Six Moving Averages Study (use as a manual strategy indicator)I made this based on a really interesting conversation I had with a good friend of mine who ran a long/short hedge fund for seven years and worked at a major hedge fund as a manager for 20 years before that. This is an unconventional approach and I would not recommend it for bots, but it has worked unbelievably well for me over the last few weeks in a mixed market.
The first thing to know is that this indicator is supposed to work on a one minute chart and not a one hour, but TradingView will not allow 1m indicators to be published so we have to work around that a little bit. This is an ultra fast day trading strategy so be prepared for a wild ride if you use it on crypto like I do! Make sure you use it on a one minute chart.
The idea here is that you get six SMA curves which are:
1m 50 period
1m 100 period
1m 200 period
5m 50 period
5m 100 period
5m 200 period
The 1m 50 period is a little thicker because it's the most important MA in this algo. As price golden crosses each line it becomes a stronger buy signal, with added weight on the 1m 50 period MA. If price crosses all six I consider it a strong buy signal though your mileage may vary.
*** NOTE *** The screenshot is from a 1h chart which again, is not the correct way to use this. PLEASE don't use it on a one hour chart.
"curve" için komut dosyalarını ara
Market Maker BalanceWhere is the market maker in his cycle of building longs or shorts? When is that big drop or big pump coming?
This is a simple and unexpectedly powerful indicator that shows you an estimate of the market maker's position over the last 200 candles. It works on any timeframe.
How does it work?
It combines a simple 10-candle Price Volume Support Resistance Analysis metric of climactic and rising volume. That volume is combined to create a bullish and bearish balance over a period of 200 candles. The curves are smoothed out with a 10 period EMA.
The MMB (Marker Maker Balance) oscillator is the resulting bearish volume - bullish volume, which shows us THEIR position balance.
Indications:
when shorts are increasing (further below 0), we are in a bullish trend -- you should be taking profit on longs
when shorts are flat or decreasing, the trend is due for a reversal -- you should be closing longs and looking to short
when shorts cross 0 to long, the trend is reversing down -- you should be in a short position by now
when longs are increasing, we are in a bearish trend -- you should be taking profits on your shorts
when longs are flat or decreasing, the trend is due for a reversal -- you should be closing your shorts
For extra information, there are also the separate lines for rising and climactic volume to give you early indications of reversal or change in Market Maker behaviour. You can disable them in the Style settings, but they can be a useful early indicator that the current trend is losing strength when rising volume overtakes climax volume (MM's no longer moving out of zones higher/lower).
Ways to use this indicator are quite simple and eerily accurate:
for short term gains, do the opposite of MMs: long when MM are opening more shorts, short when they are opening more longs
for huge positions, mimic the MM position: build long positions / close shorts when MMB is rising, build shorts / close longs when MMB is falling or crosses above 0 (be careful with leverage, begin on 1x leverage)
Note: the results of this indicator will be different for each exchange, because of their different trading volumes per candle. It's advisable to use it for the exchange you're trading on or use a chart that averages all exchanges for that asset, like INDEX:BTCUSD.
For those of you who use the Backtesting & Trading Engine by PineCoders, the BTE Signal plot generates long and short entries as well as filter states. Use this plot as the source for BTE.
Shout out to @infernixx for PVSRA calculations in his awesome Traders Reality indicator, the code of which I shamelessly ripped off and edited for this indicator.
Leave comments below if you want something added.
Ethereum Logarithmic Growth Curves & ZonesThis script was modified to fit ethereum logarithmic pricing action.
Moving Regression Prediction BandsIntroducing the Moving Regression Prediction Bands indicator.
Here I aimed to combine the principles of traditional band indicators (such as Bollinger Bands), regression channel and outlier detection methods. Its upper and lower bands define an interval in which the current price was expected to fall with a prescribed probability, as predicted by the previous-step result of the local polynomial regression (for the original Moving Regression script, see link below).
Algorithm
1. At every time step, the script performs local polynomial regression of the sample data within the lookback window specified by the Length input parameter.
2. The fitted polynomial is used to construct the Moving Regression time series as well as to extrapolate data, that is, to predict the next data point ( MRPrediction ).
3. The accuracy of local interpolation is estimated by means of the root-mean-square error ( RMSE ), that is, the deviation between the fitted polynomial and the observed values.
4. The MRPrediction and RMSE values calculated for the previous bar are then used to build the upper and lower bands , which I define as follows:
Upper Band = MRPrediction_prev + Multiplier *( RMSE_prev )
Lower Band = MRPrediction_prev - Multiplier *( RMSE_prev )
Here the Multiplier is a user-defined parameter that should be interpreted as a quantile in the standard normal distribution (the default value of 2.0 roughly corresponds to the 95% prediction interval).
To visualize the central line , the script offers the following options:
Previous-Period MR Prediction: MRPrediction_prev time series from the above equation.
MR: Conventional Moving Regression time series.
Ribbon: “Previous-Period MR Prediction” and “MR” curves plotted together and colored according to their relative value (green if MR > Previous MR Prediction; red otherwise).
Usage
My original idea was to use the band breakouts as potential trading signals. For example, the price crossing above the upper band is a bullish signal , being a potential sign that price is gaining momentum and is out of a previously predicted trend. The exit signal could be the crossing under the lower band or under the central line.
However, be aware that it is an experimental indicator, so you might fin some better strategies.
Feel free to play around!
Trend ChannelMarket engineers can use channels to find out when a market has entered an undervalued or overvalued zone. Purchases and sales take place in these zones. Professionals use trending channels to find out when the market has overtaken itself and where it is likely to reverse.
Upper channel line = EMA + EMA x channel coefficient
Lower channel line = EMA - EMA x channel coefficient
The topline reflects the bulls' strength in raising prices above the average value consensus. This line marks the normal limit of optimism in the market.
The bottom line of the channel reflects the strength of the bears pushing prices below the average consensus of values. This line marks the normal limit of pessimism in the market.
The coefficient is used to correct the distance to the moving average until the channel contains 95% of all prices. Only the tips and the lowest bottoms are allowed to protrude. For these peaks and curves and sideways trends, I have added two more switchable lines to the border lines, with a distance of 23.6% (light blue).
The larger the time frame, the wider the channel.
If you buy near a rising moving average, you take profits near the upper line of the channel.
If you are short near a falling moving average, you should close out near the bottom of the channel.
