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)
Komut dosyalarını "entry" için ara
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.
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.
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
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:
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.
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.
Ultimate P&L IndicatorHello everyone,
Excited to release this P&L Indicator! Read below for more details.
What it does:
This is an indicator that permits you to track your active P&L live on Tradingview. As well, it provides some insight into DCAing your position by giving you live estimates of your revised DCA if you were to add to your position at various targets/price points.
Who is it for:
I developed it because I trade 100% off of Tradingview but my broker does not support Tradingview integration. So I wanted a way to track my position live on the Tradingview platform without having to constantly reference my broker. I also wanted to be able to set position specific alerts right on Tradingview.
How does it work:
It works by the user manually inputting their trade information, including their DCA, position size and the date and time of position entry. The indicator can provide real time and live DCA adjusted estimates if you were to add to your position at the current stock price, or you can manually calculcate your revised DCA at a specific price target.
The indicator also displays your current and past performance on your position for the duration of the position period:
Elements:
Capabilities:
The indicator is compatible with both futures and share trading.
Option trading is not directly available, however, you can get an idea for your option position P&L by following the 1 option contract = 100 share rule.
So if you have 5 option contracts that you bought at a ticker price of, say, 38$, your average cost or DCA would be 38 and your position size would be 500. This will not be 100% accurate, but will be close enough to give you a feel for your active P&L.
If you are trading futures, you will need to select "Futures Trading" and specify the TIck and Index costs. A cheat sheet has been provided in the tool tip for ES, Oil and MNQ. The default is set for ES1! mini futures at 0.25 ticks per 50$.
Important tips:
1. Select the date and time of your position (optional): This is optional but will provide you with the clearest and most accurate review of how your position has performed, including the highest and lowest (drawdown).
2. Select whether it is a share position or a futures position (this is required).
3. Select whether it is a long or short position (this is required).
4. Input your DCA and position size (this is required).
5. Most importantly, select the ticker your position is based in!
I have also prepared a quick start video which is linked below:
As always, please let me know your comments/questions and feedback for the indicator.
Thanks for checking it out and safe trades everyone!
Trend Indicator with RSI and Fibbonacci Band 0.702 crossingsToday we have a new Indicator set, which I created using inspiration from the Trend Magic Indicator from KivancOzbilgic and adding several new aspects to it and a slightly modified calculation of the trend indicator itself.
You can change the inputs by changing the pre set values in the settings, but I found the current settings quite accurate. Feel free to experiment to fine tune the indicators.
Here are the details of the script:
Trend indicated within candles and as a line
- bullish and bearish trends are now also indicated within the candle based on the CCI calculation.
- Bullish is indicated by a green circle below the candle or as one may call it a "dot"
- bearish trend is indicated by a red circle above the candle
Entry Signal based on RSI crossing its EMA
- my motivation was to have a clearer entry signal besides highlighting a trend, which can not really be used to identify a good entry but to give confidence or when loosing trend to give an exit signal.
- after studiying the RSI and how it works together with its EMA it looks quite interesting as an entry or exit signal. But be cautios if the EMA and RSI values are moving in a narrow area we get a lot of crosses and therefore signals which should rather be ignored rather to be act on. So the the range where the cross happens is also quite important. But this aspect is not yet reflected as a rule/ logic.
But I am thinking of adding something.. or alternativly best to switch to another timeframe to get some better data
RSI overbought and oversold as Diamonds
- I also added key indications of oversold or overbought as Blue and Pink diamonds, can be considered as additional information to maybe identify a short term top or bottom.. but its not very accurate.
