Blockunity Level Presets (BLP)A simple tool for setting performance targets.
Level Presets (BLP) is a simple tool for setting upside and downside levels relative to the current price of any asset. In this way, you can track which price the asset needs to move towards in order to achieve a defined performance.
How to Use
This indicator is very easy to use, you can set up to 5 upward and downward targets in the parameters.
Elements
The main elements of this tool are upward (default green) and downward (default red) levels.
Settings
Several parameters can be defined in the indicator configuration.
In addition to configuring which performance value to set the level at, you can choose not to display it if you don't need it. For example, here we display only two levels:
You can also choose not to display the labels:
Also concerning labels, you can choose not to display them in currency format, but in numerical format only (for example, if you're viewing a non-USD pair, such as ETHBTC):
Finally, you can modify design elements such as colors, level widths and text size:
How it Works
Here's how upside (_u) and downside (_d) levels are calculated:
source = close
level_1_u = source + (source * (level_1 / 100))
level_1_d = math.max(source - (source * (level_1 / 100)), 0)
Statistics
Arbitrage Spread v1 : 1 pair + 1 chart [Arby.Trade]This indicator allows you to track in real time the change in the spread (the difference in the exchange rate) between two assets.
How does the indicator work?
In the indicator settings menu, the user selects two trading pairs, for example BTCUSDT on the Binance exchange and BTCUSDT on the Bybit exchange, after which the script will receive prices from both exchanges and compare them with each other, calculating the percentage deviation between prices (spread). The script can only work with those assets and exchanges that are on board TradingView.
According to the calculated spread value, the spread line is displayed on the screen. This line moves between values above zero and below. When the spread line is below zero, it means that the price of the asset on the first exchange is less than on the second. That is, by buying an asset on the first exchange and selling it on the second one, you can earn money (of course, it is important to take into account the commissions of the exchanges for these transactions). When the spread line is above zero, the opposite is true. When the spread is zero, the prices on both exchanges are the same and there is no arbitrage situation.
Indicator settings.
For a better visual representation of the current spread value, the indicator has the ability to set two threshold spread levels. The first threshold level is the level below which the spread is not interesting to the trader and he will not consider arbitrage deals. The second threshold level is the level of a particularly high spread. When the spread value exceeds the second threshold level, the spread values will be signed above the spread line, and the extreme values for the user-defined period of bars back will be additionally highlighted in a brighter color. Both threshold levels are displayed on the chart and the user can change their values in the indicator settings menu.
Alerts.
Additionally, you can set the threshold value of the spread, at which the script will send notifications from TradingView. We called it the Spread Signal Threshold. This threshold level has nothing to do with the visual thresholds described above. You can set a signal level exceeding the second visual threshold or make it lower, but it is important to understand that TradingView alerts will only be triggered if the Spread Signal Threshold is exceeded.
To set up alerts, open the "Alerts" tab in the TradingView menu on the right. Click the "Create Alert" button. Then, in the window that opens, select this indicator in the "Condition" line. After that, you can set a name for this alert and complete the notification setup by clicking the "Create" button.
We, the authors of this script, have been engaged in cryptocurrency arbitrage for a long time and, first of all, created it for ourselves and our daily arbitrage trading, but this does not prevent you from using it at your discretion for any types of assets and in any markets.
--
Данный индикатор позволяет отслеживать в реальном времени изменение спреда (разницы в курсе) между двумя активами.
Как устроен индикатор?
В меню настроек индикатора пользователь выбирает две торговые пары, например BTCUSDT на бирже Binance и BTCUSDT на бирже Bybit, после чего скрипт получит цены с обеих бирж и сравнит их между собой, рассчитав процентное отклонение между ценами (спред). Скрипт может работать только с теми активами и биржами, которые есть на борту TradingView, и это не мало.
По рассчитанному значению спреда на экран выводится линия спреда. Данная линия двигается между значениями то выше нуля, то ниже. Когда линия спреда ниже нуля это значит что цена на актив на первой бирже меньше, чем на второй. То есть, купив актив на первой бирже и продав его на второй можно заработать (конечно при этом важно учитывать комиссии бирж на совершение данных сделок). Когда линия спреда выше нуля - наоборот. Когда спред равен нулю - цены на обеих биржах одинаковы и арбитражная ситуация отсутствует.
Настройки индикатора.
Для лучшего визуального представления о текущем значении спреда индикатор имеет возможность задать два пороговых уровня спреда. Первый пороговый уровень – это уровень, ниже которого спред не интересен трейдеру и он не будет рассматривать арбитражные сделки. Второй пороговый уровень – это уровень особенно повышенного спреда. Когда значение спреда превышает второй пороговый уровень над линией спреда будут подписаны значения спреда, а экстремальные значения за заданный пользователем период баров назад будут дополнительно выделены более ярким цветом. Оба пороговых уровня отображаются на графике и пользователь может менять их значения в меню настроек индикатора.
Уведомления.
Дополнительно можно настроить пороговое значение спреда, при достижении которого скрипт будет отправлять уведомления от TradingView. Мы назвали это Spread Signal Threshold. Этот пороговый уровень никак не связан с визуальными пороговыми уровнями, описанными выше. Вы можете задать сигнальный уровень превышающий второй визуальный пороговый уровень или сделать его ниже, но важно понимать, что оповещения TradingView будут срабатывать только от превышения именно Spread Signal Threshold.
Для настройки оповещений откройте вкладку «Оповещения» в меню TradingView справа. Нажмите кнопку «Создать оповещение». Затем в открывшемся окне в строке «Условие» выберете данный индикатор. После чего вы можете задать название данному оповещению и завершить настройку оповещения, нажав кнопку «Создать».
Мы, авторы данного скрипта, давно занимаемся арбитражем криптовалюты и, в первую очередь, создавали его для себя и своей каждодневной арбитражной торговли, но это не мешает вам использовать его по своему усмотрению для любых видов активов и на любых рынках.
Inflation IndicatorThis script provides a great view of Year-over-Year (YoY) inflation rates for key countries.
The inflation data used per default are TradingView Tickers, but you can change them to anything you want from the settings.
There is no calculation in this script, all it does is providing a overview of inflation rates in a single indicator.
Inflation data for the USA, European Union, Australia, Canada, Switzerland, Japan, United Kingdom, and New Zealand (Inflation Symbols editable in the settings)
Customizable static line to indicate a specific threshold value (default: 2.0).
Table displaying country flags, names, and the latest inflation rates.
Country-representative colors for easy identification.
Conditional Volatility PercentileSimple Description: This indicator can basically help you find when a big move might happen ( This indicator can't determine the direction but when a big move could happen. ) Basically, a low-extreme value like 0 means that it only has room for upside, so volatility can only expand from that point on, and the fact that volatility mean reverts supports this.
Conditional Volatility Percentile Indicator
This indicator is a tool designed to view current market volatility relative to historical levels. It uses a statistical approach to assess the percentile rank of the calculated conditional volatility.
The Volatility Calculation
This indicator calculates conditional variance with user-defined parameters, which are Omega, Alpha, Beta, and Sigma, and then takes the square root of the variance to calculate the standard deviation. The script then calculates the percentile rank of the conditional variance over a specified lookback.
What this indicator tells you:
Volatility Assessment: Higher percentile values indicate heightened conditional volatility, suggesting increased market activity or potential stress. Meanwhile, lower percentiles suggest relatively lower conditional volatility.
Extreme Values: Volatility is a mean-reverting process. If the volatility percentile value is at a low value for an extended period of time, you can eventually bet on the volatility percentile value increasing with high confidence.
In financial markets, volatility itself exhibits mean-reverting properties. This means that periods of high volatility are likely to be followed by periods of lower volatility, and vice versa.
1. High Volatility Periods: High volatility levels may be followed by a subsequent decrease in volatility as the market returns to a more typical state.
