Moving Average Crossover MonitorMoving Average Crossover Monitor: Gain Insight into Market Trends
The Moving Average Crossover Monitor is a specialized tool crafted for traders seeking to understand and predict market trends more effectively. This indicator's primary focus lies in analyzing consecutive candle movements above or below specified moving averages and providing predictive estimates based on historical data.
Key Features:
1. Consecutive Candle Tracking: The indicator meticulously counts and tracks the number of consecutive candles that close above or below a selected moving average (MA1). This tracking offers a tangible measure of trend persistence over time.
2. Historical Analysis for Future Prediction: By analyzing past trends, the indicator provides insights into potential future movements. It estimates the likelihood of upcoming candles continuing above or below the moving average based on historical patterns.
3. Dynamic Visualization: Moving averages (SMA, WMA, EMA) are dynamically plotted on the chart, clearly displaying crossover points and trend transitions.
How It Works:
1. Moving Average Calculation: Select your preferred moving average type (SMA, WMA, EMA) and define short and long periods. The indicator computes two moving averages (MA1 and MA2) based on these parameters.
2. Consecutive Candle Analysis:
- Above MA1: Tracks and counts consecutive candles closing above MA1, indicating potential bullish momentum.
- Below MA1: Tracks and counts consecutive candles closing below MA1, suggesting potential bearish sentiment.
3. Future Trend Prediction: Based on historical data of consecutive candle movements, the indicator estimates the likelihood of the next candle continuing in the same direction (above or below MA1).
Advantages for Traders:
1. Quantitative Insights: Use numerical data on consecutive candles to gauge trend strength and durability.
2. Predictive Analytics: Leverage historical patterns to anticipate future market movements and adjust trading strategies accordingly.
3. Decision Support Tool: Gain clarity on trend transitions, empowering timely and informed trading decisions.
Disclaimer:
This indicator is provided for educational purposes only and should not be considered as financial advice. Trading involves risks, and past performance is not indicative of future results. Traders should conduct their own analysis and exercise caution when making trading decisions based on any indicator or tool. Always consider risk management strategies and consult with a qualified financial advisor if needed.
在腳本中搜尋"moving average crossover"
Moving Average Crossover Histogram IndicatorA modified version of the MACD indicator. As its name suggests, this is a moving average crossover indicator but the difference in values between moving averages is represented by a histogram. It subtracts the value of a fast MA and slow MA then the result is represented in a histogram which makes it easier for you to identify and visualize every moving average crossover.
If you use moving average crossover as your buy/sell signal this indicator is for you.
You could use this indicator instead of using two moving averages on your main chart. Really convenient, easy to use, and make your chart clutter-free. You could set the fast and slow MA values also the moving average types according to your trading style.
Hope you like it. :)
Moving Average Crossover Strategy by AI and Anton ThomasDescription:
Indicator Name: Moving Average Crossover Strategy
Overview:
The "Moving Average Crossover Strategy" is a technical analysis indicator that combines moving averages and the Relative Strength Index (RSI) to identify potential buy and sell signals. It aims to capture trend reversals and momentum shifts in the market.
Key Components:
Moving Averages:
The indicator calculates two moving averages:
Fast Moving Average (10-period SMA): This average reacts more quickly to price changes.
Slow Moving Average (30-period SMA): This average provides a smoother trend indication.
A bullish signal occurs when the fast moving average crosses above the slow moving average (golden cross), indicating a potential uptrend.
A bearish signal occurs when the fast moving average crosses below the slow moving average (death cross), indicating a potential downtrend.
Relative Strength Index (RSI):
The RSI measures the strength and momentum of price movements on a scale of 0 to 100.
A reading above 70 indicates overbought conditions, suggesting a potential reversal to the downside.
A reading below 30 indicates oversold conditions, suggesting a potential reversal to the upside.
Trading Signals:
Buy Signal:
Generated when the fast moving average crosses above the slow moving average (longCondition).
Additionally, a buy signal is identified when the RSI is oversold (below 30) and then crosses above the oversold threshold.
The indicator plots a green triangle above the bar to indicate the buy signal.
Sell Signal:
Generated when the fast moving average crosses below the slow moving average (shortCondition).
Additionally, a sell signal is identified when the RSI is overbought (above 70) and then crosses below the overbought threshold.
The indicator plots a red triangle below the bar to indicate the sell signal.
Additional Features:
Bullish Engulfing Pattern:
Detects bullish engulfing candlestick patterns, indicating potential bullish reversals.
Plots a green triangle below the bar to highlight the bullish engulfing pattern.
Bearish Engulfing Pattern:
Detects bearish engulfing candlestick patterns, indicating potential bearish reversals.
Plots a red triangle above the bar to highlight the bearish engulfing pattern.
Oversold and Overbought Levels:
Plots horizontal dashed lines at 30 (oversold) and 70 (overbought) on the RSI indicator.
Usage:
Traders can use this indicator to identify potential entry and exit points in the market based on moving average crossovers, RSI conditions, and candlestick patterns. It provides a comprehensive view of trend direction and momentum.
