Price-Filtered Spearman Rank Correl. w/ Floating Levels [Loxx]Price-Filtered Spearman Rank Correl. w/ Floating Levels is a Spearman Rank Correlation indicator with optional source filtering and floating levels.
What is Spearman rank correlation?
Spearman rank correlation, also known as Spearman coefficient is a formula used to identify the strength of the link between two datasets. This coefficient is a method that can be used to assess the strength of a relationship apart from the direction it takes. The formula, named after Charles Spearman, a mathematician, can only be used in circumstances where data can be categorized or put in order, for instance, the highest to the lowest.
For a better understanding of Spearman coefficient, it helps to get a sense of what monotonic function means. There’s a monotonic relationship under these circumstances:
– When the variable values rise together.
– When one variable value rises the other variable value lowers.
– The rate of movement of the variables need not necessarily be constant.
The Spearman correlation coefficient or rs, between +1 and -1, where +1 indicates a perfect strength between variables, while zero shows no association and -1 shows a perfect negative strength.
Spearman rank correlation theory:
A nonparametric (distribution-free) rank statistic proposed by Spearman in 1904 as a measure of the strength of the associations between two variables (Lehmann and D'Abrera 1998). The Spearman rank correlation coefficient can be used to give an R-estimate, and is a measure of monotone association that is used when the distribution of the data make Pearson's correlation coefficient undesirable or misleading.
Included:
Zero-line and signal cross options for bar coloring, signals, and alerts
Alerts
3 Signal types
Loxx's Expanded Source Types
Signals
Fisher Transform w/ Dynamic Zones [Loxx]What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included
3 signal types
Bar coloring
Alerts
Channels fill
Loxx's Expanded Source Types
Dynamic Zone Range on OMA [Loxx]Dynamic Zone Range on OMA is an One More Moving Average oscillator with Dynamic Zones.
What is the One More Moving Average (OMA)?
The usual story goes something like this : which is the best moving average? Everyone that ever started to do any kind of technical analysis was pulled into this "game". Comparing, testing, looking for new ones, testing ...
The idea of this one is simple: it should not be itself, but it should be a kind of a chameleon - it should "imitate" as much other moving averages as it can. So the need for zillion different moving averages would diminish. And it should have some extra, of course:
The extras:
it has to be smooth
it has to be able to "change speed" without length change
it has to be able to adapt or not (since it has to "imitate" the non-adaptive as well as the adaptive ones)
The steps:
Smoothing - compared are the simple moving average (that is the basis and the first step of this indicator - a smoothed simple moving average with as little lag added as it is possible and as close to the original as it is possible) Speed 1 and non-adaptive are the reference for this basic setup.
Speed changing - same chart only added one more average with "speeds" 2 and 3 (for comparison purposes only here)
Finally - adapting : same chart with SMA compared to one more average with speed 1 but adaptive (so this parameters would make it a "smoothed adaptive simple average") Adapting part is a modified Kaufman adapting way and this part (the adapting part) may be a subject for changes in the future (it is giving satisfactory results, but if or when I find a better way, it will be implemented here)
Some comparisons for different speed settings (all the comparisons are without adaptive turned on, and are approximate. Approximation comes from a fact that it is impossible to get exactly the same values from only one way of calculation, and frankly, I even did not try to get those same values).
speed 0.5 - T3 (0.618 Tilson)
speed 2.5 - T3 (0.618 Fulks/Matulich)
speed 1 - SMA , harmonic mean
speed 2 - LWMA
speed 7 - very similar to Hull and TEMA
speed 8 - very similar to LSMA and Linear regression value
Parameters:
Length - length (period) for averaging
Source - price to use for averaging
Speed - desired speed (i limited to -1.5 on the lower side but it even does not need that limit - some interesting results with speeds that are less than 0 can be achieved)
Adaptive - does it adapt or not
Variety Moving Averages w/ Dynamic Zones contains 33 source types and 35+ moving averages with double dynamic zones levels.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included
4 signal types
Bar coloring
Alerts
Channels fill
itrade buy/sellThe indicator was written based on several types of other indicators.
