Elder Impulse System + ATR BandsDisregard the above chart, I am not sure why it isn't showing the one I want, which is linked below:
This is as far as I can tell the closest representation to Dr. Alexander Elder's updated "Elder Impulse System" that has added ATR-volatility bands up to 3x deviations from price. I got the idea from watching this recent video (www.youtube.com) of Dr. Elder reviewing some recent trades and noticed he had updated his system from his original books. The Impulse System colour coding was inspired by AstralLoverFlow and LazyBear. ATR Bands are pre-programmed Keltner Channels with some modifications such as filing in the ATR Zones with user-selected colour bands and modifying the ATR value to better suit the volatility of the market being traded.
The script has several components, which I will detail below:
Exponential Moving Averages:
1) A 13-period EMA that is used as a staple in all of Dr. Elder's technical analysis. He uses this EMA as the basis for all of his indicators and why it is included here.
2) A 26-period EMA which can be used as a base-line of sorts to filter when to go long or when to go short. For instance, price over the 26-EMA, price is strong and the rally upwards is likely to continue, underneath it, price is weak and likely to continue downwards for a time.
Volatility Bands:
By definition these are nothing more than 3 separate Keltner Channels of a 13-period EMA each set to one additional multiplier from the moving average. This gives us a 1x, 2x, and 3x multiplier of average volatility from the 13-period EMA based on a 14-period Average True Range (ATR) reading. The ATR was chosen as it accommodates price gaps and also is the standard formula calculation in TradingView. The values of the bands cannot be adjusted but the colour coding of them can be.
Elder Impulse System:
These colour-coded bars show you the strength and direction of the current chart resolution, calculated by the slope of a 13-period EMA and the slope of a MACD histogram. These are used not as a buying or selling recommendation alone but as trend filters, as per Dr. Elder's own description of them.
Green Bars = The 13-period EMA is sloping positively and the MACD histogram is rising compared to previous bars. The trader should only consider buying/long opportunities when a green bar is most recent.
Red Bars = The 13-period EMA is sloping negatively and the MACD histogram is falling compared to previous bars. The trader should only consider selling/short opportunities when a red bar is most recent.
Blue Bars = The 13-period EMA and the MACD histogram are not aligned. One of the indicators is sloping opposite to the other indicator. These are known as indecision bars and are typically seen near the end of a previously established trend. The trader can choose to wait for either a green or red bar to shape their trading bias if they are more risk-averse while a counter-trend trader may decide to try opening a position against the currently-established trend.
How To Trade the System:
This system is unique in that it is so versatile and will fit the styles of many traders, be it trend following traders (generally the original Elder Impulse System design) or mean-reversion/counter-trend trading (the original Keltner Channel design). None of the examples below or in the chart above are financial advice and are just there for demonstration purposes only.
1) The most basic signal given would be the moving average cross up or down. A cross of the 13-EMA over the 26-EMA signals upward trend strength and the trader could look for buying opportunities. Conversely, the 13-EMA under the 26-EMA shows downward trend strength and the trader could look for selling opportunities.
2) Following the Elder Impulse system in conjunction with the EMAs. Look for long opportunities when a green bar is printed and price is over both of the 13- and 26-period EMAs. Look for short opportunities when a red bar is printed and price is below both of the 13- and 26-period EMAs. Keep in mind this does not necessarily need a moving average cross to be viable, a green or red bar over both EMAs is a valid signal in this system, usually. Examine price more closely for better entry signals when a blue bar is printed and price is either above or below both EMAs if you are a trend trader. This is how Dr. Elder originally intended the system to be used in conjunction with his famous Triple Screen Trading System. I am not going into detail here as it is a deep subject but I would suggest an interested trader to examine this Triple Screen System further as it is widely accepted as a strong strategy.
3) Mean Reversion and Counter-Trend Trading. Dr. Elder mentions that the zone between the two EMAs is called the Value Zone. A mean reversion trader could look for buying opportunities if price has generally been in an uptrend and falls back to value, conversely, they could look for shorting opportunities if price has generally been in a downtrend and rises back to value. These are your very basic pull backs found in trends that create your higher lows in an uptrend or your lower highs in a downtrend. A mean reversion/scalper trader may also look to use the upper and lower most ATR bands as an indication of price being overbought or oversold and could look to enter a counter-trend trade here once a blue indecision bar is printed and to ride that move back down to the Value Zone.
Taking Profits and Risk Management
This system again is very versatile and will fit a wide range of trading styles. It has built in take profit levels and risk management depending on your style of trading.
1a) In original Triple Screen Trading (and the original Elder Impulse system), a trader was to place a buy order one tick above a newly printed green bar with a stop loss one tick below the most recent 2-day low, and vice-versa for red bars on short selling. as long as other criteria were met, that I will not go into. It is all over YouTube and in his books and on Investopedia if you want more information. The general idea is to continue the trend in the direction if price is strong and you are bought into that move with a close stop, or if price falls back a little bit, you can get in at a better price. This would be a system typically better suited to a scalper.
1b) The updated risk management according to the above video is to place a stop loss at least 2ATR away from price. These bands already have calculated these values so a trader can place a stop one tick below the 2 or even 3ATR zones depending on their risk appetite. This is assuming you have already received a strong buy signal based on the system you follow. This would be a system typically better suited to a trend-trader.
2a) Taking profits if you are a trend trader has several possibilities. The first, as Dr. Elder suggests, is to place a price target 2ATR values away from your entry giving you approximately a 1:1 risk-reward ratio.
2b) The second possibility if the trade is successful is to ride the trend upwards until a blue bar is printed, suggesting indecision in the market. A modified version of this that could let a winning trade run longer is to wait for the price to close under the 13-EMA in fast markets, or close under the 26-EMA in slightly slower markets to maximize potential winnings.
2c) A scalper trader may wish to have a target at either the value zone if they are playing an extended buy/short back to the mean, or if they are being at the mean, to sell or cover when price extends back out to the 2x or 3x zone.
3) Trend traders can additionally use the ATR zones as a sort of safety guidelines for entering a trade. Anything within the 1ATR zone is typically a safer entry as the market is less volatile at this time. Entering when price has gone into the 2ATR zone is signaled as a strong momentum move and can signal a stronger move in the direction of the current closing bar. While not always the case, it is suggested by Dr. Elder to not enter trend trades at the 3ATR zone as this is where you will be likely looking for a counter-trend retracement back to value and a trader entering here in the direction of the trade has a higher chance of being stopped out or not getting in at the best possible price.
Pesquisar nos scripts por "one一季度财报"
AB=CD Pattern Educational (Source Code)This indicator was intended as educational purpose only for AB=CD Patterns.
AB=CD Patterns were explained and modernized starting from The Harmonic Trader and Harmonic Trading: Volume One until Volume Three written by Scott M Carney.
Indikator ini bertujuan sebagai pendidikan sahaja untuk AB=CD Pattern.
AB=CD Patterns telah diterangkan dan dimodenkan bermula dari The Harmonic Trader dan Harmonic Trading: Volume One hingga Volume Three ditulis oleh Scott M Carney.
Indicator features :
1. List AB=CD patterns including ratio and reference page.
2. For desktop display only, not for mobile.
Kemampuan indikator :
1. Senarai AB=CD pattern termasuk ratio and rujukan muka surat.
2. Untuk paparan desktop sahaja, bukan untuk mobile.
FAQ
1. Credits / Kredit
Scott M Carney
Scott M Carney, Harmonic Trading: Volume One until Volume Three
2. Pattern and Chapter involved / Pattern dan Bab terlibat
Ideal AB=CD - The Harmonic Trader - Page 118 & 129
Standard AB=CD - The Harmonic Trader - Page 116, 117, 127 & 128, Harmonic Trading: Volume One - Page 42, 51, Harmonic Trading: Volume Three - Page 76 & 78
Alternate AB=CD - The Harmonic Trader - Page 142 & 145, Harmonic Trading: Volume One - Page 62, 63
Perfect AB=CD - Harmonic Trading: Volume One - Page 64 & 66
Reciprocal AB=CD - Harmonic Trading: Volume Two - Page 74 & 76
AB=CD with ab=cd - The Harmonic Trader - Page 149 & 153
AB=CD with BC Layering Technique - Harmonic Trading: Volume Three - Page 81 & 84
3. Code Usage / Penggunaan Kod
Free to use for personal usage but credits are most welcomed especially for credits to Scott M Carney.
Bebas untuk kegunaan peribadi tetapi kredit adalah amat dialu-alukan terutamanya kredit kepada Scott M Carney.
Bullish / Bearish Ideal AB=CD
Bullish / Bearish Standard AB=CD
Bullish / Bearish Alternate AB=CD
Bullish / Bearish Perfect AB=CD
Bullish / Bearish Reciprocal AB=CD (Additional value for reciprocal retracement 3.140 and 3.618)
Bullish / Bearish AB=CD with ab=cd
Bullish / Bearish AB=CD with BC Layering Technique
72s Strat: Backtesting Adaptive HMA+ pt.1This is a follow up to my previous publication of Adaptive HMA+ few months ago, as a mean to provide some kind of initial backtesting tools. Which can be use to explore many possible strategies, optimise its settings to better conform user's pair/tf, and hopefully able to help tweaking your general strategy.
If you haven't read the study or use the indicator, kindly go here first to get the overall idea.
The first strategy introduce in this backtest is one most basic already described in the study; buy/sell is when movement is there and everything is on the right side; When RSI has turned to other side, we can use it as exit point (if in profit of course, else just let it hit our TP/SL, why would we exit before profit). Also, base on RSI when we make entry, we can further differentiate type of signals. --Please check all comments in code directly where the signals , entries , and exits section are.
Second additional strategy to check; is when we also use second faster Adaptive HMA+ for exit. So this is like a double orders on a signal but with different exit-rule (/more on this on snapshots below). Alternatively, you can also work the code so to only use this type of exit.
There's also an additional feature which you can enable its visuals, the Distance Zone , is to help measuring price distance to our xHMA+. It's just a simple atr based envelope really, I already put the sample code in study's comment section, but better gonna update it there directly for non-coder too, after this.
In this sample I use Lot for order quantity size just because that's what I use on my broker. Also what few friends use while we forward-testing it since the study is published, so we also checked/compared each profit/loss report by real number. To use default or other unit of measurement, change the entry code accordingly.
If you change your order size, you should also change the commission in Properties Tab. My broker commission is 5 USD per order/lot, so in there with example order size 0.1 lot I put commission 0.5$ per order (I'll put 2.5$ for 0.5 lot, 10$ for 2 lot, and so on). Crypto usually has higher charge. --It is important that you should fill it base on your broker.
SETTINGS
I'm trying to keep it short. Please explore it further again. (Beginner should also first get acquaintance with terms use here.)
