Percentage of direction alternationThis is just an idea I had and I have no idea whether it will be useful but I thought I would “toss it out into the wild” because if someone finds it of benefit then all the better.
How it works is really simple. It looks at a number of bars/candles back and if two bars next two each other close where one is higher than its open and the other closes lower (a bullish and bearish candle next to each other) then it adds one to the count of alternations. So, if you are looking 10 (adjustable of course) bars back then you can have 9 compares (number of bars subtract one).
If all nine compares are opposite closes of each other then you get a 100% alternation.
I’m not sure if this is useful for anyone but my original thought was the more alternation the more likely you are in ranging and the less you should consider entering a trade or the more you should consider exiting a trade. It might also reflect choppiness to some extent as well.
I also noticed in a couple of spots when I was looking at the results that good trends came just after the alternation peaked around 100% so it might be a bit of an indicator to enter a trade before the move happens.
It shows the alternation percentage but also the “weighted alternation” percentage which I think looks more useful as it give more credence to the alternations closer the live trading.
For visual usefulness you can invert the output so that maximum alternation is 0 instead of 100.
I’ve set it up as being displayed as area but as normal lines is also good.
Let me know if you find a way that it shows something useful for entering or exiting your trades. The more feedback I get the more I’ll throw my crazy notions out there!
The code is structured to easily drop into a bigger system so use it as a lone indicator or add the code to some bigger project you are creating. If you do integrate it into something else then send me a note as it would be nice to know it's being well used.
Enjoy and good luck!
Search in scripts for "one一季度财报"
Trail Blaze - (Multi Function Trailing Stop Loss) - [mutantdog]Shorter version:
As the title states, this is a 'Trailing Stop' type indicator, albeit one with a whole bunch of additional functionality, making it far more versatile and customisable than a standard trailing stop.
The main set of features includes:
Three independent trailing types each with their own +/- multipliers:
- Standard % change
- ATR (aka Supertrend)
- IQR (inter-quartile range)
These can be used in isolation or summed together. A subsequent pair of direction specific multipliers are also included.
Two separate custom source inputs are available, both feature the standard options alongside a selection of 'weighted inputs' and the option to use another indicator (selected via 'AUX'):
- 'Centre' determines the value about which the trailing sum will be added to define the stop level.
- 'Trigger' determines the value used for crossing of stops, initiating trend changes and triggering alerts.
A selection of optional filters and moving averages are available for both.
Furthermore there are various useful visualisation options available, including the underlying bands that govern the stop levels. Preset alerts for trend reversals are also included.
This is not really an 'out-of-the-box' indicator. Depending upon the market and timeframe some adjustments will be necessary for it to function in a useful manner, these can be as simple or complex as the feature-set allows. Basic settings are easy to dial in however and the default state is intended as a good starting point. Alternatively with some experimentation, a plethora of unique and creative configurations are possible, making this a great tool for tweaking. Below is a more detailed overview followed by a bunch of simple example settings.
------------------------
Lengthy Version :
DESIGN & CONCEPT
Before we start breaking this down, a little background. This started off as an attempt to improve upon the ever-popular Supertrend indicator. Of course there are many excellent user created variants available utilising some interesting methods to overcome the drawbacks of the basic version. To that end, rather than copying the work of others, the direction here shifted towards a hybrid trailing stop loss with a bunch of additional user customisation options. At some point, a completely different project involving IQR got morphed into this one. After sitting through months of sideways chop (where this proved to be of limited use), at the time of publication the market has began to form some near term trend direction and it appears to be performing well in many different timeframes.
And so with that out of the way...
INPUTS
The standard Supertrend (and most other variants) includes a single source input, as default set to 'hl2' (candle mid-range). This is the centre around which the atr bands are added/subtracted to govern the stop levels. This is not however the value which is used to trigger the trend reversal, that is usually hard-coded to 'close'. For this version both source values are adjustable: labelled 'centre' and 'trigger' respectively.
Each has custom input selectors including the usual options, a selection of 'weighted inputs' and the option to use another indicator (selected from the Aux input). The 'weighted inputs' are those introduced in Weight Gain 4000, for more details please refer to that listing. These should be treated as experimental, however may prove useful in certain configurations. In this case 'hl-oc2' can be considered an estimate of the candle median and may be a good alternative to the default 'centre' setting of 'hl2', in contrast 'cc-ohlc4' can tend to favour the extremes in the trend direction so could be useful as a faster 'trigger' than the default 'close'.
To cap them off both come with a selection of moving average filters (SMA, EMA, WMA, RMA, HMA, VWMA and a simple VWEMA - note: not elastic) aswell as median and mid-range. 'Centre' can also be set to the output of 'trigger' post-filter which can be useful if working with fast/slow crosses as the basis.
DYNAMICS
This is the main section, comprised of three separate factors: 'TSL', 'ATR' and 'IQR'. The first two should be fairly obvious, 'TSL' (trailing stop loss) is simply a percentage of the 'centre' value while 'ATR' (average true range) is the standard RMA-based version as used in Supertrend, Volatility Stop etc.
The third factor is less common however: 'IQR' (inter-quartile range). In case you are unfamiliar the principle here is, for a given dataset, the greatest 25% and smallest 25% of samples are removed. The remainder is then treated as a set and the range is calculated by highest - lowest. This is a commonly used method in statistical analysis, by removing the extremes it is less prone to influence by outliers and gives a good representation of the main dispersion around the median. In practise i have found it can be a good alternative to ATR, translating better across multiple time-frames due to it representing a fraction of the total range rather than an average of per-candle range like ATR. Used in combination with the others it can also add a factor more representative of longer-term/higher-timeframe trend. By discarding outliers it also benefits from not being impacted by brief pumps/volatility, instead responding only to more sustained changes in trend, such as rallies and parabolic moves. In order to give an accurate result the IQR is calculated using a dataset of high, low and hlcc4 values for all bars within the lookback length. Once calculated this value is then halved which, strictly speaking, makes it a semi-interquartile range.
All three of these components can be used individually or summed together to create a hybrid dynamics factor. Furthermore each multiplier can be set to both positive and negative values allowing for some interesting and creative possibilities. An optional smoothing filter can be applied to the sum, this is a basic SWMA-4 which is can reduce the impact of sudden changes but does incur a noticeable lag. Finally, a basic limiter condition has been hard-coded here to prevent the sum total from ever going below zero.
Capping off this section is a pair of direction multipliers. These simply take the prior dynamics sum and allow for further multiplication applied only to one side (uptrend/lo-stop and downtrend/hi-stop). To see why this is useful consider that markets often behave differently in each direction, we've all seen prices steadily climb over several weeks and then abruptly dump in the process of a day or two, shorter time frames are no stranger to this either. A lack of downside liquidity, a panicked market, aggressive shorts. All these things contribute to significant differences in downward price action. This function allows for tighter stops in one direction compared to the other to reflect this imbalance.