Considerations:
Always confirm signals with other technical analysis tools and market conditions.
Implement proper risk management strategies to minimize potential losses.
Example:
A buy signal is generated when the fast moving average crosses above the slow moving average, and the RSI is below 30 but crosses above it.
A sell signal is generated when the fast moving average crosses below the slow moving average, and the RSI is above 70 but crosses below it.
If you find this indicator profitable, please support by gifting some USDT (BSC NETWORK): 0x2c5c2dd39bbcc9453dd1428d881da37dacd9bf47
or just a thank you email at antonthomasfull(at)gmail.com
Moving Average Crossover with Shading Signals This script uses 3 moving averages (2 simple moving averages and 1 exponential moving average ) to signal long and short opportunities based on moving average crossovers.
A long SMA (Signal SMA2) is used to determine longer term trend. When the EMA crosses above the Slow SMA1 and price is above the Signal SMA2. The space between the moving averages will shade green and the Signal SMA should also be green.
A sell signal occurs when the EMA crosses below the Slow SMA1 and price is below the Signal SMA2. The space between the moving averages will turn red and the Signal SMA should also be red.
A retracement, consolidation, or reversal may be occurring if the shaded color is yellow.
Use the identifying shapes to learn when to open or close positions.
Moving Average CrossoverIt was planned as an addition to Moving Average Smoothness Benchmark and Profitable Moving Average Crossover , but can be used standalone.
Supports 62 types of well-known moving averages and allows full-featured customization.
Supported types of averages and filters:
AEMA , Adaptive Exponential MA (by Vitali Apirine)
AHMA , Ahrens MA (by Richard D. Ahrens)
ALMA , Arnaud Legoux MA (by Arnaud Legoux and Dimitris Kouzis-Loukas)
ALF , Adaptive Laguerre Filter (by John F. Ehlers)
AMA , Adaptive MA (by Vitali Apirine)
ARSI , Adaptive RSI
BAMA , Bryant Adaptive MA (by Michael R. Bryant)
BF2 , Butterworth Filter with 2 poles
BF3 , Butterworth Filter with 3 poles
DEMA , Double Exponential MA (by Patrick G. Mulloy)
DWMA , Double Weighted (Linear) MA
EDCF , Ehlers Distance Coefficient Filter (by John F. Ehlers)
EDSMA , Ehlers Deviation-Scaled MA (by John F. Ehlers)
EHMA , Exponential Hull MA
EMA , Exponential MA
EVWMA , Elastic Volume Weighted MA (by Christian P. Fries)
FRAMA , Fractal Adaptive MA (by John F. Ehlers)
GF1 , Gaussian Filter with 1 pole
GF2 , Gaussian Filter with 2 poles
GF3 , Gaussian Filter with 3 poles
GF4 , Gaussian Filter with 4 poles
HFSMA , Hampel Filter on Simple Moving Average
HFEMA , Hampel Filter on Exponential Moving Average
HMA , Hull MA (by Alan Hull)
HWMA , Henderson Weighted MA (by Robert Henderson)
IDWMA , Inverse Distance Weighted MA
IIRF , Infinite Impulse Response Filter (by John F. Ehlers)
JAMA , Jurik Adaptive MA (by Mark Jurik)
JMA , Jurik MA (by Mark Jurik, )
KAMA , Kaufman Adaptive MA (by Perry J. Kaufman)
LF , Laguerre Filter (by John F. Ehlers)
LMA , Leo MA (by ProRealCode' user Leo)
LSMA , Least Squares MA (Moving Linear Regression)
MAMA (by John F. Ehlers)
FAMA , Following Adaptive MA (by John F. Ehlers)
MD , McGinley Dynamic (by John R. McGinley)
MHLMA , Middle-High-Low MA (by Vitali Apirine)
MNMA , McNicholl MA (by Dennis McNicholl)
NSMA , Moving Average 3.0 on SMA (by Manfred G. Dürschner)
NEMA , Moving Average 3.0 on EMA (by Manfred G. Dürschner)
NWMA , Moving Average 3.0 on WMA (by Manfred G. Dürschner)
NVWMA , Moving Average 3.0 on VWMA (by Manfred G. Dürschner)
PEMA , Pentuple Exponential MA (by Bruno Pio)
PWMA , Parabolic Weighted MA
QMA , Quick MA (by John McCormick)
QEMA , Quadruple Exponential MA (by Bruno Pio)
REMA , Regularized Exponential MA (by Chris Satchwell)
RMA , Running MA (by J. Welles Wilder)
RMF , Recursive Median Filter (by John F. Ehlers )
RMTA , Recursive Moving Trend Average (by Dennis Meyers)
SHMMA , Sharp Modified MA (by Joe Sharp)
SMA , Simple MA
SSF2 , Super Smoother Filter with 2 poles (by John F. Ehlers)
SSF3 , Super Smoother Filter with 3 poles (by John F. Ehlers)
SWMA , Sine Weighted MA
TEMA , Triple Exponential MA (by Patrick G. Mulloy)
TMA , Triangular MA (generalized by John F. Ehlers)
T3 , (by Tim Tillson)
VIDYA , Variable Index Dynamic Average (by Tushar S. Chande)
VWMA , Volume Weighted MA (by Buff P. Dormeier)
WMA , Weighted (Linear) MA
ZLEMA , Zero Lag Exponential MA (by John F. Ehlers and Ric Way)
TeoTrading 38 - Moving Average Crossover - Long-ShortWith this indicator you can obtain the percent of gain / loss of each trade based on Moving Average Crossover.