ORDERS:
Base Minimum Profit Before Exit:
The number is multiplier of ongoing ATR. Means that when basic exit condition is met, algo will check whether you're already in minimum profit or not, if not, let it still run to TP or SL, or until it meets subsequent exit condition, then it will check again.
Default Target Profit:
Multiplier of ATR at signal. If reached before any eligible exit condition is met, exit TP.
Base StopLoss Point:
You can change directly in code to use other like ATR Trailing SL, fix percent SL, or whatever. In the sample, 4 options provided.
Maximum StopLoss:
This is like a safety-net, that if at some point your chosen SL point from input above happens to be exceeding this maximum input that you can tolerate, then this max point is the one will be use as SL.
Activate 2nd order...:
The additional doubling of certain buy/sell with different exits as described above. If enable, you should also set pyramiding to at least: 2. If not, it does nothing.
ADAPTIVE HMA+ PERIOD
Many users already have their own settings for these. So in here I only sample the default as first presented in the study. Make it to your adaptive.
MARKET MOVEMENT
(1) Now you can check in realtime how much slope degree is best to define your specific pair/tf is out of congestion (yellow) area. And (2) also able to check directly what ATR lengths are more suitable defining your pair's volatility.
DISTANCE ZONE
Distance Multiplier. Each pair/tf has its own best distance zone (in xHMA+ perspective). The zone also determine whether a signal should appear or not. (Or what type of signal, if you wanna go more detail in constructing your strategy)
USAGE
(Provided you already have your own comfortable settings for minimum-maximum period of Adaptive HMA+. Best if you already have backtested it manually too and/or apply as an add-on to your working strategy)
1. In our experiences, first most important to define is both elements in the Market Movement Settings . These also tend to be persistent for whole season since it's kinda describing that pair/tf overall behaviour. Don't worry if you still get a low Profit Factor here, but by tweaking you should start to see positive changes in one of Max Drawdown and Net Profit, or Percent Profitable.
2. Afterwards, find your pair/tf Distance Zone . When optimising this, what we seek is just a "not to bad" equity curves to start forming. At least Max Drawdown should lessen more. Doesn't have to be great already, but should be better, no red in Net Profit.
3. Then go manage the "Trailing Minimum Profit", TP, SL, and max SL.
4. Repeat 1,2,3. 👻
5. Manage order size, commission, and/or enable double-order (need pyramiding) if you like. Check if your equity can handle max drawdown before margin call.
6. After getting an acceptable backtest result, go to List of Trades tab and find the biggest loss or when many sequencing loss in a row happened. Click on it to go to exact point on chart, observe why the signal failed and get at least general idea how it can be prevented . The rest is yours, you should know your pair/tf more than other.
You can also re-explore your minimum-maximum period for both Major and minor xHMA+.
Keep in mind that all numbers in Setting are conceptually in a form of range . You don't want to get superb equity curves but actually a "fragile" , means one can easily turn it to disaster just by changing only a fraction in one/two of the setting.
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If you just wanna test the strength of the indicator alone, you can disable "Use StopLoss" temporarily while optimising settings.
Using no SL might be tempting in overall result data in some cases, but NOTE: It is not recommended to not using SL, don't forget that we deliberately enter when it's in high volatility. If want to add flexibility or trading for long-term, just maximise your SL. ie.: chose SL Point>ATR only and set it maximum. (Check your max drawdown after this).
I think this is quite important specially for beginners, so here's an example; Hypothetically in below scenario, because of some settings, the buy order after the loss sell signal didn't appear. Let's say if our initial capital only 1000$ using leverage and order size 0,5 lot (risky position sizing already), moreover if this happens at the beginning of your trading season, that's half of account gone already in one trade . Your max SL should've made you exit after that pumping bar.
The Trailing Minimum Profit is actually look like this. Search in the code if you want to plot it. I just don't like too many lines on chart.
To maximise profit we can try enabling double-order. The only added rule coded is: RSI should rising when buy and falling when sell. 2nd signal will appears above or below default buy/sell signal. (Of course it's also prone to double-loss, re-check your max drawdown after. Profit factor play its part in here for a long run). Snapshot in comparison:
Two default sell signals on left closed at RSI exit, the additional sell signal closed later on when price crossover minor xHMA+. On buy side, price haven't met our minimum profit when first crossunder minor xHMA+. If later on we hit SL on this "+buy" signal, at least we already profited from default buy signal. You can also consider/treat this as multiple TP points.
For longer-term trading, what you need to maximise is the Minimum Profit , so it won't exit whenever an exit condition happened, it can happen several times before reaching minimum profit. Hopefully this snapshot can explain:
Notice in comparison default sell and buy signal now close in average after 3 days. What's best is when we also have confirmation from higher TF. It's like targeting higher TF by entering from smaller TF.
As also mention in the study, we can still experiment via original HMA by putting same value for minimum-maximum period setting. This is experimental EU 1H with Major xHMA+: 144-144, Flat market 13, Distance multiplier 3.6, with 2nd order activated.
Kiwi was a bit surprising for me. It's flat market is effectively below 6, with quite far distance zone of 3.5. Probably because I'm using big numbers in adaptive period.
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The result you see in strategy tester report below for EURUSD 15m is using just default settings you see in code, as follow:
0,1 lot for each order (which is the smallest allowed by my broker).
No pyramiding. Commission: 0.5 usd per order. Slippage: 3
Opening position is only using basic strategy #1 (RSI exit). Additional exit not activated.
Minimum Profit: 1. TP: 3.
SL use: Half-distance zone. Max SL: 4.5.
Major xHMA+: 172-233. minor xHMA+: 89-121
Distance Zone Multiplier: 2.7
RSI: Standard 14.
(From our forward-testing, the difference we get from net profit is because of the spread, our entry isn't exactly at the close/open price. Not so much though, but not the same. If somebody can direct me to any example where we can code our entry via current bid/ask price, that would be awesome!)
It's already a long post (sorry), think I'm gonna pause here. Check out the code :)
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DISCLAIMER: Past performance is no guarantee of future results , and so on.. you know the drill ;)
Please read whole description first before using, don't take 1-2 paragraph and claim it's the whole logic, you are responsible of your own actions and understanding.
+ BB %B: MA selection, bar coloring, multi-timeframe, and alerts+ %B is, at its simplest, the classic Bollinger Bands %B indicator with a few added bells and whistles.
However, the right combination of bells and whistles will often improve and make a more adaptable indicator.
Classically, Bollinger Bands %B is an indicator that measures volatility, and the momentum and strength of a trend, and/or price movements.
It shows "overbought" and "oversold" spots on a chart, and is also useful for identifying divergences between price and trend (similar to RSI).
With + %B I've added the options to select one or two moving averages, candle coloring, and a host of others.
Let's start with the moving averages:
There are options for two: one faster and one slower. Or combine them how you will, or omit one or both of them entirely.
Here you will find options for SMA, EMA (as well as double and triple), Hull MA, Jurik MA, Least Squares MA, Triangular MA, Volatility Adjusted MA, and Weighted MA.
A moving average essentially helps to define trend by smoothing the noise of movements of the underlying asset, or, in this case, the output of the indicator.
All of these MAs available track this in a different way, and it's up to the trader to figure out which makes most sense to him/her.
MA's, in my opinion, improve the basic %B by providing a clearer picture of what the indicator is actually "seeing", and may be useful for providing entries and exits.
Next up is candle coloring:
I've added the option for this indicator to color candles on the chart based on where the %B is in relation to its upper and lower bounds, and median line.
If the %B is above the median but below the upper bound, candles will be green (showing bullish market structure). If %B is below the median but above the lower bound, candles will be red (denoting bearish market structure).
Overbought and oversold candles will also be colored on the chart, so that a quick glance will tell you whether price action is bullish/bearish or "oversold"/"overbought".
I've also added functionality that enables candles to be colored based on if the %B has crossed up or crossed down the primary moving average.
One example as a way to potentially use these features is if the candles are showing oversold coloration followed by the %B crossing up your moving average coloration. You might consider a long there (or exit a short position if you are short).
And the last couple of tweaks:
You may set the timeframe to whatever you wish, so maybe you're trading on the hourly, but you want to know where the %B is on the 4h chart. You can do that.
The background fill for the indicator is split into bullish and bearish halves. Obviously you may turn the background off, or make it all one color as well.
I've also added alerts, so you may set alerts for "overbought" and "oversold" conditions.
You may also set alerts for %B crossing over or under the primary moving average, or for crossing the median line.
All of these things may be turned on and off. You can pretty much customize this to your heart's delight. I see no reason why anyone would use the standard %B after playing with this.
I am no coder. I had this idea in my head, though, and I made it happen through referencing another indicator I was familiar with, and watching tutorials on YouTube.
Credits:
Firstly, thanks to www.tradingview.com for his brilliant, free tutorials on YouTube.
Secondly, thanks to www.tradingview.com for his beautiful SSL Hybrid indicator (and his clean code) from which I obtained the MAs.
Please enjoy this indicator, and I hope that it serves you well. :)
Uber Stochastic Index v2 + HistogramRealized how useful a histogram could be for a Stochastic, so I added it to my Uber Stochastic. It actually has two histograms - one on the primary stochastic, and one on a stochastic of the stochastic. So you can histogram while you histogram and stoch while you stoch.
The second stoch is actually really useful sometimes as a early warning but can get ugly on some settings. The histograms are also quite fast on fast settings.
What separates the Uber from the standard stoch? Well, you get 7 K stochastics, technically, to weigh together into one. Looks like one, but I assure you its 7 complete stochastics. You can have a long term stochastic with short term influence or a short term with long term influence, or have one thats all-encompassing.
Why histograms? Stochastic is already read similar to MACD, with crossover signals derived from two lines reflected in one another, one slower then the other. It just makes sense. This way, with a slower running histogram, you can more readily "see" it close in. After all, the best trades are rarely made when the stochastic crosses, but rather as it approaches crossing.
I included a lot of settings for max tweaking. The histograms seem to shift in size considerably depending how you have it set, hence the resolution settings for each. I actually recommend setting the 2nd histogram to inverted resolution, that way you can see them more clearly, but you will also see them on both sides of 0.
And yes, I offset the stochastic so the histogram would look right.
"Wealth beyond measure, Outlander" -Unknown Dunmer
ACD - Layers 1 & 2An implementation of layers 1 & 2 of ACD strategy of Mark Fisher, based on the book "The Logical Trader".
This implementation contains:
- OR lines
- A lines
- C lines
- Daily pivot range
- N days pivot range
- Customizable trading session
Strategy summary (This implementation):
There is 3 main concepts, each of which represented as two price levels.
1) OR (Opening Range) is the range of the first bar of the day. In other words, it's just "high - low" of the first resolution (usually 15min.) bar of the day. So, OR lines (Aqua color) visualize this range for each trading session.
