Variety N-Tuple Moving Averages w/ Variety Stepping [Loxx]Variety N-Tuple Moving Averages w/ Variety Stepping is a moving average indicator that allows you to create 1- 30 tuple moving average types; i.e., Double-MA, Triple-MA, Quadruple-MA, Quintuple-MA, ... N-tuple-MA. This version contains 2 different moving average types. For example, using "50" as the depth will give you Quinquagintuple Moving Average. If you'd like to find the name of the moving average type you create with the depth input with this indicator, you can find a list of tuples here: Tuples extrapolated
Due to the coding required to adapt a moving average to fit into this indicator, additional moving average types will be added as they are created to fit into this unique use case. Since this is a work in process, there will be many future updates of this indicator. For now, you can choose from either EMA or RMA.
This indicator is also considered one of the top 10 forex indicators. See details here: forex-station.com
Additionally, this indicator is a computationally faster, more streamlined version of the following indicators with the addition of 6 stepping functions and 6 different bands/channels types.
STD-Stepped, Variety N-Tuple Moving Averages
STD-Stepped, Variety N-Tuple Moving Averages is the standard deviation stepped/filtered indicator of the following indicator
Last but not least, a big shoutout to @lejmer for his help in formulating a looping solution for this streamlined version. this indicator is speedy even at 50 orders deep. You can find his scripts here: www.tradingview.com
How this works
Step 1: Run factorial calculation on the depth value,
Step 2: Calculate weights of nested moving averages
factorial(depth) / (factorial(depth - k) * factorial(k); where depth is the depth and k is the weight position
Examples of coefficient outputs:
6 Depth: 6 15 20 15 6
7 Depth: 7 21 35 35 21 7
8 Depth: 8 28 56 70 56 28 8
9 Depth: 9 36 34 84 126 126 84 36 9
10 Depth: 10 45 120 210 252 210 120 45 10
11 Depth: 11 55 165 330 462 462 330 165 55 11
12 Depth: 12 66 220 495 792 924 792 495 220 66 12
13 Depth: 13 78 286 715 1287 1716 1716 1287 715 286 78 13
Step 3: Apply coefficient to each moving average
For QEMA, which is 5 depth EMA , the calculation is as follows
ema1 = ta. ema ( src , length)
ema2 = ta. ema (ema1, length)
ema3 = ta. ema (ema2, length)
ema4 = ta. ema (ema3, length)
ema5 = ta. ema (ema4, length)
In this new streamlined version, these MA calculations are packed into an array inside loop so Pine doesn't have to keep all possible series information in memory. This is handled with the following code:
temp = array.get(workarr, k + 1) + alpha * (array.get(workarr, k) - array.get(workarr, k + 1))
array.set(workarr, k + 1, temp)
After we pack the array, we apply the coefficients to derive the NTMA:
qema = 5 * ema1 - 10 * ema2 + 10 * ema3 - 5 * ema4 + ema5
Stepping calculations
First off, you can filter by both price and/or MA output. Both price and MA output can be filtered/stepped in their own way. You'll see two selectors in the input settings. Default is ATR ATR. Here's how stepping works in simple terms: if the price/MA output doesn't move by X deviations, then revert to the price/MA output one bar back.
ATR
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma σ or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis we usually use it to measure the level of current volatility .
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA , we can call it EMA deviation. And added to that, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
See how this compares to Standard Devaition here:
Adaptive Deviation
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
For this indicator, I used a manual recreation of the quantile function in Pine Script. This is so users have a full inside view into how this is calculated.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is widely used indicator in many occasions for technical analysis . It is calculated as the RMA of true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range
See how this compares to ATR here:
ER-Adaptive ATR
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
For Pine Coders, this is equivalent of using ta.dev()
Bands/Channels
See the information above for how bands/channels are calculated. After the one of the above deviations is calculated, the channels are calculated as output +/- deviation * multiplier
Signals
Green is uptrend, red is downtrend, yellow "L" signal is Long, fuchsia "S" signal is short.
Included:
Alerts
Loxx's Expanded Source Types
Bar coloring
Signals
6 bands/channels types
6 stepping types
Related indicators
3-Pole Super Smoother w/ EMA-Deviation-Corrected Stepping
STD-Stepped Fast Cosine Transform Moving Average
ATR-Stepped PDF MA
Cerca negli script per "indicators"
Rsi/W%R/Stoch/Mfi: HTF overlay mini-plotsOverlay mini-plots for various indicators. Shows current timeframe; and option to plot 2x higher timeframes (i.e. 15min and 60min on the 5min chart above).
