA, KAMA).
Calibration Mode
Calibration Mode: Enables calibration for fine-tuning inputs.
Calibrate: Specifies which moving average type to calibrate.
Strategy View: Shifts entries and exits by one bar for non-repainting backtesting.
Calculation Logic
Rate of Change (R): Calculates the rate of change in the price.
Set of Moving Averages: Generates multiple moving averages with different lengths for each type.
diflen(length) =>
int L1 = na, int L_1 = na
int L2 = na, int L_2 = na
int L3 = na, int L_3 = na
int L4 = na, int L_4 = na
if robustness == "Narrow"
L1 := length + 1, L_1 := length - 1
L2 := length + 2, L_2 := length - 2
L3 := length + 3, L_3 := length - 3
L4 := length + 4, L_4 := length - 4
else if robustness == "Medium"
L1 := length + 1, L_1 := length - 1
L2 := length + 2, L_2 := length - 2
L3 := length + 4, L_3 := length - 4
L4 := length + 6, L_4 := length - 6
else
L1 := length + 1, L_1 := length - 1
L2 := length + 3, L_2 := length - 3
L3 := length + 5, L_3 := length - 5
L4 := length + 7, L_4 := length - 7
// Function to calculate different types of moving averages
ma_calculation(source, length, ma_type) =>
if ma_type == "EMA"
ta.ema(source, length)
else if ma_type == "HMA"
ta.sma(source, length)
else if ma_type == "WMA"
ta.wma(source, length)
else if ma_type == "DEMA"
ta.dema(source, length)
else if ma_type == "LSMA"
lsma(source,length)
else if ma_type == "KAMA"
kama(source, length)
else
na
// Function to create a set of moving averages with different lengths
SetOfMovingAverages(length, source, ma_type) =>
= diflen(length)
MA = ma_calculation(source, length, ma_type)
MA1 = ma_calculation(source, L1, ma_type)
MA2 = ma_calculation(source, L2, ma_type)
MA3 = ma_calculation(source, L3, ma_type)
MA4 = ma_calculation(source, L4, ma_type)
MA_1 = ma_calculation(source, L_1, ma_type)
MA_2 = ma_calculation(source, L_2, ma_type)
MA_3 = ma_calculation(source, L_3, ma_type)
MA_4 = ma_calculation(source, L_4, ma_type)
Exponential Growth Factor: Computes an exponential growth factor based on the current bar index and growth rate.
// The function `e(L)` calculates an exponential growth factor based on the current bar index and a given growth rate `L`.
e(L) =>
// Calculate the number of bars elapsed.
// If the `bar_index` is 0 (i.e., the very first bar), set `bars` to 1 to avoid division by zero.
bars = bar_index == 0 ? 1 : bar_index
// Define the cuttime time using the `cutout` parameter, which specifies how many bars will be cut out off the time series.
cuttime = time
// Initialize the exponential growth factor `x` to 1.0.
x = 1.0
// Check if `cuttime` is not `na` and the current time is greater than or equal to `cuttime`.
if not na(cuttime) and time >= cuttime
// Use the mathematical constant `e` raised to the power of `L * (bar_index - cutout)`.
// This represents exponential growth over the number of bars since the `cutout`.
x := math.pow(math.e, L * (bar_index - cutout))
x
Equity Calculation: Calculates the equity based on starting equity, signals, and the rate of change, incorporating a natural decay rate.
pine code
// This function calculates the equity based on the starting equity, signals, and rate of change (R).
eq(starting_equity, sig, R) =>
cuttime = time
if not na(cuttime) and time >= cuttime
// Calculate the rate of return `r` by multiplying the rate of change `R` with the exponential growth factor `e(La)`.
r = R * e(La)
// Calculate the depreciation factor `d` as 1 minus the depreciation rate `De`.
d = 1 - De
var float a = 0.0
// If the previous signal `sig ` is positive, set `a` to `r`.
if (sig > 0)
a := r
// If the previous signal `sig ` is negative, set `a` to `-r`.
else if (sig < 0)
a := -r
// Declare the variable `e` to store equity and initialize it to `na`.
var float e = na
// If `e ` (the previous equity value) is not available (first calculation):
if na(e )
e := starting_equity
else
// Update `e` based on the previous equity value, depreciation factor `d`, and adjustment factor `a`.
e := (e * d) * (1 + a)
// Ensure `e` does not drop below 0.25.
if (e < 0.25)
e := 0.25
e
else
na
Signal Generation: Generates signals based on crossovers and computes a weighted signal from multiple moving averages.
Main Calculations
The indicator calculates different moving averages (EMA, HMA, WMA, DEMA, LSMA, KAMA) and their respective signals, applies exponential growth and decay factors to compute equities, and then derives a final signal by averaging weighted signals from all moving averages.
Visualization and Alerts
The final signal, along with additional visual aids like color bars and arrows, is plotted on the chart. Users can also set up alerts based on specific conditions to receive notifications for potential trading opportunities.
Repainting
The indicator does support intra-bar changes of signal but will not repaint once the bar is closed, if you want to get alerts only for signals after bar close, turn on “Strategy View” while setting up the alert.
Conclusion
The Adaptive Trend Classification: Moving Averages Indicator is a sophisticated tool for investors, offering extensive customization and adaptability to changing market conditions. By integrating multiple moving averages and leveraging dynamic weighting based on performance, it aims to provide reliable and timely investing signals.
Moving Averages
Swing High/Low & EMA Cross AlertScript Description:
This script on TradingView combines the detection of Swing High/Low points with exponential moving average (EMA) crossovers to provide buy and sell alerts and to mark swing points on the chart.
What the Script Does:
Swing High/Low Detection:
Uses the ta.pivothigh function to detect significant high points and the ta.pivotlow function to detect significant low points.
For each detected point, the script checks if it is a new higher high (HH) or lower high (LH) for the highs, and a new lower low (LL) or higher low (HL) for the lows.
Creates visual labels to identify these points on the chart, helping traders to visualize potential reversal points.
EMA Crossover:
Calculates two EMAs: a fast EMA (fastEMA) with a default period of 50 and a slow EMA (slowEMA) with a default period of 200.
Detects bullish crossovers (when fastEMA crosses above slowEMA) and bearish crossunders (when fastEMA crosses below slowEMA).
Generates buy and sell alerts based on these crossovers.
How the Script Works:
EMA Calculation: EMAs are calculated using the closing prices and user-defined periods.
Swing High/Low Detection: Uses the high and low values from the previous length bars to determine the swing points.
