Naresh CE with 13 62 crossThank you to Lauris, for sharing knowledge and logic for the EMA cross-over (13/62).
The provided Pine Script is a custom script, which is designed to display Chandelier Exit levels on the price chart and generate buy and sell labels based on specific conditions.
Here's a breakdown of the key components and logic of the Pine Script:
Exponential Moving Averages (EMAs):
ema1: The 13-period Exponential Moving Average (EMA) of the closing price.
ema2: The 62-period Exponential Moving Average (EMA) of the closing price.
EMA Plotting:
The script plots the ema1 (13 EMA) and ema2 (62 EMA) lines on the price chart using the plot() function.
Chandelier Exit Calculation:
The Chandelier Exit values are calculated using the Average True Range (ATR).
The script calculates the atr (Average True Range) using the atr() function with the given length.
longStop is calculated as the highest price of the specified length minus the ATR, and shortStop is calculated as the lowest price plus the ATR.
Directional Indicator (dir):
The dir variable is used to determine the direction of the Chandelier Exit based on the comparison of the current close price with the previous long and short stops.
Buy and Sell Signals:
The script generates buy signals when the Chandelier Exit direction changes from short to long (buySignal).
Similarly, sell signals are generated when the Chandelier Exit direction changes from long to short (sellSignal).
The conditions for buy and sell signals are based on the value of dir and its previous value.
Buy and Sell Labels:
Buy and sell labels are plotted on the chart using plotshape() based on the generated buy and sell signals.
The showLabels input parameter controls whether to display the buy and sell labels.
Highlighting States:
The script fills the chart area with color (green for long, red for short) based on the direction of the Chandelier Exit values.
The highlightState input parameter controls whether to apply this highlighting.
Alerts:
The script includes alert conditions based on the direction change (changeCond), buy signal (buySignal), and sell signal (sellSignal) using the alertcondition() function.
The script aims to help traders identify potential buy and sell signals based on the Chandelier Exit levels derived from the 13 EMA and 62 EMA crossovers. The Chandelier Exit values can serve as dynamic stop-loss levels for long and short positions.
Cari dalam skrip untuk "Exponential Moving Average"
Range Weighted Moving Average (RWMA)The Range Weighted Moving Average (RWMA) :
The Range Weighted Moving Average (RWMA) is a variation of the traditional moving average that incorporates the price range within each period as a weighting factor.
It assigns higher weights to periods with larger price ranges, aiming to provide a moving average that responds more dynamically to changes in price range and volatility.
Compared to a normal Simple Moving Average (SMA) or Exponential Moving Average (EMA), the RWMA offers several potential advantages:
Why do i think its better than Normal SMA , EMA ?
Increased Sensitivity: The RWMA reacts faster to changes in price compared to traditional moving averages. By incorporating the price range, which represents the volatility of each period, the RWMA gives more importance to periods with larger price ranges. This increased sensitivity can help traders identify price movements and trends more quickly.
Adaptive to Volatility: The RWMA adjusts dynamically to changes in market volatility. During periods of high volatility, the RWMA places more weight on those periods, capturing and reflecting the increased price movements. This adaptability allows the RWMA to be responsive to different market conditions and better capture significant price swings.
Filtering Potential: The RWMA can be utilized as a filtering tool in trading strategies. By using the RWMA as a trend indicator or filter, traders can focus on trades that align with the direction indicated by the RWMA. This filtering mechanism can help eliminate trades that go against the prevailing momentum, potentially improving the overall quality of trade entries.
EMA/SMA Cross with LevelsThe EMA/SMA Cross indicator is a valuable trading tool designed to assist traders in identifying potential trend reversals or entry and exit points in the market. By plotting two moving averages, one based on the Exponential Moving Average (EMA) and the other on the Simple Moving Average (SMA), this indicator highlights the points at which these averages cross, signaling a potential change in the market trend. This straightforward yet powerful indicator follows the core principles of technical analysis, allowing traders to visualize key price levels that may influence future price action.
The underlying concept of this indicator revolves around the calculation and comparison of the short-term EMA and the long-term SMA. The EMA is a type of weighted moving average that gives more importance to recent price data, making it more responsive to new information. In contrast, the SMA assigns equal weight to all data points within a specified period, providing a smoother representation of price trends. By comparing these two averages, traders can gain insights into potential shifts in market sentiment and momentum.
When the short-term EMA crosses above the long-term SMA, it signals a possible bullish trend reversal, indicating that the recent price momentum is gaining strength. Conversely, when the short-term EMA crosses below the long-term SMA, it suggests a bearish trend reversal, implying that the recent price momentum is weakening. Traders can use these crossing points as potential entry or exit signals, depending on their trading strategy and risk tolerance.
A unique feature of this indicator is its ability to plot the crossing levels on the chart. When the short-term EMA crosses the long-term SMA, a dashed line is drawn horizontally at the level of the cross, emphasizing the significance of the price level. This line serves as a reference point for traders, helping them to identify potential support or resistance levels that may influence future price movements.
By plotting the crossing levels, the EMA/SMA Cross indicator offers traders an additional layer of information that can be used in their decision-making process. These levels can act as crucial points for stop-loss or take-profit orders, depending on the trader's strategy and risk tolerance. Additionally, they can serve as a basis for further technical analysis, such as the identification of chart patterns or the application of other technical indicators.
This indicator works best with trading methods that focus on capturing price reversals or breakouts. It is particularly useful for traders who employ trend-following or momentum-based strategies, as it helps them identify the optimal moments to enter or exit a trade. However, it's important to note that the EMA/SMA Cross indicator should be used in conjunction with other technical analysis tools and an understanding of the overall market context to make informed trading decisions.
When using the EMA/SMA Cross indicator on TradingView, users can customize the time frame, source, and length for both the short-term EMA and long-term SMA, as well as the number of recent crossing lines displayed on the chart. This flexibility allows traders to tailor the indicator to their specific trading style and preferences.
In summary, the EMA/SMA Cross indicator is an essential tool for traders looking to identify potential trend reversals or entry and exit points in the market. By comparing the short-term EMA and long-term SMA, this indicator provides valuable insights into shifts in market sentiment and momentum. It is best suited for trend-following and momentum-based trading strategies and should be used in combination with other technical analysis tools for optimal results.
BB and KC StrategyThis script is designed as a TradingView strategy that uses Bollinger Bands (BB) and Keltner Channels (KC) as the primary indicators for generating trade signals. It aims to catch potential market trends by comparing the movements of these two popular volatility measures.
