Magical SMAThis script is an intuitive trading alert system designed to identify potential entry points for both long and short positions. By utilizing a combination of Simple Moving Averages (SMA) and Ichimoku Cloud components, this script provides a robust framework for trend-following strategies.
Key Features:
SMA Crossover Detection: Monitors crossovers and crossunders between a 25-period and a 50-period SMA to signify potential bullish or bearish momentum.
Ichimoku Cloud Confirmation: Enhances the accuracy of entry signals by considering the position of the closing price relative to the Ichimoku Cloud's Lead Lines (A and B).
Long & Short Alert Conditions: Generates alert notifications for potential long and short entry signals based on the defined conditions.
Visualization: Plots the SMAs and Ichimoku Cloud components on the chart for better analysis and understanding of the prevailing market conditions.
Usage:
Long Entry Alert: Triggered when there's a crossover of the 25-period SMA above the 50-period SMA, and the closing price is above either of the Ichimoku Cloud's Lead Lines.
Short Entry Alert: Triggered when there's a crossunder of the 25-period SMA below the 50-period SMA, and the closing price is below either of the Ichimoku Cloud's Lead Lines.
This script is ideal for traders looking to capitalize on trend-following strategies with an additional layer of confirmation from the Ichimoku Cloud components. Whether you are trading equities, forex, or commodities, the "Chakibz" script is a valuable tool for identifying potential entry points and managing your trades.
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9-20 sma multi timeframe indicatorThis is an indicator to help visualizing the 9 and the 20 sma on 3 different timeframes.
When they cross, you will see a cross on the band representing the timeframe.
When a trade is favorable the band will color in green for up trend and in red for downtrend:
- Conditions in uptrend: Start after the first green candle closed above the 9 sma, Stop after the first red candle closed under the 9 sma
- Conditions in downtrend: Start after the first red candle closed below the 9 sma, Stop after the first green candle closed above the 9 sma
Machine Learning: Trend Lines [YinYangAlgorithms]Trend lines have always been a key indicator that may help predict many different types of price movements. They have been well known to create different types of formations such as: Pennants, Channels, Flags and Wedges. The type of formation they create is based on how the formation was created and the angle it was created. For instance, if there was a strong price increase and then there is a Wedge where both end points meet, this is considered a Bull Pennant. The formations Trend Lines create may be powerful tools that can help predict current Support and Resistance and also Future Momentum changes. However, not all Trend Lines will create formations, and alone they may stand as strong Support and Resistance locations on the Vertical.
The purpose of this Indicator is to apply Machine Learning logic to a Traditional Trend Line Calculation, and therefore allowing a new approach to a modern indicator of high usage. The results of such are quite interesting and goes to show the impacts a simple KNN Machine Learning model can have on Traditional Indicators.
Tutorial:
There are a few different settings within this Indicator. Many will greatly impact the results and if any are changed, lots will need ‘Fine Tuning’. So let's discuss the main toggles that have great effects and what they do before discussing the lengths. Currently in this example above we have the Indicator at its Default Settings. In this example, you can see how the Trend Lines act as key Support and Resistance locations. Due note, Support and Resistance are a relative term, as is their color. What starts off as Support or Resistance may change when the price crosses over / under them.
In the example above we have zoomed in and circled locations that exhibited markers of Support and Resistance along the Trend Lines. These Trend Lines are all created using the Default Settings. As you can see from the example above; just because it is a Green Upwards Trend Line, doesn’t mean it’s a Support Line. Support and Resistance is always shifting on Trend Lines based on the prices location relative to them.
We won’t go through all the Formations Trend Lines make, but the example above, we can see the Trend Lines formed a Downward Channel. Channels are when there are two parallel downwards Trend Lines that are at a relatively similar angle. This means that they won’t ever meet. What may happen when the price is within these channels, is it may bounce between the upper and lower bounds. These Channels may drive the price upwards or downwards, depending on if it is in an Upwards or Downwards Channel.
If you refer to the example above, you’ll notice that the Trend Lines are formed like traditional Trend Lines. They don’t stem from current Highs and Lows but rather Machine Learning Highs and Lows. More often than not, the Machine Learning approach to Trend Lines cause their start point and angle to be quite different than a Traditional Trend Line. Due to this, it may help predict Support and Resistance locations at are more uncommon and therefore can be quite useful.
In the example above we have turned off the toggle in Settings ‘Use Exponential Data Average’. This Settings uses a custom Exponential Data Average of the KNN rather than simply averaging the KNN. By Default it is enabled, but as you can see when it is disabled it may create some pretty strong lasting Trend Lines. This is why we advise you ZOOM OUT AS FAR AS YOU CAN. Trend Lines are only displayed when you’ve zoomed out far enough that their Start Point is visible.