2. Low Volatility Periods: Periods of low volatility may be followed by an uptick in volatility as the market experiences new information or changes in sentiment.
Self Optimizing PSAR [Starbots]Self Optimizing Parabolic SAR Strategy (non-repainting)
Strategy constantly backtest 169 different combinations of Parabolic SAR indicator for maximum profitability and trades based on the best performing combination at that time.
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# Parabolic SAR (PSAR)
Parabolic SAR is a time and price technical analysis tool created by J. Welles Wilder and it's primarily used to identify points of potential stops and reverses. In fact, the SAR in Parabolic SAR stands for "Stop and Reverse". The indicator's calculations create a parabola which is located below price during a Bullish Trend and above Price during a Bearish Trend.
You can read more about this indicator here:
www.tradingview.com
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The logic of self - optimizing:
This script is always backtesting 169 different combinations of Parabolic SAR settings in the background and saves the net. profit gained for every single one of them, then strategy selects and use the best performing combination of settings currently available for you to trade.
It's recalculating on every bar close - if one of the parameters starts performing better than others - have a higher net profit gain (it's literally like running 169 backtests with different settings) strategy switches to that parameter and continues trading like that until one of the other indicator parameters starts performing better again and switches to that settings.
We are optimizing our strategy based on 13 different 'Increment' factors of PSAR. We keep the 'Start' factor (default 0.02) and 'Max Value' factor (default 0.2) at default for all of them.
According to creator of this indicator J. Welles Wilder, we usually want to change only 'Increment' factors of PSAR in the calculation and leave the rest at default and that's what we do, we are changing only 'Increment' input.
Inputs : (you don't need to change them at all, it's a good balance for fast and slow detection of trends on PSAR)
Start = 0.02
Max value = 0.2
Increment1 = 0.005, Increment2 = 0.01, Increment3 = 0.015
Increment4 = 0.02, Increment5 = 0.025, Increment6 = 0.03
Increment7 = 0.035, Increment8 = 0.04, Increment9 = 0.045
Increment10 = 0.05, Increment11 = 0.055, Increment12 = 0.06
Increment13 = 0.065
PSAR buy / sell conditions looks like this:
PSAR1 = start 0.02, max value 0.2, increment1 0.005
PSAR2 = start 0.02, max value 0.2, increment2 0.01
PSAR3 = start 0.02, max value 0.2, increment3 0.015
PSAR4 = start 0.02, max value 0.2, increment3 0.02
...
PSAR13 = start 0.02, max value 0.2, increment13 0.065
Backtester in the background works like this:
backtest buying PSAR1 settings with selling PSAR1 settings => save net. profit
backtest buy PSAR1 with sell PSAR2 ;
backtest buy PSAR1 with sell PSAR3 ;
backtest buy PSAR1 with sell PSAR4 ;
..........
backtest buy PSAR1 with sell PSAR13 ;
..........
backtest buy PSAR13 with sell PSAR1 ;
backtest buy PSAR13 with sell PSAR2 ;
......
backtest buy PSAR13 with sell PSAR13 ;
=>
It will backtest 16x16=169 different PSAR settings and save their profits.
Your strategy then trades based on the best performing (highest net.profit) PSAR Setting currently available. It will check the calculations and backtest them on every new bar close - it's like running 169 strategies at time, and manually selecting the best performing one.
________________________________________________________________________
If you wish to use it as INDICATOR - turn on 'Recalculate after every tick' in Properties tab to have this script updating constantly and use it as a normal Indicator tool for manual trading.
Strategy example is backtested on Daily chart of SHIBUSDT Binance
All settings at default. (1000 capital, 100 order size, 0.1% fee, 1 tick slippage)
Settings:
-Start = default Parabolic SAR setting is 0.02
-Max Value = default Parabolic SAR setting is 0.2
--Recommended PSAR Increment settings:
0.02 is default, higher timeframes usually performs good on the faster Increment factors 0.03-0.05+, smaller timeframes on slow Increment factors 0.005-0.02. I recommend you the most common and logical 13 different Increment factors for optimizing in the strategy as default already (from 0.005 to 0.065 - strategy will then optimize and trade based on the most profitable combination).
- Noise-Intensity Filter 🐎0.00-0.20%🐢
This will punish the tiny trades made by certain combinations and give more advantage to big average trades. It's basically like fee calculation, it will deduct 0.xx% fee from every trade when optimizing on their backtests.
You will usually want to have it around 0.05-0.10% like your fees on exchange.
-> 🐎Less than <0.10% allows strategy to be VERY SENSITIVE to market. (a lot of trades - quick buy-sell changes)
-> 🐢More than >0.10% will slow down the strategy, it will be LESS SENSITIVE to market volatility. (less trades - slowly switches the trend direction from buy to sell)
Close Trades on Neutral
After a lot of Trades, Algo starts developing self-intelligence. It can also have a neutral score. (Grey Plots). Sell when the strategy is neutral.
Other settings:
-Take Profit, Multiple Take Profit, Trailing Take Profit, Stop Loss, Trailing Stop Loss with functional alerts.
-Backtesting Range - backtest within your desired time window. Example: 'from 01 / 01 /2020 to 01 / 01 /2023'.
- Strategy is trading on the bar close without repaint. You can trade Long-Sell/Short Sell or Long-Short both directions. Alerts available, insert webhook messages in the inputs.
- Turn on Profit Calendar for better overview of how your strategy performs monthly/annualy
- Notes window : add your custom comments in here or save your webhook message text inside here for later use. I find this helpful to save texts inside.
Recommended TF : 4h, 8h, 1d (Trend Indicators are good at detecting directions of the market, but we can have a lot of noise and false movements on charts, you want to avoid that and ride the long term movements)
This script is fairly simple to use. It's self-optimizing and adjusting to the markets on the go.
TimeSeriesRecurrencePlotLibrary "TimeSeriesRecurrencePlot"
In descriptive statistics and chaos theory, a recurrence plot (RP) is a plot showing, for each moment i i in time, the times at which the state of a dynamical system returns to the previous state at `i`, i.e., when the phase space trajectory visits roughly the same area in the phase space as at time `j`.
```
A recurrence plot (RP) is a graphical representation used in the analysis of time series data and dynamical systems. It visualizes recurring states or events over time by transforming the original time series into a binary matrix, where each element represents whether two consecutive points are above or below a specified threshold. The resulting Recurrence Plot Matrix reveals patterns, structures, and correlations within the data while providing insights into underlying mechanisms of complex systems.
```
~starling7b
___
Reference:
en.wikipedia.org
github.com
github.com
github.com
github.com
juliadynamics.github.io
distance_matrix(series1, series2, max_freq, norm)
Generate distance matrix between two series.
Parameters:
series1 (float) : Source series 1.
series2 (float) : Source series 2.
max_freq (int) : Maximum frequency to inpect or the size of the generated matrix.
norm (string) : Norm of the distance metric, default=`euclidean`, options=`euclidean`, `manhattan`, `max`.
Returns: Matrix with distance values.
method normalize_distance(M)
Normalizes a matrix within its Min-Max range.
Namespace types: matrix
Parameters:
M (matrix) : Source matrix.
Returns: Normalized matrix.
method threshold(M, threshold)
Updates the matrix with the condition `M(i,j) > threshold ? 1 : 0`.
Namespace types: matrix
Parameters:
M (matrix) : Source matrix.
threshold (float)
Returns: Cross matrix.
rolling_window(a, b, sample_size)
An experimental alternative method to plot a recurrence_plot.
Parameters:
a (array) : Array with data.
b (array) : Array with data.
sample_size (int)
Returns: Recurrence_plot matrix.
RPPI Futures & Indices Strategy Tester [SS Premium]Hello everyone,
As promised, here is the strategy companion to the RPPI Futures & Indicies Indicator.
