MavilimW ScreenerScreener version of MavilimW Moving Average :
Short-Term Examples (by decreasing 3 and 5 default values to have trading signals from color changes)
BUY when MavilimW turns blue from red.
SELL when MavW turns red from blue.
Long-Term Examples (with Default values 3 and 5)
BUY when the price crosses over the MavilimW line
SELL when the price crosses below the MavW line
MavilimW can also define significant SUPPORT and RESISTANCE levels in every period with its default values 3 and 5.
Screener Panel:
You can explore 20 different and user-defined tickers, which can be changed from the SETTINGS (shares, crypto, commodities...) on this screener version.
The screener panel shows up right after the bars on the right side of the chart.
Tickers seen in green are the ones that are in an uptrend, according to MavilimW.
The ones that appear in red are those in the SELL signal, in a downtrend.
The numbers in front of each Ticker indicate how many bars passed after the last BUY or SELL signal of MavW.
For example, according to the indicator, when BTCUSDT appears (3) in GREEN, Bitcoin switched to a BUY signal 3 bars ago.
-In this screener version of MavilimW, users can define the number of demanded tickers (symbols) from 1 to 20 by checking the relevant boxes on the settings tab.
-All selected tickers can be screened in different timeframes.
-Also, different timeframes of the same Ticker can be screened.
IMPORTANT NOTICE:
-Screener shows the information about the color changes of MavilimW Moving Average with default settings (as explained in the Short-Term Example section).
-Users can check the "Change Screener to show MavilimW & Price Flips" button to activate the screener as explained in the Short-Term Example section. Then the screener will give information about price flips.
移動平均線
3 Fib EMAs To Scalp Them AllThe "3 Fib EMAs To Scalp Them All" was made in order to clear up when we should look for shorts, longs, or walk away. Also it can alert you when a trend starts, or when there is a possible reversal. I use it for scalping/day trading in 5m-1h timeframes.
1. EMAs: By default, the indicator uses Fibonacci numbers (21, 55, 233), but you can change them.
2. Color Changes: The color of the Micro EMA line changes depending on its relation to the Mid and Macro EMAs.
When Micro EMA < Mid < Macro EMA, it turns red, indicating a potential bearish trend - that's when you should look for shorts
When Micro EMA > Mid > Macro EMA, it turns green, indicating a potential bullish trend - that's when you should look for longs
A white Micro EMA is when you need to take some rest, enjoy your coffee, and avoid overtrading.
3. Signals: The indicator provides visual signals in the form of diamonds and crosses and corresponding alert signals.
A red diamond above the bar signals a potential beginning of a downtrend
A red cross above the bar signals the end of the downtrend and can be used as a signal for a possible reversal up/breakout.
A green diamond below the bar signals a potential beginning of a downtrend,
A green cross below the bar signals the end of the uptrend and can be used as a signal for a possible reversal down/breakout.
4. Alerts: For algo traders and people who prefer to stay away from the monitor... there are alerts for every signal.
Friendly note: Don't blindly follow the signals for your long and short entries. The signals only pop up when the EMA cross value gets a confirmation. A smart move would be to wait for a retracement to the EMA line and use momentum indicators like market cipher B to pinpoint those ideal entry points.
EMA with Buy/Sell Signals by lbkindCertainly! Here's a description of the code:
This Pine Script code is designed to plot Exponential Moving Averages (EMAs) on a chart and generate buy/sell signals based on specific conditions. The code includes a filter to reduce false signals by considering the trend of the EMA 200.
The key components of the code are as follows:
1. Input Variables: The code starts by defining input variables such as the periods for the EMAs (ema200Period, ema50Period, ema13Period), the Average True Range period (atrPeriod), and the chopiness threshold (chopinessThreshold).
2. Calculating EMAs: The EMAs (ema200, ema50, ema13) are calculated using the `ema()` function based on the closing price.