I took ema, rsi ema and an augmented version of qqe rsi.
The indicator checks for oversold or overbought on all of these indicators and, based on this, issues a buy or sell signal.
In the indicator, you can adjust the length of each point for yourself, so you can set rsi to 10 or 100, as it suits you.
The indicator works better on higher timeframes 4h-1w
But it can also be used on smaller timeframes, but the lower the timeframe, the higher the risk.
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Индикатор был написан на основе нескольких видов других индикаторов.
Я взял ema,rsi ema идополненую версию qqe rsi.
Индикатор проверяет перепроданость или перекупленость на этих всех индикаторах и изходя из этого выдаёт сигнал на покупку или продажу.
В индикаторе можно настроить длинну каждого пункта под себя,так вы можете поставить rsi на 10 или же на 100,как вам будет удобно.
Индикатор работает лучше на больших таймфреймах 4ч-1w
Но так же его можно использовать на более мелких таймфреймах,но чем ниже таймфрейм,тем выше риск.
Fibonacci Moving AverageFibonacci moving averages are a more reactive form of EMA utilizing the Fibonacci sequence (1 2 3 5 8 13 ... etc) to weight values.
This method gives several advantages of EMAs: they respond much sooner to price action while still weighting for past values and longer MAs (200 candle, 800 candle) etc moving averages can be calculated from candle 1 - handy for newly listed cryptocurrencies, equities, ETFs, etc.
The script allows for up to 5 moving averages. They can also be set as WMAs which weight older values more than recent to create slow/fast MAs.
They can be used the same way regular EMAs/WMAs are used: crossovers give trade entry/exit points, can indicate trend by alignment with other MAs and by their angle up/down, and - less useful for FMAs since no one else uses them - they can provide resistance.
Gucci Sniper Trading Bot [Open]A simple Buy/Sell signal algo designed for a trading bot.
Uses ATR and EMA cross to get signals.
Bull/Bear Buy/Bail CandlesBased on BullBearPower indicator, this is a heavily modified version with colored candles to show when bulls or bears are buying or bailing. Includes Fibonacci Levels based on Highest/Lowest value in variable length, along with optional second timeframe and alternative calculation for candles and linear regression curves for increased versatility. Green = bullish /long, Aqua = still-bullish albeit weakening, blue = weak albeit strengthening and red = weak/short. Perfect as a confirmation indicator for those looking to time markets.
Ext/Non EMA SignalsThis allows for one EMA to reference the regular session well the other references the extended session. A green arrow will appear above a bear candle closing above both the EMAs and a Red arrow on bull candles closing below both.
This saves me time from jumping back and forth from extended sessions and regular session.
Let me know if you have any questions, I just recently started using Pine Editor to build indicators I was not able to find in the library.
SP IndicatorSP Indicator - One of the best indicators for scalping trading on any timeframes. The best readings are given on 5, 15 and 30 minute frames.
For readings, several indicators are combined into one, which allows you to get a more accurate forecast, which is more than 90%.
Instruction.
The indicator is easy to use. Just install it and follow the arrows to go long or short. Stop loss set small, about 1-2%. In most cases, this is sufficient.
Good luck in bidding!
Trend & Momentum V2Declutter your charts. Simple indicator combining trend and momentum using Moving Average (currently default to 9-day EMA) and RSI (default length of 8). A long signal is generated when the price closes above the moving average and the moving average color turns red to green which indicated that the momentum measured using RSI is greater than 50. A short signal is generated when the price closes below the moving average and the moving average color turns green to red indicating RSI is below 50. Confirmation is done if there is no reversal on the next candle. For best results use multiple timeframe charts to trade on the right side of trend and momentum.
Fibonacci Progression with Breaks [LuxAlgo]This indicator highlights points where price significantly deviates from a central level. This deviation distance is determined by a user-set value or using a multiple of a period 200 Atr and is multiplied by successive values of the Fibonacci sequence.
Settings
Method: Distance method, options include "Manual" or "Atr"
Size: Distance in points if the selected method is "Manual" or Atr multiplier if the selected method is "Atr"
Sequence Length: Determines the maximum number of significant deviations allowed.