It contains all of the models of the RPPI but the functionality is all about back-testing the strategy. As such, you cannot use this to run probabilities, run autoregression assessments, or do any of the advanced RPPI features, this is solely to allow you to develop and implement a sustainable strategy in your trading using the RPI.
When you launch the indicator, in the settings menu, you will see toggles to customize the strategy you would like to apply:
You can customize your short and long entries and your short and long exits and then review the backtest results of these various combinations.
From there, you can open up tradingview's strategy tester to see the immediate success of the strategy. If you want to test how effective your strategy is further back, you can make use of Tradingview's "Deep Backtesting" option. This allows you to select a start date way in the past, and back-test over numerous months / years, to see if the strategy has been sustainable in the long term.
To read more about the RPPI, you can check out its own page which lists the details of the indicator, how it works and how to use it. As a synopsis, the RPPI is a compendium indicator that contains various models of multiple futures and stocks. This is to attempt to accurately forecast daily, weekly, monthly, 3 month and annual moves on various futures and indices.
This strategy companion will help you hone in on ideal entries and exits and allow you to tailor them to each ticker that you are interested in trading, on whichever timeframe you are interested in trading.
Some important notes when applying the back-testing results:
1. If you are back-testing daily levels, it is recommended to use the 1 to 5-minute chart max.
2. iF you are back-testing weekly levels, it is recommended to use at least 15 to 30 minutes, up to 60 minute candles.
3. Monthly levels, its best to use 1 hour and up.
4. Greater than monthly, its best to use 3 to 4 hours, to daily candles and up.
As always, feel free to leave your questions or suggestions below.
Thank you for reading and, as always, safe trades!
Test - Most correlated assetThis is a simple test to find the most and least correlated assets in a list.
TimeSeriesGrammianAngularFieldLibrary "TimeSeriesGrammianAngularField"
provides Grammian angular field and associated utility functions.
___
Reference:
*Time Series Classification: A review of Algorithms and Implementations*.
www.researchgate.net
method normalize(data, a, b)
Normalize the series to a optional range, usualy within `(-1, 1)` or `(0, 1)`.
Namespace types: array
Parameters:
data (array) : Sample data to normalize.
a (float) : Minimum target range value, `default=-1.0`.
b (float) : Minimum target range value, `default= 1.0`.
Returns: Normalized array within new range.
___
Reference:
*Time Series Classification: A review of Algorithms and Implementations*.
normalize_series(source, length, a, b)
Normalize the series to a optional range, usualy within `(-1, 1)` or `(0, 1)`.\
*Note that this may provide a different result than the array version due to rolling range*.
Parameters:
source (float) : Series to normalize.
length (int) : Number of bars to sample the range.
a (float) : Minimum target range value, `default=-1.0`.
b (float) : Minimum target range value, `default= 1.0`.
Returns: Normalized series within new range.
method polar(data)
Turns a normalized sample array into polar coordinates.
Namespace types: array
Parameters:
data (array) : Sampled data values.
Returns: Converted array into polar coordinates.
polar_series(source)
Turns a normalized series into polar coordinates.
Parameters:
source (float) : Source series.
Returns: Converted series into polar coordinates.
method gasf(data)
Gramian Angular Summation Field *`GASF`*.
Namespace types: array
Parameters:
data (array) : Sampled data values.
Returns: Matrix with *`GASF`* values.
method gasf_id(data)
Trig. identity of Gramian Angular Summation Field *`GASF`*.
Namespace types: array
Parameters:
data (array) : Sampled data values.
Returns: Matrix with *`GASF`* values.
Reference:
*Time Series Classification: A review of Algorithms and Implementations*.
method gadf(data)
Gramian Angular Difference Field *`GADF`*.
Namespace types: array
Parameters:
data (array) : Sampled data values.
Returns: Matrix with *`GADF`* values.
method gadf_id(data)
Trig. identity of Gramian Angular Difference Field *`GADF`*.
Namespace types: array
Parameters:
data (array) : Sampled data values.
Returns: Matrix with *`GADF`* values.
Reference:
*Time Series Classification: A review of Algorithms and Implementations*.
CCOMET_Scanner_LibraryLibrary "CCOMET_Scanner_Library"
- A Trader's Edge (ATE)_Library was created to assist in constructing CCOMET Scanners
Loc_tIDs_Col(_string, _firstLocation)
TickerIDs: You must form this single tickerID input string exactly as described in the scripts info panel (little gray 'i' that
is circled at the end of the settings in the settings/input panel that you can hover your cursor over this 'i' to read the
details of that particular input). IF the string is formed correctly then it will break up this single string parameter into
a total of 40 separate strings which will be all of the tickerIDs that the script is using in your CCOMET Scanner.
Locations: This function is used when there's a desire to print an assets ALERT LABELS. A set Location on the scale is assigned to each asset.
This is created so that if a lot of alerts are triggered, they will stay relatively visible and not overlap each other.
If you set your '_firstLocation' parameter as 1, since there are a max of 40 assets that can be scanned, the 1st asset's location
is assigned the value in the '_firstLocation' parameter, the 2nd asset's location is the (1st asset's location+1)...and so on.
Parameters:
_string (simple string) : (string)
A maximum of 40 Tickers (ALL joined as 1 string for the input parameter) that is formulated EXACTLY as described
within the tooltips of the TickerID inputs in my CCOMET Scanner scripts:
assets = input.text_area(tIDset1, title="TickerID (MUST READ TOOLTIP)", tooltip="Accepts 40 TICKERID's for each
copy of the script on the chart. TEXT FORMATTING RULES FOR TICKERID'S:
(1) To exclude the EXCHANGE NAME in the Labels, de-select the next input option.
(2) MUST have a space (' ') AFTER each TickerID.
(3) Capitalization in the Labels will match cap of these TickerID's.
(4) If your asset has a BaseCurrency & QuoteCurrency (ie. ADAUSDT ) BUT you ONLY want Labels
to show BaseCurrency(ie.'ADA'), include a FORWARD SLASH ('/') between the Base & Quote (ie.'ADA/USDT')", display=display.none)
_firstLocation (simple int) : (simple int)
Optional (starts at 1 if no parameter added).
Location that you want the first asset to print its label if is triggered to do so.
ie. loc2=loc1+1, loc3=loc2+1, etc.
Returns: Returns 40 output variables in the tuple (ie. between the ' ') with the TickerIDs, 40 variables for the locations for alert labels, and 40 Colors for labels/plots
TickeridForLabelsAndSecurity(_ticker, _includeExchange)
This function accepts the TickerID Name as its parameter and produces a single string that will be used in all of your labels.
Parameters:
_ticker (simple string) : (string)
For this parameter, input the varible named '_coin' from your 'f_main()' function for this parameter. It is the raw
Ticker ID name that will be processed.
_includeExchange (simple bool) : (bool)
Optional (if parameter not included in function it defaults to false ).
Used to determine if the Exchange name will be included in all labels/triggers/alerts.
Returns: ( )
Returns 2 output variables:
1st ('_securityTickerid') is to be used in the 'request.security()' function as this string will contain everything
TV needs to pull the correct assets data.
2nd ('lblTicker') is to be used in all of the labels in your CCOMET Scanner as it will only contain what you want your labels
to show as determined by how the tickerID is formulated in the CCOMET Scanner's input.
InvalID_LblSz(_barCnt, _close, _securityTickerid, _invalidArray, _tablePosition, _stackVertical, _lblSzRfrnce)
INVALID TICKERIDs: This is to add a table in the middle right of your chart that prints all the TickerID's that were either not formulated
correctly in the '_source' input or that is not a valid symbol and should be changed.
LABEL SIZES: This function sizes your Alert Trigger Labels according to the amount of Printed Bars the chart has printed within
a set time period, while also keeping in mind the smallest relative reference size you input in the 'lblSzRfrnceInput'
parameter of this function. A HIGHER % of Printed Bars(aka...more trades occurring for that asset on the exchange),
the LARGER the Name Label will print, potentially showing you the better opportunities on the exchange to avoid
exchange manipulation liquidations.
