occ3aka weighted fair price
The ultimate price source for all your stuff, unless you go completely nuts.
The ultimate way to build line charts & do pattern trading, unless you go completely nuts.
Why occ3?
You need a one-point estimate for every bar, a typical price of every bar aye? But then you see that every bar has a different distribution of prices. You can drop a stat test on every bar and pick median, mean, or whatever. But that's still prone to error (imagine borderline cases).
Instead, you can transform the task into a geometric one and say, "I wanna find the center of mass of all dem ticks within a particular interval (a day, a week, a century)". But lol ofc you won't do it, so lets's estimate it:
1) a straight line from Open to Close more/less estimates a regression line if you woulda dropped regression on all the ticks within a given interval;
2) centroid always lies on regression line, so it's always in between the endpoints of regression line. So that's why (open + close) /2;
3) Then, you remember that sequence matters, + generally the volume is higher near the close, so...;
4) Voila, (open + close + close) / 3
Why "fair" price?
Take a daily bar:
1) High & low were the best prices to sell & buy;
2) Opening & closing auctions had acceptable prices, in exchange for the the biggest potential to transact serious volume;
3) "Fair" price, logically, is somewhere in between the acceptable prices;
4) Market is fractal => the same principles propagate everywhere;
4) No, POCs and VPOCs don't make much sense as fair prices.
Nothing else to say, really advise to use it as a line chart if you trade price patterns.
Statistics
Forex Strength IndicatorThis indicator will display the strength of 8 currencies, EUR, AUD, NZD, JPY, USD, GBP, CHF, and CAD. Each line will represent each currency. Alongside that, Fibonacci levels will be plotted based on a standard deviation from linear regression, with customizable lengths.
For more steady Fibonacci levels, use higher lengths for both Standard Deviations and Linear Regression. All currency lines come from moving averages with options like EMA, SMA, WMA, RMA, HMA, SWMA, and Linear Regression.
When lines of the active pair are far from each other, it means higher divergence in those currency strengths among the other pairs. The closer the lines are, the lower the divergence.
You can use the Fibonacci levels as points for the reversal or end of the current trend. When the lines cross can be used as a parameter for a more accurate signal of the next movement.
All 28 pairs are loaded from the same time frame and will use the same moving average for all of them
Alerts from the line crossing are available.
Chatterjee CorrelationThis is my first attempt on implementing a statistical method. This problem was given to me by @lejmer (who also helped me later on building more efficient code to achieve this) when we were debating on the need for higher resource allocation to run scripts so it can run longer and faster. The major problem faced by those who want to implement statistics based methods is that they run out of processing time or need to limit the data samples. My point was that such things need be implemented with an algorithm which suits pine instead of trying to port a python code directly. And yes, I am able to demonstrate that by using this implementation of Chatterjee Correlation.
🎲 What is Chatterjee Correlation?
The Chatterjee rank Correlation Coefficient (CCC) is a method developed by Sourav Chatterjee which can be used to study non linear correlation between two series.
Full documentation on the method can be found here:
arxiv.org
In short, the formula which we are implementing here is:
Algorithm can be simplified as follows:
1. Get the ranks of X
2. Get the ranks of Y
3. Sort ranks of Y in the order of X (Lets call this SortedYIndices)
4. Calculate the sum of adjacent Y ranks in SortedYIndices (Lets call it as SumOfAdjacentSortedIndices)
5. And finally the correlation coefficient can be calculated by using simple formula
CCC = 1 - (3*SumOfAdjacentSortedIndices)/(n^2 - 1)
🎲 Looks simple? What is the catch?
Mistake many people do here is that they think in Python/Java/C etc while coding in Pine. This makes code less efficient if it involves arrays and loops. And the simple code may look something like this.
var xArray = array.new()
var yArray = array.new()
array.push(xArray, x)
array.push(yArray, y)
sortX = array.sort_indices(xArray)
sortY = array.sort_indices(yArray)
SumOfAdjacentSortedIndices = 0.0
index = array.get(xSortIndices, 0)
for i=1 to n > 1? n -1 : na
indexNext = array.get(sortX, i)
SumOfAdjacentSortedIndices += math.abs(array.get(sortY, indexNext)-array.get(sortY, index))
index := indexNext
correlation := 1 - 3*SumOfAdjacentSortedIndices/(math.pow(n,2)-1)
But, problem here is the number of loops run. Remember pine executes the code on every bar. There are loops run in array.sort_indices and another loop we are running to calculate SumOfAdjacentSortedIndices. Due to this, chances of program throwing runtime errors due to script running for too long are pretty high. This limits greatly the number of samples against which we can run the study. The options to overcome are
Limit the sample size and calculate only between certain bars - this is not ideal as smaller sets are more likely to yield false or inconsistent results.