Alert Generation: Alerts are triggered when crossovers between the EMAs occur.
How to Use the Script:
Add to Chart: Insert the script into TradingView and apply it to the desired chart.
Configure Parameters:
Adjust the detection period for swing points (length).
Configure the periods for the EMAs (fastLen and slowLen).
Customize the colors for the swing point labels as per your preference.
Monitor Alerts: Use the EMA crossover alerts to make buy or sell decisions. Observe the swing point labels to identify potential trend reversals.
Justification for the Combination:
EMAs: Widely used to identify trend direction. Combining a fast EMA with a slow EMA helps capture both short-term and long-term trend changes.
Swing High/Low: Identifies reversal points in price, which are crucial for determining potential entry and exit points in trades.
Combination:
Combining EMAs and Swing High/Low provides a comprehensive view of price behavior, helping traders to effectively identify trends and reversal points.
This script is useful for traders who want to combine trend analysis (via EMAs) with the identification of reversal points (Swing High/Low), providing a more complete view of price behavior on the chart.
HTF Dynamic EMA Smoothing Indicator [CHE] with Kernel SelectionThe Dynamic EMA Smoothing Indicator with Kernel Selection is a powerful Pine Script indicator for TradingView designed to smooth moving averages and identify market trends more clearly. Here is a detailed description of its functionalities and settings:
Main Functions:
1. Time Period Display:
- Option to show or hide an info box displaying the current time period.
- Customizable info box: Users can adjust the size, position, and colors of the info box to suit their preferences.
2. Timeframe Type Selection:
- Auto Timeframe: Automatically calculates the best timeframe based on the current resolution.
- Multiplier: Allows using an alternate timeframe as a multiple of the current resolution.
- Manual Resolution: Users can manually set a specific timeframe.
3. Colors:
- Custom colors for various graphical elements, including EMA lines and signals.
4. Basic Settings:
- EMA and Signal Periods: Defines the periods for the exponential moving averages (EMA) and signal lines.
- Smoothing Length and Kernel Type: Allows selecting the smoothing length and the type of kernel used for weighting the EMAs.
- ATR Multiplier: Defines the multiplier for the ATR (Average True Range) to identify relevant price ranges.
5. EMA Calculations:
- The indicator calculates a weighted EMA using several methods like Linear, Exponential, Epanechnikov, Triangular, and Cosine kernels.
- Smoothing is achieved by adding and removing values in a float array that stores the EMA values.
6. Plotting EMA and Signal Lines:
- The indicator plots the smoothed EMA and signal lines on the chart. The line colors change according to the trend direction (green for uptrend, red for downtrend).
7. Trading Signals:
- Long Signals: An upward arrow is displayed when the smoothed EMA indicates an uptrend.
- Short Signals: A downward arrow is displayed when the smoothed EMA indicates a downtrend.
- Alert Conditions: Alerts are triggered when long or short signals are detected.
8. ATR Bands:
- The indicator shows upper and lower ATR bands to identify potential support and resistance zones.
9. Time Period Display on Chart:
- A table is used to display the selected time period on the chart when the corresponding option is enabled.
This indicator offers extensive customization and allows traders to conduct complex market analyses using smoothed EMAs and custom timeframes. The integration of various kernels for smoothing makes it a versatile tool adaptable to different trading strategies.
Nasan Moving Average with ForecastThe "Nasan Moving Average with Forecast" indicator is a technical analysis forecasting tool that combines the principles of historical data analysis and random walk theory. It calculates a customized moving average (Nasan Moving Average) by integrating price data and statistical measures and projects future price points by generating forecast values within calculated volatility bounds, creating a dynamic and insightful visualization of potential market movements. This indicator to blend past market behavior with probabilistic future trends to enhance forecasting.
Input Parameters:
len: Differencing length (default 21, Use a minimum of 5 and for lower time frames less than 15 min use values between 300 -3000)
len1: Correction Factor Length 1 (default 21, this determines the length of the MA you want , eg. 10 MA, 50 MA, 100 MA, )
len2: Correction Factor Length 2 (default 9, this works best if it is ~ </=1/2 of len1 )
len3: Smoothing Length (default 5, I would not change this and only use if I want to introduce lag where you want to use it for cross over strategies).
forecast_points: Number of points to forecast (default 30).
m: Multiplier for standard deviation (default 2.5).
bl: Block length for calculating max/min values (default 100).
use_calculated_max_min: Boolean to decide whether to use calculated max/min values.
Nasan Moving Average Calculation:
Calculates the simple moving average (mean) and standard deviation (sd) of the typical price (hlc3).
Computes intermediate variables (a, b, c, etc.) based on log transformation and cumulative sum.
Applies weighted moving averages (wma) to these intermediate variables to smooth them and derive the final value c6.
Plots c6 as the Nasan Moving Average if the bar is confirmed. To learn more see Nasan Moving Average.
Forecast Points Calculation:
Calculates maximum (max_val) and minimum (min_val) values for the forecast, either using a fixed value or based on standard deviation and a multiplier.
Initializes an array to store forecast values and creates polyline objects for plotting.
If the current bar is one of the last three bars and confirmed:
Clears and reinitializes the polyline.
Initializes the first forecast value from the cumulative sum c.
Generates subsequent forecast values using a random value within the range .
Updates the forecast array and plots the forecast points as an orange curved polyline.
Plotting Max/Min Values:
Plots max_val and min_val as green and red lines, respectively, to indicate the bounds of the forecast range.
Components of the Forecasting Model
Historical Dependence:
Nasan Moving Average Calculation: The script calculates a custom moving average (c6) that incorporates historical price data (hlc3), standard deviations (sd), and weighted moving averages (wma). This part of the code processes historical data to create a smoothed representation of the price trend.
Max/Min Value Calculation: The maximum (max_val) and minimum (min_val) values for the forecast can be calculated based on the historical standard deviation of a transformed variable b over a block length (bl). This introduces historical volatility into the bounds for the forecast.
Random Walk Model:
Random Value Generation: Within the forecast points calculation, a random value (random_val) is generated for each forecast point within the range . This random value introduces stochasticity into the model, characteristic of a random walk process.
Cumulative Sum for Forecasting: The script uses a cumulative sum (prev_f + random_val) to generate the next forecast point (next_f). This is a typical approach in random walk models where each new point is based on the previous point plus some random noise.
Explanation of the Forecast Model
Random Walk Characteristics: Each new forecast point is generated by adding a random value to the previous point, making the model a random walk with drift, where the drift is influenced by historical correction factors (c1, c4).
