Trailing Stop Loss SuperTrendThe Trailing Stop Loss SuperTrend indicator is a popular technical analysis tool used by traders to identify trends and determine optimal entry and exit points in financial markets. This indicator combines elements of the SuperTrend indicator and trailing stop loss orders to provide valuable insights into market trends and potential reversals. By incorporating Average True Range (ATR) calculations, it adapts to market volatility, making it suitable for various trading strategies. Let's explore the key use cases and benefits of the Trailing Stop Loss SuperTrend indicator:
Trend Identification:
The primary purpose of the Trailing Stop Loss SuperTrend indicator is to identify market trends. It plots two lines on the chart: an upper band (referred to as the "up" line) and a lower band (referred to as the "dn" line). The direction of these bands helps traders determine the prevailing trend. When the price is above the upper band, it suggests a bullish trend, and when it is below the lower band, it indicates a bearish trend.
Entry and Exit Signals:
The Trailing Stop Loss SuperTrend indicator generates entry and exit signals based on trend changes. When the trend changes from bearish to bullish, a buy signal is triggered, indicating a potential entry point. Conversely, when the trend changes from bullish to bearish, a sell signal is generated, suggesting a possible exit or short-selling opportunity. These signals can be used in conjunction with other trading strategies or indicators to enhance trading decisions.
Trailing Stop Loss Orders:
One of the distinguishing features of the Trailing Stop Loss SuperTrend indicator is its ability to incorporate trailing stop loss orders. Traders can use the indicator's upper and lower bands as trailing stop levels to protect profits and manage risk. For example, in a bullish trend, the stop loss level can be set at the lower band, and as the price rises, the stop loss level trails along with it, locking in profits and reducing potential losses.
Volatility Adaptation:
By incorporating the ATR (Average True Range) calculation, the Trailing Stop Loss SuperTrend indicator adjusts its sensitivity to market volatility. A higher ATR multiplier widens the distance between the price and the bands, accommodating higher volatility, while a lower multiplier tightens the bands during periods of lower volatility. This adaptability makes the indicator versatile and suitable for various market conditions.
Alerts and Notifications:
The Trailing Stop Loss SuperTrend indicator provides the ability to set alerts for specific events, such as trend changes, buy signals, and sell signals. Traders can receive real-time notifications via email, SMS, or on-platform alerts, ensuring they stay informed about potential trading opportunities and important market developments.
Conclusion:
The Trailing Stop Loss SuperTrend indicator is a valuable tool for traders seeking to identify trends, generate entry and exit signals, and effectively manage risk. Its ability to adapt to market volatility and incorporate trailing stop loss orders enhances trading strategies and decision-making. By combining the SuperTrend concept with trailing stop loss functionality, this indicator provides traders with a comprehensive approach to trend analysis and risk management. Whether used in isolation or in conjunction with other indicators, the Trailing Stop Loss SuperTrend indicator offers a powerful tool for navigating the dynamic world of financial markets.
在脚本中搜索"entry"
Edri Extreme Points Buy & SellEDRI EXTREME POINTS BUY & SELL INDICATOR
This Buy and Sell (non-repainting) indicator uses signals based on the combined CCI/Momentum and RSI indicators and optional regular divergence.
The idea of the indicator is to look for a potential reversal after the price reached extreme points (overbought or oversold) and signals an entry when the price shows signs of momentum for reversal.
Optionally, it considers finding a divergence while RSI is at the extreme levels to improve the predictability of a possible reversal.
Additionally, the indicator includes a simple Mean Reversion visual on the chart to assist users in identifying extreme price levels and potential reversal opportunities. It features upper and lower bands that can be optionally plotted, showing calculated values where price bounces at those extreme levels.
The purpose of these bands is to help traders avoid getting trapped in the middle of a trend and to guide them to buy low and sell high. (It's important to note that this is purely a visual aid and does not impact the generation of trade signals.)
By utilizing the Mean Reversion bands alongside the entry conditions, traders can gain insights into potential price reversals and make more informed decisions about when to enter or exit trades.
Buy and Sell Entry conditions:
• The indicator looks at the CCI/Momentum indicator to turn positive (if buy) or negative (if sell) after the RSI was overbought or oversold in the recent past.
• It also checks if there is a 3-period regular bullish divergence in the RSI (if buy), or regular bearish divergence (if sell) and consider these in the entry condition.
• If these conditions are met, this indicator suggests that it may be a good time to enter a trade.
In summary this is how this indicator works:
• The indicator takes input settings such as the choice between using CCI or Momentum as the entry signal source, length parameters for CCI/Momentum, RSI levels for overbought and oversold conditions, RSI length, and options to plot mean reversion bands on the chart.
• It calculates the CCI and Momentum and RSI values based on user-defined length..
• It checks for regular bullish and bearish divergences (3 periods) in the RSI if the option is enabled.
• The script plots shapes on the chart to indicate the buy and sell signals based on the entry conditions.
• If the mean reversion bands option is enabled, it calculates the mean reversion, standard deviation, upper band, and lower band values.
• It also plots the upper band, mean reversion line, and lower band on the chart if the mean reversion bands option is enabled.
• This indicator includes alert conditions to generate alerts for the buy and sell signals.
• On top of that, users can opt to use only one alert for both buy and sell signals. (This can save Trading view subscribers with limited alerts.)
Important! Please do not consider everything you read here as financial advice. Additionally, do not rely solely on indicators for making your trading decisions. It is important to note that no indicator or strategy is perfect. Therefore, it is always recommended to backtest everything and practice proper risk management.
I appreciate your feedback on this indicator. As I am new to script development, I am open to comments and suggestions to improve it. If you encounter any issues while using this indicator, please let me know in the comments section. If you find it helpful, I kindly ask for your support in boosting it. Thank you for your cooperation.
ATR GOD Strategy by TradeSmart (PineConnector-compatible)This is a highly-customizable trading strategy made by TradeSmart, focusing mainly on ATR-based indicators and filters. The strategy is mainly intended for trading forex , and has been optimized using the Deep Backtest feature on the 2018.01.01 - 2023.06.01 interval on the EUR/USD (FXCM) 15M chart, with a Slippage value of 3, and a Commission set to 0.00004 USD per contract. The strategy is also made compatible with PineConnector , to provide an easy option to automate the strategy using a connection to MetaTrader. See tooltips for details on how to set up the bot, and check out our website for a detailed guide with images on how to automate the strategy.
The strategy was implemented using the following logic:
Entry strategy:
A total of 4 Supertrend values can be used to determine the entry logic. There is option to set up all 4 Supertrend parameters individually, as well as their potential to be used as an entry signal/or a trend filter. Long/Short entry signals will be determined based on the selected potential Supertrend entry signals, and filtered based on them being in an uptrend/downtrend (also available for setup). Please use the provided tooltips for each setup to see every detail.
Exit strategy:
4 different types of Stop Losses are available: ATR-based/Candle Low/High Based/Percentage Based/Pip Based. Additionally, Force exiting can also be applied, where there is option to set up 4 custom sessions, and exits will happen after the session has closed.
Parameters of every indicator used in the strategy can be tuned in the strategy settings as follows:
Plot settings:
Plot Signals: true by default, Show all Long and Short signals on the signal candle
Plot SL/TP lines: false by default, Checking this option will result in the TP and SL lines to be plotted on the chart.
Supertrend 1-4:
All the parameters of the Supertrends can be set up here, as well as their individual role in the entry logic.
Exit Strategy:
ATR Based Stop Loss: true by default
ATR Length (of the SL): 100 by default
ATR Smoothing (of the SL): RMA/SMMA by default
Candle Low/High Based Stop Loss: false by default, recent lowest or highest point (depending on long/short position) will be used to calculate stop loss value. Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Candle Lookback (of the SL): 50 by default
Percentage Based Stop Loss: false by default, Set the stop loss to current price - % of current price (long) or price + % of current price (short).
Percentage (of the SL): 0.3 by default
Pip Based Stop Loss: Set the stop loss to current price - x pips (long) or price + x pips (short). Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Pip (of the SL): 10 by default
Base Risk Multiplier: 4.5 by default, the stop loss will be placed at this risk level (meaning in case of ATR SL that the ATR value will be multiplied by this factor and the SL will be placed that value away from the entry level)
Risk to Reward Ratio: 1.5 by default, the take profit level will be placed such as this Risk/Reward ratio is met
Force Exiting:
4 total Force exit on custom session close options: none applied by default. If enabled, trades will close automatically after the set session is closed (on next candle's open).
