RSI Oscillator by mattzabRSI-Oscillator is designed to be highly visual, based on strategies that recognize the RSI above 50 to be positive strength, and below 50 to be weakness.
Midpoint is 50, above is blue, below is red.
Komut dosyalarını "黄金近50年的走势" için ara
BTC 1D Alerts V1This script contains a variety of key indicator for bitcoin all-in-one and they can be activated individually in the menu. These are meant to be used on the 1D chart for Bitcoin.
1457 Day Moving Average: the bottom of the bitcoin price and arguably the rock bottom price target.
Ichimoku Cloud: a common useful indicator for bitcoin support and resistance.
350ma fibs (21 8 5 3 2 and 1.6) : Signify the tops of each logarthmic rise in bitcoin price. They are generally curving higher over the long term. For halvening #3, the predicted market crash would be after hitting the 350ma x3 fib. Also the 350 ma / 111 ma cross signifies bull market top within about 3 days as well. Using the combination of the 350ma fibs and the 350/111 crosses, reasonably identify when market top is about to occur.
50,120,200 ma: Common moving averages that bitcoin retests during bull market runs. Also, the 50/200 golden and death crosses.
1D EMA Superguppy Ribbons: green = bull market, gray is indeterminate, red = bear market. Very high specificity indicator of bull runs, especially for bitcoin. You can change to 3D candle for even more specificity for a bull market start. Use the 1W for even more specificity. 1D Superguppy is recommended for decisionmaking.
1W EMA21: a very good moving average programmed to be shown on both the daily and weekly candle time. Bitcoin commonly corrects to this repeatedly during past bull runs. Acts as support during bull run and resistance during a bear market.
Steps to identifying a bull market:
1. 50/200 golden cross
2. 1D EMA superguppy green
3. 3D EMA superguppy green (if you prefer more certainty than step 2).
4. Hitting the 1W EMA21 and bouncing off during the bull run signifies corrections.
Once a bull market is identified,
Additional recommended buying and selling techniques:
Indicators:
- Fiblines - to determine retracements from peaks (such as all time high or recent highs)
- Stochastic RSI - 1d, 3d, and 1W SRSI are great time to buy, especially the 1W SRSI which comes much less frequently.
- volumen consolidado - for multi exchange volumes compiled into a single line. I prefer buying on the lowest volume days which generally coincide with dips.
- MACD - somewhat dubious utility but many algorithms are programmed to buy or sell based on this.
Check out the Alerts for golden crosses and 350ma Fib crosses which are invaluable for long term buying planning.
I left this open source so that all the formulas can be understood and verified. Much of it hacked together from other sources but all indicators that are fundamental to bitcoin. I apologize in advance for not attributing all the articles and references... but then again I am making no money off of this anyway.
Fischy Bands (multiple periods)Just a quick way to have multiple periods. Coded at (14,50,100,200,400,600,800). Feel free to tweak it. Default is all on, obviously not as usable! Try just using 14, and 50.
This was generated with javascript for easy templating.
Source:
```
const periods = ;
const generate = (period) => {
const template = `
= bandFor(${period})
plot(b${period}, color=colorFor(${period}, b${period}), linewidth=${periods.indexOf(period)+1}, title="BB ${period} Basis", transp=show${period}TransparencyLine)
pb${period}Upper = plot(b${period}Upper, color=colorFor(${period}, b${period}), linewidth=${periods.indexOf(period)+1}, title="BB ${period} Upper", transp=show${period}TransparencyLine)
pb${period}Lower = plot(b${period}Lower, color=colorFor(${period}, b${period}), linewidth=${periods.indexOf(period)+1}, title="BB ${period} Lower", transp=show${period}TransparencyLine)
fill(pb${period}Upper, pb${period}Lower, color=colorFor(${period}, b${period}), transp=show${period}TransparencyFill)`
console.log(template);
}
console.log(`//@version=4
study(shorttitle="Fischy BB", title="Fischy Bands", overlay=true)
stdm = input(1.25, title="stdev")
bandFor(length) =>
src = hlc3
mult = stdm
basis = sma(src, length)
dev = mult * stdev(src, length)
upper = basis + dev
lower = basis - dev
`);
periods.forEach(e => console.log(`show${e} = input(title="Show ${e}?", type=input.bool, defval=true)`));
periods.forEach(e => console.log(`show${e}TransparencyLine = show${e} ? 20 : 100`));
periods.forEach(e => console.log(`show${e}TransparencyFill = show${e} ? 80 : 100`));
console.log('\n');
console.log(`colorFor(period, series) =>
