6 EMA Crypto InvestidorExponential Moving Averages - 6 EMA Crypto Investidor
Indicator developed to facilitate the use of 6 EMAs in a single indicator.
EMAs: 9, 13, 21, 55, 100 and 200 Periods
Developed by Diego do Youtube Channel Crypto Investor
Recherche dans les scripts pour "Exponential"
EMAs Crypto InvestidorExponential Moving Averages - EMAs Crypto Investor
Indicator developed to facilitate the use of 5 EMAs in a single indicator.
EMAs: 17, 34, 72, 100 and 200 Periods
Developed by Diego do Youtube Channel Crypto Investor
Exponentially Weighted AveragesImplementation of Exponentially Weighted Averages and it difference in Pine Script. It can generate a line that adjust to the overall trend of a graphic.
Exponentially Weighted Averages
This technique is used for generating smoother lines that adjust to a graphic. In finances, it is used to predict the overall trend of a graphic. The function that defines the EWA is the one bellow:
Vt = β V(t-1) + (1 - β) θt
Where:
β: Hyperparammeter that we have to adjust.
V(t-1): Value calculated for the previous element of the graphic.
θt: Current element of the graphic.
Exponential growthPurpose
The indicator plots an exponential curve based on historical price data and supports toggling between exponential regression and linear logarithmic regression. It also provides offset bands around the curve for additional insights.
Key Inputs
1. yxlogreg and dlogreg:
These are the "Endwert" (end value) and "Startwert" (start value) for calculating the slope of the logarithmic regression.
2. bars:
Specifies how many historical bars are considered in the calculation.
3.offsetchannel:
Adds an adjustable percentage-based offset to create upper and lower bands around the main exponential curve.
Default: 1 (interpreted as 10% bands).
4.lineareregression log.:
A toggle to switch between exponential function and linear logarithmic regression.
Default: false (exponential is used by default).
5.Dynamic Labels:
Creates a label showing the calculated regression values and historical bars count at the latest bar. The label is updated dynamically.
Use Cases
Exponential Growth Tracking:
Useful for assets or instruments exhibiting exponential growth trends.
Identifying Channels:
Helps identify support and resistance levels using the offset bands.
Switching Analysis Modes:
Flexibility to toggle between exponential and linear logarithmic analysis.
Exponential SAR based MA**Description:**
The "Exponential SAR" (ESAR) indicator is a modified version of the classic Parabolic SAR (Stop and Reverse) indicator, incorporating an exponential moving average (EMA) smoothing technique. It aims to provide traders with a smoother representation of trend changes in the price action of a financial instrument.
**Functionality:**
The indicator calculates the Parabolic SAR values using specified parameters for start, increment, and maximum values. These parameters control the acceleration factor of the SAR. The calculated SAR values are then smoothed using an exponential moving average with a user-defined length, providing a more refined interpretation of trend dynamics.
**Inputs:**
- **Length:** Specifies the length of the exponential moving average used to smooth the Parabolic SAR values.
- **Alpha:** Defines the smoothing factor for the exponential moving average, allowing users to adjust the level of smoothing applied to the SAR.
- **Start, Increment, Maximum:** Parameters controlling the acceleration factor of the Parabolic SAR.
**Usage:**
- **Trend Identification:** Traders can use the Exponential SAR to identify trend reversals and continuations in the price action of a security. Bullish signals occur when the price moves above the ESAR, indicating an upward trend, while bearish signals occur when the price moves below the ESAR, signaling a downtrend.
- **Trend Confirmation:** The smoothed nature of the ESAR helps traders confirm trend changes more reliably, reducing the impact of false signals commonly associated with the standard Parabolic SAR.
- **Risk Management:** By incorporating a smoothed SAR, traders can make more informed decisions regarding entry and exit points, improving risk management strategies.
**Customization:**
Users can customize the indicator by adjusting the input parameters according to their trading preferences and market conditions. Experimenting with different lengths and alpha values can provide insights into the effectiveness of the ESAR in various trading scenarios.
**Note:**
As with any technical indicator, the Exponential SAR should be used in conjunction with other analytical tools and risk management techniques to validate signals and mitigate potential losses. Additionally, traders should consider market conditions and adapt their strategies accordingly.
Exponential Directional Index (DI)Exponential Directional Index (DI)
This indicator calculates the Exponential Directional Index (DI) using the Exponential Moving Average (EMA) of true range and directional movement. The DI is a widely used technical analysis tool that measures the strength of a trend by comparing positive and negative directional movements.