3. Average True Range (ATR): The ATR is calculated using the `atr()` function with the specified period (atrPeriod).
4. Normalized ATR: The normalized ATR is computed by dividing the ATR by the closing price and multiplying by 100. This allows for better comparison across different price levels.
5. EMA 200 Trend Direction: The code determines the trend direction of the EMA 200 by comparing the current value with the previous value. The variables `ema200TrendUp` and `ema200TrendDown` are assigned `true` or `false` values based on the trend direction.
6. Generate Buy/Sell Signals: The buySignal is generated when the following conditions are met:
- There is a crossover of the shorter EMAs (ema13, ema50).
- The EMA 200 is in an uptrend (`ema200TrendUp` is true).
- The current close is above the EMA 200.
- The normalized ATR is below the specified chopiness threshold.
The sellSignal is generated when the opposite conditions are met.
7. Plotting: The EMAs (ema200, ema50, ema13) are plotted on the chart using the `plot()` function. The buy and sell signals are plotted as labels using the `plotshape()` function. The buySignal is displayed below the candle (`location=location.belowbar`), and the sellSignal is displayed above the candle (`location=location.abovebar`).
By incorporating these features, the code provides a visual representation of the EMAs, along with buy and sell signals that consider the EMA 200 trend, crossover of shorter EMAs, and the normalized ATR condition. This helps in identifying potential entry and exit points in the market while attempting to reduce false signals.
Selective Moving Average: DemoThis indicator produces a conditional moving average based off of your chosen inputs. For example, you can create an EMA that only takes into account closing prices when the 14 period RSI is greater than 50, or a VWMA that tracks hl2 values when the hl2 value is within one standard deviation from the mean. The possibilities are highly configurable to your liking. Please comment below additional conditions you might like me to add to the moving average and I will try my best to get to your feedback.
The following parameters are configurable:
--> Source: This is the source of the moving average that you want to create. You can use external sources if you have another indicator on your chart.
--> Condition: This is the condition that you want to take into account when the moving average is calculating itself. For instance, I have the following conditions pre-built (more to come): Source within 1 standard deviation of the mean (of the source), Source within 2 standard deviations of the mean (of the source), Positive volume, Negative volume, RSI greater than 50, RSI less than 50, Candlestick length greater than body.
--> Length: The length of the selective moving average. For conditions that occur infrequently, a larger length may be necessary to improve accuracy.
--> Average type: The type of moving average (SMA, EMA, RMA, etc.) that you wish to create
--> Condition length: An optional parameter if you are using a condition that depends on a length itself, i.e. the RSI - here you can change the RSI length. The RSI source will be the moving average source, but future updates may separate the two.
Super Secret 200 EMAThe indicator is called "Super Secret 200 EMA." It combines two technical indicators, the Supertrend and the 200 Exponential Moving Average (EMA), to generate buy and sell opportunities in a trading chart.
Here's how the indicator works and how you can use it:
Supertrend Calculation:
The Supertrend indicator helps identify the current trend in the market. It uses two parameters: Length and Multiplier.
Length: This parameter determines the number of periods used for the calculation.
Multiplier: It controls the width of the Supertrend line, indicating the level of volatility considered in the calculation.
The Supertrend is calculated by looping through the historical data from length to 1.
For each period, it checks whether the closing price has increased or decreased compared to the previous period.
If the closing price has increased, it updates the highestHigh value with the maximum of the current highest high and the high of the current period.
If the closing price has decreased, it updates the lowestLow value with the minimum of the current lowest low and the low of the current period.
Finally, it calculates the Supertrend value using the following formula:
If the change in the closing price is positive: Supertrend = lowestLow + (multiplier * Average True Range (ATR))
If the change in the closing price is negative: Supertrend = highestHigh - (multiplier * ATR)
The Supertrend line will be green if it is above the 200 EMA line and red if it is below.
200 EMA Calculation:
The 200 EMA is a widely used moving average indicator that gives more weight to recent prices.