VISUALISATIONS
With all of these options and possibilities, some visual aids are useful. Beneath the dynamics' section are several visual options including both sources post-filter and the actual 'bands' created by the dynamics. These are what govern the stop levels and seeing them in full can help to better understand what our various configurations actually do. We can even hide the stop levels altogether and just use the bands, making this a kind of expanded Keltner Channel. Here we can also find colour and opacity settings for everything we've discussed.
EXAMPLES
The obvious first example here is the standard %-change trailing stop loss which, from my experience, tends to be the best suited for lower time frames. Filtering should probably minimal here. In both charts here we use the default config for source inputs, the top is a standard bi-directional setup with 1.5% tsl while the bottom uses a 2.5% tsl with the histop multiplier reduced to 0 resulting in an uptrend only stoploss.
Shown here in grey is the standard Supertrend which uses 'hl2' as centre and 'close' as trigger, ATR(10) multiplied by 3. On top we have the default filtered source config with ATR(8) multiplied by 2 which gives a different yet functionally similar result, below is the same source config instead using IQR(12) multiplied by 2. Notice here the more 'stepped' response from IQR following the central rally, holding back for a while before closing in on price and ultimately initiating reversal much sooner. Unlike ATR, the length parameter for IQR is absolute and can more significantly affect its responsiveness.
Next we focus on the visualisation options, on top we have the default source config with ATR(8) multiplied by 2 and IQR(12) multiplied by 1. Here we have activated the switch to show 'bands', from this we can see the actual summed dynamics and how it influences the stop levels. Below that we have an altogether different config utilising the included filters which are now visible. In this example we have created a basic 8/21 EMA cross and set a 1% TSL, notice the brief fakeout in the middle which ordinarily might indicate a buy signal. Here the TSL functions as an additional requirement which in this case is not met and thus no buy signal is given.
Finally we have a couple of more 'experimental' examples. On top we have Lazybear's 'Variable Moving Average' in white which has been assigned via 'aux' as the centre with no additional filtering, the default config for trigger is used here and a basic TSL of 1.5% added. It's a simple example but it shows how this can be applied to other indicators. At the bottom we return to the default source config, combining a TSL of 8% with IQR(24) multiplied by -2. Note here the negative IQR with greater length which causes the stop to close in on price following significant deviations while otherwise remaining fairly wide. Combining positive and negative multiples of each factor can yield mixed results, some more useful than others depending upon suitable market conditions.
Since this has been quite lengthy, i shall leave it there. Suffice to say that there are plenty more ways to use this besides these examples. Please feel free to share any of your own ideas in the comments below. Enjoy.
Market Sessions - By LeviathanA simple indicator to help you keep track of 4 market sessions (default: Tokyo, London, New York, Sydney) in 4 different visual forms (boxes, timeline, zones, colored candles) with many other useful tools.
You can choose between 4 different market sessions. The default ones are Tokyo, London, New York and Sydney but you can easily customize the times, names and colors to make the script plot any session you need. Sessions can be viewed in 4 different ways: boxes, zones, timelines, or just colored candles, all with customizable appearances. You can make your chart cleaner by merging sessions overlaps, choosing a custom lookback period and also picking between various additional settings such as viewing session High/Low or Open/Close change in % or pips, hiding weekends, viewing the Open/Close Line to identify session’s direction and 0.5 level to see session’s “Equilibrium” and much more. More updates with interesting tools will be added in the future.
Note: The script will plot the correct default Tokyo, London, New York and Sydney sessions automatically, your chart/Tradingview app timezone does not matter! If you wish to tweak the open/close times of sessions, just make sure you input them in UTC (but even this can be changed later in the settings)
Settings Overview
SESSIONS
- You can show/hide Tokyo Session, rename it, change the color and set up start/end time.
- You can show/hide London Session, rename it, change the color and set up start/end time.
- You can show/hide New York Session, rename it, change the color and set up start/end time.
- You can show/hide Sydney Session, rename it, change the color and set up start/end time.
* Keep in mind that you can fully change and customize these sessions and therefore create any other sessions or a zone you wish to display.
ADDITIONAL TOOLS AND SETTINGS
1. “Change (Pips)” - this will add the pip distance between Session High and Session Low or the pip distance between Session Open and Session Close to the session label.
2. “Change (%)” - this will add the percentage distance between Session High and Session Low or the percentage distance between Session Open and Session Close to the session label.
3. “Merge Overlaps” - this will merge the overlapping sessions and show only one at a time (end of Tokyo is moved to start of London, the end of London is moved to the start of New York, end of New York is moved to start of Sydney and end of Sydney is moved to start of Tokyo).
4. “Hide Weekends” - this will prevent the script from plotting sessions over the weekend when the markets are closed.
5. “Open/Close Line” - this will draw a line from the session open to the session close (or current price, if session is ongoing).
6. “Session 0.5 Level” - this will draw a horizontal line halfway between the session’s high and the session’s low.
7. “Color Candles” - this will color the bars/candlesticks with the color of the session in which they occurred.
8. Display Type” - Choose between three different ways of session visualization (Boxes, Zones and Candles).
9. “Lookback (Days)” - this input tells the script to only draw sessions for X days back (1 = one day).
10. “Change (%/Pips) Source) - this is where you choose the source of “Change (Pips)” and ”Change (%) ” labels. Picking “Session High/Low” will show you the change between Session High and Session Low and picking “Session Open/Close” will show you the change between Session Open and Session Close.
11. “Input Timezone” - this defines the timezone of the session start/end inputs (you don’t have to change this unless you know what you’re doing)
Make sure to read future update logs to keep track of the most recent additions and settings of this script.
Box generation code inspired by Jos(TradingCode), session box visuals inspired by @boitoki's FX Market Sessions
Strategy Myth-Busting #4 - LSMA+HULL Crossover - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our fourth one we are automating is one of the strategies from "I Found The Best 1 Minute Scalping Strategy That Actually Works! ( Beginner Friendly )" from "Trade Domination" who claims to have made 366% profit on the 1 min chart of Solona despite having a 31% win rate in just a few weeks. As you can see from the backtest results below, I was unable to substantiate anything close to that that claim on the same symbol ( SOLUSD ), timeframe (1m) with identical instrument settings that "Trade Domination" was demonstrating with. Strategy Busted.
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
This strategy uses a combination of 2 open-source public indicators:
LSMA
Hull Suite by InSilico
Trading Rules
1 min candles
Stop Loss on recent swing High/Low
1:5 Risk Ratio
Enter Long
LSMA cross above Red Hull Suite line
Price has to be above Hull Suite Line
Enter Short
LSMA crosses under green Hull Suite Line
Price has to be below Hull Suite Line
Back to the FutureHallo, very simple indicator in order to view trends
we have two linear regressions
one is the regular one that we know at length 100
the other one is lagging or past linear which is shorter at length 30
the basic idea is that when we combine both we can see trend of the current and the past linear when they cross each other and from this we can make signals.
Assuming that past shorter trend has the value of resistance or threshold values, so cross of current linear of those points can show if the trend is to buy or to sell by signals seen in the arrows .