If the moving average is essentially flat, then you should be long on the bottom of the channel and short on the top of the channel. You realize profits when the prices have returned to their moving average to normal.
Interesting for day traders:
Adjust the moving average so that it has the same slope as the quotes on the hourly chart. With the coefficient you set the distance between the border lines. Perhaps adding the 23.6% lines will help, where the sideways trends are starting. Set the resolution to "1 hour". If you want to trade with these settings in short time units, e.g. in the 3 minute chart or in the 1 minute chart, then you now have target marks and indications in which direction the prices will possibly move when the prices have reached the moving average or one of the border lines.
The text contains excerpts from "Come into my Trading Room" by Dr. Alexander Elder.
The indicator has an additional exponential moving average with adjustable period, adjustable shift and adjustable source for the narrow range of quotations and final determination of direction.
The chart shows how the trend channel and the Fibonacc trading indicator can complement each other.
The text contains excerpts from "Come into my Trading Room" by Dr. Alexander Elder.
Markttechniker können Kanäle verwenden um heraus zu finden, wann ein Markt eine unterbewertete oder überbewertete Zone erreicht hat. An diesen Zonen finden Käufe und Verkäufe statt. Profis benutzen Trendkanäle um herauszufinden, wann der Markt sich selbst überholt hat und wo er wahrscheinlich eine Umkehrbewegung vollziehen wird.
Obere Kanallinie = EMA + EMA x Kanalkoeffizient
Untere Kanallinie = EMA - EMA x Kanalkoeffizient
Die Oberlinie reflektiert die Kraft der Bullen, mit der sie die Kurse über den durchschnittlichen Wertekonsens anheben. Diese Linie kennzeichnet die normale Grenze des Optimismus im Markt.
Die untere Linie des Kanals reflektiert die Kraft der Bären, mit der sie die Kurse unter den durchschnittlichen Wertekonsens drücken. Diese Linie kennzeichnet die normale Grenze des Pessimismus im Markt.
Mit dem Koeffizienten wird der Abstand zum gleitenden Durchschnitt so lange korrigiert, bis der Kanal 95% aller Kurse enthält. Lediglich die Spitzen und die niedrigsten Böden dürfen herausragen. Für diese Spitzen und Bögen und Seitwärtstrends habe ich zu den Grenzlinien zwei weitere zuschaltbare Linien, mit einem Abstand von 23,6%, hinzugefügt (hellblau).
Je größer der Zeitrahmen ist, um so breiter ist der Kanal.
Wenn Sie in der Nähe eines ansteigenden gleitenden Durchschnitts kaufen, nehmen Sie die Gewinne in der Nähe der oberen Grenzlinie des Kanals mit.
Wenn Sie in der Nähe eines fallenden gleitenden Durchschnitts leerverkaufen, sollten Sie in der Nähe der unteren Grenzlinie des Kanals glattstellen.
Wenn der gleitende Durchschnitt im Wesentlichen flach ist, dann sollten Sie an der unteren Kanalbegrenzung eine Long-Position und an der oberen Kanalbegrenzung eine Short-Position einnehmen. Gewinne realisieren Sie jeweils, wenn die Kurse zu ihrem gleitenden Durchschnitt, zur Normalität zurückgekehrt sind.
Für Daytrader interessant:
Stellen Sie den gleitenden Durchschnitt so ein, dass er die gleiche Steigung wie die Notierungen im Stunden-Chart hat. Mit dem Koeffizienten Stellen Sie den Abstand der Grenzlinien ein. Vielleicht hilft die Zuschaltung der 23,6%-Linien, wo die Seitwärtstrends anstoßen. Stellen Sie die Auflösung auf „1 Stunde“. Wenn Sie mit diesen Einstellungen in niedrigen Zeiteinheiten traden wollen, z.B. im 3 Minuten-Chart oder im 1 Minuten-Chart, dann haben Sie jetzt Zielmarken und Hinweise in welche Richtung die Notierungen möglicherweise laufen werden, wenn die Notierungen den gleitenden Durchschnitt oder eine der Grenzlinien erreicht haben.
Der Text enthält Auszüge aus „Come into my Trading Room“ von Dr. Alexander Elder.
Der Indikator besitzt zur engen Umfang der Notierungen und endgültigen Richtungsbestimmung einen zusätzlichen exponentiellen gleitenden Durchschnitt mit einstellbarer Periode, einstellbarer Verschiebung und einstellbarer Quelle.
Der Chart zeigt wie sich Trendkanal und Fibonacc-Trading-Indikator ergänzen könne.
Der Text enthält Auszüge aus „Come into my Trading Room“ von Dr . Alexander Elder.
Square Root Moving AverageAbstract
This script computes moving averages which the weighting of the recent quarter takes up about a half weight.
This script also provides their upper bands and lower bands.
You can apply moving average or band strategies with this script.
Introduction
Moving average is a popular indicator which can eliminate market noise and observe trend.
There are several moving average related strategies used by many traders.
The first one is trade when the price is far from moving average.
To measure if the price is far from moving average, traders may need a lower band and an upper band.
Bollinger bands use standard derivation and Keltner channels use average true range.
In up trend, moving average and lower band can be support.
In ranging market, lower band can be support and upper band can be resistance.
In down trend, moving average and upper band can be resistance.
An another group of moving average strategy is comparing short term moving average and long term moving average.
Moving average cross, Awesome oscillators and MACD belong to this group.
The period and weightings of moving averages are also topics.
Period, as known as length, means how many days are computed by moving averages.
Weighting means how much weight the price of a day takes up in moving averages.
For simple moving averages, the weightings of each day are equal.
For most of non-simple moving averages, the weightings of more recent days are higher than the weightings of less recent days.
Many trading courses say the concept of trading strategies is more important than the settings of moving averages.
However, we can observe some characteristics of price movement to design the weightings of moving averages and make them more meaningful.
In this research, we use the observation that when there are no significant events, when the time frame becomes 4 times, the average true range becomes about 2 times.
For example, the average true range in 4-hour chart is about 2 times of the average true range in 1-hour chart; the average true range in 1-hour chart is about 2 times of the average true range in 15-minute chart.
Therefore, the goal of design is making the weighting of the most recent quarter is close to the weighting of the rest recent three quarters.
For example, for the 24-day moving average, the weighting of the most recent 6 days is close to the weighting of the rest 18 days.
Computing the weighting
The formula of moving average is
sum ( price of day n * weighting of day n ) / sum ( weighting of day n )
Day 1 is the most recent day and day k+1 is the day before day k.
