Adaptive Trend Lines (Expo)Adaptive Trend Lines (Expo) identifies the current trend direction within the selected lookback period. The idea behind the indicator is that the trend lines should self adjust to the constantly changing market. The indicator adjusts itself to the market by using tr (true range) and stdev (standard deviation) as dynamic variables.
The indicator displays positive- and negative trend channels.
HOW TO USE
1. Use the indicator to identify the trend direction.
I hope you find this indicator useful , and please comment or contact me if you like the script or have any questions/suggestions for future improvements. Thanks!
I will continually work on this indicator , so please share your experience and feedback as it will enable me to make even better improvements. Thanks to everyone that has already contacted me regarding my scripts. Your feedback is valuable for future developments!
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Disclaimer
Copyright by Zeiierman.
The information contained in my scripts/indicators/ideas does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My scripts/indicators/ideas are only for educational purposes!
Pesquisar nos scripts por "THE SCRIPT"
GreedZone indicator - Contrarian Indicator"Be fearful when others are greedy, and greedy when others are fearful" - Warren Buffett. Greedzone is a contrarian indicator that gives us an indication when greed begins to take over in the market. Traders should be prepared for increased volatility and good trading opportunities.
The Greedzone is visualized with green candlesticks above the price.
HOW TO USE
1. Use the indicator to identify when investors are greedy.
2. Use the indicator to identify potential reversal points.
INDICATOR IN ACTION
1 hour chart
5 min chart
I hope you find this indicator useful , and please comment or contact me if you like the script or have any questions/suggestions for future improvements. Thanks!
I will continually work on this indicator, so please share your experience and feedback as it will enable me to make even better improvements. Thanks to everyone that has already contacted me regarding my scripts. Your feedback is valuable for future developments!
-----------------
Disclaimer
Copyright by Zeiierman.
The information contained in my scripts/indicators/ideas does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My scripts/indicators/ideas are only for educational purposes!
Fearzone (Expo) - Contrarian Indicator"Be fearful when others are greedy, and greedy when others are fearful" - Warren Buffett. Fearzone is a contrarian indicator that gives us an indication when fear begins to take over in the market. Traders should be prepared for increased volatility and good trading opportunities.
The Fearzone is visualized with red candlesticks below the price.
This version of the FearZone indicator is slightly different from the one ©kruskakli has published.
HOW TO USE
1. Use the indicator to identify when investors are fearful.
2. Use the indicator to identify potential reversal points.
INDICATOR IN ACTION
1 hour chart
5 min chart
I hope you find this indicator useful , and please comment or contact me if you like the script or have any questions/suggestions for future improvements. Thanks!
I will continually work on this indicator, so please share your experience and feedback as it will enable me to make even better improvements. Thanks to everyone that has already contacted me regarding my scripts. Your feedback is valuable for future developments!
-----------------
Disclaimer
Copyright by Zeiierman.
The information contained in my scripts/indicators/ideas does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My scripts/indicators/ideas are only for educational purposes!
Camerilla PivotsBefore starting special thanks to @QuantNomad for his script "Ultimate Pivot Point Alerts"
Link : -
Please follow and support him for his work.
In this script I'm modifying how time frame factor is imported into the script and removing other types of Pivots and cleaning it further for only CAMs, I've also added the formulas for 5 and 6 numbers, it will help in trading breakout strategies.
Note that this way of importing Time frame produces minor difference in readings/levels from how it is done in QuantNomads script, so before taking your pics you should calculate your levels on separate sheet and compare which ones are working for you and your strategy.
I've been using this CAM setup for almost a year now, so I coded it as per my needs, it is up to users to utilize it to theirs.
Further utility:
1. You can hide/unhide S/R levels 5/6
2. This is MultiTimeframe version, meaning you can change Time-frame of Pivots being displayed on any TF chart.
3. Lines are produced for only level 3 and 4. And you can choose to hide them. Only Pivot line is kept and can not be hidden.
4. You can also choose to hide/unhide level value and only see label if you want.
5. No historical levels are kept to avoid clutter.
I've not included alerts as I don't use them, but if anyone wants it I suggest referring to @QuantNomad script bank. He has published number of excellent scripts in this regard.
There is no restrictions on this script, it can be used and reproduced freely. Its my way of doing little something for community and my first script.
Enjoy.
Forex session - Opening Range- Jayy fixed updatedOpening Range (OR) for Forex 24 hour regular session. This is not for regular market day sessions addressed in a separate script.
This script fixes four issues:
syntax error when code compiles
messed up opening range the day after a holiday Monday
flaky plotting of the opening range and targets that required page reloading
TradingView problems with starting forex session at 1700 hours EST/EDT when using certain securities eg FX_IDC currently (Jan 2017)
Additions in his code are more options for trading range
Time compensation option for some securities that incorrectly start sessions at 1200 hrs instead of 1700 hrs NY time
- this glitch is likely temporary but present when this script update was created
More opening range time period choices
Opening Range Targets:
Opening Range Targets as per Leaf_West
Targets are set at 127% , 162%, 200 %, 262 %, 362%, 423%, 685%, 1109% and 1794% and this can be traded intraday using methods described here charts-by-leaf.com I also have some Leaf West PDFs that describe how the targets are set and how they are traded. There are others that use opening range.
The Time Session Glitch and the Fix:
The script will correctly default to 1700 hrs to 1700hrs EDT/EST session for FXCM.
Strangely some securities appear to erroneously start their session at 1200 hrs ie. My guess is that they are somehow tied to GMT+0 instead of New York time (GMT+5). See this for yourself by selecting EURUSD using the FXCM exchange (FX:EURUSD) and then EURUSD from the IDC exchange (FX_IDC:EURUSD). The FX-IDC session opening range starts 5 hours
before it actually should at 1700 hrs EDT/EST. To correct for this I have implemented an automatic fix (default) and a user selected "5 hour time shift adjust. ment needed on some securities".
There is also a 4 hour time shift button which might be necessary when New York reverts from Eastern Standard Time
to Eastern Daylight Time (1 hour difference) in March (and then back again in November). In the default auto adjust mode you will need to select the 1 hour time shift. That is if this glitch still exists at that time.
I have looked at other scripts, other than my own and where the script is available, that need to use information about the opening bar and all have the same time shift issue
What are the choices for Opening Range?
The dialogue box offers the standard TradingView options.
Also where you see Pick Opening Range 1 to 12 hours , SET TO 0 To USE LINE ABOVE TO DETERMINE OR LENGTH
As the note says a number other than 0 will override the standard options from the line above
The dialogue box below in offers choices by hours 1 to 12. A number greater than 12 will still only give
720 minutes (12 hours) for the length of Opening Range.
What sessions within the FOREX time-frame are available?
The default is 1700 hours to 1700 hours EST/EDT
Check any one (only one) of the time periods to change the opening range period to suit.
New York opens at 8:00 am to 5:00 pm EST (EDT)
Tokyo opens at 7:00 pm to 4:00 am EST (EDT)
Sydney opens at 5:00 pm to 2:00 am EST (EDT)
London opens at 3:00 am to 12:00 noon EST (EDT)
There is a build your own session (click the button to select)
The two lines for inputting session times are almost identical except that the second line starts the be the same as each other.
The default for the build your own session is 2200 hours to 2200 hours. As of the time of publishing this plots EURUSD FX-IDC just right. The GMT+5 and GMT+4 do not apply to this selection.
See my comments above on this strange aberration.
The script originated from work done by Chris Moody. It has changed significantly but there are remnants of that script lurking within.
Script is free to all - that way you can see what is inside
Cheers Jayy
ValueAtTime█ OVERVIEW
This library is a Pine Script® programming tool for accessing historical values in a time series using UNIX timestamps . Its data structure and functions index values by time, allowing scripts to retrieve past values based on absolute timestamps or relative time offsets instead of relying on bar index offsets.
█ CONCEPTS
UNIX timestamps
In Pine Script®, a UNIX timestamp is an integer representing the number of milliseconds elapsed since January 1, 1970, at 00:00:00 UTC (the UNIX Epoch ). The timestamp is a unique, absolute representation of a specific point in time. Unlike a calendar date and time, a UNIX timestamp's meaning does not change relative to any time zone .
This library's functions process series values and corresponding UNIX timestamps in pairs , offering a simplified way to identify values that occur at or near distinct points in time instead of on specific bars.
Storing and retrieving time-value pairs
This library's `Data` type defines the structure for collecting time and value information in pairs. Objects of the `Data` type contain the following two fields:
• `times` – An array of "int" UNIX timestamps for each recorded value.
• `values` – An array of "float" values for each saved timestamp.
Each index in both arrays refers to a specific time-value pair. For instance, the `times` and `values` elements at index 0 represent the first saved timestamp and corresponding value. The library functions that maintain `Data` objects queue up to one time-value pair per bar into the object's arrays, where the saved timestamp represents the bar's opening time .
Because the `times` array contains a distinct UNIX timestamp for each item in the `values` array, it serves as a custom mapping for retrieving saved values. All the library functions that return information from a `Data` object use this simple two-step process to identify a value based on time:
1. Perform a binary search on the `times` array to find the earliest saved timestamp closest to the specified time or offset and get the element's index.
2. Access the element from the `values` array at the retrieved index, returning the stored value corresponding to the found timestamp.
Value search methods
There are several techniques programmers can use to identify historical values from corresponding timestamps. This library's functions include three different search methods to locate and retrieve values based on absolute times or relative time offsets:
Timestamp search
Find the value with the earliest saved timestamp closest to a specified timestamp.
Millisecond offset search
Find the value with the earliest saved timestamp closest to a specified number of milliseconds behind the current bar's opening time. This search method provides a time-based alternative to retrieving historical values at specific bar offsets.
Period offset search
Locate the value with the earliest saved timestamp closest to a defined period offset behind the current bar's opening time. The function calculates the span of the offset based on a period string . The "string" must contain one of the following unit tokens:
• "D" for days
• "W" for weeks
• "M" for months
• "Y" for years
• "YTD" for year-to-date, meaning the time elapsed since the beginning of the bar's opening year in the exchange time zone.
The period string can include a multiplier prefix for all supported units except "YTD" (e.g., "2W" for two weeks).
Note that the precise span covered by the "M", "Y", and "YTD" units varies across time. The "1M" period can cover 28, 29, 30, or 31 days, depending on the bar's opening month and year in the exchange time zone. The "1Y" period covers 365 or 366 days, depending on leap years. The "YTD" period's span changes with each new bar, because it always measures the time from the start of the current bar's opening year.
█ CALCULATIONS AND USE
This library's functions offer a flexible, structured approach to retrieving historical values at or near specific timestamps, millisecond offsets, or period offsets for different analytical needs.
See below for explanations of the exported functions and how to use them.
Retrieving single values
The library includes three functions that retrieve a single stored value using timestamp, millisecond offset, or period offset search methods:
• `valueAtTime()` – Locates the saved value with the earliest timestamp closest to a specified timestamp.
• `valueAtTimeOffset()` – Finds the saved value with the earliest timestamp closest to the specified number of milliseconds behind the current bar's opening time.
• `valueAtPeriodOffset()` – Finds the saved value with the earliest timestamp closest to the period-based offset behind the current bar's opening time.
Each function has two overloads for advanced and simple use cases. The first overload searches for a value in a user-specified `Data` object created by the `collectData()` function (see below). It returns a tuple containing the found value and the corresponding timestamp.
The second overload maintains a `Data` object internally to store and retrieve values for a specified `source` series. This overload returns a tuple containing the historical `source` value, the corresponding timestamp, and the current bar's `source` value, making it helpful for comparing past and present values from requested contexts.