Base Setups:
Allow Long Entries: true by default
Allow Short Entries: true by default
Order Size: 10 by default
Order Type: Capital Percentage by default, allows adjustment on how the position size is calculated: Cash: only the set cash amount will be used for each trade Contract(s): the adjusted number of contracts will be used for each trade Capital Percentage: a % of the current available capital will be used for each trade
ATR Limiter:
Use ATR Limiter: true by default, Only enter into any position (long/short) if ATR value is higher than the Low Boundary and lower than the High Boundary.
ATR Limiter Length: 50 by default
ATR Limiter Smoothing: RMA/SMMA by default
High Boundary: 1000 by default
Low Boundary: 0.0003 by default
MA based calculation: ATR value under MA by default, If not Unspecified, an MA is calculated with the ATR value as source. Only enter into position (long/short) if ATR value is higher/lower than the MA.
MA Type: RMA/SMMA by default
MA Length: 400 by default
Waddah Attar Filter:
Explosion/Deadzone relation: Not specified by default, Explosion over Deadzone: trades will only happen if the explosion line is over the deadzone line; Explosion under Deadzone: trades will only happen if the explosion line is under the deadzone line; Not specified: the opening of trades will not be based on the relation between the explosion and deadzone lines.
Limit trades based on trends: Not specified by default, Strong Trends: only enter long if the WA bar is colored green (there is an uptrend and the current bar is higher then the previous); only enter short if the WA bar is colored red (there is a downtrend and the current bar is higher then the previous); Soft Trends: only enter long if the WA bar is colored lime (there is an uptrend and the current bar is lower then the previous); only enter short if the WA bar is colored orange (there is a downtrend and the current bar is lower then the previous); All Trends: only enter long if the WA bar is colored green or lime (there is an uptrend); only enter short if the WA bar is colored red or orange (there is a downtrend); Not specified: the color of the WA bar (trend) is not relevant when considering entries.
WA bar value: Not specified by default, Over Explosion and Deadzone: only enter trades when the WA bar value is over the Explosion and Deadzone lines; Not specified: the relation between the explosion/deadzone lines to the value of the WA bar will not be used to filter opening trades.
Sensitivity: 150 by default
Fast MA Type: SMA by default
Fast MA Length: 10 by default
Slow MA Type: SMA
Slow MA Length: 20 by default
Channel MA Type: EMA by default
BB Channel Length: 20 by default
BB Stdev Multiplier: 2 by default
Trend Filter:
Use long trend filter 1: false by default, Only enter long if price is above Long MA.
Show long trend filter 1: false by default, Plot the selected MA on the chart.
TF1 - MA Type: EMA by default
TF1 - MA Length: 120 by default
TF1 - MA Source: close by default
Use short trend filter 1: false by default, Only enter long if price is above Long MA.
Show short trend filter 1: false by default, Plot the selected MA on the chart.
TF2 - MA Type: EMA by default
TF2 - MA Length: 120 by default
TF2 - MA Source: close by default
Volume Filter:
Only enter trades where volume is higher then the volume-based MA: true by default, a set type of MA will be calculated with the volume as source, and set length
MA Type: RMA/SMMA by default
MA Length: 200 by default
Date Range Limiter:
Limit Between Dates: false by default
Start Date: Jan 01 2023 00:00:00 by default
End Date: Jun 24 2023 00:00:00 by default
Session Limiter:
Show session plots: false by default, show market sessions on chart: Sidney (red), Tokyo (orange), London (yellow), New York (green)
Use session limiter: false by default, if enabled, trades will only happen in the ticked sessions below.
Sidney session: false by default, session between: 15:00 - 00:00 (EST)
Tokyo session: false by default, session between: 19:00 - 04:00 (EST)
London session: false by default, session between: 03:00 - 11:00 (EST)
New York session: false by default, session between: 08:00 - 17:00 (EST)
Trading Time:
Limit Trading Time: true by default, tick this together with the options below to enable limiting based on day and time
Valid Trading Days Global: 123567 by default, if the Limit Trading Time is on, trades will only happen on days that are present in this field. If any of the not global Valid Trading Days is used, this field will be neglected. Values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) To trade on all days use: 123457
(1) Valid Trading Days: false, 123456 by default, values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) The script will trade on days that are present in this field. Please make sure that this field and also (1) Valid Trading Hours Between is checked
(1) Valid Trading Hours Between: false, 1800-2000 by default, hours between which the trades can happen. The time is always in the exchange's timezone
All other options are also disabled by default
PineConnector Automation:
Use PineConnector Automation: false by default, In order for the connection to MetaTrader to work, you will need do perform prerequisite steps, you can follow our full guide at our website, or refer to the official PineConnector Documentation. To set up PineConnector Automation on the TradingView side, you will need to do the following:
1. Fill out the License ID field with your PineConnector License ID;
2. Fill out the Risk (trading volume) with the desired volume to be traded in each trade (the meaning of this value depends on the EA settings in Metatrader. Follow the detailed guide for additional information);
3. After filling out the fields, you need to enable the 'Use PineConnector Automation' option (check the box in the strategy settings);
4. Check if the chart has updated and you can see the appropriate order comments on your chart;
5. Create an alert with the strategy selected as Condition, and the Message as {{strategy.order.comment}} (should be there by default);
6. Enable the Webhook URL in the Notifications section, set it as the official PineConnector webhook address and enjoy your connection with MetaTrader.
License ID: 60123456789 by default
Risk (trading volume): 1 by default
NOTE! Fine-tuning/re-optimization is highly recommended when using other asset/timeframe combinations.
lib_logLibrary "lib_log"
library for logging and debugging pine scripts
method init(this)
Namespace types: Logger
Parameters:
this (Logger)
method debug(this, message, condition)
Namespace types: Logger
Parameters:
this (Logger) : Logger to add the entry to
message (string) : The Message to add
condition (bool) : optional flag to enable disable logging of this entry dynamically (default: true)
method info(this, message, condition)
Namespace types: Logger
Parameters:
this (Logger) : Logger to add the entry to
message (string) : The Message to add
condition (bool) : optional flag to enable disable logging of this entry dynamically (default: true)
method success(this, message, condition)
Namespace types: Logger
Parameters:
this (Logger) : Logger to add the entry to
message (string) : The Message to add
condition (bool) : optional flag to enable disable logging of this entry dynamically (default: true)
method warning(this, message, condition)
Namespace types: Logger
Parameters:
this (Logger) : Logger to add the entry to
message (string) : The Message to add
condition (bool) : optional flag to enable disable logging of this entry dynamically (default: true)
method error(this, message, condition)
Namespace types: Logger
Parameters:
this (Logger) : Logger to add the entry to
message (string) : The Message to add
condition (bool) : optional flag to enable disable logging of this entry dynamically (default: true)
method debug_bar(this, message, bar, y, y_offset, last_only, condition)
Namespace types: Logger
Parameters:
this (Logger) : Logger object to check global min level condition
message (string) : The string to print
bar (int) : The bar to print the label at (default: bar_index)
y (float) : The price value to print at (default: high)
y_offset (float) : A price offset from y if you want to print multiple labels at the same spot
last_only (bool)
condition (bool)
method info_bar(this, message, bar, y, y_offset, last_only, condition)
Namespace types: Logger
Parameters:
this (Logger) : Logger object to check global min level condition
message (string) : The string to print
bar (int) : The bar to print the label at (default: bar_index)
y (float) : The price value to print at (default: high)
y_offset (float) : A price offset from y if you want to print multiple labels at the same spot
last_only (bool)
condition (bool)
method success_bar(this, message, bar, y, y_offset, last_only, condition)
Namespace types: Logger
Parameters:
this (Logger) : Logger object to check global min level condition
message (string) : The string to print
bar (int) : The bar to print the label at (default: bar_index)
y (float) : The price value to print at (default: high)
y_offset (float) : A price offset from y if you want to print multiple labels at the same spot
last_only (bool)
condition (bool)
method warning_bar(this, message, bar, y, y_offset, last_only, condition)
Namespace types: Logger
Parameters:
this (Logger) : Logger object to check global min level condition
message (string) : The string to print
bar (int) : The bar to print the label at (default: bar_index)
y (float) : The price value to print at (default: high)
y_offset (float) : A price offset from y if you want to print multiple labels at the same spot
last_only (bool)
condition (bool)
method error_bar(this, message, bar, y, y_offset, last_only, condition)
Namespace types: Logger
Parameters:
this (Logger) : Logger object to check global min level condition
message (string) : The string to print
bar (int) : The bar to print the label at (default: bar_index)
y (float) : The price value to print at (default: high)
y_offset (float) : A price offset from y if you want to print multiple labels at the same spot
last_only (bool)
condition (bool)
LogEntry
Fields:
timestamp (series__integer)
bar (series__integer)
level (series__integer)
message (series__string)
Logger
Fields:
min_level (series__integer)
color_logs (series__bool)
max_lines (series__integer)
line_idx (series__integer)
table_pos (series__string)
display (series__table)
log (array__|LogEntry|#OBJ)
Risk ManagementLibrary "RiskManagement"
This library keeps your money in check, and is used for testing and later on webhook-applications too. It has four volatility functions and two of them can be used to calculate a Stop-Loss, like Average True Range. It also can calculate Position Size, and the Risk Reward Ratio. But those calculations don't take leverage into account.