The idea is to de-clutter chart when you just want real-time snippets for an indicator.
Useful for gauging overbought/oversold, across timeframes, at a glance.
~~Indicators~~
~RSI: Relative strength index
~W%R: Williams percent range
~Stochastic
~MFI: Money flow index
~~Inputs~~
~indicator length (NB default is set to 12, NOT the standard 14)
~choose 2x HTFs, show/hide HTF plots
~choose number of bars to show (current timeframe only; HTF plots show only 6 bars)
~horizontal position: offset (bars); shift plots right or left. Can be negative
~vertical position: top/middle/bottom
~other formatting options (color, line thickness, show/hide labels, 70/30 lines, 80/20 lines)
~~tips~~
~should be relatively easy to add further indicators, so long as they are 0-100 based; by editing lines 9 and 11
~change the vertical compression of the plots by playing around with the numbers (+100, -400, etc) in lines 24 and 25
VHF-Adaptive T3 iTrend [Loxx]VHF-Adaptive T3 iTrend is an iTrend indicator with T3 smoothing and Vertical Horizontal Filter Adaptive period input. iTrend is used to determine where the trend starts and ends. You'll notice that the noise filter on this one is extreme. Adjust the period inputs accordingly to suit your take and your backtest requirements. This is also useful for scalping lower timeframes. Enjoy!
What is VHF Adaptive Period?
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA .
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA (n) = EMA (n) + EMA (time series - EMA (n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA (n) + EMA (time series - EMA (n))*.7;
This is algebraically the same as:
EMA (n)*1.7-EMA( EMA (n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD ( GD ( GD (n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included
Bar coloring
Alerts
Signals
Loxx's Expanded Source Types
Kam+ ScalpingThis study project is a Scalping trading Tool that incorporates the majority of the indicators needed to analyse and scalp Trends for 1min, 5min or 15min charts. Incorporated within this tool are the following indicators:
1. Major industry (Banks) recognised important SMAs
3SMA
2. Kijun Sen+ for entry
3. Atr Stop Loss For Stop Loss Entry/Exit.
Hint:- Use With Rsi Time Frame 15 min Custom, And Volume Flow Indicator For Trade Conformation
Crude Oil: Backwardation Vs ContangoCrude Oil, CL
Plots Futures Curve: Futures contract prices over the next 3.5 years; to easily visualize Backwardation Vs Contango(carrying charge) markets.
Carrying charge (contract prices increasing into the future) = normal, representing the costs of carrying/storage of a commodity. When this is flipped to Backwardation(As the above; contract prices decreasing into the future): it's a bullish sign: Buyers want this commodity, and they want it NOW.
Note: indicator does not map to time axis in the same way as price; it simply plots the progression of contract months out into the future; left to right; so timeframe DOESN'T MATTER for this plot
TO UPDATE (every year or so): in REQUEST CONTRACTS section, delete old contracts (top) and add new ones (bottom). Then in PLOTTING section, Delete old contract labels (bottom); add new contract labels (top); adjust the X in 'bar_index-(X+_historical)' numbers accordingly
This is one of several similar Futures Curve indicators: Meats | Metals | Grains | VIX | Crude Oil
If you want to build from this; to work on other commodities; be aware that Tradingview limits the number of contract calls to 40 (hence the multiple indicators)
Tips:
-Right click and reset chart if you can't see the plot; or if you have trouble with the scaling.
-Right click and add to new scale if you prefer this not to overlay directly on price. Or move to new pane below.
-If this takes too long to load (due to so many security calls); comment out the more distant future half of the contracts; and their respective labels. Or comment out every other contract and every other label if you prefer.
--Added historical input: input days back in time; to see the historical shape of the Futures curve via selecting 'days back' snapshot
updated 20th June 2022
© twingall
Metals:Backwardation/ContangoMETALS: Gold , Silver , Copper ( GC , SI, HG)
Quickly visualize carrying charge market vs backwardized market by comparing the price of the next 2 years of futures contracts.
Carrying charge (contract prices increasing into the future) = normal, representing the costs of carrying/storage of a commodity. When this is flipped to Backwardation (contract prices decreasing into the future): its a bullish sign: Buyers want this commodity, and they want it NOW.
