Buy/Sell/Hold/Away? This script based on Simple Moving Average and Exponential Moving Average.
The Red Line is an exponential moving average with small length. It act as a main line.
The Black Line is an average of some past data of exponential moving average. Act as Trend Line
The green circles is an exponential moving average with medium length. It act as a signal line.
The Idea is, when the price move higher from it past,past,past, repeatedly in some duration, it will gain enough energy to fly to the highest.
Buy signal when red line cross down green circle. strong buy when red line cross down black line.
Sell signal when red line cross down green circle. strong buy when red line cross down black line.
Additional 1:
Triangle up(blue) indicate Buy Signal. it happen when the price break resistant with some condition and volume>1m
Triangle down(maroon) indicate Sell Signal. it happen when the price break support with some condition and volume>1m
The more triangle show in series, the strong the trend to move accordingly.
Additional 2:
Support and Resistance line.
Hope Benefit To You All.
Trend
Simple Hurst Exponent [QuantNomad]This is a simplified version of the Hurst Exponent indicator.
In the meantime, I'm working on the full version. It's computationally intensive, so it's a challenge to squeeze it to PineScript limits. It will require some time to optimize it, so I decided to publish a simplified version for now.
The Hurst exponent is used as a measure of long-term memory of time series. It relates to the autocorrelations of the time series, and the rate at which these decrease as the lag between pairs of values increases
The Hurst exponent is referred to as the "index of dependence" or "index of long-range dependence". It quantifies the relative tendency of a time series either to regress strongly to the mean or to cluster in a direction.
In short depend on value you can spot trending / reversing market.
Values 0.5 to 1 - market trending
Values 0 to 0.5 - market tend to mean revert
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Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as good as in historical backtesting.
This post and the script don’t provide any financial advice.
Moving Regression Prediction BandsIntroducing the Moving Regression Prediction Bands indicator.
Here I aimed to combine the principles of traditional band indicators (such as Bollinger Bands), regression channel and outlier detection methods. Its upper and lower bands define an interval in which the current price was expected to fall with a prescribed probability, as predicted by the previous-step result of the local polynomial regression (for the original Moving Regression script, see link below).
Algorithm
1. At every time step, the script performs local polynomial regression of the sample data within the lookback window specified by the Length input parameter.
2. The fitted polynomial is used to construct the Moving Regression time series as well as to extrapolate data, that is, to predict the next data point ( MRPrediction ).
3. The accuracy of local interpolation is estimated by means of the root-mean-square error ( RMSE ), that is, the deviation between the fitted polynomial and the observed values.
4. The MRPrediction and RMSE values calculated for the previous bar are then used to build the upper and lower bands , which I define as follows:
Upper Band = MRPrediction_prev + Multiplier *( RMSE_prev )
Lower Band = MRPrediction_prev - Multiplier *( RMSE_prev )
Here the Multiplier is a user-defined parameter that should be interpreted as a quantile in the standard normal distribution (the default value of 2.0 roughly corresponds to the 95% prediction interval).
To visualize the central line , the script offers the following options:
Previous-Period MR Prediction: MRPrediction_prev time series from the above equation.
MR: Conventional Moving Regression time series.
Ribbon: “Previous-Period MR Prediction” and “MR” curves plotted together and colored according to their relative value (green if MR > Previous MR Prediction; red otherwise).
Usage
My original idea was to use the band breakouts as potential trading signals. For example, the price crossing above the upper band is a bullish signal , being a potential sign that price is gaining momentum and is out of a previously predicted trend. The exit signal could be the crossing under the lower band or under the central line.
However, be aware that it is an experimental indicator, so you might fin some better strategies.
Feel free to play around!
Donchian Zig-Zag [LuxAlgo]The following indicator returns a line bouncing of the extremities of a Donchian channel, with the aim of replicating a "zig-zag" indicator. The indicator can both be lagging or lagging depending on the settings user uses.
Various extended lines are displayed in order to see if the peaks and troughs made by the Donchian zig-zag can act as potential support/resistance lines.
