SMI Ergodic Indicator/Oscillator▮ Introduction
The Stochastic Momentum Index Ergodic Indicator (SMII) is a technical analysis tool designed to predict trend reversals in the price of an asset.
It functions as a momentum oscillator, measuring the ratio of the smoothed price change to the smoothed absolute price change over a given number of previous periods.
The Ergodic SMI is based on the True Strength Index (TSI) and integrates a signal line, which is an exponential moving average (EMA) of the SMI indicator itself.
It provides a clearer picture of market trends than the traditional stochastic oscillator by incorporating the concept of "ergodicity", which helps remove market noise.
On ther other hand, the Stochastic Momentum Index Ergodic Oscillator (SMIO) is a histogram that measures the difference between TSI and it's signal line.
By default, in TradingView both SMII and SMIO are provided independently.
Here in this script these two indicators are combined, providing a more comprehensive view of price direction and market strength.
▮ Motivation: why another indicator?
The intrinsic value of this indicator lies in the fact that it allows fine adjustments in both calculation parameters, data source and visualization, features that are not present in the standard indicators or similar.
Also, trend lines breakouts and divergences detector were added.
▮ What to look for
When using the indicator, there are a few things to look out for.
First, look at the SMI signal line.
When the line crosses above -40, it is considered a buy signal, while the crossing below +40 is considered a sell signal.
Also, pay attention to divergences between the SMI and the price.
If price is rising but the SMI is showing negative divergence, it could indicate that momentum is waning and a reversal could be in the offing.
Likewise, if price is falling but the SMI is showing positive divergence, this could indicate that momentum is building and a reversal could also be in the offing.
Divergences can be considered in both indicator and/or histogram.
Examples:
▮ Notes
The indicator presented here offers both the "SMII" and the "SMIO", that is, the "Stochastic Momentum Index Ergodic Indicator" together with the "Stochastic Momentum Index Ergodic Oscillator" (histogram), as per the documentation described in reference links.
So it is important to highlight the differences in relation to my other indicator, Stochastic Momentum Index (SMI) Refurbished .
This last one is purely based on the **SMI**, which is implemented using smoothed ratio between the relative range and the high/low range.
Although they may seem the same in some situations, the calculation is actually different. The TSI tends to be more responsive at the expense of being noisier, while the SMI tends to be smoother. Which of these two indicators is best depends on the situation, the context, and the analyst's personal preference.
Please refer to reference links to more info.
▮ References
SMI documentation
SMII documentation
SMIO documentation
Stochasticoscillator
Stochastic Trendlines with Breakouts [Jamshid] - EnhancedStochastic Trendlines with Breakouts - Enhanced Version
This advanced Stochastic Trendlines with Breakouts script combines several powerful features to provide enhanced breakout detection based on the Stochastic Oscillator and additional confirmation signals. This script is designed to help traders identify key trend reversals, breakout points, and pivot levels with more accuracy by integrating advanced filters such as RSI confirmation, moving average trend filtering, volatility filtering, divergence detection, and multi-timeframe analysis.
Key Features:
Stochastic Oscillator-Based Breakouts:
Automatically detects breakouts based on the smoothed Stochastic Oscillator values (%K and %D), providing insights into overbought and oversold conditions.
Customizable overbought and oversold levels, with a mid-level (50) line for additional reference.
Trendlines on Pivot Points:
Automatically plots dynamic trendlines based on pivot highs and lows of the smoothed Stochastic %K, helping to visualize potential reversal points.
RSI Confirmation (Optional):
Filters breakout signals using the Relative Strength Index (RSI) to confirm breakouts only when the RSI is below 50 for downtrend breakouts and above 50 for uptrend breakouts.
Visual confirmation with a green "RSI Conf." label displayed on the chart when the RSI condition is met.
Moving Average Filter (Optional):
Confirms breakout signals in the direction of a user-defined Moving Average (MA) to trade in the overall market trend direction.
MA length is fully customizable.
Stochastic Divergence Filter (Optional):
Detects bullish or bearish divergence between the price and Stochastic Oscillator values, adding an extra layer of confirmation.
Multi-Timeframe Confirmation (Optional):
Confirms breakouts by checking the Stochastic %K and %D values from a higher timeframe. This helps in avoiding false signals by aligning with the broader market trend.
The higher timeframe can be customized to any timeframe (e.g., daily, weekly, etc.).
Volatility Filter (Optional):
Uses the ATR (Average True Range) to filter out breakouts during periods of low volatility, ensuring signals are only triggered when there is sufficient price movement.
ATR length and multiplier are fully customizable.
Custom Alerts:
Alerts are available for new trendline detections (both pivot high and pivot low) and for confirmed breakout signals. These alerts help traders stay informed in real-time without needing to monitor the chart continuously.
How to Use:
Customize the Stochastic Oscillator settings, such as %K smoothing and %D line parameters, to fit your trading strategy.
Enable or disable additional filtering features (RSI, MA, divergence, MTF, volatility) as needed.
Set up alerts for specific breakout conditions directly in TradingView to stay notified when breakout signals are triggered.
This script is designed for traders who are looking for precision breakout signals with added layers of confirmation to avoid false breakouts and enhance trading accuracy.
Advanced Stochastic ForLoopAdvanced Stochastic ForLoop
OVERVIEW
Advanced Stochastic ForLoop is an improved version of Stochastic it is designed to calculate an array of values 1 or -1 depending if soruce for calculations is above or below basis.
It takes avereage of values over a range of lengths, providing trend signals smothed based on various moving averages in order to get rid of noise.
It offers flexibility with different signal modes and visual customizations.
TYPE OF SIGNALS
-FAST (MA > MA or MA > 0.99)
-SLOW (MA > 0)
-THRESHOLD CROSSING (set by user treshold for both directions)
-FAST THRESHOLD (when theres an change in signal by set margin e.g 0.4 -> 0.2 means bearsih when FT is set to 0.1, when MA is > 0.99 it will signal bullish, when MA < -0.99 it will signal bearish)
Generaly Lime color of line indicates Bullish, Fuchsia indicates Bearish.
This colors are not set in stone so you can change them in settings.
Alerts included when line color is:
-Bullish Trend, line color is lime
-Bearish Trend, line color is fuchsia
Credit
Idea for this script was from one of indicators created by www.tradingview.com
Warning
This indicator can be really noisy depending on the settings, signal mode so it should be used preferably as a part of an strategy not as a stand alone indicator
Remember the lower the timeframe you use the more noise there is.
No single indicator should be used alone when making investment decisions.
Theta Shield | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Theta Shield indicator! Theta is the options risk factor concerning how fast there is a decline in the value of an option over time. This indicator aims to help the trader avoid sideways market phases in the current ticker, to minimize the risk of theta decay. For more information, please check the "How Does It Work" section.
Features of the new Theta Shield Indicator :
Foresight Of Accumulation Zones
Decrease Risk Of Theta Decay
Clear "Valid" & "Non-Valid" Signals
Validness Trail
Alerts
📌 HOW DOES IT WORK ?
In options trading, theta is defined as the rate of decline in the value of an option due to the passage of time. Traders want to avoid this kind of decay in the value of an option. One of the best ways to avoid it is not holding an option contract when the market is going sideways. This indicator uses a stochastic oscillator to try to get a foresight of sideways markets, warning the trader to not hold an option contract while the price is in a range.
The indicator starts by calculating the stochastic value using close, high & low prices of the candlesticks. Then a stoch threshold & a theta length are determined depending on the option contract type defined by the user in the settings of the indicator. Each candlestick that falls above or below the stoch threshold value is counted, and a "theta valid strength" is calculated using the counted candlesticks, which has a value between -100 & 100. Here is the formula of the "theta valid strength" value :
f_lin_interpolate(float x0, float x1, float y0, float y1, float x) =>
y0 + (x - x0) * (y1 - y0) / (x1 - x0)
thetaValid = Total Candlesticks That Fall Above & Below The Threshold In Last "Theta Length" bars.
thetaValidStrength = f_lin_interpolate(0, thetaLength, -100, 100, thetaValid)
Then a trail is rendered, and "Valid" & "Non-Valid" signals are given using this freshly calculated strength value. Valid means that the indicator currently thinks that no accumulation will happen in the near future, so the option positions in the current ticker are protected from the theta decay. Non-Valid means that the indicator thinks the ticker has entered the accumulation phase, so holding any option position is not recommended, as they may be affected by the theta decay.