Prints different types of moving Average: SMA , EMA , WMA and VWMA.
It is usefull to view in only few minutes differents crossovers.
The crossver´s in LONG Trades are indicated with:
"P": Positive Crossover. Open a Long Trade.
Green: Negative Crossover with gain. Close the Long Trade.
Red: Negative Crossover with Loss. Close the Long Trade.
The crossver´s in SHORT Trades are indicated with:
"N": Negative Crossover. Open a Short Trade.
Green: Positive Crossover with gain. Close the Short Trade.
Red: Positive Crossover with Loss. Close the Short Trade.
The Percents of gain and loss are indicated in the Labels.
Input Parameters:
Type of Trade: Long/Short.
Type_: Type of Moving Average.
PrintPrice: Enable open value print.
Fast: Fast Moving Average.
Slow: Slow Moving Average.
This indicator does not generate recommendations to buy or to sell. It was designed ONLY for educational purposes.
Relative Strength Moving Average CrossoverA popular technical analysis strategy is the moving average crossover. This indicator combines a crossover with the Relative Strength Line, created by William O’Neil. The RS Line is a tool used to compare the price action of a particular stock to that of an index, with the S&P 500 being the index preferred by O'Neil.
When one moving average crosses above or below another, that may be a signal of a trend change. For example, when a shorter-term moving average (aka faster moving average) of price moves up and through a longer-term moving average (aka slower moving average), it is likely the price is trending up, this is referred to as a crossover. The opposite can also be a potential signal of a change in the trend. When a shorter-term moving average crosses under a longer-term moving average, the price may be heading down. We refer to this as a negative crossover or crossunder.
This indicator allows configuration of up to two moving averages for the RS Line. Using two moving averages you can quickly identify the direction of the trend and also pinpoint where the faster moving average crosses over or under the slower moving average.
While beta testing this indicator, we performed a study using Bitcoin. In 2021 we’ve seen an increasing correlation of BTC and the S&P 500. This is most likely due to the fact that both crypto and stocks are riskier than other financial assets such as bonds and commodities. When the market is risk-off, both the S&P 500 and Bitcoin tend to sell off together.
For the BTC test case we used two moving averages of the RS Line, 8-EMA and 50-SMA. In the chart that follows you can see a breakdown of how this played out over the last ~2 years. A positive divergence is indicated by the 8-EMA of RS crossing above the 50-SMA, and vice versa for a negative divergence.
Here's another example using TSLA:
Features
■ Configure up to two moving averages for each timeframe.
■ Optional symbols indicate moving average crossovers.
■ Configure custom alerts on crossovers, for any timeframe.
■ Optional moving average cloud makes it easy to identify if slower moving average is above/below faster moving average.
■ Configurable index, defaulting to S&P 500 (SPX).
Acknowledgement
This project is a collaborative effort with @blakedavis17 a Crypto-Equity Analyst. Based on a discussion with Blake about a moving average crossover using the RS Line, we created a simple indicator to explore the concept further. We were very encouraged with the results of backtesting and decided to publish the indicator as we believe it may be a helpful tool for both equity and crypto traders.
Profitable Moving Average CrossoverHi everyone!
Introduction
A popular use for moving averages is to develop simple trading systems based on moving average crossovers. A trading system using two moving averages would give a buy signal when the shorter (faster) moving average advances above the longer (slower) moving average. A sell signal would be given when the shorter moving average crosses below the longer moving average. The speed of the systems and the number of signals generated will depend on the length of the moving averages.
There are many types of averages that are based on different techniques. Each type has its drawbacks and merits. And if we decide to choose a certain type of average for the trading system, then how do we know that our choice is optimal?
What is this tool?
This tool will help you to choose this type to create the most profitable trading system based on crossovers for the specified periods. It backtests pairs of each type throughout the whole instrument's history and shows Net Profit curves as a result. So, the type of the most profitable crossover system will be at the top of list of labels on the chart. (Click on the price scale, point to "Labels" and switch off "No Overlapping Labels" option).
Settings
The main settings are periods for each type pair of fast and slow moving averages.
Additionally, it allows to customize some multi-parametric moving averages such as JMA, ALMA, McGinley Dynamic, Adaptive Laguerre Filter etc.