Note: indicator does not map to time axis in the same way as price; it simply plots the progression of contract months out into the future; left to right; so timeframe DOESN'T MATTER for this plot
There's likely some more efficient way to write this; e.g. when plotting for Gold ( GC ); 21 of the security requests are redundant; but they are still made; and can make this slower to load
TO UPDATE(once a year will do): in REQUEST CONTRACTS section, delete old contracts (top) and add new ones (bottom). Then in PLOTTING section, Delete old contract labels (bottom); add new contract labels (top); adjust the X in 'bar_index-(X+_historical)' numbers accordingly
This is one of three similar indicators: Meats | Metals | Grains
-If you want to build from this; to work on other commodities ; be aware that Tradingview limits the number of contract calls to 40 (hence the 3 seperate indicators)
Tips:
-Right click and reset chart if you can't see the plot; or if you have trouble with the scaling.
-Right click and add to new scale if you prefer this not to overlay directly on price. Or move to new pane below.
--Added historical input: input days back in time; to see the historical shape of the Futures curve via selecting 'days back' snapshot
updated 15th June 2022
© twingall
Grains:Backwardation/ContangoGRAINS: Wheat , Soybeans , Corn (ZW, ZS, ZC )
Quickly visualize carrying charge market vs backwardized market by comparing the price of the next 2 years of futures contracts.
Carrying charge (contract prices increasing into the future) = normal, representing the costs of carrying/storage of a commodity. When this is flipped to Backwardation (contract prices decreasing into the future): its a bullish sign: Buyers want this commodity, and they want it NOW.
The above chart shows a nice example of backwardation.
Note: indicator does not map to time axis in the same way as price; it simply plots the progression of contract months out into the future; left to right; so timeframe DOESN'T MATTER for this plot
There's likely some more efficient way to write this; e.g. when plotting for Wheat (ZW); 15 of the security requests are redundant; but they are still made; and can make this slower to load
TO UPDATE(once a year will do): in REQUEST CONTRACTS section, delete old contracts (top) and add new ones (bottom). Then in PLOTTING section, Delete old contract labels (bottom); add new contract labels (top); adjust the X in 'bar_index-(X+_historical)' numbers accordingly
This is one of three similar indicators: Meats | Metals | Grains
-If you want to build from this; to work on other commodities ; be aware that Tradingview limits the number of contract calls to 40 (hence the 3 seperate indicators)
Tips:
-Right click and reset chart if you can't see the plot; or if you have trouble with the scaling.
-Right click and add to new scale if you prefer this not to overlay directly on price. Or move to new pane below.
--Added historical input: input days back in time; to see the historical shape of the Futures curve via selecting 'days back' snapshot
updated 15th June 2022
© twingall
Meats: Backwardation/CantangoMEATS: Live Cattle , Feeder Cattle, Lean Hogs (LE, GF , HE)
Quickly visualize carrying charge market vs backwardized market by comparing the price of the next 2 years of futures contracts.
Carrying charge (contract prices increasing into the future) = normal, representing the costs of carrying/storage of a commodity. When this is flipped to Backwardation (contract prices decreasing into the future): its a bullish sign: Buyers want this commodity, and they want it NOW.
Note: indicator does NOT map to time axis in the same way as price; it simply plots the progression of contract months out into the future; left to right; so timeframe DOESN'T MATTER for this plot
There's likely some more efficient way to write this; e.g. when plotting for Live Cattle (LE); 8 of the security requests are redundant; but they are still made; and can make this slower to load
TO UPDATE(once a year will do): in REQUEST CONTRACTS section, delete old contracts (top) and add new ones (bottom). Then in PLOTTING section, Delete old contract labels (bottom); add new contract labels (top); adjust the X in 'bar_index-(X+_historical)' numbers accordingly
This is one of three similar indicators: Meats | Metals | Grains
-If you want to build from this; to work on other commodities ; be aware that Tradingview limits the number of contract calls to 40 (hence the 3 seperate indicators)
Tips:
-Right click and reset chart if you can't see the plot; or if you have trouble with the scaling.
-Right click and add to new scale if you prefer this not to overlay directly on price. Or move to new pane below.
--Added historical input: input days back in time; to see the historical shape of the Futures curve via selecting 'days back' snapshot
updated 15th June 2022
© twingall
RSI Divergence Fast by RSUAdvantages:
1. When rsi is at a high point, once it falls by 1 k line, it will detect the divergence from the previous high point. This can quickly find the divergence that has taken effect and help you quickly capture the trend before a sharp decline or rise.
The difference between other RSI divergence indicators: the official divergence indicator is to detect the 5 and the k line, which may lead to a large amount of decline.
2. This indicator detects the previous high and the previous low of 5, 10, 20 lengths at the same time, instead of only detecting a fixed length, so that more deviations can be found.