Entry signal based on crossing Fibbonachi Band 0.702
- So far the 0.702 seems to be quite an interesting retracement level which seems to be met a lot of times
- based on the assumption the price will evantually hit the 0.702 either direction I wanted to get a signal when this happens
- BUT! a big but, unfortunalty the Fibbonachi bands tend to bloat up in case of high volatility so it is not easy to find the crossing on higher timeframes
Here are the standard value which I found quite accurate for the assets I use this indicator set:
CCI Period = 5
ATR Multiplier = 1
ATR Period = 1
Source = High Low Close (hlc3 average value of the candle
Here the inputs used for the RSI Crossing signal (here you should play around a little to see which entry would have been best..)
RSI Length = 14
RSI Oversold = 25 (to be used for the "golden" entry signal based on the FBB crossing)
RSI Overbought = 80 (to be used for the "golden" entry signal based on the FBB crossing)
RSI Moving Average Length
In future versions I will add options to activate or deactive some of the plotting and espacially this golden dot when the fibbonachi band is being crossed needs some fine tuning..
And lets see if there is a way to fix the bloating of those bands..
Strong Tight Closes in Strong UptrendThis indicator helps to visually identify "strong tight closes" in an uptrend. It serves to make it easier to spot not only tight but tight AND strong consolidations in an ongoing uptrend for a potential continuation entry. Please keep in mind the indicator counts with distance between Close values of 2 separate candles, that's why it's called "Tight Back to Back Candles". This doesn't identify "tight close" in a sense of very narrow range between Open and Close of a single candle, not any other volatility measures such as average true range etc.
Caution: This is not a complete strategy, it's only a visual tool for making potential continuation patterns easier to spot.
Conditions:
- Measure the difference between CLOSE values of two candles in percentages
- If the difference is lower than a certain threshold set by the user, (1.3% by default) plot a green cross below the latter candle
Filters:
- Low of both candles must be above 10EMA on the current timeframe
- Both Closes must be in the upper half of the candles' Low to High range
Trampoline DotsTrampoline Dots (Price Divergence)
Higher Time Frame Price Divergence:
Trampoline Dots serve as a "quick bounce" tool. These little dots will trigger whenever the higher aggregation MACD is above / below zero and the price is below / above the 50 period simple moving average. When these criteria are met, the price is usually under pressure of strong divergence, more often than not price will sharply reverse into the trend direction usually within the next few bars.
The Use of The Trampoline Dots:
This indicator can serve multiple ways. Obviously the main use case is the price divergence. These "dots" will not give you any precise & exact entry. But rather a zone of possible incoming reversal. There is no timing to it. All these dots will do is warn you about potential sharp reversal in the upcoming bars. It can be used by itself alone for sure, but the best way to utilize the dots is to use them in combination of other trend or momentum studies. The best signals are the ones that are within the larger time frame trend. Another great thing is that the visuals are really straight-forward and simple. It is either green dot or a red dot. Nothing more, nothing less. Also since the indicator is pretty small, it can be easily layered onto other studies as well which can create an additional confirmation for different patterns or setups.
Which Time Frame Are Reliable?
This indicator works on any time frame. But the most "stable" one is the daily & hourly time frame. My personal favorite is the hourly since these divergences can produce amazing entries in the daily trends (which are usually hidden on the daily chart). In the most aggresive trends, I like to see the green dots triggering around the 8 EMA and 13 EMA. Daily chart can show the daily and weekly (big divergences) that can take multiple days & weeks to resolve.
Hope it helps.
Channel Trend and 3 EMA Stratgy MHG-V.6.1.4Dear Traders..
This Startgy use the 3 tools
1- Trend Detection
2- draw the Ascending and Descending channels
3- Use the 3 Moving average for take the acceptant for position entry.
If ascending channel and make the buy signal, then watch the EMA 2 if the price above the 2 EMA you can open the Long position.
SL alittle under the 2 EMA Curve.
for short position riverce the above manual...
Manage tradeThis indicator is intended to simulate a second entry to adjust the average price.