1st Period (default: 14 )
2nd Period (default: 50 )
1st ALF Median Length (default: 5 )
2nd ALF Median Length (default: 5 )
1st ALMA Offset (default: 0.85 )
1st ALMA Sigma (default: 6 )
2nd ALMA Offset (default: 0.85 )
2nd ALMA Sigma (default: 6 )
1st HF Scaling Factor (default: 3 )
2nd HF Scaling Factor (default: 3 )
1st JMA Phase (default: 50 )
2nd JMA Phase (default: 50 )
1st MD Constant (default: 0.6 )
2nd MD Constant (default: 0.6 )
1st MHLMA Range (default: 10 )
2nd MHLMA Range (default: 10 )
1st PWMA Power (default: 2 )
2nd PWMA Power (default: 2 )
1st REMA Lambda (default: 0.5 )
2nd REMA Lambda (default: 0.5 )
1st RMF Median Length (default: 5 )
2nd RMF Median Length (default: 5 )
1st T3 Alpha (default: 0.7 )
2nd T3 Alpha (default: 0.7 )
MAMA & FAMA Fast Limit (default: 0.5 )
MAMA & FAMA Slow Limit (default: 0.05 )
Supported types of averages and filters (use short titles to match averages on the chart)
AHMA , Ahrens MA (by Richard D. Ahrens)
ALMA , Arnaud Legoux MA (by Arnaud Legoux and Dimitris Kouzis-Loukas)
ALF , Adaptive Laguerre Filter (by John F. Ehlers)
ARSI , Adaptive RSI
BF2 , Butterworth Filter with 2 poles
BF3 , Butterworth Filter with 3 poles
DEMA , Double Exponential MA (by Patrick G. Mulloy)
DWMA , Double Weighted (Linear) MA
EDCF , Ehlers Distance Coefficient Filter (by John F. Ehlers)
EHMA , Exponential Hull MA
EMA , Exponential MA
EVWMA , Elastic Volume Weighted MA (by Christian P. Fries)
FRAMA , Fractal Adaptive MA (by John F. Ehlers)
GF1 , Gaussian Filter with 1 pole
GF2 , Gaussian Filter with 2 poles
GF3 , Gaussian Filter with 3 poles
GF4 , Gaussian Filter with 4 poles
HFSMA , Hampel Filter on Simple Moving Average
HFEMA , Hampel Filter on Exponential Moving Average
HMA , Hull MA (by Alan Hull)
HWMA , Henderson Weighted MA (by Robert Henderson)
IDWMA , Inverse Distance Weighted MA
IIRF , Infinite Impulse Response Filter (by John F. Ehlers)
JMA , Jurik MA (by Mark Jurik, )
LF , Laguerre Filter (by John F. Ehlers)
LMA , Leo MA (by ProRealCode' user Leo)
LSMA , Least Squares MA (Moving Linear Regression)
MAMA & FAMA , (by John F. Ehlers, special case that used as a benchmark)
MD , McGinley Dynamic (by John R. McGinley)
MHLMA , Middle-High-Low MA (by Vitali Apirine)
PWMA , Parabolic Weighted MA
REMA , Regularized Exponential MA (by Chris Satchwell)
RMA , Running MA (by J. Welles Wilder)
RMF , Recursive Median Filter (by John F. Ehlers)
RMTA , Recursive Moving Trend Average (by Dennis Meyers)
SHMMA , Sharp Modified MA (by Joe Sharp)
SMA , Simple MA
SSF2 , Super Smoother Filter with 2 poles (by John F. Ehlers)
SSF3 , Super Smoother Filter with 3 poles (by John F. Ehlers)
SWMA , Sine Weighted MA
TEMA , Triple Exponential MA (by Patrick G. Mulloy)
TMA , Triangular MA (generalized by John F. Ehlers)
T3 , (by Tim Tillson)
VIDYA , Variable Index Dynamic Average (by Tushar S. Chande)
VWMA , Volume Weighted MA (by Buff P. Dormeier)
WMA , Weighted (Linear) MA
ZLEMA , Zero Lag Exponential MA (by John F. Ehlers and Ric Way)
NOTE : The results may vary on different tickers and timeframes.
If you see the preview result it doesn't mean that these crossovers will be profitable on other instruments and timeframes. This is a normal situation because time series and their characteristics differ.
I know that because I tested this tool before publishing.
NOTE 2 : You can use this tool by yourself and experiment with it, or you can order a study and I will share the spreadsheet that contains results with you.
Good luck!
Inverted EMAThe concept of an inverted Exponential Moving Average (EMA) isn't commonly used in traditional technical analysis or trading strategies. Inverting the EMA essentially means taking the reciprocal of the EMA values. While it may not have widespread use or recognition, here are some potential considerations or interpretations for the inverted EMA:
1. **Inverse Trend Indicator:**
- Inverting the EMA might be considered as an alternative approach to trend analysis. When the inverted EMA is rising, it could suggest a potential bearish trend, and when it is falling, it might indicate a bullish trend. Traders might explore using this as a contrarian or unconventional trend indicator.