Retrieving multiple values
The library includes the following functions to retrieve values from multiple historical points in time, facilitating calculations and comparisons with values retrieved across several intervals:
• `getDataAtTimes()` – Locates a past `source` value for each item in a `timestamps` array. Each retrieved value's timestamp represents the earliest time closest to one of the specified timestamps.
• `getDataAtTimeOffsets()` – Finds a past `source` value for each item in a `timeOffsets` array. Each retrieved value's timestamp represents the earliest time closest to one of the specified millisecond offsets behind the current bar's opening time.
• `getDataAtPeriodOffsets()` – Finds a past value for each item in a `periods` array. Each retrieved value's timestamp represents the earliest time closest to one of the specified period offsets behind the current bar's opening time.
Each function returns a tuple with arrays containing the found `source` values and their corresponding timestamps. In addition, the tuple includes the current `source` value and the symbol's description, which also makes these functions helpful for multi-interval comparisons using data from requested contexts.
Processing period inputs
When writing scripts that retrieve historical values based on several user-specified period offsets, the most concise approach is to create a single text input that allows users to list each period, then process the "string" list into an array for use in the `getDataAtPeriodOffsets()` function.
This library includes a `getArrayFromString()` function to provide a simple way to process strings containing comma-separated lists of periods. The function splits the specified `str` by its commas and returns an array containing every non-empty item in the list with surrounding whitespaces removed. View the example code to see how we use this function to process the value of a text area input .
Calculating period offset times
Because the exact amount of time covered by a specified period offset can vary, it is often helpful to verify the resulting times when using the `valueAtPeriodOffset()` or `getDataAtPeriodOffsets()` functions to ensure the calculations work as intended for your use case.
The library's `periodToTimestamp()` function calculates an offset timestamp from a given period and reference time. With this function, programmers can verify the time offsets in a period-based data search and use the calculated offset times in additional operations.
For periods with "D" or "W" units, the function calculates the time offset based on the absolute number of milliseconds the period covers (e.g., `86400000` for "1D"). For periods with "M", "Y", or "YTD" units, the function calculates an offset time based on the reference time's calendar date in the exchange time zone.
Collecting data
All the `getDataAt*()` functions, and the second overloads of the `valueAt*()` functions, collect and maintain data internally, meaning scripts do not require a separate `Data` object when using them. However, the first overloads of the `valueAt*()` functions do not collect data, because they retrieve values from a user-specified `Data` object.
For cases where a script requires a separate `Data` object for use with these overloads or other custom routines, this library exports the `collectData()` function. This function queues each bar's `source` value and opening timestamp into a `Data` object and returns the object's ID.
This function is particularly useful when searching for values from a specific series more than once. For instance, instead of using multiple calls to the second overloads of `valueAt*()` functions with the same `source` argument, programmers can call `collectData()` to store each bar's `source` and opening timestamp, then use the returned `Data` object's ID in calls to the first `valueAt*()` overloads to reduce memory usage.
The `collectData()` function and all the functions that collect data internally include two optional parameters for limiting the saved time-value pairs to a sliding window: `timeOffsetLimit` and `timeframeLimit`. When either has a non-na argument, the function restricts the collected data to the maximum number of recent bars covered by the specified millisecond- and timeframe-based intervals.
NOTE : All calls to the functions that collect data for a `source` series can execute up to once per bar or realtime tick, because each stored value requires a unique corresponding timestamp. Therefore, scripts cannot call these functions iteratively within a loop . If a call to these functions executes more than once inside a loop's scope, it causes a runtime error.
█ EXAMPLE CODE
The example code at the end of the script demonstrates one possible use case for this library's functions. The code retrieves historical price data at user-specified period offsets, calculates price returns for each period from the retrieved data, and then populates a table with the results.
The example code's process is as follows:
1. Input a list of periods – The user specifies a comma-separated list of period strings in the script's "Period list" input (e.g., "1W, 1M, 3M, 1Y, YTD"). Each item in the input list represents a period offset from the latest bar's opening time.
2. Process the period list – The example calls `getArrayFromString()` on the first bar to split the input list by its commas and construct an array of period strings.
3. Request historical data – The code uses a call to `getDataAtPeriodOffsets()` as the `expression` argument in a request.security() call to retrieve the closing prices of "1D" bars for each period included in the processed `periods` array.
4. Display information in a table – On the latest bar, the code uses the retrieved data to calculate price returns over each specified period, then populates a two-row table with the results. The cells for each return percentage are color-coded based on the magnitude and direction of the price change. The cells also include tooltips showing the compared daily bar's opening date in the exchange time zone.
█ NOTES
• This library's architecture relies on a user-defined type (UDT) for its data storage format. UDTs are blueprints from which scripts create objects , i.e., composite structures with fields containing independent values or references of any supported type.
• The library functions search through a `Data` object's `times` array using the array.binary_search_leftmost() function, which is more efficient than looping through collected data to identify matching timestamps. Note that this built-in works only for arrays with elements sorted in ascending order .
• Each function that collects data from a `source` series updates the values and times stored in a local `Data` object's arrays. If a single call to these functions were to execute in a loop , it would store multiple values with an identical timestamp, which can cause erroneous search behavior. To prevent looped calls to these functions, the library uses the `checkCall()` helper function in their scopes. This function maintains a counter that increases by one each time it executes on a confirmed bar. If the count exceeds the total number of bars, indicating the call executes more than once in a loop, it raises a runtime error .
• Typically, when requesting higher-timeframe data with request.security() while using barmerge.lookahead_on as the `lookahead` argument, the `expression` argument should be offset with the history-referencing operator to prevent lookahead bias on historical bars. However, the call in this script's example code enables lookahead without offsetting the `expression` because the script displays results only on the last historical bar and all realtime bars, where there is no future data to leak into the past. This call ensures the displayed results use the latest data available from the context on realtime bars.
Look first. Then leap.
█ EXPORTED TYPES
Data
A structure for storing successive timestamps and corresponding values from a dataset.
Fields:
times (array) : An "int" array containing a UNIX timestamp for each value in the `values` array.
values (array) : A "float" array containing values corresponding to the timestamps in the `times` array.
█ EXPORTED FUNCTIONS
getArrayFromString(str)
Splits a "string" into an array of substrings using the comma (`,`) as the delimiter. The function trims surrounding whitespace characters from each substring, and it excludes empty substrings from the result.
Parameters:
str (series string) : The "string" to split into an array based on its commas.
Returns: (array) An array of trimmed substrings from the specified `str`.
periodToTimestamp(period, referenceTime)
Calculates a UNIX timestamp representing the point offset behind a reference time by the amount of time within the specified `period`.
Parameters:
period (series string) : The period string, which determines the time offset of the returned timestamp. The specified argument must contain a unit and an optional multiplier (e.g., "1Y", "3M", "2W", "YTD"). Supported units are:
- "Y" for years.
- "M" for months.
- "W" for weeks.
- "D" for days.
- "YTD" (Year-to-date) for the span from the start of the `referenceTime` value's year in the exchange time zone. An argument with this unit cannot contain a multiplier.
referenceTime (series int) : The millisecond UNIX timestamp from which to calculate the offset time.
Returns: (int) A millisecond UNIX timestamp representing the offset time point behind the `referenceTime`.
collectData(source, timeOffsetLimit, timeframeLimit)
Collects `source` and `time` data successively across bars. The function stores the information within a `Data` object for use in other exported functions/methods, such as `valueAtTimeOffset()` and `valueAtPeriodOffset()`. Any call to this function cannot execute more than once per bar or realtime tick.
Parameters:
source (series float) : The source series to collect. The function stores each value in the series with an associated timestamp representing its corresponding bar's opening time.
timeOffsetLimit (simple int) : Optional. A time offset (range) in milliseconds. If specified, the function limits the collected data to the maximum number of bars covered by the range, with a minimum of one bar. If the call includes a non-empty `timeframeLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
timeframeLimit (simple string) : Optional. A valid timeframe string. If specified and not empty, the function limits the collected data to the maximum number of bars covered by the timeframe, with a minimum of one bar. If the call includes a non-na `timeOffsetLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
Returns: (Data) A `Data` object containing collected `source` values and corresponding timestamps over the allowed time range.
method valueAtTime(data, timestamp)
(Overload 1 of 2) Retrieves value and time data from a `Data` object's fields at the index of the earliest timestamp closest to the specified `timestamp`. Callable as a method or a function.
Parameters:
data (series Data) : The `Data` object containing the collected time and value data.
timestamp (series int) : The millisecond UNIX timestamp to search. The function returns data for the earliest saved timestamp that is closest to the value.
Returns: ( ) A tuple containing the following data from the `Data` object:
- The stored value corresponding to the identified timestamp ("float").
- The earliest saved timestamp that is closest to the specified `timestamp` ("int").
valueAtTime(source, timestamp, timeOffsetLimit, timeframeLimit)
(Overload 2 of 2) Retrieves `source` and time information for the earliest bar whose opening timestamp is closest to the specified `timestamp`. Any call to this function cannot execute more than once per bar or realtime tick.
Parameters:
source (series float) : The source series to analyze. The function stores each value in the series with an associated timestamp representing its corresponding bar's opening time.
timestamp (series int) : The millisecond UNIX timestamp to search. The function returns data for the earliest bar whose timestamp is closest to the value.
timeOffsetLimit (simple int) : Optional. A time offset (range) in milliseconds. If specified, the function limits the collected data to the maximum number of bars covered by the range, with a minimum of one bar. If the call includes a non-empty `timeframeLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
timeframeLimit (simple string) : (simple string) Optional. A valid timeframe string. If specified and not empty, the function limits the collected data to the maximum number of bars covered by the timeframe, with a minimum of one bar. If the call includes a non-na `timeOffsetLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
Returns: ( ) A tuple containing the following data:
- The `source` value corresponding to the identified timestamp ("float").
- The earliest bar's timestamp that is closest to the specified `timestamp` ("int").
- The current bar's `source` value ("float").
method valueAtTimeOffset(data, timeOffset)
(Overload 1 of 2) Retrieves value and time data from a `Data` object's fields at the index of the earliest saved timestamp closest to `timeOffset` milliseconds behind the current bar's opening time. Callable as a method or a function.
Parameters:
data (series Data) : The `Data` object containing the collected time and value data.
timeOffset (series int) : The millisecond offset behind the bar's opening time. The function returns data for the earliest saved timestamp that is closest to the calculated offset time.
Returns: ( ) A tuple containing the following data from the `Data` object:
- The stored value corresponding to the identified timestamp ("float").
- The earliest saved timestamp that is closest to `timeOffset` milliseconds before the current bar's opening time ("int").
valueAtTimeOffset(source, timeOffset, timeOffsetLimit, timeframeLimit)
(Overload 2 of 2) Retrieves `source` and time information for the earliest bar whose opening timestamp is closest to `timeOffset` milliseconds behind the current bar's opening time. Any call to this function cannot execute more than once per bar or realtime tick.
Parameters:
source (series float) : The source series to analyze. The function stores each value in the series with an associated timestamp representing its corresponding bar's opening time.
timeOffset (series int) : The millisecond offset behind the bar's opening time. The function returns data for the earliest bar's timestamp that is closest to the calculated offset time.
timeOffsetLimit (simple int) : Optional. A time offset (range) in milliseconds. If specified, the function limits the collected data to the maximum number of bars covered by the range, with a minimum of one bar. If the call includes a non-empty `timeframeLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
timeframeLimit (simple string) : Optional. A valid timeframe string. If specified and not empty, the function limits the collected data to the maximum number of bars covered by the timeframe, with a minimum of one bar. If the call includes a non-na `timeOffsetLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
Returns: ( ) A tuple containing the following data:
- The `source` value corresponding to the identified timestamp ("float").
- The earliest bar's timestamp that is closest to `timeOffset` milliseconds before the current bar's opening time ("int").