INPUTS:
Current price || Coins -> Current price, your first entry || Initial amount of coins
Simulate entry || Coins -> New entry, from this entry the average price will be calculated || new amount of coins
Simulate partial % || Coins -> Percentage over current price or average price || Amount of coins withdrawn
* Currency conversion
Value $ || Target price -> amount or coins, example: 25 dolar or 25 busd || Acquisition target price, returns desired coin amount, visible in table.
Table information:
simbol = current symbol
current price = First entry price
total coins = Total coins from first entry
profit or loss = self explanatory
update value = increases or decreases according to profit or loss
Partial profit = partial simulation result,
$ ⮕ ₿ = total amount of currencies in the conversion
Trend Following based on Trend ConfidenceThis is a Trend Following strategy based on the Trend Confidence indicator.
The goal of this strategy is to be a simple Trend Following strategy, but also to be as precise as possible when it comes to the question 'how confident are we that a linear trend is ongoing?'. For this we calculate the 'confidence' of a linear trend in the past number of closing prices. The idea of this strategy is that past a certain confidence, the ongoing linear trend is more likely to continue than not.
Trend Confidence:
The Trend Confidence shows us how strong of a linear trend the price has made in the past number (given by Length parameter) of closing prices. The steepness of the price change makes the Trend Confidence more extreme (more positive for an uptrend or more negative for a downtrend), and the deviation from a straight line makes the Trend Confidence less extreme (brings the confidence closer to 0). This way we can filter out signals by wild/sudden price moves that don't follow a clear linear trend.
Math behind the Trend Confidence:
A linear fit is made on the past number of closing prices, using Ordinary Linear Regression. We have the steepness of the linear fit: b in y=a+bx . And we have the standard deviation of the distances from the closing prices to the linear fit: sd . The Trend Confidence is the ratio b/sd .
Entries and Exits:
For entry and exit points we look at how extreme the Trend Confidence is. The strategy is based on the assumption that past a certain confidence level, the ongoing linear trend is more likely to continue than not.
So when the Trend Confidence passes above the 'Long entry" threshold, we go Long. After that when the Trend Confidence passes under the 'Long exit' threshold, we exit. The Long entry should be a positive value so that we go Long once a linear uptrend with enough confidence has been detected.
When the Trend Confidence passes below the 'Short entry' threshold, we go Short. After that when the Trend Confidence passes above the 'Short exit' threshold, we exit. The Short entry should be a negative value so that we go Short once a linear downtrend with enough confidence has been detected.
Default Parameters:
The strategy is intended for BTC-USD market, 4 hour timeframe. The strategy also works on ETH-USD with similar parameters.
The Length is arbitrarily set at 30, this means we look at the past 30 closing prices to determine a linear trend. Note that changing the length will change the range of Trend Confidence values encountered.
The default entry and exit thresholds for Longs and Shorts do not mirror each other. This is because the BTC-USD market goes up more heavily and more often than it goes down. So the ideal parameters for Longs and Shorts are not the same.
The positive results of the strategy remain when the parameters are slightly changed (robustness check).
The strategy uses 100% equity per trade, but has a 10% stop loss so that a maximum of 10% is risked per trade.
Commission is set at 0.1% as is the highest commission for most crypto exchanges.
Slippage is set at 5 ticks, source for this is theblock.co.
GIRISH indicatorHello traders,
This indicator is the enhancement to my previous indicator (RSI+OBV). There is combined RSI and OBV with DMI. This new indicator is combination of RSI and OBV with VWAP . I have been using this indicator for intraday trades in NIFTY & BANKNIFTY .
The white line indicates the movement of VWAP wrt current price. There default range for this has been defined as -40 to 40 .
Entry for long: When white line goes below -40, we need to wait for green background. Entry has to be taken when green background appears. If price goes below the entry point, averaging can be done once. Price will surely go long and give us good profit.
Entry for short: When white line goes above 40 , we need to wait for red background (if darker red comes, it is better) . Entry has to be taken when red background appears. If price goes above the entry point, averaging can be done once. Price will surely go down and give us good profit on short side.