*** SHOULD NOT be used as size of labels that are your asset Name Labels next to each asset's Line Plot...
if your CCOMET Scanner includes these as you want these to be the same size for every asset so the larger ones dont cover the
smaller ones if the plots are all close to each other ***
Parameters:
_barCnt (float) : (float)
Get the 1st variable('barCnt') from the Security function's tuple and input it as this functions 1st input
parameter which will directly affect the size of the 2nd output variable ('alertTrigLabel') that is also outputted by this function.
_close (float) : (float)
Put your 'close' variable named '_close' from the security function here.
_securityTickerid (string) : (string)
Throughout the entire charts updates, if a '_close' value is never registered then the logic counts the asset as INVALID.
This will be the 1st TickerID variable (named _securityTickerid) outputted from the tuple of the TickeridForLabels()
function above this one.
_invalidArray (array) : (array string)
Input the array from the original script that houses all of the invalidArray strings.
_tablePosition (simple string) : (string)
Optional (if parameter not included, it defaults to position.middle_right). Location on the chart you want the table printed.
Possible strings include: position.top_center, position.top_left, position.top_right, position.middle_center,
position.middle_left, position.middle_right, position.bottom_center, position.bottom_left, position.bottom_right.
_stackVertical (simple bool) : (bool)
Optional (if parameter not included, it defaults to true). All of the assets that are counted as INVALID will be
created in a list. If you want this list to be prited as a column then input 'true' here, otherwise they will all be in a row.
_lblSzRfrnce (string) : (string)
Optional (if parameter not included, it defaults to size.small). This will be the size of the variable outputted
by this function named 'assetNameLabel' BUT also affects the size of the output variable 'alertTrigLabel' as it uses this parameter's size
as the smallest size for 'alertTrigLabel' then uses the '_barCnt' parameter to determine the next sizes up depending on the "_barCnt" value.
Returns: ( )
Returns 2 variables:
1st output variable ('AssetNameLabel') is assigned to the size of the 'lblSzRfrnceInput' parameter.
2nd output variable('alertTrigLabel') can be of variying sizes depending on the 'barCnt' parameter...BUT the smallest
size possible for the 2nd output variable ('alertTrigLabel') will be the size set in the 'lblSzRfrnceInput' parameter.
PrintedBarCount(_time, _barCntLength, _barCntPercentMin)
The Printed BarCount Filter looks back a User Defined amount of minutes and calculates the % of bars that have printed
out of the TOTAL amount of bars that COULD HAVE been printed within the same amount of time.
Parameters:
_time (int) : (int)
The time associated with the chart of the particular asset that is being screened at that point.
_barCntLength (int) : (int)
The amount of time (IN MINUTES) that you want the logic to look back at to calculate the % of bars that have actually
printed in the span of time you input into this parameter.
_barCntPercentMin (int) : (int)
The minimum % of Printed Bars of the asset being screened has to be GREATER than the value set in this parameter
for the output variable 'bc_gtg' to be true.
Returns: ( )
Returns 2 outputs:
1st is the % of Printed Bars that have printed within the within the span of time you input in the '_barCntLength' parameter.
2nd is true/false according to if the Printed BarCount % is above the threshold that you input into the '_barCntPercentMin' parameter.
Volume Footprint Voids [BigBeluga]Volume Footprint Voids is a unique tool that uses lower timeframe calculation to plot different styles of single candle POC.
This indicator is very powerful for scalping and finding very precise entry and exits, spotting potential trapped traders, and more.
Unlike many other volume profiles, this aims to plot single candle profiles as well as their own footprints.
🔶 FEATURES
The script includes the following settings:
Windows: Plotting style and calculations
Coloring modes
Display modes
lower-timeframe calculations
🔶 CALCULATION
In the image above we can see how the script calculates each level position that will serve as a calculation process to see how much volume/closes there are within the levels.
In the image above, we can have a more clear example of how we count each candle close.
We use the prior screenshot as an example, after setting each level we will use the lower-timeframe input to measure the amount of closes within the ranges.
Depending on the lot size, the box will be larger or smaller, usually the POC will always have the highest box size.
NOTE: Size is the starting point, always from the low of the candle.
To find more voids, select a closer LTF to the current one you're using.
To find fewer voids, select a timeframe away from your current one.
Due to Pine Script limitations, we are only able to plot a certain amount of footprints, and we can't plot the whole history chart.
POC will be the largest block displayed, indicating the time point of control
Gray areas are closes above the average
Black are Void or imbalance that price will fill in the future, like FVG
The image above shows an incorrect size input that will lead to bad calculations, while on the other side, a correct size input that will lead to a clear vision and better calculation.
🔶 WINDOWS
The "▲▼" Mode will display delta buyers and delta sellers coloring with voids as black.
It also offers a gradient mode for a beautier visualization
The "Total Volume" mode will display the net volume within the lot size (closes within the levels).
This is useful to spot possible highest net volume within the same highest lot size.
The "POC + Gaps" will show both POC and Gaps as the highest block while all the rest will be considered as the smaller block.
This is useful to see where the highest lot were and if there are higher or lower imbalances within the candle
The last option "Gaps" will simply display the gaps as the highest block, while the POC as the lowest block.
This is useful to have a better view of the gaps areas
🔶 EXAMPLE
This is one of the most basic examples of how this script can be used. POC at the bottom creating a strong support area as price holds and creates higher voids gap that price fills while rising.
🔶 SETTINGS
Users have full control over the script, from colors to choosing the lower-timeframe inputs to disabling the lot size.
Drawdown % (with SMA)This script, titled "Drawdown % (with SMA)" and designed for Pine Script version 5
offers a sophisticated tool for traders to monitor drawdown percentages, a crucial metric in assessing investment risks. The script calculates the drawdown as the percentage decrease from the all-time high value of the selected financial instrument.
Portfolio Management [TrendX_]Portfolio Management is a powerful tool that helps you create and manage your own portfolio of stocks, based on your risk and return preferences.
*** Note: You should select the appropriate index for each stock as the benchmark to compare your portfolio’s performance.
*** Note: You should apply the indicator to the same chart as the benchmark, so that it can capture the historical trends of all the 10 stocks in your portfolio.
USAGE
Analyze your portfolio’s return factor, which shows the compound annual growth rate (CAGR) of each stock and the portfolio as a whole, as well as the weight of each stock in the portfolio.
The Weighting approach contains 2 options, Equal and Growth-based method:
Customize your portfolio by selecting up to 10 stocks from a wide range of markets and sectors:
Compare your portfolio’s performance with a benchmark of your choice, which is the S&P500 by default setting.
Evaluate your portfolio’s risk factor, which includes the capital asset pricing model (CAPM), the portfolio beta, and the Sharpe ratio of both the portfolio and the benchmark:
- CAPM is a model that calculates the expected return of the portfolio based on its risk and the risk-free rate of return.
- Portfolio beta is a measure of how sensitive the portfolio is to the movements of the benchmark. A beta of 1 means the portfolio moves in sync with the benchmark, a beta of less than 1 means the portfolio is less volatile than the benchmark, and a beta of more than 1 means the portfolio is more volatile than the benchmark.
- Sharpe ratio measures how much excess return the portfolio generates per unit of risk. It is calculated by subtracting the risk-free rate of return from the portfolio’s return, and dividing by the portfolio’s standard deviation. A higher Sharpe ratio means the portfolio has a better risk-adjusted return. A Sharpe ratio of more than 1 is considered good, a Sharpe ratio of more than 2 is considered very good, and a Sharpe ratio of more than 3 is considered excellent .