How it Works:
- **EMA Length:** Traders can adjust the length of the EMA calculation according to their trading preferences. A longer EMA length will result in a smoother DI line, while a shorter length will be more responsive to recent price action.
- **True Range (TR):** The true range is the greatest of the following: current high minus the current low, absolute value of the current high minus the previous close, and the absolute value of the current low minus the previous close.
- **Positive Directional Movement (+DM):** Calculates the difference between the current high and the previous high if positive, otherwise, it assigns a value of zero.
- **Negative Directional Movement (-DM):** Calculates the difference between the previous low and the current low if positive, otherwise, it assigns a value of zero.
- **Smoothed True Range (ATR):** Calculates the Exponential Moving Average (EMA) of the true range over the specified EMA length.
- **Smoothed Positive Directional Movement (+DI):** Calculates the Exponential Moving Average (EMA) of the positive directional movement over the specified EMA length.
- **Smoothed Negative Directional Movement (-DI):** Calculates the Exponential Moving Average (EMA) of the negative directional movement over the specified EMA length.
- **Directional Movement Index (DMI):** Calculates the DI values by dividing the smoothed positive and negative directional movements by the smoothed true range and multiplying by 100.
- **Bar Color:** The bar color changes based on whether the +DI is greater than, less than, or equal to the -DI. Green bars indicate that +DI is greater than -DI, red bars indicate that -DI is greater than +DI, and blue bars indicate that +DI is equal to -DI.
- **Background Highlight:** A background highlight is applied when the +DI crosses over the -DI or vice versa, providing a visual indication of potential trend changes.
Ideal Usage:
- **Trend Strength:** Traders can use the DI to gauge the strength of a trend. A rising +DI indicates bullish strength, while a rising -DI indicates bearish strength.
- **Trend Reversals:** Changes in the relationship between +DI and -DI, along with crossover signals, can indicate potential trend reversals.
- **Customization:** The indicator offers flexibility through customizable parameters, allowing traders to adapt it to various market conditions and trading strategies.
Warnings:
- **False Signals:** Like any technical indicator, false signals may occur, especially during periods of low volume or choppy market conditions. It's essential to use additional analysis and risk management techniques to avoid potential losses.
- **Parameter Sensitivity:** Adjusting the EMA length can affect the indicator's sensitivity to price movements. Traders should test different parameter settings and consider market conditions when using the indicator.
Exponential Bollinger Bands (EBB)This script is a variation of the popular Bollinger Bands indicator, which uses exponential moving averages (EMA) instead of simple moving averages (SMA) as its core calculation. The indicator is designed to provide a visual representation of volatility, with the distance between the upper and lower bands being determined by the standard deviation of the underlying data.
The script starts by defining a number of helper functions that are used to calculate the moving averages and standard deviations required for the indicator. The first helper function is sma(), which calculates the simple moving average of the input data over a specified length. This function uses linear interpolation to smooth the data when the length is not an integer. The stdev() function calculates the standard deviation of the input data using the simple moving average calculated by the sma() function.
The bes() function calculates the exponential moving average of the input data over a specified length. The estdev() function calculates the standard deviation of the input data using the exponential moving average calculated by the bes() function.
The estdev function calculates the standard deviation using an exponential moving average method, rather than the traditional simple moving average method used by the stdev function. The exponential moving average method gives more weight to recent data, which can make the estdev more responsive to recent changes in volatility. This can make it more useful in certain types of analysis, such as identifying trends in volatility. Additionally, it also uses the same EMA algorithm to calculate the average value of the data set, which can help to keep the output of the estdev and average functions consistent.
The script also defines two more helper functions, average() and standard_deviation(), which allow the user to switch between using simple moving averages (SMA) and exponential moving averages (EMA) as the basis for the indicator. These functions take three arguments, the input data, the length of the moving average, and a string that specifies whether to use SMA or EMA.
The script then defines the input parameters for the indicator. The user can choose whether to use SMA or EMA as the basis for the indicator using the select parameter. The user can also specify the length of the moving average and the multiplier for the standard deviation using the length and multiplier parameters, respectively.
Finally, the script calculates the average and standard deviation of the input data using the selected method (SMA or EMA), and plots the upper and lower bands of the indicator. The upper band is calculated as the average plus the standard deviation multiplied by the specified multiplier, while the lower band is calculated as the average minus the standard deviation multiplied by the specified multiplier.