position_size(portfolio, risk, entry, stop_loss, use_leverage, qty_as_integer)
This function calculates the definite amount of contracts/shares/units you should use to buy or sell. This value can used by `strategy.entry(qty)` for example.
Parameters:
portfolio (float) : This is the total amount of the currency you own, and is also used by strategy.initial_capital, for example. The amount is needed to calculate the maximum risk you are willing to take per trade.
risk (float) : This is the percentage of your Portfolio you willing to loose on a single trade. Possible values are between 0.1 and 100%. Same usecase with strategy(default_qty_type=strategy.percent_of_equity,default_qty_value=100), except its calculation the risk only.
entry (float) : This is the limit-/market-price for the investment. In other words: The price per contract/share/unit you willing to buy or sell.
stop_loss (float) : This is the limit-/market-price when to exit the trade, to minimize your losses.
use_leverage (bool) : This value is optional. When not used or when set to false then this function will let you invest your portfolio at max.
qty_as_integer (bool) : This value is optional. When set to true this function will return a value used with integers. The largest integer less than or equal to the given number. Because some Broker/Exchanges let you trade hole contracts/shares/units only.
Returns: float
position_size_currency(portfolio, risk, entry, stop_loss)
This function calculates the definite amount of currency you should use when going long or short.
Parameters:
portfolio (float) : This is the total amount of the currency you own, and is also used by strategy.initial_capital, for example. The amount is needed to calculate the maximum risk you are willing to take per trade.
risk (float) : This is the percentage of your Portfolio you willing to loose on a single trade. For example: 1 is 100% and 0,01 is 1%. Default amount is 0.02 (2%).
entry (float) : This is the limit-/market-price for the current investment. In other words: The price per contract/share/units you willing to buy or sell.
stop_loss (float) : This is the limit-/market-price when to exit the trade, to minimize your losses.
Returns: float
rrr(entry, stop_loss, take_profit)
This function calculates the Risk Reward Ratio. Common values are between 1.5 and 2.0 and you should not go lower except for very few special cases.
Parameters:
entry (float) : This is the limit-/market-price for the investment. In other words: The price per contract/share/unit you willing to buy or sell.
stop_loss (float) : This is the limit-/market-price when to exit the trade, to minimize your losses.
take_profit (float) : This is the limit-/market-price when to take profits.
Returns: float
change_in_price(length)
This function calculates the difference between price now and close price of the candle 'n' bars before that. If prices are very volatile but closed where they began, then this method would show zero volatility. Over many calculations, this method returns a reasonable measure of volatility, but will always be lower than those using the highs and lows.
Parameters:
length (int) : The length is needed to determine how many candles/bars back should take into account.
Returns: float
maximum_price_fluctuation(length)
This function measures volatility over most recent candles, which could be used as an estimate of risk. It may also be effective as the basis for a stop-loss or take-profit, like the ATR but it ignores the frequency of directional changes within the time interval. In other words: The difference between the highest high and lowest low over 'n' bars.
Parameters:
length (int) : The length is needed to determine how many candles/bars back should take into account.
Returns: float
absolute_price_changes(length)
This function measures volatility over most recent close prices. This is excellent for comparing volatility. It includes both frequency and magnitude. In other words: Sum of differences between second to last close price and last close price as absolute value for 'n' bars.
Parameters:
length (int) : The length is needed to determine how many candles/bars back should take into account.
Returns: float
annualized_volatility(length)
This function measures volatility over most recent close prices. Its the standard deviation of close over the past 'n' periods, times the square root of the number of periods in a year.
Parameters:
length (int) : The length is needed to determine how many candles/bars back should take into account.
Returns: float
Williams %R Cross Strategy with 200 MA Filter
1. The script is a trading strategy based on the Williams %R indicator and a 200-period moving average (MA) filter.
2. The user can input the length of the Williams %R indicator (`wrLength`), the threshold for %R crossing (`crossPips`), the take profit level in pips (`takeProfitPips`), and the stop loss level in pips (`stopLossPips`).
3. The script calculates the Williams %R using the `ta.highest` and `ta.lowest` functions to find the highest high and lowest low over the specified length (`wrLength`).
4. It also calculates a 200-period simple moving average (`ma200`) using the `ta.sma` function.
5. The entry conditions are defined as follows:
- For a long entry, it checks if the Williams %R crosses above the -50 line by a threshold of `crossPips` and if the close price is above the 200-period MA.
- For a short entry, it checks if the Williams %R crosses below the -50 line by a threshold of `crossPips` and if the close price is below the 200-period MA.
6. The exit conditions are defined as follows:
- For a long position, it checks if the close price reaches the take profit level (defined as the average entry price plus `takeProfitPips` in pips) or the stop loss level (defined as the average entry price minus `stopLossPips` in pips).
- For a short position, it checks if the close price reaches the take profit level (defined as the average entry price minus `takeProfitPips` in pips) or the stop loss level (defined as the average entry price plus `stopLossPips` in pips).
7. The script uses the `strategy.entry` function to place long and short orders when the respective entry conditions are met.
8. It uses the `strategy.close` function to close the long and short positions when the respective exit conditions are met.
The script allows you to customize the parameters such as the length of Williams %R, the crossing threshold, take profit and stop loss levels, and the moving average period to suit your trading preferences.
Machine Learning : Torben's Moving Median KNN BandsWhat is Median Filtering ?
Median filtering is a non-linear digital filtering technique, often used to remove noise from an image or signal. Such noise reduction is a typical pre-processing step to improve the results of later processing (for example, edge detection on an image). Median filtering is very widely used in digital image processing because, under certain conditions, it preserves edges while removing noise (but see the discussion below), also having applications in signal processing.
The main idea of the median filter is to run through the signal entry by entry, replacing each entry with the median of neighboring entries. The pattern of neighbors is called the "window", which slides, entry by entry, over the entire signal. For one-dimensional signals, the most obvious window is just the first few preceding and following entries, whereas for two-dimensional (or higher-dimensional) data the window must include all entries within a given radius or ellipsoidal region (i.e. the median filter is not a separable filter).
The median filter works by taking the median of all the pixels in a neighborhood around the current pixel. The median is the middle value in a sorted list of numbers. This means that the median filter is not sensitive to the order of the pixels in the neighborhood, and it is not affected by outliers (very high or very low values).
The median filter is a very effective way to remove noise from images. It can remove both salt and pepper noise (random white and black pixels) and Gaussian noise (randomly distributed pixels with a Gaussian distribution). The median filter is also very good at preserving edges, which is why it is often used as a pre-processing step for edge detection.
However, the median filter can also blur images. This is because the median filter replaces each pixel with the value of the median of its neighbors. This can cause the edges of objects in the image to be smoothed out. The amount of blurring depends on the size of the window used by the median filter. A larger window will blur more than a smaller window.