User Settings
Length : Period of the Donchian channel indicator, higher values will return fewer changes of directions from the zig-zag line
Bounce Speed : Determine the speed of bounces made by the zig-zag line, with higher values making the zig-zag line converge faster toward the extremities of the Donchian channel.
Gradient : Determine whether to use a gradient to color the area between each Donchian channel extremities, "On" by default.
Transparency : Transparency of the area between each Donchian channel extremities.
Usage
It is clear that this is not a very common indicator to see, as such usages can be limited and very hypothetical. Nonetheless, when a bounce speed value of 1 is used, the zig-zag line will have the tendency to lag behind the price, and as such can provides crosses with the prices which can provide potential entries.
The advantage of this approach against most indicators relying on crosses with the price is that the linear nature of the indicator allows avoiding retracements, thus potentially holding a position for the entirety of the trend.
Altho this indicator would not necessarily be the most adapted to this kind of usage.
When using a bounce speed superior to 1, we can see the predictive aspects of the indicator:
We can link the peaks/troughs made by the zig-zag with the precedent ones made to get potential support and resistance lines, while such a method is not necessarily accurate it still allows for an additional to interpret the indicator.
Conclusions
We presented an indicator aiming to replicate the behaviour of a zig-zag indicator. While somehow experimental, it has the benefits of being innovative and might inspire users in one way or another.
Put Call OscillatorThis is a volume-based oscillator used for detecting market sentiment.
This plots two moving averages of the CBOE S&P500 PCR (put call ratio), and a histogram to measure the distance between them. The histogram will generate signals of green (bullish) or red (bearish), depending on whether put volume is decreasing or increasing.
The moving averages are adjustable. They are set at 4 and 16 by default. Increasing the moving averages will generate less signals, while decreasing them will generate more signals.
The background will change color from red to green depending on whether the PCR is above or below 1.
I used capriole_charles script "Put/Call Ratio (PCR)" to help me build this.
New Map For TradersUsing previous principles, This setup plots 60 moving averages on the chart. The averages are colored using a normalized oscillation technique (FFT).
To achieve the same display as above, put the same indicator twice and set the 'osx' parameter of one to 0 and the other to 2.
Feel free to play with the 'mul' parameter in ranges between 1-90. Most useful ranges will be 4-16 in my opinion.
Leave me a message if you'd like to explore the behaviors of the fractal dimension further ;)
Trend MagicTrend Magic is originally a MT platform (MetaTrader) indicator and it can be used with any forex trading systems / strategies for additional confirmation of trading entries or exits. Converted the MT platform code to TradingView Pine version 4. Also you can use Multiple Time Frame.
It also works well with Crypto and Stock Markets.
Trend Magic consists of two main calculation parts as momentum and volatility:
First part is ATR based (like ATR Trailing Stop) logic, second part is all about CCI which also determines the color of Trend Magic.
Blue: when CCI is positive
Red: when CCI is negative
Also added alert condition regarding price crosses :
when LOW CrossesAbove TM
and HIGH CrossesBelow TM
Enjoy
Kıvanç Özbilgiç
Bollinger Band with Fib Golden Ratio (0.618)This startegy uses Fib level (0.618) of Bollinger Band for long entry. I find this is the only strategy which gives similar results on the different time frames. I have tested QQQ for 1H, 2H , 3H and 4H charts , all showed over 70% winning rate.
BB settings 50 , mult 1.5 (or you can use 2.5 or 3 )
Note: for the basis I have used VWMA instead of SMA .
BUY
=========
ema 50 is above ema 200
when the price close or low touches BB50(Fib0.615) lower band
Exit
=========
when the price crossover BB50(Fib0.615) upper band
Stop Loss
=========
Stop oss set to 5% , configurable
Strategy works similar to mean reversion style. When it touches the lower bans (which 0.615 level of the BB50) , it bounces from there.
Warning
=========
This strategy is for educational purposes only. Please do your own reserach for trading decissions.