Historical and Statistical Dependence: The bounds of the random values and the initial conditions are derived from historical data, ensuring that the forecast respects historical volatility and trends.
The forecasting model in the script is a hybrid approach: It uses a random walk to generate future points, characterized by adding random values to the previous forecasted value.
The historical and statistical dependence is incorporated through initial conditions, scaling factors, and bounds derived from historical price data and its statistical properties.
This combination ensures that the forecasts are not purely stochastic but are grounded in historical price behavior, making the model more robust and potentially more accurate in reflecting market conditions.
Nasan Moving AverageNasan Moving Average belong to the group of moving average which provides a high degree of smoothness with very low lag.
The calculation process involves several steps to analyze the typical price of a financial asset over specific periods. It starts by computing a simple moving average and standard deviation of the typical price. Then, it standardizes (differencing TP - Average Typical price over previous n periods) the price and applies an inverse hyperbolic sine transformation to the standardized value. The transformed values are summed cumulatively, and various weighted moving averages are calculated to adjust and smooth the data. The final output is a smoothed signal with reduced lag.
Input Parameters:
len: Differencing length (default 21, Use a minimum of 5 and for lower time frames less than 15 min use values between 300 -3000)
len1: Correction Factor Length 1 (default 21, this determines the length of the MA you want , eg. 10 MA, 50 MA, 100 MA, )
len2: Correction Factor Length 2 (default 9, this works best if it is ~ </=1/2 of len1 )
len3: Smoothing Length (default 5, I would not change this and only use if I want to introduce lag where you want to use it for cross over strategies).
Differencing and Standardization:
The code calculates the standardized price a by differencing the typical price and normalizing it using the mean and standard deviation. This step standardizes the price changes.
Transformation:
The transformation using logarithms and square roots (b) aim to stabilize the variance and make the distribution more normal-like, improving the robustness of the cumulative sum c.
Cumulative Sum:
The cumulative sum c of the transformed series helps in integrating the series over time, capturing the overall trend and movement.
Correction Factors:
Correction factors c1 and c4 adjust the cumulative sum based on weighted averages, to correct any biases or to align it with the typical price.
Smoothing:
The final result c6 is smoothed using a weighted moving average, reducing noise and making it easier to interpret trends.
Moving average to price cloudHi all!
This indicator shows when the price crosses the defined moving average. It plots a green or red cloud (depending on trend) and the moving average. It also plots an arrow when the trend changes (this can be disabled in 'style'->'labels' in the settings).
The moving average itself can be used as dynamic support/resistance. The trend will change based on your settings (described below). By default the trend will change when the whole bar is above/below the moving average for 2 bars (that's closed). This can be changed by "Source" and "Bars".
Settings
• Length (choose the length of the moving average. Defaults to 21)
• Type (choose what type of moving average).
- "SMA" (Simple Moving Average)
- "EMA" (Exponential Moving Average)
- "HMA" (Hull Moving Average)
- "WMA" (Weighted Moving Average)
- "VWMA" (Volume Weighted Moving Average)
- "DEMA" (Double Exponential Moving Average)
Defaults to"EMA".
• Source (Define the price source that must be above/below the moving average for the trend to change. Defaults to 'High/low (passive)')
- 'Open' The open of the bar has to cross the moving average
- 'Close' The close of the bar has to cross the moving average
- 'High/low (passive)' In a down trend: the low of the bar has to cross the moving average
- 'High/low (aggressive)' In a down trend: the high of the bar has to cross the moving average
• Source bar must be close. Defaults to 'true'.
• Bars (Define the number bars whose value (defined in 'Source') must be above/below the moving average. All the bars (defined by this number) must be above/below the moving average for the trend to change. Defaults to 2.)
Let me know if you have any questions.
Best of trading luck!
Uptrick: Complex WMA Indicator with Trend Transitions
The "Complex WMA Indicator with Trend Transitions" is a technical analysis tool designed to help traders identify and visualize market trends using three Weighted Moving Averages (WMAs) of varying lengths. The primary purpose of this indicator is to provide a clearer and more nuanced view of market trends by highlighting bullish and bearish phases and filtering out noise, thereby enabling more informed trading decisions.
Detailed Explanation
This indicator allows users to set the lengths of three WMAs through input parameters. The default lengths are set to 10, 20, and 50, but users can customize these values according to their trading strategy. The WMAs are calculated using the closing prices of the specified periods, and the results are plotted on the chart in red, green, and blue, corresponding to the first, second, and third WMAs, respectively.
The indicator defines two primary conditions for trend analysis: bullish and bearish trends. A bullish trend is identified when both the shorter WMAs (first and second) are above the longest WMA (third), indicating upward momentum. Conversely, a bearish trend is identified when both the shorter WMAs are below the longest WMA, signaling downward momentum.
Crossover Signals and Trend Transitions
The script also identifies crossover signals between the first and second WMAs. A bullish crossover occurs when the first WMA crosses above the second WMA, generating a buy signal. This event is marked on the chart with a green upward label. A bearish crossover, marked with a red downward label, occurs when the first WMA crosses below the second WMA, indicating a sell signal.
To track the trend transitions effectively, the indicator employs a state machine. It maintains two variables, currentTrend and prevTrend, to store the current and previous trend states. The trend state is updated based on the defined trend conditions. When the trend changes from one state to another (e.g., from a bullish trend to a bearish trend), the indicator creates a label at the beginning of the new trend to mark this transition. This helps traders quickly recognize significant changes in market direction.
Visual Enhancements
The indicator enhances visual clarity by coloring the background of the chart based on the identified trend. When a bullish trend is detected, the background turns green, and when a bearish trend is identified, it turns red. The script ensures that only clear bullish and bearish trends are highlighted by excluding the "No Clear Trend" state, which reduces noise and prevents false signals.
Alerts
To further aid traders, the indicator includes alert conditions for both bullish and bearish crossovers. These alerts notify traders when a crossover occurs, enabling them to take timely action based on the identified signals.
Purpose and Unique Features
The primary purpose of the "Complex WMA Indicator with Trend Transitions" is to provide traders with a more precise and actionable analysis of market trends. Unlike simple moving average indicators, this tool uses multiple WMAs and incorporates a state machine to track and highlight trend transitions more effectively. By focusing on clear trend signals and filtering out noise, it helps traders make more informed decisions.
This indicator differs from other moving average-based tools in several ways:
Multi-WMA Analysis: It uses three WMAs of different lengths, providing a more comprehensive view of the market trend.