So past and present mix and give us the future.
need to solve issue when market goes sideways but it easy to see how the trend look by the signals .
past linear seen in concave lines the current is the other one.
signals of positive trends are arrow up green or blue. negative trend red or orange arrow down
RedK K-MACD : a MACD with some more musclesMoving Averages are probably the most commonly used analysis tools, and MACD is possibly the first charting indicator a trader gets to learn about.
MACD Basic concept
----------------------------
Without repeating all the tons of documentation about what MACD does, let's quickly re-visit the MACD concept from a 10-mile altitude (note we're keen on simplifying here rather than being technically accurate - so please forgive the use of any "common lingos")
- MACD goal is to represent the distance between 2 Moving Averages (MAs) - one fast and one slow, relatively - as an unrestricted zero-based oscillator.
- The value of the main MACD line is the distance, or the displacement between the 2 MA's
- usually a signal line is used (which is another MA of that distance value) to enable better visualization of the change (and rate of change, since this is all depicted on a time axis) of that displacement - this represents price momentum (price movement in the recent period versus movements for a relatively longer period).
- the difference between the main MACD line and its signal is then represented as a histogram above and below the zero line. in this case, that histogram is really redundant, since it shows a value that is already represented visually by the main line and its signal line.
How K-MACD is different
---------------------------------
K-MACD takes that simple concept of the classic MACD and expands around it - the idea is to use the same simple approach to representing price momentum while bringing in more insight to price moves in the short, medium and long terms, ability to represent more than 2 MA's and to enable better identification of tradeable patterns (like Volatility Contraction and others) - while still keeping things simple and visually clean.
K-MACD is an indicator that allows us to view how price moves against 3 moving averages: a fast / slow pair, and a "market" Filter or Baseline (very long) that will be used as a flag for Bear/Bull market mode. Many traders and trading literature use the 200 day (40 week) SMA as that key filter
so in total, there are 4 MA lines in K-MACD (excluding the "orange" signal line):
* Price Proxy: Which is a very fast moving average that will represent the price itself - let's use a WMA(3) or something close to that here - there will be a signal line to enable better visualization of this similar to a classic MACD - that's the orange line
* Fast & Slow MA's : Use whatever represents the "medium term" momentum for your trading - Some traders use 20 and 50, others use 10 and 20 .. if on your price chart, you keep using a pair of MA's for this, use the same settings in K-MACD - these will be represented by the 3-color Momentum Bars that fluctuate above and below the baseline
* Filter/Baseline MA: Should be your long (Bullish/Bearish Mode) MA. so 100 or 200 or any other value you consider your market to be bearish below and bullish above. on K-MACD this is actually the blue zero line - everything else is "relative" to it
Review the sample chart which explains various elements and the "price chart" setup that K-MACD represents. With K-MACD you can clean up your chart from those various Moving Averages - or use a different set than the ones you already have K-MACD represent - or other indicators (like ATR channels..etc)
Other "muscles" in the K-MACD
---------------------------------------------
- Relative vs Classic Calculation Mode
A key issue with the classic MACD is that the displacement between the 2 moving averages is represented as "absolute or direct" values - as the price of the underlying increases with time, you can't really use these values to make useful comparison between the past and now (see below example) - also you can't use them to compare 2 different instruments.
- The "Relative" calculation option in K-MACD addresses that issue by relating all "distances" to the Baseline MA as percentage (above or below) - you can see this clear when you look at the above chart the far left versus the far right and compare K-MACD with the classic MACD - the Classic option is still available
- More MA "type" options for all MA lines: choose between SMA, EMA, WMA, and RSS_WMA (which i use a lot in my trading and is my default for the Price Proxy)
- More Alerts: a total or 9 alerts (in 3 groups) are available with K-MACD (Momentum above or below baseline, Price Proxy crossing signal line, and Price Proxy crossing baseline)
- New 52 week High / Low markers: These will show as Green/red circles on the zero line in K-MACD. this will only work for 1D timeframe and above, i'm just using a simple approach and would like to keep it that way.
- i know i added some more features not covered above :) -- if you have questions about any of the settings, feel free to ask below
Closing thoughts
-------------------------
K-MACD is a combination of couple of indicators i published in the past (xMACD and Mo_Bars) - so you can go back and read about them if needed - I then added improvements to accommodate ideas from swing trading literature and common practices that i plan to focus on in future. So K-MACD is really part of my own trading setup.
I assume here that most traders are familiar with what a MACD is - so kept this post short - if you thing we should expand more about the concepts covered here let me know in the comments - i can make some separate posts with examples and more details.
I hope many fellow traders find this work useful - and feel free let me know in comments below if you do.
FrizBugLibrary "FrizBug"
Debug Tools | Pinescript Debugging Tool Kit
All in one Debugger - the benefit of wrapper functions to simply wrap variables or outputs and have the code still execute the same. Perfect for Debugging on Pine
str(inp)
Overloaded tostring like Function for all type+including Object Variables will also do arrays and matricies of all Types
Parameters:
inp : All types
Returns: string
print_label(str, x_offset, y, barstate, style, color, textcolor, text_align, size)
Label Helper Function - only needs the Str input to work
Parameters:
str :
x_offset : offset from last bar + or -
y : price of label
barstate : barstate built in variable
style : label style settin7
color : color setting
textcolor : textcolor
text_align : text align setting
size : text_sise
Returns: label
init()
initializes the database arrays
Returns: tuple | 2 matrix (1 matrix is varip(live) the other is reagular var (Bar))
update(log, live, live_console, log_console, live_lbl, log_lbl)
Put at the very end of your code / This updates all of the consoles
Parameters:
log : This matrix is the one used for Bar updates
live : This matrix is the one used for Real Time updates
live_console : on_offs for the consoles and lbls - call in the update function
log_console : on_offs for the consoles and lbls - call in the update function
live_lbl : on_offs for the consoles and lbls - call in the update function
log_lbl : on_offs for the consoles and lbls - call in the update function
Returns: void
log(log, inp, str_label, off, rows, index_cols, bars_back)
Function Will push to the Console offset to the right of Current bar, This is the main Console - it has 2 Feeds left and right (changeable)"
Parameters:
log : Matrix - Log or Live
inp : All types
str_label : (optional) This input will label it on the feed
off : Useful for when you don't want to remove the function"
rows : when printing or logging a matrix this will shorten the output will show last # of rows"
index_cols : When printing or logging a array or matrix this will shorten the array or the columns of a matrix by the #"
bars_back : Adjustment for Bars Back - Default is 1 (0 for barstate.islast)"
Returns: inp - all types (The log and print functions can be used as wrapper functions see usage below for examples)
Print(log, str_label, off, bars_back)
Function can be used to send information to a label style Console, Can be used as a wrapper function, Similar to str.format use with str()
Parameters:
log :
str_label : (optional) Can be used to label Data sent to the Console
off : Useful for when you don't want to remove the function
bars_back : Adjustment for Bars Back - Default is 1 (0 for barstate.islast)
Returns: string
print(inp, str_label, off, bars_back)
This Function can be used to send information to a label style Console, Can be used as a wrapper function, Overload print function
Parameters:
inp : All types
str_label : string (optional) Can be used to label Data sent to the Console
off : Useful for when you don't want to remove the function
bars_back : Adjustment for Bars Back - Default is 1 (0 for barstate.islast)
Returns: inp - all types (The log and print functions can be used as wrapper functions see usage below for examples)
Credits:
@kaigouthro - for the font library
@RicardoSantos - for the concept I used to make this
Thanks!