Adjust your portfolio’s rebalancing strategy, which determines when and how to change the weight of each stock in the portfolio to optimize your return and risk objectives. The tool also suggests a default hedging-stock asset, which is the US dollar interpreted through the dollar index (DXY):
- The dollar index is a measure of the value of the US dollar relative to a basket of other major currencies. It is often used as a proxy for the global economic sentiment and the demand for safe-haven assets. A rising dollar index means the US dollar is strengthening, which may indicate a bearish outlook for the stock market. A falling dollar index means the US dollar is weakening, which may indicate a bullish outlook for the stock market.
- The rebalancing strategy suggest increasing the weight of the hedging-stock asset when the dollar index is under positive supertrend condition, and decreasing the weight of the hedging-stock asset when the dollar index is in the downward supertrend. This way, you can hedge against the adverse effects of the stock market fluctuations on your portfolio, simply you can just cash out at the suggested hedging weight.
CONCLUSION
Investors can gain a deeper insight into their portfolio’s performance, risk, and potential, and make informed decisions to achieve their financial goals with confidence and ease.
DISCLAIMER
The results achieved in the past are not all reliable sources of what will happen in the future. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur.
Therefore, you should always exercise caution and judgment when making decisions based on past performance.
Qullamaggie ADR and Volatility and Price Change IndicatorElevate your trading strategy with Qullamaggie ADR, a dynamic indicator inspired by the Kristjan Qullamaggie trading approach. Gain a deeper understanding of market dynamics, daily price movements, and potential turning points.
Key Features:
Qullamaggie ADR: Assess market volatility through the QullaADR, offering customizable time intervals (5, 10, 15, 20 days) to adapt to various trading styles.
Today's Change: Monitor price changes relative to the low of the current trading day, providing valuable intraday insights.
PrevDay price differentials from the previous day's low, aiding in the identification of potential trend reversals.
Track the percentage change from the opening price, offering a snapshot of intraday market sentiment.
Percent from 10-day SMA: Visualize the percentage difference between the closing price and a 10-day Simple Moving Average (SMA), a key trend-following indicator.
Usage:
Utilize QullaADR to set realistic profit targets and stop-loss levels based on current market conditions.
Identify potential trend shifts by observing changes from the previous day's low with Today's QullaChange.
Incorporate QullaPercent from 10-day SMA for trend confirmation and well-informed trading decisions.
Strategy Inspiration:
QullaADR draws inspiration from the Kristjan Qullamaggie trading strategy, aiming to complement your trading toolkit and enhance decision-making.
Disclaimer:
Trading involves risk, and past performance is not indicative of future results. Use this indicator as a supplementary tool within a comprehensive trading strategy.
Version: 1.0
Ichimoku Strategy - Easiest Backtest [A.R.]▓ INTRODUCTION
This indicator allows a new "sandbox" approach to the Ichimoku system allowing to combine several entry, confirmation and exit conditions, to add basic risk management, to be able to backtest the performance of the strategy using a table directly on chart, and automate entry and exit signals using alerts.
▓ DEFINITION
The Ichimoku strategy is a trading system based on technical analysis, using a set of graphical indicators to evaluate the trend, strength and support/resistance levels of a financial asset. It integrates components such as the conversion line (Tenkan), the baseline (Kijun), the cloud delimited by the Senkou Span A and the Senkou Span B (SSA - SSB - Kumo) and the lagging span (Chikou) to provide different trading signals.
▓ ADDED VALUE
Several indicators and strategies concerning Ichimoku are already available on Tradingview, we are publishing this indicator to make this strategy even more accessible, what makes it original:
▪️ Unique Settings Windows, easy-to-read. The settings categories are clearly separated. Some parameters are aligned to avoid having an endless list of parameters to modify. This makes the settings window easy to understand and pleasant to use.
▪️ Sandbox type settings, you can choose 1 or 2 Entry conditions, choose to add 1 Confirmation, choose to add between 1 and 3 Exit Conditions. Dozens of possible configurations.
▪️ Possibility of adding basic Risk Management (TP/SL)
▪️ Backtest table directly on chart that allow to get quickly the results (script execution <1 sec) which makes it practical, allowing dozens of different configurations to be tested in a short period of time
▪️ Monitoring historical and current trades on chart thanks to Boxes and Labels
▓ HOW TO USE
You can try the indicator with default settings but you can also modify backtesting settings and trade Entry conditions, Entry Confirmation, and Exit conditions, also you can decide to add a Stop Loss and/or a Take Profit. Then you can find the stats of the backtesting in a table directly in the top right corner of the chart. Finally you can automate the strategy using Alert conditions. You can find all the settings below:
Initial backtesting settings:
🔹Set up Side: Choose Long|Short, Long or Short
🔹Set up Investment: Choose an amount in $, it simulates the equity / funds on the trading account.
🔹Set up Position Size: Choose an amount in $, it simulates the amount of the position size of each trade. If you want to simulate leverage trading, you can put a Position Size superior to Investment. For exemple Investment = 10000 and Position Size = 20000 simulates a x2 leverage.
🔹Set up your Fee rate %: Each trade entry and trade exit, a % of position size will be deducted from the PnL stats. For example if you choose 0.04% with 10000 Position Size, 4$ will be deducted each trade entry and each trade exit = 8$ fees each trade.
🔹Set up the Start and End date: It allows to backtest the strategy over a period of time, for Example from 01-01-2021 to 01-12-2022. By default the end date is year 2050, the backtest will start to take into account data from Start Date to the current time.
Backtest the main Ichimoku sub-strategies choosing entry conditions:
🔸Cloud Breakouts trading: Choose this Entry condition to start a trade when Price crosses the Cloud Upside (Long) or Downside (Short)
🔸Tenkan x Kijun cross trading: Choose this Entry condition to start a trade when Tenkan (Red line) crosses Kijun (Blue line) Upside (Long) or Downside (Short)
* There is no repaint, a signal is validated after the condition is confirmed at the end of the previous candle. If a signal appears on the chart, it won't ever disappear.
Entry Confirmations:
✔️ Chikou Above or Below price: if you check this setting, Long entry signals will be confirmed only when the Chikou (White Line) is Above the current price and Short entry signals will be confirmed only when the Chikou (White Line) is below the current price. In the Ichimoku system the Chikou is often used to confirm all types of signals.
Exit Conditions:
❌ Cloud Reintegrations: When a trade is open (Long or Short), if the price goes back into the cloud the trade is closed
❌ Reverse Cloud Breakouts: When a Long trade is open, if the price breaks out of the cloud from below the trade is closed. When a Short trade is open, if the price breaks out of the cloud from above the trade is closed.
❌ Reverse Tenkan-Kijun Cross: When a Long trade is open, if the Tenkan crosses Downside the Kijun the trade is closed. When a Short trade is open, if the Tenkan crosses Upside the Kijun the trade is closed.
Basic Risk Management:
⛔️ SL: Choose to set up a Stop Loss
✅ 1 single TP: Choose to set up a Take Profit
Signals:
🔔 Entry/Exit Alerts available: 4 types of alert conditions are available ENTRY LONG, ENTRY SHORT, EXIT LONG, EXIT SHORT. The entry conditions trigger at the beginning of the candle, choose alert frequence = once per bar.
👉 Tips: Easier to find profitable configurations in High Timeframe above H4.
▓ BACKTESTING SYSTEM
The Backtesting system integrated into the script tracks each trade. It allows you to test the strategy over a fixed period between a start date and an end date. It also allows to quickly and directly display on the chart the most important data to determine if a configuration is profitable such as the % PnL, the Max Drawdown, the amount of fees, the risk-reward ratio. It has been designed to be easy and quick to use even for a beginner.
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The information published here on TradingView is not prohibited, doesn't constitute investment advice, and isn't created solely for qualified investors.
Important to note: The source code of this indicator is not accessible because it benefits from the code of our backtesting system present in other non-public indicators that we protect. Our indicators with the same backtesting system are published in separate publications because putting them together in a single script would considerably slow down the execution of the script.
