[Old] TL with K/K and CustomizationThe old version of Trap Light before the most recent update. In order to facilitate the table functionality that is currently available for Trap Light, I had to make some values that are used in calculations hard-coded. By request, I'm quickly making this version available.
Trap Light
Description
Trap Light is an indicator that uses the K value of the Stochastic RSI to indicate potential long or short entries. It was designed to operate like a traffic stop light that is displayed near the current candle so that you don't have to look away from the candlesticks while trading.
Kriss/Kross is simply a cross over/under strategy that utilizes the 10 EMA and the 50 EMA .
Signals and Available Alerts:
1. Max Sell (Red Sell Label)
When K is equal to 100.00.
This is the strongest sell signal, remember that you only need to make sure that the trend is reversing before you make an entry, because several of these signals can appear in a row if a strong trend hasn't yet reversed.
2. Sell (Red Sell Label)
When K is equal to or greater than 99.50.
A sell signal.
3. Close to Sell (Red Down Arrow)
When K is equal to or greater than 95.00.
A sell signal may be produced soon.
4. Not Ready (Yellow Circle)
When K is less than 95 and greater than 5.00.
This indicates that neither a sell nor buy signal are close to being produced.
5. Close to Buy (Green Up Arrow)
When K is equal to or less than 5.00.
A buy signal may be produced soon.
6. Buy (Green Buy Label)
When K is equal to or less than 0.50 and greater than 0.00.
A buy signal.
7. Max Buy (Green Buy Label)
When K is equal to 0.00.
Strongest buy signal, remember to make sure that the trend is reversing before making an entry.
8. Kriss (Buy)
A buy signal when the 10 EMA (Blue) crosses above the 50 EMA (Yellow). This is also illustrated by the triggering candle being colored blue.
9. Kross (Sell)
A sell signal when the 10 EMA (Blue) crosses below the 50 EMA (Yellow). This is also illustrated by the triggering candle being colored yellow.
Customization of many different options is available, and the code is open-source for your reference, etc.
Remember to do you own due diligence and feel free to leave a comment with questions, etc.
Cari dalam skrip untuk "scalping"
VWAP Push StrategyThis strategy is unfortunately not finished yet.
A pretty simple strategy. If price broke through VWAP and had three consecutive candles following the breakthroughs trend, the high of the third candle will be drawn. If this happened after a crossover of the vwap and price breaks through the high of the third candle, strategy will go long. Short will be the same after crossing under the vwap. A long or short will be closed after crossing the vwap in the opposite direction, so the vwap is kind of a trailing stop.
Unfortunately, I could not manage to stop the script from entering multiple times into one drawn high or low. Of course, if a high was crossed the script should wait for a new formed high before entering a new long. If someone would find a solution to this, it would be great, because I think it is a nice strategy .
Should work great scalping 5min charts (when scripting, I used the SPX for reference).
Higher Time Frame EMAs and 1% volatility indicatorSet the "higher time frame" (HTF) from which the EMAs will be calculated in all timeframes.
Example: I chose timeframe 1D and I will see the EMAs from TF 1D also in smaller TF as 1, 5, 30, 60 minutes.
There are 4 EMAs. The default values are 5, 10, 60 and 223 periods from "Scalping the Bull" indicator.
You can change the periods of each EMA.
The indicator have also a volatility indication, showing -1% and +1% price levels.
Strategy Myth-Busting #3 - BB_BUY+SuperTrend - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our third one we are automating is one of the strategies from "The Best 3 Buy And Sell Indicators on Tradingview + Confirmation Indicators ( The Golden Ones ))" from "Online Trading Signals (Scalping Channel)". No formal backtesting was done by them so wanted to validate their claims.
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
This strategy uses a combination of 2 open-source public indicators:
BB_Buy and Sell by guikroth (default settings)
SuperTrend from TradingView's Technicals (default settings)
Trading Rules
15 min candles
Long
Long condition when BB_BUY indicates buy signal and SuperTrend is green
Short
Short condition when BB_BUY indicates Sell signal and SuperTrend is red
V Bottom & V Top Pattern [Misu]█ This indicator shows V bottom & V top patterns as well as potential V bottom & V top.
These V bottom & V top are chart powerful reversal patterns.