c = period == 14 ? color.white :
period == 50 ? color.aqua :
period == 100 ? color.orange :
period == 200 ? color.purple :
period == 400 ? color.lime :
period == 600 ? color.yellow :
period == 800 ? color.orange :
color.black
c
`);
periods.forEach(e => generate(e))
```
Principe de NY - Rodrigo CohenIndicador criado baseado nas informações de fechamento de bollinger, seguindo o Setup Principe de NY sugerido pelo Analista Rodrigo Cohen, ainda em fase de testes para aprimorar a eficácia do setup
*Considerado apenas Fechamento fora e nesta condição + 50 pontos para entrada sendo assim
Fechamentos com Candles em Vermelho soma 50 pontos e entra vendido
Fechamentos com Candles em Verde soma 50 pontos e entra comprado
O setup pelo que percebi é composto de mais detalhes, aos quais quando tiver acesso realizarei as atualizações devidas
Também estão disponíveis versões de indicadores para Forex
Em breve posto a lista completa com os resultados no MQL5
General Filter Estimator-An Experiment on Estimating EverythingIntroduction
The last indicators i posted where about estimating the least squares moving average, the task of estimating a filter is a funny one because its always a challenge and it require to be really creative. After the last publication of the 1LC-LSMA , who estimate the lsma with 1 line of code and only 3 functions i felt like i could maybe make something more flexible and less complex with the ability to approximate any filter output. Its possible, but the methods to do so are not something that pinescript can do, we have to use another base for our estimation using coefficients, so i inspired myself from the alpha-beta filter and i started writing the code.
Calculation and The Estimation Coefficients
Simplicity is the key word, its also my signature style, if i want something good it should be simple enough, so my code look like that :
p = length/beta
a = close - nz(b ,close)
b = nz(b ,close) + a/p*gamma
3 line, 2 function, its a good start, we could put everything in one line of code but its easier to see it this way. length control the smoothing amount of the filter, for any filter f(Period) Period should be equal to length and f(Period) = p , it would be inconvenient to have to use a different length period than the one used in the filter we want to estimate (imagine our estimation with length = 50 estimating an ema with period = 100) , this is where the first coefficients beta will be useful, it will allow us to leave length as it is. In general beta will be greater than 1, the greater it will be the less lag the filter will have, this coefficient will be useful to estimate low lagging filters, gamma however is the coefficient who will estimate lagging filters, in general it will range around .
We can get loose easily with those coefficients estimation but i will leave a coefficients table in the code for estimating popular filters, and some comparison below.
Estimating a Simple Moving Average
Of course, the boxcar filter, the running mean, the simple moving average, its an easy filter to use and calculate.
For an SMA use the following coefficients :
beta = 2
gamma = 0.5
Our filter is in red and the moving average in white with both length at 50 (This goes for every comparison we will do)
Its a bit imprecise but its a simple moving average, not the most interesting thing to estimate.
Estimating an Exponential Moving Average
The ema is a great filter because its length times more computing efficient than a simple moving average. For the EMA use the following coefficients :
beta = 3
gamma = 0.4
N.B : The EMA is rougher than the SMA, so it filter less, this is why its faster and closer to the price
Estimating The Hull Moving Average
Its a good filter for technical analysis with tons of use, lets try to estimate it ! For the HMA use the following coefficients :
beta = 4
gamma = 0.85
Looks ok, of course if you find better coefficients i will test them and actualize the coefficient table, i will also put a thank message.
Estimating a LSMA
Of course i was gonna estimate it, but this time this estimation does not have anything a lsma have, no moving average, no standard deviation, no correlation coefficient, lets do it.
For the LSMA use the following coefficients :
beta = 3.5
gamma = 0.9
Its far from being the best estimation, but its more efficient than any other i previously made.
Estimating the Quadratic Least Square Moving Average
I doubted about this one but it can be approximated as well. For the QLSMA use the following coefficients :
beta = 5.25
gamma = 1
Another ok estimate, the estimate filter a bit more than needed but its ok.