LordPepe Stochastic SignalsThis is the Lord Pepe. Howdy. Basic buy/sell indicator to accumulate along a downtrend and release your stack during the uptrend and oversold levels of the stochastic. The buys should be used to stack, and sells indicate levels of profit taking, they do not signal a long term reversal, only < 25% of stack should be released on "OB" signals.
OB - overbought (sell)
OS - oversold (buy)
Donchian Channels Strategy by KrisWatersDoncian Channels is a trend tracking indicator developed by Richard Doncian. The upper line of the channel is determined by the highest value seen by the price in the defined period, the lower line of the channel is determined by the lowest value seen by the price in the defined period. The middle line takes the average value of the lower and upper channels.
Strategy Settings:
- Can apply only LONG positions.
- Can apply only SHORT positions.
- Use LONG/SHORT both.
- You can use ATR as a second exit condition. If ATR stop disabled, Donchian upper or lower channel value is use for the exit rule to long and short positions.
Strategy can be able to optimize by changing channel lengths and timeframe.
Statistical and Financial MetricsGood morning traders!
This time I want to share with you a little script that, thanks to the use of arrays, allows you to have interesting statistical and financial insights taken from the symbol on chart and compared to those of another symbol you desire (in this case the metrics taken from the perpetual future ETHUSDT are compared to those taken from the perpetual future BTCUSDT, used as a proxy for the direction of cryptocurrency market)
By enabling "prevent repainting", the data retrieved from the compared symbol won't be on real time but they will static since they will belong to the previous closed candle
Here are the metrics you can have by storing data from a variable period of candles (by default 51):
✓ Variance (of the symbol on chart in GREEN; of the compared symbol in WHITE)
✓ Standard Deviation (of the symbol on chart in OLIVE; of the compared symbol in SILVER)
✓ Yelds (of the symbol on chart in LIME; of the compared symbol in GRAY) → yelds are referred to the previous close, so they would be calculated as the the difference between the current close and the previous one all divided by the previous close
✓ Covariance of the two datasets (in BLUE)
✓ Correlation coefficient of the two datasets (in AQUA)
✓ β (in RED) → this insight is calculated in three alternative ways for educational purpose (don't worry, the output would be the same).
WHAT IS BETA (β)?
The BETA of an asset can be interpretated as the representation (in relative terms) of the systematic risk of an asset: in other terms, it allows you to understand how big is the risk (not eliminable with portfolio diversification) of an asset based on the volatilty of its yelds.
We say that this representation is made in relative terms since it is expressed according to the market portfolio: this portfolio is hypothetically the portfolio which maximizes the diversification effects in order to kill all the specific risk of that portfolio; in this way the standard deviation calculated from the yelds of this portfolio will represent just the not-eliminable risk (the systematic risk), without including the eliminable risk (the specific risk).
The BETA of an asset is calculated as the volatilty of this asset around the volatilty of the market portfolio: being more precise, it is the covariance between the yelds of the current asset and those of the market portfolio all divided by the variance of the yelds of market portfolio.
Covariance is calculated as the product between correlation coefficient, standard deviation of the first dataset and standard deviation of the second asset.
So, as the correlation coefficient and the standard deviation of the yelds of our asset increase (it means that the yelds of our asset are very similiar to those of th market portfolio in terms of sign and intensity and that the volatility of these yelds is quite high), the value of BETA increases as well
According to the Capital Asset Pricing Model (CAPM) promoted by William Sharpe (the guy of the "Sharpe Ratio") and Harry Markowitz, in efficient markets the yeld of an asset can be calculated as the sum between the risk-free interest rate and the risk premium. The risk premium of the specific asset would be the risk premium of the market portfolio multiplied with the value of beta. It is simple: if the volatility of the yelds of an asset around the yelds of market protfolio are particularly high, investors would ask for a higher risk premium that would be translated in a higher yeld.