Use cases at the bottom
Extended Recursive Bands StrategyThe original indicator was created by alexgrover .
All credit goes to alexgrover for creating the indicator that this strategy uses.
This strategy was posted because there were multiple requests for it, and no strategy based on this indicator exists yet.
The Recursive Bands Indicator, an indicator specially created to be extremely efficient, I think you already know that calculation time is extra important in algorithmic trading, and this is the principal motivation for the creation of the proposed indicator. Originally described in Alex's paper "Pierrefeu, Alex (2019): Recursive Bands - A New Indicator For Technical Analysis", the indicator framework has been widely used in his previous uploaded indicators, however it would have been a shame to not upload it, however user experience being a major concern for me, I decided to add extra options, which explain the term "extended".
The Indicator
The indicator displays one upper and one lower band, every common usages applied to bands indicators such as support/resistance , breakout, trailing stop, etc, can also be applied to this one. Length controls how reactive the bands are, higher values will make the bands cross the price less often.
In order to provide more flexibility for the user alexgrover added the option to use various methods for the calculation of the indicator, therefore the indicator can use the average true range , standard deviation, average high-low range, and one totally exclusive method specially designed for this indicator.
Added logic:
We have implemented a logic that checks whether the bands have been following in the same direction for a set amount of bars. This logic must be true before it can enter trades. This is completely new code that was written by us entirely, and it makes a huge difference on strategy performance.
Strategy Long conditions:
1 — Price low is below the the lower band.
2 — The lower band keeps increasing in value until the 'lookback' setting amount of bars is reached.
Strategy Short conditions:
1 — Price high is above the upper band.
2 — The upper band keeps decreasing in value until the 'lookback' setting amount of bars is reached.
Strategy Properties:
We have set a default commission of 0.06% because these are Bybit's fees. The strategy uses an order size of 10% of equity, since drawdown is very low like this. We also use a 10 tick slippage to keep results realistic and account for this. All other settings were left as default apart from initial capital, just to decrease the size of the numbers.
Sigma Expected Movement [D/W/M]Based on the VIX, this indicator shows the expected movement of a stock, ETF or index.
This indicator has two standard deviations that you can set for better guidance.
You can also adjust it for a result in one day, one week or one month.
Settings
* Period
* 1st Deviation: Default 68%
* 2nd Deviation: Default 90%
*Round To Integer: If it checked, it will search for the nearest integer (+/-). Optimal for people who do Options.
*Table Position: refers to which corner you want to put the table with information.
Volume composition / quantifytools— Overview
While net volume is useful information, it can be a blunt data point. Volume composition breaks down the content of volume, allowing a more detailed look inside each volume node. Volume composition consists of the following information:
Total volume (buy and sell). By default gray node.
Dominating volume (buy or sell). By default dark green/dark red node.
Dominating active volume (buy or sell). By default light green/light red node.
Dominating volume as percentage of total volume.
Dominating active volume as percentage of total active volume.
Buy and sell volume is defined by volume associated with lower timeframe up/down moves. This classification is further broken down to passive/active, standing for decreasing/increasing volume, e.g. a move up with volume higher than previous bar volume = active buy volume, a move up with volume lower than previous bar volume = passive buy volume.
Volume data is fetched from a lower timeframe that is automatically adjusted to fit the timeframe you're using. By default, the following settings are applied:
Charts <= 30 min: 1 minute timeframe
Charts > 30 min & <= 3 hours : 5 minute timeframe
Charts > 3 hours & <= 8 hours : 15 minute timeframe
Charts > 8 hours & <= 1D: 1 hour timeframe
Charts > 1D & <= 3D : 2 hour timeframe
Charts > 3D: 4 hour timeframe
Timeframe settings can be changed via input menu. The lower the timeframe, the more precision you get but with the cost of less historical data and slower loading time. Users can also choose which source to use for determining buy/sell volume, e.g. using close as source, a close that is higher than previous close would be considered as buy volume. This could be replaced with OHLC4 for example, resulting in a volume direction based on OHLC average.
Volume composition of current chart can also be replaced with any other chart volume composition:
— Visuals
Breakdown of visual elements:
1. Symbol and timeframe used for volume composition calculations. By default the chart that is viewed and automatically selected lower timeframe.
2. Dominating volume threshold exceeded. Can be defined via input menu, 70% of total volume by default.
3. Dominating volume as percentage of total volume. Plotted below volume nodes, without % symbol.
4. Dominating active volume, + or - symbol, standing for buy and sell. Plotted below dominating volume percentage. When dominating volume and dominating active volume sides are in a disagreement (e.g. dominating volume is on buy side while dominating active volume is on sell side) this symbol will appear inside brackets, (+) or (-).
5. Dominating active volume as percentage of total active volume. Plotted below +/- symbol.
6. Dominating active volume threshold exceeded. Can be defined via input menu, 70% by default.
Dominating volume & active volume percentages can be rounded to single numbers to avoid clutter caused by overlapping values. The percentage values will be rounded to closest single number value, e.g. dominating volume percentage at 54% = 5, dominating volume percentage at 55% = 6.
Volume anomalies can be highlighted on the chart with a color for studying the events and their past implications in greater detail. Available anomalies for highlights are the following:
Buy volume threshold exceeded
Sell volume threshold exceeded
Active buy volume threshold exceeded
Active sell volume threshold exceeded
Volume & active volume divergence
— Practical guide
Volume is arguably one of the most important data points as it directly relates to liquidity. High volume can be an indication of strength (price likely to continue moving) or absorption (price likely to halt/turn). Same applies to active volume, but with an element of aggression. High active volume serves as an indication of exuberance or otherwise forceful transacting, like stop losses triggering. With these principles in mind, the composition of volume allows distinguishing potentially important events.
Example #1 : Identifying areas of trapped market participants
Often when volume spikes distinctively, we can make the case that price has found sufficient liquidity to halt/turn. Since we know which side was absorbed, in what quantity and type (passive/active), we can identify areas of trapped market participants. In such scenarios, the higher the dominant active volume and volume spike itself, the better.
Example #2 : Identifying a healthy trend
A healthy trend is one that has an active and consistent bid driving it. When this is the case, it can be seen in consistently supportive active volume.
Example #3 : Identifying inflection points
When dominant side of volume and dominant side of active volume diverge, something is up. A divergence often marks an area of indecision, hinting an imminent move one way or the other.
Directional Sentiment LineRepost with explanation and description:
This is a simple SMA based indicator that I have, for lack of a better term, called directional sentiment line.