The EMA period is set to 200 in this case.
The 200 EMA is calculated using the EMA formula, taking into account the closing prices over the specified period.
Plotting:
The Supertrend and 200 EMA lines are plotted on the chart using the plot function.
The Supertrend line is colored green if it is above the 200 EMA line and red if it is below.
The 200 EMA line is colored green if the closing price is above it and red if it is below.
Buy and Sell Conditions:
The indicator determines the buy and sell conditions based on the crossover and crossunder of the closing price with the 200 EMA line and the Supertrend line.
Buy Condition: A buy signal is generated when the closing price crosses above the 200 EMA line and is also above the Supertrend line.
Sell Condition: A sell signal is generated when the closing price crosses below the 200 EMA line and is also below the Supertrend line.
Plotting Buy and Sell Signals:
You can use this indicator to identify potential buy and sell opportunities in your trading strategy. However, please note that this is a simplified explanation, and it's essential to thoroughly understand the indicator's principles and backtest it with historical data before relying on it for actual trading decisions.
Use this with other confluences for best results and never rely on a single indicator
Vwma Oscillator [MMD]This line calculates the exponential moving average (EMA) of the product of the close price and volume, divided by the EMA of the volume. The EMA is calculated over a period of 4 bars.
This line calculates the difference between the value of a1 and the volume-weighted moving average (VWMA) of the close price. The VWMA is calculated over a period of 8 bars.
This line calculates a3 as twice the VWMA of a2 over a period of 8 bars, minus the VWMA of a2 over a period of 16 bars.
This line plots the value of a3 on the chart. The color of the plot is determined by the condition inside the color argument. If a3 is within 20% of its previous value (a3 ) in either direction, the color is set to silver. Otherwise, if a3 is greater than 0, the color is set to green; otherwise, it is set to red. The linewidth parameter sets the thickness of the plot, and the style parameter specifies that circles should be used to plot the values.
These lines plot two horizontal lines on the chart, one at 80% of the previous a3 value (a3 *0.8) and the other at 120% of the previous a3 value (a3 *1.2). The transp=100 parameter makes the lines transparent. The fill function is then used to fill the area between these lines with either a red or green color, depending on whether a3 at the current bar is greater or smaller than the corresponding values.
This line plots a horizontal line at a value of 0 on the chart. The color is set to gray, and the line width is set to 2.
Overall, this indicator calculates the values of a1, a2, and a3 based on moving averages and
Buy Sell using 5-8-13 EMA, RSI, PSAR IndicatorThis indicator generates Scalping and Strong Buy/Sell Signals.
Quick Scalp signals are generated using 5 EMA and RSI.
Strong Buy/Sell Signals are generated using combination of 5-8-13 EMA and Parabolic SAR.
Signals generated:
QB: Quick Buy
QS: Quick Sell
SB: Strong Buy
SS: Strong Sell
Machine Learning : Cosine Similarity & Euclidean DistanceIntroduction:
This script implements a comprehensive trading strategy that adheres to the established rules and guidelines of housing trading. It leverages advanced machine learning techniques and incorporates customised moving averages, including the Conceptive Price Moving Average (CPMA), to provide accurate signals for informed trading decisions in the housing market. Additionally, signal processing techniques such as Lorentzian, Euclidean distance, Cosine similarity, Know sure thing, Rational Quadratic, and sigmoid transformation are utilised to enhance the signal quality and improve trading accuracy.
Features:
Market Analysis: The script utilizes advanced machine learning methods such as Lorentzian, Euclidean distance, and Cosine similarity to analyse market conditions. These techniques measure the similarity and distance between data points, enabling more precise signal identification and enhancing trading decisions.
Cosine similarity:
Cosine similarity is a measure used to determine the similarity between two vectors, typically in a high-dimensional space. It calculates the cosine of the angle between the vectors, indicating the degree of similarity or dissimilarity.