Key aspects of this strategy:
1. **Bollinger Bands and Keltner Channels:** Both are volatility-based indicators. The Bollinger Bands consist of a middle band (simple moving average) and two outer bands calculated based on standard deviation, which adjusts itself to market conditions. Keltner Channels are a set of bands placed above and below an exponential moving average of the price. The distance between the bands is calculated based on the Average True Range (ATR), a measure of price volatility.
2. **Entry Signals:** The strategy enters a long position when the upper KC line crosses above the upper BB line and the volume is above its moving average. Conversely, it enters a short position when the lower KC line crosses below the lower BB line and the volume is above its moving average.
3. **Exit Signals:** The strategy exits a position under two conditions. First, if the trade has been open for a certain number of bars defined by the user (default 20 bars). Second, a stop loss and trailing stop are in place to limit potential losses and lock in profits as the price moves favorably. The stop loss is set at a percentage of the entry price (default 1.5% for long and -1.5% for short), and the trailing stop is also a percentage of the entry price (default 2%).
4. **Trade Quantity:** The script allows specifying the investment amount for each trade, set to a default of 1000 currency units.
Remember, this is a strategy script, which means it is used for backtesting and not for real-time signals or live trading. It is also recommended that it is used as a tool to aid your trading, not as a standalone system. As with any strategy, it should be tested over different market conditions and used in conjunction with other aspects of technical and fundamental analysis to ensure robustness and effectiveness.
RSI Exponential Smoothing (Expo)█ Background information
The Relative Strength Index (RSI) and the Exponential Moving Average (EMA) are two popular indicators. Traders use these indicators to understand market trends and predict future price changes. However, traders often wonder which indicator is better: RSI or EMA.
What if these indicators give similar results? To find out, we wanted to study the relationship between RSI and EMA. We focused on a hypothesis: when the RSI goes above 50, it might be similar to the price crossing above a certain length of EMA. Similarly, when the RSI goes below 50, it might be similar to the price crossing below a certain length of EMA.
Our goal was simple: to figure out if there is any connection between RSI and EMA.
Conclusion: Yes, it seems that there is a correlation between RSI and EMA, and this indicator clearly displays that relationship. Read more about the study here:
█ Overview of the indicator
The RSI Exponential Smoothing indicator displays RSI levels with clear overbought and oversold zones, shown as easy-to-understand moving averages, and the RSI 50 line as an EMA. Another excellent feature is the added FIB levels. To activate, open the settings and click on "FIB Bands." These levels act as short-term support and resistance levels which can be used for scalping.
█ Benefits of using this indicator instead of regular RSI
The findings about the Relative Strength Index (RSI) and the Exponential Moving Average (EMA) highlight that both indicators are equally accurate (when it comes to crossings), meaning traders can choose either one without compromising accuracy. This empowers traders to pick the indicator that suits their personal preferences and trading style.
█ How it works
Crossings over/under the value of 50
The EMA line in the indicator acts as the corresponding 50 line in the RSI. When the RSI crosses the value 50 equals when Close crosses the EMA line.
Bouncess from the value 50
In this example, we can see that the EMA line on the chart acts as support/resistance equals when RSI rejects the 50 level.
Overbought and Oversold
The indicator comes with overbought and oversold bands equal when RSI becomes overbought or oversold.
█ How to use
This visual representation helps traders to apply RSI strategies directly on the price chart, potentially making RSI trading easier for traders.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
HS,HH,LL,and EMA by: rpalconitHello everyone,
HS,HH,LL, and EMA stands for Hull Suite, Higher High, Lower Low and Exponential Moving Average.
Signal Features:
• Long Position: If the Higher High and Lower Low signals are LL and LH at the SUPPORT LEVEL, plot the Fibonacci Retracement and get retracement from 0.382,0.5 and 0.618 for EP. and your SL should be at 1.1 level of the Fibonacci, target TP should be 1.5 ratio. For confirmations the Hull Suite (HS) should be green color and on or below the Exponential Moving Average (EMA).
• Short Position: If the Higher High and Lower Low signals are HH and HL at the RESISTANCE LEVEL, plot the Fibonacci Retracement and get retracement from 0.382,0.5 and 0.618 for EP. and your SL should be at 1.1 level of the Fibonacci, target TP should be 1.5 ratio. For confirmations the Hull Suite (HS) should be red color and on or above the Exponential Moving Average (EMA).
You can change EMA length in any of your preference. The Default is 50.
Details about the indicator
INPUTS
Time Frame
• Time Frames Chart: You can select your preferred timeframe at the dropdown list. Default is 4H. Aside from Time Fame, I advice not to change anything at input default for better result.
STYLE
• Note: For effective signals results and to minimize noise, you need to uncheck first on the style tab: MHULL, BAR COLOR AND LINES.
Best regards,
ruelpalconit
Moving Averages Ribbon (7 EMAs/SMAs)This Indicator provides a combination which is suitable for visualizing many Simple Moving Averages (SMAs) and Exponential Moving Averages (EMAs). There are 7 possible periods 5,9,20,50,100,200,250. There is a possibility to show only EMAs or only SMAs or both. EMAs have thinner curves by default, to be able to distinguish them from SMAs. Additionally, there are highlighted channels between the MAs of the highs and the MAs of the lows, showing a channel of specific moving averages. It comes with a presetting showing EMAs 5,9,20,50,200 and SMAs 9,20,50,200, while the MA channels are only visible for 9 and 50.
EMAs:
SMAs:
Both
DEMA Supertrend Bands [Misu]█ Indicator based on DEMA (Double Exponential Moving Average) & Supertrend to show Bands .
DEMA attempts to remove the inherent lag associated with Moving Averages by placing more weight on recent values.
Supertrend aims to detect price trends, it's also used to set protective stops.
█ Usages:
Combining Dema to calculate Supertrend results in nice lower and upper bands.
This can be used to identify potential supports and resistances and set protective stops.
█ Parameters:
Length DEMA: Double Ema lenght used to calculate DEMA. Dema is used by Supertrend indicator.
Length Atr: Atr lenght used to calculate Atr. Atr is used by Supertrend indicator.
Band Mult: Used to calculate Supertrend Bands width.
█ Other Applications:
The mid band can be used to filter bad signals in the manner of a more classical Moving Average.
Moving Average Crossover StrategyThe Moving Average Crossover indicator uses 3 moving averages (2 simple moving averages and 1 exponential moving average ) to signal long and short opportunities based on moving average crossovers. This strategy serves as a backtest to that indicator. By taking entry and exit positions based on moving average crossovers, we are able to project profit with this script. You are given the option to select which moving average crossings trigger entry and exit signals. Fast refers to an EMA which should be your shortest MA. Slow refers to the first SMA which will serve as a signal line. Trend refers to a long SMA which will help determine if you should take long positions or short. You can also filter by extra conditions such as minimum volume or RSI. For example, you may have the script trigger a buy signal if the 5ema crosses the 20 sma while RSI reads 60 and sell if it crosses again.