PS: Please do back testing in chart before taking trades.
strategyLibrary "strategy"
Library containing few key calculations for strategy involving leveraged limit and stop orders
getQty(entry, stop, riskPercentage)
calculate qty and leverage based on entry and stop price for given risk percentage.
Parameters:
entry : Entry Price
stop : Stop Price
riskPercentage : risk percentage per trade
Returns: - Quantity based on the risk and calculated leverage on position including existing positions
bracketOrder(entry, stop, target, maxLeverage, isLimitOrder, riskPercentage)
Calculates position size based on risk and creates bracket orders for given entry/stop/target
Parameters:
entry : Entry Price
stop : Stop Price
target : Target Price
maxLeverage : Maximum leverage allowed
isLimitOrder : if true, places limit order for entry, else places stop order.
riskPercentage : risk percentage per trade
Returns: orderPlaced - true if orders successfully placed, false otherwise.
order(entry, stop, maxLeverage, isLimitOrder, riskPercentage)
Calculates position size based on risk and creates order for given entry/stop
Parameters:
entry : Entry Price
stop : Stop Price
maxLeverage : Maximum leverage allowed
isLimitOrder : if true, places limit order for entry, else places stop order.
riskPercentage : risk percentage per trade
Returns: orderPlaced - true if orders successfully placed, false otherwise.
Position Tool█ OVERVIEW
This script is an interactive measurement tool that can be used to evaluate or keep track of trades. Like the long and short position drawing tools, it calculates a risk reward ratio and a risk-adjusted position size from the entry, stop and take profit levels, but it also does much more:
• It can be used to configure long or short trades.
• All monetary values can be expressed in any number of currencies.
• The value of tick/pip movement (which varies with the position's size) is displayed in the currency you have selected.
• The CAGR ( Compound Annual Growth Rate ) for the trade can be displayed.
• It does live tracking of the position.
• You can configure alerts on entries and exits.
█ HOW TO USE IT
Load the indicator on an active chart (see here if you don't know how).
When you first load this script on a chart, you will enter an interactive selection mode where the script asks you to pick three points in price and time on your chart by clicking on the chart. Directions will appear in a blue box at the bottom of the screen with each click of the mouse. The first selection is the entry point for the trade you are considering, which takes into account both the time and level you choose, the next are the take profit and stop levels. Once you have selected all three points, the script will draw trade zones and labels containing the trade metrics. The script determines if the trade is a long or short from the position of the take profit and stop loss levels in relation to the entry price. If the take profit level is above the entry price, the stop must be below and vice versa, otherwise an error occurs.
You can change levels by dragging the handles that appear when you select the indicator, or by entering new values in the script's settings. The only way to re-enter interactive mode is to re-add the indicator to your chart.
Once you place the position tool on a chart, it will appear at the same levels on all symbols you use. If your scale is not set to "Scale price chart only", the position tool's levels will be taken into account when scaling the chart, which can cause the symbol's bars to be compressed. If your scale is set to "Scale price chart only", the position tool will still be there, but it will not impact the scale of the chart's bars, so you won't see it if it sits outside the symbol's price scale.
If you select the position tool on your chart and delete it, this will also delete the indicator from the chart. You will need to re-add it if you want to draw another position tool. You can add multiple instances of the indicator if you need a position tool on more than one of your charts.
█ FEATURES
Display
The position tool displays the following information for entries:
• The entry's price level with an '@' sign before it.
• Open or Closed P&L : For an open trade, the "Open P&L" displays the difference in money value between the entry level and the chart's current price.
For a closed trade, the "Closed P&L" displays the realized P&L on the trade.
• Quantity : The trade size, which takes into account the risk tolerance you set in the script's settings.
• RR : The reward to risk ratio expresses the relationship of the distance between the entry and the take profit level vs the entry and the stop level.
Example: A $100 stop with a $100 target will have a ratio of 1:1, whereas a $200 target with the same stop will have a 2:1 ratio.