Notice:
Because it is a quick divergence detection, it is recommended to confirm that the divergence takes effect after the current k is completely closed first. I have identified this state in the indicator as "k not end"
Disadvantages and Risks
Since it is a quick discovery, there will be error identification. I listed the difference between the two indicators when deleting errors. The indicator turns off the "delete error" option by default.
Please do not:
Don't go short in the uptrend, don't go long in the downtrend.
Top divergences that occur because of a strong uptrend are usually only temporary pullbacks. Bottom divergences in persistent declines are also temporary rallies. Do not attempt to trade such low-return trades.
It is recommended to use the divergence indicator when the stock price has made a new high and retraced, and once again made a new high, because this often leads to the end of the trend.
Divergence how to use:
1. After the previous K line was completely closed, a bottom divergence was found.
2. Open an long order at the beginning of the second bar, or as close to the bottom as possible (because the stop loss will be smaller).
3. Break the stop loss price below the previous low where the divergence occurred, which already means that the divergence is wrong.
RSI usage:
1. RSI is above the 50 line, in an uptrend, below 50 in a downtrend.
2. Above 70 is overbought, falling below the oversold zone may mean the end of the uptrend.
Below 30 is oversold, above the oversold zone may mean the end of the downtrend.
S2BU2 True Range BandsWhat it is:
A twist on the DMI and ATR indicators.
How it is calculated:
What you see is a basic 14-period EMA calculated based on the opening price of the candle.
Extending from this base is the average true range, showing the expected realistic movement in that direction.
How you may interpret what you see:
Extended movement outside of those bands indicates a strong trend and also indicates a bad time to enter. In a sideways market the best time to get in and out is whenever the chart crosses the upper/lower bands. As usual, do not use this indicator alone to determine your entries/exits. If you find a regular behaviour related to this indicator that is not mentioned here feel free to reach out to me. I will consider adding it the list
How you may improve accuracy:
Most obvious - combine with different indicators measuring different things. This indicator measures potential direction. You may combine it with a simple trendindicator, momentum-indicator, etc. There is little use in combining it with another indicator measuring the same thing. When using 2 indicators for the same aspect, pick the one that is more reliable or reacts faster - depending on your preference and strategy.
Another Option to improve accuracy is to overlap the indicator on several timeframes. Dissonance is weakness. Ressonance is strength. if you see many tfs showing the same movement it may be a good time to get in - you will have to judge it yourself though ;)
The Witcher [30MIN] - AlertsHello,
This is the Witcher Bot
This bot is got best performance at BTCUSDTPERP BINANCE FUTURES
this is bot for leverage 1x,
I tried focusing at highest % profitable trades, bot could be optimalised to even higher profit net.
TP: 1.1
SL: 8.2
Stop-loss unfortunelly have to be high to avoid bear/bull traps
The core of this strategy is trend strenght ( MONEY FLOW INDKES)
Strategy can only open position on strong price movment, to avoid wrong decision
Settings are set for highest profitable trades %
Bot using 10 indicators to trigger basic condtition for long and short :
1) ADX - Is one of the most powerful and accurate trend indicators. ADX measures how strong a trend is, and can give valuable information on whether there is a potential trading opportunity.
2) RSI - value helps strategy to stop trade in right time. When RSI is overbought strategy don't open new longs , also when RSI is oversold strategy don't open new shorts
3) TREND STRENGHT
4) JURIK MOVING AVERAGE - The Jurik Moving Average indicator is one of the surest ways to smoothen price curves within a minimum time lag. The indicator offers currency traders one of the best price filters during strong price moves. In this time, when bitcoin price action is so strong, this indicator is necessary.
5) SAR - The parabolic SAR is a technical indicator used to determine the price direction of an asset, as well as draw attention to when the price direction is changing. SAR supporting bot, to not open new trades when the trends are slowly changing
6) TREND INDICATOR
7) MOMENTUM - Indicator istechnical analysis tool used to determine the strength or weakness of a stock's price. Momentum measures the rate of the rise or fall of stock prices. Common momentum indicators include the relative strength index ( RSI ) and moving average convergence divergence ( MACD ).
8) OBV - On-balance volume (OBV) is a technical trading momentum indicator that uses volume flow to predict changes in stock price.
9) FAST MA - like previous ones this is for better view of trends, and correctly define the trends, also Speed_MA are using for predict the future price action.
10) RANGE FILTER - this indicator is for the better view of trends, define trends, that is important for every bull/bear traps which helps a lot becouse of the very variable trends.
I decided to add momentum indicator to strategy, to make a fast-reacting decision on lower timeframes at extremly price volatility
Also bot got additional EMA scalping option, which increase profit net but, in some situation, that could be risky.