State Machine for Trends: The use of a state machine to track trend transitions ensures that only significant trends are highlighted, reducing noise.
Visual Clarity: The combination of colored backgrounds and labeled transitions makes it easier for traders to identify and act on trends.
Customization: Users can adjust the lengths of the WMAs to suit their trading strategies, making the indicator versatile.
In summary, the "Complex WMA Indicator with Trend Transitions" offers a sophisticated and customizable approach to trend analysis, providing clear visual cues and alerts for significant market movements, which sets it apart from simpler moving average indicators.
Support and Resistance Breakouts By RICHIESupport and resistance are fundamental concepts in technical analysis used to identify price levels on charts that act as barriers, preventing the price of an asset from getting pushed in a certain direction. Here’s a detailed description of each and how breakout strategies are typically used:
Support
Support is a price level where a downtrend can be expected to pause due to a concentration of demand. As the price of an asset drops, it hits a level where buyers tend to step in, causing the price to rebound.
Support Level Identification: Support levels are identified by looking at historical data where prices have repeatedly fallen to a certain level but have then rebounded.
Strength of Support: The more times an asset price hits a support level without breaking below it, the stronger that support level is considered to be.
Resistance
Resistance is a price level where an uptrend can be expected to pause due to a concentration of selling interest. As the price of an asset increases, it hits a level where sellers tend to step in, causing the price to drop.
Resistance Level Identification: Resistance levels are identified by looking at historical data where prices have repeatedly risen to a certain level but have then fallen back.
Strength of Resistance: The more times an asset price hits a resistance level without breaking above it, the stronger that resistance level is considered to be.
Breakouts
A breakout occurs when the price moves above a resistance level or below a support level with increased volume. Breakouts can be significant because they suggest a change in supply and demand dynamics, often leading to strong price movements.
Breakout Above Resistance: Indicates a bullish market sentiment. Traders often interpret this as a sign to enter a long position (buy).
Breakout Below Support: Indicates a bearish market sentiment. Traders often interpret this as a sign to enter a short position (sell).
Breakout Trading Strategies
Confirmation: Wait for a candle to close beyond the support or resistance level to confirm the breakout.
Volume: Increased volume on a breakout adds credibility, suggesting that the price move is supported by strong buying or selling interest.
Retest: Sometimes, after a breakout, the price will return to the breakout level to test it as a new support or resistance. This retest offers another entry point.
Stop-Loss: Place stop-loss orders just below the resistance (for long positions) or above the support (for short positions) to limit potential losses in case of a false breakout.
Take-Profit: Identify target levels for taking profits. These can be set based on previous support/resistance levels or using tools like Fibonacci retracements.
Median Moving Average @shrilssThe "Median Moving Average" (MMA) It allows users to select from two moving average lengths—short and long—and plots the median moving average, which is the midpoint between these two averages. Colored green for upward trends and red for downward trends, enhancing visual analysis.
Additionally, users can choose from a range of moving average types including Simple (SMA), Exponential (EMA), Weighted (WMA), Double Exponential (DEMA), Triple Exponential (TEMA), Hull (HMA), and Volume Weighted (VWMA).
Color Hull Moving AverageDescription:
The Color Hull Moving Average (CHMA) is a technical indicator designed to smooth and remove lag from traditional moving averages, making it more responsive to price movements. This indicator automatically adjusts the color of the moving average to green when it is rising and red when it is falling, helping to identify trends in a more visual and sophisticated way.
Characteristics:
Period: User configurable (default: 20)
Data Source: Can be applied to any price series, such as closing, opening, high, low, etc.
Dynamic Colors: The HMA line changes color based on its direction, making it easy to see trends.
Green: Uptrend
Red: Downtrend
How to use:
Period Configuration: Adjust the period to improve improvements and reactivity according to the asset and timeframe analyzed.
Color Interpretation: Use color changes to identify inflection points in the market.
Combination with Other Indicators: The HMA can be combined with other technical indicators to validate entry and exit signals.
Warning: Although HMA is a powerful tool, we recommend using it in conjunction with other forms of analysis for best results.
Combined IndicatorSummary
This custom Pine Script combines three main indicators into one, each with its own functionalities and visual cues. It provides a comprehensive approach to trend analysis by integrating short-term, medium-term, and long-term indicators. Each part of the indicator can be toggled on or off independently to suit the trader’s needs.
Part 1: EMA 14 and EMA 200
Purpose: This part of the indicator is designed to identify short-term and long-term trends using Exponential Moving Averages (EMA). It helps traders spot potential entry and exit points based on the relationship between short-term and long-term moving averages.
Visuals:
• EMA 14: Plotted in blue (#2962ff)
• EMA 200: Plotted in red (#f23645)
Signals:
• Long Signal: Generated when EMA 14 crosses above EMA 200, indicating a potential upward trend.
• Short Signal: Generated when EMA 14 crosses below EMA 200, indicating a potential downward trend.
Usage: Toggle this part on or off using the checkbox input to focus on short-term vs. long-term trends.
Part 2: EMA 9 and SMA 20
Purpose: This part combines Exponential and Simple Moving Averages to provide a medium-term trend analysis. It helps smooth out price data and identify potential trend reversals and continuation patterns.
Visuals:
• EMA 9: Plotted in green
• SMA 20: Plotted in dark red
Usage: Toggle this part on or off using the checkbox input to focus on medium-term trends and price smoothing.
Part 3: Golden Cross and Death Cross
Purpose: This part identifies long-term bullish and bearish market conditions using the 50-day and 200-day Simple Moving Averages (SMA). It highlights major trend changes that can inform long-term investment decisions.
Visuals:
• 50-day SMA: Plotted in gold (#ffe600)
• 200-day SMA: Plotted in black
Signals:
• Golden Cross: Generated when the 50-day SMA crosses above the 200-day SMA, indicating a potential long-term upward trend.
• Death Cross: Generated when the 50-day SMA crosses below the 200-day SMA, indicating a potential long-term downward trend.
Usage: Toggle this part on or off using the checkbox input to focus on long-term trend changes.
How to Use
1. Enable/Disable Indicators: Use the checkboxes provided in the input settings to enable or disable each part of the indicator according to your analysis needs.
2. Interpret Signals: Look for crossover events to determine potential entry and exit points based on the relationship between the moving averages.
3. Visual Confirmation: Use the color-coded lines and shape markers on the chart to visually confirm signals and trends.
4. Customize Settings: Adjust the lengths of the EMAs and SMAs in the input settings to suit your trading strategy and the specific asset you are analyzing.