This strategy starts with $100,000 and uses 10% of the account per trade.
Stochastic & MAThis trading system comes from the experience of having a "fast" signal for entry at low prices (such as the stoscastic) and then "following" the stock with a "slower" indicator such as the exponential moving average. Both the input and output signals are filtered.
The use of the trading system only carries out long operations and has been tested on shares and ETFs, including indices, on daily bases (End Of Day).
ENTRY CONDITION: when stochastic's k is higher than d (on the default value of 21 periods) we enter the lower part of the oversold, to which we apply a filter or the confirmation that the closing of the day of the crossing is higher than that of the n -th previous bar (the 2nd previous bar recommended).
Other default settings are k = 6 and d = 4; the oversold level is also customizable (recommended = 25).
EXIT CONDITIONS: once the entry has "gone well", we follow the upward trend of the stock not with a stochastic oscillator - which tends to exit too soon, especially in case of strong trends - but with a simple moving average exponential (by default at 38 periods). Also in this case a filter is added, that is, k must be> to a filter threshold (recommended = 65) which is used to distinguish the decline between a "physiological" tracking. "(k drops" slowly "together with the approach of prices to the moving average) from a more" violent "tracking (prices are below the moving average and k consequently fall" suddenly ", in a few bars).
MONEY MANAGEMENT: 13% stop loss inserted (the physiological level of tracking of the shares is generally max 8-12% so we also consider a 1% margin due to trading). For more volatile stocks, the level can be extended to 20%.
LEVERAGE: the default value is equal to 1, but it is advisable, for simulations on shares, to use higher levers (x2, x3, ...) if you trade the relative CFD or on the index in case of buying and selling of Leveraged ETFs (e.g. LEVMIB which is 2x leveraged ETFs on Italian index).
Trading Made Easy Pressure OscillatorAs always, this is not financial advice and use at your own risk. Trading is risky and can cost you significant sums of money if you are not careful. Make sure you always have a proper entry and exit plan that includes defining your risk before you enter a trade.
Those who have looked at my other indicators know that I am a big fan of Dr. Alexander Elder and John Carter. This is relevant to my trading style and to this indicator in general. While I understand it goes against TradingView rules generally to display other indicators while describing a new one, I need the Bollinger Bands, Bollinger Bands Width, and a secondary directional indicator to explain the full power of this indicator. In short, if this is strongly against the rules, I will edit the post as needed.
Those of you who are aware of John Carter are going to know this already, but for those who don’t, an explanation is necessary. John Carter is a relatively famous retail-turned-institutional (sort of) trader. He is the founder of TradetheMarkets, that later turned into SimplerTrading. Him and his company have a series of YouTube videos, he has made appearances on the MoneyShow, TastyTrade, and has authored a couple of books about trading. However, he is probably most famous for his “Squeeze” indicator that was originally launched on Thinkorswim and through his website but has now been incorporated into several trading platforms and even has a few open-source versions available here. In short, the Squeeze indicator looks to identify periods of consolidation and marry that with a momentum oscillator so you can position yourself in a quiet period before a large move. This in my opinion, is one of the best indicators an option trader can have, since options are priced both on time and volatility. To do this, the Squeeze identifies when the Bollinger Bands, a measure of price standard deviation, have contracted inside the Keltner Channels (a measure of the average range of a stock). This highlights something known as “the Squeeze”, when the 2x standard deviations (95% of all likely price movement using data from the past 20 periods) is less than the 1.5x average true range (ATR) of the stock over the same number of periods. These periods are when a stock is resting and in a period of consolidation and is generally followed by another large move once it has rested long enough. The momentum oscillator is used to determine the direction of this next move.
While I think this is one of the best indicators ever made, it is not without its pitfalls. I find that the “Squeeze” periods sometimes take too long to setup (something that was addressed by John and released in a new indicator, the Squeeze Pro, but even that is still slowish) and that the momentum oscillator was also a bit slow. They used a linear regression formula to track momentum, which can lag considerably at times. Collectively, this meant that getting into moves a few candles late was not uncommon or someone solely trading squeeze setups could have missed very good trade opportunities.
To improve on this, I present, the Trading Made Easy Pressure Oscillator. This more accurately identifies when volatility is reducing and the trading range is likely to contract, increasing the “pressure” on the price. This is often marked several candles before a “Squeeze” has started. To identify these ranges, I applied a 21-period exponential moving average to the Bollinger Bands Width indicator (BBW). As mentioned above, the Bollinger Bands measure the 2x standard deviation of price, typically based on a 20-period SMA. When the BBs expand, it marks periods of high volatility, when they contract, conversely, periods of low volatility. Therefore, applying an EMA to the BBW indicator allows us to confidently mark when volatility has slowed down earlier than traditional methods. The second improvement I made was using the Absolute Price oscillator instead of a linear regression-style oscillator. The APO is very similar to a MACD, it measures the difference between two exponential moving averages, here the 8 and 21 (Fibonacci EMAs). However, I find the APO to be smoother than the MACD, yet more reactive than the linear regression-style oscillators to get you into moves earlier.
Uses:
1) Buying before a bigger than expected move. This is especially relevant for options traders since theta decay will often eat away much of our profits while we wait for a large enough price move to offset the time decay. Here, we buy a call option/shares when the momentum oscillator matches the longer-term trend (i.e. the APO crosses over the zero line when price is above the 200-day EMA, and vice versa for puts/shorting the stock). This coincides with Dr. Elder’s Triple Screen Trading System, that we are aligning ourselves with the path of least resistance. We want to do this when price is currently in an increasing pressure situation (i.e. volatility is contracting) to make sure we are buying an option when premium and Implied Volatility is low so we can get a better price and have a better risk to reward ratio. Low volatility is denoted by a purple dot, high volatility a blue dot along the midline of the indicator. A scalper or short-term swing trader may look to exit when the blue dots turn purple signalling a likely end to a move. A longer-term trend trader can look to other exit scenarios, such as a cross of the oscillator below the zero line, signalling to go short, or using a moving average as a trailing stop.
2) Sell premium after a larger than expected move has finished. After a larger than expected move has completed (a series of blue dots is followed by a purple dot), use this time to sell theta-driven options strategies such as straddles, strangles, iron condors, calendar spreads, or iron butterflies, anything that benefits from contracting volatility and stagnating prices. This is useful here since reducing volatility typically means a contraction of prices and the reduced likelihood of a move outside of the normal range.