In this way the expected yeld of an asset would be calculated from the linear expression of the "Security Market Line": r_i = r_f + β*(r_m-r_f)
where:
r_i = expected yeld of the asset
r_f = risk free interest rate
β = beta
r_m = yeld of market portfolio
I know that considering Bitcoin as a proxy of the market portfolio involved in the calculation of Beta would be an inaccuracy since it doesn't have the property of maximum diversification (since it is a single asset), but there's no doubt that it's tying the prices of altcoins (upward and downward) thanks to the relevance of its dominance in the capitalization of cryptocurrency market. So, in the lack of a good index of cryptocurrencies (as the FTSE MIB for the italian stock market), and as long the dominance of Bitcoin will persist with this intensity, we can use Bitcoin as a proxy of the market portfolio
Rainbow Trend IndicatorThis is an indicator based on the MA rainbow concept. It is possible to choose between 15 or 20 MA's and if all 15 MA's is picked, the calculation will be calculated on 15 MA's and if 20 is picked the calculation is calculated on 20 MA's. The indicator will then be a line which is assigned a value from the calculation based on the MA's. If the line is above the dashed zero line, meaning the line's last value is a positive value, the price is in a uptrend and if the line is below the dashed zero line, meaning the line's last value is a negative value, the price is in a downtrend.
In short
If the line is green, the price is in a uptrend. If the line is red, the price is in a downtrend.
Linear Correlation OscillatorYou don't need loops to get the rolling correlation between an input series and a linear sequence of values, this can be obtained from the normalized difference between a WMA and an SMA of the input series.
The closed-form solutions for the moving average and standard deviation of a linear sequence can be easily calculated, while the same rolling statistics for the input series can be computed using cumulative sums. All these concepts were introduced in previous indicators posts long ago.
This approach can allow to efficiently compute the rolling R-Squared of a linear regression, as well as its SSE.
Using the rolling correlation as a trend indicator is often attributed to John Ehlers with the correlation trend indicator (Correlation As A Trend Indicator), but the applications of this precise method can be traced back quite a while ago by a wide variety of users, in fact, the LSMA can be computed using this precise indicator. You can see an example where the correlation oscillator appears below:
Twin Optimized Trend Tracker Strategy TOTTAnıl Özekşi's new strategy which is a combination of 2 Optimized Trend Tracker lines which are vertical displaced from original version with a COEFFICIENT to cope with sideways' false signals which he explained in "Toy Borsacı İçin OTT Kullanım Kılavuzu 2"
original version of OTT:
OTT Strategy and Screener:
You can find a detailed explanation with subtitles from the developer of OTT Anıl Özekşi himself as: "Toy Borsacı İçin OTT Kullanım Kılavuzu 2"
SemaforHello Traders!
I have been away for a while but am recovering back gradually! Here is a gift to all of you.
It is based on the much loved ZigZag++ Script
The Semafor is used to spot future multi-level Supports and Resistance zones.
It is also useful to spot HL or LL or HH or LH zones at different Depth settings.
The red zones are the extreme places where the market has a higher chance of reversing while the green zones have the lowest setting with lower chances of the market reversal
To ease understanding of the code, I used the function `zigzag()` to show the simplicity in calculation
More will be coming this Year!
Volume Weighted SSL ChannelVolume-weighted SSl channel.
new concept of indicator that does not have in the entire library, different from SSL based on EMA or MA, this indicator can identify turns faster than a conventional indicator that only takes into account the price.
Enjoy and give the feedback.
On Balance Volume FieldsThe On Balance Volume (OBV) indicator was developed by Joseph E. Granville and published first in his book "New key to stock market profits" in 1963. It uses volume to determine momentum of an asset. The base concept of OBV is - in simple terms - you take a running total of the volume and either add or subtract the current timeframe volume if the market goes up or down. The simplest use cases only use the line build that way to confirm direction of price, but the possibilities and applications of OBV go far beyond that and are (at least to my knowledge) not found in existing indicators available on this platform.
If you are interested to get a deeper understanding of OBV, I recommend the lecture of the above mentioned book by Granville. All the features described below are taken directly from the book or are inspired by it (deviations will be marked accordingly). If you have no prior experience with OBV, I recommend to start simple and read an easy introduction (e.g. On-Balance Volume (OBV) Definition from Investopedia) and start applying the basic concepts first before heading into the more advanced analysis of OBV fields and trends.