As you can see in this example above, there were 3 major Upward Trend Lines created in 2020 that have had a major impact on Support and Resistance Locations within the last year. Lets zoom in and get a closer look.
We have zoomed in for this example above, and circled some of the major Support and Resistance locations that these Upward Trend Lines may have had a major impact on.
Please note, these Machine Learning Trend Lines aren’t a ‘One Size Fits All’ kind of thing. They are completely customizable within the Settings, so that you can get a tailored experience based on what Pair and Time Frame you are trading on.
When any values are changed within the Settings, you’ll likely need to ‘Fine Tune’ the rest of the settings until your desired result is met. By default the modifiable lengths within the Settings are:
Machine Learning Length: 50
KNN Length:5
Fast ML Data Length: 5
Slow ML Data Length: 30
For example, let's toggle ‘Use Exponential Data Averages’ back on and change ‘Fast ML Data Length’ from 5 to 20 and ‘Slow ML Data Length’ from 30 to 50.
As you can in the example above, all of the lines have changed. Although there are still some strong Support Locations created by the Upwards Trend Lines.
We will conclude our Tutorial here. Hopefully you’ve learned how to use Machine Learning Trend Lines and will be able to now see some more unorthodox Support and Resistance locations on the Vertical.
Settings:
Use Machine Learning Sources: If disabled Traditional Trend line sources (High and Low) will be used rather than Rational Quadratics.
Use KNN Distance Sorting: You can disable this if you wish to not have the Machine Learning Data sorted using KNN. If disabled trend line logic will be Traditional.
Use Exponential Data Average: This Settings uses a custom Exponential Data Average of the KNN rather than simply averaging the KNN.
Machine Learning Length: How strong is our Machine Learning Memory? Please note, when this value is too high the data is almost 'too' much and can lead to poor results.
K-Nearest Neighbour (KNN) Length: How many K-Nearest Neighbours are allowed with our Distance Clustering? Please note, too high or too low may lead to poor results.
Fast ML Data Length: Fast and Slow speed needs to be adjusted properly to see results. 3/5/7 all seem to work well for Fast.
Slow ML Data Length: Fast and Slow speed needs to be adjusted properly to see results. 20 - 50 all seem to work well for Slow.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
LBR-Volatility Breakout BarsThe originator of this script is Linda Raschke of LBR Group.
This Pine Script code is the version 5 of LBR Paintbars for TradingView, called "LBR-Bars." It was originally coded for TradingView in version 3 by LazyBear. It is a complex indicator that combines various features such as coloring bars based on different conditions, displaying Keltner channels, and showing volatility lines.
Let me break down the key components and explain how it works:
1. Inputs Section: This section defines various input parameters that users can adjust when adding the indicator to their charts. These parameters allow users to customize the behavior and appearance of the indicator. Here are some of the key input parameters:
- Users can control whether to color bars under different conditions. For example,
they can choose to color LBR bars, color bars above/below Kelts, or color non-LBR
bars.
- Users can choose whether to show volatility lines or shade Keltner channels' area
with the Mid being the moving average on the chart.
- In the calculation of Keltner channels, users can set the length of the moving
average that the Keltner channels use as the mid and then set the Keltner multiplier.
If users want to use "True Range" to determine calculations, they can turn it on or
off; it defaults to off.
- Users can change the calculation of volatility lines and set the length for finding the
lowest and highest prices. The user sets the ATR length and multiplier for the ATR.
2. Calculation Section: This section defines the calculation of the upper and lower standard deviation bands based on the input parameters. It uses Exponential Moving Averages (EMAs) and optionally True Range to calculate these bands if turned on. These bands are used in the Keltner channel calculation.
3. Keltner Channel Section: This section calculates the upper, middle, and lower lines of the Keltner channels. It also plots these lines on the chart. The colors and visibility of these lines are controlled by user inputs.
4. Volatility Lines Section: This section calculates the upper and lower volatility lines based on the lowest and highest prices over a specified period and the ATR. It also checks whether the current close price is above or below these lines accordingly. The colors and visibility of these lines are controlled by user inputs.
5. Bar Colors Section: This section determines the color of the bars on the chart based on various conditions. It checks whether the current bar meets conditions like being an LBR bar, being above or below volatility lines, or being in "No Man's Land." The color of the bars is set accordingly based on user inputs.
This Pine Script creates an indicator that provides visual cues on the chart based on Keltner channels, volatility lines, and other customizable conditions. Users can adjust the input parameters to tailor the indicator's behavior and appearance to their trading preferences.
Grospector DCA V.4This is system for DCA with strategy and can trade on trend technique "CDC Action Zone".
We upgrade Grospector DCA V.3 by minimizing unnecessary components and it is not error price predictions.
This has 5 zone Extreme high , high , normal , low , Extreme low. You can dynamic set min - max percent every zone.