For max security I recommend to turn off this option.
Commision are set at standard binancefutures VIP-0 = 0.04%
After converting strategy into study version, bot is ready for automation.
All the ploting color depends of adx value.
Strategy are not Repainting
For the source code I tried to keep as clean as I could
Enjoy
tickerTracker MFI OscillatorDid you ever want to have a neat indicator window in line with your chart showing a different ticker? tickerTracker is a Money Flow Index (MFI) oscillator. The Money Flow Index (MFI) is a technical oscillator that uses price and volume for identifying overbought or oversold conditions in an asset. More or less, everything is connected in the market. The tickerTracker lets you see what is happening with another ticker that you have connected a correlation between them. For my example here, I'm using COIN in the main chart with the tickerTracker displaying BTC, QQQ and COIN Money Flow Index (MFI) in its window. As the end user, you can customize the colors, the length input and the ticker. Like any other indicator, the shorter length input, the more quickly responsive and the longer the length input, the smoother curve print.
Default Values:
MFI Length = 13
Chart ticker = white
SPY = white
QQQ = blue
IWM = yellow
DIA = orange
BTC/USD = yellow
ETH/USD = green
SOL/USD = purple
ADA/USD = red
Do your own due diligence, your risk is 100% your responsibility. This is for educational and entertainment purposes only. You win some or you learn some. Consider being charitable with some of your profit to help humankind. Good luck and happy trading friends...
*3x lucky 7s of trading*
7pt Trading compass:
Price action, entry/exit
Volume average/direction
Trend, patterns, momentum
Newsworthy current events
Revenue
Earnings
Balance sheet
7 Common mistakes:
+5% portfolio trades, capital risk management
Beware of analyst's motives
Emotions & Opinions
FOMO : bad timing, the market is ruthless, be shrewd
Lack of planning & discipline
Forgetting restraint
Obdurate repetitive errors, no adaptation
7 Important tools:
Trading View app!, Brokerage UI
Accurate indicators & settings
Wide screen monitor/s
Trading log (pencil & graph paper)
Big, organized desk
Reading books, playing chess
Sorted watch-list
Checkout my indicators:
Fibonacci VIP - volume
Fibonacci MA7 - price
pi RSI - trend momentum
TTC - trend channel
AlertiT - notification
tickerTracker - MFI Oscillator
www.tradingview.com
Stochastic + Keltner Channels for ScalpingSimple arrow indicator, indicating the direction go the next slight movement. This indicator will work on any time frame or market.
How does this indicator work?
It will use Stochastic and Keltner Channels to detect potential reversals depending on the frequency you choose in the indicator's settings. The higher the frequency, the fewer candles will be used in the calculation.
When to use this indicator?
It will work better in higher time frames for low volatility indicators. You can mix with other indicators like RSI or ADX. This way, you will be able to check if the time selected frame has enough volatility to move the price enough to cover the spreads and fees of your broker.
When to exit the trade after the signal from this indicator?
A good target would be for 1x ATR value and stop-loss 2x the ATR value. Doing trailing stop will reduce your risk and secure some profits, but make sure to use values for possible fakeouts
Can this indicator be used alone as the main source of entry signal for the trades?
You can use it alone, but I recommend mixing with other trend-based indicators, like Moving Averages, so you get the best results. Since it's for scalping purposes, small moments, and reversals, it doesn't have the trend filter, but it can work trading in favor of a significant trend as well
this is a better version of my other script Scalping Arrows
Support Resistance Zones using confluence & Std. DeviationOverview:
This indicator takes (interactive) input from the user for support and resistance levels and plots important zones considering the other confluence levels in the indicator.
Working of indicator:
This indicator takes six input of Support/resistance level form the user
It has following 32 confluence levels
a.4 Recent positive Divergence levels (DN1, DN2, DN3, DN4)
b.4 recent negative divergence levels (DP1, DP2, DP3, DP4)
d.5 Fibonacci levels (Fib0, Fib236, Fib5, Fib618, Fib786)
e. 7 Pivot levels (P, PR1, PR2, PR3, PS1, PS2, PS3)
f.4 EMAs (E20, E200, E100, E50)
g. ATH, ATL, Weekly High, Weekly Low, two days ago high, two days ago low, previous day high , previous day low
The code checks nearest ‘n’ CONFLUENCE for each level (“Number of confluences to check”) in the indicator, after getting the nearest confluence it calculates the standard deviation of those levels WITH RESPECT TO THE MANUAL INPUT LEVELS.
If the Std. Deviation is less than the input value (“Minimum standard deviation” option) then the zone is displayed on the chart.