In the context of trading or signal processing, cosine similarity can be employed to compare the similarity between different data points or signals. The vectors in this case represent the numerical representations of the data points or signals.
Cosine similarity ranges from -1 to 1, with 1 indicating perfect similarity, 0 indicating no similarity, and -1 indicating perfect dissimilarity. A higher cosine similarity value suggests a closer match between the vectors, implying that the signals or data points share similar characteristics.
Lorentzian Classification:
Lorentzian classification is a machine learning algorithm used for classification tasks. It is based on the Lorentzian distance metric, which measures the similarity or dissimilarity between two data points. The Lorentzian distance takes into account the shape of the data distribution and can handle outliers better than other distance metrics.
Euclidean Distance:
Euclidean distance is a distance metric widely used in mathematics and machine learning. It calculates the straight-line distance between two points in Euclidean space. In two-dimensional space, the Euclidean distance between two points (x1, y1) and (x2, y2) is calculated using the formula sqrt((x2 - x1)^2 + (y2 - y1)^2).
Dynamic Time Windows: The script incorporates a dynamic time window function that allows users to define specific time ranges for trading. It checks if the current time falls within the specified window to execute the relevant trading signals.
Custom Moving Averages: The script includes the CPMA, a powerful moving average calculation. Unlike traditional moving averages, the CPMA provides improved support and resistance levels by considering multiple price types and employing a combination of Exponential Moving Averages (EMAs) and Simple Moving Averages (SMAs). Its adaptive nature ensures responsiveness to changes in price trends.
Signal Processing Techniques: The script applies signal processing techniques such as Know sure thing, Rational Quadratic, and sigmoid transformation to enhance the quality of the generated signals. These techniques improve the accuracy and reliability of the trading signals, aiding in making well-informed trading decisions.
Trade Statistics and Metrics: The script provides comprehensive trade statistics and metrics, including total wins, losses, win rate, win-loss ratio, and early signal flips. These metrics offer valuable insights into the performance and effectiveness of the trading strategy.
Usage:
Configuring Time Windows: Users can customize the time windows by specifying the start and finish time ranges according to their trading preferences and local market conditions.
Signal Interpretation: The script generates long and short signals based on the analysis, custom moving averages, and signal processing techniques. Users should pay attention to these signals and take appropriate action, such as entering or exiting trades, depending on their trading strategies.
Trade Statistics: The script continuously tracks and updates trade statistics, providing users with a clear overview of their trading performance. These statistics help users assess the effectiveness of the strategy and make informed decisions.
Conclusion:
With its adherence to housing trading rules, advanced machine learning methods, customized moving averages like the CPMA, and signal processing techniques such as Lorentzian, Euclidean distance, Cosine similarity, Know sure thing, Rational Quadratic, and sigmoid transformation, this script offers users a powerful tool for housing market analysis and trading. By leveraging the provided signals, time windows, and trade statistics, users can enhance their trading strategies and improve their overall trading performance.
Disclaimer:
Please note that while this script incorporates established tradingview housing rules, advanced machine learning techniques, customized moving averages, and signal processing techniques, it should be used for informational purposes only. Users are advised to conduct their own analysis and exercise caution when making trading decisions. The script's performance may vary based on market conditions, user settings, and the accuracy of the machine learning methods and signal processing techniques. The trading platform and developers are not responsible for any financial losses incurred while using this script.
By publishing this script on the platform, traders can benefit from its professional presentation, clear instructions, and the utilisation of advanced machine learning techniques, customised moving averages, and signal processing techniques for enhanced trading signals and accuracy.
I extend my gratitude to TradingView, LUX ALGO, and JDEHORTY for their invaluable contributions to the trading community. Their innovative scripts, meticulous coding patterns, and insightful ideas have profoundly enriched traders' strategies, including my own.