The median filter is a very versatile tool that can be used for a variety of tasks in image processing. It is a good choice for removing noise and preserving edges, but it can also blur images. The best way to use the median filter is to experiment with different window sizes to find the setting that produces the desired results.
What is this Indicator ?
K-nearest neighbors (KNN) is a simple, non-parametric machine learning algorithm that can be used for both classification and regression tasks. The basic idea behind KNN is to find the K most similar data points to a new data point and then use the labels of those K data points to predict the label of the new data point.
Torben's moving median is a variation of the median filter that is used to remove noise from images. The median filter works by replacing each pixel in an image with the median of its neighbors. Torben's moving median works in a similar way, but it also averages the values of the neighbors. This helps to reduce the amount of blurring that can occur with the median filter.
KNN over Torben's moving median is a hybrid algorithm that combines the strengths of both KNN and Torben's moving median. KNN is able to learn the underlying distribution of the data, while Torben's moving median is able to remove noise from the data. This combination can lead to better performance than either algorithm on its own.
To implement KNN over Torben's moving median, we first need to choose a value for K. The value of K controls how many neighbors are used to predict the label of a new data point. A larger value of K will make the algorithm more robust to noise, but it will also make the algorithm less sensitive to local variations in the data.
Once we have chosen a value for K, we need to train the algorithm on a dataset of labeled data points. The training dataset will be used to learn the underlying distribution of the data.
Once the algorithm is trained, we can use it to predict the labels of new data points. To do this, we first need to find the K most similar data points to the new data point. We can then use the labels of those K data points to predict the label of the new data point.
KNN over Torben's moving median is a simple, yet powerful algorithm that can be used for a variety of tasks. It is particularly well-suited for tasks where the data is noisy or where the underlying distribution of the data is unknown.
Here are some of the advantages of using KNN over Torben's moving median:
KNN is able to learn the underlying distribution of the data.
KNN is robust to noise.
KNN is not sensitive to local variations in the data.
Here are some of the disadvantages of using KNN over Torben's moving median:
KNN can be computationally expensive for large datasets.
KNN can be sensitive to the choice of K.
KNN can be slow to train.
D-Bot Alpha RSI Breakout StrategyHello dear Traders,
Here is a simple yet effective strategy to use, for best profit higher time frame, such as daily.
Structure of the code
The code defines inputs for SMA (simple moving average) length, RSI (relative strength index) length, RSI entry level, RSI stop loss level, and RSI take profit level. The default values of these variables can be customized as per the user's preferences.
The script calculates SMA and RSI based on the input parameters and the closing price of the asset.
Trading logic
This strategy allows the placement of a long position when:
The RSI crosses above the RSI entry level and
The close price is above the SMA value.
After entering a long position, it applies a trailing stop mechanism. The stop price is updated to the close price if the close price is lower than the last close price.
The script closes the long position when:
RSI falls below the stop loss level.
RSI reaches or exceeds the take profit level.
If the trailing stop is activated (once RSI reaches or exceeds the take profit level), the closing price falls below the trailing stop level.
Strengths
The strategy includes mechanisms for entering a position, taking profit, and stopping losses, which are fundamental aspects of a trading strategy.
It applies a trailing stop mechanism that allows to capture further gains if the price keeps increasing while protecting from losses if the price starts to decrease.
Weaknesses
This strategy only contemplates long positions. Depending on the market situation, the strategy may miss opportunities for short selling when the market is on a downward trend.
The choice of the fixed RSI entry, stop loss, and take profit levels may not be ideal for all market conditions or assets. It might benefit from a more adaptive mechanism that adjusts these levels according to market volatility or trend.
The strategy doesn't factor in trading costs (such as spread or commission), which could have a significant impact on the net profit, especially if the user is trading with a high frequency or in a low liquidity market.
How to trade with this strategy
Given these parameters and the strategy outlined by the code, the trader would enter a long position when the RSI crosses above the RSI entry level (default 34) and the closing price is above the SMA value (SMA calculated with default period of 200). The trader would exit the position when either the RSI falls below the RSI stop loss level (default 30), or RSI rises above the RSI take profit level (default 50), or when the trailing stop is hit.
Remember "The strategies I have prepared are entirely for educational purposes and should not be considered as investment advice. Support your trades using other tools. Wishing everyone profitable trades..."
Mechanical Trading StrategyThe "Mechanical Trading Strategy" is a simple and systematic approach to trading that aims to capture short-term price movements in the financial markets. This strategy focuses on executing trades based on specific conditions and predetermined profit targets and stop loss levels.
Key Features:
Profit Target: The strategy allows you to set a profit target as a percentage of the entry price. This target represents the desired level of profit for each trade.
Stop Loss: The strategy incorporates a stop loss level as a percentage of the entry price. This level represents the maximum acceptable loss for each trade, helping to manage risk.
Entry Condition: The strategy triggers trades at a specific time. In this case, the condition for entering a trade is based on the hour of the candle being 16 (4:00 PM). This time-based entry condition provides a systematic approach to executing trades.
Position Sizing: The strategy determines the position size based on a fixed percentage of the available equity. This approach ensures consistent risk management and allows for potential portfolio diversification.
Execution:
When the entry condition is met, signified by the hour being 16, the strategy initiates a long position using the strategy.entry function. It sets the exit conditions using the strategy.exit function, with a limit order for the take profit level and a stop order for the stop loss level.
Take Profit and Stop Loss:
The take profit level is calculated by adding a percentage of the entry price to the entry price itself. This represents the profit target for the trade. Conversely, the stop loss level is calculated by subtracting a percentage of the entry price from the entry price. This level represents the maximum acceptable loss for the trade.
By using this mechanical trading strategy, traders can establish a disciplined and systematic approach to their trading decisions. The predefined profit target and stop loss levels provide clear exit rules, helping to manage risk and potentially maximize returns. However, it is important to note that no trading strategy is guaranteed to be profitable, and careful analysis and monitoring of market conditions are always recommended.
Adaptive Mean Reversion IndicatorThe Adaptive Mean Reversion Indicator is a tool for identifying mean reversion trading opportunities in the market. The indicator employs a dynamic approach by adapting its parameters based on the detected market regime, ensuring optimal performance in different market conditions.
To determine the market regime, the indicator utilizes a volatility threshold. By comparing the average true range (ATR) over a 14-period to the specified threshold, it determines whether the market is trending or ranging. This information is crucial as it sets the foundation for parameter optimization.
The parameter optimization process is an essential step in the indicator's calculation. It dynamically adjusts the lookback period and threshold level based on the identified market regime. In trending markets, a longer lookback period and higher threshold level are chosen to capture extended trends. In ranging markets, a shorter lookback period and lower threshold level are used to identify mean reversion opportunities within a narrower price range.
The mean reversion calculation lies at the core of this indicator. It starts with computing the mean value using the simple moving average (SMA) over the selected lookback period. This represents the average price level. The deviation is then determined by calculating the standard deviation of the closing prices over the same lookback period. The upper and lower bands are derived by adding and subtracting the threshold level multiplied by the deviation from the mean, respectively. These bands serve as dynamic levels that define potential overbought and oversold areas.
In real-time, the indicator's adaptability shines through. If the market is trending, the adaptive mean is set to the calculated mean value. The adaptive upper and lower bands are adjusted by scaling the threshold level with a factor of 0.75. This adjustment allows the indicator to be less sensitive to minor price fluctuations during trending periods, providing more robust mean reversion signals. In ranging market conditions, the regular mean, upper band, and lower band are used as they are more suited to capture mean reversion within a confined price range.
The signal generation component of the indicator identifies potential trading opportunities based on the relationship between the current close price and the adaptive upper and lower bands. If the close price is above the adaptive upper band, it suggests a potential short entry opportunity (-1). Conversely, if the close price is below the adaptive lower band, it indicates a potential long entry opportunity (1). When the close price is within the range defined by the adaptive upper and lower bands, no clear trading signal is generated (0).
To further strengthen the quality of signals, the indicator introduces a confluence condition based on the RSI. When the RSI exceeds the threshold levels of 70 or falls below the threshold level of 30, it indicates a strong momentum condition. By incorporating this confluence condition, the indicator ensures that mean reversion signals align with the prevailing market momentum. It reduces the likelihood of false signals and provides traders with added confidence when entering trades.