Start thinking in pine instead of python and code in such a way that it is optimised for pine. - This is exactly what we have done in the published code.
🎲 How to think in Pine?
In order to think in pine, you should try to eliminate the loops as much as possible. Specially on the data which is continuously growing.
My first thought was that sorting takes lots of time and need to find a better way to sort series - specially when it is a growing data set. Hence, I came up with this library which implements Binary Insertion Sort.
Replacing array.sort_indices with binary insertion sort will greatly reduce the number of loops run on each bar. In binary insertion sort, the array will remain sorted and any item we add, it will keep adding it in the existing sort order so that there is no need to run separate sort. This allows us to work with bigger data sets and can utilise full 20,000 bars for calculation instead of few 100s.
However, last loop where we calculate SumOfAdjacentSortedIndices is not replaceable easily. Hence, we only limit these iterations to certain bars (Even though we use complete sample size). Plots are made for only those bars where the results need to be printed.
🎲 Implementation
Current implementation is limited to few combinations of x and fixed y. But, will be converting this into library soon - which means, programmers can plug any x and y and get the correlation.
Our X here can be
Average volume
ATR
And our Y is distance of price from moving average - which identifies trend.
Thus, the indicator here helps to understand the correlation coefficient between volume and trend OR volatility and trend for given ticker and timeframe. Value closer to 1 means highly correlated and value closer to 0 means least correlated. Please note that this method will not tell how these values are correlated. That is, we will not be able to know if higher volume leads to higher trend or lower trend. But, we can say whether volume impacts trend or not.
Please note that values can differ by great extent for different timeframes. For example, if you look at 1D timeframe, you may get higher value of correlation coefficient whereas lower value for 1m timeframe. This means, volume to trend correlation is higher in 1D timeframe and lower in lower timeframes.
Aggregated Volume Profile Spot & Futures ⚉ ＯＶＥＲＶＩＥＷ ⚉
Aggregate Volume Profile - Shows the Volume Profile from 9 exchanges. Works on almost all CRYPTO Tickers!
You can enter your own desired exchanges, on/off any others, as well as select the sources of SPOT, FUTURES and others.
The script also includes several input parameters that allow the user to control which exchanges and currencies are included in the aggregated data.
The user can also choose how volume is displayed (in assets, U.S. dollars or euros) and how it is calculated (sum, average, median, or dispersion).
WARNING Indicator is for CRYPTO ONLY.
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Data Type — Choose Single or Aggregated data.
• Single — Show only current Volume.
• Aggregated — Show Aggregated Volume.
Volume By — You can also select how the volume is displayed.
• COIN — Volume in Actives.
• USD — Volume in United Stated Dollar.
• EUR — Volume in European Union.
• RUB — Volume in Russian Ruble.
Calculate By — Choose how Aggregated Volume it is calculated.
• SUM — This displays the total volume from all sources.
• AVG — This displays the average price of the volume from all sources.
• MEDIAN — This displays the median volume from all sources.
• VARIANCE — This displays the variance of the volume from all sources.
• Delta Type — Select the Volume Profile type.
• Bullish — Shows the volume of buyers.
• Bearish — Shows the volume of sellers.
• Both — Shows the total volume of buyers and sellers.
Additional features
The remaining functions are responsible for the visual part of the Volume Profile and are intuitive and I recommend that you familiarize yourself with them simply by using them.
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If you have any ideas what to add to my work to add more sources or make calculations cooler, suggest in DM .
Also I recommend exploring and trying out my similar work.
Expected Move Plotter IntradayHello everyone!
I am releasing my Intra-day expected move plotter indicator.
About the indicator:
This indicator looks at 3 differing time frames, the 15, 30 and 60 minute time frames.
It calculates the average move from high to low over the past 5 candle period and then plots out the expected move based on that average.
It also attempts to determine the sentiment. How it does this is by taking the average of the High, Low and Close of the previous 5 minute candle and comparing it in relation to the close of the current 5 minute candle. It essentially is the premise of pivot points.