2. **Volatility Indicator:**
- The inverted EMA might be used as a measure of volatility. When the values are fluctuating rapidly, it could imply increased volatility in the underlying asset. This could be useful for traders who are interested in gauging market dynamics.
3. **Divergence Analysis:**
- Traders may explore divergences between price and the inverted EMA. For instance, if prices are making new highs, but the inverted EMA is not, it could signal potential weakness or divergence in the bullish trend.
4. **Inverse Moving Average Crossovers:**
- In the context of moving average crossovers, traders usually look for crossovers between shorter and longer EMAs as potential signals. Inverting this concept, crossovers between inverted short-term and long-term EMAs might be explored for unconventional trading signals.
5. **Systematic Exploration:**
- Traders and researchers sometimes experiment with unconventional indicators to discover new patterns or behaviors in the market. The inverted EMA could be part of systematic exploration to uncover unique insights that traditional indicators might not reveal.
It's important to note that the interpretation and use of the inverted EMA depend on the trader's strategy, risk tolerance, and specific market conditions. Traders should thoroughly backtest any strategy involving unconventional indicators and use them cautiously in live trading. Additionally, the effectiveness of the inverted EMA may vary across different financial instruments and timeframes.
Triple Moving Average CrossoverBelow is the Pine Script code for TradingView that creates an indicator with three user-defined moving averages (with default periods of 10, 50, and 100) and labels for buy and sell signals at key crossovers. Additionally, it creates a label if the price increases by 100 points from the buy entry or decreases by 100 points from the sell entry, with the label saying "+100".
Explanation:
Indicator Definition: indicator("Triple Moving Average Crossover", overlay=true) defines the script as an indicator that overlays on the chart.
User Inputs: input.int functions allow users to define the periods for the short, middle, and long moving averages with defaults of 10, 50, and 100, respectively.
Moving Averages Calculation: The ta.sma function calculates the simple moving averages for the specified periods.
Plotting Moving Averages: plot functions plot the short, middle, and long moving averages on the chart with blue, orange, and red colors.
Crossover Detection: ta.crossover and ta.crossunder functions detect when the short moving average crosses above or below the middle moving average and when the middle moving average crosses above or below the long moving average.
Entry Price Tracking: Variables buyEntryPrice and sellEntryPrice store the buy and sell entry prices. These prices are updated whenever a bullish or bearish crossover occurs.
100 Points Move Detection: buyTargetReached checks if the current price has increased by 100 points from the buy entry price. sellTargetReached checks if the current price has decreased by 100 points from the sell entry price.
Plotting Labels: plotshape functions plot the buy and sell labels at the crossovers and the +100 labels when the target moves are reached. The labels are displayed in white and green colors.
On Chart Anticipated Moving Average Crossover IndicatorIntroducing the on chart moving average crossover indicator.
This is my On Chart Pinescript implementation of the Anticipated Simple Moving Average Crossover idea.
This indicator plots 6 user defined moving averages.
It also plots the 5 price levels required on the next close to cross a user selected moving average with the 5 other user defined moving averages
It also gives signals of anticipated moving average crosses as arrows on chart and also as tradingview alerts with a very high degree of accuracy
Much respect to the creator of the original idea Mr. Dimitris Tsokakis
Moving Averages
A moving average simplifies price data by smoothing it out by averaging closing prices and creating one flowing line which makes seeing the trend easier.
Moving averages can work well in strong trending conditions, but poorly in choppy or ranging conditions.
Adjusting the time frame can remedy this problem temporarily, although at some point, these issues are likely to occur regardless of the time frame chosen for the moving average(s).
While Exponential moving averages react quicker to price changes than simple moving averages. In some cases, this may be good, and in others, it may cause false signals.
Moving averages with a shorter look back period (20 days, for example) will also respond quicker to price changes than an average with a longer look back period (200 days).
Trading Strategies — Moving Average Crossovers
Moving average crossovers are a popular strategy for both entries and exits. MAs can also highlight areas of potential support or resistance.
The first type is a price crossover, which is when the price crosses above or below a moving average to signal a potential change in trend.
Another strategy is to apply two moving averages to a chart: one longer and one shorter.
When the shorter-term MA crosses above the longer-term MA, it's a buy signal, as it indicates that the trend is shifting up. This is known as a "golden cross."
Meanwhile, when the shorter-term MA crosses below the longer-term MA, it's a sell signal, as it indicates that the trend is shifting down. This is known as a "dead/death cross."
MA and MA Cross Strategy Disadvantages
Moving averages are calculated based on historical data, and while this may appear predictive nothing about the calculation is predictive in nature.
Moving averages are always based on historical data and simply show the average price over a certain time period.
Therefore, results using moving averages can be quite random.
At times, the market seems to respect MA support/resistance and trade signals, and at other times, it shows these indicators no respect.
One major problem is that, if the price action becomes choppy, the price may swing back and forth, generating multiple trend reversal or trade signals.
When this occurs, it's best to step aside or utilize another indicator to help clarify the trend.
The same thing can occur with MA crossovers when the MAs get "tangled up" for a period of time during periods of consolidation, triggering multiple losing trades.