🚩 UNIQUENESS
This indicator offers a unique way to avoid theta decay in options trading. It uses a stochastic oscillator and thresholds to calculate a "theta strength" value, which is used for rendering validness signals and a trail. Traders can follow the valid & non-valid signals when deciding to hold their options position or not. The indicator also has an alerts feature, so you can get notified when a ticker is about to enter a range, or when it's about to get out of it.
⚙️ SETTINGS
1. General Configuration
Contract Type -> You can set the option contract type here. The indicator will adjust itself to get a better foresight depending on the contract length.
2. Style
Fill Validness -> Will render a trail based on "theta strength" value.
MACD with 1D Stochastic Confirmation Reversal StrategyOverview
The MACD with 1D Stochastic Confirmation Reversal Strategy utilizes MACD indicator in conjunction with 1 day timeframe Stochastic indicators to obtain the high probability short-term trend reversal signals. The main idea is to wait until MACD line crosses up it’s signal line, at the same time Stochastic indicator on 1D time frame shall show the uptrend (will be discussed in methodology) and not to be in the oversold territory. Strategy works on time frames from 30 min to 4 hours and opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Higher time frame confirmation: Strategy utilizes 1D Stochastic to establish the major trend and confirm the local reversals with the higher probability.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
MACD line of MACD indicator shall cross over the signal line of MACD indicator.
1D time frame Stochastic’s K line shall be above the D line.
1D time frame Stochastic’s K line value shall be below 80 (not overbought)
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 3.25, value multiplied by ATR to be subtracted from position entry price to setup stop loss)
ATR Trailing Profit Activation Level (by default = 4.25, value multiplied by ATR to be added to position entry price to setup trailing profit activation level)
Trailing EMA Length (by default = 20, period for EMA, when price reached trailing profit activation level EMA will stop out of position if price closes below it)
User can choose the optimal parameters during backtesting on certain price chart, in our example we use default settings.
Justification of Methodology
This strategy leverages 2 time frames analysis to have the high probability reversal setups on lower time frame in the direction of the 1D time frame trend. That’s why it’s recommended to use this strategy on 30 min – 4 hours time frames.
To have an approximation of 1D time frame trend strategy utilizes classical Stochastic indicator. The Stochastic Indicator is a momentum oscillator that compares a security's closing price to its price range over a specific period. It's used to identify overbought and oversold conditions. The indicator ranges from 0 to 100, with readings above 80 indicating overbought conditions and readings below 20 indicating oversold conditions.
It consists of two lines:
%K: The main line, calculated using the formula (CurrentClose−LowestLow)/(HighestHigh−LowestLow)×100 . Highest and lowest price taken for 14 periods.
%D: A smoothed moving average of %K, often used as a signal line.
Strategy logic assumes that on 1D time frame it’s uptrend in %K line is above the %D line. Moreover, we can consider long trade only in %K line is below 80. It means that in overbought state the long trade will not be opened due to higher probability of pullback or even major trend reversal. If these conditions are met we are going to our working (lower) time frame.
On the chosen time frame, we remind you that for correct work of this strategy you shall use 30min – 4h time frames, MACD line shall cross over it’s signal line. The MACD (Moving Average Convergence Divergence) is a popular momentum and trend-following indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in a stock's price.
The MACD consists of three components:
MACD Line: This is the difference between a short-term Exponential Moving Average (EMA) and a long-term EMA, typically calculated as: MACD Line=12-period EMA−26-period
Signal Line: This is a 9-period EMA of the MACD Line, which helps to identify buy or sell signals. When the MACD Line crosses above the Signal Line, it can be a bullish signal (suggesting a buy); when it crosses below, it can be a bearish signal (suggesting a sell).
Histogram: The histogram shows the difference between the MACD Line and the Signal Line, visually representing the momentum of the trend. Positive histogram values indicate increasing bullish momentum, while negative values indicate increasing bearish momentum.
In our script we are interested in only MACD and signal lines. When MACD line crosses signal line there is a high chance that short-term trend reversed to the upside. We use this strategy on 45 min time frame.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -4.79%
Maximum Single Profit: +20.14%
Net Profit: +2361.33 USDT (+44.72%)
Total Trades: 123 (44.72% win rate)
Profit Factor: 1.623
Maximum Accumulated Loss: 695.80 USDT (-5.48%)
Average Profit per Trade: 19.20 USDT (+0.59%)
Average Trade Duration: 30 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe between 30 min and 4 hours and chart (optimal performance observed on 45 min BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
MTF-Colored EMA Difference and Stochastic indicatorThis indicator combines two popular technical analysis tools: the Exponential Moving Average (EMA) and the Stochastic Oscillator, with the added flexibility of analyzing them across multiple time frames. It visually represents the difference between two EMAs and the crossover signals from the Stochastic Oscillator, providing a comprehensive view of the market conditions.
Components:
EMA Difference Histogram :
EMA Calculation : The indicator calculates two EMAs (EMA1 and EMA2) for the selected time frame.
EMA Difference : The difference between EMA1 and EMA2 is plotted as a 4 coloured histogram.
Stochastic Oscillato r:
Calculation : The %K and %D lines of the Stochastic Oscillator are calculated for the selected time frame.
Additional Confirmation via Colors :
Green: %K is above %D, indicating a bullish signal.
Red: %K is below %D, indicating a bearish signal.
Entry and Exit Strategies
Entry Strategy :
Bullish Entry :
Condition 1: The histogram is Dark green (indicating a strong upward trend).
Condition 2: The Stochastic colour is green (%K is above %D).
Bearish Entry :
Condition 1: The histogram is Dark Red (indicating a strong downward trend).
Condition 2: The Stochastic colour is red (%K is below %D).
Exit Strategy:
Bullish Exit:
Condition: The Stochastic colour turns red (%K crosses below %D).
Bearish Exit:
Condition: The Stochastic colour turns green (%K crosses above %D).
Additional Considerations:
Time Frame Selection : The chosen time frame for both the EMA and Stochastic calculations should align with the trader’s strategy (e.g., daily for swing trading, hourly for intraday trading).
Risk Management : Implement stop-loss orders to manage risk effectively. The stop-loss can be placed below the recent swing low for long positions and above the recent swing high for short positions.
Confirmation : Consider using this indicator in conjunction with other technical analysis tools to confirm signals and reduce the likelihood of false entries and exits.
Stochastics - Made EasyThis indicator is a visually improved version of Stochastics. It makes it much easier to see what's happening by simplifying those confusing, intersecting lines. With this, you can detect the Stochastics direction more clearly. All the features are also explained in the tooltips of the input fields. Some extra features are included, such as average top and bottom calculation, standard deviation and divergences.
Color legend:
Green: Stoch K Above D and Rising
Light Green: Stoch K Above D and Falling
Red: Stoch K Below D and Falling
Light Red: Stoch K Below D and Rising
Blue: Stoch K Crossover D
Orange: Stoch K Crossunder D
Blue Arrow: Bullish Divergence
Orange Arrow: Bearish Divergence
Reversal Candlestick Structure [LuxAlgo]The Reversal Candlestick Structure indicator detects multiple candlestick patterns occurring when trends are most likely to experience a reversal in real-time. The reversal detection method includes various settings allowing users to adjust the reversal detection algorithm more precisely.
A dashboard showing the percentage of patterns detected as reversals is also included.
🔶 USAGE
Candlestick patterns are ubiquitous to technical analysts, allowing them to detect trend continuations, reversals, and indecision.
The proposed tool effectively detects reversals by using the confluence between candlestick patterns and a reversal detection method based on the stochastic oscillator, acting as a filter for the patterns. If a candlestick pattern occurs while conditions suggest a potential reversal then the pattern is highlighted.
The displayed candle coloring allows users to observe the reversal detection method, with colored candles indicating potential reversals.
Users wanting to detect longer-term reversals can use a higher "Trend Length" setting, this can however lead to an increased amount of displayed candlestick patterns.
To prevent false positives users also have control over a "Threshold" setting in a range between (0, 100), with values closer to 100 preventing candlesticks from being detected at the start of trends.