- The current bar's `source` value ("float").
method valueAtPeriodOffset(data, period)
(Overload 1 of 2) Retrieves value and time data from a `Data` object's fields at the index of the earliest timestamp closest to a calculated offset behind the current bar's opening time. The calculated offset represents the amount of time covered by the specified `period`. Callable as a method or a function.
Parameters:
data (series Data) : The `Data` object containing the collected time and value data.
period (series string) : The period string, which determines the calculated time offset. The specified argument must contain a unit and an optional multiplier (e.g., "1Y", "3M", "2W", "YTD"). Supported units are:
- "Y" for years.
- "M" for months.
- "W" for weeks.
- "D" for days.
- "YTD" (Year-to-date) for the span from the start of the current bar's year in the exchange time zone. An argument with this unit cannot contain a multiplier.
Returns: ( ) A tuple containing the following data from the `Data` object:
- The stored value corresponding to the identified timestamp ("float").
- The earliest saved timestamp that is closest to the calculated offset behind the bar's opening time ("int").
valueAtPeriodOffset(source, period, timeOffsetLimit, timeframeLimit)
(Overload 2 of 2) Retrieves `source` and time information for the earliest bar whose opening timestamp is closest to a calculated offset behind the current bar's opening time. The calculated offset represents the amount of time covered by the specified `period`. Any call to this function cannot execute more than once per bar or realtime tick.
Parameters:
source (series float) : The source series to analyze. The function stores each value in the series with an associated timestamp representing its corresponding bar's opening time.
period (series string) : The period string, which determines the calculated time offset. The specified argument must contain a unit and an optional multiplier (e.g., "1Y", "3M", "2W", "YTD"). Supported units are:
- "Y" for years.
- "M" for months.
- "W" for weeks.
- "D" for days.
- "YTD" (Year-to-date) for the span from the start of the current bar's year in the exchange time zone. An argument with this unit cannot contain a multiplier.
timeOffsetLimit (simple int) : Optional. A time offset (range) in milliseconds. If specified, the function limits the collected data to the maximum number of bars covered by the range, with a minimum of one bar. If the call includes a non-empty `timeframeLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
timeframeLimit (simple string) : Optional. A valid timeframe string. If specified and not empty, the function limits the collected data to the maximum number of bars covered by the timeframe, with a minimum of one bar. If the call includes a non-na `timeOffsetLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
Returns: ( ) A tuple containing the following data:
- The `source` value corresponding to the identified timestamp ("float").
- The earliest bar's timestamp that is closest to the calculated offset behind the current bar's opening time ("int").
- The current bar's `source` value ("float").
getDataAtTimes(timestamps, source, timeOffsetLimit, timeframeLimit)
Retrieves `source` and time information for each bar whose opening timestamp is the earliest one closest to one of the UNIX timestamps specified in the `timestamps` array. Any call to this function cannot execute more than once per bar or realtime tick.
Parameters:
timestamps (array) : An array of "int" values representing UNIX timestamps. The function retrieves `source` and time data for each element in this array.
source (series float) : The source series to analyze. The function stores each value in the series with an associated timestamp representing its corresponding bar's opening time.
timeOffsetLimit (simple int) : Optional. A time offset (range) in milliseconds. If specified, the function limits the collected data to the maximum number of bars covered by the range, with a minimum of one bar. If the call includes a non-empty `timeframeLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
timeframeLimit (simple string) : Optional. A valid timeframe string. If specified and not empty, the function limits the collected data to the maximum number of bars covered by the timeframe, with a minimum of one bar. If the call includes a non-na `timeOffsetLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
Returns: ( ) A tuple of the following data:
- An array containing a `source` value for each identified timestamp (array).
- An array containing an identified timestamp for each item in the `timestamps` array (array).
- The current bar's `source` value ("float").
- The symbol's description from `syminfo.description` ("string").
getDataAtTimeOffsets(timeOffsets, source, timeOffsetLimit, timeframeLimit)
Retrieves `source` and time information for each bar whose opening timestamp is the earliest one closest to one of the time offsets specified in the `timeOffsets` array. Each offset in the array represents the absolute number of milliseconds behind the current bar's opening time. Any call to this function cannot execute more than once per bar or realtime tick.
Parameters:
timeOffsets (array) : An array of "int" values representing the millisecond time offsets used in the search. The function retrieves `source` and time data for each element in this array. For example, the array ` ` specifies that the function returns data for the timestamps closest to one day and one week behind the current bar's opening time.
source (float) : (series float) The source series to analyze. The function stores each value in the series with an associated timestamp representing its corresponding bar's opening time.
timeOffsetLimit (simple int) : Optional. A time offset (range) in milliseconds. If specified, the function limits the collected data to the maximum number of bars covered by the range, with a minimum of one bar. If the call includes a non-empty `timeframeLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
timeframeLimit (simple string) : Optional. A valid timeframe string. If specified and not empty, the function limits the collected data to the maximum number of bars covered by the timeframe, with a minimum of one bar. If the call includes a non-na `timeOffsetLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
Returns: ( ) A tuple of the following data:
- An array containing a `source` value for each identified timestamp (array).
- An array containing an identified timestamp for each offset specified in the `timeOffsets` array (array).
- The current bar's `source` value ("float").
- The symbol's description from `syminfo.description` ("string").
getDataAtPeriodOffsets(periods, source, timeOffsetLimit, timeframeLimit)
Retrieves `source` and time information for each bar whose opening timestamp is the earliest one closest to a calculated offset behind the current bar's opening time. Each calculated offset represents the amount of time covered by a period specified in the `periods` array. Any call to this function cannot execute more than once per bar or realtime tick.
Parameters:
periods (array) : An array of period strings, which determines the time offsets used in the search. The function retrieves `source` and time data for each element in this array. For example, the array ` ` specifies that the function returns data for the timestamps closest to one day, week, and month behind the current bar's opening time. Each "string" in the array must contain a unit and an optional multiplier. Supported units are:
- "Y" for years.
- "M" for months.
- "W" for weeks.
- "D" for days.
- "YTD" (Year-to-date) for the span from the start of the current bar's year in the exchange time zone. An argument with this unit cannot contain a multiplier.
source (float) : (series float) The source series to analyze. The function stores each value in the series with an associated timestamp representing its corresponding bar's opening time.
timeOffsetLimit (simple int) : Optional. A time offset (range) in milliseconds. If specified, the function limits the collected data to the maximum number of bars covered by the range, with a minimum of one bar. If the call includes a non-empty `timeframeLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
timeframeLimit (simple string) : Optional. A valid timeframe string. If specified and not empty, the function limits the collected data to the maximum number of bars covered by the timeframe, with a minimum of one bar. If the call includes a non-na `timeOffsetLimit` value, the function limits the data using the largest number of bars covered by the two ranges. The default is `na`.
Returns: ( ) A tuple of the following data:
- An array containing a `source` value for each identified timestamp (array).
- An array containing an identified timestamp for each period specified in the `periods` array (array).
- The current bar's `source` value ("float").
- The symbol's description from `syminfo.description` ("string").
Geo. Geo.
This library provides a comprehensive set of geometric functions based on 2 simple types for point and line manipulation, point array calculations, some vector operations (Borrowed from @ricardosantos ), angle calculations, and basic polygon analysis. It offers tools for creating, transforming, and analyzing geometric shapes and their relationships.
View the source code for detailed documentation on each function and type.
═════════════════════════════════════════════════════════════════════════
█ OVERVIEW
This library enhances TradingView's Pine Script with robust geometric capabilities. It introduces the Point and Line types, along with a suite of functions for various geometric operations. These functionalities empower you to perform advanced calculations, manipulations, and analyses involving points, lines, vectors, angles, and polygons directly within your Pine scripts. The example is at the bottom of the script. ( Commented out )
█ CONCEPTS
This library revolves around two fundamental types:
• Point: Represents a point in 2D space with x and y coordinates, along with optional 'a' (angle) and 'v' (value) fields for versatile use. Crucially, for plotting, utilize the `.to_chart_point()` method to convert Points into plottable chart.point objects.
• Line: Defined by a starting Point and a slope , enabling calculations like getting y for a given x, or finding intersection points.
█ FEATURES
• Point Manipulation: Perform operations like addition, subtraction, scaling, rotation, normalization, calculating distances, dot products, cross products, midpoints, and more with Point objects.
• Line Operations: Create lines, determine their slope, calculate y from x (and vice versa), and find the intersection points of two lines.
• Vector Operations: Perform vector addition, subtraction, multiplication, division, negation, perpendicular vector calculation, floor, fractional part, sine, absolute value, modulus, sign, round, scaling, rescaling, rotation, and ceiling operations.
• Angle Calculations: Compute angles between points in degrees or radians, including signed, unsigned, and 360-degree angles.
• Polygon Analysis: Calculate the area, perimeter, and centroid of polygons. Check if a point is inside a given polygon and determine the convex hull perimeter.
• Chart Plotting: Conveniently convert Point objects to chart.point objects for plotting lines and points on the chart. The library also includes functions for plotting lines between individual and series of points.
• Utility Functions: Includes helper functions such as square root, square, cosine, sine, tangent, arc cosine, arc sine, arc tangent, atan2, absolute distance, golden ratio tolerance check, fractional part, and safe index/check for chart plotting boundaries.
█ HOW TO USE
1 — Include the library in your script using:
import kaigouthro/geo/1
2 — Create Point and Line objects:
p1 = geo.Point(bar_index, close)
p2 = geo.Point(bar_index , open)
myLine = geo.Line(p1, geo.slope(p1, p2))
// maybe use that line to detect a crossing for an alert ... hmmm
3 — Utilize the provided functions:
distance = geo.distance(p1, p2)
intersection = geo.intersection(line1, line2)
4 — For plotting labels, lines, convert Point to chart.point :
label.new(p1.to_chart_point(), " Hi ")
line.new(p1.to_chart_point(),p2.to_chart_point())
█ NOTES
This description provides a concise overview. Consult the library's source code for in-depth documentation, including detailed descriptions, parameter types, and return values for each function and method. The source code is structured with comprehensive comments using the `//@` format for seamless integration with TradingView's auto-documentation features.
█ Possibilities..