Ensure you use a robust risk management system to avoid getting "Chopped Up" or "Whip Sawed" during these periods.
Anticipated Simple Moving Average Crossover IndicatorIntroducing the Anticipated Simple Moving Average Crossover Indicator
This is my Pinescript implementation of the Anticipated Simple Moving Average Crossover Indicator
Much respect to the original creator of this idea Dimitris Tsokakis
This indicator removes one bar of lag from simple moving average crossover signals with a high degree of accuracy to give a slight but very real edge.
Moving Averages
A moving average simplifies price data by smoothing it out by averaging closing prices and creating one flowing line which makes seeing the trend easier.
Moving averages can work well in strong trending conditions, but poorly in choppy or ranging conditions.
Adjusting the time frame can remedy this problem temporarily, although at some point, these issues are likely to occur regardless of the time frame chosen for the moving average(s).
While Exponential moving averages react quicker to price changes than simple moving averages. In some cases, this may be good, and in others, it may cause false signals.
Moving averages with a shorter look back period (20 days, for example) will also respond quicker to price changes than an average with a longer look back period (200 days).
Trading Strategies — Moving Average Crossovers
Moving average crossovers are a popular strategy for both entries and exits. MAs can also highlight areas of potential support or resistance.
The first type is a price crossover, which is when the price crosses above or below a moving average to signal a potential change in trend.
Another strategy is to apply two moving averages to a chart: one longer and one shorter.
When the shorter-term MA crosses above the longer-term MA, it's a buy signal, as it indicates that the trend is shifting up. This is known as a "golden cross."
Meanwhile, when the shorter-term MA crosses below the longer-term MA, it's a sell signal, as it indicates that the trend is shifting down. This is known as a "dead/death cross."
MA and MA Cross Strategy Disadvantages
Moving averages are calculated based on historical data, and while this may appear predictive nothing about the calculation is predictive in nature.
Moving averages are always based on historical data and simply show the average price over a certain time period.
Therefore, results using moving averages can be quite random.
At times, the market seems to respect MA support/resistance and trade signals, and at other times, it shows these indicators no respect.
One major problem is that, if the price action becomes choppy, the price may swing back and forth, generating multiple trend reversal or trade signals.
When this occurs, it's best to step aside or utilize another indicator to help clarify the trend.
The same thing can occur with MA crossovers when the MAs get "tangled up" for a period of time during periods of consolidation, triggering multiple losing trades.
Ensure you use a robust risk management system to avoid getting "Chopped Up" or "Whip Sawed" during these periods.
CT Moving Average Crossover IndicatorMoving Average Crossover Indicator
Here I present a moving average indicator with 9 user definable moving averages from which up to 5 pairs can be selected to show what prices would need to be closed at on the current bar to cross each individual pair.
I have put much emphasis here on simplicity of setting the parameters of the moving averages, selecting the crossover pairs and on the clarity of the displayed information in the optional “Moving Average Crossover Level” Information Box.
What Is a Moving Average (MA)?
According to Investopedia - “In statistics, a moving average is a calculation used to analyze data points by creating a series of averages of different subsets of the full data set.
In finance, a moving average (MA) is a stock indicator that is commonly used in technical analysis. The reason for calculating the moving average of a stock is to help smooth out the price data by creating a constantly updated average price.
By calculating the moving average, the impacts of random, short-term fluctuations on the price of a stock over a specified time-frame are mitigated.”
The user can set the color, type (SMA/EMA) and length of each of the 9 moving averages.
Then the user may choose 5 pairs of moving averages from the set of 9.
The script will then calculate the price needed to be crossed by the close of the current bar in order to crossover each of the user defined pairs and outputs the results as optional lineplots and/or an Infobox which shows the relevant information in a very clear way.
The user may switch the moving averages, crossover lineplots and infobox on and off easily with one click boxes in the settings menu.
The number of decimal places shown in the Infobox can be altered in the settings menu.
If the price required to cross a pair of moving averages is zero or less, the crossover level will display “Impossible” and the plots will plot at zero. (this helps ameliorate chart auto-focus issues)
Quoting a variety of online resources …….
Understanding Moving Averages (MA)
Moving averages are a simple, technical analysis tool. Moving averages are usually calculated to identify the trend direction of a stock or to determine its support and resistance levels. It is a trend-following—or lagging—indicator because it is based on past prices.
The longer the time period for the moving average, the greater the lag. So, a 200-day moving average will have a much greater degree of lag than a 20-day MA because it contains prices for the past 200 days. The 50-day and 200-day moving average figures for stocks are widely followed by investors and traders and are considered to be important trading signals.
Moving averages are a totally customizable indicator, which means that an investor can freely choose whatever time frame they want when calculating an average. The most common time periods used in moving averages are 15, 20, 30, 50, 100, and 200 days. The shorter the time span used to create the average, the more sensitive it will be to price changes. The longer the time span, the less sensitive the average will be.