How to use:
Add the indicator on the chart select your important support and resistance levels.
Set standard deviation, if the confluence is less than the input standard deviation then you will see those zones on the chart.
You can display all divergence levels; you can display all fib levels. All confluences can be displayed by using the setting of the indicator
How to read the indicator values:
The zone will show all the confluence it has in its zone,
Example:
Table details:
The table shows the maximum and minimum deviation out of all six levels .To see at least one zone you have to make sure that Input value Std. Deviation must be greater than Min Std. Deviation of the table
Sources & refences :
Big thank to www.pinecoders.com and kodify.net
Standard deviation :
www.investopedia.com
function to find 'k' closest elements :
www.techiedelight.com
Interactive support resistance :
Divergence for many indicators:
Auto fib level by DGT:
www.tradingview.com
lib_Indicators_DTLibrary "lib_Indicators_DT"
This library functions returns some Moving averages and indicators.
Created it to feed my indicator/strategy "INDICATOR & CONDITIONS COMBINATOR FRAMEWORK v1 " which I will publish it as soon as possible.
Credits: Library includes some public indicators, snippets from tradingview & @03.freeman's ("All MAs displayed") scripts.
(I hope, I dont break Tradingview's House Rules on Script Publishing)
f_plotPrep(src_, src_, src_, src_) Prepare Indicator Plot Type
Parameters:
src_ : Source
src_ : plotingType_ "Original, Stochastic, Percent"
src_ : stochlen_ Stochasting plottingtype length
src_ : plotSWMA_ Use SWMA for the output
Returns: Return the prepared indicator
f_funcPlot(string, float, simple, string, simple, bool) f_funcPlot(string f, float src_, simple int length_, string plotingType_ = "Original", simple int stochlen_=50, bool plotSWMA=false) Return selected indicator value with different parameters
Parameters:
string : f indicator-> options=
float : src_ close,open.....
simple : int length_ indicator length
string : plotingType return param-> options= ['Original', 'Stochastic', 'PercentRank')
simple : int stochlen_ length for return Param
bool : plotSWMA Use SWMA on Plot
Returns: float
MTF DPO-RSI IndicatorThis indicator uses the principle of taking the RSI of DPO readings across multiple time frames in order to provide trade signals and an overarching view of market conditions to the trader. My hope with creating this indicator was to present more divergence based signals than your typical indicator, while still keeping those signals at a high quality.
In the settings menu, you may specify:
Indicator Timeframe - the chart resolution that is used to calculate values.
Source DPO Length - the number of bars used to calculate the Detrended Price Oscillator value. The DPO value is the source for the RSI calculations.
DPO Hull Smoothing - how much smoothing is applied to the DPO . Smoothing is accomplished by taking a Hull Moving Average of the closing price, and using this to calculate the DPO value.
RSI Length - the number of bars used to calculate the RSI of the DPO value.
Time Multipliers 1 through 6 - use this to define what resolution each plot will represent. A value of 1 will represent the current Indicator Timeframe. A value of 3 will represent 3 times the current Indicator Timeframe, etc.
Show Plot 1 through 6 - toggles the display of plots.
How I trade with this indicator:
A value of under 30 represents an over sold state for that particular plot. A value of over 70 represents an overbought state for that plot.
Identify divergences on a lower timeframe plot which are apparent in overbought or oversold conditions, and confirm the signal with an overbought or oversold condition, or a divergence on a higher timeframe plot. Divergences which begin in oversold or overbought territory and end inside the 30-70 range tend to be more reliable signals, in my experience. Like all indicators, this is best when used in conjunction with other indicators. Trend indicators, such as double EMA's and Supertrend are my favorite pairing, and a stochastic RSI is a good tool to have as well.
This is my first published indicator! If you find unique ways to use it, drop me a message. I'd love to know what you find. :)
On-chart Wavetrend Divergence with PivotsThis is an OnChart WaveTrend Divergence Indicator with Pivots and Alerts
LazyBears WaveTrend Indicator or also known as "Market Cipher" is an Indicator that is based on Moving Averages, therefore its an "lagging indicator". Lagging indicators are best used in combination with leading indicators. In this script the "leading indicator" component are Daily, Weekly or Monthly Pivots. These Pivots can be used as dynamic Support and Resistance, Stoploss, Take Profit etc.
This indicator combination is best used in larger timeframes. For lower timeframes you might need to change settings to your liking.
What are those circles?
-These are the WaveTrend Divergences. Red for Regular-Bearish. Orange for Hidden-Bearish. Green for Regular-Bullish. Aqua for Hidden-Bullish.