The "Warmup Length" serves a similar purpose, and aims to prevent sudden moves to be classified as reversals. Higher values of this setting will require trends to be established for a longer period of time for reversal conditions to be detected.
🔹 Dashboard
To evaluate the role of individual candlestick patterns as potential reversal signals relative to the proposed reversal detection method, a dashboard displaying the percentage of candlestick patterns displayed (that occur when a potential reversal is detected) over the total amount detected.
Hovering on the dashboard cells of the "Reversal %" column allows displaying the total amount of patterns detected.
🔶 CANDLESTICKS PATTERNS
This tool detects 16 popular candlestick patterns, each listed in the sub-sections below.
🔹 Bullish Patterns
Hammer - A bullish reversal pattern that forms after a decline, characterized by a small body at the upper end of the trading range and a long lower shadow.
Inverted Hammer - A bullish reversal pattern that forms after a downtrend, featuring a small body at the lower end of the trading range and a long upper shadow.
Bullish Engulfing - A bullish reversal pattern where a small bearish candlestick is followed by a larger bullish candlestick that completely engulfs the previous candle.
Rising 3 - A bullish continuation pattern that consists of a long bullish candlestick followed by three smaller bearish candlesticks and then another long bullish candlestick.
3 White Soldiers - A bullish reversal pattern consisting of three consecutive long bullish candlesticks, each opening within the previous candle's body and closing higher.
Morning Star - A bullish reversal pattern made up of three candlesticks: a long bearish candlestick, followed by a short candlestick, and then a long bullish candlestick.
Bullish Harami - A bullish reversal pattern where a small bullish candlestick is completely within a previous larger bearish candlestick.
Tweezer Bottom - A bullish reversal pattern identified by an initial bullish candle, followed by a bearish candle, both having equal lows.
🔹 Bearish Patterns
Hanging Man - A bearish reversal pattern that forms after an uptrend, characterized by a small body at the upper end of the trading range and a long lower shadow.
Shooting Star - A bearish reversal pattern that forms after an uptrend, featuring a small body at the lower end of the trading range and a long upper shadow.
Bearish Engulfing - A bearish reversal pattern where a small bullish candlestick is followed by a larger bearish candlestick that completely engulfs the previous candle.
Falling 3 - A bearish continuation pattern that consists of a long bearish candlestick followed by three smaller bullish candlesticks and then another long bearish candlestick.
3 Black Crows - A bearish reversal pattern consisting of three consecutive long bearish candlesticks, each opening within the previous candle's body and closing lower.
Evening Star - A bearish reversal pattern made up of three candlesticks: a long bullish candlestick, followed by a short candlestick, and then a long bearish candlestick.
Bearish Harami - A bearish reversal pattern where a small bearish candlestick is completely within a previous larger bullish candlestick.
Tweezer Top - A bearish reversal pattern is identified by an initial bullish candle, followed by a bearish candle, both having equal highs."
🔶 SETTINGS
🔹 Patterns
Group including toggles for each of the supported candlestick patterns. Enabled toggles will allow detection of the associated candlestick pattern.
🔹 Reversal Detection
Trend Length: Determines the sensitivity of the reversal detection method to shorter-term variation, with higher values returning a detection method more sensitive to longer-term trends.
Threshold: Determines how easy it is for the reversal detection method to consider a trend at an extreme point.
Warmup Length: Warmup period in the reversal detection method, longer values will require a longer-term trend to detect potential reversals.
🔹 Style
Color Candles: Enable candle coloring on the user chart based on the reversal detection method.
Use Gradient: Use a gradient as candle coloring.
Label Size: Size of the labels displaying the detected candlesticks patterns.
🔹 Dashboard
Show Dashboard: Display the dashboard on the user chart when enabled.
Location: Dashboard location on the user chart.
Size: Size of the displayed dashboard.
Christmas Toolkit [LuxAlgo]It's that time of the year... and what would be more appropriate than displaying Christmas-themed elements on your chart?
The Christmas Toolkit displays a tree containing elements affected by various technical indicators. If you're lucky, you just might also find a precious reindeer trotting toward the tree, how fancy!
🔶 USAGE
Each of the 7 X-mas balls is associated with a specific condition.
Each ball has a color indicating:
lime: very bullish
green: bullish
blue: holding the same position or sideline
red: bearish
darkRed: very bearish
From top to bottom:
🔹 RSI (length 14)
rsi < 20 - lime (+2 points)
rsi < 30 - green (+1 point)
rsi > 80 - darkRed (-2 points)
rsi > 70 - red (-1 point)
else - blue
🔹 Stoch (length 14)
stoch < 20 - lime (+2 points)
stoch < 30 - green (+1 point)
stoch > 80 - darkRed (-2 points)
stoch > 70 - red (-1 point)
else - blue
🔹 close vs. ema (length 20)
close > ema 20 - green (+1 point)
else - red (-1 point)
🔹 ema (length 20)
ema 20 rises - green (+1 point)
else - red (-1 point)
🔹 ema (length 50)
ema 50 rises - green (+1 point)
else - red (-1 point)
🔹 ema (length 100)
ema 100 rises - green (+1 point)
else - red (-1 point)
🔹 ema (length 200)
ema 200 rises - green (+1 point)
else - red (-1 point)
The above information can also be found on the right side of the tree.
You'll see the conditions associated with the specific X-mas ball and the meaning of color changes. This can also be visualized by hovering over the labels.
All values are added together, this result is used to color the star at the top of the tree, with a specific color indicating:
lime: very bullish (> 6 points)
green: bullish (6 points)
blue: holding the same position or sideline
red: bearish (-6 points)
darkRed: very bearish (< -6 points)
Switches to green/lime or red/dark red can be seen by the fallen stars at the bottom.
The Last Switch indicates the latest green/lime or red/dark red color (not blue)
🔶 ANIMATION
Randomly moving snowflakes are added to give it a wintry character.
There are also randomly moving stars in the tree.
Garland rotations, style, and color can be adjusted, together with the width and offset of the tree, put your tree anywhere on your chart!
Disabling the "static tree" setting will make the needles 'move'.
Have you happened to see the precious reindeer on the right? This proud reindeer moves towards the most recent candle. Who knows what this reindeer might be bringing to the tree?
🔶 SETTINGS
Width: Width of tree.
Offset: Offset of the tree.
Garland rotations: Amount of rotations, a high number gives other styles.
Color/Style: sets the color & style of garland stars.
Needles: sets the needle color.
Static Tree: Allows the tree needles to 'move' with each tick.
Reindeer Speed: Controls how fast the deer moves toward the most recent bar.
🔶 MESSAGE FROM THE LUXALGO TEAM
It has been an honor to contribute to the TradingView community and we are always so happy to see your supportive messages on our scripts.
We have posted a total of 78 script publications this year, which is no small feat & was only possible thanks to our team of Wizard developers @alexgrover + @dgtrd + @fikira , the development team behind Pine Script, and of course to the support of our legendary community.
Happy Holidays to you all, and we'll see ya next year! ☃️
[KVA]K Stochastic IndicatorOriginal Stochastic Oscillator Formula:
%K=(C−Lowest Low)/(Highest High−Lowest Low)×100
Lowest Low refers to the lowest low of the past n periods.
Highest High refers to the highest high of the past n periods.
K Stochastic Indicator Formula:
%K=(Source−Lowest Source)/(Highest Source−Lowest Source)×100
Lowest Source refers to the lowest value of the chosen source over the past length periods.
Highest Source refers to the highest value of the chosen source over the past length periods.
Key Difference :
The original formula calculates %K using the absolute highest high and lowest low of the price over the past n periods.
The K Stochastic formula calculates %K using the highest and lowest values of a chosen source (which could be the close, open, high, or low) over the specified length periods.
So, if _src is set to something other than the high for the Highest Source or something other than the low for the Lowest Source, the K Stochastic will yield different results compared to the original formula which strictly uses the highest high and the lowest low of the price.
Impact on Traders :
Flexibility in Price Source :
By allowing the source (_src) to be customizable, traders can apply the Stochastic calculation to different price points (e.g., open, high, low, close, or even an average of these). This could provide a different perspective on market momentum and potentially offer signals that are more aligned with a trader's specific strategy.
Sensitivity to Price Action :
Changing the source from high/low to potentially less extreme values (like close or open) could result in a less volatile oscillator, smoothing out some of the extreme peaks and troughs and possibly offering a more filtered view of market conditions.