Jurik Moving Average
Its far from being a filter that i like and its a bit old. For the comparison i will use the JMA provided by @everget described in this article : c.mql5.com
For the JMA use the following coefficients :
for phase = 0
beta = pow*2 (pow is a parameter in the Jma)
gamma = 0.5
Here length = 50, phase = 0, pow = 5 so beta = 10
Looks pretty good considering the fact that the Jma use an adaptive architecture.
Discussion
I let you the task to judge if the estimation is good or not, my motivation was to estimate such filters using the less amount of calculations as possible, in itself i think that the code is quite elegant like all the codes of IIR filters (IIR Filters = Infinite Impulse Response : Filters using recursion) .
It could be possible to have a better estimate of the coefficients using optimization methods like the gradient descent. This is not feasible in pinescript but i could think about it using python or R.
Coefficients should be dependant of length but this would lead to a massive work, the variation of the estimation using fixed coefficients when using different length periods is just ok if we can allow some errors of precision.
I dont think it should be possible to estimate adaptive filter relying a lot on their adaptive parameter/smoothing constant except by making our coefficients adaptive (gamma could be)
So at the end ? What make a filter truly unique ? From my point of sight the architecture of a filter and the problem he is trying to solve is what make him unique rather than its output result. If you become a signal, hide yourself into noise, then look at the filters trying to find you, what a challenging game, this is why we need filters.
Conclusion
I wanted to give a simple filter estimator relying on two coefficients in order to estimate both lagging and low-lagging filters. I will try to give more precise estimate and update the indicator with new coefficients.
Thanks for reading !
BTC Volume Index [v2018-11-21] @ LekkerCryptisch.nlIndicates the volume trend:
~50 = short term volume is the same as long term volume
> 50 = short term volume is higher than long term volume (i.e. trend is rising volume)
< 50 = short term volume is lower than long term volume (i.e. trend is declining volume)
Reverse Engineered RSI - Key Levels + MTFThis indicator overlays 5 Reverse Engineered RSI (RERSI) levels on your main chart window.
The RERSI was first developed by Giorgos Siligardos in the June 2003 issue of Stocks and Commodities Magazine. HPotter provided the initial implementation - from which this script is derived - so all credit to them (see: ).
In simple terms, RERSI plots lines on the price chart that reflect levels of the RSI . E.g. if you set up a RERSI line at a level of 50, then price will touch that line when the standard RSI indicator reads 50. Hopefully that makes sense, but compare the two if it doesn't.
Why is the RERSI useful if it's just plotting RSI values? Well, it simplifies things, and enables you to get a clearer picture of trend direction, RSI support and resistance levels, RSI trading signals, and it keeps your chart window uncluttered.
I've set up 5 RERSI lines to be plotted: Overbought and Oversold Levels, a Middle Level (generally leave this at 50), and then Down/Up Trend Lines. The latter two are loosely based on the work of Constance Brown (and they in turn were influenced by Andrew Brown), who posited that RSI doesn't breach certain levels during trends (e.g. 40-50 is often a support level during an uptrend).
Play around with the levels, and the RSI Length, to see how your particular market reacts, and where key levels may lie. Remember, this isn't meant as a stand-alone system (although I think there's potential to use it as such, especially with price action trading - which I guess wouldn't make it stand-alone then!!), and works best with confirmation from other sources.
Oh, and there's MTF capability, because I think that's useful for all indicators.
Any queries, please let me know.
Cheers,
RJR
Better RSI with bullish / bearish market cycle indicator This script improves the default RSI. First. it identifies regions of the RSI which are oversold and overbought by changing the color of RSI from white to red. Second, it adds additional reference lines at 20,40,50,60, and 80 to better gauge the RSI value. Finally, the coolest feature, the middle 50 line is used to indicate which cycle the price is currently at. A green color at the 50 line indicates a bullish cycle, a red color indicators a bearish cycle, and a white color indicates a neutral cycle.
The cycles are determined using the RSI as follows:
if RSI is overbought, cycle switches to bullish until RSI falls below 40, at which point it becomes neutral
if RSI is oversold, cycle switches bearish until RSI rises above 60, at which point it becomes neutral
a neutral cycle is exited at either overbought or oversold conditions
Very useful, please give it a try and let me know what you think
ACM22 not repaintedДелал данный скрипт для FORTS.Идеально подойдет тем,кто использует трейлинг стопы.В основе стратегии лежит RSI.Как по мне,хорошая вещь для проверки стратегии и ее оптимизиации.На скрине 50 контрактов,так что не сильно радуйтесь,а просто делите на 50 и получите показатели на 1 контракт.