Each time frame can be shut off or selected based on your preference, as well as the sentiment fills.
How to use:
Please play around with it and determine how you feel you could best use it, but I can share with you some tips that I have picked up from using this.
Wait for a clear rejection of respect of a level:
Once you have confirmed rejection or support, you can scalp to the next support level:
As well, you can switch between the 30 and 60 minute time frames as reference
30 Minute:
And that's it!
Its a very simplistic indicator, but it is quite helpful to help identify potential areas of reversal.
There really isn't much to it!
Also, it can be used on any stock!
As always, I have provided a quick tutorial video for your reference, linked below:
Let me know if you have any questions or recommendations for modification to make the indicator more useful and helpful.
Thanks so much for checking it out and trying it out everyone!
As always, safe trades and green days!
Probabilities Module - The Quant Science This module can be integrate in your code strategy or indicator and will help you to calculate the percentage probability on specific event inside your strategy. The main goal is improve and simplify the workflow if you are trying to build a quantitative strategy or indicator based on statistics or reinforcement model.
Logic
The script made a simulation inside your code based on a single event. For single event mean a trading logic composed by three different objects: entry, take profit, stop loss.
The script scrape in the past through a look back function and return the positive percentage probability about the positive event inside the data sample. In this way you are able to understand and calculate how many time (in percentage term) the conditions inside the single event are positive, helping to create your statistical edge.
You can adjust the look back period in you user interface.
How can set up the module for your use case
At the top of the script you can find:
1. entry_condition : replace the default condition with your specific entry condition.
2. TPcondition_exit : replace the default condition with your specific take profit condition.
3. SLcondition_exit : replace the default condition with your specific stop loss condition.
New Highs-New-Lows on US Stock Market - Main Chart Edition#### ENGLISH ####
This script visualizes divergences between the price and new highs and new lows in the US stock market. The indicator should be used exclusively on the US stock indices (timeframe >= D).
This is the indicator for the main chart. It should be used together with the subchart indicator of the same name. In order to get the same results between the main and subchart editions, the indicator settings must be manually adjusted equally in both charts.
The approach:
Let's take a bull market as an example. A bull market is characterized by rising highs and rising lows. We can therefore assume that with the rising prices, the number of stocks that form new highs also rises or at least remains constant. This confirms the upward trend and thus expresses that it is supported by the broad stock market. If the market forms new highs and the number of stocks forming new highs decreases at the same moment, these new index highs are no longer supported by the broad stock market but exclusively by a few highly capitalized stocks. This creates a bearish divergence between the index and the NHNL indicator. This means that the uptrend tends to be overheated and a correction becomes more likely. Stops should be drawn closer.
The approach applies conversely, of course, to downtrends as well.
The indicator itself:
The number of new highs and lows (NHNL) are determined using the data sources included in Tradingview, such as "INDEX:HIGN" for NYSE highs. This data is provided on a daily basis. For higher time units (week, month) the daily numbers are shown summed up and not only the Friday value like most other NHNL indicators.
The signal strength is determined on the basis of two factors. The stronger the signal, the clearer (less transparent) the line/arrow. The two factors are on the one hand the strength of the divergence in and of itself, and on the other hand the strength of the overriding trend. The trend strength is determined using a 50 EMA on the NHNL indicator.
To avoid displaying every small divergence and to reduce false signals, the threshold for the signal strength can be set in the indicator settings.
#### GERMAN #####
Dieses script visualisiert Divergenzen zwischen dem Preis und neuer Hochs sowie neuer Tiefs im US Aktienmarkt. Der Indikator sollte ausschließlich auf den US Aktienindizes verwendet werden (Timeframe >= D).
Dies ist der Indikator für den Hauptchart. Er sollte zusammen mit dem gleichnamigen Subchart Indikator verwendet werden. Um gleiche Ergebnisse zwischen Haupt- und Subchart Edition zu erhalten, müssen die Indikatoreistellung manuell in beiden Charts gleichermaßen eigestellt werden.