Exponential Smoothing FilterThe digital exponential filter, in finance known as Exponential Moving Average (EMA) , can be used as a technical indicator for chart analysis to visualize uptrends and downtrends in the market. Unlike the classic simple moving average, the EMA requires only two values for its calculation: the last calculated exponential average price and the current price. This is a simple and fast calculation - even for wide smoothing windows. For further details and the math please refer to the "exponential smoothing" article on Wikipedia.
Here are some additional key points about the exponential moving average:
The EMA can react more quickly to price changes because it can give more weight to current prices - depending on your parameter settings.
Short-term, disruptive price fluctuations are smoothed out well, making prevailing trends more visible.
Despite good smoothing properties, it delays the input values slightly, so it can follow sudden trend changes well.
The EMA is well suited to dynamic markets and trading strategies.
The filter is a good basis for further processing such as gradient analysis.
How to use
When you add the script to your charts, you'll immediately see a thin orange line across your time series, smoothing out price fluctuations.
There are only two parameters to set
smoothing factor between 0.0000 = no smoothing and 0.9999 = strong smoothing
input source : open, high, low, close hl2, etc.
Chart output
In the example chart above, you can see that the orange line follows the highs and lows better than the blue line , which is a simple moving average (SMA).
Additionally, the orange line has a shorter lag, or reacts faster when the trend of the original price data suddenly changes. These characteristics are critical for buying and selling decisions: quickly reacting and tracking highs and lows while providing a smooth line that filters out distracting noise.
Exponential-Decay Cumulative Spread (Cycle-Tuned)## Indicator Overview
**Exponential-Decay Cumulative Spread (Cycle-Tuned)** – short title **LambdaCumDelta** – tracks the percentage spread between CEXs BTC spot prices.
By clipping outliers, applying an exponential-decay running sum, and comparing that sum to rolling percentile bands, the script flags potential **cycle bottoms** and **cycle tops** whenever the cumulative spread stays beyond extreme thresholds for three consecutive bars.
---
### Core Logic
1. **Price Spread**
`spread_pct = (cexA – cexB) / cexB × 100`.
2. **Outlier Suppression**
* Calculates the **90-day standard deviation σ** of `spread_pct`.
* Uses a **clip coefficient `k_clip`** (0.5–5.0) to cap the spread at `±k_clip × σ`, damping single-day anomalies.
3. **Exponential-Decay Sum**
* Applies a decay factor **λ** (0.50–0.999):
```
CumΔₜ = spread_clipₜ + λ × CumΔₜ₋₁
```
* Larger λ → longer memory half-life.
4. **Rolling Percentile Bands**
* Uses a **365-bar window** to derive dynamic percentile thresholds.
* Upper / Lower bands are set by **perc\_hi** and **perc\_lo** (e.g., 85 % and 15 %).
5. **Signal Definition**
* **Bullish** (cycle bottom): `CumΔ` above the upper band for **3 straight bars**.
* **Bearish** (cycle top): `CumΔ` below the lower band for **3 straight bars**.
---
### Chart Elements
| Plot | Style | Meaning |
| --------------- | ----------------- | ----------------------------------- |
| **CumΔ** | Teal thick line | Exponential-decay cumulative spread |
| Upper Threshold | Green thin line | Rolling upper percentile |
| Lower Threshold | Red thin line | Rolling lower percentile |
| Background | Faded green / red | Bullish / bearish signal zone |
---
### Key Inputs
| Input | Default | Purpose |
| -------------------- | ------- | ------------------------------- |
| **Decay factor λ** | 0.95 | Memory length of CumΔ |
| **Clip coefficient** | 2.0 | Multiple of σ for outlier cap |
| **Upper percentile** | 85 | Cycle-bottom trigger percentile |
| **Lower percentile** | 15 | Cycle-top trigger percentile |
---
### Practical Tips
1. **Timing bias**
* Green background often precedes mean-reversion of the spread – consider scaling into longs or covering shorts.
* Red background suggests stretched positive spread – consider trimming longs or lightening exposure.
2. **Combine with volume, trend filters (MA, MACD, etc.)** to weed out false extremes.
3. Designed for **daily charts**; ensure both exchange feeds are synchronized.
---
### Alerts
Two built-in `alertcondition`s fire when bullish or bearish criteria are met, enabling push / email / webhook notifications.