T3 JMA KAMA VWMAEnhancing Trading Performance with T3 JMA KAMA VWMA Indicator
Introduction
In the dynamic world of trading, staying ahead of market trends and capitalizing on volume-driven opportunities can greatly influence trading performance. To address this, we have developed the T3 JMA KAMA VWMA Indicator, an innovative tool that modifies the traditional Volume Weighted Moving Average (VWMA) formula to increase responsiveness and exploit high-volume market conditions for optimal position entry. This article delves into the idea behind this modification and how it can benefit traders seeking to gain an edge in the market.
The Idea Behind the Modification
The core concept behind modifying the VWMA formula is to leverage more responsive moving averages (MAs) that align with high-volume market activity. Traditional VWMA utilizes the Simple Moving Average (SMA) as the basis for calculating the weighted average. While the SMA is effective in providing a smoothed perspective of price movements, it may lack the desired responsiveness to capitalize on short-term volume-driven opportunities.
To address this limitation, our T3 JMA KAMA VWMA Indicator incorporates three advanced moving averages: T3, JMA, and KAMA. These MAs offer enhanced responsiveness, allowing traders to react swiftly to changing market conditions influenced by volume.
T3 (T3 New and T3 Normal):
The T3 moving average, one of the components of our indicator, applies a proprietary algorithm that provides smoother and more responsive trend signals. By utilizing T3, we ensure that the VWMA calculation aligns with the dynamic nature of high-volume markets, enabling traders to capture price movements accurately.
JMA (Jurik Moving Average):
The JMA component further enhances the indicator's responsiveness by incorporating phase shifting and power adjustment. This adaptive approach ensures that the moving average remains sensitive to changes in volume and price dynamics. As a result, traders can identify turning points and anticipate potential trend reversals, precisely timing their position entries.
KAMA (Kaufman's Adaptive Moving Average):
KAMA is an adaptive moving average designed to dynamically adjust its sensitivity based on market conditions. By incorporating KAMA into our VWMA modification, we ensure that the moving average adapts to varying volume levels and captures the essence of volume-driven price movements. Traders can confidently enter positions during periods of high trading volume, aligning their strategies with market activity.
Benefits and Usage
The modified T3 JMA KAMA VWMA Indicator offers several advantages to traders looking to exploit high-volume market conditions for position entry:
Increased Responsiveness: By incorporating more responsive moving averages, the indicator enables traders to react quickly to changes in volume and capture short-term opportunities more effectively.
Enhanced Entry Timing: The modified VWMA aligns with high-volume periods, allowing traders to enter positions precisely during price movements influenced by significant trading activity.
Improved Accuracy: The combination of T3, JMA, and KAMA within the VWMA formula enhances the accuracy of trend identification, reversals, and overall market analysis.
Comprehensive Market Insights: The T3 JMA KAMA VWMA Indicator provides a holistic view of market conditions by considering both price and volume dynamics. This comprehensive perspective helps traders make informed decisions.
Analysis and Interpretation
The modified VWMA formula with T3, JMA, and KAMA offers traders a valuable tool for analyzing volume-driven market conditions. By incorporating these advanced moving averages into the VWMA calculation, the indicator becomes more responsive to changes in volume, potentially providing deeper insights into price movements.
When analyzing the modified VWMA, it is essential to consider the following points:
Identifying High-Volume Periods:
The modified VWMA is designed to capture price movements during high-volume periods. Traders can use this indicator to identify potential market trends and determine whether significant trading activity is driving price action. By focusing on these periods, traders may gain a better understanding of the market sentiment and adjust their strategies accordingly.
Confirmation of Trend Strength:
The modified VWMA can serve as a confirmation tool for assessing the strength of a trend. When the VWMA line aligns with the overall trend direction, it suggests that the current price movement is supported by volume. This confirmation can provide traders with additional confidence in their analysis and help them make more informed trading decisions.