Der Ansatz:
Nehmen wir uns als Beispiel einen Bullenmarkt. Ein Bullenmarkt zeichnet sich durch steigende Hochs und steigende Tiefs aus. Man kann also annehmen, dass mit den steigenden Preisen auch die Anzahl der Aktien die neuen Hochs ausbilden steigt oder zumindest konstant bleibt. Dies bestätigt den Aufwärtstrend und drückt somit aus, dass dieser vom breiten Aktienmarkt mitgetragen wird. Wenn der Markt neue Hochs bildet und die Anzahl der Aktien, die neue Hochs bilden im selben Moment sinkt, so werden diese neuen Indexhochs vom breiten Aktienmarkt nicht mehr getragen sonder ausschließlich von wenigen hochkapitalisierten Aktien. Es entsteht eine bärische Divergenz zwischen Index und dem NHNL Indikator. Das bedeutet, dass der Aufwärtstrend tendenziell überhitzt ist und ein Korrektur wahrscheinlicher wird. Die Stops sollten näher herangezogen werden.
Der Ansatz gilt umgekehrt natürlich auch bei Abwärtstrends.
Der Indikator an sich:
Die Anzahl der neuen Hochs und Tiefs (NHNL) werden anhand der in Tradingview enthaltenen Datenquellen wie z.B. "INDEX:HIGN" für die NYSE Hochs ermittelt. Diese Daten werden auf Tagesbasis bereitgestellt. Für höher Zeiteinheiten (Woche, Monat) werden die Tageszahlen aufsummiert dargestellt und nicht wie bei den meisten anderen NHNL Indikatoren nur der Freitagswert.
Die Signalstärke wird Anhand zweier Faktoren ermittelt. Je stärker das Signal um so deutlicher (weniger transparent) die Linie/der Pfeil. Die zwei Faktoren sind zum einen die stärke der Divergenz an und für sich, sowie zum anderen die Stärke des übergeordneten Trends. Die Trendstärke wird anhand eines 50er-EMA auf den NHNL-Indikator ermittelt.
Um nicht jede kleine Divergenz anzuzeigen und um Fehlsignale zu reduzieren, kann die Schwelle für die Signalstärke in den Indikatoreinstellungen festgelegt werden.
New Highs-New-Lows on US Stock Market - Sub Chart Edition#### ENGLISH ####
This script visualizes divergences between the price and new highs and new lows in the US stock market. The indicator should be used exclusively on the US stock indices (timeframe >= D).
This is the indicator for the sub chart. It should be used together with the main chart indicator of the same name. In order to get the same results between the main and subchart editions, the indicator settings must be manually adjusted equally in both charts.
The approach:
Let's take a bull market as an example. A bull market is characterized by rising highs and rising lows. We can therefore assume that with the rising prices, the number of stocks that form new highs also rises or at least remains constant. This confirms the upward trend and thus expresses that it is supported by the broad stock market. If the market forms new highs and the number of stocks forming new highs decreases at the same moment, these new index highs are no longer supported by the broad stock market but exclusively by a few highly capitalized stocks. This creates a bearish divergence between the index and the NHNL indicator. This means that the uptrend tends to be overheated and a correction becomes more likely. Stops should be drawn closer.
The approach applies conversely, of course, to downtrends as well.
The indicator itself:
The number of new highs and lows (NHNL) are determined using the data sources included in Tradingview, such as "INDEX:HIGN" for NYSE highs. This data is provided on a daily basis. For higher time units (week, month) the daily numbers are shown summed up and not only the Friday value like most other NHNL indicators.
The signal strength is determined on the basis of two factors. The stronger the signal, the clearer (less transparent) the line/arrow. The two factors are on the one hand the strength of the divergence in and of itself, and on the other hand the strength of the overriding trend. The trend strength is determined using a 50 EMA on the NHNL indicator.
To avoid displaying every small divergence and to reduce false signals, the threshold for the signal strength can be set in the indicator settings.
#### GERMAN #####
Dieses script visualisiert Divergenzen zwischen dem Preis und neuer Hochs sowie neuer Tiefs im US Aktienmarkt. Der Indikator sollte ausschließlich auf den US Aktienindizes verwendet werden (Timeframe >= D).
Dies ist der Indikator für den Subchart. Er sollte zusammen mit dem gleichnamigen Hauptchart Indikator verwendet werden. Um gleiche Ergebnisse zwischen Haupt- und Subchart Edition zu erhalten, müssen die Indikatoreistellung manuell in beiden Charts gleichermaßen eigestellt werden.