Practical Application
• Short-Term Trading: Use the EMA 14 and EMA 200 signals to identify quick trend changes.
• Medium-Term Trading: Use the EMA 9 and SMA 20 to capture medium-term trends and reversals.
• Long-Term Investing: Monitor the Golden Cross and Death Cross signals to make decisions based on long-term trend changes.
Example of Unique Features
• Integrated Toggle System: Allows users to enable or disable specific parts of the indicator to customize their analysis.
• Multi-Tier Trend Analysis: Combines short-term, medium-term, and long-term indicators to provide a comprehensive view of the market.
Guppy Wave [UkutaLabs]█ OVERVIEW
The Guppy Wave Indicator is a collection of Moving Averages that provide insight on current market strength. This is done by plotting a series of 12 Moving Averages and analysing where each one is positioned relative to the others.
In doing this, this script is able to identify short-term moves and give an idea of the current strength and direction of the market.
The aim of this script is to simplify the trading experience of users by automatically displaying a series of useful Moving Averages to provide insight into short-term market strength.
█ USAGE
The Guppy Wave is generated using a series of 12 total Moving Averages composed of 6 Small-Period Moving Averages and 6 Large Period Moving Averages. By measuring the position of each moving average relative to the others, this script provides unique insight into the current strength of the market.
Rather than simply plotting 12 Moving Averages, a color gradient is instead drawn between the Moving Averages to make it easier to visualise the distribution of the Guppy Wave. The color of this gradient changes depending on whether the Small-Period Averages are above or below the Large-Period Averages, allowing traders to see current short-term market strength at a glance.
When the gradient fans out, this indicates a rapid short-term move. When the gradient is thin, this indicates that there is no dominant power in the market.
█ SETTINGS
• Moving Average Type: Determines the type of Moving Average that get plotted (EMA, SMA, WMA, VWMA, HMA, RMA)
• Moving Average Source: Determines the source price used to calculate Moving Averages (open, high, low, close, hl2, hlc3, ohlc4, hlcc4)
• Bearish Color: Determines the color of the gradient when Small-Period MAs are above Large-Period MAs.
• Bullish Color: Determines the color of the gradient when Small-Period MAs are below Large-Period MAs.
Fibonacci Moving Averages [UkutaLabs]█ OVERVIEW
The Fibonacci Moving Averages are a toolkit which allows the user to configure different types of Moving Averages based on key Fibonacci numbers.
Moving Averages are used to visualise short-term and long-term support and resistance which can be used as a signal where price might continue or retrace. Moving Averages serve as a simple yet powerful tool that can help traders in their decision-making and help foster a sense of where the price might be moving next.
The aim of this script is to simplify the trading experience of users by automatically displaying a series of useful Moving Averages, allowing the user to easily configure multiple at once depending on their trading style.
█ USAGE
This script will automatically plot 5 Moving Averages, each with a period of a key Fibonacci Level (5, 8, 13, 21 and 34).
Both the Source and Type of the Moving Averages can be configured by the user (see all options below under SETTINGS), making this a versatile trading tool that can provide value in a wide variety of trading styles.
█ SETTINGS
Configuration
• MA Source: Determines the source of the Moving Averages (open, high, low, close, hl2, hlc3, ohlc4, hlcc4)
• MA Source: Determines the type of the Moving Averages (SMA, EMA, VWMA, WMA, HMA, RMA)
Colors
• 5: Determines the color of the 5 period Moving Average
• 8: Determines the color of the 8 period Moving Average
• 13: Determines the color of the 13 period Moving Average
• 21: Determines the color of the 21 period Moving Average
• 34: Determines the color of the 34 period Moving Average
High Probability OS/OB {DCAquant}DCAquant - High Probability OS/OB
The DCAquant - High Probability OS/OB Pine Script is a sophisticated indicator that provides insights into overbought (OB) and oversold (OS) conditions based on Hull Moving Averages (HMA) and Volume Weighted Moving Averages (VWMA). Here's a detailed breakdown of its functionality:
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THIS INDICATOR IS ONLY WRITTEN FOR BTC, ETH and TOTAL!!!!!!!!!!!!!
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Functionality
The script identifies high-probability OB and OS zones by combining multiple moving averages (MAs).
1. Volume Weighted Moving Average (VWMA)
The VWMA function computes the VWMA over a specified length, incorporating both the price and volume.
2. Hull Moving Average with Volume Weight (HMA-VW)
The hullma_vw function calculates the HMA using the VWMA. This involves:
Computing VWMAs over the full length and half-length.
Using these VWMAs to derive the HMA-VW through a weighted approach.
5. Standard Hull Moving Average (HMA)
The hull function computes the HMA using the standard weighted moving average (WMA).
4. Smoothed HMA-VW
This is an Exponential Moving Average (EMA) of the HMA-VW to smooth out short-term fluctuations.
How this works
First, the distance between the 2 MA's is calculated.
The distance is scored against the average price of the last 100 days.
By getting this score we can calculate extremes
The Extremes are categorized into 4 levels. The transparency of the background color distinguishes these 4 levels.
Only the MOST extremes are plotted ON THE CHART. Within the indicator, all 4 levels are plotted.
Usage
Extreme Buy zone: Consider entering the market when the indicator shows deep negative values (oversold). These are highlighted with a cyan background, with increasing opacity indicating stronger buy signals (Level 4 Zones).
Extreme Sell Zone: Consider exiting the market when the indicator shows high positive values (overbought). These are highlighted with a magenta background, with increasing opacity indicating stronger sell signals (Level 4 Zones).
Disclaimer
This indicator should not be used in isolation. It is recommended to use this as part of a systematic approach, incorporating other tools and analysis methods to confirm signals and make well-informed trading decisions.
Supertrend + BB + Consecutive Candles + QQE + EMA [Pineify]Overview
This indicator, developed by Pineify, is a comprehensive tool designed to assist traders in making informed decisions by combining multiple technical analysis methods. It integrates Supertrend, Bollinger Bands (BB), Consecutive Candles, Quantitative Qualitative Estimation (QQE), and Exponential Moving Averages (EMA) into a single, cohesive script. This multi-faceted approach allows traders to analyze market trends, volatility, and potential buy/sell signals with greater accuracy.
Key Features
1. Supertrend: Utilizes the Supertrend indicator to identify the prevailing market trend. It provides clear buy and sell signals based on the direction of the trend.
2. Bollinger Bands (BB): Measures market volatility and identifies overbought or oversold conditions. The script calculates the middle, upper, and lower bands, along with the Bollinger Band Width (BBW) and Bollinger Band %B (BBR).