For more convenient explanation, we don't expect sum ( weighting of day n ) is equal to 1.
To make the weighting of the most recent quarter is close to the weighting of the rest recent three quarters, we have
sum ( weighting of day 4n ) = 2 * sum ( weighting of day n )
If when weighting of day 1 is 1, we have
sum ( weighting of day n ) = sqrt ( n )
weighting of day n = sqrt ( n ) - sqrt ( n-1 )
weighting of day 2 ≒ 1.414 - 1.000 = 0.414
weighting of day 3 ≒ 1.732 - 1.414 = 0.318
weighting of day 4 ≒ 2.000 - 1.732 = 0.268
If we follow this formula, the weighting of day 1 is too strong and the moving average may be not stable.
To reduce the weighting of day 1 and keep the spirit of the formula, we can add a parameter (we call it as x_1w2b).
The formula becomes
weighting of day n = sqrt ( n+x_1w2b ) - sqrt ( n-1+x_1w2b )
if x_1w2b is 0.25, then we have
weighting of day 1 = sqrt(1.25) - sqrt(0.25) ≒ 1.1 - 0.5 = 0.6
weighting of day 2 = sqrt(2.25) - sqrt(1.25) ≒ 1.5 - 1.1 = 0.4
weighting of day 3 = sqrt(3.25) - sqrt(2.25) ≒ 1.8 - 1.5 = 0.3
weighting of day 4 = sqrt(4.25) - sqrt(3.25) ≒ 2.06 - 1.8 = 0.26
weighting of day 5 = sqrt(5.25) - sqrt(4.25) ≒ 2.3 - 2.06 = 0.24
weighting of day 6 = sqrt(6.25) - sqrt(5.25) ≒ 2.5 - 2.3 = 0.2
weighting of day 7 = sqrt(7.25) - sqrt(6.25) ≒ 2.7 - 2.5 = 0.2
What you see and can adjust in this script
This script plots three moving averages described above.
The short term one is default magenta, 6 days and 1 atr.
The middle term one is default yellow, 24 days and 2 atr.
The long term one is default green, 96 days and 4 atr.
I arrange the short term 6 days to make it close to sma(5).
The other twos are arranged according to 4x length and 2x atr.
There are 9 curves plotted by this script. I made the lower bands and the upper bands less clear than moving averages so it is less possible misrecognizing lower or upper bands as moving averages.
x_src : how to compute the reference price of a day, using 1 to 4 of open, high, low and close.
len : how many days are computed by moving averages
atr : how many days are computed by average true range
multi : the distance from the moving average to the lower band and the distance from the moving average to the lower band are equal to multi * average true range.
x_1w2b : adjust this number to avoid the weighting of day 1 from being too strong.
Conclusion
There are moving averages which the weighting of the most recent quarter is close to the weighting of the rest recent three quarters.
We can apply strategies based on moving averages. Like most of indicators, oversold does not always means it is an opportunity to buy.
If the short term lower band is close to the middle term moving average or the middle term lower band is close to the long term moving average, it may be potential support value.
References
Computing FIR Filters Using Arrays
How to trade with moving averages : the eight trading signals concluded by Granville
How to trade with Bollinger bands
How to trade with double Bollinger bands
Tilson T3 and MavilimW Triple Combined StrategyInspired by truly greatful Kivanç Ozbilgic (www.tradingview.com).
The strategy tries to combined three different moving average strategies into one.
Strategies covered are:
1. Tillson T3 Moving Average Strategy
Developed by Tim Tillson, the T3 Moving Average is considered superior to traditional moving averages as it is smoother, more responsive and thus performs better in ranging market conditions as well. However, it bears the disadvantage of overshooting the price as it attempts to realign itself to current market conditions.
It incorporates a smoothing technique which allows it to plot curves more gradual than ordinary moving averages and with a smaller lag. Its smoothness is derived from the fact that it is a weighted sum of a single EMA, double EMA, triple EMA and so on. When a trend is formed, the price action will stay above or below the trend during most of its progression and will hardly be touched by any swings. Thus, a confirmed penetration of the T3 MA and the lack of a following reversal often indicates the end of a trend. Here is what the calculation looks like:
T3 = c1*e6 + c2*e5 + c3*e4 + c4*e3, where:
– e1 = EMA (Close, Period)
– e2 = EMA (e1, Period)
– e3 = EMA (e2, Period)
– e4 = EMA (e3, Period)
– e5 = EMA (e4, Period)
– e6 = EMA (e5, Period)
– a is the volume factor, default value is 0.7 but 0.618 can also be used
– c1 = – a^3
– c2 = 3*a^2 + 3*a^3
– c3 = – 6*a^2 – 3*a – 3*a^3
– c4 = 1 + 3*a + a^3 + 3*a^2
T3 MovingThe T3 Moving Average generally produces entry signals similar to other moving averages and thus is traded largely in the same manner.
Strategy for Tillson T3 is if the close crossovers T3 line and for at least five bars the close was under the T3
2. Tillson T3 Fibonacci Cross
Kivanc Ozbilgic added a second T3 line with a volume factor of 0.618 (Fibonacci Ratio) and length of 3 (fibonacci number) which can be added by selecting the T3 Fibonacci Strategy input box.
Strategy for Tillson T3 Fibo is when the Fibo Line crossover the T3 it gives long signal vice versa.
3. MavilimW
MavilimW is originally a support and resistance indicator based on fibonacci injected weighted moving averages.
Strategy for MavilimW is is if the close crossovers T3 line and for at least five bars the close was under the T3
Hope you enjoy
[2020 Updated]Bitcoin Logarithmic Growth CurvesCredit goes to the original writer of the script, Quantadelic, who generously allowed anyone to copy/edit. I adjusted the value of the bottom/top intercept and slope to better fit the March 2020 coronavirus dip.
Use Bitstamp BTCUSD for better reading.
Bitcoin Block Height (Total Blocks)Bitcoin Block Height by RagingRocketBull 2020
Version 1.0
Differences between versions are listed below:
ver 1.0: compare QUANDL Difficulty vs Blockchain Difficulty sources, get total error estimate
ver 2.0: compare QUANDL Hash Rate vs Blockchain Hash Rate sources, get total error estimate
ver 3.0: Total Blocks estimate using different methods
--------------------------------
This indicator estimates Bitcoin Block Height (Total Blocks) using Difficulty and Hash Rate in the most accurate way possible, since
QUANDL doesn't provide a direct source for Bitcoin Block Height (neither QUANDL:BCHAIN, nor QUANDL:BITCOINWATCH/MINING).