Sessions [TradingFinder] New York, London, Tokyo & Sydney ForexTiming is one of the influential factors in a trader's position. This indicator categorizes transactions into three sessions (Asia, Europe, and America). Five significant trading cities (New York, London, Frankfurt, Tokyo, and Sydney) are selectable.
I recommend using the tool on a 5-minute time frame, but it is usable on all time frames.
Settings:
• Trading sessions: Display or hide each trading session as needed.
• Color: Change the color of each box.
• Session time intervals: The default is based on the main working hours for each time interval and can be adjusted.
• Information table: Delete or display additional information table.
Information Table:
• Trading sessions
• Opening and closing times of each trading session
How to Use:
Initiating trading sessions involves entering with increased liquidity, and the market usually experiences significant movements. Many trading strategies are based on "time" and "session openings." This tool empowers traders to focus intensely on each time interval.
These trading sessions are crucial for all Forex, stock, and index traders:
The total price ceiling and floor in the Asia session (Tokyo and Sydney) are crucial for traders in the European session.
The European session starts with Frankfurt, and an hour later, London begins, collectively forming the European session.
The dashboard provides additional information, displaying hours based on UTC.
Customization options are considered in all sections so that everyone can apply their own settings.
Important: Default times are the most accurate for each region, and in most indicators, this time is not correctly selected. Therefore, the level of influence and time intervals are specified at the beginning of each session. If you are using another indicator, match its default time to the announced time and share the results with me in the comments.
Kendall's Tau Correlation Regimes [NariCapitalTrading]The "Kendall's Tau Correlation Regimes" indicator is designed to analyze price data and determine market regimes based on Kendall's Tau correlation coefficient. It provides insight into the strength and direction of the correlation between two data series: close price and a selected moving average.
User Inputs:
Period: Defines the lookback period for calculating Kendall's Tau correlation. It can be adjusted using the input slider, with a minimum value of 1.
Threshold: Sets the threshold for identifying bullish and bearish market regimes. The user can adjust this value within the range of 0.1 to 1.0 with step increments of 0.1.
MA Type: Allows users to select the type of moving average to be used in the correlation calculation. Options include Simple Moving Average (SMA), Exponential Moving Average (EMA), and Hull Moving Average (HMA).
Kendall's Tau Correlation Calculation:
Calculates Kendall's Tau correlation coefficient between the closing price and the selected moving average.
Kendall's Tau measures the strength and direction of the ordinal association between two data series. It assesses whether the data pairs are in the same order or not.
The calculation involves counting concordant and discordant pairs of data points and then computing the coefficient.
Market Regime Identification:
Based on the threshold defined by the user, the indicator identifies two market regimes: bullish and bearish.
A regime is considered bullish when the Kendall's Tau correlation coefficient is greater than the threshold.
A regime is considered bearish when the Kendall's Tau correlation coefficient is less than the negative of the threshold.
Plotting:
The indicator plots the calculated Kendall's Tau correlation coefficient as a blue line on a separate indicator pane.
It also highlights bullish regimes with a green background and bearish regimes with a red background.
Conclusion:
The "Kendall's Tau Correlation Regimes" indicator provides traders with a visual aid for assessing market regimes based on the strength of correlation between price and a selected moving average.
Disclaimer: This indicator is for educational and informational purposes only.
Least Median of Squares Regression | ymxbThe Least Median of Squares (LMedS) is a robust statistical method predominantly used in the context of regression analysis. This technique is designed to fit a model to a dataset in a way that is resistant to outliers. Developed as an alternative to more traditional methods like Ordinary Least Squares (OLS) regression, LMedS is distinguished by its focus on minimizing the median of the squares of the residuals rather than their mean. Residuals are the differences between observed and predicted values.
The key advantage of LMedS is its robustness against outliers. In contrast to methods that minimize the mean squared residuals, the median is less influenced by extreme values, making LMedS more reliable in datasets where outliers are present. This is particularly useful in linear regression, where it identifies the line that minimizes the median of the squared residuals, ensuring that the line is not overly influenced by anomalies.
STATISTICAL PROPERTIES
A critical feature of the LMedS method is its robustness, particularly its resilience to outliers. The method boasts a high breakdown point, which is a measure of an estimator's capacity to handle outliers. In the context of LMedS, this breakdown point is approximately 50%, indicating that it can tolerate corruption of up to half of the input data points without a significant degradation in accuracy. This robustness makes LMedS particularly valuable in real-world data analysis scenarios, where outliers are common and can severely skew the results of less robust methods.
Rousseeuw, Peter J.. “Least Median of Squares Regression.” Journal of the American Statistical Association 79 (1984): 871-880.
The LMedS estimator is also characterized by its equivariance under linear transformations of the response variable. This means that whether you transform the data first and then apply LMedS, or apply LMedS first and then transform the data, the end result remains consistent. However, it's important to note that LMedS is not equivariant under affine transformations of both the predictor and response variables.
ALGORITHM
The algorithm randomly selects pairs of points, calculates the slope (m) and intercept (b) of the line, and then evaluates the median squared deviation (mr2) from this line. The line minimizing this median squared deviation is considered the best fit.
DISCLAIMER
In the LMedS approach, a subset of the data is randomly selected to compute potential models (e.g., lines in linear regression). The method then evaluates these models based on the median of the squared residuals. Since the selection of data points is random, different runs may select different subsets, leading to variability in the computed models.
Autocorrelation Candles [SS]Hey everyone, this is the Autocorrelation Candles indicator!
I have formulated it in a way that is similar to the TD 9 candle counting indicators, only instead of TD, its using a lagged autocorrelation of previous candle over a 14 period look back.
It operates similar to trend correlations (for example, my Trend Correlation Oscillator Indicator), however instead of correlating to time, it correlates to itself (autoregression). The theory being, as the autoregression correlation increases and the market becomes too "trendy", we are due for a reversal.
The indicator will display the current lagged correlation of each candle below it. When we approach a period of previous reversal, it will change the colour to orange. When we reach a very high autocorrelation (0.94 or greater), it will turn red and signal a potential reversal to the upside or downside:
Uses:
I will reference this on the larger timeframes (Daily, weekly and 4 hour) about a couple times a week or after a major trend day to see where we are.
You can use this on the smaller timeframes as well, it will work just fine.
Customizations:
I have been listening and learning my lesson, I have made the ability to customize the base text colour to black or white depending on your theme use! SO if you have white theme, you can change to black and vice versa.
As well, if you don't want labels on every candle, in the settings menu there is an option to limit the labels to a desired amount. You select the max amount and it will adjust.
You can also adjust the size of the labels between tiny, medium, and large.
Conclusion
And that's the indicator! Despite being fairly simple in concept, I have been working away on it for a bit with some logistic issues that I finally got sorted.
Hopefully, you enjoy,
Leave your questions below!
Safe trades everyone!
Advanced Volume Analytics and Distribution IndicatorThe Advanced Volume Analytics and Distribution Indicator is a sophisticated tool designed for financial analysts and traders who seek in-depth insights into market volume dynamics. This Pine Script-based indicator is a comprehensive solution, offering a rich set of features that analyze volume data using various statistical methods and theories. It's tailored for those who require a deeper understanding of market movements and volume distribution.
Key Features:
Volume Distribution Analysis: Utilizes standard deviation and mean calculations to analyze the distribution of trading volume. Employs z-scores to measure the standard deviations of volume from its mean, offering insights into volume anomalies.
Bell Curve Modeling: Constructs a bell curve (normal distribution) based on volume data, enabling users to visualize and assess the distribution of volume in a standard statistical format.
Provides a z-score based bell curve, offering a normalized view of volume deviations.
Exponential Smoothing: Applies exponential smoothing to volume data, giving more weight to recent observations. This feature is crucial for analyzing trending behaviors in volume data.