• Per tick/pip : Represents the money value of a tick or pip movement.
• CAGR : The Compound Annual Growth Rate will be displayed on the main order label on trades that exceed one day in duration.
This value is calculated the same way as in our CAGR Custom Range indicator.
If the trade duration is less than one day, the metric will not be present in the display.
The stop and take profit levels display:
• Their price level with an '@' sign before it.
• Their distance from the entry in money value, percentage and ticks/pips.
• The projected end money value of the position if the level is reached. These values are calculated based on the trade size and the currency.
Currency adjustments
This indicator modifies the trade label's colors and values based on the final Profit and Loss (P&L), which considers the dynamic exchange rate between base and conversion currencies in its calculations when the conversion currency is a specified value other than the default. Depending on the cross rate between the base and account currencies, this process can yield a negative P&L on an otherwise successful simulated trade.
For instance, if your account is in currency XYZ, you might buy 10 Apple shares at $150 each, with the XYZ to USD exchange rate being 2:1. This purchase would cost you 3000 units of XYZ. Suppose that later on, the shares appreciate to $170 each, and you decide to sell. One might expect this trade to result in profit. However, if the exchange rate has now equalized to 1:1, the return on selling the shares, calculated in XYZ, would only be 1700 units, resulting in a loss of 1300 units XYZ.
The indicator will mark the P&L and the target labels in red in such cases, regardless of whether the market price reached the profit target, as the trade produced a net loss due to reduced funds after currency conversion. Conversely, an otherwise unsuccessful position can result in a net profit in the account currency due to conversion rate fluctuations. The final losses or gains appear in the label metrics, and the corresponding color coding reflects the trade's success or failure.
Settings
The settings in the "Trade sizing" section are used to calculate the position size and the monetary value of trades. Two types of risk can be chosen from the menu; a percentage based risk calculation, or a fixed money value. The risk is used to calculate the quantity of units to purchase to achieve that level of risk exposure. Example: An account size of $1000 and 10% risk will have a projected end amount of $900 if the stop loss is hit. The quantity is a product of this relationship; a projected number of units to allow for the equivalent of $100 of risk exposure over the change in price from the entry to the stop value.
The "Trade levels" allow you to manually set the entry, take profit and stop levels of an existing position tool on your chart.
You can control the appearance of the tool and the values it displays in the settings following these first two sections.
Alerts
Three alerts that will trigger when you configure an alert on this indicator. The first will send an alert when the entry price is breached by price action if that price has not already been breached in the previous price history. This is dependant on the entry location you select when placing the indicator on the chart. The other two alerts will trigger when either the stop loss or the take profit level is breached to signal that a trade exit has occurred.
█ NOTES FOR Pine Script™ CODERS
• Interactive inputs are implemented for input.time() and input.price() . These specialized input functions allow users to interact with a script.
You can create one interactive input for both time and price values by using the same `inline` argument in a pair of input.time() and input.price() function calls.
• We use the `cagr()` function from our ta library.
• The script uses the runtime.error() function to throw an error if the stop and limit prices are not placed on opposing sides of the entry price.
• We use the `currency` parameter in a request.security() call to convert currencies.
Look first. Then leap.
MA20 Hi-Lo-Close Magic BandThis is an improvement over my previous MA20 High Low Magic Band, as it keeps a central 20 MA reference point. So it can help find the up from MA20 lows and down from MA20 highs resisted or supported by MA20 average before final entry. Usable in any time frame of choice - 15m, 30m, Hourly or Daily. In the Hourly / Daily time frame, the signal used with the volume data may work in 6/10 events or more ... Happy trading!
Faytterro Estimator StrategyWhat is "Faytterro Estimator Strategy"?
"Faytterro Estimator Strategy" is strategy of faytterro estimator. if you want to know more about faytterro estimator:
What it does?
It trades according to the signals given by faytterro estimator and some additional restrictions.