Bitcoin Block Height can be used in other calculations, for instance, to estimate the next date of Bitcoin Halving.
Using this indicator I demonstrate:
- that QUANDL data is not accurate and differ from Blockchain source data (industry standard), but still can be used in calculations
- how to plot a series of data points from an external csv source and compare it with another source
- how to accurately estimate Bitcoin Block Height
Features:
- compare QUANDL Difficulty source (EOD, D1) with external Blockchain Difficulty csv source (EOD, D1, embedded)
- show/hide Quandl/Blockchain Difficulty curves
- show/hide Blockchain Difficulty candles
- show/hide differences (aqua vertical lines)
- show/hide time gaps (green vertical lines)
- count source differences within data range only or for the whole history
- multiply both sources by alpha to match before comparing
- floor/round both matched sources when comparing
- Blockchain Difficulty offset to align sequences, bars > 0
- count time gaps and missing bars (as result of time gaps)
WARNING:
- This indicator hits the max 1000 vars limit, adding more plots/vars/data points is not possible
- Both QUANDL/Blockchain provide daily EOD data and must be plotted on a daily D1 chart otherwise results will be incorrect
- current chart must not have any time gaps inside the range (time gaps outside the range don't affect the calculation). Time gaps check is provided.
Otherwise hardcoded Blockchain series will be shifted forward on gaps and the whole sequence become truncated at the end => data comparison/total blocks estimate will be incorrect
Examples of valid charts that can run this indicator: COINBASE:BTCUSD,D1 (has 8 time gaps, 34 missing bars outside the range), QUANDL:BCHAIN/DIFF,D1 (has no gaps)
Usage:
- Description of output plot values from left to right:
- c_shifted - 4x blockchain plotcandles ohlc, green/black (default na)
- diff - QUANDL Difficulty
- c_shifted - Blockchain Difficulty with offset
- QUANDL Difficulty multiplied by alpha and rounded
- Blockchain Difficulty multiplied by alpha and rounded
- is_different, bool - cur bar's source values are different (1) or not (0)
- count, number of differences
- bars, total number of bars/data points in the range
- QUANDL daily blocks
- Blockchain daily blocks
- QUANDL total blocks
- Blockchain total blocks
- total_error - difference between total_blocks estimated using both sources as of cur bar, blocks
- number_of_gaps - number of time gaps on a chart
- missing_bars - number of missing bars as result of time gaps on a chart
- Color coding:
- Blue - QUANDL data
- Red - Blockchain data
- Black - Is Different
- Aqua - number of differences
- Green - number of time gaps
- by default the indicator will show lots of vertical aqua lines, 138 differences, 928 bars, total error -370 blocks
- to compare the best match of the 2 sources shift Blockchain source 1 bar into the future by setting Blockchain Difficulty offset = 1, leave alpha = 0.01 =>
this results in no vertical aqua lines, 0 differences, total_error = 0 blocks
if you move the mouse inside the range some bars will show total_error = 1 blocks => total_error <= 1 blocks
- now uncheck Round Difficulty Values flag => some filled aqua areas, 218 differences.
- now set alpha = 1 (use raw source values) instead of 0.01 => lots of filled aqua areas, 871 differences.
although there are many differences this still doesn't affect the total_blocks estimate provided Difficulty offset = 1
Methodology:
To estimate Bitcoin Block Height we need 3 steps, each step has its own version:
- Step 1: Compare QUANDL Difficulty vs Blockchain Difficulty sources and estimate error based on differences
- Step 2: Compare QUANDL Hash Rate vs Blockchain Hash Rate sources and estimate error based on differences
- Step 3: Estimate Bitcoin Block Height (Total Blocks) using different methods in the most accurate way possible
QUANDL doesn't provide block time data, but we can calculate it using the Hash Rate approximation formula:
estimated Hash rate/sec H = 2^32 * D / T, where D - Difficulty, T - block time, sec
1. block time (T) can be derived from the formula, since we already know Difficulty (D) and Hash Rate (H) from QUANDL
2. using block time (T) we can estimate daily blocks as daily time / block time
3. block height (total blocks) = cumulative sum of daily blocks of all bars on the chart (that's why having no gaps is important)
Notes:
- This code uses Pinescript v3 compatibility framework
- hash rate is in THash/s, although QUANDL falsely states in description GHash/s! THash = 1000 GHash
- you can't read files, can only embed/hardcode raw data in script
- both QUANDL and Blockchain sources have no gaps
- QUANDL and Blockchain series are different in the following ways:
- all QUANDL data is already shifted 1 bar into the future, i.e. prev day's value is shown as cur day's value => Blockchain data must be shifted 1 bar forward to match
- all QUANDL diff data > 1 bn (10^12) are truncated and have last 1-2 digits as zeros, unlike Blockchain data => must multiply both values by 0.01 and floor/round the results
- QUANDL sometimes rounds, other times truncates those 1-2 last zero digits to get the 3rd last digit => must use both floor/round
- you can only shift sequences forward into the future (right), not back into the past (left) using positive offset => only Blockchain source can be shifted
- since total_blocks is already a cumulative sum of all prev values on each bar, total_error must be simple delta, can't be also int(cum()) or incremental
- all Blockchain values and total_error are na outside the range - move you mouse cursor on the last bar/inside the range to see them
TLDR, ver 1.0 Conclusion:
QUANDL/Blockchain Difficulty source differences don't affect total blocks estimate, total error <= 1 block with avg 150 blocks/day is negligible
Both QUANDL/Blockchain Difficulty sources are equally valid and can be used in calculations. QUANDL is a relatively good stand in for Blockchain industry standard data.
Links:
QUANDL difficulty source: www.quandl.com
QUANDL hash rate source: www.quandl.com
Blockchain difficulty source (export data as csv): www.blockchain.com
Dual_Spread_FTX[Schmittie]//This script displays 2 spreads between FTX perpetuals contracts and futures contracts.
//In the settings, you can choose which curves to display for direct comparison.
//It is based on Thojdid's Multi-Spread script, but loads faster as there are only 2 coins
//An high-low range can be added
Gann High Low StrategyGann High Low is a moving average based trend indicator consisting of two different simple moving averages.
The Gann High Low Activator Indicator was described by Robert Krausz in a 1998 issue of Stocks & Commodities Magazine. It is a simple moving average SMA of the previous n period's highs or lows.