The indicator offers alert conditions to notify traders of potential trading opportunities. Alert conditions are set to trigger when a potential long entry signal (1) or a potential short entry signal (-1) aligns with the confluence condition. These alerts allow traders to stay informed about favorable mean reversion setups, even when they are not actively monitoring the charts. By leveraging alerts, traders can efficiently manage their time and take advantage of market opportunities.
To enhance visual interpretation, the indicator incorporates background coloration that provides valuable insights into the prevailing market conditions. When the indicator generates a potential short entry signal (-1) that aligns with the confluence condition, the background color is set to lime. This color suggests a bullish trend that is potentially reaching an exhaustion point and about to revert downwards. Similarly, when the indicator generates a potential long entry signal (1) that aligns with the confluence condition, the background color is set to fuchsia. This color represents a bearish trend that is potentially reaching an exhaustion point and about to revert upwards. By employing background coloration, the indicator enables traders to quickly identify market conditions that may offer mean reversion opportunities with a directional bias.
The indicator further enhances visual clarity by incorporating bar coloring that aligns with the prevailing market conditions and signals. When the indicator generates a potential short entry signal (-1) that aligns with the confluence condition, the bar color is set to lime. This color signifies a bullish trend that is potentially reaching an exhaustion point, indicating a high probability of a downward reversion. Conversely, when the indicator generates a potential long entry signal (1) that aligns with the confluence condition, the bar color is set to fuchsia. This color represents a bearish trend that is potentially reaching an exhaustion point, indicating a high probability of an upward reversion. By using distinct bar colors, the indicator provides traders with a clear visual distinction between bullish and bearish trends, facilitating easier identification of mean reversion opportunities within the context of the broader trend.
While the "Adaptive Mean Reversion Indicator" offers a robust framework for identifying mean reversion opportunities, it's important to remember that no indicator is foolproof. Traders should exercise caution and employ risk management strategies. Additionally, it is recommended to use this indicator in conjunction with other technical analysis tools and fundamental factors to make well-informed trading decisions. Regular backtesting and refinement of the indicator's parameters are crucial to ensure its effectiveness in different market conditions.
Pure Morning 2.0 - Candlestick Pattern Doji StrategyThe new "Pure Morning 2.0 - Candlestick Pattern Doji Strategy" is a trend-following, intraday cryptocurrency trading system authored by devil_machine.
The system identifies Doji and Morning Doji Star candlestick formations above the EMA60 as entry points for long trades.
For best results we recommend to use on 15-minute, 30-minute, or 1-hour timeframes, and are ideal for high-volatility markets.
The strategy also utilizes a profit target or trailing stop for exits, with stop loss set at the lowest low of the last 100 candles. The strategy's configuration details, such as Doji tolerance, and exit configurations are adjustable.
In this new version 2.0, we've incorporated a new selectable filter. Since the stop loss is set at the lowest low, this filter ensures that this value isn't too far from the entry price, thereby optimizing the Risk-Reward ratio.
In the specific case of ALPINE, a 9% Take-Profit and and Stop-Loss at Lowest Low of the last 100 candles were set, with an activated trailing-stop percentage, Max Loss Filter is not active.
Name : Pure Morning 2.0 - Candlestick Pattern Doji Strategy
Author : @devil_machine
Category : Trend Follower based on candlestick patterns.
Operating mode : Spot or Futures (only long).
Trades duration : Intraday
Timeframe : 15m, 30m, 1H
Market : Crypto
Suggested usage : Short-term trading, when the market is in trend and it is showing high volatility .
Entry : When a Doji or Morning Doji Star formation occurs above the EMA60.
Exit : Profit target or Trailing stop, Stop loss on the lowest low of the last 100 candles.
Configuration :
- Doji Settings (tolerances) for Entry Condition
- Max Loss Filter (Lowest Low filter)
- Exit Long configuration
- Trailing stop
Backtesting :
⁃ Exchange: BINANCE
⁃ Pair: ALPINEUSDT
⁃ Timeframe: 30m
⁃ Fee: 0.075%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start: 2022-02-28 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Disclaimer : Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Bollinger Bands, RSI, and MA StrategyThe "Bollinger Bands, RSI and MA Strategy" is a trend-following strategy that combines the Bollinger Bands indicator, the Relative Strength Index (RSI), and a moving average (MA). It aims to identify potential entry and exit points in the market based on price volatility, momentum, and trend.
The strategy uses two Bollinger Bands with different standard deviations to create price channels. The default settings for the Bollinger Bands are a length of 20 periods and a standard deviation of 2.0. The upper and lower bands of the Bollinger Bands serve as dynamic resistance and support levels, respectively.
The RSI indicator is employed to gauge the strength of price momentum.
The strategy also incorporates a 50-period moving average (MA) to help identify the overall trend direction. When the price is above the MA, it suggests an uptrend, and when the price is below the MA, it suggests a downtrend.
The entry conditions for long trades are when the RSI is above the overbought level and there is no contraction in the Bollinger Bands. For short trades, the entry conditions are when the RSI is below the oversold level and there is no contraction in the Bollinger Bands.
The exit conditions for long trades are when the RSI drops below the overbought level or when the price closes below the 50-period MA.
For short trades, the exit conditions are when the RSI goes above the oversold level or when the price closes above the 50-period MA.
The strategy generates alerts for potential long and short entry signals, as well as for exit signals when the specified conditions are met. These alerts can be used to receive notifications or take further actions, such as placing trades manually or using automated trading systems.
It is important to note that this strategy serves as a starting point and should be thoroughly backtested and validated with historical data before applying it to live trading. Additionally, it is recommended to consider risk management techniques, including setting appropriate stop-loss and take-profit levels, to effectively manage trades.
MACD TrueLevel StrategyThis strategy uses the MACD indicator to determine buy and sell signals. In addition, the strategy employs the use of "TrueLevel Bands," which are essentially envelope bands that are calculated based on the linear regression and standard deviation of the price data over various lengths.
The TrueLevel Bands are calculated for 14 different lengths and are plotted on the chart as lines. The bands are filled with a specified color to make them more visible. The highest upper band and lowest lower band values are stored in variables for easy access.
The user can input the lengths for the TrueLevel Bands and adjust the multiplier for the standard deviation. They can also select the bands they want to use for entry and exit, and enable long and short positions.
The entry conditions for a long position are either a crossover of the MACD line over the signal line or a crossover of the price over the selected entry lower band. The entry conditions for a short position are either a crossunder of the MACD line under the signal line or a crossunder of the price under the selected exit upper band.
The exit conditions for both long and short positions are not specified in the code and are left to the user to define.
Overall, the strategy aims to capture trends by entering long or short positions based on the MACD and TrueLevel Bands, and exiting those positions when the trend reverses.
Relative VolumeHello traders,
"There's nothing new on Wall Street" is an age-old saying that still shows its relevance in modern day financial markets; volume still serves as a valuable tool for any trader just as it did for those that came and succeeded before us; in order to succeed in modern day markets one has to take it up a notch and dabble in complicated topics, like math. Now I dunno about you reader but I’m not keen on sitting around all day just to watch numbers on a screen; it’s pretty important to add some color into your life before it becomes dull but how can someone add colors into their trading toolkit as an aid rather than bother? With a bit of help from 3 other amazing open-source indicators you too can become a statistics enjoyer by combining math and colors to make pattern recognition much more intuitive and offering more peace of mind when trading. “Sir but how?”, glad you didn’t ask, it helps with simplifying statistics, in this case a Gaussian bellcurve
“HUH?”, you say? Alright class, Gaussian bellcurves for math dislikers 101 is in session
- Imagine that we have a bunch of numbers that we want to graph. We could just draw a line and plot the numbers on it, but that might not be very interesting.
- Instead, we can use the shape of a bell to show how many of each number we have.
- Let's say we have a lot of people and we want to graph how tall they are. We would start by making a line from the shortest person to the tallest person, and then we would draw the bell shape around the line.
- The bell shape is called a "Gaussian Bell Curve," and it shows us how many people are a certain height.