3) Divergences. This indicator is sensitive enough to highlight divergences. I personally don’t use it as such as I prefer to trend trade vs. reversion trade. Use at your own risk, but they are there.
In summary, this indicator improves upon the famous Squeeze indicator by increasing the speed at which periods of consolidation are marked and trend identification. I hope you enjoy it.
Price Movement Trend By Alireza Phoenix (Logarithmic)hi Traders
This logarithmic indicator shows the price movement trend, which is designed based on logarithmic functions and moving averages.
The Price Movement Trend Display Composed By :
A leading line consisting of the natural logarithm of Running Moving Average with length 60 and Offset 20 , and is displayed in red line.
A signal line consisting of a natural logarithm of an exponential moving average of length 90 , and is displayed in green line.
A price line consisting of the natural logarithm of a simple moving average along 1 whose source is price close , and is displayed in blue line.
A hidden price line consisting of the natural logarithm of a simple moving average along 1 and its source being the highest and lowest average prices , and is displayed in maroon line.
Learning how to get a signal from the price Movement trend indicator:
Moving the signal line and breaking the leading line upwards to form a green cloud is a buy signal.
Moving the signal line and breaking the leading line downwards that forms a red cloud is a sell signal.
Moving the price line and breaking the trend cloud upward , is a buy signal
Moving the price line and breaking the trend cloud downwards , is a sell signal
My instagram id : @pnxf6
ترجمه فارسی :
سلام تریدرها
این اندیکاتور لگاریتمی ، نمایش دهنده روند حرکتی قیمت است ، که بر اساس توابع لگاریتمی و میانگین های متحرک قیمت طراحی شده است
این اندیکاتور تشکیل شده از :
یک خط پیشرو متشکل از لگاریتم طبیعی متحرک وزنی نمایی مورد استفاده درآر اس آی به طول 60 و انحراف 20 است
یک خط سیگنال متشکل از لگاریتم طبیعی میانگین متحرک نمایی با طول 90
یک خط قیمت که متشکل از لگاریتم طبیعی میانگین متحرک ساده در طول 1 که منبع آن بسته شدن قیمت است.
یک خط قیمت مخفی که متشکل از لگاریتم طبیعی میانگین متحرک ساده در طول 1 و منبع آن میانگین بالاترین و پایین ترین قیمت است
یک فضای ابری مابین خط پیشرو و خط سیگنال که که با "نمایش روند حرکت قیمت" مشخص شده و در رنگ های سبز و قرمز قابل مشاهده میباشد.
آموزش گرفتن سیگنال ازاندیکاتور نمایش روند قیمت :
حرکت خط سیگنال و شکستن خط پیشرو رو به بالا که تشکیل ابر سبز رنگ میدهد یک سیگنال خرید میباشد .
حرکت خط سیگنال و شکستن خط پیشرو رو به پایین که تشکیل ابر قرمز رنگ میدهد یک سیگنال فروش میباشد .
حرکت خط قیمت و شکستن ابر روند حرکت قیمت رو به بالا سیگنال خرید میباشد
حرکت خط قیمت و شکستن ابر روند حرکت قیمت رو به پایین سیگنال فروش میباشد.
Sentiment OscillatorPrice moves when there are more market takers than there are market makers at a certain price (i.e. price moves up when there are more market buys than limit sells and vice versa). The idea of this indicator is to show the ratio between market takers and market makers in a way that is intuitive to technical analysis methods, and hopefully revealing the overall sentiment of the market in doing so. You can use it in the same way you would other oscillators (histogram crossing zero, divergences, etc). The main difference between this and most volume-weighted indicators is that the price is divided by volume instead of multiplied by it, thus giving you a rough idea of how much "effort" it took to move the price. My hypothesis is that when more volume is needed to move the price, that means bulls and bears are not in agreement of what the "fair price" should be for an asset (e.g. if the candle closes only a bit higher than its open but there's a huge spike in volume, that tells you that a majority of the market are starting to think the price is too high and they've started selling).
Methods of Calculation
1. Price Change Per Volume
The main method this indicator uses to reveal market sentiment is by comparing price change to the volume of trades in a bar.
You will see this calculation plotted in its most basic form by ticking the "Show Bar per Bar Change/Volume" box in the inputs dialog. I personally found that the plots were too noisy and cannot be used in real time reliably due to the fact that there is not much volume at the open of a new bar. I decided to leave in the option to use this method, in case you'd like to experiment with it or get a better grasp of how the indicator works.
2. Exponential Moving Averages
In my quest to smooth out the plotted data, I experimented with exponential moving averages. Applying an EMA on the change per volume data did smooth it out a bit, but still left in a lot of noise. So I worked around it by applying the EMA to the price change first, and then dividing it by the EMA of the volume. The term I use for the result of this calculation is "Market Sentiment" (do let me know if you have a better-fitting term for it ;-)), and I have kept it as an option that you can use in the way you would use other oscillators like CMF, OBV, etc. This option is unticked by default.
3. MACD
I left "Market Sentiment" unchecked as the default option because I thought an easier way to use this indicator would be as a momentum indicator like the MACD . So that's what I turned it into! I applied another EMA on the Market Sentiment, added a slower EMA to subtract from the first, and now we have a MACD line. I added a signal line to subtract from the MACD , and the result is plotted as a histogram... ish . I used area instead of columns for plot style so you don't get confused when comparing with a regular MACD indicator, but you can always change it if an actual histogram is more your taste.
The "histogram" is the main gauge of sentiment change momentum and it is easiest to use, that is why it is the only calculation plotted by default.
Methods of Use
As I have mentioned before, you can use this as you would other oscillators.
-The easiest way to use this indicator is with the Momentum histogram, where crosses over 0 indicate increasing bullish sentiment, and crosses below 0 indicate increasing bearish sentiment. You may also spot occasional divergences with the histogram.
-For the Market Sentiment option, the easiest way to use it is to look for divergences.
-And if you use the "Price Change per Volume of Each Bar", well... I honestly don't know. I guess divergences would be apparent towards the close of a bar, but in realtime, I don't recommend you use this. Maybe if you'd like to study the market movement, looking at historical data and comparing price, volume , and Change per Volume of each bar would come in handy in a pseudo-tape-reading kind of way.
Anyway, that's my explanation of this indicator. The default values were tested on BTC/USDT (Binance) 4h with decent results. You'll have to adjust the parameters for different markets and timeframes.
I have published this as a strategy so you can test out how the indicator performs as you're tweaking the parameters.
I'm aware that the code might not be the cleanest as I have only started learning pine (and code in general) for about a month, so any suggestions to improve the script would be appreciated!