Usage
The indicator allows highlighting potential reversal points, but it can also determine trends using the central level, with an uptrend detected if the central level is higher than its previous value and vice versa for a downtrend.
When an uptrend is detected, and the price deviates significantly upward from it a first checkmark will be highlighted alongside the Fibonacci sequence used as a multiplier, if the price deviates downward, a cross will be shown instead, then the distance threshold will be multiplied by the next value in the Fibonacci sequence.
If the price deviates from the central level such that the length of the sequence is greater than the user set Sequence Length , a break label will be shown alongside a new central level with a value determined by the current closing price, while the Fibonacci multiplier will be reset to 1.
Upper and lower extremities made from the central level and threshold distance are highlighted and can be used as support and resistances.
Z-Score with Buy & Sell SignalsThis is my open-source indicator of z-score with buy and sell indicators.
I see there are other z-score indicators, I just am particular about how I like my z-scores calculated and so decided to make my own and add buy and sell signals to help guide me. And I figured I could share it openly here!
What is a Z-Score
A z-score is a statistical measures of the distance, in standard deviations, a value is from its given mean. It is expressed as a standard deviation (or SD). The further a value (in this case, a stock) is from their mean, the more likely a regression to the mean is possible (i.e. a return to the average). So if a stock is trading at 3 standard deviations away from its mean, then we can anticipate it wanting to regress back towards 1 to 0 standard deviations from its mean (i.e. sell off back to a value that brings it closer to that SD).
The inverse is true if it is trading below.
Z-Scores and Stocks
Stocks, like everything in nature, like to trade between -1 and +1 SD away from its mean. Anything above this, we can interpret that there is "stress" on the stock. Anything over 2.50 is tremendous stress on the stock and we can anticipate that it will want to revert to its mean in the near future and bring that value down to at least 1, ideally between the -0.5 and 0.5 range.
Please note, I set the standard VERY high for the indicator to issue a buy and sell signal (/=2.50). Lately with the volatility, stocks have been entering these ranges frequently and so there have been plenty of signals, but traditionally in a stable environment you may not get these signals. I set the bar extremely high because I want to avoid false buy and sell signals (you will still get them though, nothing is perfect!). So the value in this indicator is in interpreting the actual z-score itself, so please be sure you understand exactly what the Z-score is (see the description above).
How the indicator works
The indicator works by calculating the average Z-Score between a stocks high and low. This indicator will present the average deviation a stock has from its high and low average. The higher the Z-Score, the more "overbought" the stock is. The lower the z-score, the more "oversold" the stock is. It uses the previous 500 candles worth of data to calculate its SMA and its Standard deviation in order to calculate the z-score.
Anytime a stock trades 2.50 SDs or more above or below its mean, you will be presented with a Buy or Sell signal, as generally, statistically speaking, after something has travelled 2.50 SDs aware from its mean, there is an increased probability of a reversion happening.
You can use this indicator to determine whether the stock is trading within normal parameters or not and to help you in your analysis as to whether or not a stock could be shorted or longed.
I personally like this for swing trading on the 1 hour chart; however, this can be used on any time from 1 minute to 1 hour. It also allows you to track a stocks progress in its reversion to the mean.
Examples of it in Use:
Gold ETF (ARCA: GLD) on 1 minute
Dow Jones ETF (ARCA: DIA) on 1 minute (my favourite Stock!)
SPY ETF (ARCA: SPY) on 1 hour chart
Disclaimer:
This is not meant to be placed as a sole and single strategy. It should be used in COJUNCTION with your other strategies to help you make a determination.
No indicator is infallible and should never be relied on 100%!
Please let me know your questions/comments/experiences/recommendations below!
Thanks everyone!
Momentum 2.0 [AstrideUnicorn]Momentum 2.0 is a normalized Momentum oscillator with a moving base-level. The oscillator value is normalized by its standard deviation, similar to the z-score technique. Instead of the zero level, the indicator uses the base-level calculated as the inverted long-term average value of the oscillator. Similar to the zero-level crossing signal used for the Momentum oscillator, our oscillator calculates the base level crossing signal.