How it works:
The ribbon/band:
The main band tracks 4 SMAs, the Open, High, Low and Close.
The user can input the length for lookback time, I do 75 and I have it defaulted at 75, however you can do whatever time frame you prefer.
The color of the indicator changes based on the overall trend. Green means an uptrend and red means a downtrend.
When the stock is trading within the band, you generally want to avoid a trend until you see a break out one way or the other. In the image below, you see the green arrow pointing to an area where it re-tests the band but the band remains green to affirm there is support. It then bounces off.
The red arrow, you see that the band is flashing red, meaning that it seems to be losing support and its best to wait for a break out one way or the other prior to taking the trade:
The outer lines:
You will see the two outer bands which generally appear blue while a stock is trading within them.
These are the SMAs of the highest high and lowest low in your defined period (default 75).
They can act as moving targets.
When the colour of one of them changes orange, it means the stock is trading above or below them. If the highest high turns orange, it means the stock is trading high above the bands and highest high SMA. Inverse for the lowest low. See the image below:
The purple arrows are pointing to these max band lines and show how they change colour depending on the location of the highest high.
How to use it:
So I made this simply to give me a reference point for day trades off open. However, looking at the large timeframes, I do see there is quite a lot of potential for larger timeframe analyses as well.
I recommend playing around with it and seeing what you like. But I can give you the rules I use for this as a day trading aid:
My Rules:
1. If stock opens below DSL, wait to see if it will retest. It naturally likes to continually make contact with the DSL line at random intervals:
2. If stock opens above DSL, again wait for re-test:
A hold above DSL = Bullish
A break and hold below DSL = bearish
3. When playing a breakout (sentiment shift from bearish to bullish or vice versa), wait for a retest of the line because frequently, there are fakeouts:
A re-test and bounce off the line confirms a breakout. A re-test and fails confirms a continuation of the predominate sentiment.
For further reference, I have done a tutorial video below:
Let me know your questions, comments and suggestions below!
Thanks!
Bitcoin Miner Extreme SellingThis script is for identifying extreme selling. Judging by the chart, Bitcoin miners often (not always) sell hard for two reasons: to take profit into parabolic price rises, or to stay solvent when the price is very low.
Extreme selling thus often coincides with long-term tops and bottoms in Bitcoin price. This can be a useful EXTRA data point when trying to time long-term Bitcoin spot or crypto equity investment (NOT advice, you remain responsible, etc). The difference between selling measured in BTC and in USD gives a reasonable idea of whether miners are selling to make a profit or to stay solvent.
CREDITS
The idea for using the ratio of miner outflows to reserves comes from the "Bitcoin Miner Sell Pressure" script by the pioneering capriole_charles.
The two request.security calls are identical. Another similarity is that you have to sum the outflows to make it make sense. But it doesn't make much difference, it turns out from testing, to use an average of the reserves, so I didn't. All other code is different.
The script from capriole_charles uses Bollinger bands to highlight periods when sell pressure is high, uses a rolling 30-day sum, and only uses the BTC metrics.
My script uses a configurable 2-6 week rolling sum (there's nothing magical about one month), uses different calculations, and uses BTC, USD, and composite metrics.
INPUTS
Rolling Time Basis : Determines how much data is rolled up. At the lowest level, daily data is too volatile. If you choose, e.g., 1 week, then the indicator displays the relative selling on a weekly basis. Longer time periods, obviously, are smoother but delayed, while shorter time periods are more reactive. There is no "real" time period, only an explicit interpretation.
Show Data > Outflows : Displays the relative selling data, along with a long-term moving average. You might use this option if you want to compare the "real" heights of peaks across history.
Show Data > Delta (the default): Only the difference between the relative selling and the long-term moving average is displayed, along with an average of *that*. This is more signal and less noise.
Base Currency : Configure whether the calculations use BTC or USD as the metric. This setting doesn't use the BTC price at all; it switches the data requested from INTOTHEBLOCK.
If you choose Composite (the default), the script combines BTC and USD together in a relative way (you can't simply add them, as USD is a much bigger absolute value).
In Composite mode, the peaks are coloured red if BTC selling is higher than USD, which usually indicates forced selling, and green if USD is higher, which usually indicates profit-taking. This categorisation is not perfectly accurate but it is interesting insomuch as it is derived from block data and not Bitcoin price.
In BTC or USD mode, a gradient is used to give a rough visual idea of how far from the average the current value is, and to make it look pretty.
USAGE NOTES
Because of the long-term moving averages, the length of the chart does make a difference. I recommend running the script on the longest Bitcoin chart, ticker BLX.
To use it to compare selling with pivots in crypto equities, use a split chart: one BLX with the indicator applied, and one with the equity of your choice. Sync Interval, Crosshair, Time, and Date Range, but not Symbol.
Wavetrend in Dynamic Zones with Kumo Implied VolatilityI was asked to do one of those, so here we go...
As always free and open source as it should be. Do not pay for such indicators!
A WaveTrend Indicator or also widely known as "Market Cipher" is an Indicator that is based on Moving Averages, therefore its an "lagging indicator". Lagging indicators are best used in combination with leading indicators. In this script the "leading indicator" component are Daily, Weekly or Monthly Pivots . These Pivots can be used as dynamic Support and Resistance , Stoploss, Take Profit etc.
This indicator combination is best used in larger timeframes. For lower timeframes you might need to change settings to your liking.
The general Wavetrend settings are the same that are used in Market Cipher, Market Liberator and such popular indicators.
What are these circles?
-These are the WaveTrend Divergences. Red for Regular-Bearish. Orange for Hidden-Bearish. Green for Regular-Bullish. Aqua for Hidden-Bullish.
What are these white, orange and aqua triangles?
-These are the WaveTrend Pivots. A Pivot counter was added. Every time a pivot is lower than the previous one, an orange triangle is printed, every time a pivot is higher than the previous one an aqua triangle is printed. That mimics a very common way Wavetrend is being used for trading when using those other paid Wavetrend indicators.
What are these Orange and Aqua Zones?
-These are Dynamic Zones based on the indicator itself, they offer more information than static zones. Of course static lines are also included and can be adjusted.
What are the lines between the waves?
-This is a Kumo Cloud Implied Volatility indicator. It is color coded and can be used to indicate if a major market move/bottom/top happened.
What are those numbers on the right?
-The first number is a Bollinger Band indicator that shows if said Bollinger Band is in a state of Oversold/Overbought, the second number is the actual Bollinger Band Width that indicates if the Bollinger Band squeezes, normally that happens right before the market makes an explosive move.
Please keep in mind that this indicator is a tool and not a strategy, do not blindly trade signals, do your own research first! Use this indicator in conjunction with other indicators to get multiple confirmations.
Multi Delta-Agnostic Correlation Coefficient (tartigradia)Display three DACC plots simultaneously, to visualize both directional (up on top, down at bottom) and adirectional DACC (in the middle) simultaneously.