Extreme zone is derivative short and long which It change Extreme zone to Normal zone all position will be closed.
Every Zone is splitted 10 channel. and this strategy calculate contribution.
and now can predict price in future.
Idea : Everything has average in its life. For bitcoin use 4 years for halving. I think it will be interesting price.
Default : I set MA is 365*4 days and average it again with 365 days.
Input :
len: This input represents the length of the moving average.
strongLen: This input represents the length of the moving average used to calculate the strong buy and strong sell zone.
shortMulti: This input represents the multiplier * moveing average used to calculate the short zone.
strongSellMulti: This input represents the multiplier used to calculate the strong sell signal.
sellMulti: This input represents the multiplier * moveing average used to calculate the sell zone.
strongBuyMulti: This input represents the multiplier used to calculate the strong sell signal.
longMulti: This input represents the multiplier * moveing average used to calculate the long zone.
*Diff sellMulti and strongBuyMulti which is normal zone.
useDerivative: This input is a boolean flag that determines whether to use the derivative display zone. If set to true, the derivative display zone will be used, otherwise it will be hidden.
zoneSwitch: This input determines where to display the channel signals. A value of 1 will display the signals in all zones, a value of 2 will display the signals in the chart pane, a value of 3 will display the signals in the data window, and a value of 4 will hide the signals.
price: Defines the price source used for the indicator calculations. The user can select from various options, with the default being the closing price.
labelSwitch: Defines whether to display assistive text on the chart. The user can select a boolean value (true/false), with the default being true.
zoneSwitch: Defines which areas of the chart to display assistive zones. The user can select from four options: 1 = all, 2 = chart only, 3 = data only, 4 = none. The default value is 2.
predictFuturePrice: Defines whether to display predicted future prices on the chart. The user can select a boolean value (true/false), with the default being true.
DCA: Defines the dollar amount to use for dollar-cost averaging (DCA) trades. The user can input an integer value, with a default value of 5.
WaitingDCA: Defines the amount of time to wait before executing a DCA trade. The user can input a float value, with a default value of 0.
Invested: Defines the amount of money invested in the asset. The user can input an integer value, with a default value of 0.
strategySwitch: Defines whether to turn on the trading strategy. The user can select a boolean value (true/false), with the default being true.
seperateDayOfMonth: Defines a specific day of the month on which to execute trades. The user can input an integer value from 1-31, with the default being 28.
useReserve: Defines whether to use a reserve amount for trading. The user can select a boolean value (true/false), with the default being true.
useDerivative: Defines whether to use derivative data for the indicator calculations. The user can select a boolean value (true/false), with the default being true.
useHalving: Defines whether to use halving data for the indicator calculations. The user can select a boolean value (true/false), with the default being true.
extendHalfOfHalving: Defines the amount of time to extend the halving date. The user can input an integer value, with the default being 200.
Every Zone: It calculate percent from top to bottom which every zone will be splited 10 step.
To effectively make the DCA plan, I recommend adopting a comprehensive strategy that takes into consideration your mindset as the best indicator of the optimal approach. By leveraging your mindset, the task can be made more manageable and adaptable to any market
Dollar-cost averaging (DCA) is a suitable investment strategy for sound money and growth assets which It is Bitcoin, as it allows for consistent and disciplined investment over time, minimizing the impact of market volatility and potential risks associated with market timing
[blackcat] L1 MartinGale Scalping Strategy**MartinGale Strategy** is a popular money management strategy used in trading. It is commonly applied in situations where the trader aims to recover from a losing streak by increasing the position size after each loss.
In the MartinGale Strategy, after a losing trade, the trader doubles the position size for the next trade. This is done in the hopes that a winning trade will eventually occur, which will not only recover the previous losses but also generate a profit.
The idea behind the MartinGale Strategy is to take advantage of the law of averages. By increasing the position size after each loss, the strategy assumes that eventually, a winning trade will occur, which will not only cover the previous losses but also generate a profit. This can be especially appealing for traders looking for a quick recovery from a losing streak.
However, it is important to note that the MartinGale Strategy carries significant risks. If a trader experiences a prolonged losing streak or lacks sufficient capital, the strategy can lead to substantial losses. The strategy's reliance on the assumption of a winning trade can be dangerous, as there is no guarantee that a winning trade will occur within a certain timeframe.
Traders considering implementing the MartinGale Strategy should carefully assess their risk tolerance and thoroughly understand the potential drawbacks. It is crucial to have a solid risk management plan in place to mitigate potential losses. Additionally, traders should be aware that the strategy may not be suitable for all market conditions and may require adjustments based on market volatility.
In summary, the MartinGale Strategy is a money management strategy that involves increasing the position size after each loss in an attempt to recover from a losing streak. While it can offer the potential for quick recovery, it also comes with significant risks that traders should carefully consider before implementing it in their trading approach.