How it does it?
Using the faytterro estimator and the following variables, it gives buy and sell signals in different sizes at ideal points.
How to use it?
The "source" part is used to change the source of faytterro estimator.
The "length" is the length of the fayterro estimator.
"Minimum entry-close gap" is the minimum distance between two transactions opened in opposite directions. For example, if you opened long at 20 500 and "Minimum entry-close gap" is 400, you will not receive a sell signal before the price goes above 20900.
If "minimum entry-entry gap" is the minimum difference between two transactions opened in the same direction. For example, if you open long at 20500 level and the "minimum entry-entry gap" is 400, you will not receive a "buy" signal before the price goes below the 20100 level.
"strong entry size" determines the size of strong signals. The size of ordinary signals is always 1.
note: default values for btc/usdt 1 hour timeframe.
Tick StrategyTick Strategy:
Questions many pine coders/traders have is, How to enter/exit trade as soon as trade condition is met i.e. do not wait till candle completion to enter/exit the trade. This strategy will help you to understand one of the way to achieve it.
This is an educational strategy to demonstrate, how one can trade based on tick data. This being a strategy based on tick data, it can be tested only on real time candles. This strategy will not take any trades on historical candles and cannot be used for back testing. All the strategy trades taken on real time candles will disappear (repainting) once chart is refreshed and new trades will be entered on real time candles.
The strategy will do nothing during off market hours and will not take any trades.
The strategy has been designed based on rules/inputs below:
1. Count the ticks from start of a candle till end of candle
2. Bifurcate ticks as up-ticks and down-ticks. If tick price is above previous tick price the tick is considered as up-tick and vice versa
3. Count the successive up-ticks and successive down-ticks
Strategy rules:
1. Track candle type (green or red) continuously on each tick (green candle is when latest tick price > previous tick price)
2. Take a long trade if work in progress (WIP) candle is green candle and we get successive up-ticks equal to user input ticks for trade
3. Take a short trade if work in progress (WIP) candle is red candle and we get successive down-ticks equal to user input ticks for trade
4. Exit the trade when we get successive ticks equal to user input ticks in opposite direction
5. Optionally for trade entry, user can decide whether to calculate successive up-ticks/down-ticks from beginning of candle or successive up-ticks/down-ticks anytime during the candle formation
6. Optionally for trade exit/square off, user can decide whether to apply exit rules on the entry candle or only from subsequent candle
Strategy setting:
1. '' – This is just to describe when trades are entered. This parameter is not used for any calculation
2. 'No of successive ticks to enter the trade' – User input to decide, number of successive ticks for trade entry
3. 'Count successive ticks for trade only from start of candle' – check this to count successive ticks only from beginning of a candle
4. 'Exit if succussive ticks in opposite direction' - User input to decide, number of successive ticks in opposite direction for exiting the trade
5. 'Apply exit criteria on entry candle' – check to allow exit of trade on the entry candle, if un-checked, trade will not be exited on the entry candle i.e. opposite direction ticks will be counted from subsequent candle
Information below will be displayed continuously on the chart:
1. Candle no – Candles are counted from start of the trading session. This is current candle being formed on the chart
2. Candle now – This shows either ‘Green’ or ‘Red’ based on type of candle being formed
3. Tick count – This is current tick number being processed. Tick number starts from 1 for each new candle
4. Up-tick count – Number of up-ticks during formation of current candle
5. Down-tick count – Number of down-ticks during formation of current candle
6. Successive up-ticks – Current successive up-tick count
7. Successive down-ticks – Current successive down-tick count
8. Up-tick volume – Volume associated with up-ticks
9. Down-tick volume – Volume associated with down-ticks
10. Up-tick volume % - This is % of volume associated with up-ticks
11. Total volume – Candle volume till now. (Some times you might observe small difference between total volume and the volume shown by volume indicator. The difference could be because of refresh rate of your screen)
12. Candle completion % - This shows current candles completion %. This is candle progress from start of candle till close of candle
PineHelperLibrary "PineHelper"
This library provides various functions to reduce your time.