Library "geo"
This library provides a comprehensive set of geometric functions and types, including point and line manipulation, vector operations, angle calculations, and polygon analysis. It offers tools for creating, transforming, and analyzing geometric shapes and their relationships.
sqrt(value)
Square root function
Parameters:
value (float) : (float) - The number to take the square root of
Returns: (float) - The square root of the input value
sqr(x)
Square function
Parameters:
x (float) : (float) - The number to square
Returns: (float) - The square of the input value
cos(v)
Cosine function
Parameters:
v (float) : (series float) - The value to find the cosine of
Returns: (series float) - The cosine of the input value
sin(v)
Sine function
Parameters:
v (float) : (series float) - The value to find the sine of
Returns: (series float) - The sine of the input value
tan(v)
Tangent function
Parameters:
v (float) : (series float) - The value to find the tangent of
Returns: (series float) - The tangent of the input value
acos(v)
Arc cosine function
Parameters:
v (float) : (series float) - The value to find the arc cosine of
Returns: (series float) - The arc cosine of the input value
asin(v)
Arc sine function
Parameters:
v (float) : (series float) - The value to find the arc sine of
Returns: (series float) - The arc sine of the input value
atan(v)
Arc tangent function
Parameters:
v (float) : (series float) - The value to find the arc tangent of
Returns: (series float) - The arc tangent of the input value
atan2(dy, dx)
atan2 function
Parameters:
dy (float) : (float) - The y-coordinate
dx (float) : (float) - The x-coordinate
Returns: (float) - The angle in radians
gap(_value1, __value2)
Absolute distance between any two float values
Parameters:
_value1 (float) : First value
__value2 (float)
Returns: Absolute Positive Distance
phi_tol(a, b, tolerance)
Check if the ratio is within the tolerance of the golden ratio
Parameters:
a (float) : (float) The first number
b (float) : (float) The second number
tolerance (float) : (float) The tolerance percennt as 1 = 1 percent
Returns: (bool) True if the ratio is within the tolerance, false otherwise
frac(x)
frad Fractional
Parameters:
x (float) : (float) - The number to convert to fractional
Returns: (float) - The number converted to fractional
safeindex(x, limit)
limiting int to hold the value within the chart range
Parameters:
x (float) : (float) - The number to limit
limit (int)
Returns: (int) - The number limited to the chart range
safecheck(x, limit)
limiting int check if within the chartplottable range
Parameters:
x (float) : (float) - The number to limit
limit (int)
Returns: (int) - The number limited to the chart range
interpolate(a, b, t)
interpolate between two values
Parameters:
a (float) : (float) - The first value
b (float) : (float) - The second value
t (float) : (float) - The interpolation factor (0 to 1)
Returns: (float) - The interpolated value
gcd(_numerator, _denominator)
Greatest common divisor of two integers
Parameters:
_numerator (int)
_denominator (int)
Returns: (int) The greatest common divisor
method set_x(self, value)
Set the x value of the point, and pass point for chaining
Namespace types: Point
Parameters:
self (Point) : (Point) The point to modify
value (float) : (float) The new x-coordinate
method set_y(self, value)
Set the y value of the point, and pass point for chaining
Namespace types: Point
Parameters:
self (Point) : (Point) The point to modify
value (float) : (float) The new y-coordinate
method get_x(self)
Get the x value of the point
Namespace types: Point
Parameters:
self (Point) : (Point) The point to get the x-coordinate from
Returns: (float) The x-coordinate
method get_y(self)
Get the y value of the point
Namespace types: Point
Parameters:
self (Point) : (Point) The point to get the y-coordinate from
Returns: (float) The y-coordinate
method vmin(self)
Lowest element of the point
Namespace types: Point
Parameters:
self (Point) : (Point) The point
Returns: (float) The lowest value between x and y
method vmax(self)
Highest element of the point
Namespace types: Point
Parameters:
self (Point) : (Point) The point
Returns: (float) The highest value between x and y
method add(p1, p2)
Addition
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (Point) - the add of the two points
method sub(p1, p2)
Subtraction
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (Point) - the sub of the two points
method mul(p, scalar)
Multiplication by scalar
Namespace types: Point
Parameters:
p (Point) : (Point) - The point
scalar (float) : (float) - The scalar to multiply by
Returns: (Point) - the multiplied point of the point and the scalar
method div(p, scalar)
Division by scalar
Namespace types: Point
Parameters:
p (Point) : (Point) - The point
scalar (float) : (float) - The scalar to divide by
Returns: (Point) - the divided point of the point and the scalar
method rotate(p, angle)
Rotate a point around the origin by an angle (in degrees)
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to rotate
angle (float) : (float) - The angle to rotate by in degrees
Returns: (Point) - the rotated point
method length(p)
Length of the vector from origin to the point
Namespace types: Point
Parameters:
p (Point) : (Point) - The point
Returns: (float) - the length of the point
method length_squared(p)
Length squared of the vector
Namespace types: Point
Parameters:
p (Point) : (Point) The point
Returns: (float) The squared length of the point
method normalize(p)
Normalize the point to a unit vector
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to normalize
Returns: (Point) - the normalized point
method dot(p1, p2)
Dot product
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - the dot of the two points
method cross(p1, p2)
Cross product result (in 2D, this is a scalar)
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - the cross of the two points
method distance(p1, p2)
Distance between two points
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - the distance of the two points
method Point(x, y, a, v)
Point Create Convenience
Namespace types: series float, simple float, input float, const float
Parameters:
x (float)
y (float)
a (float)
v (float)
Returns: (Point) new point
method angle(p1, p2)
Angle between two points in degrees
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - the angle of the first point and the second point
method angle_between(p, pivot, other)
Angle between two points in degrees from a pivot point
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to calculate the angle from
pivot (Point) : (Point) - The pivot point
other (Point) : (Point) - The other point
Returns: (float) - the angle between the two points
method translate(p, from_origin, to_origin)
Translate a point from one origin to another
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to translate
from_origin (Point) : (Point) - The origin to translate from
to_origin (Point) : (Point) - The origin to translate to
Returns: (Point) - the translated point
method midpoint(p1, p2)
Midpoint of two points
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (Point) - The midpoint of the two points
method rotate_around(p, angle, pivot)
Rotate a point around a pivot point by an angle (in degrees)
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to rotate
angle (float) : (float) - The angle to rotate by in degrees
pivot (Point) : (Point) - The pivot point to rotate around
Returns: (Point) - the rotated point
method multiply(_a, _b)
Multiply vector _a with _b
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (Point) The result of the multiplication
method divide(_a, _b)
Divide vector _a by _b
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (Point) The result of the division
method negate(_a)
Negative of vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to negate
Returns: (Point) The negated point
method perp(_a)
Perpendicular Vector of _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The perpendicular point
method vfloor(_a)
Compute the floor of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The floor of the point
method fractional(_a)
Compute the fractional part of the elements from vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The fractional part of the point
method vsin(_a)
Compute the sine of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The sine of the point
lcm(a, b)
Least common multiple of two integers
Parameters:
a (int) : (int) The first integer
b (int) : (int) The second integer
Returns: (int) The least common multiple
method vabs(_a)
Compute the absolute of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The absolute of the point
method vmod(_a, _b)
Compute the mod of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
_b (float) : (float) The mod
Returns: (Point) The mod of the point
method vsign(_a)
Compute the sign of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The sign of the point
method vround(_a)
Compute the round of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The round of the point
method normalize_y(p, height)
normalizes the y value of a point to an input height
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to normalize
height (float) : (float) - The height to normalize to
Returns: (Point) - the normalized point
centroid(points)
Calculate the centroid of multiple points
Parameters:
points (array) : (array) The array of points
Returns: (Point) The centroid point
random_point(_height, _width, _origin, _centered)
Random Point in a given height and width
Parameters:
_height (float) : (float) The height of the area to generate the point in
_width (float) : (float) The width of the area to generate the point in
_origin (Point) : (Point) The origin of the area to generate the point in (default: na, will create a Point(0, 0))
_centered (bool) : (bool) Center the origin point in the area, otherwise, positive h/w (default: false)
Returns: (Point) The random point in the given area
random_point_array(_origin, _height, _width, _centered, _count)
Random Point Array in a given height and width
Parameters:
_origin (Point) : (Point) The origin of the area to generate the array (default: na, will create a Point(0, 0))
_height (float) : (float) The height of the area to generate the array
_width (float) : (float) The width of the area to generate the array
_centered (bool) : (bool) Center the origin point in the area, otherwise, positive h/w (default: false)
_count (int) : (int) The number of points to generate (default: 50)
Returns: (array) The random point array in the given area
method sort_points(points, by_x)
Sorts an array of points by x or y coordinate
Namespace types: array
Parameters:
points (array) : (array) The array of points to sort
by_x (bool) : (bool) Whether to sort by x-coordinate (true) or y-coordinate (false)
Returns: (array) The sorted array of points
method equals(_a, _b)
Compares two points for equality
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (bool) True if the points are equal, false otherwise
method max(origin, _a, _b)
Maximum of two points from origin, using dot product
Namespace types: Point
Parameters:
origin (Point)
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (Point) The maximum point
method min(origin, _a, _b)
Minimum of two points from origin, using dot product
Namespace types: Point
Parameters:
origin (Point)
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (Point) The minimum point
method avg_x(points)
Average x of point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The average x-coordinate
method avg_y(points)
Average y of point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The average y-coordinate
method range_x(points)
Range of x values in point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The range of x-coordinates
method range_y(points)
Range of y values in point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The range of y-coordinates
method max_x(points)
max of x values in point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The max of x-coordinates
method min_y(points)
min of x values in point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The min of x-coordinates
method scale(_a, _scalar)
Scale a point by a scalar
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to scale
_scalar (float) : (float) The scalar value
Returns: (Point) The scaled point
method rescale(_a, _length)
Rescale a point to a new magnitude
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to rescale
_length (float) : (float) The new magnitude
Returns: (Point) The rescaled point
method rotate_rad(_a, _radians)
Rotate a point by an angle in radians
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to rotate
_radians (float) : (float) The angle in radians
Returns: (Point) The rotated point
method rotate_degree(_a, _degree)
Rotate a point by an angle in degrees
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to rotate
_degree (float) : (float) The angle in degrees
Returns: (Point) The rotated point
method vceil(_a, _digits)
Ceil a point to a certain number of digits
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to ceil
_digits (int) : (int) The number of digits to ceil to
Returns: (Point) The ceiled point
method vpow(_a, _exponent)
Raise both point elements to a power
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
_exponent (float) : (float) The exponent
Returns: (Point) The point with elements raised to the power
method perpendicular_distance(_a, _b, _c)
Distance from point _a to line between _b and _c
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
_b (Point) : (Point) The start point of the line
_c (Point) : (Point) The end point of the line
Returns: (float) The perpendicular distance
method project(_a, _axis)
Project a point onto another
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to project
_axis (Point) : (Point) The point to project onto
Returns: (Point) The projected point
method projectN(_a, _axis)
Project a point onto a point of unit length
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to project
_axis (Point) : (Point) The unit length point to project onto
Returns: (Point) The projected point
method reflect(_a, _axis)
Reflect a point on another
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to reflect
_axis (Point) : (Point) The point to reflect on
Returns: (Point) The reflected point
method reflectN(_a, _axis)
Reflect a point to an arbitrary axis
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to reflect
_axis (Point) : (Point) The axis to reflect to
Returns: (Point) The reflected point
method angle_rad(_a)
Angle in radians of a point
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (float) The angle in radians
method angle_unsigned(_a, _b)
Unsigned degree angle between 0 and +180 by given two points
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (float) The unsigned angle in degrees
method angle_signed(_a, _b)
Signed degree angle between -180 and +180 by given two points
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (float) The signed angle in degrees
method angle_360(_a, _b)
Degree angle between 0 and 360 by given two points
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (float) The angle in degrees (0-360)
method clamp(_a, _vmin, _vmax)
Restricts a point between a min and max value
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to restrict
_vmin (Point) : (Point) The minimum point
_vmax (Point) : (Point) The maximum point
Returns: (Point) The restricted point
method lerp(_a, _b, _rate_of_move)
Linearly interpolates between points a and b by _rate_of_move
Namespace types: Point
Parameters:
_a (Point) : (Point) The starting point
_b (Point) : (Point) The ending point
_rate_of_move (float) : (float) The rate of movement (0-1)
Returns: (Point) The interpolated point
method slope(p1, p2)
Slope of a line between two points
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - The slope of the line
method gety(self, x)
Get y-coordinate of a point on the line given its x-coordinate
Namespace types: Line
Parameters:
self (Line) : (Line) - The line
x (float) : (float) - The x-coordinate
Returns: (float) - The y-coordinate
method getx(self, y)
Get x-coordinate of a point on the line given its y-coordinate
Namespace types: Line
Parameters:
self (Line) : (Line) - The line
y (float) : (float) - The y-coordinate
Returns: (float) - The x-coordinate
method intersection(self, other)
Intersection point of two lines
Namespace types: Line
Parameters:
self (Line) : (Line) - The first line
other (Line) : (Line) - The second line
Returns: (Point) - The intersection point
method calculate_arc_point(self, b, p3)
Calculate a point on the arc defined by three points
Namespace types: Point
Parameters:
self (Point) : (Point) The starting point of the arc
b (Point) : (Point) The middle point of the arc
p3 (Point) : (Point) The end point of the arc
Returns: (Point) A point on the arc
approximate_center(point1, point2, point3)
Approximate the center of a spiral using three points
Parameters:
point1 (Point) : (Point) The first point
point2 (Point) : (Point) The second point
point3 (Point) : (Point) The third point
Returns: (Point) The approximate center point
createEdge(center, radius, angle)
Get coordinate from center by radius and angle
Parameters:
center (Point) : (Point) - The center point
radius (float) : (float) - The radius of the circle
angle (float) : (float) - The angle in degrees
Returns: (Point) - The coordinate on the circle
getGrowthFactor(p1, p2, p3)
Get growth factor of spiral point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
p3 (Point) : (Point) - The third point
Returns: (float) - The growth factor
method to_chart_point(point)
Convert Point to chart.point using chart.point.from_index(safeindex(point.x), point.y)
Namespace types: Point
Parameters:
point (Point) : (Point) - The point to convert
Returns: (chart.point) - The chart.point representation of the input point
method plotline(p1, p2, col, width)
Draw a line from p1 to p2
Namespace types: Point
Parameters:
p1 (Point) : (Point) First point
p2 (Point) : (Point) Second point
col (color)
width (int)
Returns: (line) Line object
method drawlines(points, col, ignore_boundary)
Draw lines between points in an array
Namespace types: array
Parameters:
points (array) : (array) The array of points
col (color) : (color) The color of the lines
ignore_boundary (bool) : (bool) The color of the lines
method to_chart_points(points)
Draw an array of points as chart points on the chart with line.new(chartpoint1, chartpoint2, color=linecolor)
Namespace types: array
Parameters:
points (array) : (array) - The points to draw
Returns: (array) The array of chart points
polygon_area(points)
Calculate the area of a polygon defined by an array of points
Parameters:
points (array) : (array) The array of points representing the polygon vertices
Returns: (float) The area of the polygon
polygon_perimeter(points)
Calculate the perimeter of a polygon
Parameters:
points (array) : (array) Array of points defining the polygon
Returns: (float) Perimeter of the polygon
is_point_in_polygon(point, _polygon)
Check if a point is inside a polygon
Parameters:
point (Point) : (Point) The point to check
_polygon (array)
Returns: (bool) True if the point is inside the polygon, false otherwise
method perimeter(points)
Calculates the convex hull perimeter of a set of points
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (array) The array of points forming the convex hull perimeter
Point
A Point, can be used for vector, floating calcs, etc. Use the cp method for plots
Fields:
x (series float) : (float) The x-coordinate
y (series float) : (float) The y-coordinate
a (series float) : (float) An Angle storage spot
v (series float) : (float) A Value
Line
Line
Fields:
point (Point) : (Point) The starting point of the line
slope (series float) : (float) The slope of the line
GOMTRY.