Customization of Periods :
The ability to adjust the length period offers traders the opportunity to fine-tune the sensitivity of the indicator to match their trading horizon. Shorter periods may provide earlier signals, while longer periods could filter out market noise.
Possibility of Applying the Indicator on Other Indicators :
Layered Technical Analysis :
The K Stochastic can be applied to other indicators, not just price. For example, it could be applied to a moving average to analyze its momentum or to indicators like RSI or MACD, offering a meta-analysis that studies the oscillator's behavior of other technical tools.
Creation of Composite Indicator s:
By applying the K Stochastic logic to other indicators, traders could create composite indicators that blend the characteristics of multiple indicators, potentially leading to unique signals that could offer an edge in certain market conditions.
Enhanced Signal Interpretation :
When applied to other indicators, the K Stochastic can help in identifying overbought or oversold conditions within those indicators, offering a different dimension to the interpretation of their output.
Overall Implications :
The KStochastic Indicator's modifications could lead to a more tailored application, giving traders the ability to adapt the tool to their specific trading style and analysis preferences.
By being applicable to other indicators, it broadens the scope of stochastic analysis beyond price action, potentially offering innovative ways to interpret data and make trading decisions.
The changes might also influence the trading signals, either by smoothing the oscillator's output to reduce noise or by altering the sensitivity to generate more or fewer signal
Including the additional %F line, which is unique to the K Stochastic Indicator, further expands the potential impacts and applications for traders:
Impact on Traders with the %F Line:
Triple Smoothing :
The %F line introduces a third level of smoothing, which could help in identifying longer-term trends and filtering out short-term fluctuations. This could be particularly useful for traders looking to avoid whipsaws and focus on more sustained movements.
Potential for Enhanced Confirmation :
The %F line might be used as a confirmation signal. For instance, if all three lines (%K, %D, and %F) are in agreement, a trader might consider this as a stronger signal to buy or sell, as opposed to when only the traditional two lines (%K and %D) are used.
Risk Management:
The additional line could be utilized for more sophisticated risk management strategies, where a trader might decide to scale in or out of positions based on the convergence or divergence of these lines.
Possibility of Applying the Indicator on Other Indicators with the %F Line:
Depth of Analysis :
When applied to other indicators, the %F line can provide an even deeper layer of analysis, perhaps identifying macro trends within the indicator it is applied to, which could go unnoticed with just the traditional two-line approach.
Refined Signal Strength Assessment :
The strength of signals from other indicators could be assessed by the position and direction of the %F line, providing an additional filter to evaluate the robustness of buy or sell signals.
Overall Implications with the %F Line :
The inclusion of the %F line in the K Stochastic Indicator enhances its utility as a tool for trend analysis and signal confirmation. It allows traders to potentially identify and act on more reliable trading opportunities.
This feature can enrich the trader's toolkit by providing a nuanced view of momentum and trend strength, which can be particularly valuable in volatile or choppy markets.
For those applying the K Stochastic to other indicators, the %F line could be integral in creating a multi-tiered analysis strategy, potentially leading to more sophisticated interpretations and decisions.
The presence of the %F line adds a dimension of depth to the analysis possible with the K Stochastic Indicator, making it a versatile tool that could be tailored to a variety of trading styles and objectives. However, as with any indicator, the additional complexity requires careful study and back-testing to ensure its signals are understood and actionable within the context of a comprehensive trading plan.
VCC SmtmWorks better for Cryptos (1W and greater than) timeframes.
This strategy incorporates multiple indicators to make informed trading signals. It leverages the Stochastic indicator to assess price momentum, utilizes the Bollinger Band to identify potential oversold and overbought conditions, and closely monitors Moving Averages to gauge the trend's bullish or bearish nature.
A long signal will be displayed if the following conditions are met:
The Stochastic D and Stochastic K both indicate an oversold condition, with Stochastic K being lower than Stochastic D.
The current Price Low is below the Bollinger Lower Band.
The Price Close is currently below all Moving Averages.
A Death Cross pattern has formed among the Moving Averages.
A short signal will be displayed if the opposite of the long conditions are true:
The Stochastic D and Stochastic K both indicate an overbought condition, with Stochastic K being higher than Stochastic D.
The current Price High is above the Bollinger Upper Band.
The Price Close is currently above all Moving Averages.
A Golden Cross pattern has formed among the Moving Averages.
Price Exhaustion IndicatorThe Price Exhaustion Indicator (PE) is a powerful tool designed to identify trends weakening and strengthening in the financial markets. It combines the concepts of Average True Range (ATR), Moving Average Convergence Divergence (MACD), and Stochastic Oscillator to provide a comprehensive assessment of trend exhaustion levels. By analyzing these multiple indicators together, traders and investors can gain valuable insights into potential price reversals and long-term market highs and lows.
The aim of combining the ATR, MACD, and Stochastic Oscillator, is to provide a comprehensive analysis of trend exhaustion. The ATR component helps assess the volatility and range of price movements, while the MACD offers insights into the convergence and divergence of moving averages. The Stochastic Oscillator measures the current price in relation to its range, providing further confirmation of trend exhaustion. The exhaustion value is derived by combining the MACD, ATR, and Stochastic Oscillator. The MACD value is divided by the ATR value, and then multiplied by the Stochastic Oscillator value. This calculation results in a single exhaustion value that reflects the combined influence of these three indicators.
Application
The Price Exhaustion Indicator utilizes a unique visual representation by incorporating a gradient color scheme. The exhaustion line dynamically changes color, ranging from white when close to the midline (40) to shades of purple as it approaches points of exhaustion (overbought at 100 and oversold at -20). As the exhaustion line approaches the color purple, this represents extreme market conditions and zones of weakened trends where reversals may occur. This color gradient serves as a visual cue, allowing users to quickly gauge the strength or weakness of the prevailing trend.
To further enhance its usability, the Price Exhaustion Indicator also includes circle plots that signify potential points of trend reversion. These plots appear when the exhaustion lines cross or enter the overbought and oversold zones. Red circle plots indicate potential short entry points, suggesting a weakening trend and the possibility of a downward price reversal. Conversely, green circle plots represent potential long entry points, indicating a strengthening trend and the potential for an upward price reversal.
Traders and investors can leverage the Price Exhaustion Indicator in various ways. It can be utilized as a trend-following tool, or a mean reversion tool. When the exhaustion line approaches the overbought or oversold zones, it suggests a weakening trend and the possibility of a price reversal, helping identify potential market tops and bottoms. This can guide traders in timing their entries or exits in anticipation of a trend shift.
Utility
The Price Exhaustion Indicator is particularly useful for long-term market analysis, as it focuses on identifying long-term market highs and lows. By capturing the gradual weakening or strengthening of a trend, it assists investors in making informed decisions about portfolio allocation, trend continuation, or potential reversals.
In summary, the Price Exhaustion Indicator is a comprehensive and visually intuitive tool that combines ATR, MACD, and Stochastic Oscillator to identify trend exhaustion levels. By utilizing a gradient color scheme and circle plots, it offers traders and investors valuable insights into potential trend reversals and long-term market highs and lows. Its unique features make it a valuable addition to any trader's toolkit, providing a deeper understanding of market dynamics and assisting in decision-making processes. Please note that future performance of any trading strategy is fundamentally unknowable, and past results do not guarantee future performance.
Kalman Filtered ROC & Stochastic with MA SmoothingThe "Smooth ROC & Stochastic with Kalman Filter" indicator is a trend following tool designed to identify trends in the price movement. It combines the Rate of Change (ROC) and Stochastic indicators into a single oscillator, the combination of ROC and Stochastic indicators aims to offer complementary information: ROC measures the speed of price change, while Stochastic identifies overbought and oversold conditions, allowing for a more robust assessment of market trends and potential reversals. The indicator plots green "B" labels to indicate buy signals and blue "S" labels to represent sell signals. Additionally, it displays a white line that reflects the overall trend for buy signals and a blue line for sell signals. The aim of the indicator is to incorporate Kalman and Moving Average (MA) smoothing techniques to reduce noise and enhance the clarity of the signals.