Good luck and happy trading :-)
Percentage Distance From Moving AverageThis indicator shows the percentage that an asset price is above or below its 50-period simple moving average.
You can change the 50-period moving average to whatever you'd like in the settings of the indicator.
There are other versions of this indicator that are currently public, but they all use the exponential moving average instead of the simple moving average.
RK's 10 ∴ MA Types Ribbons (Fibonacci, Guppy and others)After some tips in my indicator
RK's 04 - Lots of MA Types Ribbon I Put some time and effort to make it better.
So, I'm sharing with you the results.
This is an up to 10 lines Moving Average Ribbon with an Auto Evaluate Length and a lots of options!!!
Type of Moving Average you can use:
SMA - Simple Moving Average
SMMA - Smoothed Moving Average
EMA - Exponential Moving Average
DEMA - Double Exponential Moving Average
TEMA - Triple Exponential Moving Average
WMA - Weighted Moving Average
HMA - Hull Moving Average
EHMA - Exponential Hull Moving Average
RMA - RSI Moving average
2PSS - Ehlers 2 Pole Super Smoother
3PSS - Ehlers 3 Pole Super Smoother
VWMA - Volume-Weighted Moving Average
ALMA - Arnaud Legoux Moving Average
STMA - Simple Triangular Moving Average
ETMA - Exponential Triangular Moving Average
LSMA - Least Squares Moving Average
ZSMA - Zero-Lag Simple Moving Average
ZEMA - Zero-Lag Exponential Moving Average
COVWMA - Coefficient of Variation Weighted Moving Average
COVWEMA - Coefficient of Variation Weighted Exponential Moving Average
FRAMA - Fractal Adaptive Moving Average
KAMA - Kaufman's Adaptive Moving Average
VIDYA - Variable Index Dynamic Average
If you want to change faster the MA type, in "Moving Average Setup:", Select "🤖 Use numbers to change MA Type", click inside the box in "🤖 Moving Average Type per Number:" and just scroll your mouse wheel. You can check what MA type you are using looking in the info panel label.
There is 4 automatic evaluate length:
Fibonacci Sequence
Arithmetic Progression
Geometric Progression
Guppy Multiple Moving Average (GMMA) without Lengths 03 and 05
And I already put a Manual Length, but I keep it inside the code, so if you want to use different lengths, just change the code, or ask me and I will put as an input.
And attending a request, this indicator can creates alerts when all the colors of the ribbons changes.
Hope you like it!
Any other good idea, just send me.
Moving A. By AndersonGA moving average (MA) is a widely used indicator in technical analysis that helps smooth out price action by filtering out the “noise” from random short-term price fluctuations.
Moving average is a trend-following, or lagging, indicator because it is based on past prices. The most common applications of moving averages are:
to identify the trend direction
to determine support and resistance levels.
The two basic and commonly used moving averages are the simple moving average ( SMA ), which is the arithmetic average of a security over a defined number of time periods, and the exponential moving average ( EMA ), which gives greater weight to more recent prices.
Source; Investopedia
Logarithmic Moving AverageLogarithmically weighted moving average.
Here is how weight is distributed in LMA and RMA (exponential moving average)
As you know, logarithm of 1 is 0... This means the last bar in specified period will be ignored, and the log curve above applies to LMA of 9 bars.
So one bar should be added to the length when calculating the weight.
Result is faster than simple moving average, but a bit slower than linearly weighted moving average.
Baseline - evoPlots the high and low of your chosen moving average.
Options are:
SMA = Simple Moving Average
EMA = Exponential Moving Average
WMA = Weighted Moving Average
HMA = Hull Moving Average
VWMA = Volume Weighted Moving Average
RMA = Exponetial Weighted Moving Average
ALMA = Arnaud Legoux Moving Average
Unbox "Use Current Timeframe" to use chosen timeframe below
I mainly use this to get in and out of the market for futures trading, to reduce fake outs of having just one moving average line.
Let me know if you like it..
Inspired from LazyBear's EMAenvelope :)
General Filter Estimator-An Experiment on Estimating EverythingIntroduction
The last indicators i posted where about estimating the least squares moving average, the task of estimating a filter is a funny one because its always a challenge and it require to be really creative. After the last publication of the 1LC-LSMA , who estimate the lsma with 1 line of code and only 3 functions i felt like i could maybe make something more flexible and less complex with the ability to approximate any filter output. Its possible, but the methods to do so are not something that pinescript can do, we have to use another base for our estimation using coefficients, so i inspired myself from the alpha-beta filter and i started writing the code.
Calculation and The Estimation Coefficients
Simplicity is the key word, its also my signature style, if i want something good it should be simple enough, so my code look like that :
p = length/beta
a = close - nz(b ,close)
b = nz(b ,close) + a/p*gamma
3 line, 2 function, its a good start, we could put everything in one line of code but its easier to see it this way. length control the smoothing amount of the filter, for any filter f(Period) Period should be equal to length and f(Period) = p , it would be inconvenient to have to use a different length period than the one used in the filter we want to estimate (imagine our estimation with length = 50 estimating an ema with period = 100) , this is where the first coefficients beta will be useful, it will allow us to leave length as it is. In general beta will be greater than 1, the greater it will be the less lag the filter will have, this coefficient will be useful to estimate low lagging filters, gamma however is the coefficient who will estimate lagging filters, in general it will range around .
We can get loose easily with those coefficients estimation but i will leave a coefficients table in the code for estimating popular filters, and some comparison below.
Estimating a Simple Moving Average
Of course, the boxcar filter, the running mean, the simple moving average, its an easy filter to use and calculate.
For an SMA use the following coefficients :
beta = 2
gamma = 0.5
Our filter is in red and the moving average in white with both length at 50 (This goes for every comparison we will do)
Its a bit imprecise but its a simple moving average, not the most interesting thing to estimate.
Estimating an Exponential Moving Average
The ema is a great filter because its length times more computing efficient than a simple moving average. For the EMA use the following coefficients :
beta = 3
gamma = 0.4
N.B : The EMA is rougher than the SMA, so it filter less, this is why its faster and closer to the price
Estimating The Hull Moving Average
Its a good filter for technical analysis with tons of use, lets try to estimate it ! For the HMA use the following coefficients :
beta = 4
gamma = 0.85
Looks ok, of course if you find better coefficients i will test them and actualize the coefficient table, i will also put a thank message.
Estimating a LSMA
Of course i was gonna estimate it, but this time this estimation does not have anything a lsma have, no moving average, no standard deviation, no correlation coefficient, lets do it.
For the LSMA use the following coefficients :
beta = 3.5
gamma = 0.9
Its far from being the best estimation, but its more efficient than any other i previously made.