Delta Agnostic Correlation calculates a correlation between two symbols based only on the sign of their changes using a Sign Test (en.m.wikipedia.org), regardless of the amplitude of price change. Compared to a standard Pearson correlation (quantitative test), Sign Test correlations (discrete test) are highly sensitive to directional change with 0 lag, at the expense of lacking sensitivity to quantity correlation (ie, it does not matter if changes are big or small).
Hence, this Delta-Agnostic Correlation Coefficient (DCC or DACC) indicator is better used to detect early changes in correlations, and then confirmation with a typical Pearson correlation or a non-parametric Spearman test or Mutual Information (all three are quantitative tests, hence accounting for quantity and not just direction) can allow to be more sensitive to quantities too and hence be a robust combination to demonstrate strong correlations both in direction and amplitude.
Adequate statistical significance testing, using a two-sided binomial statistical test, is also implemented. Note however that one assumption of the sign test may here be violated: independence of observations for each symbol. If you assume the market is not acting on a random walk, then there is a temporal autocorrelation, and this biases the sign test. However, in practice, the test works well enough.
The directional variants of the test allow to test the correlation hypothesis only if the index symbol goes into one direction. For example, if we suspect that the index symbol is correlated with the current symbol but only when the index symbol is bullish, we can select "Up" to test this hypothesis. Note that given the specificities of how directional and adirectional tests differ in how they work, the default fill is different: zero-value fill for adirectional test to simulate how price action tend to lose momentum during market close periods, previous DCC_MA (= no change in DCC value) during both market close periods and when the direction is opposite for the directional variants of the test, so that while the market is moving opposite, we don't lose the statistical significance built up to now, otherwise it would be nonsensical (for the directional tests).
For more information on the theory behind, see the original DACC indicator, which is the same script but with only one plot:
Candlestick - Kicker PatternNot many candlestick patterns hurt traders on the other side of the trade more than this signal, when it happens, think of it as kicking in the teeth, the pain is real.
An upwards signal is painted when you have a two-bar formation, the one on the left is a bearish one whereas the successive one is bullish, when you have fat bodies in both candles, meaning the open is close to the high and the close is close to the low for the first candle, while the open is close to the low and the close is close to the high for the adjacent candle, the pain is ever more excruciating, the other important condition is the open of the first candle must be lower than the open of the latter one.
The downwards signal is vice versa of the upwards signal.
Volume Profile Volume Delta OI Delta [Kioseff Trading]Hello!
This script serves to distinguish volume delta for any asset and open interest delta for Binance perpetual futures.
The image above provides further explanation of functionality and color correspondence.
The image above shows the indicator calculating volume at each tick level and displaying the metric.
The label color outline (neon effect) is configurable; the image above is absent the feature.
The image above shows Open Interest (OI) Delta calculated - similar to how the script calculates volume delta - for a Binance Perpetual Future pair.
This feature only works for Binance Futures pairs; the script will not load when trying to calculate OI Delta on other assets.
Additionally, a heatmap is displayable should you configure the indicator to calculate it.
The image above shows a heatmap using volume delta calculations.
The image above shows a heatmap using OI delta calculations.
Of course, these calculations - when absent requisite data - require some assumptions to better replicate calculations with access to requisite data.
The indicator assumes a 60/40 split when a tick level is traded at and only one metric - "buy volume" or "sell volume" is recorded. This means there shouldn't be any levels recorded where "buy volume" is greater than 0 and "sell volume" equals 0 and vice versa. While this assumption was performed arbitrarily, it may help better replicate volume delta and OI delta calculations seen on other charting platforms.
This option is configurable; you can select to have the script not assume a 60/40 split and instead record volume "as is" at the corresponding tick level.
The script also divides volume and open interest if a one-minute bar violates multiple tick levels. The volume or open interest generated on the one-minute bar will be divided by the number of tick levels it exceeds. The results are, subsequently, appended to the violated tick levels.
Further, the script can be set to recalculate after a user-defined time threshold is exceeded. You can also define the percentage or tick distance between levels.
Also, it'd be great if this indicator can nicely replicate volume delta indicators on other charting platforms. If you've any ideas on how price action can be used to better assume volume at the corresponding price area please let me know!
Thank you (:
Minervini QualifierThe Minervini Qualifier indicator calculates the qualifying conditions from Mark Minervini’s book “Trade like a Stock Market Wizard”.
The condition matching is been shown as fill color inside an SMA 20day envelope curve.
If the envelope color is red, current close price is below the SMA20 and when blue, current close price is above the SMA20. The fill color can be transparent (not matching qualifying conditions), yellow (matching all conditions except close is still below SMA50), green (all conditions match, SMA200 trending for at least one month up) or blue (all conditions match, SMA200 trending up for at least 5 months)
As I wanted also to see which of the qualifying conditions match over time, I’ve added add. lines, each representing one conditions. If it matches, line color is blue, or red if not. Use the data windows (right side), so you know what line represents which condition. Can be turned on/off (default:on)
In addition, a relative strength is been calculated, to compare the stock to a reference index. It is just one possible way to calculate it, might be different to what Mark Minervini is using. If the shown value (top right) is above 100, stock performs better compared to reference index (can be set in settings), when below 100, stock performs worse compared to reference index. Can be turned on/off (default:on)
How to use it:
For more details, read Mark’s book and watch his videos.
Limitations:
It gives only useful information on daily timeframe
(No financial advise, for testing purposes only)
REVE MarkersREVE stands for ‘Range Extensions Volume Expansions’. It seeks to report the same as the REVE which I published before. However the code uses a different algorithm to find the ‘usual range’ or ‘usual volume’ to which the current range and volume is compared. In the old REVE a function is coded which mimics a median() function..
In this code the median() function provided in pinescript is used, which makes the code of the actual algorithm nice and short in lines 21 through 27
For example line 23: “morevol=ta.median(curvol , usual)*eventnorm” in which
‘morevol ‘ is the calculated level above which the volume is deemed considerable,
‘curvol’ is the current volume (see line 21); curvol the volume of the previous period.
‘usual’ is the lookback period (see line 8)
‘ta.median(curvol , usual)’ is therfore the median volume in the lookback period
‘eventnorm’ is the percent which sets when “normal” becomes “considerable” (see line 6)
In line 26 the same is done for range.
The code in lines 30 to 92, concern logic manipulations to arrive at choosing the appropriate marker, which are plotted in lines 95 through 136.
Using the shapes as provided by Pinescript offers the possibility to give a much better and more meaningful visualization of volume and range events than different colored columns and histograms in the ‘old’ REVE in the below panel (see example chart).
Using the Pinescript function to find the median opens the possibility of letting the user play in the inputs with the lookback period and the norms for considerable and excessive to find a setting he or she likes most.
Using median in stead of average is necessary in volume and range analysis because these are so volatile. E.g. range or volume can be 10 times larger in the next period! If you have a few excessive volumes or ranges in the lookback period the ‘average volume or range’ is much higher than the ‘usual volume or range’ In statistics this is referred to as the outlier problem.