Please keep in mind that this indicator is a tool and not a strategy, do not blindly trade signals, do your own research first! Use this indicator in conjunction with other indicators to get multiple confirmations.
MACD - STOCH - RSI This indicator combines the
- MACD w/ Volume Conditions
- STOCHASTIC
- RSI
All into one place, to help find confluences between popular convergence / divergence indicators.
It's primary use is the histogram of the MACD.
The colors change whether or not the current bar is higher or lower than the previous.
Lighter shade signifies the bars are getting smaller.
You can also enable a feature which will change the color of the histogram depending on the volume.
There are 2 conditions which can be met which signify ' Increasing Volume ' and ' Above Average Volume '.
If the MACD is above 0,
Light Blue signifies increasing volume.
Dark Blue signifies above average volume
If the MACD is below 0,
Light Purple signifies increasing volume.
Dark Purple signifies above average volume.
Having volume conditions within the histogram are meant to act as confluence. For example, if the histogram is
rising and light blue or dark blue bars are shown, this could hint towards a larger move to the upside if previous
upswings on the histogram were only green.
Increased volume near the peak of a move can also signify lots of orders coming into the market in hopes
of reversing the current trend or starting a correction.
formula:
Avg of volume over past 10 bars * 1.5 = increasing volume
Avg of volume over past 10 bars * 2 = Above Average Volume
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The RSI and STOCHASTIC have been run through a custom function which moves the values. The middle line is now 0.
Where on most RSI and STOCHASTIC indicators the middle line can be considered 50, with overbought levels nearing 70
and oversold levels around 30.
On the M.S.R , the RSI overbought levels are by default 20, and oversold -20.
I've done this because for myself it was easier to understand RSI was becoming oversold if it went below 0, not 50.
The same function also applies to the STOCHASTIC indicator.
The RSI and STOCHASTIC can also be displayed together to help see the conditions of both indicators at once.
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Bollinger Bands And Aroon Scalping (by Coinrule)Many technical indicators can be profitable in certain market conditions while failing in others. No indicator is perfect alone.
All the best trading strategies involve multiple indicators and leverage the benefit of each of them. The following is an optimised strategy based on Bollinger Bands and the Aroon indicator.
The Bollinger Bands are among the most famous and widely used indicators. They can suggest when an asset is oversold or overbought in the short term, thus provide the best time for buying and selling it.
A strategy buying dips can work well during times of uptrend. Downtrends will result in a drawdown for the P&L of the strategy. The suggested approach minimises the drawdowns, ensuring that the system trades only when it's more likely to close the trade in profit.
The Setup
ENTRY
The price crosses below the basis line of the Bollinger Band indicator
The Aroon Indicator is above 90
EXIT
The price crosses below the upper Bollinger Band
The Aroon Indicator drops below 70
The Aroon Indicator plays a key role in this strategy. It acts as a confirmation that the asset is currently in an uptrend. On the other hand, it acts as a stop if market conditions deteriorate. The strategy uses an Aroon Indicator set to 288 periods to provide a longer-term view on market conditions, not being heavily dependent on short-term volatility.
The best time frame for this strategy based on our backtest is the 4-hr . The 1-hr can work well with three times more trades, on average. As trades increase, the profitability decreases. Yet again, this is the confirmation that trading more does not mean gaining more.
To make the results more realistic, the strategy assumes each order to trade 30% of the available capital. A trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange.
Trend ExplorerAre we in a bull or a bear market?
From the technical analysis point of view, the answer is "It depends". It depends from the parameters of your indicator, the timeframe of the pair you are looking and the volatility of that specific market you are looking to.
After I experimented with various trending indicators I decided to develop a framework that potentially could "embed" already existing logic from well known indicators (e.g. Supertrend OTT etc.).
The most important part is that I managed to abstract that logic away and experiment even further to produce some more robust, market and timeframe resolution agnostic results. While at the same time I was able to switch between market and timeframe resolution specific configuration to take some decision.
Finally, I decided to share this code with you folks! Developed this indicator "Trend Explorer" in an effort to make the aforementioned abstraction of all those trending indicators.
The goal is to enable the user to explore and combine different approaches in order to create a more robust and market general/specific, timeframe resolution invariant/fluctuating and volatility auto/manual adjusted indicator according to his needs.