3. Consecutive Candles: Detects sequences of consecutive bullish or bearish candles, providing signals when a specified number of consecutive candles are detected.
4. Quantitative Qualitative Estimation (QQE): Combines the Relative Strength Index (RSI) with a smoothing factor to generate buy and sell signals based on the QQE methodology.
5. Exponential Moving Averages (EMA): Includes both fast and slow EMAs to identify potential crossovers, which are used as buy and sell signals.
How It Works
- Supertrend: The Supertrend indicator is calculated using a factor and ATR length. It plots the trend direction and generates buy/sell signals when the trend changes.
- Bollinger Bands: The BB indicator calculates the middle band as a Simple Moving Average (SMA) of the closing prices. The upper and lower bands are derived by adding and subtracting a multiple of the standard deviation from the middle band.
- Consecutive Candles: This feature counts the number of consecutive candles that close higher or lower than the previous candle. When the count reaches a specified threshold, it generates a buy or sell signal.
- QQE: The QQE indicator smooths the RSI values and calculates the QQE Fast and QQE Slow lines. Buy and sell signals are generated based on the crossover of these lines.
- EMA: The script calculates fast and slow EMAs and generates buy/sell signals based on their crossovers.
How to Use
1. Inputs: Customize the indicator settings through the input parameters:
- Supertrend Factor and ATR Length
- BB Length
- Consecutive Candles Counting
- QQE RSI Length
- Fast and Slow EMA Lengths
- Enable/Disable Alerts for various signals
2. Alerts: Set up alerts for Supertrend, Consecutive Candles, and EMA crossovers. Alerts can be enabled or disabled based on user preference.
3. Visualization: The indicator plots the Supertrend, Bollinger Bands, and EMA lines on the chart. It also marks buy and sell signals with arrows and labels for easy identification.
Concepts Underlying Calculations
- Supertrend: Based on the Average True Range (ATR) to determine the trend direction and potential reversal points.
- Bollinger Bands: Utilizes standard deviation to measure market volatility and identify overbought/oversold conditions.
- Consecutive Candles: A method to detect momentum by counting consecutive bullish or bearish candles.
- QQE: Enhances the traditional RSI by smoothing it and using a dynamic threshold to generate signals.
- EMA: A widely used moving average that gives more weight to recent prices, making it responsive to market changes.
This indicator is a powerful tool for traders looking to combine multiple technical analysis methods into a single, easy-to-use script. By integrating these diverse techniques, it provides a comprehensive view of market conditions and potential trading opportunities.
stockexploderits just for identifying moving average crossover 20 and 50 to identify trend in stocks
easily without taking much time
Death Cross and Golden Cross HighlighterOverview
The script is designed to visually indicate the occurrence of Death Cross and Golden Cross events on a TradingView chart. It achieves this by calculating two moving averages (short-term and long-term) and plotting them on the chart. It then detects when these moving averages cross and highlights these points with labels and background colors.
Inputs
The script begins by defining input parameters:
- Short Moving Average Length: This is set to 50 by default, representing the short-term moving average period.
- Long Moving Average Length: This is set to 200 by default, representing the long-term moving average period.
These inputs allow users to customize the lengths of the moving averages according to their trading strategy.
Moving Averages Calculation
The script calculates two simple moving averages (SMAs) based on the closing prices:
- Short Moving Average (shortMA): Calculated over the short-term period specified by the user.
- Long Moving Average (longMA): Calculated over the long-term period specified by the user.
Plotting the Moving Averages
The moving averages are then plotted on the chart:
- The short-term moving average is plotted in blue.
- The long-term moving average is plotted in red.
These lines help users visually track the trends and potential crossover points.
Identifying Crossovers
The script identifies two key events:
- Golden Cross: Occurs when the short-term moving average crosses above the long-term moving average. This is typically considered a bullish signal, indicating a potential upward trend.
- Death Cross: Occurs when the short-term moving average crosses below the long-term moving average. This is typically considered a bearish signal, indicating a potential downward trend.
Highlighting Crossovers
To make the crossover events more noticeable, the script adds visual cues:
- Golden Cross: When a Golden Cross is detected, a green label with an upward arrow is plotted below the bar where the crossover occurs.
- Death Cross: When a Death Cross is detected, a red label with a downward arrow is plotted above the bar where the crossover occurs.
Background Coloring
Additionally, the script highlights the background of the chart:
- When a Golden Cross occurs, the background color is changed to a translucent green.
- When a Death Cross occurs, the background color is changed to a translucent red.
These background colors help emphasize the crossover events, making them easier to spot.
Usage
To use this script, a user would:
1. Copy the script and paste it into the Pine Script editor on TradingView.
2. Save the script and apply it to their chart.
By doing so, the user will see the moving averages plotted, and any Golden Cross or Death Cross events will be highlighted with labels and background colors. This visual aid helps traders quickly identify significant crossover events, which can inform their trading decisions.
Volume-Enhanced Momentum Moving Average (VEMMA)Volume-Enhanced Momentum Moving Average (VEMMA)
Overview:
The Volume-Enhanced Momentum Moving Average (VEMMA) helps you spot market trends by combining momentum and volume as a moving average. This unique moving average adjusts itself based on the strength and activity of the market, giving you a clearer picture of what’s happening.
How It Works:
1. Key Settings (all of these are adjustable in the settings panel of the indicator):
◦ Base Length: Looks back over the last 50 days by default.
◦ Momentum Length: Uses the past 14 days to measure market strength.
◦ Volume Length: Uses the past 30 days to average trading volume.
◦ High/Low Thresholds: Considers RSI values above 70 as high momentum and below 30 as low momentum.
2. Momentum and Volume:
◦ Momentum: Calculated using the Relative Strength Index (RSI) to see if the market is gaining or losing strength.
◦ Volume: Average trading volume is calculated over the last 30 days to gauge trading activity.
3. VEMMA Calculation:
◦ For each of the past 50 days:
▪ Check Momentum: If RSI > 70, it’s high momentum; if RSI < 30, it’s low.
▪ Weight by Volume: High momentum days with high volume get more weight; low momentum days get less.
▪ Combine: Multiply the closing price by this weight and sum it up.
◦ Average: Divide the total by 50 to get the VEMMA value.
4. Visuals:
◦ Lines: Two lines, VEMMA1 (blue) and VEMMA2 (orange), show the adjusted moving averages.
◦ Colours: Background colors help you quickly spot high (green) and low (red) momentum periods.