- In the middle of the bell, where it's the widest, we have the most people who are about average height. As we move to the sides of the bell, the curve gets lower because there are fewer people who are really tall or really short.
The bell curve discussed is the main idea for the candle coloring component of this indicator as being able to analyze the distribution of an entire dataset, in this case volume, can alert us when volume/participation in the market is away from its average using color, and therefore an opportunity could be present. Fair warning, it’s important to not strictly focus on volume as volume is meant to be confluence to the current structure of the market rather than causing tunnel vision.
Why 3 indicators to combine?
It starts with the RVOL by Mik3Christ3ns3n indicator as the backbone by calculating the average volume over a specified period of time, and then compares each new volume value to this average to determine whether it is above or below the average. The indicator then normalizes the volume data and calculates the z-score/standard deviation to determine whether the volume is within normal range or is an anomaly beyond a specified threshold which can also be set into an alert to aid in eyeing possible opportunities.
The code also includes Candle Coloring by Morty as it calculates a function to get the z-score for the size of the candle's body, and then compares it to the z-score for volume to determine whether the body size is a factor in the price action.
Finally, the code plots the anomalies and the normalized volume data on the chart using the first RVOL indicator mentioned, and colors the bars of the chart based on whether they are within normal range or are anomalies which comes from using code from veryfid's relative volume indicator.
Overall, this custom technical indicator is best used to identify unusual changes in trading volume, which may indicate potential price movements in the underlying.
How about some examples?
This first example is for my scalpers wanting to get in and out but not having much of an idea where or let alone how; using a tool like VWAP can be great for determining the area value to execute mean reversion trades once a speculator spots a colored candle anomaly at standard deviation band. Works best when VWAP is flat as it signals lack of conviction from both bulls and bears
This second example is for my fire and forget intraweek swing traders who want to execute a higher timeframe trend-following bias. A speculator starting 2023 off notices that the negative sentiment around Binance from late last year has quieted down and has conviction in upside after BTC began an uptrend as monthly VWAP (right chart) has began sloping up as well as a rally with momentum shown with the blue colored candle so the trader waits wait for a pullback for entry. On the chart to the left of the 4H the speculator notices a pullback into the area of interest to do business so a limit bid is left to enter for continued upside in Bitcoin through January 2023 just by keeping things simple
That’s really the main purpose of this indicator: simplicity of statistics for confluence using volume
Volume precedes price and price moves only for narrative to follow- why wait for your subjective Twitter timeline to give you a biased narrative to trade when you can use objective analysis by combining statistics and colors to allow for a cleaner execution process
“But what about risk management?” Glad you didn’t ask reader!
One last example then, we meet our trend following trader again feeling euphoric so they know profit taking season is coming soon but wants to leave emotion out of it. How to go about it? Same idea as our last trend following example: we see on the 4h chart to the right side shows Bitcoin lose and trade back within the 2nd standard deviation of quarterly VWAP which is telling our speculator that the uptrend has broken on top of which notices on the 30 minute chart on the left that aggressive market buyers have been steadily absorbed by limit sellers on multiple occasions of retesting 30,500 shown with the green colored candles and volume bars below, time to sell.
Turns out that selling was proactive risk management because price dumped thereafter
Hope this explanation gave you some useful insights on using statistics as colors from cherrypicked examples, remember that just because my examples are cherrypicked doesn’t invalidate these concepts at all as the market only does two things, initiate aggressive auctions and respond passively to auctions. This tool makes for seeing where that initiative aggressive activity is happening much simpler to deduce if others will respond to an anomaly of initiative aggressive activity or if the aggression will continue.
If there’s just one thing you take from this- simplicity above all, cheers and good luck
Trading Zones based on RS / Volume / PullbackThis is an Indicator which identifies different Trading Zones on the chart.
This should be Primarily used for Long Trades.
Trading Zones: and the Reasoning behind them
Long Zone -> One can do a Potential Entry (Buy) when this Zone is identified, but one could also wait for 'Entry Zone' (explained next) for a better Risk/Reward Trade.
Long Zones are identified with the help of Relative Strength and by an Intermediate Top in price.
Entry Zone -> This can be a better Risk/Reward zone to enter positions within the Long Zone.
Entry Zone is identified by a Pullback in Price & Volume contraction after the Long Zone is activated
Warning Zone -> One needs to be careful in this zone, no need to panic, Script will now try to find an Exit when Price Retraces towards Highs.
Warning Zone identifies weakness in the Price using Relative Strength of the current Stock (w.r.t. the Reference Symbol configured) and the severity of Pullback in Price.
Exit Zone -> are found only after transitioning to Warning Zone, this is a Zone which helps in minimising losses after a trade has gone into losses. Exit Zone is identified by making sure a local peak forms in Warning Zone. However, there are instances when Exit Zone detection can get prolonged when a local price peak is not formed soon enough. So one needs to be careful and use other strategies for exit.
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What is different in this Script:
The Script uses Relative Strength in combination with Pullback in Price from Highs in a Novel way.
Over-trading is avoided by ignoring Sideways price movements, using Relative Strength.
Only Trending Upward movement is detected and traded.
How to use this Indicator:
Use these 'Trading Zones' only as a reference so it can minimise your time in screening stocks.
Preferred Settings for using the Indicator:
Stick to 1-Day candles
Keep Relative Symbol as "Nifty" for Indian Stocks.
For US stocks, we can use "SPX" as the Relative Symbol.
//----------------
FEW EXAMPLES:
//----------------
ASIANPAINT
TATAMOTORS
TITAN
ITC
DIVISLAB
MARUTI
---------------------------------------------
Feedback is welcome.
Yesterday’s High Breakout - Trend Following StrategyYesterday’s High Breakout it is a trading system based on the analysis of yesterday's highs, it works in trend-following mode therefore it opens a long position at the breakout of yesterday's highs even if they occur several times in one day.
There are several methods for exiting a trade, each with its own unique strategy. The first method involves setting Take-Profit and Stop-Loss percentages, while the second utilizes a trailing-stop with a specified offset value. The third method calls for a conditional exit when the candle closes below a reference EMA.
Additionally, operational filters can be applied based on the volatility of the currency pair, such as calculating the percentage change from the opening or incorporating a gap to the previous day's high levels. These filters help to anticipate or delay entry into the market, mitigating the risk of false breakouts.
In the specific case of NULS, a 9% Take-Profit and a 3% Stop-Loss were set, with an activated trailing-stop percentage. To postpone entry and avoid false breakouts, a 1% gap was added to the price of yesterday's highs.
Name : Yesterday's High Breakout - Trend Follower Strategy
Author : @tumiza999
Category : Trend Follower, Breakout of Yesterday's High.
Operating mode : Spot or Futures (only long).
Trade duration : Intraday.
Timeframe : 30M, 1H, 2H, 4H
Market : Crypto
Suggested usage : Short-term trading, when the market is in trend and it is showing high volatility.
Entry : When there is a breakout of Yesterday's High.
Exit : Profit target or Trailing stop, Stop loss or Crossunder EMA.
Configuration :
- Gap to anticipate or postpone the entry before or after the identified level
- Rate of Change for Entry Condition
- Take Profit, Stop Loss and Trailing Stop
- EMA length
Backtesting :
⁃ Exchange: BINANCE
⁃ Pair: NULSUSDT
⁃ Timeframe: 2H
⁃ Fee: 0.075%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start : 2018-07-26 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Credits : LucF for Pine Coders (f_security function to avoid repainting using security)
Disclaimer : Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Rounded Forex Levels: Big-Figure, Mid-Figure, 80-20 levels, BFRNSimple indicator to show Rounded levels in typical Forex pairs: Big figure, Mid-figure, 80-20 Insitutional Levels, 10pip levels, 5pip levels
Wrote this indicator because other ones out there seem to clutter the chart. This is simple, low-clutter and can be set by user to have arbitrary start and end points for the lines.
I wanted the ability for lines to plot discreetly to the right hand side of price as in the chart above, since in my opinion, these are only of secondary consideration to a trader, an extra confirmation/confluence to an existing idea.
//Purpose & Usage:
-Big-figure levels (100pips) & Mid-figure levels (50pips) will have a senstitivity to price, that can be an additional tool when looking for confluence for a target or an entry.