As stated by Mark Fisher in his book, this range is meant to be a statistically significant range such that when price breaks the range in one direction, This is UNUSUAL to infiltrate it again AND break through the other side. So we can consider it as a potential enter signal (long or short).
2) A lines (Blue color) are drawn above and below OR lines with difference of 10% 0f 10 days ATR. The ATR period and the A multiplier (usually 10%) is customizable.
3) C lines (Gray color) are drawn above and below OR lines at 15% of 10 Days ATR difference. These lines help detecting AND confirming that UNUSUAL situation.
These concepts form the layer 1, which you can spot potential opportunities with it.
There is also two ranges to show support and resistance levels based on price action of previous days. Pivot ranges are rolling ranges that calculated and last for each day separately. They only differ in calculation period - the first one is daily (yellow color area) and the other one (red color area) is customizable, but is usually 3 or 5 days.
Each range consists of two price levels, valid for the current trading session. One of theme is HL2 , and the other one is "HLC3 + abs(HLC3 - HL2 )".
These two ranges, "Daily pivot range" and "N days pivot range", form the layer 2, which you can see them as two dynamic support/resistance ranges - one for daily, and the other for N days. They help filtering opportunities spotted from layer 1.
There is 2 more layers in the ACD strategy, which is omitted in this free implementation.
Trend Reversal Indicator (EMA of slopes)Good morning Traders
Inspirated by lukescream EMA-slope strategy, today I want to share with you this simple indicator whose possible use-case would be for detecting in advance possible trend reversals, specially on higher timeframes.
Once that you've chosen the desired source (RSI, EMA or Stochastic k or d), the indicator will calculate its "slope" approximating its first order derivative by the division between the last variation of the series and its last value.
You can see the slope as a white line by enabling the relative checkmark (it's disabled by default since it simply messes up the the graph)
Then, the slope itself becomes the source for two exponential moving averages: the fast one (in blue) has a period of 20 while the slow one (in red, it becomes similiar to a horizontal line actually) has a period of 500
Why the slope? Since all the sources mentioned before are directly or indirectly calculated on the price action, a more aggressiveness in the price movement would be translated into a more (positive/negative) steepness of those indicator (of course this effect would be far more evident if the indicators are calculated on low periods, but really low periods could compromise the consistency of the signals).
In this way, the slope would mirror the decisiveness of price movements and a comparison between two averages calculated from it (the first one based on more recent values, the second one that conisders also older values) could tell you in advance what direction the market is possibly about to take
The usage is simple: once that the fast moving average crosses upward the slow one, this could be a sign of potential trend reversal from bearish to bullish. On the contrary, if the fast EMA crosses downward the slow one, this could be a sign of potential trend reversal from bullish to bearish.
What I suggest you is to integrate this indicator with Exponential Moving Averages plotted on the price candles, in order to have a general bias for opening long or short positions, and with an oscillator as well such as the Stochastisc RSI in order to detect the overbought/oversold zones for opening/closing positions at the right moment.
Happy Trading!
|AG| Previous Analysis█ OVERVIEW
Analysis of previous levels is one of the best strategies in order to get good entries or take profits levels. This analysis involves Monthly and Weekly Previous Levels and One User Definition Option. So u could select any period like Daily or even hours according to ur trading style. The previous levels are High and Low. And the Current (NOT PREVIOUS) open level.
This script also includes one Fibonacci Selector that will calculate the Fibbo level between previous High and Low Levels of the user selection. Almost everything could be modified in the input panel.
Input Options
A detailed explanation of input settings:
• # Of Previous
• This option leads us to select the number of previous weeks, months, or the user selection back.
• Example: If we select Previous High, Low WEEKLY so if # Of previous is one is going to be the past levels but if is 2 so consequently 2 previous levels.
• In the case of 0 is going to be the actual levels
• Fibbo & Label Selector
Here we can select the period.
• Monthly, Weekly, And User Definition is available.
• Fibonacci Selector :
• Here we could choose between different levels of Fibonacci or No_Plot Option
• Label Offset
• Here we select the amount of distance between label and actual price
• Time Start
• Here we could highlight one period START and END like one Week start day and end day.
• User Definition Value in order to be more flexible.
Interesting Code Lines:
• Fibonacci function
getFib(a, b)=>
fib1 = a + (b - a) * -0.618
fib2 = a + (b - a) * -0.270
fib3 = a + (b - a) * 0.114
fib4 = a + (b - a) * 0.214
fib5 = a + (b - a) * 0.382
fib6 = a + (b - a) * 0.500
fib7 = a + (b - a) * 0.618
fib8 = a + (b - a) * 0.786
fib9 = a + (b - a) * 0.886
ext_ = a + (b - a) * 1.270
ext1 = a + (b - a) * 1.618
• Exact Distance and % Distance
f_dist (_src, _src3) =>
float _dist = _src3 - _src
float _perc = _dist / _src3 //* 100
Difference over barsDescription:
One of my followers asked about an indicator that shows the difference between the open and a previous close and didn't find one so I wrote this one. This is similar to a momentum indicator except it offers more flexibility. While the standard momentum indicator calculates a difference between current close and a previous close (sometimes customizable to work on open, high or lows instead of close), this allows to mix and match between open, high, low and close. It also offers multiple kinds of moving averages.
Settings:
Current point of reference
Previous point of reference
Difference over how many bars?
How it works:
The indicator calculates the difference between the current point of reference and a previous (n-bars back) point of reference (where n is given by the "Difference over how many bars?").
How to use it:
find historical support lines like the 0.68 line in the cart above where in the past the indicator tends to bounce back; similarly find resistance lines like the -0.75 line in the chart (which servers as a resistance line both for the main indicator line and its moving average )
look for convergence between the price and the indicator; for example, if the price is going up and the indicator is going down a change in the price direction may be coming soon
look for the indicator crossing its moving average: moving up will signify an up trend and vice-versa
since the difference between the open and previous close (which is what the blue line in the chart shows) since to go up to 0.68 (the upper horizontal line) and down to -0.75 (the lower horizontal line) most of the time, one strategy, using options, is to to buy, right before the close of a trading day, a "long iron butterfly": buy-to-open (BTO) both a call and a put at the strike price and sell-to-open (STO) a call at a strike of around $0.68 more and sell to open a put at a strike of around $0.75 less. The STO legs should be for the next expiration and the BTO legs for the next expiration after that. This way the STO will decrease their time value faster than the BTO legs if the price stays flat (which plays to your advantage) and the BTO legs may make profit if the next day it opens away from the price at which the ticker closed the previous day (when the position was opened). The most profit is when it moves right up to one of the STO legs. This position would normally be closed next day at opening. The percentage of profit it makes is low compared to other strategies but also the percentage of the total cost at risk is also low which could potentially allow a trader to increase the lot and thus, in the end, the total profit amount may be comparable to other strategies.
Notes:
The indicator in the chart above comes with the standard options. For a more standard momentum indicator set both the current and previous reference point to the same OHLC value (such as "close").
The 0.68 and -0.75 levels are for open/close (current/previous point of reference) for ticker INTC. Obviously, other tickers will likely have other levels and you will have to find those yourself. If you use INTC but use other combination of current and previous reference points, they will have different levels as well.
Percent Calculator (Return On Investment Target Price)First and foremost: I was inspired to publish my first script after reading some of the other member's scripts -a token of my appreciation and support, Thank You.
The percent calculator is a very simple and basic indicator to use, it''s function is to simply output the target price from either the close or ones trade-entry based on a desired percent return on investment (R.O.I.).
Say you want to profit 15% from your entry: simply plug in your entry value and the number 15 into the appropriate settings and the indicator displays what the target price should be (rounded to two decimal places).
The percent calculator also goes one step further by finding the average percent return on investment over a desired interval of time (the default is 20 candles) as well as allows one to adjust the size of the price move the average percent return on investment is being calculated for.
Say you want to find the average percent return on investment for a 3 candle swing over a 200 candle interval of time: simply plug the number 200 into the interval setting and the number 3 into the price-move setting and the indicator displays what the average 3 candle swing returns on investment.
Practical Application: comparing ones desired return on investment to the average return on investment can help determine how realistic ones goals are... it's unlikely to achieve 100% return on investment if the average is only around 10% (given the parameters one is working within) but on the other hand achieving 5% return on investment is highly likely.
SIMPLE MOVING AVG 10,20,50,100,200 with RESOLUTIONThis indicator is the best than all other sma indicators.Because in just one click you can change all the resolution /time frames for all the sma .
Multitime frame analysis can be done in just one click. just change the resolution to
15 min/30 min/1hr- if you intraday trader
1D- LONG TERM INVESTORS.
Multi-timeframe analysis (MTF) is a process in which traders can view the same ticker/indicator using a higher time frame than the chart’s, for example, displaying a daily moving average on a one-hour chart in just two clicks.
How to Use this to Buy Stocks ?
The technical indicator known as the Death cross occurs when the 50-day SMA crosses below the 200-day SMA => Bearish Signal.
An opposite indicator, known as the Golden cross, occurs when the 50-day SMA crosses above the 200-day SMA => Bullish Signal.
Crossovers are one of the main moving average strategies.
1st Strategy is the first type is a price crossover, which is when the price crosses above the sma => Buy signal
when the price crosses below the sma => Sell signal
2nd Strategy is to apply two moving averages to a chart: one longer and one shorter.
When the shorter-term MA (100) crosses above the longer-term MA (200), it's a buy signal, indicates trend is shifting up.
This is known as a "Golden cross."
Meanwhile, when the shorter-term MA (100) crosses below the longer-term MA (200), it's a sell signal, indicates trend is shifting down.
This is known as a "Dead/death cross."
The time frame or length you choose for a moving average, also called the "look back period," can play a big role in how effective it is.
An MA with a short time frame will react much quicker to price changes than an MA with a long look back period. In the figure below, the 20-day moving average more closely tracks the actual price than the 100-day moving average does.
A 20-day MA = more beneficial to a shorter-term trader, since it follows the price more closely.
A 100-day MA = more beneficial to a longer-term trader.
Moving averages work quite well in strong trending conditions but poorly in choppy or ranging conditions.
use this indicator along with Price action theory and not alone.
Moving average crossovers are a popular strategy for both entries and exits. MAs can also highlight areas of potential support or resistance
Happy Trading
Bitcoin Margin Call Envelopes [saraphig & alexgrover]Bitcoin is the most well known digital currency, and allow two parties to make a transaction without the need of a central entity, this is why cryptocurrencies are said to be decentralized, there is no central unit in the transaction network, this can be achieved thanks to cryptography. Bitcoin is also the most traded cryptocurrency and has the largest market capitalization, this make it one of the most liquid cryptocurrency.