The MartinGale Scalping Strategy is a trading strategy designed to generate profits through frequent trades. It utilizes a combination of moving average crossovers and crossunders to generate entry and exit signals. The strategy is implemented in TradingView's Pine Script language.
The strategy begins by defining input variables such as take profit and stop loss levels, as well as the trading mode (long, short, or bidirectional). It then sets a rule to allow only long entries if the trading mode is set to "Long".
The strategy logic is defined using SMA (Simple Moving Average) crossover and crossunder signals. It calculates a short-term SMA (SMA3) and a longer-term SMA (SMA8), and plots them on the chart. The crossoverSignal and crossunderSignal variables are used to track the occurrence of the crossover and crossunder events, while the crossoverState and crossunderState variables determine the state of the crossover and crossunder conditions.
The strategy execution is based on the current position size. If the position size is zero (no open positions), the strategy checks for crossover and crossunder events. If a crossover event occurs and the trading mode allows long entries, a long position is entered. The entry price, stop price, take profit price, and stop loss price are calculated based on the current close price and the SMA8 value. Similarly, if a crossunder event occurs and the trading mode allows short entries, a short position is entered with the corresponding price calculations.
If there is an existing long position and the current close price reaches either the take profit price or the stop loss price, and a crossunder event occurs, the long position is closed. The entry price, stop price, take profit price, and stop loss price are reset to zero.
Likewise, if there is an existing short position and the current close price reaches either the take profit price or the stop loss price, and a crossover event occurs, the short position is closed and the price variables are reset.
The strategy also plots entry and exit points on the chart using plotshape function. It displays a triangle pointing up for a buy entry, a triangle pointing down for a buy exit, a triangle pointing down for a sell entry, and a triangle pointing up for a sell exit.
Overall, the MartinGale Scalping Strategy aims to capture small profits by taking advantage of short-term moving average crossovers and crossunders. It incorporates risk management through take profit and stop loss levels, and allows for different trading modes to accommodate different market conditions.
Double AI Super Trend Trading - Strategy [PresentTrading]█ Introduction and How It is Different
The Double AI Super Trend Trading Strategy is a cutting-edge approach that leverages the power of not one, but two AI algorithms, in tandem with the SuperTrend technical indicator. The strategy aims to provide traders with enhanced precision in market entry and exit points. It is designed to adapt to market conditions dynamically, offering the flexibility to trade in both bullish and bearish markets.
*The KNN part is mainly referred from @Zeiierman.
BTCUSD 8hr performance
ETHUSD 8hr performance
█ Strategy, How It Works: Detailed Explanation
1. SuperTrend Calculation
The SuperTrend is a popular indicator that captures market trends through a combination of the Volume-Weighted Moving Average (VWMA) and the Average True Range (ATR). This strategy utilizes two sets of SuperTrend calculations with varying lengths and factors to capture both short-term and long-term market trends.
2. KNN Algorithm
The strategy employs k-Nearest Neighbors (KNN) algorithms, which are supervised machine learning models. Two sets of KNN algorithms are used, each focused on different lengths of historical data and number of neighbors. The KNN algorithms classify the current SuperTrend data point as bullish or bearish based on the weighted sum of the labels of the k closest historical data points.
3. Signal Generation
Based on the KNN classifications and the SuperTrend indicator, the strategy generates signals for the start of a new trend and the continuation of an existing trend.
4. Trading Logic
The strategy uses these signals to enter long or short positions. It also incorporates dynamic trailing stops for exit conditions.
Local picture
█ Trade Direction
The strategy allows traders to specify their trading direction: long, short, or both. This enables the strategy to be versatile and adapt to various market conditions.
█ Usage
ToolTips: Comprehensive tooltips are provided for each parameter to guide the user through the customization process.
Inputs: Traders can customize numerous parameters including the number of neighbors in KNN, ATR multiplier, and types of moving averages.
Plotting: The strategy also provides visual cues on the chart to indicate bullish or bearish trends.
Order Execution: Based on the generated signals, the strategy will execute buy or sell orders automatically.
█ Default Settings
The default settings are configured to offer a balanced approach suitable for most scenarios:
Initial Capital: $10,000
Default Quantity Type: 10% of equity
Commission: 0.1%
Slippage: 1
Currency: USD
These settings can be modified to suit various trading styles and asset classes.
Interactive MA Stop Loss [TANHEF]This indicator is "Interactive." Once added to the chart, you need to click the start point for the moving average stoploss. Dragging it afterward will modify its position.
Why choose this indicator over a traditional Moving Average?
To accurately determine that a wick has crossed a moving average, you must examine the moving average's range on that bar (blue area on this indicator) and ensure the wick fully traverses this area.