The moving base-level helps to reduce the number of false signals. In an uptrend the base-level is below zero, in a downtrend it is above it. This allows us to take into account the trend stability effect. In this case, to form a reversal signal, the oscillator must cross a lower value in an uptrend and a higher value in a downtrend.
HOW TO USE
When the oscillator crosses above the base-level, it gives a bullish signal, when below it gives a bearish signal. The signals are displayed as green and red labels, respectively.
The color of the histogram shows the current direction of the price momentum. Green indicates an upward move and red indicates a downward move. The blue line represents the base-level.
SETTINGS
Oscillator Period - determines the period of the Momentum oscillator
Base Level Period - determines the period used for long-term averaging when calculating the base-level and normalizing the oscillator
Botvenko ScriptI just test&learn pine script...
Damn, what should I write here? So... Its just a differense between the logarithms of two prices of different periods (You can set the period you want)... And it looks really nice... Ahem...
I hope, you enjoy this piece of... Have a nice day, my dear.
Combo 2/20 EMA & Average True Range Reversed This is combo strategies for get a cumulative signal.
First strategy
This indicator plots 2/20 exponential moving average. For the Mov
Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
Second strategy
Average True Range Trailing Stops Strategy, by Sylvain Vervoort
The related article is copyrighted material from Stocks & Commodities Jun 2009
Please, use it only for learning or paper trading. Do not for real trading.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo 2/20 EMA & ADXR This is combo strategies for get a cumulative signal.
First strategy
This indicator plots 2/20 exponential moving average. For the Mov
Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
Second strategy
The Average Directional Movement Index Rating (ADXR) measures the strength
of the Average Directional Movement Index (ADX). It's calculated by taking
the average of the current ADX and the ADX from one time period before
(time periods can vary, but the most typical period used is 14 days).
Like the ADX, the ADXR ranges from values of 0 to 100 and reflects strengthening
and weakening trends. However, because it represents an average of ADX, values
don't fluctuate as dramatically and some analysts believe the indicator helps
better display trends in volatile markets.
WARNING:
- For purpose educate only
- This script to change bars colors.
Ichimoku Buy/Sell Signals of manual MTF Tenkan crossing KijunIchimoku Buy/Sell Signals based on fast, small time frame Tenkans crossing longer timeframes Kijuns - Manual MTF Analysis
This code marks the potential change of direction based on the input of one timeframe's Ichimoku Tenkan (conversion) line crossing over a higher, longer timeframe's Ichimoku Kijun (base) line.
Feel free to change the inputs if need be and to hide the yellow box. Use Ichimoku rules of Tenkan, Kijun, Lagging Span, and Cloud for Take profit/Stop Losses. It is best to wait 3-5 minutes after the signal to enter to confirm the trend and to confirm if the Lagging Span has broken key levels. I refer to the book Trading with Ichimoku - A Practical Guide to Low-Risk Ichimoku Strategies by Karen Peloille as the Ichimoku rulebook. Good luck.
For day trading/scalping/intraday - 1min/3min/5min
Tenkan Line Timeframe = 1min
Kijun Line Timeframe = 5min
For swing trading - multiple days/weeks - 4HR/Daily/Weekly Charts
Tenkan Line Timeframe = day
Kijun Line Timeframe = week
Money Maykah -- DC-ATR , Stochastic RSI signals v.1-89 --This indicator shows the Stochastic RSI (SSRI) for overbought when the Donchian Channel (DC) is in the upper zone (between basis and upper), and SSRI for oversold when the DC is in the lower zone.
The DC upper and lower have a percentage of the ATR added I call this DC-ATR.
There can be numerous ways to form a strategy based on this. For a bull trend, an ABCD could be traced by A/C = blue signals and B/D = red signals.
Let me know what you think or if there is something wrong with the code. It's probably not the cleanest or more efficient but I am not a pro. If you find a good way to make a strategy from the indicator let me know.
Hope you enjoy!