Investors may choose different time periods of varying lengths to calculate moving averages based on their trading objectives. Shorter moving averages are typically used for short-term trading, while longer-term moving averages are more suited for long-term investors.
There is no correct time frame to use when setting up your moving averages. The best way to figure out which one works best for you is to experiment with a number of different time periods until you find one that fits your strategy.
Predicting trends in the stock market is no simple process. While it is impossible to predict the future movement of a specific stock, using technical analysis and research can help you make better predictions.
A rising moving average indicates that the security is in an uptrend, while a declining moving average indicates that it is in a downtrend. Similarly, upward momentum is confirmed with a bullish crossover, which occurs when a short-term moving average crosses above a longer-term moving average. Conversely, downward momentum is confirmed with a bearish crossover, which occurs when a short-term moving average crosses below a longer-term moving average.
Types of Moving Averages
Simple Moving Average (SMA)
The simplest form of a moving average, known as a simple moving average (SMA), is calculated by taking the arithmetic mean of a given set of values. In other words, a set of numbers–or prices in the case of financial instruments–are added together and then divided by the number of prices in the set.
Exponential Moving Average (EMA)
The exponential moving average is a type of moving average that gives more weight to recent prices in an attempt to make it more responsive to new information.
To calculate an EMA, you must first compute the simple moving average (SMA) over a particular time period. Next, you must calculate the multiplier for weighting the EMA (referred to as the "smoothing factor"), which typically follows the formula: 2/(selected time period + 1). So, for a 20-day moving average, the multiplier would be 2/(20+1)= 0.0952. Then you use the smoothing factor combined with the previous EMA to arrive at the current value.
The EMA thus gives a higher weighting to recent prices, while the SMA assigns equal weighting to all values.
RSI Moving Average CrossoversThis script is an improved version of the RSI indicator, using a moving average on the RSI itself, as well as two other moving averages used to determine the current trend.
A small screener indicating the current movement is displayed in the bottom-left zone of the chart: trend (Bullish/Bearish/Uncertain) and status (Impulse or Correction)
Trends are simply based on moving averages crossovers, coupled to the fact that the current candle closes above the fast MA in a bull trend, and under the fast MA in a bear trend. In other cases, the trend and the movement are considered as "Uncertain" by the indicator.
Options
Various types of moving averages for the RSI and trend MA
Show/Hide crossovers between the RSI and its MA
Color the RSI normal zone with the current trend/movement colors
Show/Hide the screener indicating the current movement
Defaults Parameters
Fast MA 20
Slow MA 50
MA source: Close
RSI Length 14
RSI MA: SMMA (RMA)
RSI MA Length: 20
Don't hesitate to suggest any idea which could improve this indicator.
Simple Moving Average CrossoverThis Pine Script is a TradingView script for creating a technical analysis indicator known as a Simple Moving Average Crossover (SMAC). The script visualizes two moving averages on a chart and provides buy and sell signals based on the crossover of these moving averages.
Here's a breakdown of the script:
Input Parameters:
fastLength: The length of the fast/simple moving average.
slowLength: The length of the slow/simple moving average.
Moving Averages Calculation:
fastMA: Calculates the simple moving average with a length of fastLength using the closing prices.
slowMA: Calculates the simple moving average with a length of slowLength using the closing prices.
Plotting:
Plots the fast and slow moving averages on the chart using different colors.
Buy and Sell Signals:
buySignal: Generates a boolean series indicating a buy signal when the fast moving average crosses above the slow moving average.
sellSignal: Generates a boolean series indicating a sell signal when the fast moving average crosses below the slow moving average.
Plotting Signals:
Plots green triangle-up shapes below price bars for buy signals.
Plots red triangle-down shapes above price bars for sell signals.
In summary, this script helps traders visualize potential trend reversals by identifying points where a shorter-term moving average crosses above (buy signal) or below (sell signal) a longer-term moving average. These crossover signals are often used in trend-following strategies to capture potential changes in market direction. Traders can customize the script by adjusting the input parameters to suit their trading preferences.
Triple Colored Least Squares Moving Average + Crossover AlertsThis script is forked from the ‘ Double Colored Least Squares Moving Average + Crossover Alerts ‘ from @IronKnightmare.
First release & notes : 2021-11-03.
Overview:
The Least Squares Moving Average is used mainly as a crossover signal to identify bullish or bearish trends. When a shorter duration line cross a longer one a trend can be identified. When multiple lines or the price action cross a longterm trend the confirmation can be further validated. Tradingview contains already some indicators with 1 or two LSMA trendlines that can be configured and toggled.
The original script that I forked had two LSMA lines that could be plotted with other valuable functions, I added a third for further confirmation as some trading systems will use three lines or some combination of those for validation.
Usage:
In inputs
- You will see LSMA 1, LSMA 2 & LSMA 3. The default values are 40, 100 & 400 representing the number of periods plotted by that line : fast, medium and slow changing trendlines will be plotted. The offset value and source are standard for most scripts.