When the price moves away from a moving average, the average also shifts towards the price. This can make it look like the wick crossed the average, even if it didn't.
How is the moving average area calculated?
For each bar, the moving average calculation is standard, but when the current bar is involved, its high or low is used instead of the close. For precise results, simply setting the source in a typical moving average calculation to 'Low' or 'High' is not sufficient in calculating the moving average area on a current bar.
Moving Average Options:
Simple Moving Average
Exponential Moving Average
Relative Moving Average
Weighted Moving Average
Indicator Explanation
After adding indicator to chart, you must click on a location to begin an entry.
The moving average type can be set and length modified to adjust the stoploss. An optional profit target may be added.
A symbol is display when the stoploss and profit target are hit. If a position is create that is not valid, "Overlapping MA and Bar" is displayed.
Alerts
'Check' alerts to use within indicator settings (stop hit and/or profit target hit).
Select 'Create Alert'
Set the condition to 'Interactive MA''
Select create.
Alert messages can have additional details using these words in between two Curly (Brace) Brackets:
{{stop}} = MA stop-loss (price)
{{upper}} = Upper MA band (price)
{{lower}} = Lower MA band (price)
{{band}} = Lower or Upper stoploss (word)
{{type}} = Long or Short stop-loss (word)
{{stopdistance}} = Stoploss Distance (%)
{{targetdistance}} = Target Distance (%)
{{starttime}} = Start time of stoploss (day:hour:minute)
{{maLength}} = MA Length (input)
{{maType}} = MA Type (input)
{{target}} = Price target (price)
{{trigger}} = Wick or Close Trigger input (input)
{{ticker}} = Ticker of chart (word)
{{exchange}} = Exchange of chart (word)
{{description}} = Description of ticker (words)
{{close}} = Bar close (price)
{{open}} = Bar open (price)
{{high}} = Bar high (price)
{{low}} = Bar low (price)
{{hl2}} = Bar HL2 (price)
{{volume}} = Bar volume (value)
{{time}} = Current time (day:hour:minute)
{{interval}} = Chart timeframe
{{newline}} = New line for text
I will add further moving averages types in the future. If you suggestions post them below.
Market Performance TableThe Market Performance Table displays the performance of multiple tickers (up to 5) in a table format. The tickers can be customized by selecting them through the indicator settings.
The indicator calculates various metrics for each ticker, including the 1-day change percentage, whether the price is above the 50, 20, and 10-day simple moving averages (SMA), as well as the relative strength compared to the 10/20 SMA and 20/50 SMA crossovers. It also calculates the price deviation from the 50-day SMA.
The table is displayed on the chart and can be positioned in different locations.
Credits for the idea to @Alex_PrimeTrading ;)
Donchian MA Bands [LuxAlgo]The Donchian MA Bands script is a complete trend indicator derived from the popular Donchian channel indicator as well as various customizable moving averages to estimate trend direction and build support/resistance levels & zones.
🔶 USAGE
The indicator outputs various elements, the main ones being a lower dynamic zone (blue by default), an upper dynamic zone (in orange by default), and one support and resistance level/zones (red/green by default).
A prominent lower zone is indicative of an uptrend, while a prominent upper zone is indicative of a downtrend. These zones can be used as support/resistance as well.
Support/resistance zones and levels can be used using a breakout methodology or to determine price bounced if a level was tested multiple times.
The indicator contains various modes affecting the output of the indicator, described below.
🔹 Clouds
Clouds return one upper/lower dynamic zone and look/act similarly to a trailing stop. Price over the lower zone is indicative of an uptrend, and price under the upper zone is indicative of a downtrend.
🔹 Upper Band
The upper band mode returns a dynamic zone closer to prices during an uptrend, and farther away during a downtrend.
This band can act as a support during uptrends.
🔹 Lower Band
The lower band mode returns a dynamic zone closer to prices during an uptrend, and farther away during a downtrend.
This band can act as a resistance during downtrends.
🔹 Bands
Bands return both upper and lower zones, the zones are more apparent depending on the price trend direction, with uptrends being indicated by a more visible lower zone, and downtrends being indicated by a more visible upper zone.
Breakout dots are highlighted when price breakout the indicator displayed extremities, and can be indicative of a confirmed trend reversal.
These breakouts can be more effective for trend following during trending markets. Ranging markets might return breakouts highlighting the top/bottom.
🔶 DETAILS
The core of this script is the highest / lowest mean average (MA) value for a given number of bars back ( Donchian lines).
This is repeated a few times with the obtained values.
When Bands are chosen ( Style ) this will be repeated 1 more time.
The type of mean average can be customized ( Type MA ), as well as the number of bars back ( Length ).
Depending on the choice of bands ( Style ) the script will focus on certain area's of interest.