---
### Disclaimer
This script is for educational and research purposes only and is **not** financial advice. Test thoroughly and trade at your own risk.
Exponential Regression Channel with novel volatilityThis code is a modified version of the built-in "linear regression" script of Tradingviews which can be plotted correctly on logarithmic charts
The log reg code of Forza was adjusted by altustro to generate an exponential regression (or a correct linear regression on the log scale, this is equivalent).
The standard deviation in the log scale is a better volatility measure which we call novola, and which defines the trend channel displayed in addition to the main indicator.
The exponential regression slope and channel also defines the typical holding time of the stock and the SL/TP boundaries, which are calculated and displayed at the last bar.
The display works both in log and regular scale. But only in the log scale it can be compared to the linear extension, which can also be plotted when activated in the properties.
The underlying exponential fit can not be displayed in regular scale as only lines can be plotted by TV. But with the related script Exponental Regression also the exponential regression can be exactly displayed using a workaround.
Exponential RegressionIn Tradingview it is not possible to actually display arbitrary non-linear functions retrospectively.
Series objects can only depend on the current or past bars
Thus, while regression is possible, display of a non-linear curve into the past is not possible
This script is a workaround to be able to still display an exponential fit of the last n bars.
It is based on a linear regression of the log(close). The parameters of this regression are printed in the label.
To create the correct plot, these parameters have to be written into the properties of the indicator.
The functions displayed follow the expression exp(A)* exp(pot*t+d)
where d =0 for the center line, and d = +-std * upperMult for the upper and lower line respectiveley.
The parameters of the function are:
amplitude in log scale A
exponent of the exponential function pot
standard deviation of the linear regression std
number of bars of the current chart bindex
multiplicator of the std of the upper and lower exponential line upperMult and lowerMult +
This code is a version of the built-in "linear regression" script of Tradingview alztered by Forza so it can be plotted correctly on logarithmic charts
The code of Forza was further adjusted by altustro to be able to plot the full exponential curve also in regular scale
Exponential Moving Average with ADR bandIndicator: Exponential Moving Average with ADR Band
This TradingView script calculates and displays an Exponential Moving Average (EMA) along with an Average Daily Range (ADR) band around it. The indicator helps traders identify potential dynamic support and resistance levels adjusted for market volatility. Especially significant moves that originate from the ZONE and reach outside should be taken seriously.
Key Features:
EMA Calculation: The script computes the Exponential Moving Average (EMA) of the closing prices over a user-defined period.
ADR Band: It calculates the Average Daily Range (ADR) using a Simple Moving Average (SMA) of the daily high-low range over the same period.
Adjustable Parameters:
Length: The period for both the EMA and the ADR calculation, which can be set by the user (default is 20).
Multiple: A multiplier for the ADR to adjust the width of the bands around the EMA (default is 1).
Plotting: The EMA is plotted as an orange line. The upper and lower ADR bands are plotted around the EMA, and the area between these bands is filled with a translucent orange color to highlight the channel.
How It Works:
EMA Calculation: The script computes the EMA of the closing prices using the specified length.
ADR Calculation: The daily range (high-low) is averaged over the same length to get the ADR.
Band Creation: The upper band is created by adding the ADR (multiplied by the user-defined multiple) to the EMA. The lower band is created by subtracting the ADR (multiplied by the user-defined multiple) from the EMA.
Visualization: The EMA and ADR bands are plotted, and the area between the bands is filled to create a clear visual representation of the ADR channel.
Usage:
This indicator can be used to gauge market volatility and potential support/resistance zones.
The ADR band provides a dynamic range that adjusts with market conditions, helping traders identify potential breakout and reversal points.
To customize the indicator, adjust the 'Length' and 'ADR multiple' parameters to suit your trading style and the specific characteristics of the asset you are analyzing.
Exponential Bollinger BandsThese Bollinger Bands are exponential because the variance is calculated using the exponential moving average, rather than just adding the normal standard deviation to the ema. This may be more useful because the exponential standard deviation should be more sensitive to near term increases or decreases in volatility.
Please do not forget that Bollinger Bands should always be combined with another method of analysis. Bollinger Bands just provide an easy way to gauge where the price could range in. At 2 standard deviations of a continuously random variable, more than 98% of data points are in this range. I am however going to test this in excel to get the average number of data points that stay in the range for Bitcoin. I will upload my findings when I complete that. Please monitor this description if your interested.