Markets and Timeframes
As the OBV is "just" a momentum indicator, it should be applicable to any market and timeframe.
As a long term investor, my experience is limited to the longer timeframes (primarily daily), which is also how Granville applies it. But that is most likely due to the time it was developed and the lack of lower timeframe data at that point in time. I don't see why it wouldn't be applicable to any timeframe, but cannot speak from experience here so do your own research and let me know. Likewise, I invest in the crypto markets almost exclusively and hence this is where my experience with this indicator comes from.
Feature List
As a general note before starting into the description of the individual features: I use the colors and values of the default settings of the indicator to describe it. The general look and feel obviously can be customized (and I highly recommend doing so, as this is a very visual representation of volume, and it should suit your way of looking at a chart) and I also tried to make the individual features as customizable as possible.
Also, all additions to the OBV itself can be turned off so that you're left with just the OBV line (although if that's what you want, I recommend a version of the indicator with less overhead).
Fields
Fields are defined as successive UPs or DOWNs on the OBV. An UP is any OBV reading above the last high pivot and subsequently a DOWN is any reading below the last low pivot. An UP-field is the time from the first UP after a DOWN-field to the first DOWN (not including). The same goes for a DOWN field but vice versa.
The field serves the same purpose as the OBV itself. To indicate momentum direction. I haven't found much use for the fields themselves other than serving as a more smoothed view on the current momentum. The real power of the fields emerges when starting to determine larger trends of off them (as you will see soon).
Therefor the fields are displayed on the indicator as background colors (UP = green, DOWN = red), but only very faint to not distract too much from the other parts of the indicator.
Major Volume Trend
The major volume trend - from which Granville says, it's the one that tends to precede price - is determined as the succession of the highest highs and lowest lows of UP and DOWN fields. It is represented by the colors of the numbers printed on the highs and lows of the fields.
The trend to be "Rising" is defined as the highest high of an UP field being higher than the highest high of the last UP field and the lowest low of the last DOWN field being higher than the lowest low of the prior DOWN field. And vice versa for a "Falling" trend. If the trend does not have a rising or falling pattern, it is said to be "Doubtful". The colors are indicated as follows:
Rising = green
Falling = red
Doubtful = blue
ZigZag Swing count
The swing count is determined by counting the number of swings within a trend (as described above) and is represented by the numbers above the highs and lows of the fields. It determines the length and thus strength of a trend.
In general there are two ways to determine the count. The first one is by counting the swings between pivots and the second one by counting the swings between highs and lows of fields. This indicator represents the SECOND one as it represents the longer term trend (which I'm more interested in as it denotes a longer term perspective).
However, the ZigZag count has three applications on the OBV. The "simple ZigZag" is a count of three swings which mainly tells you that the shorter term momentum of the market has changed and the current trend is weakening. This doesn't mean it will reverse. A count of three downs is still healthy if it occurs on a strong uptrend (and vice versa) and it should primarily serve as a sign of caution. If the count increases beyond three, the last trend is weakening considerably, and you should probably take action.
The second count to look out for is five swings - the "compound ZigZag". If this goes hand in hand with breaking a major support/resistance on the OBV it can offer a buying/selling opportunity in the direction of the trend. Otherwise, there's a good chance that this is a reversal signal.
The third count is nine. To quote Granville directly: "there is a very strong tendency FOR MAJOR REVERSAL OF REND AFTER THE NINTH SWING" (emphasis by the author). This is something I look out for and get cautious about, although I have found signal to be weak in an overextended market. I have observed counts of 10 and even 12 which did not result in a major reversal and the market trended further after a short period of time. This is still a major sign of caution and should not be taken lightly.
Moving average
Although Granville talks only briefly about averages and the only mention of a specific one is the 10MA, I found moving averages to be a very valuable addition to my analysis of the OBV movements.
The indicator uses three Exponential Moving Averages. A long term one to determine the general direction and two short term ones to determine the momentum of the trend. Especially for the latter two, keep in mind that those are very indirect as they are indicators of an indicator anyway and I they should not necessarily be used as support or resistance (although that might sometimes be helpful). I recommend paying most attention to the longterm average as I've found it to be very accurate when determining the longterm trend of a market (even better than the same indicator on the price).
