Pearson's R Convergence DivergenceThis script calculates the convergence divergence and breakouts from the deviations for a fast and slow linear regression slope.
This can be used to predict major market moves before they happen.
For users familiar with MacD, the blue line is similar to the MacD line and the orange line the signal.
The difference is this is not a moving average comparison but a comparison between Pearson's R values.
-0.1 (positive direction)
0.1 (negative direction)
This is why the colors look inverse for a typical MacD.
How to use this:
The idea is that when both trends converge in the 0.8 or -0.8 range and you see a breakout cross occur on either line then the price has a high likelihood of reversing its current trend.
If you see a green cross it means the top of the linear regression for the 'fast' or 'slow' linear regression deviation was broken by the current price. This can signify that upward movement is coming soon.
On the flip side a red cross means the bottom of the linear regression for the 'fast' or 'slow' linear regression deviation was broken by the current price. This can signify that downward movement is coming soon.
These crosses mean a lot more if the pearson's R value is already maxed out near 0.8 or -0.8.
This indicator works because the more sure a trend becomes the more likely it is to break as more traders see the pattern.
The histogram colors do not mean much being 'red' or 'green', what you want to look for is when the histogram starts to approach the 0 mark. This signifies that both linear regression trends are about to reach their peak before reversing trend. So don't confuse this with how you might read the MacD even though it looks very similar. The histogram sloping towards the 0 line will give you a clue how long it might take before the reversal occurs .
Please PM me if you have any questions, and enjoy!
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High Liquidity Zones and Threshold VolumeThe High Liquidity Zones indicator is designed to identify areas of significant liquidity in the market. It helps traders recognize regions where trading volume is notably higher, indicating potential areas of increased market activity and interest.
The indicator calculates the average volume over a specified lookback period, which can be customized according to individual preferences. This average volume acts as a reference point to determine the threshold volume level. The threshold percentage input allows users to set the sensitivity of the indicator, defining the minimum volume required for an area to be considered a high liquidity zone.
When the current volume surpasses the threshold volume level, the indicator highlights these areas as high liquidity zones. This visual representation allows traders to quickly identify and focus on periods of heightened trading activity. The high liquidity zones are marked with square shapes below the histogram, providing a clear visual indication on the chart.
The first plot line represents the threshold volume level as a histogram, showing the volume levels in relation to the threshold. This histogram helps traders assess the magnitude of the volume in the identified high liquidity zones.
The second plot line represents the threshold volume's simple moving average (SMA) over the lookback period. The SMA acts as a reference line, smoothing out fluctuations in the threshold volume and providing a more stable measure of high liquidity zones. Traders can use this line to better understand the overall trend and dynamics of liquidity.
The High Liquidity Zones indicator offers flexibility, allowing traders to adapt it to their preferred trading style and timeframe. By adjusting the lookback period and threshold percentage, users can fine-tune the sensitivity of the indicator based on their trading strategies and market conditions.
Furthermore, traders can combine the High Liquidity Zones indicator with other technical analysis tools to confirm trading signals or identify areas of potential support and resistance. It can help them locate price levels where market participants have a substantial presence and where significant buying or selling pressure may occur.
Overall, the High Liquidity Zones indicator is a valuable tool for traders seeking to gain insights into market liquidity dynamics. By highlighting areas of intense trading activity, it assists in making informed trading decisions and identifying opportunities within the market.
Price Action - Support & Resistance + MACD LONG StrategyUsing "Price Action - Support & Resistance by DGT" and the MACD (Moving Average Convergence Divergence) indicator in TradingView can help develop a trade strategy. Here's a step-by-step approach you can follow:
1. Identifying Support and Resistance Levels: Apply the "Price Action - Support & Resistance by DGT" indicator to your chart. This indicator helps you identify key support and resistance levels based on price action. These levels act as potential areas where the price may reverse or consolidate.
2. Confirming Support and Resistance Levels: Once the indicator has plotted support and resistance levels on your chart, analyze the historical price action around these levels. Look for multiple touches or bounces from the same level, which adds strength to the support or resistance zone.
3. Analyzing the MACD Indicator: Add the MACD indicator to your chart. The MACD consists of two lines: the MACD line and the signal line, along with a histogram representing the difference between the two lines. The MACD helps identify momentum and potential trend reversals.
When the MACD line crosses above the signal line and the histogram turns positive, it suggests bullish momentum.