When the option Clouds , Upper band or Lower band is chosen, an extra feature, support/resistance (S/R), will be shown.
These color-filled areas are visible when there is a difference between the 2nd and 3rd highest/lowest values.
The lines/areas can be used for stop loss, entry, exit,...
You can set the type of MA and Length separately ( Settings -> S/R ).
If you don't need this feature, simply set Type ( Settings -> S/R ) -> NONE
The shape sometimes resembles triangles, indicating a potential direction
Default the average of the highest and lowest values is plotted (Style -> Mid Donchian)
This can act as potential support/resistance or visualization of the trend, the mean average is not plotted but can be (Style -> MA)
🔹 Note
When the option Bands is chosen, an indication is plotted when the closing price breaks above the highest band or breaks below the lower band. This isn't necessarily a buy/sell signal, it is merely a signal that these lines are broken.
Users should decide on their own how they use the bands/lines/areas as entry, exit, trailing stop, stop loss, profit taking,...
🔶 SETTINGS
🔹 Bands
Style: Clouds (default), Upper band, Lower band, Bands
Type MA: choose between SMA, EMA, RMA, HullMA, WMA, VWMA (default), DEMA, TEMA, NONE (off)
Length: Length of moving average and Donchian calculations (default 20)
Colour Bands
🔹 S/R (Support/Resistance, visible with Clouds, Upper band or Lower band)
Type MA: choose between SMA, EMA, RMA, HullMA, WMA, VWMA (default), DEMA, TEMA, NONE (off)
Length: Length of moving average and Donchian calculations (default 20)
Colour S/R
RSI + Fibonacci HH LL Support Resistance I have integrated my past scripts and brushed them up further.
This tool allows for support/resistance, stop loss, take profit, and trend analysis using RSI and Fibonacci ratios.
For example, the Fibonacci ratio is used as follows
l1 = m - dist * 0.618
l2 = m - dist * 1.618
l3 = m - dist * 2.618
l4 = m - dist * 4.235
l5 = m - dist * 6.857
l6 = m - dist * 11.089
When the Fibonacci ratio reaches 2.618 or higher and the RSI smoothed by the 5-day EMA is oversold/overbought, the bar color is changed by a gradation.
We have tried to make the design as beautiful and good-looking as possible. You can also hide the lines to suit your own preference.
Example usages are here:
BTCUSDT 1Hour Chart
Using Fibonacci numbers
BTCUSDT 15min Chart, for Scalping
Here, to set the highest and lowest prices one hour ago, "4" is substituted as the calculation: 15 minutes x 4 = 60
BTCUSDT 15min Chart, for Scalping
To set the highest and lowest prices 4 hours ago , "4" is substituted as the calculation: 15 minutes x 16 = 240
BTCUSDT 15min Chart, for Scalping
To draw yesterday's high and low as support/resistance lines, I substituted the number "96" as 1440/15=96.
BTCUSDT 1min Chart, for Scalping
Substituted "60" to trail the highest and lowest prices over a 60-minute period on a 1-minute chart, and removed lines to beautify
BTCUSDT 1day Chart, for Long-Term Investers
This is an example of using "90" because it is a 1-day chart and assumes that 3 months = 90 days in order to trail the highest and lowest prices over a 3-month period and no lines.
My past scripts are here:
RSI + FIB HH LL StopLoss Finder／Contrarian Trades
Fibonacci HH LL TRAMA Band
MA RSI @KINGThis Pine Script is designed to create a trading indicator with moving averages (MA) and relative strength index (RSI), along with arrow signals and background color changes based on those signals. Here's a description of its functions:
1. Moving Averages and RSI Calculation:
- Two moving averages (`fastMA` and `slowMA`) are calculated based on user-input lengths.
- The Relative Strength Index (`rsi`) is calculated based on a user-defined length.
2. Crossover Conditions:
- `crossoverUp` is true when the fastMA crosses above the slowMA and RSI is above an overbought level.
- `crossoverDown` is true when the fastMA crosses below the slowMA and RSI is below an oversold level.
3. Arrow Signals:
- Triangle-shaped arrows (`arrowUp` and `arrowDown`) are plotted below and above bars, indicating buy (green) and sell (red) signals, respectively.
4. Background Color Changes:
- The background color (`bgColor`) changes based on buy and sell signals.
- If there's a buy signal (`crossoverUp`), the background color is set to a light blue with 40% transparency.
- If there's a sell signal (`crossoverDown`), the background color is set to a light red with 40% transparency.
- On the next opposite signal, the background color is scaled up (transparency set to 80%) to indicate a stronger signal.
In summary, this script provides visual cues through arrows and background color changes to assist traders in identifying potential buy and sell signals based on moving average crossovers and RSI conditions. The background color variations aim to highlight the strength of the signal, with scaling based on consecutive signals in the same direction.