-As well as BF levels and MF levels; Institutional levels (20pips below and 20 pips above a Big Figure level) and standard 10pip or 5pip levels, can be useful in the right context (i.e added confirmation that of a minor sweep target; added conviction in an idea if the level aligns with another seperately derived level).
//User inputs:
-Toggle on/off each of the types of level.
-Line spacing: choose pip spacing of lines .
-Number of lines above/below (i.e. setting of 5 will be 11 lines. One central, 5 above, 5 below).
-Formatting: for each class of lines, code by color, style and width (as per the example chart below).
-Line start offset and line end offset: bars forward/back for each of start point and end point. So lines could be spread right across chart; or neatly pushed to the far right or left of the chart.
//Notes:
-Designed for typical Forex pairs with units close to 1.0 (like Eur/Usd, Usd/Cad, Aud/Usd, Gbp/Usd, Eur/Gbp, Nzd/Usd).
-Lines are based from the rounded close of the previous bar, Updating (if applicable) on each new bar.
Demo Plotting levels in the past; Dialog box example display:
Range Filter x Hull SuiteRange Filter x Hull Suite
This indicator is a hybrid of two popular indicators, with a twist; namely the Range Filter (Guikroth version) and the Hull Suite (by Insilico) .
Originally developed as a 1 minute trend following strategy and traded during the New York Session for it's typically high volume / likely trending nature, it provides entry signals based on the following logic:
For bullish entry signals:
The first bullish* candle (*defined by the Range Filter bar color logic, blue by default - which is not necessarily technically a bullish candle as defined by the OHLC values) which appears after the consolidation candles (also defined by the Range Filter bar color logic, orange by default), and where the Hull Suite moving average is also bullish.
For bearish entry signals:
The first bearish* candle (*defined by the Range Filter bar color logic, red by default - which is not necessarily technically a bearish candle as defined by the OHLC values) which appears after the consolidation candles (also defined by the Range Filter bar color logic, orange by default), and where the Hull Suite moving average is also bearish.
The indicator aims to filter out signals where possible consolidation is occurring and comes with styling options and alternative filter options such as a triple moving average trend detection method. Signals can also be filtered by a specific trading session. Standard options for the Range Filter and Hull Suite settings are also able to be customised within the settings menu.
Alerts
Various alerts are built-in, including the custom entry signals unique to this strategy.
Note : The above features listed above are accurate at the time of publishing, but may be altered in future.
Many thanks to guikroth & Insilico for sharing their open source indicators, and also to the original developer of the strategy itself for sharing it.
Trend Bands [starlord_xrp]This indicator uses multiple trendlines to determine the overall trend and trend changes. It also highlights areas of potential pullbacks to entry.
HarmonicPatternTrackingLibrary "HarmonicPatternTracking"
Library contains few data structures and methods for tracking harmonic pattern trades via pinescript.
method draw(this)
Creates and draws HarmonicDrawing object for given HarmonicPattern
Namespace types: HarmonicPattern
Parameters:
this (HarmonicPattern) : HarmonicPattern object
Returns: current HarmonicPattern object
method addTrade(this)
calculates HarmonicTrade and sets trade object for HarmonicPattern
Namespace types: HarmonicPattern
Parameters:
this (HarmonicPattern) : HarmonicPattern object
Returns: bool true if pattern trades are valid, false otherwise
method delete(this)
Deletes drawing objects of HarmonicDrawing
Namespace types: HarmonicDrawing
Parameters:
this (HarmonicDrawing) : HarmonicDrawing object
Returns: current HarmonicDrawing object
method delete(this)
Deletes drawings of harmonic pattern
Namespace types: HarmonicPattern
Parameters:
this (HarmonicPattern) : HarmonicPattern object
Returns: current HarmonicPattern object
HarmonicDrawing
Drawing objects of Harmonic Pattern
Fields:
xa (series line) : xa line
ab (series line) : ab line
bc (series line) : bc line
cd (series line) : cd line
xb (series line) : xb line
bd (series line) : bd line
ac (series line) : ac line
xd (series line) : xd line
x (series label) : label for pivot x
a (series label) : label for pivot a
b (series label) : label for pivot b
c (series label) : label for pivot c
d (series label) : label for pivot d
xabRatio (series label) : label for XAB Ratio
abcRatio (series label) : label for ABC Ratio
bcdRatio (series label) : label for BCD Ratio
xadRatio (series label) : label for XAD Ratio
HarmonicTrade
Trade tracking parameters of Harmonic Patterns
Fields:
initialEntry (series float) : initial entry when pattern first formed.
entry (series float) : trailed entry price.
initialStop (series float) : initial stop when trade first entered.
stop (series float) : current stop updated as per trailing rules.
target1 (series float) : First target value
target2 (series float) : Second target value
target3 (series float) : Third target value
target4 (series float) : Fourth target value
status (series int) : Trade status referenced as integer
retouch (series bool) : Flag to show if the price retouched after entry
HarmonicProperties
Display and trade calculation properties for Harmonic Patterns
Fields:
fillMajorTriangles (series bool) : Display property used for using linefill for harmonic major triangles
fillMinorTriangles (series bool) : Display property used for using linefill for harmonic minor triangles
majorFillTransparency (series int) : transparency setting for major triangles
minorFillTransparency (series int) : transparency setting for minor triangles
showXABCD (series bool) : Display XABCD pivot labels
lblSizePivots (series string) : Pivot label size
showRatios (series bool) : Display Ratio labels
useLogScaleForScan (series bool) : Use log scale to determine fib ratios for pattern scanning
useLogScaleForTargets (series bool) : Use log scale to determine fib ratios for target calculation
base (series string) : base on which calculation of stop/targets are made.
entryRatio (series float) : fib ratio to calculate entry
stopRatio (series float) : fib ratio to calculate initial stop
target1Ratio (series float) : fib ratio to calculate first target
target2Ratio (series float) : fib ratio to calculate second target
target3Ratio (series float) : fib ratio to calculate third target
target4Ratio (series float) : fib ratio to calculate fourth target
HarmonicPattern
Harmonic pattern object to track entire pattern trade life cycle
Fields:
id (series int) : Pattern Id
dir (series int) : pattern direction
x (series float) : X Pivot
a (series float) : A Pivot
b (series float) : B Pivot
c (series float) : C Pivot
d (series float) : D Pivot
xBar (series int) : Bar index of X Pivot
aBar (series int) : Bar index of A Pivot
bBar (series int) : Bar index of B Pivot
cBar (series int) : Bar index of C Pivot
dBar (series int) : Bar index of D Pivot
przStart (series float) : Start of PRZ range
przEnd (series float) : End of PRZ range
patterns (bool ) : array representing the patterns
patternLabel (series string) : string representation of list of patterns
patternColor (series color) : color assigned to pattern
properties (HarmonicProperties) : HarmonicProperties object containing display and calculation properties
trade (HarmonicTrade) : HarmonicTrade object to track trades
drawing (HarmonicDrawing) : HarmonicDrawing object to manage drawings
VWAP ROC Weighted AverageThe VWAP ROC Weighted Average indicator combines the concepts of Volume Weighted Average Price (VWAP) and Rate of Change (ROC) to create a unique and versatile tool for traders. The indicator calculates the average VWAP and average ROC over a specified period (default: 200 bars) and then creates a weighted average of these two values. This provides a single line that can help traders identify potential entry and exit points in a market.
How it can be used in trading:
Trend Confirmation: The VWAP_ROC_WA can be used to confirm the prevailing trend of an asset. If the weighted average line is moving upward, it indicates a bullish trend, while a downward-moving line suggests a bearish trend. Traders can use this information to enter trades in the direction of the trend to improve their odds of success.
Support and Resistance: The VWAP_ROC_WA line can act as dynamic support and resistance levels. When the price is above the weighted average line, it can act as a support level, and when the price is below the line, it can serve as a resistance level. Traders can use these levels to set stop-loss and take-profit orders or to identify potential entry and exit points.
Divergences: Traders can look for divergences between the price and the VWAP_ROC_WA line to identify potential reversals. For instance, if the price is making higher highs while the weighted average line is making lower highs, it may signal a bearish divergence, indicating a potential reversal to the downside. Conversely, if the price is making lower lows while the weighted average line is making higher lows, it may signal a bullish divergence, indicating a potential reversal to the upside.