-Casey R
Candle relative powerThis indicator tries to measure the power of candle.
You can also integrate some candles to measure the power. The “Length” is for integrating candles. If the Length is equal 5, it means indicator calculate power of recent 5 candles.
The second editable factor in “Shadow index” which represent the power of shadows.
The last factor in Average Criteria which is the module of comparing the integrated candles to the past market moves.
This indicator do not supposed to create trading signals! But, you can see every time it breaks the static line it is a sign of bulls or bears power.
I personally use it as a candle power meter so I will evaluate the power of breakouts or trend continuations.
Kahlman HullMA / WT Cross StrategyA strategy created using Hull Moving Average and WT Cross .
Hull Moving Average turns green and WT Cross crossover this is a long. Otherwise short.
Stop Loss and Take Profit settings are available. You can set it to the level you want or turn it off.
According to my measurements, it shows the best performance in the 4-hour period. But you can find the best settings that are correct from the Strategy settings.
EMA Options Clouds With SignalsEMA Clouds for Options!
This indicator can help you confidently open and close options positions. Note that you should set stop a little below midline EMA . Risk reward for good signals is fairly consistent in profit. Most of the simulations I ran got between 1:2 and 1:4 profits. The losers usually can be avoided by making sure you are not in a choppy trading channel. Wait for EMAs to start separating and don't blindly follow every buy/sell.
3 wave EMA + Clouds:
Defaults:
EMA 8/32/64
Signals (off by default - turn on in settings):
Buy Call/Sell Call (open/exit call positions)
Buy Put/Sell Put (open/exit put positions)
Enter signals bullish:
Close over Middle EMA AND Short EMA > Middle EMA > Long EMA
Exit signals bullish:
Close under Middle EMA OR trend turns bearish (Short EMA < Middle EMA < Long EMA )
Enter signals bearish:
Close under Middle EMA AND Short EMA < Middle EMA < Long EMA
Exit signals bearish:
Close over Middle EMA OR Short EMA > Middle EMA > Long EMA
Cloud Colors (Default)
Green: Bullish
Red: Bearish
White: Chop/Transition
Accumulation/Distribution Bands & Signals (BTC, 1D, BITSTAMP) This is an accumulation/distribution indicator for BTC/USD (D) based on variations of 1400D and 120D moving averages and logarithmic regression. Yellow plot signals Long Term Accumulation, which is based on 1400D (200W) ALMA, orange plot signals Mid Term Accumulation and is based on 120D ALMA, and finally the red plot signals Long Term Distribution that's based on log regression. It should be noted that for red plot to work BTC 1D BITSTAMP graph must be used, because the function of the logarithmic regression was modified according to the x axis of the BITSTAMP data.
Signal bands have different coefficients; long term accumulation (yellow) and and the log regression (red) plots have the highest coefficients and mid term accumulation (orange) has the lowest coefficients. Coefficients are 6x, 3x and 1.5x for the red (sell) and yellow (buy) plots and 1x, 2x and 3x for the orange (buy) plot. Selling coefficient for the yellow and the orange plots are respectively 2x and 1x. Buy and sell signals are summed up accordingly and plotted at the top of the highest band.
Acknowledgement: Credits for the logarithmic regression function are due @memotyka9009 and Benjamin Cowen
[Fedra Algotrading LR + TTP Indicator Lite]How it works?
- It calculates the linear regression of the last X candles and define a range based on a linear regression deviation (represented by the 3 parallel lines over the last candle).
-Open trades based on the breakout of the deviation of the linear regression (represented by the yellow triangle).
-Advanced trend filter to not open trades against the trend consist in 2 SMA cross and and a few other conditions, including sptionally super trend (Represented by the red and green background).
-Percentage take profit (represented by the horizontal green line. configurable)
-Percentage stop loss (represented by the horizontal red line. Configurable
-Break even when a trade has already opened and there is a change of trend. Calculated in 1.5% when the price is under the yellow SMA.
Alerts in each case to receive notifications (BUY & SELL, TP BE SL).
Added labels with entry price and PnL of each closed trade to facilitate optimization