Script make for futures on MICEX.U can change paramets of RSI,traling stop and stop loss .On a ps 50 futures USDollar-russian ruble.Use for testing and optimisation.
Inertia Indicator The inertia indicator measures the market, stock or currency pair momentum and
trend by measuring the security smoothed RVI (Relative Volatility Index).
The RVI is a technical indicator that estimates the general direction of the
volatility of an asset.
The inertia indicator returns a value that is comprised between 0 and 100.
Positive inertia occurs when the indicator value is higher than 50. As long as
the inertia value is above 50, the long-term trend of the security is up. The inertia
is negative when its value is lower than 50, in this case the long-term trend is
down and should stay down if the inertia stays below 50
GC RSI Columns V2016This is a basic RSI indicator but in column format.I had been using this for a while and it gives a nice visual representation of trend change by changing color of the column.
Base line is 50 level. Anything above 50 is buy opportunity and below 50 is sell opportunity . Try it on higher time frames and see the results.
Example on chart above.
Note: i published it on demand. many folks were asking me for this ,since it(column rsi) was not available in public indicators
Golden Cross, SMA 200 Moving Average Strategy (by ChartArt)This famous moving average strategy is very easy to follow to decide when to buy (go long) and when to take profit.
The strategy goes long when the faster SMA 50 (the simple moving average of the last 50 bars) crosses above the slower SMA 200. Orders are closed when the SMA 50 crosses below the SMA 200. This simple strategy does not have any other stop loss or take profit money management logic. The strategy does not short and goes long only!
Here is an article explaining the "golden cross" strategy in more detail:
www.stockopedia.com
On the S&P 500 index (symbol "SPX") this strategy worked on the daily chart 81% since price data is available since 1982. And on the DOW Jones Industrial Average (symbol "DOWI") this strategy worked on the daily chart 55% since price data is available since 1916. The low number of trades is in both cases not statistically significant though.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
Forex Master v4.0 (EUR/USD Mean-Reversion Algorithm)DESCRIPTION
Forex Master v4.0 is a mean-reversion algorithm currently optimized for trading the EUR/USD pair on the 5M chart interval. All indicator inputs use the period's closing price and all trades are executed at the open of the period following the period where the trade signal was generated.
There are 3 main components that make up Forex Master v4.0:
I. Trend Filter
The algorithm uses a version of the ADX indicator as a trend filter to trade only in certain time periods where price is more likely to be range-bound (i.e., mean-reverting). This indicator is composed of a Fast ADX and a Slow ADX, both using the same look-back period of 50. However, the Fast ADX is smoothed with a 6-period EMA and the Slow ADX is smoothed with a 12-period EMA. When the Fast ADX is above the Slow ADX, the algorithm does not trade because this indicates that price is likelier to trend, which is bad for a mean-reversion system. Conversely, when the Fast ADX is below the Slow ADX, price is likelier to be ranging so this is the only time when the algorithm is allowed to trade.
II. Bollinger Bands
When allowed to trade by the Trend Filter, the algorithm uses the Bollinger Bands indicator to enter long and short positions. The Bolliger Bands indicator has a look-back period of 20 and a standard deviation of 1.5 for both upper and lower bands. When price crosses over the lower band, a Long Signal is generated and a long position is entered. When price crosses under the upper band, a Short Signal is generated and a short position is entered.
III. Money Management
Rule 1 - Each trade will use a limit order for a fixed quantity of 50,000 contracts (0.50 lot). The only exception is Rule
Rule 2 - Order pyramiding is enabled and up to 10 consecutive orders of the same signal can be executed (for example: 14 consecutive Long Signals are generated over 8 hours and the algorithm sends in 10 different buy orders at various prices for a total of 350,000 contracts).
Rule 3 - Every order will include a bracket with both TP and SL set at 50 pips (note: the algorithm only closes the current open position and does not enter the opposite trade once a TP or SL has been hit).
Rule 4 - When a new opposite trade signal is generated, the algorithm sends in a larger order to close the current open position as well as open a new one (for example: 14 consecutive Long Signals are generated over 8 hours and the algorithm sends in 10 different buy orders at various prices for a total of 350,000 contracts. A Short Signal is generated shortly after the 14th Long Signal. The algorithm then sends in a sell order for 400,000 contracts to close the 350,000 contracts long position and open a new short position of 50,000 contracts).