Stress Metric Calculation: Introduces a unique 'stress' metric, calculated using a custom formula. This metric is designed to evaluate the volatility or variability in the volume data over a specified period.
Central Limit Theorem (CLT) Mean Estimation: Implements CLT for estimating the mean of volume data. The CLT states that the distribution of sample means approximates a normal distribution as the sample size becomes larger.
Variance Point Estimation: Calculates the variance of volume data, providing insights into its variability and consistency over time.
Chi-Squared Test (Commented): Although not active in the initial release, the script includes a framework for a Chi-Squared Test to compare observed and expected volume frequencies, offering potential for future statistical comparisons.
Percentile Calculations and Convolution: Performs percentile calculations on volume data and employs convolution to these percentiles, enabling a more nuanced analysis of volume distribution.
Customizability: Users can input various parameters like anchor period, degrees of freedom, and smoothing preferences, making the tool adaptable to different analysis needs.
Visualization and Plotting: Features multiple plots for easy visualization of volume metrics, including stress, bell curves, point estimators, and smoothed data.
Theoretical Foundations:
This indicator is grounded in established statistical theories and methods, including the Central Limit Theorem, Chi-Squared Test (for future implementations), and convolution techniques. These foundations ensure that the indicator not only provides practical insights but also maintains a high standard of statistical rigor.
Intended Users:
This indicator is ideal for technical analysts, traders, and financial professionals who require a deep and statistically sound understanding of market volume behavior.
Release Notes:
This tool is designed a theoretical test of established statistical models and requires familiarity with Pine Script for customization. Future updates may include activation and expansion of the Chi-Squared Test functionality and additional statistical modules based on user feedback. It should be noted that it is advisable to use a logarithmic-inverted scale; when combined, these scales can provide a unique perspective that neither could offer alone. This combination might be particularly useful in highlighting exponential growth or decay trends, or in cases where the most significant data points are in the lower range of the dataset.
Notes of Stress Calculations:
The "stress metric" in the script is a custom-designed feature intended to measure the level of variability or volatility in the volume data over a given time period. This metric is calculated using a novel approach with concepts similar to those used in the field of engineering , particularly in stress analysis and finite element analysis (FEA).
Segmentation of Time Frame:
The script divides the given time frame (timeFrame) into smaller segments based on a specified number of units (units). This segmentation essentially breaks down the entire period into smaller, more manageable intervals for analysis. For each segment, the script calculates a 'stress' value. This involves iterating through each segment and performing calculations based on the source data (src), the default src is the volume data.
Calculation per Segment:
For each segment, the script identifies two points: the starting point (x1) and the ending point (x2). It then retrieves the corresponding values of the source data at these points (y1 and y2).
It calculates the difference in the x-axis (delta_x, the length of the segment) and the difference in the y-axis (delta_y, the change in volume over that segment).
Stress Calculation:
The script then calculates the 'stress' for each segment as the ratio of delta_y to delta_x. This ratio gives a measure of how much the volume has changed per unit of time within each segment. The stress values for each segment are then summed up to provide a cumulative measure of stress over the entire time frame.
The stress metric is essentially a measure of the volatility or variability in volume data. High stress values indicate larger changes in volume over shorter periods, suggesting more volatile market conditions. For traders and analysts, understanding the level of volatility is crucial. It can inform decision-making processes, risk management strategies, and provide insights into market sentiment. By comparing stress levels across different time frames or different securities, analysts can gain insights into relative market dynamics.
KD Momentum MatrixI believe many traders think that fluctuation is very troublesome. The money earned in the trends is easily lost in the fluctuation. Because it is hard to find the high and low points of range.
Indicator: KD Momentum Matrix is the best choice for analyzing fluctuation, with potential volatility reminder.
KD Momentum Matrix is not only a momentum indicator, but also a short-term indicator. It divides the movement of the candle into long and short term trends, as well as bullish and bearish momentum. It identifies the points where the bullish and bearish momentum increases and weakens, and effectively capture profits.
💠Usage：
Potential volatility reminder:
"strong" represents an increase in potential volatility, indicating that the fluctuation of the candles may increase in the future.
"weak" represents a decrease in potential volatility, indicating that the fluctuation of the candles may decrease in the future.
Momentum column:
·The short-term momentum column, the "green and red columns", represents the short-term bullish and bearish momentum, and is the main reference feature of this indicator.
·Long term momentum columns, known as "dark green and purple columns", represent long-term bullish and bearish momentum and serve as auxiliary reference feature.
Note: Long and short term momentum columns usually have the same direction, and in rare cases, they may deviate. Sometimes there may be overlapping long and short term columns. The reference bullish and bearish directions are consistent regardless of the long and short term.
🎈Tip I：
When there is a potential volatility reminder: "weak" or "strong", it is important to note that there may be something different on amplitude of fluctuation in the future. If you have a position, you need to think new about the direction of your position.
🎈Tip II：
Taking the main reference feature - the short-term momentum column as an example, when the momentum column changes from red to green, it indicates short-term bullishness, and there may be a small upward trend. If the price happens to be near the bottom of the visible range at this time, consider executing a round of opening long positions or closing short positions.
When holding a long position, the bearish signal indicated by the momentum bar is used for departure, i.e. the momentum bar changes from green to red.
🎈Advanced tip I：
Deviation. The long and short term momentum columns are mostly consistent, but occasionally there may be deviations, indicating intense competition between bulls and bears. In the short term, it is recommended not to engage in trading because of its high uncertainty.
🎈Advanced tip II：
Volatility indicators can also be used in trends, but it is important to remember the idea of following the trend. For example, when there is a callback during an upward trend, we choose to buy or add a long position when the momentum bar becomes a long signal.
*The signals in the indicators are for reference only and not intended as investment advice. Past performance of a strategy is not indicative of future earnings results.
Update -
Optimize the alarm function. If you need to monitor the "strong " or "weak" signal, when creating an alarm, set the condition bar to:
KD Momentum Matrix --> "strong " or "weak" --> Crossing Up --> value -> 1
Universal RPPI Indices & Futures [SS Premium]Hello everyone,
For the much-anticipated indicator release, the universal RPPI for Futures and Indices!
If you follow me, chances are you know this indicator by now, since its the basis of all of my analyses and target prices, but if not, let me introduce you!
What is it?
The RPPI for Indices & Futures is essentially a compendium indicator. It contains hundreds of, just over 100 different math models of various futures and indices.
These models are designed to forecast the current targets on multiple timeframes including:
1. The daily
2. The weekly
3. The monthly
4. The Three Month (for SPY and QQQ ONLY)
5. The 6 Month (for DJI, SPX and USOIL/CLI1! ONLY)
6. The annual (for DJI, SPX and USOIL/CLI1! ONLY)
7. The 3 hour
So I will go over the details of the models within the indicators compendium and how they are produced. If you are not interested, just skip to the next section!
What is a model and how is it produced?
Models are math equations and frameworks that attempt to predict future behavior. They are developed in many ways and through many methods. In this particular indicator, each index and future is unique and has been created in various ways, such as using principles of data smoothing, data interpolation, data substitution and data omission.
All this means is, I have manually adjusted model parameters to correct for rare, outlier events. The outcome is having a more accurate model that is better prepared to predict what you want it to predict.
Now let's get into the indicator use.
The first thing we need to talk about is selecting a model type. Different model types are available on a handful of stocks in the indicator, such as SPY, QQQ, DJI and DIA, and so it is important to explain the difference.
Corrected vs Uncorrected Models (i.e. Low Precision vs High Precision Models)
In the settings menu, you will see the second option that reads "Precision". This is where you have the ability to select the model type.
"High Precision" is a corrected model. It is a model that I have used data manipulation for (like the examples above) to enhance its accuracy.
"Low Precision" is a UNCORRECTED model. These models have undergone no data manipulation and are just raw projections.