Der Ansatz:
Nehmen wir uns als Beispiel einen Bullenmarkt. Ein Bullenmarkt zeichnet sich durch steigende Hochs und steigende Tiefs aus. Man kann also annehmen, dass mit den steigenden Preisen auch die Anzahl der Aktien die neuen Hochs ausbilden steigt oder zumindest konstant bleibt. Dies bestätigt den Aufwärtstrend und drückt somit aus, dass dieser vom breiten Aktienmarkt mitgetragen wird. Wenn der Markt neue Hochs bildet und die Anzahl der Aktien, die neue Hochs bilden im selben Moment sinkt, so werden diese neuen Indexhochs vom breiten Aktienmarkt nicht mehr getragen sonder ausschließlich von wenigen hochkapitalisierten Aktien. Es entsteht eine bärische Divergenz zwischen Index und dem NHNL Indikator. Das bedeutet, dass der Aufwärtstrend tendenziell überhitzt ist und ein Korrektur wahrscheinlicher wird. Die Stops sollten näher herangezogen werden.
Der Ansatz gilt umgekehrt natürlich auch bei Abwärtstrends.
Der Indikator an sich:
Die Anzahl der neuen Hochs und Tiefs (NHNL) werden anhand der in Tradingview enthaltenen Datenquellen wie z.B. "INDEX:HIGN" für die NYSE Hochs ermittelt. Diese Daten werden auf Tagesbasis bereitgestellt. Für höher Zeiteinheiten (Woche, Monat) werden die Tageszahlen aufsummiert dargestellt und nicht wie bei den meisten anderen NHNL Indikatoren nur der Freitagswert.
Die Signalstärke wird Anhand zweier Faktoren ermittelt. Je stärker das Signal um so deutlicher (weniger transparent) die Linie/der Pfeil. Die zwei Faktoren sind zum einen die stärke der Divergenz an und für sich, sowie zum anderen die Stärke des übergeordneten Trends. Die Trendstärke wird anhand eines 50er-EMA auf den NHNL-Indikator ermittelt.
Um nicht jede kleine Divergenz anzuzeigen und um Fehlsignale zu reduzieren, kann die Schwelle für die Signalstärke in den Indikatoreinstellungen festgelegt werden.
Average Range @coldbrewroshTaking the average daily range from low to high or high to low isn't the "best" way to get an idea of how much to set targets. So, I made this indicator to make the system better.
This indicator calculates the daily range from Open to High on Bullish Days & Open to Low on Bearish Days .
Nobody can catch the absolute low of the day on bullish days and get out at the high but one can enter at a reasonable price around the open ( 17:00 EST ) .
To complement the Average Range, another table shows the movement in the opposite direction.
For Instance: On Bullish Days how much it moved from Open to Low so that we have an idea of where to put the stop loss and vice versa. The time ranges calculated are the last 5 days, last 1 month, last 3 months & last 1 year.
Note #1: Even though the date range is predefined, it has a different meaning. For Instance: date range of last 5 days means "calculation of the range of last 5 bullish daily candles & not last 5 days" .
Note #2: Exclusive to Forex at the time of posting this.
Fiat Currency and Gold Indices (FGXY) CandlesA modification of my previous indicator "Crypto Index (DXY) Candles". The idea was to create a similar currency basket to the standard DXY, but from the perspective of other currencies. Still using the standard DXY weights, this indicator allows you to create a tailored index for other currencies, provided that a currency pair exists for each of the 6 components. This means that even currencies that aren't included should work in theory; just find the 3 character currency prefix used by tradingview and give it a shot! This indicator is useful for gauging how well countries/currencies are holding up and when paired with the standard DXY may help see potential inflection points. For use on longer time frames (~1h-~3d) as some of the data being pulled seems to have issues on lower timeframes.
SAFE MARGINE_OSHi dear Investors!
Here I present you my last prepared indicator that works with searching on the most visited prices in a period. It also take an average of them which is described here as balance line.
Inputs:
+BACKWARD: range of your search area on history from current moment.
+MEMORY: number of memory stacks that would be used to save previous calculated values for taking an average.
+REFRESH: this parameter is in mili-seconds and describe saving data in memory stacks.
+METHODOLOGY:
++OC-BASED: OPEN/CLOSE would be used for calculations
++HL-BASED: HIGH/LOW would be used for calculations
++MID-BASED: HL2/OHLC4 would be used for calculations
Please do not forget to 'BOOST' the script if you use it!
Happy trading!
PlanB4.