The indicator tracks both curves (of the highs and the lows). The close of the bar defines which of the two gets plotted.
Bitcoin Logarithmic Growth Curves for intraday usersI wish to thank @Quantadelic who created this great indicator and leaving it open for others to improve.
I have made changes to make it user-friendly for the intraday traders.
The changes made have been;
1. Compartmentalized each area of the major Fibonacci level;
2. Added minor Fibonacci levels;
3. Color-coded the support and resistance levels, for better viewing;
4. Zoned each area of the major Fibonacci level; and
5. Created a time-frame display period for quicker loading of the indicator.
I have removed a few things to allow the indicator to run quicker;
1. Future projections; and
2. The major higher levels of the Fibonacci, which may be useful when Bitcoin reaches 100k.
Enjoy
Hull SuiteHull is its extremely responsive and smooth moving average created by Alan Hull in 2005.
Minimal lag and smooth curves made HMA extremely popular TA tool.
alanhull.com
Script was made to regroup multiple hull variants in one indicator,maintaining flexible customization and intuitive visualization
Option to chose between 3 Hull variations
Option to chose between 2 visualization modes ( Bands or single line)
Option to Paint hull and/or candlesticks according to hulls trend
Shortcut for personalizing Line/band thickness,instead of changing every object manually ,there is global option in inputs
HMA
THMA ( 3HMA)
EHMA
HMA:
Alan Hull
EHMA:
Slower than hull by default.
Raudys, Aistis & Lenčiauskas, Vaidotas & Malčius, Edmundas. (2013). Moving Averages for Financial Data Smoothing ( 403. 34-45. 10.1007/978-3-642-41947-8_4.) Vilnius University, Faculty of Mathematics and Informatics
3HMA (THMA) :
Documentation on link below
alexgrover
Gann High LowGann High Low is a moving average based trend indicator consisting of two different simple moving averages.
The Gann High Low Activator Indicator was described by Robert Krausz in a 1998 issue of Stocks & Commodities Magazine. It is a simple moving average SMA of the previous n period's highs or lows.
The indicator tracks both curves (of the highs and the lows). The close of the bar defines which of the two gets plotted.
This version is showing the channel that needs to be broken if the trend is going to be changed, and it allows you to chose from the 4 basic averages type for calculation (by definition, Gann High Low Activator uses only simple moving average, but some other averages can give you results that are probably more acceptable for trading in some conditions).
Increasing HPeriod and decreasing LPeriod better for short trades, vice versa for long positions.
Tillson T3 Moving Average MTFMULTIPLE TIME FRAME version of Tillson T3 Moving Average Indicator
Developed by Tim Tillson, the T3 Moving Average is considered superior -1.60% to traditional moving averages as it is smoother, more responsive and thus performs better in ranging market conditions as well. However, it bears the disadvantage of overshooting the price as it attempts to realign itself to current market conditions.
It incorporates a smoothing technique which allows it to plot curves more gradual than ordinary moving averages and with a smaller lag. Its smoothness is derived from the fact that it is a weighted sum of a single EMA , double EMA , triple EMA and so on. When a trend is formed, the price action will stay above or below the trend during most of its progression and will hardly be touched by any swings. Thus, a confirmed penetration of the T3 MA and the lack of a following reversal often indicates the end of a trend.
The T3 Moving Average generally produces entry signals similar to other moving averages and thus is traded largely in the same manner. Here are several assumptions:
If the price action is above the T3 Moving Average and the indicator is headed upward, then we have a bullish trend and should only enter long trades (advisable for novice/intermediate traders). If the price is below the T3 Moving Average and it is edging lower, then we have a bearish trend and should limit entries to short. Below you can see it visualized in a trading platform.
Although the T3 MA is considered as one of the best swing following indicators that can be used on all time frames and in any market, it is still not advisable for novice/intermediate traders to increase their risk level and enter the market during trading ranges (especially tight ones). Thus, for the purposes of this article we will limit our entry signals only to such in trending conditions.
Once the market is displaying trending behavior, we can place with-trend entry orders as soon as the price pulls back to the moving average (undershooting or overshooting it will also work). As we know, moving averages are strong resistance/support levels, thus the price is more likely to rebound from them and resume its with-trend direction instead of penetrating it and reversing the trend.
And so, in a bull trend, if the market pulls back to the moving average, we can fairly safely assume that it will bounce off the T3 MA and resume upward momentum, thus we can go long. The same logic is in force during a bearish trend .
And last but not least, the T3 Moving Average can be used to generate entry signals upon crossing with another T3 MA with a longer trackback period (just like any other moving average crossover). When the fast T3 crosses the slower one from below and edges higher, this is called a Golden Cross and produces a bullish entry signal. When the faster T3 crosses the slower one from above and declines further, the scenario is called a Death Cross and signifies bearish conditions.
I Personally added a second T3 line with a volume factor of 0.618 (Fibonacci Ratio) and length of 3 (fibonacci number) which can be added by selecting the box in the input section. traders can combine the two lines to have Buy/Sell signals from the crosses.
Developed by Tim Tillson
Tillson T3 Moving Average by KIVANÇ fr3762Developed by Tim Tillson, the T3 Moving Average is considered superior to traditional moving averages as it is smoother, more responsive and thus performs better in ranging market conditions as well. However, it bears the disadvantage of overshooting the price as it attempts to realign itself to current market conditions.
It incorporates a smoothing technique which allows it to plot curves more gradual than ordinary moving averages and with a smaller lag. Its smoothness is derived from the fact that it is a weighted sum of a single EMA , double EMA , triple EMA and so on. When a trend is formed, the price action will stay above or below the trend during most of its progression and will hardly be touched by any swings. Thus, a confirmed penetration of the T3 MA and the lack of a following reversal often indicates the end of a trend.
The T3 Moving Average generally produces entry signals similar to other moving averages and thus is traded largely in the same manner. Here are several assumptions:
If the price action is above the T3 Moving Average and the indicator is headed upward, then we have a bullish trend and should only enter long trades (advisable for novice/intermediate traders). If the price is below the T3 Moving Average and it is edging lower, then we have a bearish trend and should limit entries to short. Below you can see it visualized in a trading platform.
Although the T3 MA is considered as one of the best swing following indicators that can be used on all time frames and in any market, it is still not advisable for novice/intermediate traders to increase their risk level and enter the market during trading ranges (especially tight ones). Thus, for the purposes of this article we will limit our entry signals only to such in trending conditions.