There has been tons of academic research studying the profitability of Bitcoin as well as its role as a safe heaven asset, with all giving mixed conclusions, some says that Bitcoin is to risky to be considered as an hedging instrument while others highlight similarities between Bitcoin and gold thus showing evidence on the usefulness of Bitcoin acting as an hedging instrument. Yet Bitcoin seems to attract more short term speculative investors rather than other ones that would use Bitcoin as an hedging instrument.
Once introduced, cryptocurrencies where of course heavily analyzed by technical analyst, and technical indicators where used by retail as well as institutional investors in order to forecast the future trends of bitcoin. I never really liked the idea of designing indicators that specifically worked for only one type of market and ever less on only one symbol. Yet the user @saraphig posted in Feb 20 an indicator called " Margin Call MovingAverage " who calculate liquidation price by using a volume weighted moving average. It took my attention and we decided to work together on a relatively more complete version that would include resistances levels.
I believe the proposed indicator might result useful to some users, the code also show a way to restrict the use of an indicator to only one symbol (line 9 to 16).
The Indicator
The indicator only work on BTCUSD, if you use another symbol you should see the following message:
The indicator plot 6 extremities, with 3 upper (resistance) extremities and 3 lower (support) extremities, each one based on the isolated margin mode liquidation price formula:
UPlp = MA/Leverage × (Leverage+1-(Leverage*0.005))
for upper extremities and:
DNlp = MA × Leverage/(Leverage+1-(Leverage*0.005))
for lower extremities.
Length control the period of the moving averages, with higher values of length increasing the probability of the price crossing an extremity. The Leverage's settings control how far away their associated extremities are from the price, with lower values of Leverage making the extremity farther away from the price, Leverage 3 control Up3 and Dn3, Leverage 2 control Up2 and Dn2, Leverage 1 control Up1 and Dn1, @saraphig recommend values for Leverage of either : 25, 20, 15, 10 ,5.
You can select 3 different types of moving average, the default moving average is the volume weighted moving average (VWMA), you can also choose a simple moving average (SMA) and the Kaufman adaptive moving average (KAMA).
Based on my understanding (which could be wrong) the original indicator aim to highlight points where margin calls might have occurred, hence the name of the indicator.
If you want a more "DSP" like description then i would say that each extremity represent a low-pass filter with a passband greater than 1 for upper extremities and lower than 1 for lower extremities, unlike bands indicators made by adding/subtracting a volatility indicator from another moving average this allow to conserve the original shape of the moving average, the downside of it being the inability to show properly on different scales.
here length = 200, on a 1h tf, each extremities are able to detect short-terms tops and bottoms. The extremity become wider when using lower time-frames.
You would then need to increase the Leverages settings, i recommend a time frame of 1h.
Conclusion
I'am not comfortable enough to make a conclusion, as i don't know the indicator that well, however i liked the original indicator posted by @saraphig and was curious about the idea behind it, studying the effect of margin calls on market liquidity as well as making indicators based on it might result a source of inspiration for other traders.
A big thanks to @saraphig who shared a lot of information about the original indicator and allowed me to post this one. I don't exclude working with him/her in the future, i invite you to follow him/her:
www.tradingview.com
Thx for reading and have a nice weekend! :3
Extended Recursive Bands - Maximum Efficiency With Extra OptionsIntroducing A New Calculation For Efficient Bands Calculation !
Here it is ! 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 my paper "Pierrefeu, Alex (2019): Recursive Bands - A New Indicator For Technical Analysis" , the indicator framework has been widely used in my 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".
On The Indicator Calculation
You can skip this part if it doesn't interest you. The calculation of the indicator is based on recursion, but i want to explain the mathematical formula described in the paper.
I've seen some users trying to remake it from the calculations, however there was always something weird, and i understand, mathematical notations are always a bit weird, even myself don't always write them correctly/understand them, however this one is relatively simple to understand.
First lets explain each elements of the calculation :
α = smoothing constant, or 2/(length+1)
max/min = maximum and minimum function, max return the greatest input value while min return the lowest one, for example :
max(4,2) = 4 while min(4,2) = 2
the "||" notation mean taking the absolute value, for example : |-1| = abs(-1) = 1
The calculation after the max/min function is called the correction factor, and is the core of the indicator. The last two variables are just here to provide an initial value for upper and lower, basically when we start our calculations we will assign the value of the closing price for upper and lower.
The motivation behind using a smoothing constant in range of (0,1) was to tell the reader that the indicator is easily made adaptive, this is what i did on my adaptive trailing stop indicator by using the efficiency ratio as smoothing variable, the user can use 1/length instead of the provided calculation for alpha.
If you interested on the indicator main logic, it is actually really simple, by using upper = max(price,upper) and lower = min(price,lower) we would get the maximum/minimum price value at time t , therefore upper can only be greater or equal than its precedent value, while lower can only be lower or equal than its precedent value, in order to fix that we subtract/sum upper/lower with a value, this allow the upper band to be lower than its precedent value and lower to be greater than its precedent value, this is the role of the correction factor.
The Indicator
The indicator display 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 control how reactive the bands are, higher values of length will make the bands cross the price less often.
In order to provide more flexibility for the user i 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.
Classic Method
This option make the indicator use its classical calculation, this is the most efficient method of all.
Atr Method (atr)
This method use the average true range as correction factor, notice that lower values of length can still produce wide band.
Standard Deviation Method (stdev)
This method use a biased estimate of the standard deviation as correction factor.
The method produce smoother bands that converge more slowly toward the price in comparison with the classic correction factor.
Average High-Low Range Method (ahlr)
This method use the average of the high-low range as correction factor, extremely similar to the average true range.
Rising Falling Volatility (rfv) Method
A new method created for this indicator, this correction factor use the absolute prices changes when price value is greater/lower than any length past values of the price, this allow to have more boxy shaped bands, work best with greater values of length.
The bands can be in contact with this method, a possible fix in the future.
Conclusion
The recursive band indicator is one of my greatest indicators in my opinion (i would love to have yours), as you can see the idea behind it is extremely simple and allow for a super efficient band indicator, which was the original motivation behind it, in order to provide more fun for the users i also added more option for the correction factor, this allow the user to be creative and not get stuck with the original calculation.
Like the trend step indicator family we have almost ended our series on the recursive band framework, 1 more trailing stop will be added in the future, and then we'll have more "boring" stuff until i find something cool again, it shouldn't be long ;)
Thanks for reading !
How to avoid repainting when using security() - PineCoders FAQNOTE
The non-repainting technique in this publication that relies on bar states is now deprecated, as we have identified inconsistencies that undermine its credibility as a universal solution. The outputs that use the technique are still available for reference in this publication. However, we do not endorse its usage. See this publication for more information about the current best practices for requesting HTF data and why they work.
This indicator shows how to avoid repainting when using the security() function to retrieve information from higher timeframes.
What do we mean by repainting?
Repainting is used to describe three different things, in what we’ve seen in TV members comments on indicators:
1. An indicator showing results that change during the realtime bar, whether the script is using the security() function or not, e.g., a Buy signal that goes on and then off, or a plot that changes values.
2. An indicator that uses future data not yet available on historical bars.
3. An indicator that uses a negative offset= parameter when plotting in order to plot information on past bars.
The repainting types we will be discussing here are the first two types, as the third one is intentional—sometimes even intentionally misleading when unscrupulous script writers want their strategy to look better than it is.
Let’s be clear about one thing: repainting is not caused by a bug ; it is caused by the different context between historical bars and the realtime bar, and script coders or users not taking the necessary precautions to prevent it.
Why should repainting be avoided?
Repainting matters because it affects the behavior of Pine scripts in the realtime bar, where the action happens and counts, because that is when traders (or our systems) take decisions where odds must be in our favor.
Repainting also matters because if you test a strategy on historical bars using only OHLC values, and then run that same code on the realtime bar with more than OHLC information, scripts not properly written or misconfigured alerts will alter the strategy’s behavior. At that point, you will not be running the same strategy you tested, and this invalidates your test results , which were run while not having the additional price information that is available in the realtime bar.
The realtime bar on your charts is only one bar, but it is a very important bar. Coding proper strategies and indicators on TV requires that you understand the variations in script behavior and how information available to the script varies between when the script is running on historical and realtime bars.
How does repainting occur?
Repainting happens because of something all traders instinctively crave: more information. Contrary to trader lure, more information is not always better. In the realtime bar, all TV indicators (a.k.a. studies ) execute every time price changes (i.e. every tick ). TV strategies will also behave the same way if they use the calc_on_every_tick = true parameter in their strategy() declaration statement (the parameter’s default value is false ). Pine coders must decide if they want their code to use the realtime price information as it comes in, or wait for the realtime bar to close before using the same OHLC values for that bar that would be used on historical bars.
Strategy modelers often assume that using realtime price information as it comes in the realtime bar will always improve their results. This is incorrect. More information does not necessarily improve performance because it almost always entails more noise. The extra information may or may not improve results; one cannot know until the code is run in realtime for enough time to provide data that can be analyzed and from which somewhat reliable conclusions can be derived. In any case, as was stated before, it is critical to understand that if your strategy is taking decisions on realtime tick data, you are NOT running the same strategy you tested on historical bars with OHLC values only.
How do we avoid repainting?
It comes down to using reliable information and properly configuring alerts, if you use them. Here are the main considerations:
1. If your code is using security() calls, use the syntax we propose to obtain reliable data from higher timeframes.
2. If your script is a strategy, do not use the calc_on_every_tick = true parameter unless your strategy uses previous bar information to calculate.
3. If your script is a study and is using current timeframe information that is compared to values obtained from a higher timeframe, even if you can rely on reliable higher timeframe information because you are correctly using the security() function, you still need to ensure the realtime bar’s information you use (a cross of current close over a higher timeframe MA, for example) is consistent with your backtest methodology, i.e. that your script calculates on the close of the realtime bar. If your system is using alerts, the simplest solution is to configure alerts to trigger Once Per Bar Close . If you are not using alerts, the best solution is to use information from the preceding bar. When using previous bar information, alerts can be configured to trigger Once Per Bar safely.
What does this indicator do?
It shows results for 9 different ways of using the security() function and illustrates the simplest and most effective way to avoid repainting, i.e. using security() as in the example above. To show the indicator’s lines the most clearly, price on the chart is shown with a black line rather than candlesticks. This indicator also shows how misusing security() produces repainting. All combinations of using a 0 or 1 offset to reference the series used in the security() , as well as all combinations of values for the gaps= and lookahead= parameters are shown.
The close in the call labeled “BEST” means that once security has reached the upper timeframe (1 day in our case), it will fetch the previous day’s value.
The gaps= parameter is not specified as it is off by default and that is what we need. This ensures that the value returned by security() will not contain na values on any of our chart’s bars.
The lookahead security() to use the last available value for the higher timeframe bar we are using (the previous day, in our case). This ensures that security() will return the value at the end of the higher timeframe, even if it has not occurred yet. In our case, this has no negative impact since we are requesting the previous day’s value, with has already closed.