Financial Data Spreadsheet [By MUQWISHI]The Financial Data Spreadsheet indicator displays tables in the form of a spreadsheet containing a set of selected financial performances of a company within the most recent reported period. Analyzing Financial data is one of the classic methods to evaluate whether the company’s stock price is overvalued or undervalued based on its income statement, balance sheet, and cash flow statement. This indicator might be practical to investors to collect needed data of a company to analyze and compare it with other companies on a TradingView chart or print it in spreadsheet form.
█ OVERVIEW
█ BEST PRACTICES
Due to strict limitations on calling request.financial() function, I tried to develop the table with the best ways to be more dynamic to move and the ability to join multiple tables into a spreadsheet. Users can add up to 20 instruments and 2 financial metrics per table. However, it’s possible to add many tables with other financial metrics, then connect them to the main table.
Credits: The idea of joining multiple tables inspired by @QuantNomad Screener for 40+ instruments
█ INDICATOR SETTINGS
1- Moving Table toward right-left up-down from its origin.
2- Hiding Column Title checkmark. Useful for adding a joined table underneath with additional instruments.
3- Hiding Instruments Title checkmark. Useful for adding a joined table on the right with other financial metrics.
4- Shade Alternate Rows checkmark. I believe it’ll make the table easier to read.
5- Selecting Financial Period. (Year, Quarter).
6- Entering a currency.
7- Choosing a financial ID for each column. There’re over 200 financial IDs. Source: What financial data is available in Pine? — TradingView
8- Optional to highlight values in between.
9- Entering the ticker’s symbol with the ability to activate/deactivate.
█ TIP
For best technical performance, use the indicator in a 1D timeframe.
Please let me know if you have any questions.
Thank you.
Open Interest Denominated in QuoteOpen Interest indicator in TradingView doesn't have option to denominate in quote, so I made one.
Monthly ReturnsDisplays monthly and yearly returns in tabular format along with maximum, minimum, average returns and standard deviations.
This uses boxes to build the table and as maximum boxes that could be used is 500, it displays up to 32 years of returns. However, for maximum, minimum, average and standard deviation calculations, it uses data from all months since inception.
This requires timeframe to be set to one month (1M). Cell widths correspond to years. For the first year, cell widths may be shorter and there could be overlap of numbers as nothing could be drawn before the first bar.
Provide sufficient space for the table to render properly. Zooming out or less space may lead to overlapping of numbers.
Position Size ToolUpdated - Version 2
This tool is used to calculate the size of a trade.
Settings - Type in total account size and % of capital that can be risked on each trade.
The table will display:
Column 1 - Stop placement based on low, mid or high value of the current candle.
Column 2 - Percent risk on the trade.
Column 3 - Amount of shares that can be traded (calculated from account size, risk and selected stop placement).
Green color is intended for long position, stop at the low of the candle.
Red color is intended for short position, stop at the high of the candle.
Middle value can shift between either color since its measured from open to close.
AlexD Market annual seasonalityThe indicator displays the percentage of bullish days with a given date over several years.
This allows you to determine the days of the year when the price usually goes up or down.
Indicator has a built-in "simple moving average" shifted back by half a period, due to which the delay of this smoothing is removed.
Z-Score Buy and Sell SignalsHello everyone!
Happy Holidays, Merry/Happy Christmas!
Here is my Christmas gift to you to show my appreciation of your support and engagement over the past year!
This is the Z-Score Buy and Sell Signal indicator!
How it works:
It works by looking at the Z-Score of an equities close price and looking for previous areas over reversals over the defined period of time.
It also looks at areas that are overbought or oversold (manifested by Z-Scores greater than or less than 2 Standard Deviations away) and displays them as bar colour changes.
Historic reversals are signaled with buy and/or sell signals.
Oversold is signaled with a green bar colour change (colour can be customaized).
Overbought is signaled with an orange bar colour change.
How to use it:
You can use it with support resistance or other indicators. You can use this on both the larger and small timeframes, depending on the style of trader you are.
You can modify the input length to look back on shorter or longer periods.
As a general rule from my experience using it, if you are using the shorter timeframes (i.e. 1 minute tfs), its best to look back between 50 and 75 candles for most equities.
If you are looking at the larger timeframes (i.e. Daily, 1 to 2 hour, etc.) its best to set the input value to between 500 to 800.
But, as always, you should check to ensure the indicator is providing correct signals by reviewing the previous signals to ensure that they adequate identified reversals.