Exponential Stochastic Strategywhat is Exponential Stochastic?
it is a modified version of the stochastic indicator. This strategy does not include pyramiding, repaint, trailing stop or take profit.
what it does?
It contains an extra input in addition to the stochastic indicator. Thanks to this input, different exponential weights can be given to the outputs and the indicator can be made more sensitive or insensitive. The strategy buys when the indicator leaves the overbought zone, sells when it leaves the oversold zone and always stays in the trade.
how it does it?
it uses this formula: i.hizliresim.com
Thanks to this formula, even if the weights given to the outputs change, the indicator always continues to take a value between 0 and 100.
how to use it ?
With the input named "exp", you can change the sensitivity of the indicator and develop different strategies. other inputs are the same as the stochastic indicator. Increasing the exp value causes the indicator to signal less, decreasing it makes it much more sensitive.
Exponential Regression Slope Annualized with R-squared HistogramMy other indicator shows the linear regression slope of the source. This one finds the exponential regression slope and optionally multiplies it by R-squared and optionally annualizes it. Multiplying by R-squared makes sure that the price movement was significant in order to avoid volatile movements that can throw off the slope value. Annualizing the exponential slope will let you see how much percentage you will make in a year if the price continues at its current pace.
The annualized number is the number of trading days in a year. This and the length might need adjusting for the extra bars that might be in futures or other markets. The number does not have to be a year. For example, it can be a month if you set the number to 20 or so trading days to find how much you would make in a month if price continues at its current pace, etc. This can also be used as an alternative to relative strength or rate of change.
Exponential Hull Moving Average (EHMA)Source for Exponential Hull Moving Average (EHMA) formula:
Raudys, Aistis & Lenčiauskas, Vaidotas & Malčius, Edmundas. (2013). Moving Averages for Financial Data Smoothing. Communications in Computer and Information Science. 403. 34-45. 10.1007/978-3-642-41947-8_4.
The Exponential Hull Moving Average is nearly identical to the Hull MA, but EMA used instead of WMA.
Credit to @RicardoSantos for the existing implementation of the Hull Moving Average in pinescript:
Exponential Avg Body Size Green vs RedDescription :
This indicator calculates and plots the Exponential Moving Average (EMA) of green and red candlestick body sizes, allowing traders to easily visualize market momentum and sentiment shifts. The script includes the following features:
Customizable EMA Period: Users can set the number of candles to calculate the EMA through an input setting, with a default value of 21.
Separate Green and Red Candle Averages: Differentiates between bullish (green) and bearish (red) candlestick movements, plotting them as distinct lines.
Dynamic Range Control: Users can adjust the chart range (e.g., -50 to 50) for better visibility of the plotted lines.
Baseline for Reference: A horizontal baseline at 0 serves as a visual aid for easier interpretation.
Standalone Indicator Pane: The script is designed to display in a separate pane, preventing overlap with the price chart.
Use Case:
This indicator is ideal for traders seeking to analyze the relative strength of bullish versus bearish price movements over a specific period. The separation of green and red averages helps identify trends, potential reversals, or shifts in momentum.
Exponential Top and Bottom FinderThis is an indicator to identify possible tops and bottoms after exponential price surges and drops, it works best on ETH 1D, but you can also use it for bitcoin and altcoins.
It's based on stochastic first and second derivatives of a close moving average
Exponential Hull Moving AverageThis script is a tweaked version of the Exponential Hull Moving Average that allows you to introduce a longer lookback period for reversal signals. In all current implementations of the EHMA, the reversal (color change from red to green) is calculated by taking the current value of the MA and comparing it to the previous calculated value. This EHMA version allows you to alter the lookback for more conservative reversal signals. The default value is 3, meaning if the EMA is greater than the value of the EHMA calculated 3 periods ago, it will turn green. This makes it less responsive, and less prone to early signalling.
Exponential Moving Averages Major Exponential Moving Averages as a single indicator for trading view
the showline = true/false shows/hides the price line of the moving average
Exponential Moving Average (by Ethrex)Allows to see how Exponential Moving Averages are computed.
This script is for demonstration purposes and the built-in 'ema' TradingView function will be much faster.
Exponential Moving Averages [etherbunny]This plots the 8, 13, 21, 55 and 100 day exponential moving averages.