The indicator’s Settings/Inputs allow you to set:
- The higher timeframe security() calls will use
- The source security() calls will use
- If you want identifying labels printed on the lines that have no gaps (the lines containing gaps are plotted using very thick lines that appear as horizontal blocks of one bar in length)
For the lines to be plotted, you need to be on a smaller timeframe than the one used for the security() calls.
Comments in the code explain what’s going on.
Look first. Then leap.
Triple Kijun Trend by SpiralmanIspired from "Oscars Simple Trend Ichimoku Kijun-sen" by CapnOscar
Script displays 3 kijun lines: one for current TF, second one emulates it for TF 4 times higher, third one for x16.
For example on 1H chart there will be 3 kijuns: one for 1H, second one for 4H (emulated), third one for 16H (emulated).
Kijuns change colors based on their position relative to price.
Kijun Sen
The base line, the slower EMA derivative, and a dynamic representation of the mean. With that said, the Kijun serves as both critical support and resistance levels for price. How does it work, and why would the Kijun be superior to commonly used moving average indicators? Fun fact: The Kijun dynamically equalizes itself to be the 50% retracement (or 0.5 Fibonacci level) of price for any given swing, and price will ALWAYS gravitate to the Kijun at some point regardless of how far above or below it is from it. By taking the median of price extremes, the Kijun accounts for volatility that other MAs or EMAs do not. A flat horizontal Kijun means that price extremes have not changed, and that the current trend losing momentum. Crypto-adjusted calculation: (highest high + lowest low) / 2 calculated over the last 60 periods.
Back to zero: Understanding seriestype: pine series basic example
time required: 10 minutes
level: medium (need to know the "array" data variable as a generic programming concept, basic Pine syntax)
tl;dr how variables and series work in Pine
Pine is an array/vector language. That's something that twists how it behaves, and how we have to think about it. A lot of misunderstandings come from forgetting this fact. This example tries to clear that concept.
First, you need to know what an array is, and how it works in a programmig language. Also, having javascript under your belt helps too. If you don't, google "javascript array basic tutorial" is your friend :)
So, in pine arrays are called "series". Every variable is an array with values for each candle in the chart. if we do:
myVar = true
this is not a constant. It is a series of values for each candle, { true, true,....., true }
In practice, the result is the same, but we can access each of the values in the series, like myVar{0}, myVar{7}, myVar{anyNumber}....
Again, it is not a constant, since you can access/modify the each value individually
so, lets show it:
plot (myVar, clolor = gray)
this plots an horizontal line of value 1 ( 1 is equal to true ) so it's all good.
On to a more usual series:
tipicalSeries = close > open ? true : false
plot(tipicalSeries, color= blue)
This gives the expected result, a tipical up and down line with values at 1 or 0. Naturally, "tipicalSeries" is an array, the "ups" and "downs" are all stored under the same variable, indexed by the candles.
In Pine, the ZERO position in the array is the last one, which corresponds to the last candle on the right. Say you have a chart with 12 candles. The close would be the closing value of what we intuitively think as first candle, the one on the left. then close ... and so on.... until close , the value of the "last" candle, the one on the right. It actually helps to start thinking of the positions backwards, counting down to zero, rocket launch style :)
And back to our series. The myVar will also be the same size, from myVar to myVar .
When we do some operation with them, something simple like
if ( myVar == tipicalSeries)
what is really happening is that internally, Pine is checking each of the indexes, as in myVar == tipicalSeries , myVar == tipicalSeries .... myVar == tipicalSeries
And we can store that stuff to check it. simply:
result = (myVar == tipicalSeries) ? true : false //yes, this is the same as tipicalSeries, but we're not in a boolean logic tut ;)
plot (result)
The reason we can plot the result is that it is an array, not a single value. The example indicator i provide shows a plot where the values are obtained from different places in the array, this line here:
mySeries3 = mySeries2 and mySeries1
this creates a series that is the result of the PREVIOUS values stored (the zero index is the one most at the right, or the "current" one), which here just causes a shift in the plotted line by one candle.
Go ahead, grab a copy of my code, try to change the indexes and see the results. Understanding this stuff is critical to go deeper into Pine :)
ADX Forecast Colorful [DiFlip]ADX Forecast Colorful
Introducing one of the most advanced ADX indicators available — a fully customizable analytical tool that integrates forward-looking forecasting capabilities. ADX Forecast Colorful is a scientific evolution of the classic ADX, designed to anticipate future trend strength using linear regression. Instead of merely reacting to historical data, this indicator projects the future behavior of the ADX, giving traders a strategic edge in trend analysis.
⯁ Real-Time ADX Forecasting
For the first time, a public ADX indicator incorporates linear regression (least squares method) to forecast the future behavior of ADX. This breakthrough approach enables traders to anticipate trend strength changes based on historical momentum. By applying linear regression to the ADX, the indicator plots a projected trendline n periods ahead — helping users make more accurate and timely trading decisions.
⯁ Highly Customizable
The indicator adapts seamlessly to any trading style. It offers a total of 26 long entry conditions and 26 short entry conditions, making it one of the most configurable ADX tools on TradingView. Each condition is fully adjustable, enabling the creation of statistical, quantitative, and automated strategies. You maintain full control over the signals to align perfectly with your system.
⯁ Innovative and Science-Based
This is the first public ADX indicator to apply least-squares predictive modeling to ADX dynamics. Technically, it embeds machine learning logic into a traditional trend-strength indicator. Using linear regression as a predictive engine adds powerful statistical rigor to the ADX, turning it into an intelligent, forward-looking signal generator.
⯁ Scientific Foundation: Linear Regression
Linear regression is a fundamental method in statistics and machine learning used to model the relationship between a dependent variable y and one or more independent variables x. The basic formula for simple linear regression is:
y = β₀ + β₁x + ε
Where:
y = predicted value (e.g., future ADX)
x = explanatory variable (e.g., bar index or time)
β₀ = intercept
β₁ = slope (rate of change)
ε = random error term
The goal is to estimate β₀ and β₁ by minimizing the sum of squared errors. This is achieved using the least squares method, ensuring the best linear fit to historical data. Once the coefficients are calculated, the model extends the regression line forward, generating the ADX projection based on recent trends.
⯁ Least Squares Estimation
To minimize the error, the regression coefficients are calculated as:
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
Σ = summation
x̄ and ȳ = means of x and y
i ranges from 1 to n (number of data points)
These formulas provide the best linear unbiased estimator under Gauss-Markov conditions — assuming constant variance and linearity.
⯁ Linear Regression in Machine Learning
Linear regression is a foundational algorithm in supervised learning. Its power in producing quantitative predictions makes it essential in AI systems, predictive analytics, time-series forecasting, and automated trading. Applying it to the ADX essentially places an intelligent forecasting engine inside a classic trend tool.
⯁ Visual Interpretation
Imagine an ADX time series like this:
Time →
ADX →
The regression line smooths these values and projects them n periods forward, creating a predictive trajectory. This forecasted ADX line can intersect with the actual ADX, offering smarter buy and sell signals.
⯁ Summary of Scientific Concepts
Linear Regression: Models variable relationships with a straight line.
Least Squares: Minimizes prediction errors for best fit.
Time-Series Forecasting: Predicts future values using historical data.
Supervised Learning: Trains models to predict outcomes from inputs.
Statistical Smoothing: Reduces noise and highlights underlying trends.
⯁ Why This Indicator Is Revolutionary
Scientifically grounded: Based on rigorous statistical theory.
Unprecedented: First public ADX using least-squares forecast modeling.
Smart: Uses machine learning logic.
Forward-Looking: Generates predictive, not just reactive, signals.
Customizable: Flexible for any strategy or timeframe.
⯁ Conclusion
By merging ADX and linear regression, this indicator enables traders to predict market momentum rather than merely follow it. ADX Forecast Colorful is not just another indicator — it’s a scientific leap forward in technical analysis. With 26 fully configurable entry conditions and smart forecasting, this open-source tool is built for creating cutting-edge quantitative strategies.
⯁ Example of simple linear regression with one independent variable
This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables.
⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x)
This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component.
⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab
Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models.
⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted
This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model.
⯁ Result of fitting a set of data points with a quadratic function
This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line.
⯁ What is the ADX?
The Average Directional Index (ADX) is a technical analysis indicator developed by J. Welles Wilder. It measures the strength of a trend in a market, regardless of whether the trend is up or down.
The ADX is an integral part of the Directional Movement System, which also includes the Plus Directional Indicator (+DI) and the Minus Directional Indicator (-DI). By combining these components, the ADX provides a comprehensive view of market trend strength.
⯁ How to use the ADX?
The ADX is calculated based on the moving average of the price range expansion over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and has three main zones:
Strong Trend: When the ADX is above 25, indicating a strong trend.
Weak Trend: When the ADX is below 20, indicating a weak or non-existent trend.
Neutral Zone: Between 20 and 25, where the trend strength is unclear.
⯁ Entry Conditions
Each condition below is fully configurable and can be combined to build precise trading logic.
📈 BUY
🅰️ Signal Validity: The signal will remain valid for X bars .
🅰️ Signal Sequence: Configurable as AND or OR .
🅰️ +DI > -DI
🅰️ +DI < -DI
🅰️ +DI > ADX
🅰️ +DI < ADX
🅰️ -DI > ADX
🅰️ -DI < ADX
🅰️ ADX > Threshold
🅰️ ADX < Threshold
🅰️ +DI > Threshold
🅰️ +DI < Threshold
🅰️ -DI > Threshold
🅰️ -DI < Threshold
🅰️ +DI (Crossover) -DI
🅰️ +DI (Crossunder) -DI
🅰️ +DI (Crossover) ADX
🅰️ +DI (Crossunder) ADX
🅰️ +DI (Crossover) Threshold
🅰️ +DI (Crossunder) Threshold
🅰️ -DI (Crossover) ADX
🅰️ -DI (Crossunder) ADX
🅰️ -DI (Crossover) Threshold
🅰️ -DI (Crossunder) Threshold
🔮 +DI (Crossover) -DI Forecast
🔮 +DI (Crossunder) -DI Forecast
🔮 ADX (Crossover) +DI Forecast
🔮 ADX (Crossunder) +DI Forecast
📉 SELL
🅰️ Signal Validity: The signal will remain valid for X bars .
🅰️ Signal Sequence: Configurable as AND or OR .