In Style
- You can toggle LSMA 1, 2 or 3 and any combination of those. There are much more possibilities this way.
- For each LSMA, Color 0 & Color 1 are for coloring the slope of the trendline,
- Color 0 for rising slope,
- Color 1 for descending slope.
- The script will automatically color the rise or fall of the trendline accordingly. You can also set one identical color in both slopes for one unique color.
- The ‘ Long Crossover 1 on 2 ’ is a signal for when the LSMA 1 cross over the LSMA 2, usually a shorter periods trendline, more volatile, climbing over the medium term one. A Signal will be traced on the chart at that crossing, you can configure this. The ‘Short Crossover 1 on 2’ is when the LSMA 1 cross under the LSMA 2, a signal will be traced on the chart accordingly.
- The Long Crossover 1 on 3 & Short Crossover 1 on 3 act on the same principle, although the crossing of the fast LSMA on the long / slow LSMA are used. Both can be toggled.
- The ‘ Background Coloring Line 1 : 0-Neutral, 1-Up, 2-Down ’ is an optional background coloring for the LSMA1 line. This can provide additional information at a quick glance, especially if you combine the two other lines backgrounds, the partial transparency will compound.
Ultimate Moving Average Crossover Indicator by SAMQUANT📈 Ultimate Moving Average Crossover Indicator | All-in-One MA Strategy
Unlock the power of multiple moving averages in one versatile indicator designed to give you clear, actionable signals in any market condition.
📌 Key Features:
- Supports **all major moving averages**:
- **SMA, EMA, WMA, HMA, RMA, DEMA, TEMA**, and more.
- Each MA is **fully customizable** with different lengths and types for ultimate flexibility.
- **Binary Long/Short signals** based on crossover logic—perfect for alerts, strategies, or discretionary trading.
- **Dynamic background coloring**:
- **Green** for bullish trends
- **Red** for bearish trends
Quickly gauge market direction at a glance.
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🚀 Why Use This Indicator?
✅ Combines the strength of all major MA types
✅ Customizable to fit any trading style—scalping, swing, or trend following
✅ Built-in alerts ready for your next trade
✅ Visually intuitive with built-in signal clarity
✅ Excellent tool for **confluence-based** strategies
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Great trades start with great tools. Clarity, precision, and flexibility—this indicator brings it all to your charts. Trade smarter, not harder.
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> ⚠️ **Disclaimer:**
This script is intended for **educational and informational purposes only**. It does not constitute financial advice. Past performance is not indicative of future results. Always practice sound risk management and test strategies thoroughly before using real capital.
Custom Profitable Moving Average CrossoverA custom version of Profitable Moving Average Crossover that shows the last estimations on profit for each crossover type and allows to set date range for analysis.
Indicator420double hull moving average crossover
hull moving average / volume weighted moving average crossover
Red dot = SELL
Green dot = BUY
or
Longest MA color change to green = BUY
Longest MA color change to red = SELL
by SeaSide420
Jurik Moving Average Crossover Strategy [ChuckBanger]The classic moving average crossover strategy does not work well in markets that, instead of trending, tend to frequently reverse within a trading range. The lag between the actual time the market has reversed direction and when the moving average is signalling a trade, the trend is already over and the market is about to go against your position. In this environment, a more appropriate trading strategy is suggested here using an JMA Keltner Channel.
The idea is to create a channel based of support and resistance. When the market breaks out of the channel, and fails to maintain momentum. It is likely the price will fall back toward the center of the channel. This tendency can be exploited in the following manner.
In the chart above, The aqua and maroon (center line) and the blue lines are part of a channel. The middle line is a slow running JMA of the closing prices, with Length = 30 and phase = 0. The upper blue band is constructed by adding 1.5 times of 30-bar ATR (average true range) to the center JMA line and the lower blue band by deducting the same amount. There is a grey line running through the data- That is a fast running JMA with length = 5 and phase = 100 representing the price.
The red dots indicate that the the price is going back in the channel and the market is retracting from a failed upward breakout, and the green dots mark when price is retracting from a failed downward breakout. These are places where one might want to enter the trade. The orange dots indicate where price crosses the center line, a reasonable place to take profit from or even exit the trade.
The center line also shows the up or down movements if the setting is ticked. This feature is useful to use when exit a trade. For example, you enter a long position on a green dot signal and the color is maroon. You can wait for 3-5 candles (depending of markets). And if the color doesn’t change it can be an indication that the price is going lower. Here it is possible to switch to a short possible or the opposite apply if you enter on a red dot.
The parameter use in this study is for demonstrating purposes only. This is to show how you can use JMA. Do not trade with real money without thoroughly test the strategy. And always use stop-losses.
[RS]Moving Average Cross System V0moving average crossover with added functions:
if you want crossover with price set ma1 length to 1, or use as dual ma with both lengths, ability to turn ma's on and off leaving the crossover signals behind, ability to chose ma mode (sma, ema, rma, wma, vwma, swma and alma), ability to chose source (open, high, low, close, hl2, hlc3 or ohlc4).