They appear in all markets and time-frames, but due to the nature of the aggressive moves that take place when a market reverses direction, it can be difficult to identify this pattern in real-time.
To address this problem, I added potential V pattern as well as the confirmed one.
█ Usages:
You can use V top & V bottoms for reversal zones.
You can use it for scalping strategies, as a main buy & sell signal.
Potential V patterns can be used to anticipate the market, in addition to volatility or momentum indicators, for example.
█ How it works?
This indicator uses pivot points to determine potential V patterns and confirm them.
Paramaters are available to filter breakouts of varying strengths.
Patterns also have a "max number bars" to be validated.
█ Why a Strategy type indicator?
Due to the many different parameters, this indicator is a strategy type.
This way you can overview the best settings depending on your pair & timeframe.
Parameters are available to filter.
█ Parameters:
Deviation: Parameter used to calculate parameters.
Depth: Parameter used to calculate parameters.
Confirmation Type: Type of signal used to confirme the pattern.
> Mid Pivot: pattern will confirm on mid pivot breakout.
> Opposit Pivot: pattern will confirm on opposit pivot breakout.
> No confirmation: no confirmation.
Lenght Avg Body: Lenght used to calculate the average body size.
First Breakout Factor: This factor multiplied by the "body avg" filters out the non-significant breakout of potential V pattern.
Confirmation Breakout Factor: This factor multiplied by the "body avg" filters out the non-significant breakout for the confirmation.
Max Bars Confirmation: The maximum number of bars needed to validate the pattern.
EMA scalping - PapamallisEma of highs and low and macd.
Can be used as
*macd filter
*breakout
*range market filter
BBSS - Bollinger Bands Scalping SignalsModified Bollinger Bands Indicator
Added:
- color change divergence (green) and narrowing (red) of the upper and lower bands
- color change of the moving average - upward trend (green) and downward trend (red)
- the appearance of a potential signal for long and short positions when the candle closes behind the upper or lower bands.
How to use the indicator:
Long conditions:
- the price breaks through the upper band
- Bollinger bands are expanding and should be green
- the mid-line is green
- the trigger candle should be green
Short conditions:
- the price breaks through the lower band
- Bollinger bands are expanding and should be red
- the mid-line is red
- the trigger candle should be red
Stochastic Rsi+Ema - Auto Buy Scalper Scirpt v.0.3Simple concept for a scalping script, written for 5 minute candles, optimized for BTC.
1st script I've created from scratch, somewhat from scratch. Also part of the goal of this one is to hold coin as often as possible, whenever it's sideways or not dropping significantly.
Designed to buy on the stochastic bottoms (K>D and rising, and <17)
Then and sell after 1 of 3 conditions;
a. After the price goes back up at least 1 % and then 1-2 period ema reversal
b. After the rsi reversal (is dropping) and K<D Flip
c. Stop loss at -1.5%
2 Ema Pullback StrategyHi everyone!
CAUTION... This is only an indicator. Do not rely 100% on it.
I made this indicator hoping to help everyone with this specific Pull Back Scalping Strategy.
RULES:
Time Chart of 5minuts
LONG Condition - "EMA Red Line" below the "EMA Blue Line" and wait for a green long signal.
SHORT Condition - "EMA Red Line" below the "EMA Blue Line" and wait for a red short signal
Feel free to add any adjustments or give feedback so we can improve.
The strategy idea and guidelines came from "The Master" Juan Luis.
Autor: © Germangroa
EMA-Deviation-Corrected Super Smoother [Loxx]This indicator is using the modified "correcting" method. Instead of using standard deviation for calculation, it is using EMA deviation and is applied to Ehlers' Super Smoother.
What is EMA-Deviation?
By definition, the Standard Deviation (SD, 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 is not doing that. It is, instead, using the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA. It is similar to Standard Deviation, but on a first glance you shall notice that it is "faster" than the Standard Deviation and that makes it useful when the speed of reaction to volatility is expected from any code or trading system.
What is Ehlers Super Smoother?