🅰️ +DI > -DI
🅰️ +DI < -DI
🅰️ +DI > ADX
🅰️ +DI < ADX
🅰️ -DI > ADX
🅰️ -DI < ADX
🅰️ ADX > Threshold
🅰️ ADX < Threshold
🅰️ +DI > Threshold
🅰️ +DI < Threshold
🅰️ -DI > Threshold
🅰️ -DI < Threshold
🅰️ +DI (Crossover) -DI
🅰️ +DI (Crossunder) -DI
🅰️ +DI (Crossover) ADX
🅰️ +DI (Crossunder) ADX
🅰️ +DI (Crossover) Threshold
🅰️ +DI (Crossunder) Threshold
🅰️ -DI (Crossover) ADX
🅰️ -DI (Crossunder) ADX
🅰️ -DI (Crossover) Threshold
🅰️ -DI (Crossunder) Threshold
🔮 +DI (Crossover) -DI Forecast
🔮 +DI (Crossunder) -DI Forecast
🔮 ADX (Crossover) +DI Forecast
🔮 ADX (Crossunder) +DI Forecast
🤖 Automation
All BUY and SELL conditions are compatible with TradingView alerts, making them ideal for fully or semi-automated systems.
⯁ Unique Features
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
Third eye • StrategyThird eye • Strategy – User Guide
1. Idea & Concept
Third eye • Strategy combines three things into one system:
Ichimoku Cloud – to define market regime and support/resistance.
Moving Average (trend filter) – to trade only in the dominant direction.
CCI (Commodity Channel Index) – to generate precise entry signals on momentum breakouts.
The script is a strategy, not an indicator: it can backtest entries, exits, SL, TP and BreakEven logic automatically.
2. Indicators Used
2.1 Ichimoku
Standard Ichimoku settings (by default 9/26/52/26) are used:
Conversion Line (Tenkan-sen)
Base Line (Kijun-sen)
Leading Span A & B (Kumo Cloud)
Lagging Span is calculated but hidden from the chart (for visual simplicity).
From the cloud we derive:
kumoTop – top of the cloud under current price.
kumoBottom – bottom of the cloud under current price.
Flags:
is_above_kumo – price above the cloud.
is_below_kumo – price below the cloud.
is_in_kumo – price inside the cloud.
These conditions are used as trend / regime filters and for stop-loss & trailing stops.
2.2 Moving Average
You can optionally display and use a trend MA:
Types: SMA, EMA, DEMA, WMA
Length: configurable (default 200)
Source: default close
Filter idea:
If MA Direction Filter is ON:
When Close > MA → strategy allows only Long signals.
When Close < MA → strategy allows only Short signals.
The MA is plotted on the chart (if enabled).
2.3 CCI & Panel
The CCI (Commodity Channel Index) is used for entry timing:
CCI length and source are configurable (default length 20, source hlc3).
Two thresholds:
CCI Upper Threshold (Long) – default +100
CCI Lower Threshold (Short) – default –100
Signals:
Long signal:
CCI crosses up through the upper threshold
cci_val < upper_threshold and cci_val > upper_threshold
Short signal:
CCI crosses down through the lower threshold
cci_val > lower_threshold and cci_val < lower_threshold
There is a panel (table) in the bottom-right corner:
Shows current CCI value.
Shows filter status as colored dots:
Green = filter enabled and passed.
Red = filter enabled and blocking trades.
Gray = filter is disabled.
Filters shown in the panel:
Ichimoku Cloud filter (Long/Short)
Ichimoku Lines filter (Conversion/Base vs Cloud)
MA Direction filter
3. Filters & Trade Direction
All filters can be turned ON/OFF independently.
3.1 Ichimoku Cloud Filter
Purpose: trade only when price is clearly above or below the Kumo.
Long Cloud Filter (Use Ichimoku Cloud Filter) – when enabled:
Long trades only if close > cloud top.
Short Cloud Filter – when enabled:
Short trades only if close < cloud bottom.
If the cloud filter is disabled, this condition is ignored.
3.2 Ichimoku Lines Above/Below Cloud
Purpose: stronger trend confirmation: Ichimoku lines should also be on the “correct” side of the cloud.
Long Lines Filter:
Long allowed only if Conversion Line and Base Line are both above the cloud.
Short Lines Filter:
Short allowed only if both lines are below the cloud.
If this filter is OFF, the conditions are not checked.
3.3 MA Direction Filter
As described above:
When ON:
Close > MA → only Longs.
Close < MA → only Shorts.
4. Anti-Re-Entry Logic (Cloud Touch Reset)
The strategy uses internal flags to avoid continuous re-entries in the same direction without a reset.
Two flags:
allowLong
allowShort
After a Long entry, allowLong is set to false, allowShort to true.
After a Short entry, allowShort is set to false, allowLong to true.
Flags are reset when price touches the Kumo:
If Low goes into the cloud → allowLong = true
If High goes into the cloud → allowShort = true
If Close is inside the cloud → both allowLong and allowShort are set to true
There is a key option:
Wait Position Close Before Flag Reset
If ON: cloud touch will reset flags only when there is no open position.
If OFF: flags can be reset even while a trade is open.
This gives a kind of regime-based re-entry control: after a trend leg, you wait for a “cloud interaction” to allow new signals.
5. Risk Management
All risk management is handled inside the strategy.
5.1 Position Sizing
Order Size % of Equity – default 10%
The strategy calculates:
position_value = equity * (Order Size % / 100)
position_qty = position_value / close
So position size automatically adapts to your current equity.
5.2 Take Profit Modes
You can choose one of two TP modes:
Percent
Fibonacci
5.2.1 Percent Mode
Single Take Profit at X% from entry (default 2%).
For Long:
TP = entry_price * (1 + tp_pct / 100)
For Short:
TP = entry_price * (1 - tp_pct / 100)
One strategy.exit per side is used: "Long TP/SL" and "Short TP/SL".
5.2.2 Fibonacci Mode (2 partial TPs)
In this mode, TP levels are based on a virtual Fib-style extension between entry and stop-loss.
Inputs:
Fib TP1 Level (default 1.618)
Fib TP2 Level (default 2.5)
TP1 Share % (Fib) (default 50%)
TP2 share is automatically 100% - TP1 share.
Process for Long:
Compute a reference Stop (see SL section below) → sl_for_fib.
Compute distance: dist = entry_price - sl_for_fib.
TP levels:
TP1 = entry_price + dist * (Fib TP1 Level - 1)
TP2 = entry_price + dist * (Fib TP2 Level - 1)
For Short, the logic is mirrored.
Two exits are used:
TP1 – closes TP1 share % of position.
TP2 – closes remaining TP2 share %.
Same stop is used for both partial exits.
5.3 Stop-Loss Modes
You can choose one of three Stop Loss modes:
Stable – fixed % from entry.
Ichimoku – fixed level derived from the Kumo.
Ichimoku Trailing – dynamic SL following the cloud.
5.3.1 Stable SL
For Long:
SL = entry_price * (1 - Stable SL % / 100)
For Short:
SL = entry_price * (1 + Stable SL % / 100)
Used both for Percent TP mode and as reference for Fib TP if Kumo is not available.
5.3.2 Ichimoku SL (fixed, non-trailing)
At the time of a new trade:
For Long:
Base SL = cloud bottom minus small offset (%)
For Short:
Base SL = cloud top plus small offset (%)
The offset is configurable: Ichimoku SL Offset %.
Once computed, that SL level is fixed for this trade.
5.3.3 Ichimoku Trailing SL
Similar to Ichimoku SL, but recomputed each bar:
For Long:
SL = cloud bottom – offset
For Short:
SL = cloud top + offset
A red trailing SL line is drawn on the chart to visualize current stop level.
This trailing SL is also used as reference for BreakEven and for Fib TP distance.
6. BreakEven Logic (with BE Lines)
BreakEven is optional and supports two modes:
Percent
Fibonacci
Inputs:
Percent mode:
BE Trigger % (from entry) – move SL to BE when price goes this % in profit.
BE Offset % from entry – SL will be set to entry ± this offset.
Fibonacci mode:
BE Fib Level – Fib level at which BE will be activated (default 1.618, same style as TP).
BE Offset % from entry – how far from entry to place BE stop.
The logic:
Before BE is triggered, SL follows its normal mode (Stable/Ichimoku/Ichimoku Trailing).
When BE triggers:
For Long:
New SL = max(current SL, BE SL).
For Short:
New SL = min(current SL, BE SL).
This means BE will never loosen the stop – only tighten it.
When BE is activated, the strategy draws a violet horizontal line at the BreakEven level (once per trade).
BE state is cleared when the position is closed or when a new position is opened.
7. Entry & Exit Logic (Summary)
7.1 Long Entry
Conditions for a Long:
CCI signal:
CCI crosses up through the upper threshold.
Ichimoku Cloud Filter (optional):
If enabled → price must be above the Kumo.
Ichimoku Lines Filter (optional):
If enabled → Conversion Line and Base Line must be above the Kumo.
MA Direction Filter (optional):
If enabled → Close must be above the chosen MA.
Anti-re-entry flag:
allowLong must be true (cloud-based reset).
Position check:
Long entries are allowed when current position size ≤ 0 (so it can also reverse from short to long).
If all these conditions are true, the strategy sends:
strategy.entry("Long", strategy.long, qty = calculated_qty)
After entry:
allowLong = false
allowShort = true
7.2 Short Entry
Same structure, mirrored:
CCI signal:
CCI crosses down through the lower threshold.
Cloud filter: price must be below cloud (if enabled).
Lines filter: conversion & base must be below cloud (if enabled).
MA filter: Close must be below MA (if enabled).
allowShort must be true.
Position check: position size ≥ 0 (allows reversal from long to short).
Then:
strategy.entry("Short", strategy.short, qty = calculated_qty)
Flags update:
allowShort = false
allowLong = true
7.3 Exits
While in a position:
The strategy continuously recalculates SL (depending on chosen mode) and, in Percent mode, TP.
In Fib mode, fixed TP levels are computed at entry.
BreakEven may raise/tighten the SL if its conditions are met.
Exits are executed via strategy.exit:
Percent mode: one TP+SL exit per side.
Fib mode: two partial exits (TP1 and TP2) sharing the same SL.
At position open, the script also draws visual lines:
White line — entry price.
Green line(s) — TP level(s).
Red line — SL (if not using Ichimoku Trailing; with trailing, the red line is updated dynamically).
Maximum of 30 lines are kept to avoid clutter.
8. How to Use the Strategy
Choose market & timeframe
Works well on trending instruments. Try crypto, FX or indices on H1–H4, or intraday if you prefer more trades.
Adjust Ichimoku settings
Keep defaults (9/26/52/26) or adapt to your timeframe.
Configure Moving Average
Typical: EMA 200 as a trend filter.
Turn MA Direction Filter ON if you want to trade only with the main trend.
Set CCI thresholds
Default ±100 is classic.
Lower thresholds → more signals, higher noise.
Higher thresholds → fewer but stronger signals.
Enable/disable filters
Turn on Ichimoku Cloud and Ichimoku Lines if you want only “clean” trend trades.
Use Wait Position Close Before Flag Reset to control how often re-entries are allowed.