If the OBV is above the long term average, the space between OBV and average is filled green and filled red if below. The colors and defaults for the averages are:
long term, 144EMA, green
short term 1, 21EMA, blue
short term 2, 55EMA, red
Divergences
This is a very rudimentary adaption of the standard TradingView "Divergence Indicator". I find it helpful to have these on the radar, but do not actively use them (as in having a strategy based on OBV/price divergence). This is something that I would eventually pick up in a later version of the indicator if there is any demand for it, or I find the time to look into strategies based on this.
Comparison line
A small but very helpful addition to the indicator is a horizontal line that traces the current OBV value in real time, which makes it very easy to compare the current value of the OBV to historic values (which is a study I can highly recommend).
Ichimoku Trend DirectionThis script will help you detect the current trend of market use Ichimoku trading system. We use the default parameters.
To reduce risk, ONLY trade follow the trend of high time frame!
Very simple to use:
- Green background when market Up trend
- Red background when market Down trend
Have a nice trade! :P
HalfTrendA popular trend indicator based on ATR. Similar to the SuperTrend but uses a different trend's identification logic.
I am publishing a disclosed code without license. Remember that in the future you may see a lot of paid IO scripts called BuySellScalper, Trend Trader Karan, Trend Trader and etc (by other authors) which will be based on this script. I found the same script on Ebay for $10 with a free shipping. Beware, always check and follow one Russian wisdom: "Do not pay for something you can get for free".
EMA CrossoversUseful for identifying and receiving alerts about uptrends and downtrends.
This script uses two Exponential Moving Averages (EMAs) to find price uptrends and downtrends. An Exponential Moving Average (EMA) is a type of moving average that places a greater weight and significance on the most recent data points. The script produces uptrend and downtrend signals based on crossovers and divergences between the two EMAs, the user will be able to spot a trend change (when the EMAs crossover) and to determine the strength of the current trend (when the EMAs diverge). It is also posible to get alerts for uptrends and downtrends on the web and mobile app with sound and pop-ups as well as via email. The optimal time to enter and exit the market can be concluded from this trend changes.
The user can set their own EMAs, by default they are set to 21 and 55 periods for medium and long term respectively. When the medium term EMA crosses below the long term EMA the asset is in a downtrend and the price will decline, and when the medium term EMA crosses above the long term EMA the asset is in an uptrend and price will increase.
This scripts plots the following indicators and signals on the chart to help the user to identify trends:
1.- Medium and long term EMAs as lines overlaid on the price chart.
2.- Up green triangles above bars when the price is on an uptrend and down red triangles below bars when the price is on a downtrend.
3.- Arrows with text to indicate the start of an uptrend or downtrend.
The user can enable and disable the indicators and signals as well as set colors and shapes to their liking.
This script also lets the user create alerts for uptrends and downtrends. To create a new alert using this script follow this instructions:
1.- Once you added this script to your chart, go to the alerts panel (right on web or bottom tool bar on the mobile app) and add a new alert (alarm clock icon with a plus sign).
2.- A modal window will open. On the “Condition” dropdown menu select “EMA Crossovers”.
3.- On the next dropdown menu (right below the “Condition” one) you can select from two types of alerts “Uptrend started” and “Downtrend started”.
4.- Lastly you can set all the normal alert options and create the alert.