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a a Two-pole Butterworth filter combined with a 2-bar SMA (Simple Moving Average) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Things to know
The yellow and fuchsia thin line is the original Super Smoother
The green and red line is the Corrected Super Smoother
When the original Super Smoother crosses above the Corrected Super Smoother line, its a long, when it crosses below, its a short
Included
Alerts
Signals
Bar coloring
RSI Mean Reversion StrategyThis is a scalping strategy designed to be used for crypto trading. It uses an Exponential Moving Average with a default length of 100 in order to identify the trend of the market. If the price is trading above 100, it will only take long trades, and vice versa for shorts. It places long orders when the RSI value closes below 40, and the price is also above the 100 EMA. It places short orders when the RSI value is above 60, and the price is below the 100 EMA.
*Note: for custom alert messages to be read, "{{strategy.order.alert_message}}" must be placed into the alert dialogue box when the alert is set.
Strategy Myth-Busting #1 - UT Bot+STC+Hull [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our first one is an automated version of the " The ULTIMATE Scalping Trading Strategy for 2022 " strategy from " My Trading Journey " who claims to have achieved not only profits but a 98.3% win rate. As you can see from the backtest results below, I was unable to substantiate anything close to that that claim on the same symbol (NVDA), timeframe (5m) with identical instrument settings that " My Trading Journey " was demonstrating with. Strategy Busted.
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
This strategy uses a combination of 3 open-source public indicators:
UT Bot Alerts by QuantNomad
STC Indicator - A Better MACD By shayankm
Basic Hull Ma Pack tinkered by InSilico
Trading Rules:
5 min candles
Long
New Buy Signal from UT Bot Alerts Strategy
STC is green and below 25 and rising
Hull Suite is green
Short
New Sell Signal from UT Bot Alerts Strategy
STC is red and above 75 and falling
Hull Suite is red
ADXVMA iTrend [Loxx]ADXVMA iTrend is an iTrend indicator with ADXVMA smoothing. Trend is used to determine where the trend starts and ends. Adjust the period inputs accordingly to suit your backtest requirements. This is also useful for scalping lower timeframes.
What is the ADXvma - Average Directional Volatility Moving Average?
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
Included
Bar coloring
Alerts
Signals
Loxx's Expanded Source Types
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
2 EMA PullbackHi everyone!
CAUTION... This is only an indicator. Do not rely 100% on it.
I made this indicator hoping to help everyone with this specific Pull Back Scalping Strategy.
RULES:
Time Chart of 5minuts
Long Condition - "EMA Red Line" below the "EMA Blue Line" and wait for a green long signal.
Short Condition - "EMA Red Line" below the "EMA Blue Line" and wait for a red short signal
Feel free to add any adjustments or give feedback so we can improve.
The strategy idea and guidelines came from the "Master Juan Luis"
Autor: © Germangroa
Pips-Stepped, OMA-Filtered, Ocean NMA [Loxx]Pips-Stepped, OMA-Filtered, Ocean NMA is an Ocean Natural Moving Average Filter that is pre-filtered using One More Moving Average (OMA) and then post-filtered using stepping by pips. This indicator is quadruple adaptive depending on the settings used:
OMA adaptive
Hiekin-Ashi Better Source Input Adaptive (w/ AMA of Kaufman smoothing)
Ocean NMA adaptive
Pips adaptive
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
What is the Ocean Natural Moving Average?
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programed to do so. For more info, read his guide "Ocean Theory, an Introduction"
What's the difference between this indicator and Sloan's original NMA?
Sloman's original calculation uses the natural log of price as input into the NMA , here we use moving averages of price as the input for NMA . As such, this indicator applies a certain level of Ocean theory adaptivity to moving average filter used.
Included:
Bar coloring
Alerts
Expanded source types
Signals
Flat-level coloring for scalping
3C QFL Mean reversalWhat is QFL trading strategy?
QFL stands for Quickfingersluc, and sometimes it is referred to as the Base Strategy or Mean Reversals. Its main idea is about identifying the moment of panic selling and buying below the base level and utilizing Safety orders.
What is Base level or Support Level?
Base level or Support Level refers to the lowest price level that was reached before the moment the price started increasing again. At that level, you can notice that buyers of some cryptocurrencies make a strong reaction.
In this strategy we can also reverse the strategy and go short. But i must warn you that that is alot riskier.
QFL is meant to be used on higher TF's like 1hr, 2hr and 4hr. But this strategy also work well on lower Timeframes.