The logic behind the abstraction is fairly simple. The trending indicator consists of two boundary lines the "bull trend low boundary" (green) and the "bear trend high boundary" (red). The indicator also has a control line (orange). Every time the control line crosses a boundary there is a trend reversal! The boundary lines are defined by the thresholds. To be more precise, boundaries are pulled upwards by thresholds (blue) during a bull market and downwards during a bear market. I challenge the user to experiment with the different ways of calculating the thresholds and the control. I am open to suggestions that might improve and extend the possibilities of this indicator. Any feedback, comments, general thoughts or bug reports are welcome.
Why did I chose those defaults?
For threshold calculation I chose MINMAX which calculates the local minimum and maximum using a sliding window. As far as I know it is not used in any existing trending indicator, but it seems reasonable for a trader to search for local min and max to make a decision. The width of the sliding window a.k.a the "period to remember" the local min and max is 30 days by default, just because I believe that for regular people it is a reasonable period of time to forget too.
Also, compared to the SUBADD method MINMAX does not seem to lag behind, especially when using averages in the SUBADD mode. Moreover, I consider MINMAX to be more general than the margins used by the SUBADD since margins should be configured based on the underlying market volatility.
For a source of min and max I chose the low and high values just because they are timeframe resolution invariant, meaning that they have the same (not exactly due to number precision and rounding, but very close) results for a single pair whether you use "4 hour" or "1 day" time interval! Another popular choice might be (close, close) since many traders wait for the daily candle to close in order to discard outliers. However, this approach is not resolution invariant and it depends from the time interval the user has selected.
Do you have any interesting trending indicator you would like to see how it performs in this framework logic? Let me know!
Do you have in mind any variation of Control or Thresholds calculation you would like to test? Please describe it in the comments below so I can add it in my implementation for you!
Did you find any other bug or you experienced any strange behavior? PM me with a description of the bug, the trading pair the timeframe resolution the exact time (candle) and all the necessary configurations for this indicator so I can reproduce it on my machine!
Please enjoy with caution,
Jason
Natural Market Mirror [CC]The Natural Market Mirror was created by Jim Sloman (Ocean Theory pgs 49-57) and this is a continuation of my series from Jim Sloman's indicators. This indicator is also a momentum indicator and is very similar to the previous indicator I published, the Ocean Indicator and of course this indicator is built using ideas from the Ocean indicator. It may just be my opinion but I feel like this indicator provides better buy and sell signals in comparison. I built this using strong buy and sell indicators in addition to normal ones so darker colors are the strong signals and lighter colors are the normal signals. Buy when the line turns green and sell when it turns red.
Let me know what other indicators you would like me to publish!
[Sidders] MACDEMASAR IndicatorCame across a cool idea for a strategy that couldn't find in the indicator database, so decided to code it up myself for your pleasure.
Indicators consists of 3 indicators: EMA(200) to determine the overall trend, and the MACD & Parabolic SAR to determine entries (and exits).
Long entry contains 4 conditions and is generated when price is above the 200EMA (1), the MACD crosses above the signal line (2), while they are both below 0 line (3) and when the parabolic SAR is below the closing price of the bar (4).
Short entry is build up the same but in reverse: price is below the 200EMA(1), signal line crosses below the MACD line (2), while they are both above the 0 line (3) and when the parabolic SAR is above the closing price of the bar (4).
Place the stoploss on the parabolic SAR dot below/above the candle that created the signal. Profit target 1:1 risk:reward ratio, but can ofcourse be changed according to your risk apetite. Might add automatically drawn SL/TPs in a later update.
Concept behind the strategy should work on all timeframes, but will require proper backtesting. I think with additional filters the strategy can also be way more finetuned and profitable, personally haven't had the time yet to dive into that.
Have also added alerts for your convenience.
Enjoy!
Commodity Channel Index + Relative Strength Index (Same Scale)Mashup, combining (adjusted) RSI and CCI.
These two indicators serve similar functions, but on different scales. I combined the two versions from the TradingView Built-In library into one chart, keeping the default setting for the CCI signal lines and fitting the RSI's default signal lines to them, so that they line up. I therefore adjusted the RSI to match the approximate range of the CCI and added additional lines to represent the maximum and minimum values of the RSI (0 - 100).
I did that by multiplying the RSI with 5, and subtracting 250.
Adjusted RSI = (RSI * 5) - 250
So the upper signal line (default: 70) now matches the line used for the CCI at 100. The lower signal line (default: 30) lines up with -100.
If you want to adjust them, you need to use the formula. I annotated the code if you want to dive deeper.
This indicator uses the original code and styling of the default Built-In RSI and CCI. Credit goes to the appropriate developers. My only intent is to mash up both of these indicators, making it easier to compare them.
Interpreting this indicator is the same as interpreting the underlying indicators. If you find any unexpected correlations, comment.