The markers are located on the bottom of the instrument pane. Those indicating volume events (with ‘event’ I mean a considerable or excessive expansion or extension) are colored triangles or squares, triangles indicate direction, squares that the price stays the same. those indicating range events with ‘normal’ volume are crosses, plus-cross means considerable range event and x-cross is excessive event.
The red, fuchsia and maroon triangles and squares indicate a combination of volume and range events. I call this ‘effective volume’ because more trade leads to shifting prices. The green and blue triangles and squares indicate a volume event with ‘normal’ ranges. I call this ‘ineffective volume’ because more volume does not lead to price shits. Effective volume can be attributed to occasional traders, because these do not care much for the price effect of their orders. The ineffective volume is attributable to institutional traders, because these go to great length to hide the size of their selling or buying objective by trading many small amounts in a day. Therefore one can theorize that ‘smart money’ is active when green and blue markers show up.
There is an option in the inputs to show markers around the candles (or bars). Those above indicate volume events, plus-cross for considerable and x-cross for excessive volume.
Those below the candles (or bars) indicate range events, triangles for direction or a plus-cross when the price stays the same. The small ones indicate considerable range events and the big ones excessive range events. This option can be used for better understanding of the colors of the bottom markers or to check which marker applies to which candle or bar.
If the instrument is without volume, the indicator will show only range markers.
Have fun and take care.
Time & volume point of control / quantifytoolsWhat are TPOC & VPOC?
TPOC (time point of control) and VPOC (volume point of control) are points in price where highest amount of time/volume was traded. This is considered key information in a market profile, as it shows where market participant interest was highest. Unlike full fledged market profile that shows total time/volume distribution, this script shows the points of control for each candle, plotted with a line (time) and a dot (volume). The script hides your candles/bars by default and forms a line in the middle representing candle range. In case of candles, borders will still be visible. This feature can be turned off in the settings.
Volume and time data are fetched from a lower timeframe that is automatically adjusted to fit the timeframe you're using. By default, the following settings are applied:
Charts <= 30 min: 1 minute timeframe
Charts > 30 min & <= 3 hours : 5 minute timeframe
Charts > 3 hours & <= 8 hours : 15 minute timeframe
Charts > 8 hours & <= 1D: 1 hour timeframe
Charts > 1D & <= 3D : 2 hour timeframe
Charts > 3D: 4 hour timeframe
Timeframe settings can be changed via input menu. The lower the timeframe, the more precision you get but with the cost of less historical data and slower loading time. Users can also choose which source to use for determining price for points of control, e.g. using close as source, the point of control is set to match the value of lower timeframe candle close. This could be replaced with OHLC4 for example, resulting in a point of control based on OHLC average.
To identify more profound points of market participant interest, TPOC & VPOC as percentage of total time/volume thresholds can be set via input menu. When a point of control is equal to or greater than the set percentage threshold, visual elements will be highlighted in a different color, e.g. 50% VPOC threshold will activate a highlight whenever volume traded at VPOC is equal to or greater than 50% of total volume. All colors are customizable.
VPOC is defined by fetching lower timeframe candle with the most amount of volume traded and using its close (by default) as a mark for point of control. For TPOC, each candle is divided into 10 lots which are used for calculating amount of closes taking place within the bracket values. The lot with highest amount of closes will be considered a point of control. This mark is displayed in the middle point of a lot:
How to utilize TPOC & VPOC
Example #1: Trapped market participants
One or both points of control at one end of candle range (wick tail) and candle close at the other end serves as an indication of market participants trapped in an awkward position. When price runs away further from these trapped participants, they are eventually forced to cover and drive price even further to the opposite direction:
Example #2: Trend initiation
A large move that leaves TPOC behind while VPOC is supportive serves as an indication of a trend initiation. Essentially, this is one way to identify an event where price traded sideways most of the time and suddenly moved away with volume:
Example #3: POC supported trend
A trend is healthy when it's supported by a point of control. Ideally you want to see either time or volume supporting a trend:
VOLQ Sigma TableThis indicator replaces the implied volatility of VOLQ with the daily volatility and reflects that value into the price on the NDX chart to create the VOLQ standard deviation table.
It will only be useful for stocks related to the Nasdaq Index.
For example, NDX, QQQ or so.
And we want to predict the range of weekly fluctuations by plotting those values as a line in the future.
It is expressed as High 2σ by adding the standard deviation 2 sigma value of the VOLQ value from last week's closing price.
It is expressed as High 1σ by adding the standard deviation 1 sigma value of the VOLQ value from last week's closing price.
It is expressed as Low 1σ by subtracting the standard deviation 1 sigma value of the VOLQ value from the closing price of the previous week.
It is expressed as Low 2σ by subtracting the standard deviation 2 sigma value of the VOLQ value from last week's closing price.
1day predicts daily fluctuations.
2day predicts 2-day fluctuations.
3day predicts 3-day fluctuations.
4day predicts 4-day fluctuations.
5day predicts 5-day fluctuations.
In the settings you can select the start date to display the VOLQ line via input.
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What motivated me to create this indicator?
From my point of view, the reason for classifying vix volq historical volatility (realized volatility) is that the most important point is that VIXX and VolQ are calculated from implied volatility. It can be standardized as one-month volatility. There are many strike prices, but exchanges use the implied volatility of options traded on their own exchanges.
Because historical volatility depends on how the period is set, to compare with VIXX, we compare it with a month, that is, 20 business days. One-month implied volatility means (actually different depending on the strike price), because option traders expect that the one-month volatility will be this much, and it is the volatility created by volatility trading.
So we see it as the volatility expected by derivatives traders, especially volatility traders.
I'm trying to infer what the market thinks will fluctuate this much from the numbers generated there.
Volume Buoyancy [LucF]█ OVERVIEW
This indicator uses simple analysis of past volume to determine how well it supports recent market activity. What I call Volume buoyancy measures the strength and direction of that support.
█ CONCEPTS
Buoyancy
In physics, buoyancy is the force described in Archemedes' principle :
Any object, wholly or partially immersed in a fluid, is buoyed up by a force equal to the weight of the fluid displaced by the object.
I use the term loosely in this indicator's context, as "Volume buoyancy" here can be directed either up or down, indicating that past volume displays a bullish or bearish bias.
The calculation of buoyancy begins from a target quantity of volume summed over n bars. We then search chart bars backward, adding the volume of up and down bars in two different slots until each slot reaches the target. We then calculate two average distances: one each for the up and down bars whose volume was summed to reach the target. These average distances are then subtracted and the difference is divided by the farthest distance we had to go to find the target in either up or down bars. The last part of the calculations looks like this:
(avgDistanceDn - avgDistanceUp) / barsAnalyzed
When the average distance of down bars is greater than that of up bars, buoyancy will be positive, indicating that past activity favors the upside and vice versa. The force's strength, which in the case of actual buoyancy is the weight of the displaced fluid, in our case is measured by the size of the gap between the average distance of up vs down bars in relation to the farthest distance we had to go in the past. Buoyancy is always between +1 and -1, with values higher/lower than 0.3/-0.3 typically being unsustainable.