RSI-EMA IndicatorThis indicator calculates and plots 2 separate EMAs of the RSI. The default settings below work great on SPX/SPY daily chart. General rule is if an EMA is above 50, the stock's near term outlook is bullish. If an EMA is below 50, the near term outlook is bearish. Personally, I like to use a fast EMA as a buy signal and a slow EMA as a sell signal.
Default settings:
RSI = 50
EMA1 = 100
EMA2 = 200
High-Low Index [LazyBear]-- Fixed ---
Source: pastebin.com
Fixes an issue with "Combined" mode, using wrong symbols.
--- Original ---
The High-Low Index is a breadth indicator based on Record High Percent, which is based on new 52-week highs and new 52-week lows.
Readings below 50 indicate that there were more new lows than new highs. Readings above 50 indicate that there were more new highs than new lows. 0 indicates there were zero new highs (0% new highs). 100 indicates there was at least 1 new high and no new lows (100% new highs). 50 indicates that new highs and new lows were equal (50% new highs).
Readings consistently above 70 usually coincide with a strong uptrend. Readings consistently below 30 usually coincide with a strong downtrend.
More info:
stockcharts.com
List of my public indicators: bit.ly
List of my app-store indicators: blog.tradingview.com
Just noticed @Greeny has already published this -> Linking it here.
TimWest Long Short FiltersTimWest Long Short Filters
Indicator Has 3 Separate Filters that Create Green(Bullish) or Red(Bearish) BackGround Highlights
If Price is Above or Below a certain LookBack Period - Tim Defaults to 63 on Daily Chart to Quickly View if Price is Above or Below it’s Price 1 Quarter Ago.
A Simple Moving Average Filter - Tim Defaults to 50 SMA and 200 SMA also known as the “Golden Cross”.
A Exponential Moving Average Filter - For Those Who Want To View Shorter Term Market Swings. Defaults to 50 EMA and 100 EMA used By Chuck Hughes, 7 Time World Trading Champion. Chuck Claims the 50/100 EMA's Show the Earliest Change in Market Direction the Equal - Sustainable Moves
Inputs Tab has Checkboxes to Turn On/Off any of the 3 Filters Above.
Reference Chart Post www.tradingview.com
3 projection Indicators - PBands, PO & PBAll these indicators are by Mel Widner.
Projection Bands :
-------------------------------------------------------
These project market data along the trend with the maxima and minima of the projections defining the band. The method provides a way to signal potential direction changes relative to the trend. Usage is like any other trading band.
Projection Oscillator :
-------------------------------------------------------
This indicates the relative position of price with in the bands. It fluctuates between the values 0 to 100. You can configure the "basis" to make it oscillate around a specific value (for ex., basis=50 will make it oscillate between +50 and -50). EMA of PO (length configurable, default is 5) is plotted as a signal line. There is also an option to plot the difference (oscillator - signal), just like MACD histogram. When you see a divergence in this oscillator, remember that it just indicates a potential movement with in the band (for ex., a bullish divergence shown may cause the price to cross the median and move up to the top band).
Projection Bandwidth :
-------------------------------------------------------
This shows the % width of the projection bands. A trend reversal is signaled by a high value. Low value may indicate the start of a new trend. This is also a trend strength indicator.
More info: drive.google.com
Borrowed the color theme for this chart from @liw0. Thanks :)
Frank-Setup EMA, RS & RSI ✅It is a clean and simple indicator designed to identify weakness in stocks using two proven methods: RSI and Relative Strength (RS) vs. a benchmark (e.g., NIFTY).
🔹 Features
RSI Weakness Signals
Plots when RSI crosses below 50 (weakness begins).
Plots when RSI moves back above 50 (weakness ends).
Relative Strength (RS) vs Benchmark
Compares stock performance to a chosen benchmark.
Signals when RS drops below 1 (stock underperforming).
Signals when RS recovers above 1 (strength resumes).
Clear Visual Markers
Circles for RSI signals.
Triangles for RS signals.
Optional RSI labels for clarity.
Built-in Alerts
Get notified instantly when RSI or RS weakness starts or ends.
No need to constantly watch charts.
🎯 Use Case
This tool is built for traders who want to:
Spot shorting opportunities when a stock shows weakness.