Rationale for using Kalman Filter:
The Kalman Filter is chosen as a smoothing tool in the indicator because it effectively reduces noise and fluctuations. The Kalman Filter is a mathematical algorithm used for estimating and predicting the state of a system based on noisy and incomplete measurements. It combines information from previous states and current measurements to generate an optimal estimate of the true state, while simultaneously minimizing the effects of noise and uncertainty. In the context of the indicator, the Kalman Filter is applied to smooth the input data, which is the source for the Rate of Change (ROC) calculation. By considering the previous smoothed state and the difference between the current measurement and the predicted value, the Kalman Filter dynamically adjusts its estimation to reduce the impact of outliers.
Calculation:
The indicator utilizes a combination of the ROC and the Stochastic indicator. The ROC is smoothed using a Kalman Filter (credit to © Loxx: ), which helps eliminate unwanted fluctuations and improve the signal quality. The Stochastic indicator is calculated with customizable parameters for %K length, %K smoothing, and %D smoothing. The smoothed ROC and Stochastic values are then averaged using the formula ((roc + d) / 2) to create the blended oscillator. MA smoothing is applied to the combined oscillator aiming to further reduce fluctuations and enhance trend visibility. Traders are free to choose their own preferred MA type from 'EMA', 'DEMA', 'TEMA', 'WMA', 'VWMA', 'SMA', 'SMMA', 'HMA', 'LSMA', and 'PEMA' (credit to: © traderharikrishna for this code: ).
Application:
The indicator's buy signals (represented by green "B" labels) indicate potential entry points for buying assets, suggesting a bullish trend. The white line visually represents the trend, helping traders identify and follow the upward momentum. Conversely, the sell signals (blue "S" labels) highlight possible exit points or opportunities for short selling, indicating a bearish trend. The blue line illustrates the bearish movement, aiding in the identification of downward momentum.
The "Smoothed ROC & Stochastic" indicator offers traders a comprehensive view of market trends by combining two powerful oscillators. By incorporating the ROC and Stochastic indicators into a single oscillator, it provides a more holistic perspective on the market's momentum. The use of a Kalman Filter for smoothing helps reduce noise and enhance the accuracy of the signals. Additionally, the indicator allows customization of the smoothing technique through various moving average types. Traders can also utilize the overbought and oversold zones for additional analysis, providing insights into potential market reversals or extreme price conditions. Please note that future performance of any trading strategy is fundamentally unknowable, and past results do not guarantee future performance.
Stochastic Zone Strength Trend [wbburgin](This script was originally invite-only, but I'd vastly prefer contributing to the TradingView community more than anything else, so I am making it public :) I'd much rather share my ideas with you all.)
The Stochastic Zone Strength Trend indicator is a very powerful momentum and trend indicator that 1) identifies trend direction and strength, 2) determines pullbacks and reversals (including oversold and overbought conditions), 3) identifies divergences, and 4) can filter out ranges. I have some examples below on how to use it to its full effectiveness. It is composed of two components: Stochastic Zone Strength and Stochastic Trend Strength.
Stochastic Zone Strength
At its most basic level, the stochastic Zone Strength plots the momentum of the price action of the instrument, and identifies bearish and bullish changes with a high degree of accuracy. Think of the stochastic Zone Strength as a much more robust equivalent of the RSI. Momentum-change thresholds are demonstrated by the "20" and "80" levels on the indicator (see below image).
Stochastic Trend Strength
The stochastic Trend Strength component of the script uses resistance in each candlestick to calculate the trend strength of the instrument. I'll go more into detail about the settings after my description of how to use the indicator, but there are two forms of the stochastic Trend Strength:
Anchored at 50 (directional stochastic Trend Strength):
The directional stochastic Trend Strength can be used similarly to the MACD difference or other histogram-like indicators : a rising plot indicates an upward trend, while a falling plot indicates a downward trend.
Anchored at 0 (nondirectional stochastic Trend Strength):
The nondirectional stochastic Trend Strength can be used similarly to the ADX or other non-directional indicators : a rising plot indicates increasing trend strength, and look at the stochastic Zone Strength component and your instrument to determine if this indicates increasing bullish strength or increasing bearish strength (see photo below):
(In the above photo, a bearish divergence indicated that the high Trend Strength predicted a strong downwards move, which was confirmed shortly after. Later, a bullish move upward by the Zone Strength while the Trend Strength was elevated predicated a strong upwards move, which was also confirmed. Note the period where the Trend Strength never reached above 80, which indicated a ranging period (and thus unprofitable to enter or exit)).
How to Use the Indicator
The above image is a good example on how to use the indicator to determine divergences and possible pivot points (lines and circles, respectively). I recommend using both the stochastic Zone Strength and the stochastic Trend Strength at the same time, as it can give you a robust picture of where momentum is in relation to the price action and its trajectory. Every color is changeable in the settings.
Settings
The Amplitude of the indicator is essentially the high-low lookback for both components.
The Wavelength of the indicator is how stretched-out you want the indicator to be: how many amplitudes do you want the indicator to process in one given bar.
A useful analogy that I use (and that I derived the names from) is from traditional physics. In wave motion, the Amplitude is the up-down sensitivity of the wave, and the Wavelength is the side-side stretch of the wave.
The Smoothing Factor of the settings is simply how smoothed you want the stochastic to be. It's not that important in most circumstances.
Trend Anchor was covered above (see my description of Trend Strength). The "Trend Transform MA Length" is the EMA length of the Trend Strength that you use to transform it into the directional oscillator. Think of the EMA being transformed onto the 50 line and then the Trend Strength being dragged relative to that.
Trend Transform MA Length is the EMA length you want to use for transforming the nondirectional Trend Strength (anchored at 0) into the directional Trend Strength (anchored at 50). I suggest this be the same as the wavelength.
Trend Plot Type can transform the Nondirectional Trend Strength into a line plot so that it doesn't murk up the background.
Finally, the colors are changeable on the bottom.
Explanation of Zone Strength
If you're knowledgeable in Pine Script, I encourage you to look at the code to try to understand the concept, as it's a little complicated. The theory behind my Zone Strength concept is that the wicks in every bar can be used create an index of bullish and bearish resistance, as a wick signifies that the price crossed above a threshold before returning to its origin. This distance metric is unique because most indicators/formulas for calculating relative strength use a displacement metric (such as close - open) instead of measuring how far the price actually moved (up and down) within a candlestick. This is what the Zone Strength concept represents - the hesitation within the bar that is not typically represented in typical momentum indicators.
In the script's code I have step by step explanations of how the formula is calculated and why it is calculated as such. I encourage you to play around with the amplitude and wavelength inputs as they can make the zone strength look very different and perform differently depending on your interests.
Enjoy!
Walker
Stochastic Distance Indicator [CC]The Stochastic Distance Indicator was created by Vitali Apirine (Stocks and Commodities Jun 2023 pgs 16-21), and this is a new method that measures the absolute distance between a price and its highest and lowest values over a long period. It uses the stochastic formula to create an oscillator using this distance value and smooths the value. Obviously, there is a lag in signals due to the lookback periods, but it does a good job of staying above the midline when the stock is in a strong uptrend and vice versa. Of course, I'm open to suggestions, but I'm deciding to create buy and sell signals based on comparing the unsmoothed and smoothed values. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators you would like to see me publish!
Multi-Divergence Buy/Sell IndicatorThe "Multi-Divergence Buy/Sell Indicator" is a technical analysis tool that combines multiple divergence signals from different indicators to identify potential buy and sell opportunities in the market. Here's a breakdown of how the indicator works and how to use it:
Input Parameters:
RSI Length: Specifies the length of the RSI (Relative Strength Index) calculation.
MACD Short Length: Specifies the short-term length for the MACD (Moving Average Convergence Divergence) calculation.
MACD Long Length: Specifies the long-term length for the MACD calculation.
MACD Signal Smoothing: Specifies the smoothing length for the MACD signal line calculation.
Stochastic Length: Specifies the length of the Stochastic oscillator calculation.
Stochastic Overbought Level: Defines the overbought level for the Stochastic oscillator.
Stochastic Oversold Level: Defines the oversold level for the Stochastic oscillator.
Calculation of Indicators:
RSI: Calculates the RSI based on the specified RSI Length.
MACD: Calculates the MACD line, signal line, and histogram based on the specified MACD parameters.