Pure Price Action Liquidity Sweeps [LuxAlgo]The Pure Price Action Liquidity Sweeps indicator is a pure price action adaptation of our previously published and highly popular Liquidity-Sweeps script.
Similar to its earlier version, this indicator detects the presence of liquidity sweeps on the user's chart, while also identifying potential areas of support/resistance or entry when liquidity levels are taken. The key difference, however, is that this price action version relies solely on price patterns, eliminating the need for numerical swing length settings.
🔶 USAGE
A Liquidity Sweep occurs when the price breaks through a liquidity level , after which the price returns below/above the liquidity level , forming a wick.
The examples below show a bullish and bearish scenario of "a wick passing through a liquidity level where the price quickly comes back".
Short-term liquidity sweep detection is based on short-term swing levels. Some of these short-term levels, depending on further market developments, may evolve into intermediate-term levels and, in the long run, become long-term levels. Therefore, enabling short-term detection with the script means showing all levels, including minor and temporal ones. Depending on the trader's style, some of these levels may be considered noise. Enabling intermediate and long-term levels can help filter out this noise and provide more significant levels for trading decisions. For further details on how swing levels are identified please refer to the details section.
The Intermediate-term option selection for the same chart as above, filters out minor or noisy levels, providing clearer and more significant levels for traders to observe.
🔶 DETAILS
The swing points detection feature relies exclusively on price action, eliminating the need for numerical user-defined settings.
The first step involves detecting short-term swing points, where a short-term swing high (STH) is identified as a price peak surrounded by lower highs on both sides. Similarly, a short-term swing low is recognized as a price trough surrounded by higher lows on both sides.
Intermediate-term swing and long-term swing points are detected using the same approach but with a slight modification. Instead of directly analyzing price candles, we now utilize the previously detected short-term swing points. For intermediate-term swing points, we rely on short-term swing points, while for long-term swing points, we use the intermediate-term ones.
🔶 SETTINGS
Detection: Period options of the detected swing points.
🔶 RELATED SCRIPTS
Pure-Price-Action-Structures.
Liquidity-Sweeps.
[EVI]EMA with Volume LevelsThe " EMA with Volume Levels" script calculates the Exponential Moving Average (EMA) of the closing prices over a specified period and dynamically changes the color of the EMA based on volume levels. This indicator helps traders easily identify the current volume conditions. As the volume increases or decreases, the color of the EMA changes, providing a visual cue that can assist in making better trading decisions.
Features
This script offers the following features:
EMA Calculation: Calculates the Exponential Moving Average of the closing prices over the user-defined period (default is 360).
Volume Threshold Calculation: Computes the Simple Moving Average (SMA) and standard deviation of the volume over the user-defined period (default is 500), classifying the volume levels into extreme, high, medium, and low.
Dynamic EMA Color: Changes the color of the EMA dynamically based on volume levels, displaying it visually on the chart.
Chart Interpretation
EMA Color and Volume:
If the EMA line is red, it indicates very high volume.
If the EMA line is green, it indicates high volume.
If the EMA line is light green, it indicates medium volume.
If the EMA line is gray, it indicates low volume.
If the EMA line is dark gray, it indicates very low volume.
Cross Analysis:
When the EMA line and the candles are about to cross, and the volume is high (causing the EMA line to turn red), the candles are more likely to break through the 360-day EMA line.
Conversely, if the volume is low and the EMA line turns dark, the EMA line will likely act as a resistance or support level, increasing the likelihood of a bounce.
Additional Indicator:
Using the 20-day moving average along with this script can be beneficial. Combining these two moving averages can provide a more comprehensive view of market volatility.
Notes
Clean Chart: Ensure your chart is clean when using this script. Avoid including other scripts or unnecessary elements.
Additional Explanation: If further explanation is needed on how to use or understand the script, you can use drawings or images on the chart to provide additional context.
Divergence Toolkit (Real-Time)The Divergence Toolkit is designed to automatically detect divergences between the price of an underlying asset and any other @TradingView built-in or community-built indicator or script. This algorithm provides a comprehensive solution for identifying both regular and hidden divergences, empowering traders with valuable insights into potential trend reversals.
🔲 Methodology
Divergences occur when there is a disagreement between the price action of an asset and the corresponding indicator. Let's review the conditions for regular and hidden divergences.
Regular divergences indicate a potential reversal in the current trend.
Regular Bullish Divergence
Price Action - Forms a lower low.
Indicator - Forms a higher low.
Interpretation - Suggests that while the price is making new lows, the indicator is showing increasing strength, signaling a potential upward reversal.
Regular Bearish Divergence
Price Action - Forms a higher high.
Indicator - Forms a lower high.
Interpretation - Indicates that despite the price making new highs, the indicator is weakening, hinting at a potential downward reversal.
Hidden divergences indicate a potential continuation of the existing trend.
Hidden Bullish Divergence
Price Action - Forms a higher low.
Indicator - Forms a lower low.
Interpretation - Suggests that even though the price is retracing, the indicator shows increasing strength, indicating a potential continuation of the upward trend.
Hidden Bearish Divergence
Price Action - Forms a lower high.
Indicator - Forms a higher high.
Interpretation - Indicates that despite a retracement in price, the indicator is still strong, signaling a potential continuation of the downward trend.
In both regular and hidden divergences, the key is to observe the relationship between the price action and the indicator. Divergences can provide valuable insights into potential trend reversals or continuations.
The methodology employed in this script involves the detection of divergences through conditional price levels rather than relying on detected pivots. Traditionally, divergences are created by identifying pivots in both the underlying asset and the oscillator. However, this script employs a trailing stop on the oscillator to detect potential swings, providing a real-time approach to identifying divergences, you may find more info about it here (SuperTrend Toolkit) . We detect swings or pivots simply by testing for crosses between the indicator and its trailing stop.
type oscillator
float o = Oscillator Value
float s = Trailing Stop Value
oscillator osc = oscillator.new()
bool l = ta.crossunder(osc.o, osc.s) => Utilized as a formed high
bool h = ta.crossover (osc.o, osc.s) => Utilized as a formed low
// Note: these conditions alone could cause repainting when they are met but canceled at a later time before the bar closes. Hence, we wait for a confirmed bar.
// The script also includes the option to immediately alert when the conditions are met, if you choose so.
By testing for conditional price levels, the script achieves similar outcomes without the delays associated with pivot-based methods.
type bar
float o = open
float h = high
float l = low
float c = close
bar b = bar.new()
bool hi = b.h < b.h => A higher price level has been created
bool lo = b.l > b.l => A lower price level has been created
// Note: These conditions do not check for certain price swings hence they may seldom result in inaccurate detection.
🔲 Setup Guide
A simple example on one of my public scripts, Standardized MACD
🔲 Utility
We may auto-detect divergences to spot trend reversals & continuations.
🔲 Settings
Source - Choose an oscillator source of which to base the Toolkit on.
Zeroing - The Mid-Line value of the oscillator, for example RSI & MFI use 50.
Sensitivity - Calibrates the sensitivity of which Divergencies are detected, higher values result in more detections but less accuracy.
Lifetime - Maximum timespan to detect a Divergence.
Repaint - Switched on, the script will trigger Divergencies as they happen in Real-Time, could cause repainting when the conditions are met but canceled at a later time before bar closes.
🔲 Alerts
Bearish Divergence
Bullish Divergence
Bearish Hidden Divergence
Bullish Hidden Divergence
As well as the option to trigger 'any alert' call.
The Divergence Toolkit provides traders with a dynamic tool for spotting potential trend reversals and continuations. Its innovative approach to real-time divergence detection enhances the timeliness of identifying market opportunities.
Rolling MACDThis indicator displays a Rolling Moving Average Convergence Divergence . Contrary to MACD indicators which use a fix time segment, RMACD calculates using a moving window defined by a time period (not a simple number of bars), so it shows better results.
This indicator is inspired by and use the Close & Inventory Bar Retracement Price Line to create an MACD in different timeframes.
█ CONCEPTS
If you are not already familiar with MACD, so look at Help Center will get you started www.tradingview.com
The typical MACD, short for moving average convergence/divergence, is a trading indicator used in technical analysis of stock prices, created by Gerald Appel in the late 1970s. It is designed to reveal changes in the strength, direction, momentum, and duration of a trend in a stock's price.
The MACD indicator(or "oscillator") is a collection of three time series calculated from historical price data, most often the closing price. These three series are: the MACD series proper, the "signal" or "average" series, and the "divergence" series which is the difference between the two. The MACD series is the difference between a "fast" (short period) exponential moving average (EMA), and a "slow" (longer period) EMA of the price series. The average series is an EMA of the MACD series itself.
Because RMACD uses a moving window, it does not exhibit the jumpiness of MACD plots. You can see the more jagged MACD on the chart above. I think both can be useful to traders; up to you to decide which flavor works for you.
█ HOW TO USE IT
Load the indicator on an active chart (see the Help Center if you don't know how).