Track underperformance vs. the index.
Manage risk by exiting longs when weakness appears.
Frank-Setup ✅ (RSI + RS only)Frank-Shorting Setup ✅ is an indicator designed to help traders spot weakness in a stock by combining RSI and Relative Strength (RS) analysis.
🔹 Key Features
RSI Weakness Signals
Marks when RSI falls below 50 (downside pressure begins).
Marks when RSI moves back above 50 (weakness ends).
Relative Strength (RS) vs Benchmark
Compares stock performance to a benchmark (e.g., NIFTY).
Signals when RS drops below 1 (stock underperforming).
Signals when RS moves back above 1 (strength resumes).
Clear Chart Markings
Circles for RSI signals.
Triangles for RS signals.
Optional labels for extra clarity.
Alerts Built-In
Get notified when RSI or RS weakness starts/ends.
No need to monitor charts all the time
Frank-Shorting Setup ✅ (RSI + RS only)An indicator designed to help traders spot weakness in a stock by combining RSI and Relative Strength (RS) analysis.
🔹 Key Features
RSI Weakness Signals
Marks when RSI falls below 50 (downside pressure begins).
Marks when RSI moves back above 50 (weakness ends).
Relative Strength (RS) vs Benchmark
Compares stock performance to a benchmark (e.g., NIFTY).
Signals when RS drops below 1 (stock underperforming).
Signals when RS moves back above 1 (strength resumes).
Clear Chart Markings
Circles for RSI signals.
Triangles for RS signals.
Optional labels for extra clarity.
Alerts Built-In
Get notified when RSI or RS weakness starts/ends.
No need to monitor charts all the time
Swing Z | Zillennial Technologies Inc.Swing Z by Zillennial Technologies Inc. is an advanced algorithmic framework built specifically for cryptocurrency markets. It integrates multiple layers of technical analysis into a single decision-support tool, generating buy and sell signals only when several independent confirmations align.
Core Concept
Swing Z fuses trend structure, momentum oscillators, volatility signals, and price action tools to capture high-probability trading opportunities in volatile crypto environments.
Trend Structure (EMA 9, 21, 50, 200)
Short-term EMAs (9 & 21) detect immediate momentum shifts.
Longer-term EMAs (50 & 200) define the broader trend and dynamic support/resistance.
Momentum & Confirmation Layer
RSI measures relative strength and market conditions.
MACD crossovers confirm momentum shifts and trend continuations.
Volatility & Market Pressure
TTM Squeeze highlights compression zones likely to precede breakouts.
Volume analysis confirms conviction behind directional moves.
VWAP (Volume Weighted Average Price) establishes intraday value zones and institutional benchmarks.
Price Action Filters
Fibonacci retracements are integrated to identify key reversal and continuation levels.
Signals are produced only when multiple conditions agree, reducing noise and improving reliability in fast-moving crypto markets.
Features
Tailored for cryptocurrency trading across major pairs (BTC, ETH, and altcoins).
Works effectively on swing and trend-based timeframes (1H–1D).
Combines trend, momentum, volatility, and price action into a single framework.
Generates clear Buy/Sell markers and integrates with TradingView alerts.
How to Use
Apply to a clean chart for the clearest visualization.
Use Swing Z as a swing trading tool, aligning entries with both trend structure and momentum confirmation.
Combine with your own stop-loss, take-profit, and position sizing rules.
Avoid application on non-standard chart types such as Renko, Heikin Ashi, or Point & Figure, which may distort results.
Disclaimer
Swing Z is designed as a decision-support tool, not financial advice.
All backtesting should use realistic risk, commission, and slippage assumptions.
Past results do not guarantee future performance.
Signals do not repaint but may adjust as new data develops in real-time.
Why Swing Z is original & useful:
Swing Z unifies EMA trend structure, RSI, MACD, TTM Squeeze, VWAP, Fibonacci retracements, and volume analysis into a single algorithmic framework. This multi-confirmation approach improves accuracy by requiring consensus across trend, momentum, volatility, and price action — a design made specifically for the challenges and volatility of cryptocurrency markets.
Swing Z – Crypto Trading Algorithm | Zillennial Technologies IncSwing Z by Zillennial Technologies Inc. is an advanced algorithmic framework built specifically for cryptocurrency markets. It integrates multiple layers of technical analysis into a single decision-support tool, generating buy and sell signals only when several independent confirmations align.