Stochastic: Calculates the Stochastic oscillator based on the specified Stochastic parameters.
Divergence Detection:
RSI Divergence: Identifies a bullish divergence when the RSI crosses above its 14-period simple moving average (SMA).
MACD Divergence: Identifies a bullish divergence when the MACD line crosses above the signal line.
Stochastic Divergence: Identifies a bullish divergence when the Stochastic crosses above its 14-period SMA.
Buy and Sell Conditions:
Buy Condition: Triggers a buy signal when all three divergences (RSI, MACD, and Stochastic) occur simultaneously.
Sell Condition: Triggers a sell signal when both RSI and MACD divergences occur, but Stochastic divergence does not occur.
Plotting Buy/Sell Signals:
The indicator plots green "Buy" labels below the price bars when the buy condition is met.
It plots red "Sell" labels above the price bars when the sell condition is met.
Usage:
The indicator can be used on any timeframe and for any trading instrument.
Look for areas where all three divergences (RSI, MACD, and Stochastic) align to generate stronger buy and sell signals.
Consider additional technical analysis and risk management strategies to validate the signals and manage your trades effectively.
Remember, no indicator guarantees profitable trades, so it's essential to use this indicator in conjunction with other tools and perform thorough analysis before making trading decisions.
Feel free to ask any questions
Stochastic [Tcs] | OSCThis script is an implementation of the stochastic relative strength index (STOCH RSI) indicator
The script takes inputs from the length of the RSI, the source of the data, and parameters for the smoothing of the STOCH RSI.
The STOCH RSI is calculated by first calculating the RSI of the chosen source data, then smoothing it with an exponential moving average. The stochastic oscillator is then applied to the smoothed RSI, and smoothed again to create the final STOCH RSI.
The script also calculates a trigger value using a combination of the STOCH RSI and a volume-weighted moving average. It then plots the STOCH RSI, trigger value, and overbought/oversold levels, and fills the background of the plot based on the relationship between the trigger and STOCH RSI values.
Finally, the script plots buy and sell signals based on crossovers and crossunders of the STOCH RSI and its smoothed version.
The cross signal is stronger than the dots, in both direction and usually the best entries happen when two crosses signal on the level 0(long) or 100(short) appear after a dot signal.
Please note that this indicator is for educational purposes only and should not be used for trading without further testing and analysis.
RSI, SRSI, MACD and DMI cross - Open source codeHello,
I'm a passionate trader who has spent years studying technical analysis and exploring different trading strategies. Through my research, I've come to realize that certain indicators are essential tools for conducting accurate market analysis and identifying profitable trading opportunities. In particular, I've found that the RSI, SRSI, MACD cross, and Di cross indicators are crucial for my trading success.
Detailed explanation:
The RSI is a momentum indicator that measures the strength of price movements. It is calculated by comparing the average of gains and losses over a certain period of time. In this indicator, the RSI is calculated based on the close price with a length of 14 periods.
The Stochastic RSI is a combination of the Stochastic Oscillator and the RSI. It is used to identify overbought and oversold conditions of the market. In this indicator, the Stochastic RSI is calculated based on the RSI with a length of 14 periods.
The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of prices. It consists of two lines, the MACD line and the signal line, which are used to generate buy and sell signals. In this indicator, the MACD is calculated based on the close price with fast and slow lengths of 12 and 26 periods, respectively, and a signal length of 9 periods.
The DMI is a trend-following indicator that measures the strength of directional movement in the market. It consists of three lines, the Positive Directional Indicator (+DI), the Negative Directional Indicator (-DI), and the Average Directional Index (ADX), which are used to generate buy and sell signals. In this indicator, the DMI is calculated with a length of 14 periods and an ADX smoothing of 14 periods.
The indicator generates buy signals when certain conditions are met for each of these indicators.
1) For the RSI, a buy signal is generated when the RSI is below or equal to 35 and the Stochastic RSI %K is below or equal to 15, or when the RSI is below or equal to 28 the Stochastic RSI %K is below or equal to 15 or when the RSI is below or equal to 25 and the Stochastic RSI %K is below or equal to 10 or when the RSI is below or equal to 28.
2) For the MACD, a buy signal is generated when the MACD line is below 0, there is a change in the histogram from negative to positive, the MACD line and histogram are negative in the previous period, and the current histogram value is greater than 0.
3) For the DMI, a buy signal is generated when the Positive Directional Indicator (+DI) crosses above the Negative Directional Indicator (-DI), and the -DI is less than the +DI.
The indicator generates sell signals when certain conditions are met for each of these indicators:
1) For the RSI, a sell signal is generated when the RSI is above or equal to 75 and the Stochastic RSI %K is above or equal to 85, or when the RSI is above or equal to 80 and the Stochastic RSI %K is above or equal to 85, or when the RSI is above or equal to 85 and the Stochastic RSI %K is above or equal to 90 or when the RSI is above or equal to 82.
2)For the MACD, a sell signal is generated when the MACD line is above 0, there is a change in the histogram from positive to negative, the MACD line and histogram are positive in the previous period, and the current histogram value is less than the previous histogram value. On the other hand, a buy signal is generated when the MACD line is below 0, there is a change in the histogram from negative to positive, the MACD line and histogram are negative in the previous period, and the current histogram value is greater than the previous histogram value.
3)For the DMI a bearish signal is generated when plusDI crosses above minusDI, indicating that bulls are losing strength and bears are taking control.
The indicator uses a combination of these four indicators to generate potential buy and sell signals. The buy signals are generated when RSI and SRSI values are in oversold conditions, while sell signals are generated when RSI and SRSI values are in overbought conditions. The indicator also uses MACD crossovers and DMI crossovers to generate additional buy and sell signals.
When a signal is strong?
The use of multiple signals within a specific timeframe can increase the accuracy and reliability of the signals generated by this indicator. It is recommended to look for at least two signals within a range of 5-8 candles in order to increase the probability of a successful trade.
Why it's original?
1) There is no indicator in the library that combine all of these indicators and give you a 360 view
2)The combination of the RSI, Stochastic RSI, MACD, and DMI indicators in a single script it's unique and not available in the libray.
3)The specific parameters and conditions used to calculate the signals may be unique and not found in other scripts or libraries.
4)The use of plotshape() to plot the signals as shapes on the chart may be unique compared to other scripts that simply plot lines or bars to indicate signals.
5)The use of alertcondition() to trigger alerts based on the signals may be unique compared to other scripts that do not have custom alert functionality.
Keep attention!
It is important to note that no trading indicator or strategy is foolproof, and there is always a risk of losses in trading. While this indicator may provide useful information for making conclusions, it should not be used as the sole basis for making trading decisions. Traders should always use proper risk management techniques and consider multiple factors when making trading decisions.
Support me:)
If you find this new indicator helpful in your trading analysis, I would greatly appreciate your support! Please consider giving it a like, leaving feedback, or sharing it with your trading network. Your engagement will not only help me improve this tool but will also help other traders discover it and benefit from its features. Thank you for your support!
Stochastic RSI Strategy (with SMA and VWAP Filters)The strategy is designed to trade on the Stochastic RSI indicator crossover signals.
Below are all of the trading conditions:
-When the Stochastic RSI crosses above 30, a long position is entered.
-When the Stochastic RSI crosses below 70, a short position is entered.
-The strategy also includes two additional conditions for entry:
-Long entries must have a positive spread value between the 9 period simple moving average and the 21 period simple moving average.
-Short entries must have a negative spread value between the 9 period simple moving average and the 21 period simple moving average.
-Long entries must also be below the volume-weighted average price.
-Short entries must also be above the volume-weighted average price.
-The strategy includes stop loss and take profit orders for risk management:
-A stop loss of 20 ticks is placed for both long and short trades.
-A take profit of 25 ticks is placed for both long and short trades.
User Defined Momentum Change with Swing VisualsThis script is a groundbreaking, math-centric technical analysis tool that blends two well-established indicators, the Stochastic Oscillator and the Exponential Moving Average (EMA), to deliver a unique and visually engaging way of identifying momentum swings and stochastic indicators. Unlike mashups, this script is tailored to accommodate a wide range of trading strategies, providing traders with a distinctive perspective on market trends.