Consolidation Ranges [kingthies] Consolidation Range Analysis
Published by Eric Thies, January 2021
█ Indicator Summary
This tool calculates, analyzes and plots the visualization of a relative range over a given period of time
By adding to charts, users are enabled to see the impulsive nature of market cycles, along with their efforts to consolidate thereafter
The default period is 30, and should be adjusted to users preference
The default input is the current close price, on the chosen timeframe of the chart
█ Script Source
//
//@version=4
//© kingthies || This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
study("Consolidation Ranges ", shorttitle="CR ", overlay=true)
// !<------ User Inputs ----->
src = input(close, title='Range Input (Default set to Close'), lengthEMA=input(30,title='Length'),zoneToggle = input(true, title="Toggle Zone Highlights"), iCol = color.new(#FFFFFF, 100),
// !<---- Declarations & Calculations ---- >
trndUp = float(na),trndDwn = float(na), mid = float(na), e = ema(src, lengthEMA)
trndUp := src < nz(trndUp ) and src > trndDwn ? nz(trndUp ) : high, trndDwn := src < nz(trndUp ) and src > trndDwn ? nz(trndDwn ) : low, mid := avg(trndUp, trndDwn)
// !< ---- Plotting ----->
highRange = plot(trndUp == nz(trndUp ) ? trndUp : na, color=color.white, linewidth=2, style=plot.style_linebr, title="Top of Period Range")
lowRange = plot(trndDwn == nz(trndDwn ) ? trndDwn : na, color=color.white, linewidth=2, style=plot.style_linebr, title="Bottom of Period Range")
xzone = plot(zoneToggle ? src > e ? trndDwn : trndUp : na, color=iCol, style=plot.style_circles, linewidth=0, editable=false)
fill(highRange, xzone, color=color.lime,transp=70), fill(xzone, lowRange, color=color.red,transp=70)
//
MrBS:Directional Movement Index [Trend Friend Strategy]This goes with my MrBS:DMI+ indicator. I originally combined them into one, but then you cannot set alerts based on what the ADX and DMI is doing, only strategy alerts, so separate ones have more flexibility and uses.
Indicator Version is found under "MrBS:Directional Movement Index " ()
//// THE IDEA
The majority of profits made in the market come from trending markets. Of course there are strategies that would say otherwise but for the majority of people, THE TREND IS YOUR FRIEND (until the end). The idea is to follow the trend, entering once it has established its self and exiting positions when the trend weakens. This strategy gives a rough idea of the returns produced from following purely the ADX signals. At first Heikin Ashi values were used for the calculation but the results show it's not that effective. The functionality to switch between calculation types has been left in, so we can uses HA candle data to generate signals from while looking at an OHLC chart, if we want to experiment. Due to the way strategies work, we are unable to get reliable results when running the strategy on the HA chart even if we are calculating the signals from the real OHLC values. It is best to always run strategies on standard charts.
When using this strategy, I look for confirmation of the signal based on stochastic (14:3:6) direction, reversal level of stochastic, and divergance, to add confidence and adjust position size accordingly. I am going to try and code some version of that in future updates, if anyone can help or has suggestions please drop me a message.
//// INDICATOR DETAILS
- The default settings are for optimized Daily charts, for 4 hour I would suggest a smoothing of 2.
- The default values used for calculation are the Real OHLC, we can change this to Heikin Ashi in the menu.
- The strategy enters a position when ADX crosses the threshold level, and closes the position when ADX starts to fall.
- There is a signal filter in the form of a 377 period Hull Moving Average, which the price must be above or bellow for long and short positions respectively.
- The strategy closes the position when a cross-under of the ADX and its 4 period EMA. This is an attempt to stay into positions longer as sometimes the ADX will fall for 1 bar and then keep rising, while the overall trend is strong. The downside to this is that we exit trades later and this affects our max drawdown.
Moving Average Compilation by CryptonerdsThis script contains all commonly used types of moving averages in a single script. To our surprise, it turned out that there was no script available yet that contains multiple types of moving averages.
The following types of moving averages are included:
Simple Moving Averages (SMA)
Exponential Moving Averages (EMA)
Double Exponential Moving Averages (DEMA)
Display Triple Exponential Moving Averages (TEMA)
Display Weighted Moving Averages (WMA)
Display Hull Moving Averages (HMA)
Wilder's exponential moving averages (RMA)
Volume-Weighted Moving Averages (VWMA)
The user can configure what type of moving averages are displayed, including the length and up to five multiple moving averages per type. If you have any other request related to adding moving averages, please leave a comment in the section below.
If you've learned something new and found value, leave us a message to show your support!