Once the market is displaying trending behavior, we can place with-trend entry orders as soon as the price pulls back to the moving average (undershooting or overshooting it will also work). As we know, moving averages are strong resistance/support levels, thus the price is more likely to rebound from them and resume its with-trend direction instead of penetrating it and reversing the trend.
And so, in a bull trend, if the market pulls back to the moving average, we can fairly safely assume that it will bounce off the T3 MA and resume upward momentum, thus we can go long. The same logic is in force during a bearish trend .
And last but not least, the T3 Moving Average can be used to generate entry signals upon crossing with another T3 MA with a longer trackback period (just like any other moving average crossover). When the fast T3 crosses the slower one from below and edges higher, this is called a Golden Cross and produces a bullish entry signal. When the faster T3 crosses the slower one from above and declines further, the scenario is called a Death Cross and signifies bearish conditions.
I Personally added a second T3 line with a volume factor of 0.618 (Fibonacci Ratio) and length of 3 (fibonacci number) which can be added by selecting the box in the input section. traders can combine the two lines to have Buy/Sell signals from the crosses.
Developed by Tim Tillson
Topfinder Bottomfinder pivot matcher Midas- jayyMidas Technical Analysis: A VWAP Approach to Trading and Investing in Today’s Markets by
Andrew Coles, David G. Hawkins Copyright © 2011 by Andrew Coles and David G. Hawkins.
Appendix C: TradeStation Code for the MIDAS Topfinder/Bottomfinder Curves ported to tradingview
This code is used to assist in adjusting D volume to intersect pivot candle at a pivot candle when using this script: Top Bottom Finder Public version- Jayy found here:
The "n" number entered into the TB-F script is the topfinder/bottomfinder starting point or anchor
Be sure to enter the correct number in the "Topfinder bottomfinder initiation/anchor candle: 1 for CANDLE low - top finder, 2 for CANDLE high - bottom finder, 3 for CANDLE MIDPOINT (hl2) dialogue box
The location of the match point of the pivot candle is extremely important in the: "Match to PIVOT CANDLE: use 1 for CANDLE low, 2 for midtail of the candle below the BODY, 3 for candle BODY low, 4 for CANDLE HIGH, 5 for midpoint of candletail above body, 6 for candle BODY high". Do not
confuse body high with candle high. The body low will either be the candle open or close. The body high will be either the open or close.
If you expect a trend up the pivot candle is likely the low of the pivot candle ie 1 (2 and 3 are alternatives).
In a trend down the high of the pivot candle is often selected ie 4 (5 or 6 are alternatives)
If the candle body is aqua increase D volume if it is orange reduce D volume. Adjust iteratively until the candle body turns yellow. That will mean that the TB-F line passes through the pivot candle at the selected point.
Jayy
Vix FIX / StochRSI StrategyThis strategy is based off of Chris Moody's Vix Fix Indicator . I simply used his indicator and added some rules around it, specifically on entry and exits.
Rules :
Enter upon a filtered or aggressive entry
If there are multiple entry signals, allow pyramiding
Exit when there is Stochastic RSI crossover above 80
This works great on a number of stocks. I am keeping a list of stocks with decent Profit Factors and clean equity curves here .
Possible ways to use this:
Modify this script and setup alerts around the various entries
Use as is with different stocks or currency pairs
Modify entry / exit points to make it more profitable for even more symbols and currencies
UCS_Squeeze_Timing-V1There is an important information the Squeeze indicator is missing, which is the Pre Squeeze entry. While the Bollinger band begins to curves out of the KC, The breakout usually happens. There are many instances that the Squeeze indicator will fire, after the Major move, I cant blame the indicator, thats the nature (lagging) of all indicators, and we have to live with it.
Therefore pre-squeeze-fire Entry can be critical in timing your entry. Timing it too early could result in stoploss if it turns against you, ( or serious burn on options premium), because we never know when the squeeze will fire with the TTM squeeze, But now We know. Its a little timing tool. Managing position is critical when playing options.
I will code the timing signal when I get some time.
Updated Versions -
Hyper-Spectral Neural Flow [Pineify]Hyper-Spectral Neural Flow - Advanced Gaussian Kernel Trend Detection with Spectral Volatility Bands
Transform your chart analysis with a cutting-edge indicator that combines machine learning-inspired smoothing algorithms with stunning visual feedback systems for precise trend identification and market momentum visualization.
Overview
The Hyper-Spectral Neural Flow is a sophisticated technical analysis tool that implements Gaussian Kernel Regression smoothing to estimate the underlying price trend with minimal lag while providing dynamic volatility-based visual feedback through its signature "spectral aura" display. Unlike conventional moving averages or simple trend indicators, this tool adapts its smoothing characteristics based on localized price behavior, creating a neural-inspired pathway that represents the market's true trend direction.
The indicator's core calculation utilizes a 50-bar Gaussian window with customizable bandwidth parameters, allowing traders to balance between responsiveness and smoothness according to their trading style. Surrounding this core trend line are multi-layered spectral bands that expand and contract based on market volatility, measured through a combination of Mean Absolute Error (MAE) and user-defined multipliers.
Key Features
Gaussian Kernel Neural Core - A proprietary smoothing algorithm that calculates localized weighted averages using Gaussian distribution weights, providing superior noise reduction compared to traditional moving averages
Multi-Layered Spectral Aura - Four distinct volatility bands (inner/upper and inner/lower) that create a dynamic visual representation of market volatility and trend strength
Adaptive Gradient Fills - Color-gradient transparency that adjusts based on price position relative to the neural core, creating an energy field effect that visually communicates market momentum
Trend Pulse Markers - Automatic circular markers that appear precisely when the neural flow shifts direction, providing clear entry/exit signals
Dynamic Bar Coloring - Price bars that change color and transparency based on trend direction, enhancing visual pattern recognition
Real-Time Trend Calculation - Optimized 50-bar rolling window ensures responsive performance without excessive computational load
Customizable Alert System - Built-in alert conditions for neural flow direction changes
How It Works
The indicator's calculation engine operates on three distinct levels working in harmony:
Neural Core Calculation - For each bar, the algorithm computes a weighted average of the previous 50 bars using Gaussian kernel functions. The weight assigned to each historical bar follows a bell curve distribution, where more recent bars receive exponentially higher weights. The mathematical formula is: weight = exp(-(distance²) / (2 × bandwidth²)) , where the bandwidth parameter (default: 8.0) controls the smoothness sensitivity.