The innovation in this script lies in its mathematically-driven ability to effectively combine the Stochastic Oscillator and EMA, setting it apart from other available tools that simply offer a rehash of old ideas or slight modifications to popular indicators. The EMA is employed instead of a Simple Moving Average (SMA), enhancing the uniqueness of the calculations. This novel approach creates a new dimension for traders to evaluate potential momentum swings and visualize them on the chart, proving it to be more than just a mere mashup of existing indicators.
Central to the script's utility is its extensive customization options, which allow traders to adjust various inputs to suit their preferences and trading strategies. Users can modify the EMA length, swing range signal offsets, and smoothing factors for both the fast and slow components of the Stochastic Oscillator. Additionally, the script offers the ability to personalize the color thresholds, transparency, and line properties for the Stochastic Oscillator and swing range signal.
This script's visually dynamic representation of momentum swings empowers traders to make more informed trading decisions, particularly on the 6-hour timeframe. The swing range signal, represented by vertical lines on the chart, acts as a valuable visual aid for identifying potential entry or exit points. Furthermore, the Stochastic Oscillator provides insights into the strength and direction of momentum, which is beneficial for confirming potential trade signals.
To conclude, this script is not just another combination of MAs or a slightly modified version of a popular indicator. Instead, it offers traders a comprehensive, visually appealing, and customizable tool for technical analysis, which is both original and useful. By uniquely combining the EMA and the Stochastic Oscillator with a strong mathematical foundation, and allowing traders to adjust a variety of settings, this script adds value to the TradingView community and enhances the body of knowledge available for traders. It is designed to support traders in tailoring their analysis based on their own strategies and preferences, enabling them to make well-informed decisions in the financial markets.
MomentumIndicatorsLibrary "MomentumIndicators"
This is a library of 'Momentum Indicators', also denominated as oscillators.
The purpose of this library is to organize momentum indicators in just one place, making it easy to access.
In addition, it aims to allow customized versions, not being restricted to just the price value.
An example of this use case is the popular Stochastic RSI.
# Indicators:
1. Relative Strength Index (RSI):
Measures the relative strength of recent price gains to recent price losses of an asset.
2. Rate of Change (ROC):
Measures the percentage change in price of an asset over a specified time period.
3. Stochastic Oscillator (Stoch):
Compares the current price of an asset to its price range over a specified time period.
4. True Strength Index (TSI):
Measures the price change, calculating the ratio of the price change (positive or negative) in relation to the
absolute price change.
The values of both are smoothed twice to reduce noise, and the final result is normalized
in a range between 100 and -100.
5. Stochastic Momentum Index (SMI):
Combination of the True Strength Index with a signal line to help identify turning points in the market.
6. Williams Percent Range (Williams %R):
Compares the current price of an asset to its highest high and lowest low over a specified time period.
7. Commodity Channel Index (CCI):
Measures the relationship between an asset's current price and its moving average.
8. Ultimate Oscillator (UO):
Combines three different time periods to help identify possible reversal points.
9. Moving Average Convergence/Divergence (MACD):
Shows the difference between short-term and long-term exponential moving averages.
10. Fisher Transform (FT):
Normalize prices into a Gaussian normal distribution.
11. Inverse Fisher Transform (IFT):
Transform the values of the Fisher Transform into a smaller and more easily interpretable scale is through the
application of an inverse transformation to the hyperbolic tangent function.
This transformation takes the values of the FT, which range from -infinity to +infinity, to a scale limited
between -1 and +1, allowing them to be more easily visualized and compared.
12. Premier Stochastic Oscillator (PSO):
Normalizes the standard stochastic oscillator by applying a five-period double exponential smoothing average of
the %K value, resulting in a symmetric scale of 1 to -1
# Indicators of indicators:
## Stochastic:
1. Stochastic of RSI (Relative Strengh Index)
2. Stochastic of ROC (Rate of Change)
3. Stochastic of UO (Ultimate Oscillator)
4. Stochastic of TSI (True Strengh Index)
5. Stochastic of Williams R%
6. Stochastic of CCI (Commodity Channel Index).
7. Stochastic of MACD (Moving Average Convergence/Divergence)
8. Stochastic of FT (Fisher Transform)
9. Stochastic of Volume
10. Stochastic of MFI (Money Flow Index)
11. Stochastic of On OBV (Balance Volume)
12. Stochastic of PVI (Positive Volume Index)
13. Stochastic of NVI (Negative Volume Index)
14. Stochastic of PVT (Price-Volume Trend)
15. Stochastic of VO (Volume Oscillator)
16. Stochastic of VROC (Volume Rate of Change)
## Inverse Fisher Transform:
1.Inverse Fisher Transform on RSI (Relative Strengh Index)
2.Inverse Fisher Transform on ROC (Rate of Change)
3.Inverse Fisher Transform on UO (Ultimate Oscillator)
4.Inverse Fisher Transform on Stochastic
5.Inverse Fisher Transform on TSI (True Strength Index)
6.Inverse Fisher Transform on CCI (Commodity Channel Index)
7.Inverse Fisher Transform on Fisher Transform (FT)
8.Inverse Fisher Transform on MACD (Moving Average Convergence/Divergence)
9.Inverse Fisher Transfor on Williams R% (Williams Percent Range)
10.Inverse Fisher Transfor on CMF (Chaikin Money Flow)
11.Inverse Fisher Transform on VO (Volume Oscillator)
12.Inverse Fisher Transform on VROC (Volume Rate of Change)
## Stochastic Momentum Index:
1.Stochastic Momentum Index of RSI (Relative Strength Index)
2.Stochastic Momentum Index of ROC (Rate of Change)
3.Stochastic Momentum Index of VROC (Volume Rate of Change)
4.Stochastic Momentum Index of Williams R% (Williams Percent Range)
5.Stochastic Momentum Index of FT (Fisher Transform)
6.Stochastic Momentum Index of CCI (Commodity Channel Index)
7.Stochastic Momentum Index of UO (Ultimate Oscillator)
8.Stochastic Momentum Index of MACD (Moving Average Convergence/Divergence)
9.Stochastic Momentum Index of Volume
10.Stochastic Momentum Index of MFI (Money Flow Index)
11.Stochastic Momentum Index of CMF (Chaikin Money Flow)
12.Stochastic Momentum Index of On Balance Volume (OBV)
13.Stochastic Momentum Index of Price-Volume Trend (PVT)
14.Stochastic Momentum Index of Volume Oscillator (VO)
15.Stochastic Momentum Index of Positive Volume Index (PVI)
16.Stochastic Momentum Index of Negative Volume Index (NVI)
## Relative Strength Index:
1. RSI for Volume
2. RSI for Moving Average
rsi(source, length)
RSI (Relative Strengh Index). Measures the relative strength of recent price gains to recent price losses of an asset.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of RSI
roc(source, length)
ROC (Rate of Change). Measures the percentage change in price of an asset over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of ROC
stoch(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Stochastic Oscillator. Compares the current price of an asset to its price range over a specified time period.
Parameters:
kLength
kSmoothing : (int) Period for smoothig stochastic
dSmoothing : (int) Period for signal (moving average of stochastic)
maTypeK : (int) Type of Moving Average for Stochastic Oscillator
maTypeD : (int) Type of Moving Average for Stochastic Oscillator Signal
almaOffsetKD : (float) Offset for Arnaud Legoux Moving Average for Oscillator and Signal
almaSigmaKD : (float) Sigma for Arnaud Legoux Moving Average for Oscillator and Signal
lsmaOffSetKD : (int) Offset for Least Squares Moving Average for Oscillator and Signal
Returns: A tuple of Stochastic Oscillator and Moving Average of Stochastic Oscillator
stoch(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Stochastic Oscillator. Customized source. Compares the current price of an asset to its price range over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
kLength : (int) Period of loopback to calculate the stochastic
kSmoothing : (int) Period for smoothig stochastic
dSmoothing : (int) Period for signal (moving average of stochastic)
maTypeK : (int) Type of Moving Average for Stochastic Oscillator
maTypeD : (int) Type of Moving Average for Stochastic Oscillator Signal
almaOffsetKD : (float) Offset for Arnaud Legoux Moving Average for Stoch and Signal
almaSigmaKD : (float) Sigma for Arnaud Legoux Moving Average for Stoch and Signal
lsmaOffSetKD : (int) Offset for Least Squares Moving Average for Stoch and Signal
Returns: A tuple of Stochastic Oscillator and Moving Average of Stochastic Oscillator
tsi(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet)
TSI (True Strengh Index). Measures the price change, calculating the ratio of the price change (positive or negative) in relation to the absolute price change.