********************************************************************************
1. Buy Signal:
- Condition: The arrow points up (green) with a background color indicating a buy signal.
- Confirmation: Ensure that there is a strong upward crossover (fastMA above slowMA) and RSI is above the overbought level.
2. Sell Signal:
- Condition: The arrow points down (red) with a background color indicating a sell signal.
- Confirmation: Ensure that there is a strong downward crossover (fastMA below slowMA) and RSI is below the oversold level.
3. Exit Signal:
- Condition: No arrow is present, and the background color is reset.
- Confirmation: Confirm that there is no active buy or sell signal.
Example Trading Rules:
Opening a Long Position (Buy):
- Enter a long (buy) position when:
- The green arrow appears with a light blue background.
- Confirm that the fastMA is above the slowMA.
- Confirm that RSI is above the overbought level.
Opening a Short Position (Sell):
- Enter a short (sell) position when:
- The red arrow appears with a light red background.
- Confirm that the fastMA is below the slowMA.
- Confirm that RSI is below the oversold level.
Exiting a Position:
- Close the position when:
- There is no arrow present (neither green nor red).
- The background color is reset, indicating no active signal.
Risk Management:
Position Sizing: Determine the size of your positions based on your risk tolerance and the size of your trading account.
Stop-Loss and Take-Profit: Set stop-loss orders to limit potential losses and take-profit orders to secure profits.
Risk-Reward Ratio: Consider maintaining a favorable risk-reward ratio in your trades.
Notes:
Backtesting: Before applying this strategy in a live market, it's crucial to backtest it using historical data to assess its performance.
Market Conditions: Adapt the strategy to different market conditions, and be aware that no strategy is guaranteed to be profitable.
Continuous Monitoring: Regularly monitor the performance of the strategy and make adjustments as needed.
Educational Purpose: This strategy is for educational purposes only. Always consult with financial professionals and use your judgment when making trading decisions.
Remember that trading involves risk, and past performance is not indicative of future results. It's recommended to paper trade or use a demo account to test the strategy before risking real capital.
Best wishes on your trading journey! May your strategies be profitable, your risks well-managed, and your decisions guided by wisdom and success. Happy trading!
2Mars strategy [OKX]The strategy is based on the intersection of two moving averages, which requires adjusting the parameters (ratio and multiplier) for the moving average.
Basis MA length: multiplier * ratio
Signal MA length: multiplier
The SuperTrend indicator is used for additional confirmation of entry into a position.
Bollinger Bands and position reversal are used for take-profit.
About stop loss:
If activated, the stop loss price will be updated on every entry.
Basic setup:
Additional:
Alerts for OKX:
Optimal Moving Average (AI/ML) [wbburgin]Some traders swear by the 200-period moving average. Others, by the 100-period. Others, the 14-period. It depends on your asset, your timeframe, the trend…
The fact of the matter is that no moving average will ever be a consistent indicator for a serious trader - a fixed-length moving average will always need confirmation indicators and tests. When your instrument is trending, you need a faster moving average to better fit the data; when your instrument is ranging, you need a slower moving average that cleans the data. This just is not possible given the way the moving average is traditionally coded, which makes it a lagging indicator.
Thus we need a moving average that:
can project the next prices, and
can change its length depending on what best fits these future prices.
The Optimal Moving Average selects the optimal moving average length for a projected future price. The algorithm classifies moving averages by their effectiveness in predicting future price movement. If a moving average of length n has historically been accurate in predicting the next bar, the moving average will be tested compared to its peers ( n -1, n +5, n -100, etc.) and promoted or demoted depending on its effectiveness. This means that the indicator will not have a length input like other static moving averages or machine-learning moving averages on TradingView- it will select the ideal length for your chart from the average that has the least error and best prediction.
Advantages over other ML Moving Averages on TradingView
The vast majority of AI/ML moving average algorithms classify their moving averages only by if the average is above or below the current price.
This approach is inherently flawed because the model
Is not predictive of future prices (the structural lagging problem still exists),
Is not built on a variable-length MA (cannot select alternating lengths depending on the bar), and
does not classify the scale of difference between the MA and the price.
This indicator solves all those problems. It classifies moving averages by the scale of which their rate predicts the next price. Thus it is quick to catch trend changes but also acts as support or resistance, and models the projected price more accurately than a traditional moving average.
Multi Timeframe Indicator Signals [pAulseperformance]█ Concept:
In this TradingView Pine Script publication, we introduce a powerful tool that offers extensive capabilities for traders and analysts. With a focus on combining multiple indicators, analyzing various timeframes, and fine-tuning your trading strategies, this tool empowers you to make informed trading decisions.