The script also simulates DCA strategy with parameters used in 3commas DCA bots for futures trading.
Experiment with parameters to find your trading setup.
Beware how large your total leveraged position is and how far can market go before you get liquidated!
Do that with the help of futures liquidation calculators you can find online!
Included:
An internal average price and profit calculating, instead of TV`s native one, which is subject to severe slippage.
A graphic interface, so levels are clearly visible and back-test analyzing made easier.
Long & Short direction of the strategy.
Table display a summary of past trades
Vertical colored lines appear when the new maximum deviation from the original price has
been reached
All the trading happens with total account capital, and all order sizes inputs are expressed in percent.
Inverse MACD + DMI Scalping with Volatility Stop (By Coinrule)This script is focused on shorting during downtrends and utilises two strength based indicators to provide confluence that the start of a short-term downtrend has occurred - catching the opportunity as soon as possible.
This script can work well on coins you are planning to hodl for long-term and works especially well whilst using an automated bot that can execute your trades for you. It allows you to hedge your investment by allocating a % of your coins to trade with, whilst not risking your entire holding. This mitigates unrealised losses from hodling as it provides additional cash from the profits made. You can then choose to hodl this cash, or use it to reinvest when the market reaches attractive buying levels.
Alternatively, you can use this when trading contracts on futures markets where there is no need to already own the underlying asset prior to shorting it.
ENTRY
The trading system uses the Momentum Average Convergence Divergence (MACD) indicator and the Directional Movement Index (DMI) indicator to confirm when the best time is for selling. Combining these two indicators prevents trading during uptrends and reduces the likelihood of getting stuck in a market with low volatility.
The MACD is a trend following momentum indicator and provides identification of short-term trend direction. In this variation it utilises the 12-period as the fast and 26-period as the slow length EMAs, with signal smoothing set at 9.
The DMI indicates what way price is trending and compares prior lows and highs with two lines drawn between each - the positive directional movement line (+DI) and the negative directional movement line (-DI). The trend can be interpreted by comparing the two lines and what line is greater. When the negative DMI is greater than the positive DMI, there are more chances that the asset is trading in a sustained downtrend, and vice versa.
The system will enter trades when two conditions are met:
1) The MACD histogram turns bearish.
2) When the negative DMI is greater than the positive DMI.
EXIT
The strategy comes with a fixed take profit combined with a volatility stop, which acts as a trailing stop to adapt to the trend's strength. Depending on your long-term confidence in the asset, you can edit the fixed take profit to be more conservative or aggressive.
The position is closed when:
Take-Profit Exit: +8% price decrease from entry price.
OR
Stop-Loss Exit: Price crosses above the volatility stop.
In general, this approach suits medium to long term strategies. The backtesting for this strategy begins on 1 April 2022 to 18 July 2022 in order to demonstrate its results in a bear market. Back testing it further from the beginning of 2022 onwards further also produces good returns.
Pairs that produce very strong results include SOLUSDT on the 45m timeframe, MATICUSDT on the 2h timeframe, and AVAUSDT on the 1h timeframe. Generally, the back testing suggests that it works best on the 45m/1h timeframe across most pairs.
A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
Sherry on Crypto - MACD ScalpingThis indicator is originally made by someone else, I just modified it to increase its win rate.
How to use this indicator?
Step 1: This indicator only works in 5 minutes timeframe (BTC) . Apply 5 minutes timeframe in Tradingview.
Step 2: Apply 2 EMA(s), 1st EMA length 50, 2nd EMA length 200.
Step 3: Draw support and resistance and understand price action as well.
Step 4: Use RSI along with this indicator.
Strategy: When you see a down tick on the MACD in 5 minutes timeframe,
you are allow to take a long position. When you see an up tick on the MACD in 5 minutes timeframe, you are allow to take a Short position,
but RSI should be Included (you can do your own settings of RSI).
Recommended TP 0.50 and SL 0.40.
God Number Channel V1 (GNC V1)Channel, made of 5 MAs, which a made this way: High of N-period SMA - Low of N-period SMA + X-period SMA (check the code), where N and X are defined by your input.
Main purpose: helps you understand in what range price can move.
WARNING!
HAS TO BE USED WITH OTHER INDICATORS TO HAVE MORE ACCURATE ENTRIES!!!