The values of both are smoothed twice to reduce noise, and the final result is normalized in a range between 100 and -100.
Parameters:
source : (float) Source of series (close, high, low, etc.)
shortLength : (int) Short length
longLength : (int) Long length
maType : (int) Type of Moving Average for TSI
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: (float) TSI
smi(sourceTSI, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
SMI (Stochastic Momentum Index). A TSI (True Strengh Index) plus a signal line.
Parameters:
sourceTSI : (float) Source of series for TSI (close, high, low, etc.)
shortLengthTSI : (int) Short length for TSI
longLengthTSI : (int) Long length for TSI
maTypeTSI : (int) Type of Moving Average for Signal of TSI
almaOffsetTSI : (float) Offset for Arnaud Legoux Moving Average
almaSigmaTSI : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSetTSI : (int) Offset for Least Squares Moving Average
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
Returns: A tuple with TSI, signal of TSI and histogram of difference
wpr(source, length)
Williams R% (Williams Percent Range). Compares the current price of an asset to its highest high and lowest low over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of Williams R%
cci(source, length, maType, almaOffset, almaSigma, lsmaOffSet)
CCI (Commodity Channel Index). Measures the relationship between an asset's current price and its moving average.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
maType : (int) Type of Moving Average
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: (float) Series of CCI
ultimateOscillator(fastLength, middleLength, slowLength)
UO (Ultimate Oscilator). Combines three different time periods to help identify possible reversal points.
Parameters:
fastLength : (int) Fast period of loopback
middleLength : (int) Middle period of loopback
slowLength : (int) Slow period of loopback
Returns: (float) Series of Ultimate Oscilator
ultimateOscillator(source, fastLength, middleLength, slowLength)
UO (Ultimate Oscilator). Customized source. Combines three different time periods to help identify possible reversal points.
Parameters:
source : (float) Source of series (close, high, low, etc.)
fastLength : (int) Fast period of loopback
middleLength : (int) Middle period of loopback
slowLength : (int) Slow period of loopback
Returns: (float) Series of Ultimate Oscilator
macd(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet)
MACD (Moving Average Convergence/Divergence). Shows the difference between short-term and long-term exponential moving averages.
Parameters:
source : (float) Source of series (close, high, low, etc.)
fastLength : (int) Period for fast moving average
slowLength : (int) Period for slow moving average
signalLength : (int) Signal length
maTypeFast : (int) Type of fast moving average
maTypeSlow : (int) Type of slow moving average
maTypeMACD : (int) Type of MACD moving average
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: A tuple with MACD, Signal, and Histgram
fisher(length)
Fisher Transform. Normalize prices into a Gaussian normal distribution.
Parameters:
length
Returns: A tuple with Fisher Transform and signal
fisher(source, length)
Fisher Transform. Customized source. Normalize prices into a Gaussian normal distribution.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length
Returns: A tuple with Fisher Transform and signal
inverseFisher(source, length, subtrahend, denominator)
Inverse Fisher Transform.
Transform the values of the Fisher Transform into a smaller and more easily interpretable scale is
through the application of an inverse transformation to the hyperbolic tangent function.
This transformation takes the values of the FT, which range from -infinity to +infinity,
to a scale limited between -1 and +1, allowing them to be more easily visualized and compared.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period for loopback
subtrahend : (int) Denominator. Useful in unbounded indicators. For example, in CCI.
denominator
Returns: (float) Series of Inverse Fisher Transform
premierStoch(length, smoothlen)
Premier Stochastic Oscillator (PSO).
Normalizes the standard stochastic oscillator by applying a five-period double exponential smoothing
average of the %K value, resulting in a symmetric scale of 1 to -1.
Parameters:
length : (int) Period for loopback
smoothlen : (int) Period for smoothing
Returns: (float) Series of PSO
premierStoch(source, smoothlen, subtrahend, denominator)
Premier Stochastic Oscillator (PSO) of custom source.
Normalizes the source by applying a five-period double exponential smoothing average.
Parameters:
source : (float) Source of series (close, high, low, etc.)
smoothlen : (int) Period for smoothing
subtrahend : (int) Denominator. Useful in unbounded indicators. For example, in CCI.
denominator
Returns: (float) Series of PSO
stochRsi(sourceRSI, lengthRSI, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
sourceRSI
lengthRSI
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochRoc(sourceROC, lengthROC, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
sourceROC
lengthROC
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochUO(fastLength, middleLength, slowLength, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
fastLength
middleLength
slowLength
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochTSI(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
shortLength
longLength
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochWPR(source, length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochCCI(source, length, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochFT(length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVolume(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochMFI(source, length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochOBV(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochPVI(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochNVI(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochPVT(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVROC(length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
iftRSI(sourceRSI, lengthRSI, lengthIFT)
Parameters:
sourceRSI
lengthRSI
lengthIFT
iftROC(sourceROC, lengthROC, lengthIFT)
Parameters:
sourceROC
lengthROC
lengthIFT
iftUO(fastLength, middleLength, slowLength, lengthIFT)
Parameters:
fastLength
middleLength
slowLength
lengthIFT
iftStoch(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD, lengthIFT)
Parameters:
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
lengthIFT
iftTSI(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
shortLength
longLength
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftCCI(source, length, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
length
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftFisher(length, lengthIFT)
Parameters:
length
lengthIFT
iftMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftWPR(source, length, lengthIFT)
Parameters:
source
length
lengthIFT
iftMFI(source, length, lengthIFT)
Parameters:
source
length
lengthIFT
iftCMF(length, lengthIFT)
Parameters:
length
lengthIFT
iftVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftVROC(length, lengthIFT)
Parameters:
length
lengthIFT
smiRSI(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiROC(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVROC(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiWPR(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiFT(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiFT(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiCCI(source, length, maTypeCCI, almaOffsetCCI, almaSigmaCCI, lsmaOffSetCCI, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
maTypeCCI
almaOffsetCCI
almaSigmaCCI
lsmaOffSetCCI
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiUO(fastLength, middleLength, slowLength, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
fastLength
middleLength
slowLength
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVol(shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiMFI(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiCMF(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiOBV(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiPVT(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiPVI(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiNVI(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
rsiVolume(length)
Parameters:
length
rsiMA(sourceMA, lengthMA, maType, almaOffset, almaSigma, lsmaOffSet, lengthRSI)
Parameters:
sourceMA
lengthMA
maType
almaOffset
almaSigma
lsmaOffSet
lengthRSI
SynthSAR ConfirmationThis indicator represents confirmation of a trend based on the PSAR indicator and includes signals from the MACD, stochastic oscillator, and awesome oscillator. It displays the points of the parabolic SAR on the chart, which help determine the direction of the trend. Additionally, the indicator allows for tracking signals based on the combined analysis of three other technical indicators: MACD, stochastic oscillator, and awesome oscillator. Furthermore, the indicator includes the ability to display buy/sell labels and signals for changing the trend direction. This is not an investment recommendation.Very effective in higher timeframes.If the MACD "macd line" crosses the "signal line" from above and the Stochastic %K line crosses the %D line from above, and the last column in the Avesome Oscillator is red, then the indicator gives a signal to sell. If the MACD "macd line" crosses the "signal line" from below and the Stochastic %K line crosses the %D line from below, and the last column in the Avesome Oscillator is green, then the indicator gives a signal to buy.
Stochastic EMA, SMA, VWMA + DivergenceEvery MetaTrader User knows the function to switch the stochastic calculation from simple to exponential.
So i took the original Stochastic code from TV and enhanced it for the SMA, EMA, and VWMA smoothing. If you are using a longer K Smoothing interval you will recognize a notable difference between SMA and EMA.
Standard Stochastic Calculation that is well kown
Option to switch smoothing calculation
Choice between Simple Moving Average, Exponential Moving Average, Volume Weighted Moving Average
If you have more wishes regarding the smoothing, just leave a comment i can add a lot more...
On my to-do list is also the divergence lines known from the "divergence indicator" (RSI).
I hope this helps to get better entries ;-)
Have fun!