Time period
By default, the script uses an auto-stepping mechanism to adjust the time period of its moving window to the chart's timeframe. The following table shows chart timeframes and the corresponding time period used by the script. When the chart's timeframe is less than or equal to the timeframe in the first column, the second column's time period is used to calculate RMACD:
Chart Time
timeframe period
1min 🠆 1H
5min 🠆 4H
1H 🠆 1D
4H 🠆 3D
12H 🠆 1W
1D 🠆 1M
1W 🠆 3M
You can use the script's inputs to specify a fixed time period, which you can express in any combination of days, hours and minutes.
By default, the time period currently used is displayed in the lower-right corner of the chart. The script's inputs allow you to hide the display or change its size and location.
Minimum Window Size
This input field determines the minimum number of values to keep in the moving window, even if these values are outside the prescribed time period. This mitigates situations where a large time gap between two bars would cause the time window to be empty, which can occur in non-24x7 markets where large time gaps may separate contiguous chart bars, namely across holidays or trading sessions. For example, if you were using a 1D time period and there is a two-day gap between two bars, then no chart bars would fit in the moving window after the gap. The default value is 10 bars.
//
This indicator should make trading easier and improve analysis. Nothing is worse than indicators that give confusingly different signals.
I hope you enjoy my new ideas
best regards
Chervolino
[ChasinAlts] SuppRe-me ZonesHello fellow tradeurs, I couldn't find one similar on TV so wanted to make it.. Took me a little while to figure some things out as I am in new coding territory with this script. I had a hard time finding ways to make only a partial zone/box disappear if price only crossed part of it. Nonetheless, I figured it out so I hope you enjoy the outcome. Now, allow me to take a second to first explain the utility that is this script...or at least expose my reasoning when I decided to go ahead with this little project and take the precious time necessary to learn parts of pine that I did not previously know how to deal with. Ultimately, I built this for the 1s-15s TF(except for the "Consecutive Bars/Large Bars" Boxes...Those were meant to use on both these second TFs and Higher TFs.... ). The reasoning behind all of this was to give me a more definitive answer to all of my questions regarding the speed at which it would take price to revisit areas that it very abruptly went to/left on a VERY short TF (like the 1sec charts)...or even if it EVER would). To determine this I wanted to draw lines starting at the end of large wicks, draw boxes spanning the entire span of large wicks, and lastly to draw boxes spanning the entire span of very large bodies. For this last one, not only did I want to draw a box on a single candle that possessed a large body but also if there were consecutive red candles in a row, their bodies could be summed up and if this summation exceeds the minimum body % threshold then it too counts just like a single large candled body would if it was larger than the threshold. All in all I really enjoyed this script and most importantly the data that it produces. What I found after coding the script was that (again on the 1 sec- 15 sec charts) was that price very quickly (relatively speaking I suppose) came back over these box/zoned areas and that the lines drawn from the tip of the large wicks would at some point in the near future act as very good support and resistance for price to either bounce off of or breakout from.
Now, with each of these objects you can choose to delete them when price crosses the object or have them continuously drawn on the chart...your call...but it gets awful messy sometimes if you let them continue printing.
Peace and love people...peace and love,
-ChasinAlts
Portfolio Laboratory [Kioseff Trading]Hello!
This script looks to experiment with historical portfolio performance. However, a hypothetical cash balance is not used; weighted percentage increases and decreases are used.
You can select up to 10 assets to include in the portfolio. Long and short positions are possible.
Show in the image are the portfolio's weight, the total return of the portfolio and the total return of the asset on the chart over the selected timeframe.
Shown in the image above are the constituents of the portfolio, which can include any asset, the weighted percentage gain/loss of the constituents in addition to 10 major indices and their respective total percentage gain/loss over the timeframe.
Shown in the image above are the dividend yield % of the portfolio and relevant portfolio metrics - ex-post calculations are applied and are predicated on simple returns.
Shown in the image above is a portfolio of all short positions; portfolio calculations adjusted to the modifications.
Also shown is a change in the index the portfolio is calculated against. I have been asked a few times to include NIFTY 50 in my scripts - I made sure this was achieved, lol!
Show in the image is a performance line of performance of percentage increases/decreases for the index calculated against, the asset on the chart, and the portfolio.
All lines start simultaneously on the selected start date at the close price of the session for the asset on your chart.
However, the right-hand scale, whether displaying price or percent, cannot be used to assess the performance of each line - they are useful for visualization only and can extend below zero on a low-priced asset. Calculations will not execute correctly when selecting a start date prior to any asset in the portfolio's first trading session; calculations do not begin on the first bar of the asset on your chart.
I decided to code the script this way so statistics remain fixed when moving from asset to asset!
To compensate for this limitation, I included a label plot and background color change at the first session in which all assets in the portfolio had at least one bar of price data. You can adjust the calculation start date to the date portrayed on the label to test al possible price data!
The statistics table, and the performance lines, can be hidden in the user input section.
I plan on putting a bit more work into this script. I have some ideas on what to include; however, any input is greatly appreciated! If there's something you would like me to include please let me know.
@scheplick mentioned me in a script he recently coded:
My inspiration came from his script! I thank him for that!
benchLibrary "bench"
A simple banchmark library to analyse script performance and bottlenecks.
Very useful if you are developing an overly complex application in Pine Script, or trying to optimise a library / function / algorithm...
Supports artificial looping benchmarks (of fast functions)
Supports integrated linear benchmarks (of expensive scripts)
One important thing to note is that the Pine Script compiler will completely ignore any calculations that do not eventually produce chart output. Therefore, if you are performing an artificial benchmark you will need to use the bench.reference(value) function to ensure the calculations are executed.
Please check the examples towards the bottom of the script.
Quick Reference
(Be warned this uses non-standard space characters to get the line indentation to work in the description!)
```
// Looping benchmark style
benchmark = bench.new(samples = 500, loops = 5000)
data = array.new_int()
if bench.start(benchmark)
while bench.loop(benchmark)
array.unshift(data, timenow)
bench.mark(benchmark)
while bench.loop(benchmark)
array.unshift(data, timenow)
bench.mark(benchmark)
while bench.loop(benchmark)
array.unshift(data, timenow)
bench.stop(benchmark)
bench.reference(array.get(data, 0))
bench.report(benchmark, '1x array.unshift()')
// Linear benchmark style
benchmark = bench.new()
data = array.new_int()
bench.start(benchmark)
for i = 0 to 1000
array.unshift(data, timenow)
bench.mark(benchmark)
for i = 0 to 1000
array.unshift(data, timenow)
bench.stop(benchmark)
bench.reference(array.get(data, 0))
bench.report(benchmark,'1000x array.unshift()')
```
Detailed Interface
new(samples, loops) Initialises a new benchmark array
Parameters:
samples : int, the number of bars in which to collect samples
loops : int, the number of loops to execute within each sample
Returns: int , the benchmark array
active(benchmark) Determing if the benchmarks state is active
Parameters:
benchmark : int , the benchmark array
Returns: bool, true only if the state is active
start(benchmark) Start recording a benchmark from this point
Parameters:
benchmark : int , the benchmark array
Returns: bool, true only if the benchmark is unfinished
loop(benchmark) Returns true until call count exceeds bench.new(loop) variable
Parameters:
benchmark : int , the benchmark array
Returns: bool, true while looping
reference(number, string) Add a compiler reference to the chart so the calculations don't get optimised away
Parameters:
number : float, a numeric value to reference
string : string, a string value to reference
mark(benchmark, number, string) Marks the end of one recorded interval and the start of the next
Parameters:
benchmark : int , the benchmark array
number : float, a numeric value to reference
string : string, a string value to reference
stop(benchmark, number, string) Stop the benchmark, ending the final interval
Parameters:
benchmark : int , the benchmark array
number : float, a numeric value to reference
string : string, a string value to reference
report(Prints, benchmark, title, text_size, position)
Parameters:
Prints : the benchmarks results to the screen
benchmark : int , the benchmark array
title : string, add a custom title to the report
text_size : string, the text size of the log console (global size vars)
position : string, the position of the log console (global position vars)
unittest_bench(case) Cache module unit tests, for inclusion in parent script test suite. Usage: bench.unittest_bench(__ASSERTS)
Parameters:
case : string , the current test case and array of previous unit tests (__ASSERTS)
unittest(verbose) Run the bench module unit tests as a stand alone. Usage: bench.unittest()
Parameters:
verbose : bool, optionally disable the full report to only display failures
Relative Volume (rVol), Better Volume, Average Volume ComparisonThis is the best version of relative volume you can find a claim which is based on the logical soundness of its calculation.
I have amalgamated various volume analysis into one synergistic script. I wasn't going to opensource it. But, as one of the lucky few winners of TradingClue 2. I felt obligated to give something back to the community.
Relative volume traditionally compares current volume to prior bar volume or SMA of volume. This has drawbacks. The question of relative volume is "Volume relative to what?" In the traditional scripts you'll find it displays current volume relative to the last number of bars. But, is that the best way to compare volume. On a daily chart, possibly. On a daily chart this can work because your units of time are uniform. Each day represents a full cycle of volume. However, on an intraday chart? Not so much.
Example: If you have a lookback of 9 on an hourly chart in a 24 hour market, you are then comparing the average volume from Midnight - 9 AM to the 9 AM volume. What do you think you'll find? Well at 9:30 when NY exchanges open the volume should be consistently and predictably higher. But though rVol is high relative to the lookback period, its actually just average or maybe even below average compared to prior NY session opens. But prior NY session opens are not included in the lookback and thus ignored.
This problem is the most visibly noticed when looking at the volume on a CME futures chart or some equivalent. In a 24 hour market, such as crypto, there are website's like skew can show you the volume disparity from time of day. This led me to believe that the traditional rVol calculation was insufficient. A better way to calculate it would be to compare the 9:30 am 30m bar today to the last week's worth of 9:30 am 30m bars. Then I could know whether today's volume at 9:30 am today is high or low based on prior 9:30 am bars. This seems to be a superior method on an intraday basis and is clearly superior in markets with irregular volume
This led me to other problems, such as markets that are open for less than 24 hours and holiday hours on traditional market exchanges. How can I know that the script is accurately looking at the correct prior relevant bars. I've created and/or adapted solutions to all those problems and these calculations and code snippets thus have value that extend beyond this rVol script for other pinecoders.
The Script
This rVol script looks back at the bars of the same time period on the viewing timeframe. So, as we said, the last 9:30 bars. Averages those, then divides the: . The result is a percentage expressed as x.xxx. Thus 1.0 mean current volume is equal to average volume. Below 1.0 is below the average and above 1.0 is above the average.
This information can be viewed on its own. But there are more levels of analysis added to it.
Above the bars are signals that correlate to the "Better Volume Indicator" developed by, I believe, the folks at emini-watch and originally adapted to pinescript by LazyBear. The interpretation of these symbols are in a table on the right of the indicator.
The volume bars can also be colored. The color is defined by the relationship between the average of the rVol outputs and the current volume. The "Average rVol" so to speak. The color coding is also defined by a legend in the table on the right.
These can be researched by you to determine how to best interpret these signals. I originally got these ideas and solid details on how to use the analysis from a fellow out there, PlanTheTrade.
I hope you find some value in the code and in the information that the indicator presents. And I'd like to thank the TradingView team for producing the most innovative and user friendly charting package on the market.
(p.s. Better Volume is provides better information with a longer lookback value than the default imo)
Credit for certain code sections and ideas is due to:
LazyBear - Better Volume
Grimmolf (From GitHub) - Logic for Loop rVol
R4Rocket - The idea for my rVol 1 calculation
And I can't find the guy who had the idea for the multiples of volume to the average. Tag him if you know him
Final Note: I'd like to leave a couple of clues of my own for fellow seekers of trading infamy.