Volatility Band Derivation - The spectral bands are calculated using the Mean Absolute Error (MAE) between price and the neural core, smoothed over 50 periods and multiplied by a user-defined spectral range multiplier (default: 3.0). This creates four bands: outer upper (+1.0× MAE), inner upper (+0.5× MAE), inner lower (-0.5× MAE), and outer lower (-1.0× MAE).
Trend Direction Logic - The system determines trend direction by comparing the current neural core value to the previous bar's value. When the core rises, the bullish flow color activates; when it declines, the bearish flow color engages.
Trading Ideas and Insights
Trend Following - Use the neural core as your primary trend reference. When price is above the core with the bullish flow color active, look for long entry opportunities on pullbacks to the inner lower spectral band
Trend Reversal Detection - Watch for the trend pulse markers combined with price crossing the neural core. A bullish pulse appearing after a bearish phase, especially near the outer lower band, often signals a trend reversal
Volatility Contraction Plays - When the spectral bands narrow significantly (indicating low volatility), prepare for potential breakout trades as volatility expansion often follows consolidation periods
Support/Resistance Zones - The inner and outer spectral bands often act as dynamic support and resistance levels. Price rejection from these bands, combined with trend pulse markers, provides high-probability trade setups
Momentum Assessment - Strong trends show the spectral bands expanding in the direction of the move while maintaining consistent separation. Converging bands suggest momentum weakening
How Multiple Indicators Work Together
The true power of Hyper-Spectral Neural Flow lies in the synergistic integration of its components:
The Gaussian Kernel Core provides the foundational trend direction, eliminating noise while preserving genuine price movements
The Spectral Bands add context by showing volatility-adjusted price boundaries, preventing premature entries during low-volatility conditions
The Gradient Fill System offers immediate visual feedback about trend strength—wider, more opaque bands indicate stronger trends, while narrow, transparent bands suggest weakness
The Trend Pulse Markers serve as confirmation signals, ensuring traders don't act on minor core fluctuations but only on meaningful directional changes
This multi-component approach means each element validates the others: a trend pulse marker appearing while price is at an outer band and the spectral aura is expanding provides three independent confirmations of a significant trading opportunity .
Unique Aspects
Machine Learning Foundation - Unlike most TradingView indicators based on standard technical analysis formulas, this implements concepts from Gaussian Process Regression, a technique used in advanced machine learning applications
Visual Hierarchy - The layered design (core line → inner bands → outer bands) creates a natural visual priority system that guides the eye from the most important element (trend direction) to secondary context (volatility levels)
Adaptive Smoothing - The Gaussian bandwidth parameter allows traders to morph the indicator between a short-term scalping tool (lower values) and a long-term trend following system (higher values) without changing the underlying algorithm
Neuro-Aesthetic Design - The visual language mimics neural network imagery and spectrographic displays, making complex data intuitively understandable through association with familiar scientific visualization
How to Use
Add the indicator to your chart from the indicators library and overlay it on your price data
Begin with default settings (Neural Bandwidth: 8.0, Spectral Range: 3.0) to observe the indicator's behavior on your timeframe
For trend following: Only take long trades when the neural core is rising and showing the bullish flow color; only take short trades when the core is declining with bearish flow color
For entry timing: Use the inner spectral bands as pullback entry zones during strong trends—the inner lower band for longs, the inner upper band for shorts
For stop placement: Consider placing stops just beyond the outer spectral band opposite your trade direction
For trend confirmation: Wait for trend pulse markers to appear before entering positions, especially when trading counter-trend reversals
For exit signals: Consider partial profits when price reaches the outer band in the direction of your trade, or when a trend pulse marker signals a potential direction change
Customization
Neural Bandwidth (1.0 to 20.0) - Increase for smoother, slower signals suitable for swing trading (try 12.0-15.0 on daily charts); decrease for more responsive signals for scalping or day trading (try 3.0-5.0 on intraday timeframes)
Spectral Range (0.5 to 10.0) - Higher values widen the volatility bands, resulting in fewer signals but potentially larger winning trades; lower values create tighter bands for more frequent signals but increased false signals during volatility spikes
Bullish/Bearish Flow Colors - Customize to match your chart aesthetic or preference; consider using colors that contrast well with your background for optimal visibility
Aura Opacity (0 to 100) - Adjust to control the prominence of the spectral gradient fills; lower values make the chart less cluttered, higher values emphasize the volatility expansion/contraction cycles
Trend Pulse Marks - Disable if you prefer a cleaner visual and plan to rely solely on core direction and band relationships for signals
Conclusion
The Hyper-Spectral Neural Flow represents a paradigm shift in trend indicator design, bridging the gap between rigorous statistical methodology and intuitive visual communication. By implementing Gaussian kernel regression—typically found in advanced machine learning applications—within an accessible TradingView indicator, it offers traders a professional-grade trend detection tool that doesn't sacrifice usability for sophistication.
Whether you're a systematic trader who relies on objective, rule-based signals, a discretionary trader who values contextual market information, or a quantitative analyst seeking robust trend estimation, this indicator provides the flexibility to adapt to your methodology while maintaining mathematical rigor in its core calculations.
The integration of volatility-based spectral bands with the neural core creates a complete trading framework in a single indicator: trend identification, volatility assessment, entry timing guidance, and trend change signals—all unified through a cohesive visual language that makes complex data immediately actionable. By understanding how the Gaussian smoothing adapts to market conditions and how the spectral bands breathe with volatility, traders gain deeper insight into market structure beyond simple price movement.
Add the Hyper-Spectral Neural Flow to your chart analysis toolkit and experience the difference that machine learning-inspired indicators can make in your trading decisions.
FX Rate Bias US vs EU 2YFX Rate Bias – US vs EU (2Y)
This indicator implements a rate-differential based macro bias model using the 2-year government bond yield spread between the United States and Germany.
The methodology focuses on the short end of the yield curve, which primarily reflects central bank expectations rather than long-term inflation or risk premiums.
By applying light smoothing and a zero-line regime framework, the script classifies market conditions into USD rate advantage or EUR rate advantage states.
Calculation logic:
Retrieves daily 2Y sovereign yields for the US and Germany
Computes the yield differential (US − DE)
Applies optional smoothing to reduce noise
Uses the zero line as a regime boundary to define relative monetary bias
Practical use:
This tool is designed to provide directional macro context for FX analysis, particularly for EURUSD.