How to Use:
• Spot Trends: Rising VEMMA lines suggest an uptrend; falling lines suggest a downtrend.
• Confirm Signals: When both VEMMA1 and VEMMA2 move together, it indicates a strong trend.
• Identify Reversals: Watch for background color changes from green to red or vice versa to catch potential trend reversals.
If the market has been strong and active, the VEMMA line will rise more sharply. If the market is weak and quiet, the line will be smoother.
Benefits:
• Integrated View: Combines market strength and trading activity for a fuller picture.
• Responsive: Adapts to significant market changes, highlighting key movements.
• Easy to Read: Clear visuals with color-coded backgrounds make interpretation simple.
Remember, just like any other indicator, this is not supposed to be used alone. Use it as part of your greater trading strategy. I do however believe it works exceptionally well for finding longer term trends early. The default VEMMA settings work very well as replacement for the EMA 200. Try it and see how it goes. Play around with the settings. Feedback appreciated.
[EVI]EMA with Volume LevelsThe " EMA with Volume Levels" script calculates the Exponential Moving Average (EMA) of the closing prices over a specified period and dynamically changes the color of the EMA based on volume levels. This indicator helps traders easily identify the current volume conditions. As the volume increases or decreases, the color of the EMA changes, providing a visual cue that can assist in making better trading decisions.
Features
This script offers the following features:
EMA Calculation: Calculates the Exponential Moving Average of the closing prices over the user-defined period (default is 360).
Volume Threshold Calculation: Computes the Simple Moving Average (SMA) and standard deviation of the volume over the user-defined period (default is 500), classifying the volume levels into extreme, high, medium, and low.
Dynamic EMA Color: Changes the color of the EMA dynamically based on volume levels, displaying it visually on the chart.
Chart Interpretation
EMA Color and Volume:
If the EMA line is red, it indicates very high volume.
If the EMA line is green, it indicates high volume.
If the EMA line is light green, it indicates medium volume.
If the EMA line is gray, it indicates low volume.
If the EMA line is dark gray, it indicates very low volume.
Cross Analysis:
When the EMA line and the candles are about to cross, and the volume is high (causing the EMA line to turn red), the candles are more likely to break through the 360-day EMA line.
Conversely, if the volume is low and the EMA line turns dark, the EMA line will likely act as a resistance or support level, increasing the likelihood of a bounce.
Additional Indicator:
Using the 20-day moving average along with this script can be beneficial. Combining these two moving averages can provide a more comprehensive view of market volatility.
Notes
Clean Chart: Ensure your chart is clean when using this script. Avoid including other scripts or unnecessary elements.
Additional Explanation: If further explanation is needed on how to use or understand the script, you can use drawings or images on the chart to provide additional context.
Bayesian Trend Indicator [ChartPrime]Bayesian Trend Indicator
Overview:
In probability theory and statistics, Bayes' theorem (alternatively Bayes' law or Bayes' rule), named after Thomas Bayes, describes the probability of an event, based on prior knowledge of conditions that might be related to the event.
The "Bayesian Trend Indicator" is a sophisticated technical analysis tool designed to assess the direction of price trends in financial markets. It combines the principles of Bayesian probability theory with moving average analysis to provide traders with a comprehensive understanding of market sentiment and potential trend reversals.
At its core, the indicator utilizes multiple moving averages, including the Exponential Moving Average (EMA), Simple Moving Average (SMA), Double Exponential Moving Average (DEMA), and Volume Weighted Moving Average (VWMA) . These moving averages are calculated based on user-defined parameters such as length and gap length, allowing traders to customize the indicator to suit their trading strategies and preferences.
The indicator begins by calculating the trend for both fast and slow moving averages using a Smoothed Gradient Signal Function. This function assigns a numerical value to each data point based on its relationship with historical data, indicating the strength and direction of the trend.
// Smoothed Gradient Signal Function
sig(float src, gap)=>
ta.ema(source >= src ? 1 :
source >= src ? 0.9 :
source >= src ? 0.8 :
source >= src ? 0.7 :
source >= src ? 0.6 :
source >= src ? 0.5 :
source >= src ? 0.4 :
source >= src ? 0.3 :
source >= src ? 0.2 :
source >= src ? 0.1 :
0, 4)
Next, the indicator calculates prior probabilities using the trend information from the slow moving averages and likelihood probabilities using the trend information from the fast moving averages . These probabilities represent the likelihood of an uptrend or downtrend based on historical data.
// Define prior probabilities using moving averages
prior_up = (ema_trend + sma_trend + dema_trend + vwma_trend) / 4
prior_down = 1 - prior_up
// Define likelihoods using faster moving averages
likelihood_up = (ema_trend_fast + sma_trend_fast + dema_trend_fast + vwma_trend_fast) / 4
likelihood_down = 1 - likelihood_up
Using Bayes' theorem , the indicator then combines the prior and likelihood probabilities to calculate posterior probabilities, which reflect the updated probability of an uptrend or downtrend given the current market conditions. These posterior probabilities serve as a key signal for traders, informing them about the prevailing market sentiment and potential trend reversals.
// Calculate posterior probabilities using Bayes' theorem
posterior_up = prior_up * likelihood_up
/
(prior_up * likelihood_up + prior_down * likelihood_down)
Key Features:
◆ The trend direction:
To visually represent the trend direction , the indicator colors the bars on the chart based on the posterior probabilities. Bars are colored green to indicate an uptrend when the posterior probability is greater than 0.5 (>50%), while bars are colored red to indicate a downtrend when the posterior probability is less than 0.5 (<50%).
◆ Dashboard on the chart
Additionally, the indicator displays a dashboard on the chart , providing traders with detailed information about the probability of an uptrend , as well as the trends for each type of moving average. This dashboard serves as a valuable reference for traders to monitor trend strength and make informed trading decisions.
◆ Probability labels and signals:
Furthermore, the indicator includes probability labels and signals , which are displayed near the corresponding bars on the chart. These labels indicate the posterior probability of a trend, while small diamonds above or below bars indicate crossover or crossunder events when the posterior probability crosses the 0.5 threshold (50%).
The posterior probability of a trend
Crossover or Crossunder events
◆ User Inputs
Source:
Description: Defines the price source for the indicator's calculations. Users can select between different price values like close, open, high, low, etc.
MA's Length:
Description: Sets the length for the moving averages used in the trend calculations. A larger length will smooth out the moving averages, making the indicator less sensitive to short-term fluctuations.