Potential Entry and Exit Points:
One of the primary purposes of the modified VWMA is to assist traders in identifying potential entry and exit points. By capturing volume-driven price movements, the indicator can highlight areas where market participants are actively participating, indicating potential opportunities for opening or closing positions. Traders can use this information in conjunction with other technical analysis tools to develop comprehensive trading strategies.
Interpretation of Angle and Gradient:
The modified VWMA incorporates an angle calculation and color gradient to further enhance interpretation. The angle of the VWMA line represents the slope of the indicator, providing insights into the momentum of price movements. A steep angle indicates strong momentum, while a shallow angle suggests a slowdown. The color gradient helps visualize this angle, with green indicating bullish momentum and purple indicating bearish momentum.
Conclusion
By modifying the VWMA formula to incorporate the T3, JMA, and KAMA moving averages, the T3 JMA KAMA VWMA Indicator offers traders an innovative tool to exploit high-volume market conditions for optimal position entry. This modification enhances responsiveness, improves timing, and provides comprehensive market insights.
Enjoy checking it out!
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Credits to:
◾ @cheatcountry – Hann Window Smoothing
◾ @loxx – T3
◾ @everget – JMA
SA 2.0The 100/200 EMA crossover strategy is a popular trend-following strategy used in technical analysis. It aims to identify potential buy and sell signals based on the crossover of two exponential moving averages (EMAs), specifically the 100-period EMA and the 200-period EMA. This strategy is designed to capture the momentum of the market and take advantage of sustained trends in the price of US30. This strategy can also work on other instruments, just backtest the winrate.
How it Works:
Timeframe Selection: The strategy is optimized for the US30 index and is implemented on both the 5-minute and 3-minute charts. These shorter timeframes provide more frequent trading opportunities and allow for quicker decision-making.
EMA Crossover: The strategy focuses on the crossover of the 100-period EMA and the 200-period EMA. When the 100 EMA crosses above the 200 EMA, it generates a bullish signal, indicating a potential upward trend. Conversely, when the 100 EMA crosses below the 200 EMA, it generates a bearish signal, suggesting a potential downward trend.
Rejection Confirmation: To filter out false signals and increase the reliability of the strategy, it incorporates a rejection confirmation. After the initial crossover, the strategy looks for price rejections near the 100 EMA. A rejection occurs when the price briefly moves below the 100 EMA and then quickly bounces back above it, indicating potential support and a possible continuation of the trend. It is during this rejection that the strategy generates the buy or sell signal.
Buy and Sell Signals: When a rejection occurs after the crossover, the strategy generates a buy signal if the rejection is above the 100 EMA. This suggests that the price is likely to continue its upward momentum. On the other hand, a sell signal is generated if the rejection occurs below the 100 EMA, indicating a potential continuation of the downward trend. These signals help traders identify favorable entry points for long or short positions.
Risk Management: As with any trading strategy, proper risk management is crucial. Traders can use stop-loss orders to limit potential losses in case the market moves against their positions. Additionally, setting profit targets or trailing stops can help secure profits as the trend progresses.
It's important to note that no trading strategy guarantees success, and it's recommended to test the strategy on historical data or in a demo trading environment before applying it with real funds. Furthermore, regular monitoring and adjustment may be necessary to adapt to changing market conditions.
Disclaimer: This description is for informational purposes only and should not be considered as financial advice. Trading carries risks, and individuals should exercise caution and consult with a qualified financial professional before making any investment decisions.
EMA ProHi Traders!
This Improved EMA Cross Pro Indicator does a few things that Ease Up Our Charting.
Personally it Saved me Tons of Time searching for structure highs / lows, measuring ranges and distances from my entry to stop or take profit.
It's like having most of your trade in front of you, charted for you.
Works Across Assets & Time Frames.