It is also best not to use this alone as your sole indicator. It is meant to be supplementary to other indicators/support resistance/chart patterns you are using to guide your trades. This will not replace good TA and a good understand of the stock and its likely trajectory.
As always, please feel free to share your comments/feedback/questions and recommendations below.
As always, I do customary tutorial videos for my indicators, so please see below for an in-depth video tutorial should you want to see it in action:
Otherwise, happy holidays everyone! And all of the best over this Christmas weekend to you and your loved ones!
Multi-Polar WorldA new macro analysis tool for easily analyzing the multi-polar world's economic powerhouses / spheres of influence, making for an easy to use visual when comparing a number of statistics:
GDP, GDP per Capita, External Debt, Government Debt, Exports, Imports, Gold Reserves, Employed Persons, Military Expenditure, Population, Bank Lending Rate, Balance of Trade, Central Bank Balance Sheet, M2 Money Supply, and CPI . Includes option to provide the total for each pole, or view individually for more detailed comparison. Meant to be used when analyzing the macro-economic conditions/trends in conjunction with other "Big Picture" type indicators when adjusting your macro framework.
Seasonal tendency: week-on-week % change and 10yr Averages-shows week-on-week % change, and 10yr averages of these % changes
-scan across the 10yr averages to get a good idea of the seasonality of an asset
-best used on commodities with strong seasonal tendencies (Gold, Wheat, Coffee, Lean hogs etc)
-works only on daily timeframe
-by default it will compare SMA(length) in the following way, BTC: Sunday cf previous Sunday | ES/Gold: Monday cf previous Monday
-for most assets, 5 daily bars in a week (SMA(5)) => that's the default. For BTC can change this to 7.
~~inputs:
-change input year to show any previous decade of asset's history; the table will display over that year on the chart
-choose expression for Average of % change week on week: SMA, ohlc4, vwma, vwap (default SMA)
-choose number of daily bars in a week (i.e. SMA length)
-change label sizes/colors
~~notes:
-When applied to current year: will print the 10yr average for previous weeks in the year; 9yr average for future weeks in the year
-drawings and SMA plot on the above chart are just to show visually how the week's average is calculated, and how this lines up with the label
-current week of year will highlight in large font orange by default
-the first 2 weeks of the year are omitted because of a bug i can't figure out, which throws out bad numbers.
-cannot print all the values for each of previous 10yrs; 'code too long' error. Could likely do this via using matrices but would require a rewrite
17th Dec 2022
@twingall
Economic Calendar Events NickShows Economic Events for possible trade setups. Different events like GOP and CPI. It also works in a way if you want to avoid a trade based on the news.
Trend Finder with Coefficient of VariationCoefficient of variation (“COV”) is a statistical measure used to describe the variability of values within a data set, it’s calculated by taking the standard deviation divided by the mean.
Traditionally, COV is applied to the expected returns of competing investment portfolios. A risk adverse investor prefers to accept a portfolio with a relatively lower COV value.
On the other hand, when applying COV to price charts, the difference is that instead of looking at expected returns, we now treat price as the source of data. We look at price from a moving average perspective. This script purely focuses on price.
What this indicator does:
Firstly, to go over the parameters:
Let ‘n’ be the lookback period for computing COV, and ‘m’ be the period for comparing the ranking of COVs.
Logics in a nutshell:
This program will (A) calculate the COV by dividing the moving standard deviation by moving average over ‘n’ bars, and then (B) illustrate the relationship of how COV at each bar ranks compared to COVs over past ‘m’ bars. We use a color scale (default black and yellow) for visualizing ranking in terms of percentiles. If COV is below its median value, then we assume that price is consolidating.
Hypothesis:
Using COV on top of regular SMA signals should reduce a lot of unwanted noise such as consecutive crossovers during ranging-periods. Traders want volatility, but not too much of it when sniping for entry opportunities (speaking of initial position; need to add to winning positions after, but this is for another topic). For this reason, the median value of COV is suitable as a metric for signals.
Applications:
We use the median value of COV to form a decision rule. A signal is generated when COV > median(COV,m), and the direction of trend is determined based on relative position of price with respect to sma(price,n). When the value of COV is increasing, it can also be thought of seeing Bollinger Bands beginning to bulge. When trends begin, this program will plot triangles to signify entry opportunities.