Choose TP & SL mode
Percent mode is simpler and easier to understand.
Fibonacci mode is more advanced: it aligns TP levels with the distance to stop, giving asymmetric RR setups (two partial TPs).
Choose Stable SL for fixed-risk trades, or Ichimoku / Ichimoku Trailing to tie stops to the cloud structure.
Set BreakEven
Enable BE if you want to lock in risk-free trades after a certain move.
Percent mode is straightforward; Fib mode keeps BreakEven in harmony with your Fib TP setup.
Run Backtest & Optimize
Press “Add to chart” → go to Strategy Tester.
Adjust parameters to your market and timeframe.
Look at equity curve, PF, drawdown, average trade, etc.
Live / Paper Trading
After you’re satisfied with backtest results, use the strategy to generate signals.
You can mirror entries/exits manually or connect them to alerts (if you build an alert-based execution layer).
Multivariate Kalman Filter🙏🏻 I see no1 ever posted an open source Multivariate Kalman filter on TV, so here it is, for you. Tested and mathematically correct implementation, with numerical safeties in place that do not affect the final results at all. That’s the main purpose of this drop, just to make the tool available here. Linear algebra everywhere, Neo would approve 4 sure.
...
Personally I haven't found any real use case of it for myself, aside from a very specific one I will explain later, but others usually do…
Almost every1 in the quant industry who uses Kalman is in fact misusing it, because by its real definition, it should be applied to Not the exact known values (e.g as real ticks provided by transparent audited regulated exchange), but “measurements” of those ‘with errors’.
If your measurements don’t have errors or you have real precise data, by its internal formulas Kalman will output the exact inputs. So most who use it come up with some imaginary errors of sorts, like from some kind of imaginary fair price etc. The important easy to miss point, the errors of your measurements have to be symmetric around its mean ‘ at least ’, if errors are biased, Kalman won’t provide.
For most tasks there are better tools, including other state space models , but still Multivariate Kalman is a very powerful instrument, you can make it do all kinds of stuff. Also as a state space model it can also provide confidence & prediction intervals without explicit calculations of dem.
...
In this script I included 2 example use cases, the first one is the classic tho perfectly working misuse, the second one is what I do with it:
One
Naive, estimates “hidden” adaptive moving regression endpoint. The result you can see on the chart above. You can imagine that your real datapoints are in fact non perfect measures of some hidden state, and by defining measurement noise and process noise, and by constructing the input matrixes in certain ways, you can express what that state should be.
Two
Upscaling tick lattice, aka modelling prices as if native tick size would’ve been lower. Kinda very specific task, mostly needed in HFT or just for analytical purposes. Some like ZN have huge tick sizes, they are traded a lot but barely do more than 20 ticks range in a session. The idea is to model raw data as AR2 process , learn the phi1 and phi2, make one point forecasts based on dem, and the process noise would be the variance of errors from these forecasts. The measurement noise here is legit, it’s quantization noise based on tick size, no need in olympic gold in mental gymnastics xd
^^ artificially upscaling ZN futures tick lattice
...
I really made it available there so You guys can take it and some crazy ish with it, just let state space models abduct your conciseness and never look back
∞
CoreMACDHTF [CHE]Library "CoreMACDHTF"
calc_macd_htf(src, preset_str, smooth_len)
Parameters:
src (float)
preset_str (simple string)
smooth_len (int)
is_hist_rising(src, preset_str, smooth_len)
Parameters:
src (float)
preset_str (simple string)
smooth_len (int)
hist_rising_01(src, preset_str, smooth_len)
Parameters:
src (float)
preset_str (simple string)
smooth_len (int)
CoreMACDHTF — Hardcoded HTF MACD Presets with Smoothed Histogram Regime Flags
Summary
CoreMACDHTF provides a reusable MACD engine that approximates higher-timeframe behavior by selecting hardcoded EMA lengths based on the current chart timeframe, then optionally smoothing the resulting histogram with a stateful filter. It is published as a Pine v6 library but intentionally includes a minimal demo plot so you can validate behavior directly on a chart. The primary exported outputs are MACD, signal, a smoothed histogram, and the resolved lengths plus a timeframe tag. In addition, it exposes a histogram rising condition so importing scripts can reuse the same regime logic instead of re-implementing it.
Motivation: Why this design?
Classic MACD settings are often tuned to one timeframe. When you apply the same parameters to very different chart intervals, the histogram can become either too noisy or too sluggish. This script addresses that by using a fixed mapping from the chart timeframe into a precomputed set of EMA lengths, aiming for more consistent “tempo” across intervals. A second problem is histogram micro-chop around turning points; the included smoother reduces short-run flips so regime-style conditions can be more stable for alerts and filters.
What’s different vs. standard approaches?
Reference baseline: a standard MACD using fixed fast, slow, and signal lengths on the current chart timeframe.
Architecture differences:
Automatic timeframe bucketing that selects a hardcoded length set for the chosen preset.
Two preset families: one labeled A with lengths three, ten, sixteen; one labeled B with lengths twelve, twenty-six, nine.
A custom, stateful histogram smoother intended to damp noisy transitions.
Library exports that return both signals and metadata, plus a dedicated “histogram rising” boolean.
Practical effect:
The MACD lengths change when the chart timeframe changes, so the oscillator’s responsiveness is not constant across intervals by design.
The rising-flag logic is based on the smoothed histogram, which typically reduces single-bar flip noise compared to using the raw histogram directly.
How it works (technical)
1. The script reads the chart timeframe and converts it into milliseconds using built-in timeframe helpers.
2. It assigns the timeframe into a bucket label, such as an intraday bucket or a daily-and-above bucket, using fixed thresholds.
3. It resolves a hardcoded fast, slow, and signal length triplet based on:
The selected preset family.
The bucket label.
In some cases, the current minute multiplier for finer mapping.
4. It computes fast and slow EMAs on the selected source and subtracts them to obtain MACD, then computes an EMA of MACD for the signal line.
5. The histogram is derived from the difference between MACD and signal, then passed through a custom smoother.
6. The smoother uses persistent internal state to carry forward its intermediate values from bar to bar. This is intentional and means the smoothing output depends on contiguous bar history.
7. The histogram rising flag compares the current smoothed histogram to its prior value. On the first comparable bar it defaults to “rising” to avoid a missing prior reference.
8. Exports:
A function that returns MACD, signal, smoothed histogram, the resolved lengths, and a text tag.
A function that returns the boolean rising state.
A function that returns a numeric one-or-zero series for direct plotting or downstream numeric logic.
HTF note: this is not a true higher-timeframe request. It does not fetch higher-timeframe candles. It approximates HTF feel by selecting different lengths on the current timeframe.
Parameter Guide
Source — Input price series used for EMA calculations — Default close — Trade-offs/Tips
Preset — Selects the hardcoded mapping family — Default preset A — Preset A is more reactive than preset B in typical use
Table Position — Anchor for an information table — Default top right — Present but not wired in the provided code (Unknown/Optional)
Table Size — Text size for the information table — Default normal — Present but not wired in the provided code (Unknown/Optional)
Dark Mode — Theme toggle for the table — Default enabled — Present but not wired in the provided code (Unknown/Optional)
Show Table — Visibility toggle for the table — Default enabled — Present but not wired in the provided code (Unknown/Optional)
Zero dead-band (epsilon) — Intended neutral band around zero for regime classification — Default zero — Present but not used in the provided code (Unknown/Optional)
Acceptance bars (n) — Intended debounce count for regime confirmation — Default three — Present but not used in the provided code (Unknown/Optional)
Smoothing length — Length controlling the histogram smoother’s responsiveness — Default nine — Smaller values react faster but can reintroduce flip noise
Reading & Interpretation
Smoothed histogram: use it as the momentum core. A positive value implies MACD is above signal, a negative value implies the opposite.
Histogram rising flag:
True means the smoothed histogram increased compared to the prior bar.
False means it did not increase compared to the prior bar.
Demo plot:
The included plot outputs one when rising is true and zero otherwise. It is a diagnostic-style signal line, not a scaled oscillator display.
Practical Workflows & Combinations
Trend following:
Use rising as a momentum confirmation filter after structural direction is established by higher highs and higher lows, or lower highs and lower lows.
Combine with a simple trend filter such as a higher-timeframe moving average from your main script (Unknown/Optional).
Exits and risk management:
If you use rising to stay in trends, consider exiting or reducing exposure when rising turns false for multiple consecutive bars rather than reacting to a single flip.
If you build alerts, evaluate on closed bars to avoid intra-bar flicker in live candles.
Multi-asset and multi-timeframe:
Because the mapping is hardcoded, validate on each asset class you trade. Volatility regimes differ and the perceived “equivalence” across timeframes is not guaranteed.
For consistent behavior, keep the smoothing length aligned across assets and adjust only when flip frequency becomes problematic.
Behavior, Constraints & Performance
Repaint and confirmation:
There is no forward-looking indexing. The logic uses current and prior values only.
Live-bar values can change until the bar closes, so rising can flicker intra-bar if you evaluate it in real time.
security and HTF:
No higher-timeframe candle requests are used. Length mapping is internal and deterministic per chart timeframe.
Resources:
No loops and no arrays in the core calculation path.
The smoother maintains persistent state, which is lightweight but means results depend on uninterrupted history.
Known limits:
Length mappings are fixed. If your chart timeframe is unusual, the bucket choice may not represent what you expect.
Several table and regime-related inputs are declared but not used in the provided code (Unknown/Optional).
The smoother is stateful; resetting chart history or changing symbol can alter early bars until state settles.
Sensible Defaults & Quick Tuning
S tarting point:
Preset A
Smoothing length nine
Source close
Tuning recipes:
Too many flips: increase smoothing length and evaluate rising only on closed bars.
Too sluggish: reduce smoothing length, but expect more short-run reversals.
Different timeframe feel after switching intervals: keep preset fixed and adjust smoothing length first before changing preset.
Want a clean plot signal: use the exported numeric rising series and apply your own display rules in the importing script.
What this indicator is—and isn’t
This is a momentum and regime utility layer built around a MACD-style backbone with hardcoded timeframe-dependent parameters and an optional smoother. It is not a complete trading system, not a risk model, and not predictive. Use it in context with market structure, execution rules, and risk controls.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Candle Patterns Ver.2When someone decided to start trading the first thing we learn is how to read and understand the candlesticks. This little "boxes" with sticks tell us how the market sentiment and they can be used to "predict" future moves. I put predict inside a quotation marks because I would say predict the market is almost an utopia and we all know the reason.
Anyway with a good understand in reading the candlesticks with other indicators(like momentum or even a MA) can give us some edge when analyzing an instrument.
Since we have a lot of candlesticks types I did some back test and figured out that for my strategy that three candlestick types works very well. I will briefly describe then.