Gap Length Between Fast and Slow MA's:
Description: Determines the difference in lengths between the slow and fast moving averages. A higher gap length will increase the difference, potentially identifying stronger trend signals.
Gap Signals:
Description: Defines the gap used for the smoothed gradient signal function. This parameter affects the sensitivity of the trend signals by setting the number of bars used in the signal calculations.
In summary, the "Bayesian Trend Indicator" is a powerful tool that leverages Bayesian probability theory and moving average analysis to help traders identify trend direction, assess market sentiment, and make informed trading decisions in various financial markets.
Iron Cortex: Volume AnalysisDescription:
This Volume Analysis indicator is designed to identify potential buying and selling pressures in the market by analysing volume and price changes in conjunction with dual Exponential Moving Averages (EMAs).
Signal Identification:
Buying Pressure: This signal is identified when:
i) Volume is rising and the price is increasing.
ii) The current volume is above both the fast and slow EMAs of the volume.
iii) The fast EMA is above the slow EMA.
Selling Pressure: This signal is identified when:
i) Volume is rising and the price is decreasing.
ii) The current volume is above both the fast and slow EMAs of the volume.
iii) The fast EMA is above the slow EMA.
Interpretation:
When the volume bars change to the specified colours, it indicates potential buying or selling pressure based on the underlying conditions. Teal is buying pressure, red is selling pressure.
Use this information in conjunction with other technical analysis tools to make informed trading decisions. As with all indicators, expect some false signals in choppy markets.
This indicator is useful for traders who want to incorporate volume analysis with price trends and EMA crossovers to identify strong market movements. Adjust the settings to fit your trading strategy and enhance your market analysis.
Advanced Fractal and Hurst IndicatorAdvanced Fractal and Hurst Indicator (AFHI)
Description:
The Advanced Fractal and Hurst Indicator (AFHI) is a custom technical analysis tool designed to identify market trends and potential reversals by leveraging the concepts of Fractal Dimension and the Hurst Exponent . These advanced mathematical concepts provide insights into the complexity and persistence of price movements, making this indicator a powerful addition to any trader's toolkit.
How It Works:
Fractal Dimension (FD) :
The Fractal Dimension measures the complexity of price movements. A higher Fractal Dimension indicates a more complex, choppy market, while a lower value suggests smoother trends.
The FD is calculated using the log difference of price movements over a specified length.
Hurst Exponent (HE) :
The Hurst Exponent indicates the tendency of a time series to either regress to the mean or cluster in a direction. Values below 0.5 indicate a tendency to revert to the mean (mean-reverting), while values above 0.5 suggest a trending market.
The HE is calculated using the rescaled range method, comparing the range of price movements to the standard deviation.
Composite Indicator :
The Composite Indicator combines the smoothed Fractal Dimension and Hurst Exponent to provide a single value indicating market conditions. This is done by normalizing the FD and HE values and combining them into one metric.
A positive Composite Indicator suggests an uptrend, while a negative value indicates a downtrend.
Smoothing :
Both FD and HE values are smoothed using a simple moving average to reduce noise and provide clearer signals.
Trend Confirmation :
A 50-period moving average (MA) is used to confirm the trend direction. The price being above the MA indicates an uptrend, while below the MA indicates a downtrend.
Background Shading :
The indicator pane is shaded green during uptrend conditions (positive Composite Indicator and price above MA) and red during downtrend conditions (negative Composite Indicator and price below MA).
How Traders Can Use It:
Identifying Trends :
Traders can use the AFHI to identify current market trends. The background shading in the indicator pane provides a visual cue for trend direction, with green indicating an uptrend and red indicating a downtrend.
Trend Confirmation :
The Composite Indicator line, plotted in purple, helps confirm the trend. Positive values suggest a strong uptrend, while negative values indicate a strong downtrend.
Entry and Exit Signals :
Traders can use the transitions of the Composite Indicator and the background shading to time their entry and exit points. For instance, a shift from red to green shading suggests a potential buy opportunity, while a shift from green to red suggests a potential sell opportunity.
Alerts :
The script includes alert conditions that can notify traders when the Composite Indicator signals a new trend direction. Alerts can be set up for both uptrends and downtrends, helping traders stay informed of key market changes.
Strategy Development :
By integrating AFHI into their trading strategies, traders can develop more robust systems that account for market complexity and persistence. The indicator can be used alongside other technical tools to enhance decision-making and improve trade accuracy.
Market Slayer (i)Market Slayer (i)
This script is designed to provide insights into market trends and generate trading signals based on a combination of moving average crossovers and trend confirmation. It aims to assist traders in identifying potential entry and exit points in the market.
Input Parameters:
Trend Timeframe: Allows the user to specify the timeframe for trend analysis. Default is set to W (weekly).
Trend Value: Defines the sensitivity of the trend detection algorithm.
Short SMA Length: Length of the short-term Simple Moving Average (SMA).
Long SMA Length: Length of the long-term Simple Moving Average (SMA).
Bullish Color: Color representation for bullish signals.
Bearish Color: Color representation for bearish signals.
Take Profit Color: Color representation for take profit events.
Simple Moving Average (SMA) Logic:
Two SMAs are calculated based on the provided lengths: one short-term and one long-term.
Short-term SMA values are plotted with a semi-transparent bearish color.
Long-term SMA values are plotted with a semi-transparent bullish color.
Trend Logic:
The script employs a modified SSL (Schaff Trend Cycle) indicator to determine the trend direction.
Trend direction is determined based on whether the closing price is above or below the SSL (Schaff Trend Cycle) indicator.
Trend changes are detected by comparing the current trend direction with the previous two trend directions.
Signal Logic:
Buy signals are generated when the short-term SMA crosses above the long-term SMA and the trend is bullish.
Sell signals are generated when the short-term SMA crosses below the long-term SMA and the trend is bearish.
Signals are confirmed only if there is no open position.
Take Profit Logic:
Take profit events are triggered when the trend changes direction after a position has been opened.
Take profit events are confirmed only if there is an open position.
Alerts:
Various alerts are included to notify traders of different events such as signal generation, take profit opportunities, and trend changes.
Usage of lookahead:
Within the script, the lookahead argument is utilized in the request.security() function to control how much historical data should be loaded for trend analysis.
Setting lookahead=barmerge.lookahead_on enables the script to consider future price movements when calculating trend conditions.
This functionality can enhance the accuracy of trend detection by incorporating future bars into the analysis.
Usage:
Traders can use this script on the TradingView platform to visualize market trends, identify potential entry and exit points, and receive timely alerts for trading opportunities.