Which do you use?
There are only a handful of tickers that have both models, like SPY, GLD1! and DJI (among others). Some tickers perform better with low precision models, others perform better with high precision models.
To know what model works best with which stock, the indicator will tell you. At the bottom of the settings table, simply select "Show Model Data":
Selecting this, you will get a table that looks like this:
It will tell you the available model types and which one works best. For IWM, the high-precision corrected model is best. This is true for QQQ and NQ1! as well. However, for SPY and ES1!, the uncorrected model is actually better:
Sometimes, different models perform better at various levels of precision, for example, high on the monthly but low on the daily.
This is why I have omitted this option for the majority of stocks. I don't want this to be confusing to use. For 90% of the included tickers, I have selected the model of best fit. However, for a few of the very popular and volatile tickers (ES, NQ specifically), I have included the ability to use both.
Rule of Thumb:
The rule of thumb with selecting high vs low, is essentially this:
a) If the market is hugely volatility with major swings intraday that exceed its normal behaviour, switch to the low precesion model. This will not be skewed by the massive swings.
b) If the market is stable, trendy or range bound, but not trending beyond its normal, general behaviour, keep it at high precision.
With that, you will be good to go!
Using the indicator:
The indicator is intended as a standalone indicator. Of course, you can combine other indicators that you like to help you out, but there is a strategy version of this that will be released within the coming days/weeks, as this is intended to be a full strategy in and of itself.
As with the universal forecaster, you are given threshold levels that are labelled "Bullish Condition" and "Bearish Condition", a break and hold of the "Bullish Condition" and it is a long to the high targets. Inverse for the bearish condition.
In addition to these conditionals, the indicator also provides you with a high probability retracement level. These are available on the weekly, monthly and higher timeframes. A special moving retracement level is available for SPY only, however it moves based on the PA to give you a sort of POC.
Testing Model Performance:
It is possible to see model performance. At the bottom of the settings menu, select the option to "Show Demographic Data". You need to be sure you are on the chart of the selected timeframe.
This is ES1! on the daily timeframe. It shows you the demographics, i.e. the extent targets are hit, the extent that the high prob retracement targets are missed, the extent that ES closes in and out of its daily range.
This is very valuable information. This table is essentially saying there is only a 10% chance that ES will close above its range and a 9% chance ES closes below its range. This means, that the most ideal setups are a move outside of its range!!
You can view it on all timeframes. If your chart isn't aligned with the lookback, you will get a warning sign:
Misc Functions:
Show price accumulation:
There is an option to toggle on price accumulation. It will show you the amount of accumulation in each of the ranges:
This will show where the accumulation of price rests in relation to the targets.
Autoregression Assessment:
You can have the indicator plot an autoregressive trendline of the expected stock trajectory. You can select the forecast length and it will plot the direction it suspects the stock will go:
Show Standard Deviation:
In the menu, you can toggle on the show standard deviation function. This will plot the standard deviation that each price rests at. The default timeframe for standard deviation is the daily. If you are looking at the weekly, please select the weekly timeframe.
This is helpful because you can see which targets are likely based on where the standard deviation rests. In the above example, a move to the low range would be a move to -2 standard deviations and beyond. This is not something that a ticker would normally do in general circumstances.
FAQ Table:
There is also an option to display an FAQ table. This will show you model revisions and pending revision dates. This will allow you to see when each model was last updated and when new updates will be pushed:
Which models does this contain?
The indicator contains models for the following stocks:
SPY
QQQ
DIA
DJI
ES1!
SPX
NQ1!
NDX
SOXX
IWM
RTY
GCL1! (Gold)
CL1! / USOIL (Oil)
XLE
XLF
YM1!
And some more are in the works (like JETS).
NOTE: Feel free to leave a comment of future ones you would like to see!
The indicator will automatically select the model for whichever ticker you are on.
Some models are cross-compatible, such as CL1! and USOIL, but the indicator is programmed to recognize those that are cross-compatible and auto-select those models.
From there, you just need to select the timeframe you wish to view!
And that is the indicator! I know very wordy explanation but wanted to cover all basis on the indicator so you can be well prepared!
As always, leave your questions, and comments below, and safe trades!
Autoreg Trend Clouds [SS Premium]This is the autoregressive (or Autoreg) trend cloud indicator included in the Pro and Elite trading level.
About:
The autoregressive trend clouds operate on 2 major statistical concepts, as the name implies, the use of autoregression being the primary facet, as well as the use of an ANOVA statistical analysis of mean variance. I will elaborate on each of these below, but first will discuss the gist of what the indicator does.
The indicator plots the expected range based on an autogenerated autoregressed model of the stock. The indicator will train itself for lookback time and for modelling and will fit a model to whichever ticker, index, FOREX or crypto, etc. you are on.
These clouds represent the anticipated range for an instrument to fall in based on its current trend and its autoregressed relationship.
Below is an example with BTC on the 1 hour:
And QQQ on the 1 hour:
Autoregression:
The autoregression model uses an automatic trend identifier to identified the appropriate lookback length. It then generates two types of models, a lag 1 model (1 lag autoregression back) and a 3 lag model (using the last 3 lags, or candles, to create a model). It then compares which model is stronger and selects the best fit. It identifies this by looking at the R (correlation) of the models performance.
ANOVA:
ANOVA stands for Analysis of Variance. It is a statistical test commonly used in comparative analyses based research. What it does is it compares the statistical significance of the variance between a group of means. In this indicator, the ANOVA is uses 3 variables, the lagged high, lagged low and lagged close value over a 14 candle lookback period. In my observations, these settings have been very useful in identifying pivots and breakouts when a significant ANOVA is triggered.
There are two ways to visualize this with this indicator. The first is by just looking at the chart. When a significant ANOVA results, the chart will display "Reversal" (see below):
Reversal is a bit of a misnomer, because it doesn't always mean that a "reversal" will happen, but that a big move is coming. In this case, the stock broke out to the upside.
How do you know which direction it will go? You can get an idea based on the position within the cloud, for example, when it is at the bottom of the range, reversal signals tend to mean it will go up:
But what it does more importantly is puts you on alert that something is about to happen, whether it is a pivot or a breakout/down.
ANOVA has also been applied to buy and sell signals that the indicator produces:
The indicator will look at the SMA of the ANOVA, as well as the position of the stock in relation to the autoregerssion model, and decide when to signal a sell or buy signal. Generally, the parameters are a significant ANOVA that is above its SMA and a move outside of the expected range.
There is another way to visualize the ANOVA using this indicator, and that is with the candle counting chart:
This will show you areas of significance over the last 31 candles, so you can identify precise areas of reversals in the most recent trading history. The table and candle numbers can be toggled off as well.
Significance Value:
And important note needs to be made about the significance value. ANOVA requires a "critical value", a value that must be met in order for something to be deemed "statistically significant". There are different levels of critical values for ANOVA based on the desired confidence. All this means is, how strict to you want your signals to be. The general recommendation for this indicator is this:
On any timeframe 4 hours or below, leave the critical value at 0.01.
On any timeframe above 4 hours, including the daily timeframe, use 0.05 or 0.10.
You can toggle these settings in the menu:
It also works really well on the larger timeframes:
QQQ 1D:
Uses & Tips:
This can be used as a standalone indicator or in combination with other indicators/strategies. I personally use this indicator frequently on the 1 hour and 5 minute timeframes to see where we are in relation to the anticipated range, and whether there is any significance on the ANOVA analysis.
Some tips for use:
Works best on the 5 minute chart for intra-day trades.
Works best on a ranging market on the shorter timeframes.
Works great on the larger timeframes in all markets!
Can be used on any instrument, be it Crypto, commodities, futures, indices etc..
And that is the indicator!
As always leave your questions and comments below.
For access, please follow the instructions below.
Safe trades everyone!