The Functions
1. Signals EMA Crosses - green for Bull Cross & Red for Bear Cross
2. Signals Touches to the 55 EMA
a. In a Bull Cross it will only signal touches and closes Above the 55
b. In a Bear Cross it will only signal touches and closes Under the 55
3. Plots Current Horizontals:
a. The current position of the 55
b. The last High & Low
4. Calculation:
a. % from the 55 to the High & Low
b. Risk / Reward Ratio ("Bad Risk Management" message appears if ratio is not favorable)
c. Over Range between the Low and the High
5. Labels - Current prices for all horizontals marked as Entry, Exit & Stop
Notes:
* This Indicator is Interchanging between bull and bear crosses, it recognizes the trend and adapts its high and low output.
* You Can and Should make your personal changes. everything can be changed in the settings inputs.
* You can Turn On & Off most functions in the settings inputs.
BYBIT:BTCUSDT.P
AggBands (v1) [qrsq]The "AggBands" indicator is a custom trading indicator designed to provide a consolidated view of the price action across multiple assets or trading pairs. It combines the price data from multiple tickers and calculates an aggregated price using user-defined weights for each ticker.
The indicator starts by defining the tickers to be included in the aggregation. You can choose from predefined configurations such as "BTC PAIRS," "CRYPTO TOTAL MARKET CAP," "TOP 5 PAIRS," "TOP 5 MEMECOINS," "SPX," "DXY," or "FANG." Each configuration includes specific tickers or indices relevant to the chosen category.
The indicator then fetches the closing, high, and low prices for each ticker and applies the user-defined weights to calculate the aggregated prices. The aggregated prices are normalized within a specified length to provide a consistent scale across different assets or pairs.
Next, the indicator calculates the midpoint, which is the average of the highest high and lowest low of the aggregated prices over a specified aggregation period.
To assess the volatility, the indicator calculates the price range and applies the Average True Range (ATR) indicator to determine the volatility value. The standard deviation is then computed using the price range and aggregation period, with an additional scaling factor applied to the volatility value.
Based on the standard deviation, the indicator generates multiple bands above and below the midpoint. By default, three standard deviation bands are calculated, but the user can choose between one and five bands. The upper and lower bands are smoothed using various moving average (MA) types, such as Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA/RMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Volume Weighted Average Price (VWAP), or Arnaud Legoux Moving Average (ALMA). The user can also adjust the length, offset, and sigma parameters for the moving averages.
The indicator can optionally smooth the midpoint, upper bands, and lower bands using a separate set of moving average parameters.
The indicator can be useful for traders and analysts who want to gain a consolidated view of price movements across multiple assets or trading pairs. It helps identify trends, volatility, and potential support and resistance levels based on the aggregated price and standard deviation bands. Traders can use this information to make informed decisions about trading strategies, risk management, and market analysis.
EMA orderly stacked or notThis script plots a green circle on top of the chart when the EMAs are stacked positively, a red circle if they are stacked negatively and gray if neither positively nor negatively stacked.
The EMAs used are:
8 EMA
21 EMA
34 EMA
55 EMA
89 EMA
Useful when you look for a quick and easy way to see if these EMAs are stacked positively or negatively as a confirmation to the Squeeze Pro indicator if going long or short (Squeeze Pro is developed by John Carter at SimplerTrading.com and can be purchased there).
Default 100 bars back, but that can be adjusted.
Remember to do your own research.
Feel free to adjust the script to your liking.
The script is not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by me.
Have fun!
Recursive Moving Average DifferenceThe relative difference between a moving average and the price can be a useful tool for interpreting trend direction and identifying pullbacks or breakdowns. This indicator recursively finds all the relative moving average differences between two simple moving averages of your choosing and weighs them by their lengths. It then returns a value that represents the weighted average of all the moving average differences. This can represent the gradient of motion between moving averages, or the path of least resistance, which the price may revert to in certain situations.
For the settings: minimum MA represents the minimum simple moving average to consider for the total weighted average. Maximum MA represents the maximum simple moving average to consider. "Move By" is the increment that you want to move between these two moving averages.