Core Concept
Swing Z fuses trend structure, momentum oscillators, volatility signals, and price action tools to capture high-probability trading opportunities in volatile crypto environments.
Trend Structure (EMA 9, 21, 50, 200)
Short-term EMAs (9 & 21) detect immediate momentum shifts.
Longer-term EMAs (50 & 200) define the broader trend and dynamic support/resistance.
Momentum & Confirmation Layer
RSI measures relative strength and market conditions.
MACD crossovers confirm momentum shifts and trend continuations.
Volatility & Market Pressure
TTM Squeeze highlights compression zones likely to precede breakouts.
Volume analysis confirms conviction behind directional moves.
VWAP (Volume Weighted Average Price) establishes intraday value zones and institutional benchmarks.
Price Action Filters
Fibonacci retracements are integrated to identify key reversal and continuation levels.
Signals are produced only when multiple conditions agree, reducing noise and improving reliability in fast-moving crypto markets.
Features
Tailored for cryptocurrency trading across major pairs (BTC, ETH, and altcoins).
Works effectively on swing and trend-based timeframes (1H–1D).
Combines trend, momentum, volatility, and price action into a single framework.
Generates clear Buy/Sell markers and integrates with TradingView alerts.
How to Use
Apply to a clean chart for the clearest visualization.
Use Swing Z as a swing trading tool, aligning entries with both trend structure and momentum confirmation.
Combine with your own stop-loss, take-profit, and position sizing rules.
Avoid application on non-standard chart types such as Renko, Heikin Ashi, or Point & Figure, which may distort results.
Disclaimer
Swing Z is designed as a decision-support tool, not financial advice.
All backtesting should use realistic risk, commission, and slippage assumptions.
Past results do not guarantee future performance.
Signals do not repaint but may adjust as new data develops in real-time.
Why Swing Z is original & useful:
Swing Z unifies EMA trend structure, RSI, MACD, TTM Squeeze, VWAP, Fibonacci retracements, and volume analysis into a single algorithmic framework. This multi-confirmation approach improves accuracy by requiring consensus across trend, momentum, volatility, and price action — a design made specifically for the challenges and volatility of cryptocurrency markets.
Radial Basis Kernel RSI for LoopRadial Basis Kernel RSI for Loop
What it is
An RSI-style oscillator that uses a radial basis function (RBF) kernel to compute a similarity-weighted average of gains and losses across many lookback lengths and kernel widths (γ). By averaging dozens of RSI estimates—each built with different parameters—it aims to deliver a smoother, more robust momentum signal that adapts to changing market conditions.
How it works
The script measures up/down price changes from your chosen Source (default: close).
For each combination of RSI length and Gamma (γ) in your ranges, it builds an RSI where recent bars that look most similar (by price behavior) get more weight via an RBF kernel.
It averages all those RSIs into a single value, then smooths it with your selected Moving Average type (SMA, EMA, WMA, HMA, DEMA) and a light regression-based filter for stability.
Inputs you can tune
Min/Max RSI Kernel Length & Step: Range of RSI lookbacks to include in the ensemble (e.g., 20→40 by 1) or (e.g., 30→50 by 1).
Min/Max Gamma & Step: Controls the RBF “width.” Lower γ = broader similarity (smoother); higher γ = more selective (snappier).
Source: Price series to analyze.
Overbought / Oversold levels: Defaults 70 / 30, with a midline at 50. Shaded regions help visualize extremes.
MA Type & Period (Confluence): Final smoothing on the averaged RSI line (e.g., DEMA(44) by default).
Red “OB” labels when the line crosses down from extreme highs (~80) → potential overbought fade/exit areas.
Green “OS” labels when the line crosses up from extreme lows (~20) → potential oversold bounce/entry areas.
How to use it
Treat it like RSI, but expect fewer whipsaws thanks to the ensemble and kernel weighting.
Common approaches:
Look for crosses back inside the bands (e.g., down from >70 or up from <30).
Use the 50 midline for directional bias (above = bullish momentum tilt; below = bearish).
Combine with trend filters (e.g., your chart MA) for higher-probability signals.
Performance note: This is really heavy and depending on how much time your subscription allows you could experience this timing out. Increasing the step size is the easiest way to reduce the load time.
Works on any symbol or timeframe. Like any oscillator, best used alongside price action and risk management rather than in isolation.