Estimating the Quadratic Least Square Moving Average
I doubted about this one but it can be approximated as well. For the QLSMA use the following coefficients :
beta = 5.25
gamma = 1
Another ok estimate, the estimate filter a bit more than needed but its ok.
Jurik Moving Average
Its far from being a filter that i like and its a bit old. For the comparison i will use the JMA provided by @everget described in this article : c.mql5.com
For the JMA use the following coefficients :
for phase = 0
beta = pow*2 (pow is a parameter in the Jma)
gamma = 0.5
Here length = 50, phase = 0, pow = 5 so beta = 10
Looks pretty good considering the fact that the Jma use an adaptive architecture.
Discussion
I let you the task to judge if the estimation is good or not, my motivation was to estimate such filters using the less amount of calculations as possible, in itself i think that the code is quite elegant like all the codes of IIR filters (IIR Filters = Infinite Impulse Response : Filters using recursion) .
It could be possible to have a better estimate of the coefficients using optimization methods like the gradient descent. This is not feasible in pinescript but i could think about it using python or R.
Coefficients should be dependant of length but this would lead to a massive work, the variation of the estimation using fixed coefficients when using different length periods is just ok if we can allow some errors of precision.
I dont think it should be possible to estimate adaptive filter relying a lot on their adaptive parameter/smoothing constant except by making our coefficients adaptive (gamma could be)
So at the end ? What make a filter truly unique ? From my point of sight the architecture of a filter and the problem he is trying to solve is what make him unique rather than its output result. If you become a signal, hide yourself into noise, then look at the filters trying to find you, what a challenging game, this is why we need filters.
Conclusion
I wanted to give a simple filter estimator relying on two coefficients in order to estimate both lagging and low-lagging filters. I will try to give more precise estimate and update the indicator with new coefficients.
Thanks for reading !
Madrid Trend SpotterThis study shows a pair of colored moving averages filled with the color of the direction of the trend.
This study calculates the moving averages with standard or exponential M.A.'s. By default it uses a couple of fast exponential moving average pair (5,13) with the closing price as the source.
Parameters:
source
fast MA length
slow MA Length
type of moving average
OpenAI Signal Generator - Enhanced Accuracy# AI-Powered Trading Signal Generator Guide
## Overview
This is an advanced trading signal generator that combines multiple technical indicators using AI-enhanced logic to generate high-accuracy trading signals. The indicator uses a sophisticated combination of RSI, MACD, Bollinger Bands, EMAs, ADX, and volume analysis to provide reliable buy/sell signals with comprehensive market analysis.
## Key Features
### 1. Multi-Indicator Analysis
- **RSI (Relative Strength Index)**
- Length: 14 periods (default)
- Overbought: 70 (default)
- Oversold: 30 (default)
- Used for identifying overbought/oversold conditions
- **MACD (Moving Average Convergence Divergence)**
- Fast Length: 12 (default)
- Slow Length: 26 (default)
- Signal Length: 9 (default)
- Identifies trend direction and momentum
- **Bollinger Bands**
- Length: 20 periods (default)
- Multiplier: 2.0 (default)
- Measures volatility and potential reversal points
- **EMAs (Exponential Moving Averages)**
- Fast EMA: 9 periods (default)
- Slow EMA: 21 periods (default)
- Used for trend confirmation
- **ADX (Average Directional Index)**
- Length: 14 periods (default)
- Threshold: 25 (default)
- Measures trend strength
- **Volume Analysis**
- MA Length: 20 periods (default)
- Threshold: 1.5x average (default)
- Confirms signal strength
### 2. Advanced Features
- **Customizable Signal Frequency**
- Daily
- Weekly
- 4-Hour
- Hourly
- On Every Close
- **Enhanced Filtering**
- EMA crossover confirmation
- ADX trend strength filter
- Volume confirmation
- ATR-based volatility filter
- **Comprehensive Alert System**
- JSON-formatted alerts
- Detailed technical analysis
- Multiple timeframe analysis
- Customizable alert frequency
## How to Use
### 1. Initial Setup
1. Open TradingView and create a new chart
2. Select your preferred trading pair
3. Choose an appropriate timeframe
4. Apply the indicator to your chart
### 2. Configuration
#### Basic Settings
- **Signal Frequency**: Choose how often signals are generated
- Daily: Signals at the start of each day
- Weekly: Signals at the start of each week
- 4-Hour: Signals every 4 hours
- Hourly: Signals every hour
- On Every Close: Signals on every candle close
- **Enable Signals**: Toggle signal generation on/off
- **Include Volume**: Toggle volume analysis on/off
#### Technical Parameters
##### RSI Settings
- Adjust `rsi_length` (default: 14)
- Modify `rsi_overbought` (default: 70)
- Modify `rsi_oversold` (default: 30)
##### EMA Settings
- Fast EMA Length (default: 9)
- Slow EMA Length (default: 21)
##### MACD Settings
- Fast Length (default: 12)
- Slow Length (default: 26)
- Signal Length (default: 9)
##### Bollinger Bands
- Length (default: 20)
- Multiplier (default: 2.0)
##### Enhanced Filters
- ADX Length (default: 14)
- ADX Threshold (default: 25)
- Volume MA Length (default: 20)
- Volume Threshold (default: 1.5)
- ATR Length (default: 14)
- ATR Multiplier (default: 1.5)
### 3. Signal Interpretation
#### Buy Signal Requirements
1. RSI crosses above oversold level (30)
2. Price below lower Bollinger Band
3. MACD histogram increasing
4. Fast EMA above Slow EMA
5. ADX above threshold (25)
6. Volume above threshold (if enabled)
7. Market volatility check (if enabled)
#### Sell Signal Requirements
1. RSI crosses below overbought level (70)
2. Price above upper Bollinger Band
3. MACD histogram decreasing
4. Fast EMA below Slow EMA
5. ADX above threshold (25)
6. Volume above threshold (if enabled)
7. Market volatility check (if enabled)
### 4. Visual Indicators
#### Chart Elements
- **Moving Averages**
- SMA (Blue line)
- Fast EMA (Yellow line)
- Slow EMA (Purple line)
- **Bollinger Bands**
- Upper Band (Green line)
- Middle Band (Orange line)
- Lower Band (Green line)
- **Signal Markers**
- Buy Signals: Green triangles below bars
- Sell Signals: Red triangles above bars
- **Background Colors**
- Light green: Buy signal period
- Light red: Sell signal period
### 5. Alert System
#### Alert Types
1. **Signal Alerts**
- Generated when buy/sell conditions are met
- Includes comprehensive technical analysis
- JSON-formatted for easy integration
2. **Frequency-Based Alerts**
- Daily/Weekly/4-Hour/Hourly/Every Close
- Includes current market conditions
- Technical indicator values
#### Alert Message Format
```json
{
"symbol": "TICKER",
"side": "BUY/SELL/NONE",
"rsi": "value",
"macd": "value",
"signal": "value",
"adx": "value",
"bb_upper": "value",
"bb_middle": "value",
"bb_lower": "value",
"ema_fast": "value",
"ema_slow": "value",
"volume": "value",
"vol_ma": "value",
"atr": "value",
"leverage": 10,
"stop_loss_percent": 2,
"take_profit_percent": 5
}
```
## Best Practices
### 1. Signal Confirmation
- Wait for multiple confirmations
- Consider market conditions
- Check volume confirmation
- Verify trend strength with ADX
### 2. Risk Management
- Use appropriate position sizing
- Implement stop losses (default 2%)
- Set take profit levels (default 5%)
- Monitor market volatility
### 3. Optimization
- Adjust parameters based on:
- Trading pair volatility
- Market conditions
- Timeframe
- Trading style
### 4. Common Mistakes to Avoid
1. Trading without volume confirmation
2. Ignoring ADX trend strength
3. Trading against the trend
4. Not considering market volatility
5. Overtrading on weak signals
## Performance Monitoring
Regularly review:
1. Signal accuracy
2. Win rate
3. Average profit per trade
4. False signal frequency
5. Performance in different market conditions
## Disclaimer
This indicator is for educational purposes only. Past performance is not indicative of future results. Always use proper risk management and trade responsibly. Trading involves significant risk of loss and is not suitable for all investors.