If the price is above or below the channel, it means that the movement is very strong and you count it as a trend, but be careful then the price returns to the channel, as correction will follow very soon. Use fib correction tool to understand the approximate depth of correction, works pretty good.
Recommendation: consider using the Vortex Indicator( len 21 and 14 are fine; for trend) and "Vumanchu Divergencies + B"(for anything, but calibrate for accuracy, otherwise there will be too much false signals). If you want to see more options where the price might go, just add new MA and add/substract to/from its value avg1*(any of fibonacci correction levels, I personally use 1.618 and 2.618 and for me it is ok): plot(show_ma1 ? ma1+( [ [ ]]]*avg1) : na, color = ma1_color, title="MA №1")
Recommendations and feedback are welcome(!)
Take your wins
Fractal Potential EntryFractal Potential Entry combine 3 ema and fractal and follow the strategy from Trade Pro on YouTube:
www.youtube.com
with good performance on the 1 minute chart
Feature:
Alert Sell and buy Potential Entry
Happy Trading
LNL Pullback ArrowsBuying the dip has never been easier! LNL Pullback Arrows are here to pinpoint the best possible entries for the trend following setups. With the Pullback Arrows, trader can pick his own approach and risk level thanks to four different types of arrows. The goal of these arrows is to force the traders to scale in & out of trades which is in my opinion crucial when it comes to trend following strategies. These arrows were designed primarily for the daily & weekly time frame (swing trading).
Four Types of Pullback Arrows:
1. Aggro Arrows - Ideal for aggresive approach during parabolic trends. Sometimes trends are so strong that the price barely revisits the daily 8 EMA. This is where the aggro arrows can perfectly pinpoint the aggresive high risk entries. Ideal for halfsize or 1/4 size of the full position. Aiming for quick 1-2 day moves targeting the recent high/low. These arrows could be also named as scalping arrows for the swing traders. A quick In & Out.
2. HalfSize Arrows - Medium risk approach. First arrows to scale in. HalfSize arrows are the first sign that the pullback might be ending, yet there is still some space left for an even deeper pullback. That is the reason why they are called half-size. Ideally taken with half-sized position. When trading the HalfSize Arrows, It is better to have some "spare ammo in the gun" ready to use.
3. FullSize Arrows - Regular risk approach. These arrows represent a zone where the core of the posititon should be taken. The point of validity for the trend is not that far away, meaning the risk can be kept tight. Ideal for scailing the other halfs or quarters of the full position. Also great for more conservative traders or environments with higher volatility.
4. Rare Arrows - Offer the best risk to reward entries during the trend. Rare Arrows should be the "last kick" of the retracement, therefore stops can be positioned really tight. They either trigger the stop immidiately or they provide another juicy leg up or down in the direction of the trend. However, they really do appear rarely.
Simple EMA Cloud:
A simple cloud based on 21 and 55 exponential moving averages. This default length creates a pullback zone that is wide enough for the conservative traders but also give the opportunities to more aggresive traders. Alternatives such as 8 & 21, or 21 & 34 are forming the zone that is too aggresive and usually too thin. Of course, cloud can be fully adjusted or turned off completely. The only role of the cloud is to gauge the trend.
Tips & Tricks:
1.Importance of the Scailing
- As already stated, scailing is crucial to this since there is no way of knowing the exact level at which the price magically bounce every time. It is hard to tell where and which EMA will be respected. How can we know it will be 21 EMA every time? or 34 EMA or 10 EMA or 100 SMA or 50 DMA ... Single MA does not make a trend. This is the reason why scailing is so important. Scailing can make a difference.
2. Nothing is Perfect
- Same as any other study, nothing works 100% perfectly. Sometimes the setup will go right against you and sometimes the price will fade away sideways and breaks off the structure of the trend. This is not a magic certainty tool. This is just another probability tool.
3. Point of Validity & Other Studies
- Even though the pullback arrows can be a stand-alone strategy. It is important to use other indicators that visualize the actual trend. Whether its EMA Cloud or EMAs or DMI Bars or Keltner Channels, there should be something that validates the trend, something that tells the trend is over. (Pullback Arrows are not showing the actual stops!).
Hope it helps.