█ Key Features:
1. Combining Multiple Rules with AND / OR Operations
• Example: You can combine the Relative Strength Index (RSI) with the Moving Average Convergence Divergence (MACD) by selecting the "AND" operation. This ensures that you only get a signal when both indicators generate signals. Alternatively, you can add custom indicators and select "OR" to create more complex strategies.
2. Selecting Multiple Indicators on Different Timeframes
• Analyze the same indicator on different timeframes to get a comprehensive view of market conditions.
3. Reversing Signals
• Reverse signals generated by indicators to adapt to various market conditions and strategies.
4. Extending Signals
• Extend signals by specifying conditions such as "RSI cross AND MA cross WITHIN 2 bars."
5. Feeding Results into Backtesting Engine
• Evaluate the performance of your strategies by feeding the results into a backtesting engine.
█ Available Indicators:
External Inputs
• Combine up to 4 custom indicators to assess their effectiveness individually and in combination with other indicators.
MACD (Moving Average Convergence Divergence)
• Analyze MACD signals across multiple timeframes and customize your strategies.
• Signal Generators:
• Signal 1: 🔼 (+1) MACD ⤯ MACD Signal Line 🔽 (-1) MACD ⤰ MACD Signal Line
• Signal 2: 🔼 (+1) MACD ⤯ 0 🔽 (-1) MACD ⤰ 0
• Filter 1: 🔼 (+1) MACD > 0 🔽 (-1) MACD < 0
RSI (Relative Strength Index)
• Utilize RSI signals with flexibility across different timeframes.
• Signal Generators:
• Signal 1: 🔼 (+1) RSI ⤯ Oversold 🔽 (-1) RSI ⤰ Overbought
• Signal 2: 🔼 (+1) RSI ⤰ Oversold 🔽 (-1) RSI ⤯ Overbought
• Filter 1: 🔼 (+1) RSI <= Oversold 🔽 (-1) RSI >= Overbought
MA1 and MA2 (Moving Averages)
• Choose from various types of moving averages and analyze them across multiple timeframes.
• Signal Generators:
• Filter 1: 🔼 (+1) Source Above MA 🔽 (-1) Source Below MA
• Filter 2: 🔼 (+1) MA Rising 🔽 (-1) MA Falling
• Signal 1: 🔼 (+1) Source ⤯ MA 🔽 (-1) Source ⤰ MA
Bollinger Bands
• Multi Time Frame
• Signal Generators:
• Signal 1: 🔼 (+1) Close ⤯ BBLower 🔽 (-1) Close ⤰ BBUpper
• Signal 2: 🔼 (+1) Close ⤰ BBLower 🔽 (-1) Close ⤯ BBUpper
Stochastics
• Customize your MTF Stochastics analysis between Normal Stochastic and Stochastic RSI.
• Signal Generators:
• Filter 1: 🔼 (+1) K < OS 🔽 (-1) K > OB
• Signal 1: 🔼 (+1) K ⤯ D 🔽 (-1) K ⤰ D
• Signal 2: 🔼 (+1) K ⤯ OS 🔽 (-1) K ⤰ OB
• Signal 3: 🔼🔽 Filter 1 And Signal 1
Ichimoku Cloud
• MTF
• Signal Generators:
• Signal 1: 🔼 (+1) Close ⤯ Komu Cloud 🔽 (-1) Close ⤰ Komu Cloud
• Signal 2: 🔼 (+1) Kumo Cloud Red -> Green 🔽 (-1) Kumo Cloud Green -> Red
• Signal 3: 🔼 (+1) Close ⤯ Kijun Sen 🔽 (-1) Close ⤰ Kijun Sen
• Signal 4: 🔼 (+1) Tenkan Sen ⤯ Kijun Sen 🔽 (-1) Tenkan Sen ⤰ Kijun Sen
SuperTrend
• MTF
• Signal Generators:
• Signal 1: 🔼 (+1) Close ⤯ Supertrend 🔽 (-1) Close ⤰ Supertrend
• Filter 1: 🔼 (+1) Close > Supertrend 🔽 (-1) Close < Supertrend
Support And Resistance
• Receive signals when support/resistance levels are breached.
Price Action
• Analyze price action across various timeframes.
• Signal Generators:
• Signal 1 (Bar Up/Dn): 🔼 (+1) Close > Open 🔽 (-1) Close < Open
• Signal 2 (Consecutive Up/Dn): 🔼 (+1) Close > Previous Close # 🔽 (-1) Close < Previous Close #
• Signal 3 (Gaps): 🔼 (+1) Open > Previous High 🔽 (-1) Open < Previous Low
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Unlock the full potential of these indicators and tools to enhance your trading strategies and improve your decision-making process. With over 10 indicators and more than 30 different ways to generate signals you can rapidly test combinations of popular indicators and their strategies with ease. If your interested in more indicators or I missed a strategy, leave a comment and I can add it in the next update.
Happy trading!