Crossovers: Traders can monitor crossovers between the price and the VWAP_ROC_WA line. A bullish crossover occurs when the price crosses above the weighted average line, suggesting a potential long entry point. A bearish crossover occurs when the price crosses below the line, suggesting a potential short entry point.
CoffeeShopCrypto 3pl MAThe CoffeeShopCrypto 3pl MA indicator is a technical analysis tool that uses three different moving averages to identify trends in the price of an asset. The three moving averages have lengths of 12, 26, and 50. If these numbers sound familiar its because they are based off the standard of the MACD indicator, and can be either simple moving averages (SMA) or exponential moving averages (EMA), depending on user preference.
The following is plotted on the chart
The fast EMA/SMA (based on the 12-period length) in yellow.
The mid EMA/SMA (based on the 26-period length) in gray.
The slow EMA/SMA (based on the 50-period length) in either green or red, depending on whether the current close price is above or below the Overall Trend MA.
In addition to the moving averages, the indicator also calculates the MACD (Moving Average Convergence Divergence), and uses it to color the bars based on the momentum of the asset.
The MACD is calculated using two user-defined lengths (fast and slow), as well as a user-defined smoothing length for the signal line. The oscillator and signal line can be either SMA or EMA, and the colors of the MACD bars are based on whether the histogram is growing or falling, and whether it is above or below the zero line.
Overall, this indicator provides traders with a comprehensive tool for understanding the trend of an asset, as well as the momentum behind that trend. The moving averages provide a clear visual representation of the trend, while the MACD bars give insight into the strength of that trend and potential shifts in momentum.
---------------LONG ENTRY----------------
MA1 above MA2 and Overall trend = Green
IF RSI is above its midline you are confirmed for a long entry
-----------Short Entry--------------
MA1 below MA2 and Overall trend = Red
IF RSI is below its midline you are confirmed for a short entry
The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)
Are you tired of manually analyzing charts and trying to find profitable trading opportunities? Look no further! Our algorithmic trading strategy, "Flash," is here to simplify your trading process and maximize your profits.
Flash is an advanced trading algorithm that combines three powerful indicators to generate highly selective and accurate trading signals. The Momentum-RSI, Super-Trend Analysis and EMA-Strategy indicators are used to identify the strength and direction of the underlying trend.
The Momentum-RSI signals the strength of the trend and only generates trading signals in confirmed upward or downward trends. The Super-Trend Analysis confirms the trend direction and generates signals when the price breaks through the super-trend line. The EMA-Strategy is used as a qualifier for the generation of trading signals, where buy signals are generated when the EMA crosses relevant trend lines.
Flash is highly selective, as it only generates trading signals when all three indicators align. This ensures that only the highest probability trades are taken, resulting in maximum profits.
Our trading strategy also comes with two profit management options. Option 1 uses the so-called supertrend-indicator which uses the dynamic ATR as a key input, while option 2 applies pre-defined, fixed SL and TP levels.
The settings for each indicator can be customized, allowing you to adjust the length, limit value, factor, and source value to suit your preferences. You can also set the time period in which you want to run the backtest and how many dollar trades you want to open in each position for fully automated trading.
Choose your preferred trade direction and stop-loss/take-profit settings, and let Flash do the rest. Say goodbye to manual chart analysis and hello to consistent profits with Flash. Try it now!
General Comments
This Flash Strategy has been developed in cooperation between Baby_whale_to_moon and JS-TechTrading. Cudos to Baby_whale_to_moon for doing a great job in transforming sophisticated trading ideas into pine scripts.
Detailed Description
The “Flash” script considers the following indicators for the generation of trading signals:
1. Momentum-RSI
2. ‘Super-Trend’-Analysis
3. EMA-Strategy
1. Momentum-RSI
• This indicator signals the strength of the underlying upward- or downward-trend.
• The signal range of this indicator is from 0 to 100. Values > 60 indicate a confirmed upward- or downward-trend.
• The strategy will only generate trading signals in case the stock (or any other financial security) is in a confirmed upward- (long entry signals) or downward-trend (short entry signals).
• This indicator provides information with regards to the strength of the underlying trend and it does not give any insight with regard to the direction of the trend. Therefore, this strategy also considers other indicators which provide technical confirmation with regards to the direction of the underlying trend.
Graph 1 shows this concept:
• The Momentum-RSI indicator gives lower readings during consolidation phases and no trading signals are generated during these periods.
Example (graph 2):
2. Super-Trend Analysis
• The red line in the graph below represents the so-called super-trend-line. Trading signals are only generated in case the price action breaks through this super-trend-line indicating a new confirmed upward-trend (or downward-trend, respectively).
• If that happens, the super trend-line changes its color from red to green, giving confirmation that the trend changed from bearish to bullish and long-entries can be considered.
• The vice-versa approach can be considered for short entries.
Graph 3 explains this concept:
3. Exponential Moving Average / EMA-Strategy
The functionality of this EMA-element of the strategy has been programmed as follows:
• The exponential moving average and two other trend lines are being used as qualifiers for the generation of trading-signals.
• Buy-signals for long-entries are only considered in case the EMA (yellow line in the graph below) crosses the red line.
• Sell-signals for short-entries are only considered in case the EMA (yellow line in the graph below) crosses the green line.
An example is shown in graph 4 below:
We use this indicator to determine the new trend direction that may occur by using the data of the price's past movement.
4. Bringing it all together
This section describes in detail, how this strategy combines the Momentum-RSI, the super-trend analysis and the EMA-strategy.
The strategy only generates trading-signals in case all of the following conditions and qualifiers are being met:
1. Momentum-RSI is higher than the set value of this strategy. The standard and recommended value is 60 (graph 5):
2. The super-trend analysis needs to indicate a confirmed upward-trend (for long-entry signals) or a confirmed downward-trend (for short-entry signals), respectively.
3. The EMA-strategy needs to indicate that the stock or financial security is in a confirmed upward-trend (long-entries) or downward-trend (short-entries), respectively.
The strategy will only generate trading signals if all three qualifiers are being met. This makes this strategy highly selective and is the key secret for its success.
Example for Long-Entry (graph 6):
When these conditions are met, our Long position is opened.
Example for Short-Entry (graph 7):
Trade Management Options (graph 8)
Option 1
In this dynamic version, the so-called supertrend-indicator is being used for the trade exit management. This supertrend-indicator is a sophisticated and optimized methodology which uses the dynamic ATR as one of its key input parameters.
The following settings of the supertrend-indicator can be changed and optimized (graph 9):
The dynamic SL/TP-lines of the supertrend-indicator are shown in the charts. The ATR-length and the supertrend-factor result in a multiplier value which can be used to fine-tune and optimize this strategy based on the financial security, timeframe and overall market environment.
Option 2 (graph 10):
Option 2 applies pre-defined, fixed SL and TP levels which will appear as straight horizontal lines in the chart.
Settings options (graph 11):
The following settings can be changed for the three elements of this strategy:
1. (Length Mom-Rsi): Length of our Mom-RSI indicator.
2. Mom-RSI Limit Val: the higher this number, the more momentum of the underlying trend is required before the strategy will start creating trading signals.
3. The length and factor values of the super trend indicator can be adjusted:ATR Length SuperTrend and Factor Super Trend
4. You can set the source value used by the ema trend indicator to determine the ema line: Source Ema Ind
5. You can set the EMA length and the percentage value to follow the price: Length Ema Ind and Percent Ema Ind
6. The backtesting period can be adjusted: Start and End time of BackTest
7. Dollar cost per position: this is relevant for 100% fully automated trading.
8. Trade direction can be adjusted: LONG, SHORT or BOTH
9. As we explained above, we can determine our stop-loss and take-profit levels dynamically or statically. (Version 1 or Version 2 )
Display options on the charts graph 12):
1. Show horizontal lines for the Stop-Loss and Take-profit levels on the charts.
2. Display relevant Trend Lines, including color setting options for the supertrend functionality. In the example below, green lines indicate a confirmed uptrend, red lines indicate a confirmed downtrend.
Other comments
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