recent_opentrade_entry_bar_index()
get a recent opentrade entry bar_index
Returns: (int) bar_index
recent_closedtrade_entry_bar_index()
get a recent closedtrade entry bar_index
Returns: (int) bar_index
recent_closedtrade_exit_bar_index()
get a recent closedtrade exit bar_index
Returns: (int) bar_index
all_opnetrades_roi()
get all aopentrades roi
Returns: (float) roi
bars_since_recent_opentrade_entry()
get bars since recent opentrade entry
Returns: (int) number of bars
bars_since_recent_closedtrade_entry()
get bars since recent closedtrade entry
Returns: (int) number of bars
bars_since_recent_closedtrade_exit()
get bars since recent closedtrade exit
Returns: (int) number of bars
recent_opentrade_entry_id()
get recent opentrade entry ID
Returns: (string) entry ID
recent_closedtrade_entry_id()
get recent closedtrade entry ID
Returns: (string) entry ID
recent_closedtrade_exit_id()
get recent closedtrade exit ID
Returns: (string) exit ID
recent_opentrade_entry_price()
get recent opentrade entry price
Returns: (float) price
recent_closedtrade_entry_price()
get recent closedtrade entry price
Returns: (float) price
recent_closedtrade_exit_price()
get recent closedtrade exit price
Returns: (float) price
recent_opentrade_entry_time()
get recent opentrade entry time
Returns: (int) time
recent_closedtrade_entry_time()
get recent closedtrade entry time
Returns: (int) time
recent_closedtrade_exit_time()
get recent closedtrade exit time
Returns: (int) time
time_since_recent_opentrade_entry()
get time since recent opentrade entry
Returns: (int) time
time_since_recent_closedtrade_entry()
get time since recent closedtrade entry
Returns: (int) time
time_since_recent_closedtrade_exit()
get time since recent closedtrade exit
Returns: (int) time
recent_opentrade_size()
get recent opentrade size
Returns: (float) size
recent_closedtrade_size()
get recent closedtrade size
Returns: (float) size
all_opentrades_size()
get all opentrades size
Returns: (float) size
recent_opentrade_profit()
get recent opentrade profit
Returns: (float) profit
all_opentrades_profit()
get all opentrades profit
Returns: (float) profit
recent_closedtrade_profit()
get recent closedtrade profit
Returns: (float) profit
recent_opentrade_max_runup()
get recent opentrade max runup
Returns: (float) runup
recent_closedtrade_max_runup()
get recent closedtrade max runup
Returns: (float) runup
recent_opentrade_max_drawdown()
get recent opentrade maxdrawdown
Returns: (float) mdd
recent_closedtrade_max_drawdown()
get recent closedtrade maxdrawdown
Returns: (float) mdd
max_open_trades_drawdown()
get max open trades drawdown
Returns: (float) mdd
recent_opentrade_commission()
get recent opentrade commission
Returns: (float) commission
recent_closedtrade_commission()
get recent closedtrade commission
Returns: (float) commission
qty_by_percent_of_equity(percent)
get qty by percent of equtiy
Parameters:
percent : (series float) percent that you want to set
Returns: (float) quantity
qty_by_percent_of_position_size(percent)
get size by percent of position size
Parameters:
percent : (series float) percent that you want to set
Returns: (float) size
is_day_change()
get bool change of day
Returns: (bool) day is change or not
is_in_trade()
get bool using number of bars
Returns: (bool) allowedToTrade
discord_message(name, message)
get json format discord message
Parameters:
name : (string) name of bot
message : (string) message that you want to send
Returns: (string) json format string
telegram_message(chat_id, message)
get json format telegram message
Parameters:
chat_id : (string) chatId of bot
message : (string) message that you want to send
Returns: (string) json format string