Uptrick: Z-Trend BandsOverview
Uptrick: Z-Trend Bands is a Pine Script overlay crafted to capture high-probability mean-reversion opportunities. It dynamically plots upper and lower statistical bands around an EMA baseline by converting price deviations into z-scores. Once price moves outside these bands and then reenters, the indicator verifies that momentum is genuinely reversing via an EMA-smoothed RSI slope. Signal memory ensures only one entry per momentum swing, and traders receive clear, real-time feedback through customizable bar-coloring modes, a semi-transparent fill highlighting the statistical zone, concise “Up”/“Down” labels, and a live five-metric scoring table.
Introduction
Markets often oscillate between trending and reverting, and simple thresholds or static envelopes frequently misfire when volatility shifts. Standard deviation quantifies how “wide” recent price moves have been, and a z-score transforms each deviation into a measure of how rare it is relative to its own history. By anchoring these bands to an exponential moving average, the script maintains a fluid statistical envelope that adapts instantly to both calm and turbulent regimes. Meanwhile, the Relative Strength Index (RSI) tracks momentum; smoothing RSI with an EMA and observing its slope filters out erratic spikes, ensuring that only genuine momentum flips—upward for longs and downward for shorts—qualify.
Purpose
This indicator is purpose-built for short-term mean-reversion traders operating on lower–timeframe charts. It reveals when price has strayed into the outer 5 percent of its recent range, signaling an increased likelihood of a bounce back toward fair value. Rather than firing on price alone, it demands that momentum follow suit: the smoothed RSI slope must flip in the opposite direction before any trade marker appears. This dual-filter approach dramatically reduces noise-driven, false setups. Traders then see immediate visual confirmation—bar colors that reflect the latest signal and age over time, clear entry labels, and an always-visible table of metric scores—so they can gauge both the validity and freshness of each signal at a glance.
Originality and Uniqueness
Uptrick: Z-Trend Bands stands apart from typical envelope or oscillator tools in four key ways. First, it employs fully normalized z-score bands, meaning ±2 always captures roughly the top and bottom 5 percent of moves, regardless of volatility regime. Second, it insists on two simultaneous conditions—price reentry into the bands and a confirming RSI slope flip—dramatically reducing whipsaw signals. Third, it uses slope-phase memory to lock out duplicate signals until momentum truly reverses again, enforcing disciplined entries. Finally, it offers four distinct bar-coloring schemes (solid reversal, fading reversal, exceeding bands, and classic heatmap) plus a dynamic scoring table, rather than a single, opaque alert, giving traders deep insight into every layer of analysis.
Why Each Component Was Picked
The EMA baseline was chosen for its blend of responsiveness—weighting recent price heavily—and smoothness, which filters market noise. Z-score deviation bands standardize price extremes relative to their own history, adapting automatically to shifting volatility so that “extreme” always means statistically rare. The RSI, smoothed with an EMA before slope calculation, captures true momentum shifts without the false spikes that raw RSI often produces. Slope-phase memory flags prevent repeated alerts within a single swing, curbing over-trading in choppy conditions. Bar-coloring modes provide flexible visual contexts—whether you prefer to track the latest reversal, see signal age, highlight every breakout, or view a continuous gradient—and the scoring table breaks down all five core checks for complete transparency.
Features
This indicator offers a suite of configurable visual and logical tools designed to make reversal signals both robust and transparent:
Dynamic z-score bands that expand or contract in real time to reflect current volatility regimes, ensuring the outer ±zThreshold levels always represent statistically rare extremes.
A smooth EMA baseline that weights recent price more heavily, serving as a fair-value anchor around which deviations are measured.
EMA-smoothed RSI slope confirmation, which filters out erratic momentum spikes by first smoothing raw RSI and then requiring its bar-to-bar slope to flip before any signal is allowed.
Slope-phase memory logic that locks out duplicate buy or sell markers until the RSI slope crosses back through zero, preventing over-trading during choppy swings.
Four distinct bar-coloring modes—Reversal Solid, Reversal Fade, Exceeding Bands, Classic Heat—plus a “None” option, so traders can choose whether to highlight the latest signal, show signal age, emphasize breakout bars, or view a continuous heat gradient within the bands.
A semi-transparent fill between the EMA and the upper/lower bands that visually frames the statistical zone and makes extremes immediately obvious.
Concise “Up” and “Down” labels that plot exactly when price re-enters a band with confirming momentum, keeping chart clutter to a minimum.
A real-time, five-metric scoring table (z-score, RSI slope, price vs. EMA, trend state, re-entry) that updates every two bars, displaying individual +1/–1/0 scores and an averaged Buy/Sell/Neutral verdict for complete transparency.
Calculations
Compute the fair-value EMA over fairLen bars.
Subtract that EMA from current price each bar to derive the raw deviation.
Over zLen bars, calculate the rolling mean and standard deviation of those deviations.
Convert each deviation into a z-score by subtracting the mean and dividing by the standard deviation.
Plot the upper and lower bands at ±zThreshold × standard deviation around the EMA.
Calculate raw RSI over rsiLen bars, then smooth it with an EMA of length rsiEmaLen.