It helps traders align technical setups with prevailing interest rate expectations, and is not intended as a standalone signal or timing indicator.
15-Minute ORB Breakout Strategy with VWAP and Volume Filters# 15-Minute ORB Breakout Strategy with VWAP and Volume Filters
## Overview
This strategy implements the 15-minute Opening Range Breakout (ORB) methodology for NASDAQ futures, enhanced with session-anchored VWAP, volume confirmation, and candle strength analysis. The ORB approach waits for the first 15 minutes of the trading session to establish a range, then trades breakouts with defined risk management.
This implementation is based on rules described in a YouTube tutorial by Bull Barbie: www.youtube.com
The strategy was systematically coded and backtested to evaluate performance over an extended period.
**Backtest Disclosure:** Over 1,354 trades from 2010-2026, this systematic implementation produced negative returns. Discretionary traders may achieve different results through real-time adjustments not captured in systematic rules.
---
## How It Works
### Opening Range Calculation
The strategy identifies the high and low of the first 15 minutes after the New York open (first 3 candles on a 5-minute chart). These levels become the breakout triggers for the session.
### Entry Logic
- **Long Entry:** Price closes above the ORB High while meeting all filter conditions
- **Short Entry:** Price closes below the ORB Low while meeting all filter conditions
### Exit Logic
- **Take Profit:** 1x the ORB range beyond the breakout level (approximately 1:1 risk-reward)
- **Stop Loss:** Opposite side of the ORB range
- **Breakeven:** Stop moves to entry when price reaches 50% of the take profit distance
- **Session Close:** All positions closed at end of trading session
### Filters
All filters are toggleable:
1. **Session VWAP Filter:** Price must be above VWAP with upward slope for longs (below with downward slope for shorts). VWAP is anchored to session open and resets daily.
2. **Volume Filter:** Breakout bar must exceed minimum volume threshold (default: 2,500 contracts) to confirm participation.
3. **Candle Strength Filter:** Close must be in the top 30% of the bar range for longs (bottom 30% for shorts), indicating conviction rather than absorption.
---
## Backtest Results
**Instrument:** MNQ (Micro NASDAQ)
**Timeframe:** 5-minute
**Period:** 2010-2026
**Session:** 09:30 - 12:00 ET (Morning)
| Metric | Value |
|--------|-------|
| Total Trades | 1,354 |
| Win Rate | 50.07% |
| Profit Factor | 0.833 |
| Net P&L | -$11,916 (-23.83%) |
| Max Drawdown | $13,119 (26.21%) |
| Avg Win | +0.30% |
| Avg Loss | -0.37% |
| Expected Payoff | -$8.80/trade |
| Long Win Rate | 52.25% (360/689) |
| Short Win Rate | 47.82% (318/665) |
---
## Strategy Properties
These settings match the published backtest:
| Property | Value |
|----------|-------|
| Initial Capital | $50,000 USD |
| Position Size | 1 contract (fixed) |
| Commission | $4.00 per contract (round-trip) |
| Slippage | 2 ticks |
| Margin | 1% (NinjaTrader intraday reference) |
| Pyramiding | Disabled |
**Instrument Note:** MNQ (Micro NASDAQ) was selected because realistic account sizes ($25,000-$50,000) face margin constraints with full NQ contracts during drawdown periods.
---
## Settings Guide
### Main Settings
- **ORB Bars:** Number of bars defining the opening range (3 = 15 minutes on 5-min chart)
- **Trading Session:** Time window for trading (tested: 0930-1200 ET)
- **Take Profit:** Multiple of ORB range for target (1.0 = full range)
- **Breakeven Trigger:** Distance to move stop to entry (0.5 = halfway to TP)
- **Max Trades Per Day:** Daily trade limit (default: 2)
### VWAP Filter
- **Use VWAP Filter:** Enable/disable session VWAP confirmation
- **VWAP Slope Lookback:** Bars to measure VWAP direction (default: 5)
- **Min VWAP Slope:** Minimum slope in points (default: 0.5)
### Volume Filter
- **Use Volume Filter:** Enable/disable volume confirmation
- **Min Breakout Volume:** Minimum contracts required (default: 2,500)
### Candle Strength
- **Use Candle Strength Filter:** Enable/disable close position analysis
- **Min Candle Strength:** Required close position within bar (0.7 = top/bottom 30%)
---
## Visual Elements
- **Orange Background:** ORB forming period (first 15 minutes)
- **Green Background:** Active trading session
- **Green/Red Lines:** ORB High and Low levels
- **VWAP Line:** Color indicates slope direction (green=up, red=down, gray=flat)
- **White Line:** Trade entry price
- **Lime/Red Lines:** Take profit and stop loss levels
- **Orange Line:** Breakeven trigger level
- **Blue Background:** Breakeven activated
- **Triangle Markers:** Candle strength indicators
---
## How to Use
1. Apply to MNQ or NQ on a 5-minute chart
2. Wait for the ORB forming period (orange background) to complete
3. Monitor breakouts above/below ORB levels
4. Check VWAP color for trend alignment
5. Strategy enters automatically when conditions align
---
## Limitations
1. **Systematic vs. Discretionary:** This backtest captures only the mechanical rules. Experienced traders may apply real-time judgment (reading price action, avoiding certain setups, scaling in/out) that improves results but cannot be systematically coded.
2. **Average Loss Exceeds Average Win:** The 0.37% average loss versus 0.30% average win creates negative expectancy even with ~50% win rate.
3. **Commission Impact:** $10,832 in commissions over the test period affects net returns.
4. **Market Regime Variation:** The equity curve shows profitable periods (2023-2025) alongside extended drawdowns, suggesting regime-dependent performance.
5. **Sample Considerations:** While 1,354 trades provides statistical significance, results may vary across different time periods or market conditions.
---
## Research Notes
This strategy was built following rules from Bull Barbie's ORB tutorial video. The systematic backtest could not reproduce the performance figures mentioned in that content. This does not mean the approach is without merit—discretionary execution, trade selection, and real-time adjustments likely play significant roles that systematic backtesting cannot capture.
Traders interested in ORB strategies should consider this as a starting framework for their own research and optimization.
---
## Reference
Original strategy concept: Bull Barbie - "Battle-Tested 15-Minute ORB Trading Strategy for Nasdaq—Rules That Actually Work"
www.youtube.com