Indicators: indicators are like anemometers (The things that measure windspeed). People talk bad about them all the time because they're "lagging." Well, you can't tell what the windspeed is unless the wind is blowing. anemometers are lagging indicators of wind. But forecasters still rely on them. You would use an indicator, which I would define as a instrument of measure, to tell you the windspeed of the markets. Conversely, when people talk positively about indicators they say "This one is great and this one is terrible." This is like a farmer saying "Shovels are great, but rakes are horrible." There are certain tools that have certain functions and every good tool has a purpose for a specific job. So the next time someone shares their opinion with you about indicators. Just smile and nod, realizing one day they'll learn... hopefully before they go broke.
How to forecast: Prediction is accomplished by analyzing the behavior of instruments of measure to aggregate data (using your anemometer). The data is then assembled into a predictive model based on the measurements observed (a trading system). That predictive model is tested against reality for it's veracity (backtesting). If the model is predictive, you can optimize your decision making by creating parameter sets around the prediction that are synergistic with the implications of the prediction (risk, stop loss, target, scaling, pyramiding etc).
<3
Tic Tac Toe (For Fun)Hello All,
I think all of you know the game "Tic Tac Toe" :) This time I tried to make this game, and also I tried to share an example to develop a game script in Pine. Just for fun ;)
Tic Tac Toe Game Rules:
1. The game is played on a grid that's 3 squares by 3 squares.
2. You are "O", the computer is X. Players take turns putting their marks in empty squares.
3. if a player makes 3 of her marks in a row (up, down, across, or diagonally) the he is the winner.
4. When all 9 squares are full, the game is over (draw)
So, how to play the game?
- The player/you can play "O", meaning your mark is "O", so Xs for the script. please note that: The script plays with ONLY X
- There is naming for all squears, A1, A2, A3, B1, B2, B3, C1, C2, C3. you will see all these squares in the options.
- also You can set who will play first => "Human" or "Computer"
if it's your turn to move then you will see "You Move" text, as seen in the following screenshot. for example you want to put "O" to "A1" then using options set A1 as O
How the script play?
it uses MinMax algorithm with constant depth = 4. And yes we don't have option to make recursive functions in Pine at the moment so I made four functions for each depth. this idea can be used in your scripts if you need such an algorithm. if you have no idea about MinMax algorithm you can find a lot of articles on the net :)
The script plays its move automatically if its turn to play. you will just need to set the option that computer played (A1, C3, etc)
if it's computer turn to play then it calculates and show the move it wants to play like "My Move : B3 <= X" then using options you need to set B3 as X
Also it checks if the board is valid or not:
I have tested it but if you see any bug let me know please
Enjoy!
[Autoview][BackTest]Dual MA Ribbons R0.12 by JustUncleLThis is an implementation of a strategy based on two MA Ribbons, a Fast Ribbon and a Slow Ribbon. This strategy can be used on Normal candlestick charts or Renko charts (if you are familiar with them).
The strategy revolves around a pair of scripts: One to generate alerts signals for Autoview and one for Backtesting, to tune your settings.
The risk management options are performed within the script to set SL(StopLoss), TP(TargetProfit), TSL(Trailing Stop Loss) and TTP (Trailing Target Profit). The only requirement for Autoview is to Buy and Sell as directed by this script, no complicated syntax is required.
The Dual Ribbons are designed to capture the inferred behavior of traders and investors by using two groups of averages:
> Traders MA Ribbon: Lower MA and Upper MA (Aqua=Uptrend, Blue=downtrend, Gray=Neutral), with center line Avg MA (Orange dotted line).
> Investors MAs Ribbon: Lower MA and Upper MA (Green=Uptrend, Red=downtrend, Gray=Neutral), with center line Avg MA (Fuchsia dotted line).
> Anchor time frame (0=current). This is the time frame that the MAs are calculated for. This way 60m MA Ribbons can be viewed on a 15 min chart to establish tighter Stop Loss conditions.
Trade Management options:
Option to specify Backtest start and end time.
Trailing Stop, with Activate Level (as % of price) and Trailing Stop (as % of price)
Target Profit Level, (as % of price)
Stop Loss Level, (as % of price)
BUY green triangles and SELL dark red triangles
Trade Order closed colour coded Label:
>> Dark Red = Stop Loss Hit
>> Green = Target Profit Hit
>> Purple = Trailing Stop Hit
>> Orange = Opposite (Sell) Order Close
Trade Management Indication:
Trailing Stop Activate Price = Blue dotted line
Trailing Stop Price = Fuschia solid stepping line
Target Profit Price = Lime '+' line
Stop Loss Price = Red '+' line
Dealing With Renko Charts:
If you choose to use Renko charts, make sure you have enabled the "IS This a RENKO Chart" option, (I have not so far found a way to Detect the type of chart that is running).
If you want non-repainting Renko charts you MUST use TRADITIONAL Renko Bricks. This type of brick is fixed and will not change size.
Also use Renko bricks with WICKS DISABLED. Wicks are not part of Renko, the whole idea of using Renko bricks is not to see the wick noise.
Set you chart Time Frame to the lowest possible one that will build enough bricks to give a reasonable history, start at 1min TimeFrame. Renko bricks are not dependent on time, they represent a movement in price. But the chart candlestick data is used to create the bricks, so lower TF gives more accurate Brick creation.
You want to size your bricks to 2/1000 of the pair price, so for ETHBTC the price is say 0.0805 then your Renko Brick size should be about 2*0.0805/1000 = 0.0002 (round up).
You may find there is some slippage in value, but this can be accounted for in the Backtest by setting your commission a bit higher, for Binance for example I use 0.2%
Special thanks goes to @CryptoRox for providing the initial Risk management Framework in his "How to automate this strategy for free using a chrome extension" example.
VWAP forex Yesterday Hi/Low update fix This script is an updte fix of an earlier script that stopped functioning when TradingView updated Pine script. This script plots Forex (24 hour session) VWAP, yesterday's high, low, open and close (HLOC),
the day before's HLOC -
Also plots higher timeframe 20 emas
1 minute 5, 15, 60 period 20 ema
5 minute 15, 60 period 20 ema
15 minute 60, 120 , 240 period 20 ema
60 minute 120, 240 period 20 ema
120 minute 240, D period 20 ema
240 minute D period 20 ema
Also signals inside bars (high is less than or equal to the previous bar's high and the low is greater than or equal to the previous low) the : true inside bars have a maroon triangle below the bar as well as a ">" above the bar.
If subsequest bars are inside the last bar before the last true inside bar they also are marked with an ">"
This is probably a slight variation from the way Leaf_West plots the inside bars.
It appears that he marks all bars that are inside the original bar until one a bar has a high or low
outside the original bar. But I would need to see an example on his charts.
The Time Session Glitch and the Fix FX_IDC, COINBASE and BITSTAMP:
The script will correctly default to 1700 hrs to 1700hrs EDT/EST session for FXCM.
Strangely some securities appear to erroneously start their session at 1200 hrs ie. My guess is that they are somehow tied to GMT+0 instead of New York time (GMT+5). See this for yourself by selecting EURUSD using the FXCM exchange (FX:EURUSD) and then EURUSD from the IDC exchange (FX_IDC:EURUSD). The FX-IDC session opening range starts 5 hours before it actually should at 1700 hrs EDT/EST. To correct for this I have implemented an automatic fix (default) and a user selected "5 hour time shift adjust. ment needed on some securities".
There is also a 4 hour time shift button which might be necessary when New York reverts from Eastern Standard Time to Eastern Daylight Time (1 hour difference) in March (and then back again in November). In the default auto adjust mode you will need to select the 1 hour time shift. That is if this glitch still exists at that time.
I have looked at other scripts, other than my own and where the script is available, that need to use information about the opening bar and all have the same time shift issue
COINBASE and BITSTAMP open at 0000 hours GMT. Since I use lines instead of circles or crosses I had to make a small adjustment to plot the lines correctly.
If it needs work let me know.
Jayy
alpha Renko intraday wave timeI was asked to share my experimental Renko intraday wave time. So here it is warts and all. The same for the rest - except the Weis cumulative volume.
Renko wave time is in minutes. This script is strictly intraday and has not been played with extensively.
You must use traditional Renko and set the script wave size to the same size as the Renko brick size.
If you click on the sideways wishbone or "V" in the middle upper part of the chart you will get all of the scripts in this particular sandbox. After clicking the sideways wish bone click on "make it mine". You will then have the whole sandbox. The only published script is the Weis cumulative wave.
The "Boys MAs" is supposed to be a script for daily charts and from within some kind of consolidation. In any case I am intrigued by some signals. You have a variety of sandbox options in the format section of the boys MAs.
These codes are pretty rough with lots of abandoned lines of script.
IU Trailing Stop Loss MethodsThe 'IU Trailing Stop Loss Methods' it's a risk management tool which allows users to apply 12 trailing stop-loss (SL) methods for risk management of their trades and gives live alerts when the trailing Stop loss has hit. Below is a detailed explanation of each input and the working of the Script.
Main Inputs:
- bar_time: Specifies the date from which the trade begins and entry price will be the open of the first candle.
- entry_type: Choose between 'Long' or 'Short' positions.
- trailing_method: Select the trailing stop-loss method. Options include ATR, Parabolic SAR, Supertrend, Point/Pip based, Percentage, EMA, Highest/Lowest, Standard Deviation, and multiple target-based methods.
- exit_after_close: If checked, exits the trade only after the candle closes.
Optional Inputs:
ATR Settings:
- atr_Length: Length for the ATR calculation.
- atr_factor: ATR multiplier for SL calculation.
Parabolic SAR Settings:
- start, increment, maximum: Parameters for the Parabolic SAR indicator.
Supertrend Settings:
- supertrend_Length, supertrend_factor: Length and factor for the Supertrend indicator.
Point/Pip Based:
- point_base: Set trailing SL in points/pips.
Percentage Based:
- percentage_base: Set SL as a percentage of entry price.
EMA Settings:
- ema_Length: Length for EMA calculation.
Standard Deviation Settings:
- std_Length, std_factor: Length and factor for standard deviation calculation.
Highest/Lowest Settings:
- highest_lowest_Length: Length for the highest/lowest SL calculation.
Target-Based Inputs:
- ATR, Point, Percentage, and Standard Deviation based target SL settings with customizable lengths and multipliers.
Entry Logic:
- Trades initiate based on the entry_type selected and the specified bar_time.
- If Long is selected, a long trade is initiated when the conditions match, and vice versa for Short.
Trailing Stop-Loss (SL) Methods Explained:
The strategy dynamically adjusts stop-loss based on the chosen method. Each method has its calculation logic:
- ATR: Stop-loss calculated using ATR multiplied by a user-defined factor.
- Parabolic SAR: Uses the Parabolic SAR indicator for trailing stop-loss.
- Supertrend: Utilizes the Supertrend indicator as the stop-loss line.
- Point/Pip Based: Fixed point-based stop-loss.
- Percentage Based: SL set as a percentage of entry price.
- EMA: SL based on the Exponential Moving Average.
- Highest/Lowest: Uses the highest high or lowest low over a specified period.
- Standard Deviation: SL calculated using standard deviation.
Exit Conditions:
- If exit_after_close is enabled, the position will only close after the candle confirms the stop-loss hit.
- If exit_after_close is disabled, the strategy will close the trade immediately when the SL is breached.
Visualization:
The script plots the chosen trailing stop-loss method on the chart for easy visualization.
Target-Based Trailing SL Logic:
- When a position is opened, the strategy calculates the initial stop-loss and progressively adjusts it as the price moves favorably.
- Each SL adjustment is stored in an array for accurate tracking and visualization.
Alerts and Labels:
- When the Entry or trailing stop loss is hit this scripts draws a label and give alert to the user that trailing stop has been hit for the trade.
Note - on the historical data The Script will show nothing if the entry and the exit has happened on the same candle, because we don't know what was hit first SL or TP (basically how the candle was formed on the lower timeframe).