█ HOW TO USE THE INDICATOR
Load the indicator on an active chart (see here if you don't know how).
The default configuration displays:
• Buoyancy as a monochrome gray line.
• A channel between buoyancy and its MA, colored in one of four colors. The MA is not plotted by default, but you can see where it is with the channel.
The default settings use an Arnaud Legoux moving average over 20 bars.
• A fill between the MA and the centerline, which can be one of two colors.
• A high level at 0.30, a low level at -0.30 and the centerline at zero.
The default target is the sum of volume in the last 20 bars.
█ FEATURES
The indicator's settings allow you to define:
• A higher timeframe you want the calculations to be made on. Note that you should then ensure your chart's timeframe is always lower than the higher timeframe you specified,
as calculating on a timeframe lower than the chart's does not make much sense because the indicator is then displaying only the value of the last intrabar in the chart bar.
• The number of bars for which to add volume to obtain the target value that will be searched for in past up and down bars.
• The display of the buoyancy and MA lines, the channel between them and the fill between the MA line and the centerline.
• The type and length of the MA.
Using the "Style" tab of the indicator's settings, you can change the type and width of the lines, and the level values.
█ INTERPRETATION
Buoyancy shares the properties and shortcomings of many oscillators:
• It tends to be noisy, which is why the MA line can be helpful.
• The safest way to use it may be as a rough sentiment indicator, i.e., by paying more attention to its bull/bear state above/below the centerline.
• The more intrepid traders will want to use the channel between the main line and the MA, as it will provide earlier information than main line crosses of the centerline.
Decreasing the number of bars for which the source is added to calculate the target value will increase the noise level, somewhat like decreasing an MA's length would, but keep in mind that the number of bars is not the length of an MA.
█ LIMITATIONS
Under some circumstances, the indicator will display zero values because it cannot find the target in past bars. This will happen at the beginning of the dataset when not enough past bars have elapsed, or in the rarer cases anywhere in the dataset, when the target cannot be found in the `MAX_BARS_BACK` number of bars defined in the first line of the indicator's code (the default is 1000).
The calculations use a very primitive interpretation of volume similar to that of OBV , where all the volume of a bar is attributed to either the up or down slot. The indicator nonetheless produces results I think can be useful because we are not so much calculating precise buying/selling pressure as trying to build a big picture of where past activity over many bars appears to be taking price.
Volume data is notoriously high-variance; large values that come into or exit the calculations' scope can produce sudden variations in results, somewhat like the drop-off effect in moving averages.
█ NOTES
• The script can be used with any chart timeframe, including seconds.
• Historical values will always produce the same results. In real time, values will change until the bar closes.
[Floride] 4 Layers of Bollinger Shadow
This is the indicator I named 4LBS. That means four layers of bollinger shadow.
This is an indicator that I made to see how far past prices could affect the future prices.
And I found some very interesting and beautiful things about it, and I wanted to share them with you, so I publish this indicator.
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Hello, nice to meet you all. my name as a trader is Floride.
First of all, I am not good at English, so there may be many grammatically incorrect sentences below.
I ask for your understanding in advance. Thanks for your understanding.
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What is it?
bollinger Bands usually has one moving average line. And there's two bands that uses same period value of standard deviation as the former MA. And this indicator, by the way, has a 4 shadow bands
that uses twice,three,four,five time the value of the MA's period.
Appearance -
This indicator has four layers, and there are also other layers between them.
You can turn on or off all the shadow layers.
Uses of Indicator and Examples
examples of actual use
1. market strongness diagnosis
-It seems all layers of shadow has some degree resist/support forces.
This indicator has the 4th layer - "L4". (indicated by red lines).
I saw emergence of volatility quite frequently when this last layer breaks through.
When price breaks through this area or line, shade appear on the L4 layer in red. and red cross appear on the that point. This is I called Marlin signal.
If you saw red color shadow in this indicator, then the market may have quite high volatility.
(of course, there's not 100%. Please be careful about this.)
But I've also checked in quite several markets. when this volatility emerges, then also that market seems to started to building quite directional power afterwards.
I mean, after the marlin signal, market tends to have bigger volatility, and tends to go one direction.
again, it's not 100%. but probability is quite high.
But maybe depending on the type of market you need some adjustment.
Recommended values are M2-1.618, M3-2.618
Or M2-1, M3-2. default value is M2-1.618, M3-2.618
and also, if prices breakthrough the channels, or layers, It tends to break through the at once, in first bar. In other words, if price don't break through the first or second candle, it's very likely that the price won't break through channel for the time being.
2. market weakness diagnosis
Usually, without external momentum, the price converges to the average value and does not deviate from the band. And if price fails to break through the most inner first layer-"L1 - the green channel", In that case, the market is usually assumed to be weak, or has low volatility.
- you can set alarms on tuna, marlin signal. and you don't have to watch chart all the time.
3. Signals
I put two signals in this indicator.
One has the name "Tuna," and the second has the name "Marlin."
As you can already tell from the name's feeling, tuna is a weaker signal and marlin is a stronger signal.
Actual example of a signal
1. Tuna signal
- When the tuna signal appears, you can guess that the current market is generally not weak. or has quite good directional force. or medium volatility.
Below is important.
- If a tuna signal appears, there is a possibility that a marlin will appear later.
- In my opinion, it might be wise not to have a position without a tuna signal.
- Almost all of the marlin signal appeared shortly after the tuna signal appeared.
2. Marlin signal
- When marlin signal appears, with a high probability, volatility can increase large.
- In the backtesting of the stock, in some cases, the market moved quite frequently in the direction of the marlin signal.
- The emergence of marlin can be seen as a pretty strong indication of the emergences of direction.
Sector RotationThis script is attempt to create and observe the real-time and historical performance of the all major sectors of Indian Market in one screen.
for Data Presentation I used Short sector names so that I can manage to get space and efficient presentable data.
Short Names and Actual Sector Names
BNF : CNX-BANKNIFTY
IT : CNX-IT
PRMA : CNX - PHARMA
FMCG : CNX-FMCG
AUTO : CNX-AUTO
MTAL : CNX-METAL
MDIA : CNX-MEDIA
RLTY : CNX-REALTY
IFRA : CNX-INFRA
ENGY : CNX-ENERGY
PSU-B : CNX-PSU-BANK
PVT-B : NIFTY-PVT-BANK
F-SRV : CNX-FINANCE
CONSM : CNX-CONSUMPTION
C-DUBL : NIFTY_CONSR_DURBL
You can use this script in 30-min, Daily, Weekly and Monthly Time Frames.
The green Square denotes the current Symbol Performance.
The Blue Border boxes are created when one sector intersects other sector.
In this Update following features are added
Now users have control over sectors, what are all the sectors you wanted to plot you can select from the input menu.
Currently user can highlight any one sector in different border color so that user can easily spot and track particular sector.
This thicker blue line denotes lowest and highest point of the current timeframe.