A positive moving average difference indicates that the price is above the moving average difference (i.e. the weighted average of all moving average differences between your two selected moving averages). A negative moving average difference indicates that the price is below the moving average difference. I have added a signal with a configurable length input as well to smooth out trends.
You can configure colors and lengths, as well as the counting increment. Future updates may include different ways to calculate weights, perhaps on overlay or strategy.
ADW - MomentumADW - Momentum is a trading indicator based on the Relative Momentum Index (RMI) and Exponential Moving Averages (EMAs). This indicator plots the RMI along with its EMAs and highlights regions where RMI crosses its slow EMA. Additionally, it provides alerts when the momentum flips bullish or bearish.
Key Features:
The RMI helps to identify momentum in the market.
Three EMAs (Fast, Standard, and Slow) were calculated on the RMI. These can be utilized to analyze the momentum trend over different periods.
Highlighted regions and colour coding to indicate when RMI crosses its Slow EMA, signalling potential momentum shifts.
Customizable parameters: Users can specify the lengths of the RMI and EMAs, boundaries for RMI, and colours for various components of the plot.
Alerts: The script can alert users when the momentum has flipped bullish or bearish.
The script is organized into several sections:
Inputs: The user can customize several parameters including the RMI averaging length, momentum lookback, RMI boundaries, and the EMA lengths. In addition, users can also specify the colours for the RMI line, Slow EMA line, and the fill colour.
RMI Calculation: The script calculates the RMI based on the user-provided length and momentum lookback. This is done by first calculating two EMAs - one for the positive differences between closing prices (emaInc), and one for the negative differences (emaDec). Then, the RMI is computed using these EMAs.
Plotting: The script plots the RMI line, Slow EMA line, and two horizontal lines indicating the RMI boundaries. In addition, it also fills the region between the RMI and Slow EMA lines.
Conditions: The script computes the conditions for bullish and bearish momentum flips. These are defined as when the RMI crosses above or below the Slow EMA respectively.
Alerts: Finally, the script sets up two alert conditions based on the bullish and bearish conditions. These alert the user when the momentum has flipped bullish or bearish, with a message that includes the current RMI value.
ADW - Colour TrendColour Trend is an indicator that will give you a visual representation of the trend in a selected market, and alert you when the trend changes. The green colour represents a bullish trend (prices are going up), the red colour represents a bearish trend (prices are going down), and silver represents a neutral trend (prices are relatively stable). The script calculates these trends based on the relative price levels and their moving averages.
Below is a breakdown of the script so you can better understand how these trends are defined.
Function f_p(_length, price) : This function calculates the price relative to its highest and lowest point over the given `_length` of time. This calculation is normalized by multiplying it by 100, giving us a percentage-like measure.
User Inputs : The length of the period (default 12), you can choose to show or hide bar colours (default is true).
Variables cycle_avg, cycle_counter, cycle_count, cycle_trend, cycle_col : These variables are used to calculate the trend cycles. The `cycle_avg` is the average trend cycle, `cycle_counter` keeps track of the current trend cycle, `cycle_count` counts the total number of cycles, `cycle_trend` keeps track of the direction of the cycle (1 for up, -1 for down), and `cycle_col` defines the colour of the current cycle.
Variables ph, pl, avg, mean : These variables calculate the price level relative to the highest and lowest prices (`ph` and `pl`), the average of these two levels (`avg`), and the cumulative average of the price level (`mean`).
Conditionals for cycle trend : The if-statements are checking whether the price level has reached a trend extreme and then updating the trend cycle, colour, count, and average accordingly.
Variable col and bar color : The variable `col` is used to define the colour of the bars based on the average price level. If the `show_barcolor` is true, the colour is determined based on the `avg` value.
Alert Conditions : These are conditions that will send alerts to the user when the trend changes. Specifically, the alerts occur when the colour changes from non-green to green (bull trend), from non-red to red (bear trend), or from non-silver to silver (no trend).