Summary:
This script offers flexible trailing stop-loss options for traders who want dynamic risk management in their strategies. By offering multiple methods like ATR, SAR, Supertrend, and EMA, it caters to various trading styles and risk preferences.
Systematic Investment Tracker by Ceyhun Gonul### English Description
**Systematic Investment Tracker with Enhanced Features**
This script, titled **Systematic Investment Tracker with Enhanced Features**, is a TradingView tool designed to support systematic investments across different market conditions. It provides traders with two customizable investment strategies — **Continuous Buying** and **Declining Buying** — and includes advanced dynamic investment adjustment features for each.
#### Detailed Explanation of Script Features and Originality
1. **Two Investment Strategies**:
- **Continuous Buying**: This strategy performs purchases consistently at each interval, as set by the user, regardless of market price changes. It follows the principle of dollar-cost averaging, allowing users to build an investment position over time.
- **Declining Buying**: Unlike Continuous Buying, this strategy triggers purchases only when the asset's price has declined from the previous interval's closing price. This approach helps users capitalize on lower price points, potentially improving average costs during downward trends.
2. **Dynamic Investment Adjustment**:
- For both strategies, the script includes a **Dynamic Investment Adjustment** feature. If enabled, this feature increases the purchasing amount by 50% if the current price has fallen by a specific user-defined percentage relative to the previous price. This allows users to accumulate a larger position when the asset is declining, which may benefit long-term cost-averaging strategies.
3. **Customizable Time Frames**:
- Users can specify a **start and end date** for investment, allowing them to restrict or backtest strategies within a specific timeframe. This feature is valuable for evaluating strategy performance over specific market cycles or historical periods.
4. **Graphical Indicators and Labels**:
- The script provides graphical labels on the chart that display purchase points. These indicators help users visualize their investment entries based on the strategy selected.
- A summary **performance label** is also displayed, providing real-time updates on the total amount spent, accumulated quantity, average cost, portfolio value, and profit percentage for each strategy.
5. **Language Support**:
- The script includes English and Turkish language options. Users can toggle between these languages, allowing the summary label text and descriptions to be displayed in their preferred language.
6. **Performance Comparison Table**:
- An optional **Performance Comparison Table** is available, offering a side-by-side analysis of net profit, total investment, and profit percentage for both strategies. This comparison table helps users assess which strategy has yielded better returns, providing clarity on each approach's effectiveness under the chosen parameters.
#### How the Script Works and Its Uniqueness
This closed-source script brings together two established investment strategies in a single, dynamic tool. By integrating continuous and declining purchase strategies with advanced settings for dynamic investment adjustment, the script offers a powerful, flexible tool for both passive and active investors. The design of this script provides unique benefits:
- Enables automated, systematic investment tracking, allowing users to build positions gradually.
- Empowers users to leverage declines through dynamic adjustments to optimize average cost over time.
- Presents an easy-to-read performance label and table, enabling an efficient and transparent performance comparison for informed decision-making.
---
### Türkçe Açıklama
**Gelişmiş Özellikli Sistematik Yatırım Takipçisi**
**Gelişmiş Özellikli Sistematik Yatırım Takipçisi** adlı bu TradingView scripti, çeşitli piyasa koşullarında sistematik yatırım stratejilerini desteklemek üzere tasarlanmış bir araçtır. Script, kullanıcıya iki özelleştirilebilir yatırım stratejisi — **Sürekli Alım** ve **Düşen Alım** — ve her strateji için gelişmiş dinamik yatırım ayarlama seçenekleri sunar.
#### Script Özelliklerinin Detaylı Açıklaması ve Özgünlük
1. **İki Yatırım Stratejisi**:
- **Sürekli Alım**: Bu strateji, fiyat değişimlerine bakılmaksızın kullanıcının belirlediği her aralıkta sabit bir miktar yatırım yapar. Bu yaklaşım, uzun vadede pozisyonu kademeli olarak oluşturmak isteyenler için idealdir.
- **Düşen Alım**: Sürekli Alım’ın aksine, bu strateji yalnızca fiyat bir önceki aralığın kapanış fiyatına göre düştüğünde alım yapar. Bu yöntem, yatırımcıların daha düşük fiyatlardan alım yaparak ortalama maliyeti potansiyel olarak iyileştirmelerine yardımcı olur.
2. **Dinamik Yatırım Ayarlaması**:
- Her iki strateji için de **Dinamik Yatırım Ayarlaması** özelliği bulunmaktadır. Bu özellik aktif edildiğinde, mevcut fiyatın bir önceki fiyata göre kullanıcı tarafından belirlenen bir yüzde oranında düşmesi durumunda alım miktarını %50 artırır. Bu durum, uzun vadede maliyet ortalaması stratejilerine katkıda bulunur.
3. **Özelleştirilebilir Tarih Aralığı**:
- Kullanıcılar, yatırımı belirli bir tarih aralığında sınırlandırmak veya test etmek için bir **başlangıç ve bitiş tarihi** belirleyebilir. Bu özellik, strateji performansını geçmiş piyasa döngüleri veya belirli dönemlerde değerlendirmek için kullanışlıdır.
4. **Grafiksel İşaretleyiciler ve Etiketler**:
- Script, grafik üzerinde alım noktalarını gösteren işaretleyiciler sağlar. Bu görsel göstergeler, kullanıcıların seçilen stratejiye göre yatırım girişlerini görselleştirmesine yardımcı olur.
- Ayrıca, her strateji için harcanan toplam tutar, biriken miktar, ortalama maliyet, portföy değeri ve kâr yüzdesi gibi bilgileri gerçek zamanlı olarak gösteren bir **performans etiketi** sunar.
5. **Dil Desteği**:
- Script, İngilizce ve Türkçe dillerini desteklemektedir. Kullanıcılar, performans etiketi metninin ve açıklamalarının tercih ettikleri dilde görüntülenmesi için dil seçimini yapabilir.
6. **Performans Karşılaştırma Tablosu**:
- İsteğe bağlı olarak kullanılabilen bir **Performans Karşılaştırma Tablosu**, her iki strateji için net kâr, toplam yatırım ve kâr yüzdesi gibi bilgileri yan yana analiz eder. Bu tablo, kullanıcıların hangi stratejinin daha yüksek getiri sağladığını değerlendirmesine yardımcı olur.
#### Scriptin Çalışma Prensibi ve Özgünlüğü
Bu script, iki yatırım stratejisini gelişmiş bir araçta birleştirir. Sürekli ve düşen fiyatlara dayalı alım stratejilerini dinamik yatırım ayarlama özelliğiyle entegre ederek yatırımcılar için güçlü ve esnek bir çözüm sunar. Script’in tasarımı aşağıdaki benzersiz faydaları sağlamaktadır:
- Otomatik, sistematik yatırım takibi yaparak kullanıcıların pozisyonlarını kademeli olarak oluşturmalarına olanak tanır.
- Dinamik ayarlama ile düşüşlerden yararlanarak zaman içinde ortalama maliyeti optimize etme olanağı sağlar.
- Her iki stratejinin performansını basit ve anlaşılır bir şekilde karşılaştıran etiket ve tablo ile verimli bir performans değerlendirmesi sunar.
chrono_utilsLibrary "chrono_utils"
📝 Description
Collection of objects and common functions that are related to datetime windows session days and time ranges. The main purpose of this library is to handle time-related functionality and make it easy to reason about a future bar checking if it will be part of a predefined session and/or inside a datetime window. All existing session functionality I found in the documentation e.g. "not na(time(timeframe, session, timezone))" are not suitable for strategy scripts, since the execution of the orders is delayed by one bar, due to the script execution happening at the bar close. Moreover, a history operator with a negative value that looks forward is not allowed in any pinescript expression. So, a prediction for the next bar using the bars_back argument of "time()"" and "time_close()" was necessary. Thus, I created this library to overcome this small but very important limitation. In the meantime, I added useful functionality to handle session-based behavior. An interesting utility that emerged from this development is data anomaly detection where a comparison between the prediction and the actual value is happening. If those two values are different then a data inconsistency happens between the prediction bar and the actual bar (probably due to a holiday, half session day, a timezone change etc..)
🤔 How to Guide
To use the functionality this library provides in your script you have to import it first!
Copy the import statement of the latest release by pressing the copy button below and then paste it into your script. Give a short name to this library so you can refer to it later on. The import statement should look like this:
import jason5480/chrono_utils/2 as chr
To check if a future bar will be inside a window first of all you have to initialize a DateTimeWindow object.
A code example is the following:
var dateTimeWindow = chr.DateTimeWindow.new().init(fromDateTime = timestamp('01 Jan 2023 00:00'), toDateTime = timestamp('01 Jan 2024 00:00'))
Then you have to "ask" the dateTimeWindow if the future bar defined by an offset (default is 1 that corresponds th the next bar), will be inside that window:
// Filter bars outside of the datetime window
bool dateFilterApproval = dateTimeWindow.is_bar_included()
You can visualize the result by drawing the background of the bars that are outside the given window:
bgcolor(color = dateFilterApproval ? na : color.new(color.fuchsia, 90), offset = 1, title = 'Datetime Window Filter')
In the same way, you can "ask" the Session if the future bar defined by an offset it will be inside that session.
First of all, you should initialize a Session object.
A code example is the following:
var sess = chr.Session.new().from_sess_string(sess = '0800-1700:23456', refTimezone = 'UTC')
Then check if the given bar defined by the offset (default is 1 that corresponds th the next bar), will be inside the session like that:
// Filter bars outside the sessions
bool sessionFilterApproval = view.sess.is_bar_included()
You can visualize the result by drawing the background of the bars that are outside the given session:
bgcolor(color = sessionFilterApproval ? na : color.new(color.red, 90), offset = 1, title = 'Session Filter')
In case you want to visualize multiple session ranges you can create a SessionView object like that:
var view = SessionView.new().init(SessionDays.new().from_sess_string('2345'), array.from(SessionTimeRange.new().from_sess_string('0800-1600'), SessionTimeRange.new().from_sess_string('1300-2200')), array.from('London', 'New York'), array.from(color.blue, color.orange))
and then call the draw method of the SessionView object like that:
view.draw()
🏋️♂️ Please refer to the "EXAMPLE DATETIME WINDOW FILTER" and "EXAMPLE SESSION FILTER" regions of the script for more advanced code examples of how to utilize the full potential of this library, including user input settings and advanced visualization!
⚠️ Caveats
As I mentioned in the description there are some cases that the prediction of the next bar is not accurate. A wrong prediction will affect the outcome of the filtering. The main reasons this could happen are the following:
Public holidays when the market is closed
Half trading days usually before public holidays
Change in the daylight saving time (DST)
A data anomaly of the chart, where there are missing and/or inconsistent data.
A bug in this library (Please report by PM sending the symbol, timeframe, and settings)
Special thanks to @robbatt and @skinra for the constructive feedback 🏆. Without them, the exposed API of this library would be very lengthy and complicated to use. Thanks to them, now the user of this library will be able to get the most, with only a few lines of code!
Swing Assassin's Consolidated ScriptI put this script together to essentially consolidate a number of scripts that I use on a daily basis into one script. This is an ongoing improvement effort, so there may be some garbage in here right now so keep that in mind if you intend to use this to help in your trading.
There are 5 moving averages (Hull). I use the Fast, Mid and Slow to find entries after I us the Medium Slow and Super Slow to identify a trend. Otherwise, I have those three turned off.
This script also uses Bollinger Bands which I literally cannot trade without.
The script also has anchored VWAP , automated support/resistance lines, and a homebrewed Volume Profile that is a copy from Ildar Akhmetgaleev's indicator "Poor Man's Volume Profile" used under Mozilla Public License Version 2.0.