Engulfing Bar
This type of candlestick shows us a potential reversal based on the previous bar.
A bullish Engulfing has the close higher than the open it works better if the previous one is a bearish bar(open higher than close) and it is at a Support level. The body of the Engulfing bar should "engulf" the full body of the previous bar. If all parameters(previous bearish bar at Support level after a downtrend move) this Engulfing will represents a reversal move. When I say reversal it could means a pullback reversal(if the past trend is downtrend) or if the previous downtrend is a pullback from a past uptrend. In any way the previous bearish followed by an bullish Engulfing in general leads for an upward move.
The same picture applies to a previous bullish bar followed by an bearish Engulfing bar that if appears at the Resistance level will lead to a downward move.
One thing that is worth to mention is in a downward(or upward) move we have a small bullish bar followed by a bullish Engulfing this situation may lead to a continuation, not reversal.
Pinbar Bar:
This is another candlestick type that represents possible reversal. The Pinbar candle show a small(or medium) size but the important part is the size of the stick. If the stick is the upper one and has the size of 2 times the size of the body, it is a bearish bars and it appears after an uptrend move it represents that the buyers are losing momentum so we can expect a reversal move. When this type of bar appears after a downward move, it is a bullish bars but the stick is the lower one and has the size of two times of the body it will represents a bullish reversal. In this picture this candle is called a "Hammer".
So based on that I develop an indicator that shows me these 2 bars types and makes easy to identify with the other indicator possible entries.
Please feel free for a constructive comments and hope it help any one whe trading. Candlestick are the fundamentals of Price action.
You all have a great trading new week.
Stochastic Ensembling of OutputsStochastic Ensembling of Outputs
🙏🏻 This is a simple tool/method that would solve naturally many well known problems:
“Price reversed 1 tick before the actual level, not executing my limit order”
“I consider intraday trend change by checking whether price is above/below VWAP, but is 1 tick enough? What to do, price is now whipsawing around vwap...”.
“I want to gradually accumulate a position around a chosen anchor. But where exactly should I put my orders? And I want to automate it ofc.“
“All these DSP adepts are telling you about some kind of noise in the markets… But how can I actually see it?”
The easy fix is to make things more analog less digital, by synthesizing numerous noise instances & adding it to any price-applied metric of yours. The ones who fw techno & psytrance, and other music, probably don’t need any more explanations. Then by checking not just 2 lines or 1 process against another one, you will be checking cloud vs cloud of lines, even allowing you to introduce proxies of probabilities. More crosses -> more confirmation to act.
How-to use:
The tool has 2 inputs: source and target:
Sources should always be the underlying process. If you apply the tool to price based metric, leave it hlcc4 unless you have a better one point estimate for each bar;
Target is your target, e.g if you want to apply it to VWAP, pick VWAP as target. You can thee on the chart above how trading activity recently never exactly touched VWAP, however noised instances of VWAP 'were' touched
The code is clean and written in modular form, you can simply copy paste it to any script of yours if you don't want to have multiple study-on-study script pairs.
^^ applied to prev days highs and lows
^^ applied to MBAD extensions and basis
^^ applied to input series itself
Here’s how it works, no ML, no “AI”, no 1k lines of code, just stats:
The problem with metrics, even if they are time aware like WMA, is that they still do not directly gain information about “changes” between datapoints. If we pick noise characteristics to match these changes, we’d effectively introduce this info into our ops.
^^ this screenshot represents 2 very different processes: a sine wave and white noise, see how the noise instances learned from each process differ significantly.
Changes can be represented as AR1 process . It’s dead simple, no PHD needed, it’s just how the current datapoint is related (or not) to the previous datapoint, no more than 1, and how this relationship holds/evolves over time. Unlike the mainstream approach like MLE, I estimate this relationship (phi parameter) via MoM but giving more weights to more recent datapoints via exponential smoothing over all the data available on your charts (so I encode temporal information), algocomplexity is O(1), lighting fast, just one pass. <- that gives phi , we’d use it as color for our noise generator
Then we just need to estimate noise amplitude ( gamma ) via checking what AR1 model actually thought vs the reality, variance of these innovations. Same via exponential smoothing, time aware, O(1), one pass, it’s all it does.
Then we generate white gaussian noise, and apply 2 estimated parameters (phi and gamma), and that’s all.
Omg, I think I just made my first real DSP script xd
Just like Monte Carlo for risk management, this is so simple and natural I can’t believe so many “pros” hide it and never talk about it in open access. Sharing it here on TradingView would’ve not done anything critical for em, but many would’ve benefited.
∞
TopBot [CHE] TopBot — Structure pivots with buffered acceptance and gradient trend visualization
Summary
TopBot detects swing structure from confirmed pivot highs and lows, derives support and resistance levels, and switches trend only after a buffered and accepted break. It renders labels for recent structure points, maintains dynamic support and resistance lines that freeze on contact, and colors candles using a gradient that reflects consecutive trend persistence. The gradient communicates strength without extra panels, while the buffered acceptance reduces fragile flips around key levels. Everything runs in the main chart for immediate context.
Motivation: Why this design?
Classical swing tools often flip on single-bar spikes and produce lines that extend forever without acknowledging when price invalidates them. This script addresses that by requiring a user-controlled buffer and a run of consecutive closes before changing trend, while also freezing lines once price interacts with them. The gradient color layer communicates regime persistence so users can quickly judge whether a move is maturing or just starting.
What’s different vs. standard approaches?
Baseline reference: Simple pivot labeling and unbuffered break-of-structure tools.
Architecture differences:
Buffered level testing using ticks, percent, or ATR.
Acceptance logic that requires multiple consecutive closes.
Synchronized structure labeling with a single Top and Bottom within the active set.
Progressive support and resistance management that freezes lines on first contact.
Gradient candle and wick coloring driven by consecutive trend counts with windowed normalization and gamma control.
Practical effect: Fewer whipsaw flips, clearer status of active levels, and visual feedback about trend persistence without a secondary pane.
How it works (technical)
The script confirms swing points using left and right bar pivots, then forms a current structure window to classify each pivot as higher high, lower high, higher low, or lower low. Recent labels are trimmed to a user cap, and a postprocess step ensures one highest and one lowest label while preserving side information for the others. Support updates on higher low events, resistance on lower high events. Trend flips only after the close has moved beyond the active level by a chosen buffer and this condition holds for a chosen number of consecutive bars. Lines for new levels extend to the right and freeze once price touches them. A running count of consecutive trend bars produces a strength score, which is normalized over a rolling window, shaped by gamma, and mapped to user-defined dark and neon colors for both up and down regimes. Wick coloring uses `plotcandle`; fallback bar coloring uses `barcolor`. No higher-timeframe data is requested. Signals confirm only after the right-bar lookback of the pivot function.
Parameter Guide
Left Bars / Right Bars (default five each): Pivot sensitivity. Larger values confirm later and reduce noise; smaller values respond faster with more noise.
Draw S/R Lines (default true): Enables support and resistance line creation and updates.
Support / Resistance Colors (lime, red): Line colors for each side.
Line Style (Solid, Dashed, Dotted; default Dotted) and Width (default three): Visual style of S/R lines.
Max Labels & Lines (default ten): Cap for objects to control clutter and resource usage.
Change Bar Color (default true), Up/Down colors (blue, black): Fallback bar coloring when gradients or wick coloring are disabled.
Show Neutral Candles (default false): Optional coloring when no trend is active.
Enable Gradient Bar Colors (default true): Turns on gradient body coloring from the strength score.
Enable Wick Coloring (default true): Colors wicks and borders using `plotcandle`.
Collection Period (default one hundred): Rolling window used to scale the strength score. Shorter windows react faster but vary more.
Gamma Bars / Gamma Plots (defaults zero point seven and zero point eight): Shapes perceived contrast of bar and wick gradients. Lower values brighten early; higher values compress until stronger runs appear.
Gradient Transparency / Wick Transparency (default zero): Visual transparency for bodies and wicks.
Up/Down Trend Dark and Neon Colors: Endpoints for gradient mapping in each regime.
Acceptance closes (n) (default two): Number of consecutive closes beyond a level required before trend flips. Larger values reduce false breaks but react later.
Break buffer (None, Ticks, Percent, ATR; default ATR) and Value (default zero point five) and ATR Len (default fourteen): Defines the safety margin beyond the level. ATR mode adapts to volatility; Percent and Ticks are static.
Reading & Interpretation
Labels: “Top” and “Bottom” mark the most extreme points in the active set; “LT” and “HB” indicate side labels for lower top and higher bottom.
Lines: New support or resistance is drawn when structure confirms. A line freezes once price touches it, signaling that the dynamic phase ended.
Trend: Internal state switches to up or down only after buffered acceptance.
Colors: Brighter neon tones indicate stronger and more persistent runs; darker tones suggest early or weakening runs. When gradients are off, fallback bar colors indicate trend sign.
Practical Workflows & Combinations
Trend following: Wait for a buffered and accepted break through the most recent level, then use gradient intensity to stage entries or scale-ins.
Structure-first filtering: Trade only in the direction of the last accepted trend while price remains above support or below resistance.
Exits and stops: Consider exiting on loss of gradient intensity combined with a return through the most recent structure level.
Multi-asset / Multi-timeframe: Works on liquid symbols across common timeframes. Use larger pivot bars and higher acceptance on lower timeframes. No built-in higher-timeframe aggregation is used.
Behavior, Constraints & Performance
Repaint/confirmation: Pivot confirmation waits for the right bar window; trend acceptance is based on closes and can change during a live bar. Final signals stabilize on bar close.
security/HTF: Not used. No cross-timeframe data.
Resources: Arrays and loops are used for labels, lines, and structure search up to a capped historical span. Object counts are clamped by user input and platform limits.
Known limits: Delayed confirmation at sharp turns due to pivot windows; rapid gaps can jump over buffers; gradient scaling depends on the chosen collection period.
Sensible Defaults & Quick Tuning
Start with the defaults: pivot windows at five, ATR buffer with value near one half, acceptance at two, collection period near one hundred, gamma near zero point seven to zero point eight.
Too many flips: increase acceptance, increase buffer value, or increase pivot windows.
Too sluggish: reduce acceptance, reduce buffer value, or reduce pivot windows.
Colors too flat: lower gamma or shorten the collection period.
Visual clutter: reduce the max labels and lines cap or disable wicks.
What this indicator is—and isn’t
This is a visualization and signal layer that encodes swing structure, level state, and regime persistence. It is not a complete trading system, not predictive, and does not manage orders. Use it with broader context such as higher timeframe structure, session behavior, and defined risk controls.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Acknowledgment
Thanks to LonesomeTheBlue for the fantastic and inspiring "Higher High Lower Low Strategy" .
Original script:
Credit for the original concept and implementation goes to the author; any adaptations or errors here are mine.