Derive the RSI slope by taking the difference between the current and previous smoothed RSI.
Detect a potential reentry when price exits one of the bands on the prior bar and re-enters on the current bar.
Require that reentry coincide with an RSI slope flip (positive for a lower-band reentry, negative for an upper-band reentry).
On first valid reentry per momentum swing, fire a buy or sell signal and set a memory flag; reset that flag only when the RSI slope crosses back through zero.
For each bar, assign scores of +1, –1, or 0 for the z-score direction, RSI slope, price vs. EMA, trend-state, and reentry status.
Average those five scores; if the result exceeds +0.1, label “Buy,” if below –0.1, label “Sell,” otherwise “Neutral.”
Update bar colors, the semi-transparent fill, reversal labels, and the scoring table every two bars to reflect the latest calculations.
How It Actually Works
On each new candle, the EMA baseline and band widths update to reflect current volatility. The RSI is smoothed and its slope recalculated. The script then looks back one bar to see if price exited either band and forward to see if it reentered. If that reentry coincides with an appropriate RSI slope flip—and no signal has yet been generated in that swing—a concise label appears. Bar colors refresh according to your selected mode, and the scoring table updates to show which of the five conditions passed or failed, along with the overall verdict. This process repeats seamlessly at each bar, giving traders a continuous feed of disciplined, statistically filtered reversal cues.
Inputs
All parameters are fully user-configurable, allowing you to tailor sensitivity, lookbacks, and visuals to your trading style:
EMA length (fairLen): number of bars for the fair-value EMA; higher values smooth more but lag further behind price.
Z-Score lookback (zLen): window for calculating the mean and standard deviation of price deviations; longer lookbacks reduce noise but respond more slowly to new volatility.
Z-Score threshold (zThreshold): number of standard deviations defining the upper and lower bands; common default is 2.0 for roughly the outer 5 percent of moves.
Source (src): choice of price series (close, hl2, etc.) used for EMA, deviation, and RSI calculations.
RSI length (rsiLen): period for raw RSI calculation; shorter values react faster to momentum changes but can be choppier.
RSI EMA length (rsiEmaLen): period for smoothing raw RSI before taking its slope; higher values filter more noise.
Bar coloring mode (colorMode): select from None, Reversal Solid, Reversal Fade, Exceeding Bands, or Classic Heat to control how bars are shaded in relation to signals and band positions.
Show signals (showSignals): toggle on-chart “Up” and “Down” labels for reversal entries.
Show scoring table (enableTable): toggle the display of the five-metric breakdown table.
Table position (tablePos): choose which corner (Top Left, Top Right, Bottom Left, Bottom Right) hosts the scoring table.
Conclusion
By merging a normalized z-score framework, momentum slope confirmation, disciplined signal memory, flexible visuals, and transparent scoring into one Pine Script overlay, Uptrick: Z-Trend Bands offers a powerful yet intuitive tool for intraday mean-reversion trading. Its adaptability to real-time volatility and multi-layered filter logic deliver clear, high-confidence reversal cues without the clutter or confusion of simpler indicators.
Disclaimer
This indicator is provided solely for educational and informational purposes. It does not constitute financial advice. Trading involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. Always conduct your own testing and apply careful risk management before trading live.
First EMA Touch (Last N Bars)Okay, here's a description of the "First EMA Touch (Last N Bars)" TradingView indicator:
Indicator Name: First EMA Touch (Last N Bars)
Core Purpose:
This indicator is designed to visually highlight on the chart the exact moment when the price (specifically, the high/low range of a price bar) makes contact with a specified Exponential Moving Average (EMA) for the first time within a defined recent lookback period (e.g., the last 20 bars).
How it Works:
EMA Calculation: It first calculates a standard Exponential Moving Average (EMA) based on the user-defined EMA Length and EMA Source (e.g., close price). This EMA line is plotted on the chart, often serving as a dynamic level of potential support or resistance.
"Touch" Detection: For every price bar, the indicator checks if the bar's range (from its low to its high) overlaps with or crosses the calculated EMA value for that bar. If low <= EMA <= high, it's considered a "touch".
"First Touch" Logic: This is the key feature. The indicator looks back over a specified number of preceding bars (defined by the Lookback Period). If a "touch" occurs on the current bar, and no "touch" occurred on any of the bars within that preceding lookback window, then the current touch is marked as the "first touch".
Visual Signal: When a "first touch" condition is met, the indicator plots a distinct shape (by default, a small green triangle) below the corresponding price bar. This makes it easy to spot these specific events.
Key Components & Settings:
EMA Line: The calculated EMA itself is plotted (typically as an orange line) for visual reference.
First Touch Signal: A shape (e.g., green triangle) appears below bars meeting the "first touch" criteria.
EMA Length (Input): Determines the period used for the EMA calculation. Shorter lengths make the EMA more reactive to recent price changes; longer lengths make it smoother and slower.
Lookback Period (Input): Defines how many bars (including the current one) the indicator checks backwards to determine if the current touch is the first one. A lookback of 20 means it checks if there was a touch in the previous 19 bars before signalling the current one as the first.
EMA Source (Input): Specifies which price point (close, open, high, low, hl2, etc.) is used to calculate the EMA.
Interpretation & Potential Uses:
Identifying Re-tests: The signal highlights when price returns to test the EMA after having stayed away from it for the duration of the lookback period. This can be significant as the market re-evaluates the EMA level.
Potential Reversal/Continuation Points: A first touch might indicate:
A potential area where a trend might resume after a pullback (if price bounces off the EMA).
A potential area where a reversal might begin (if price strongly rejects the EMA).
A point of interest if price consolidates around the EMA after the first touch.
Filtering Noise: By focusing only on the first touch within a period, it can help filter out repeated touches that might occur during choppy or consolidating price action around the EMA.
Confluence: Traders might use this signal in conjunction with other forms of analysis (e.g., horizontal support/resistance, trendlines, candlestick patterns, other indicators) to strengthen trade setups.
Limitations:
Lagging: Like all moving averages, the EMA is a lagging indicator.
Not Predictive: The signal indicates a specific past event (the first touch) occurred; it doesn't guarantee a future price movement.
Parameter Dependent: The effectiveness and frequency of signals heavily depend on the chosen EMA Length and Lookback Period. These may need tuning for different assets and timeframes.
Requires Confirmation: It's generally recommended to use this indicator as part of a broader trading strategy and not rely solely on its signals for trade decisions.
In essence, the "First EMA Touch (Last N Bars)" indicator provides a specific, refined signal related to price interaction with a moving average, helping traders focus on potentially significant initial tests of the EMA after a period of separation.