4. Identifying Trade Opportunities:
Bullish Trade: Look for a bullish setup when the price approaches a strong support level identified by the "Price Action - Support & Resistance by DGT" indicator. Wait for the MACD lines to cross above the signal line and the histogram to turn positive, indicating bullish momentum. Enter a long position with a stop loss below the
support level.
Managing the Trade: Once you enter a trade, consider setting a target based on the distance between your entry point and the nearest significant support or resistance level. You can also use trailing stop losses or other risk management techniques to protect your profits and limit potential losses.
Remember that no trading strategy is guaranteed to be successful, and it's important to practice proper risk management and conduct thorough analysis before making any trading decisions. Additionally, it's recommended to backtest and demo trade this strategy before using it with real money.
ETH Volume*Close Top Exchanges in millions $The script is designed to create a custom indicator that calculates the total volume of Ethereum traded on various exchanges, calculated in millions of dollars, and then plots a histogram of that volume along with a Simple Moving Average (SMA) of the volume.
The script starts by setting some input parameters such as the length of the SMA and the range period. It then requests data on the volume of Ethereum traded on several exchanges such as Binance, Coinbase, Kraken, and others. It calculates the combined total volume across all these exchanges and multiplies it by the close price of Ethereum to get a value in millions of dollars.
The script then checks if the volume is rising while the price is lower than the previous 5 bars high and higher than the previous 5 bars low, and if so, it sets the color of the histogram bars to white. It then plots the histogram bars and the SMA on the chart.
BTC Volume*Close from Top ExchangesThe script is designed to create a custom indicator that calculates the total volume of Bitcoin traded on various exchanges, calculated in millions of dollars, and then plots a histogram of that volume along with a Simple Moving Average (SMA) of the volume.
The script starts by setting some input parameters such as the length of the SMA and the range period. It then requests data on the volume of Bitcoin traded on several exchanges such as Binance, Coinbase, Kraken, and others. It calculates the combined total volume across all these exchanges and multiplies it by the close price of Bitcoin to get a value in millions of dollars.
The script then checks if the volume is rising while the price is lower than the previous 5 bars high and higher than the previous 5 bars low, and if so, it sets the color of the histogram bars to white. It then plots the histogram bars and the SMA on the chart.
OBV-MACDThe OBV-MACD indicator is a momentum-based technical analysis tool that helps traders identify trend reversals and trend strength. This Pine script is an implementation of the OBV-MACD indicator that uses the On-Balance Volume (OBV) and Moving Average Convergence Divergence (MACD) indicators to provide a momentum data of OBV.
The OBV-MACD indicator uses the OBV to calculate the cumulative volume, which is then smoothed using two moving averages - fast and slow. The difference between these moving averages is plotted as a histogram, with a signal line plotted over it. A buy signal is generated when the histogram crosses above the signal line, indicating a bullish trend, while a sell signal is generated when the histogram crosses below the signal line, indicating a bearish trend.
This Pine script also includes an OBV-MACD-Donchian version that incorporates Donchian channels for the OBV-MACD. The Donchian channel is a technical analysis indicator that helps traders identify the highs and lows of an asset's price over a certain period. The OBV-MACD-Donchian version uses the OBV-MACD indicator along with the Donchian channels to provide signals that the momentum of OBV is making new high/low during that period of time.
Traders can customize the input parameters of the OBV-MACD indicator, such as the timeframe, method of calculation for the moving averages, and the lengths of the moving averages and breakout lengths. The colors of the plot can also be customized to suit the trader's preferences.
Strategy Myth-Busting #11 - TrendMagic+SqzMom+CDV - [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 11th one is an automated version of the "Magic Trading Strategy : Most Profitable Indicator : 1 Minute Scalping Strategy Crypto" strategy from "Fx MENTOR US" who doesn't make any official claims but given the indicators he was using, it looked like on the surface that this might actually work. The strategy author uses this on the 1 minute and 3 minute timeframes on mostly FOREX and Heiken Ashi candles but as the title of his strategy indicates is designed for Crypto. So who knows..
To backtest this accurately and get a better picture we resolved the Heiken Ashi bars to standard candlesticks . Even so, I was unable to sustain any consistency in my results on either the 1 or 3 min time frames and both FOREX and Crypto. 10000% Busted.
This strategy uses a combination of 3 open-source public indicators:
Trend Magic by KivancOzbilgic
Squeeze Momentum by LazyBear
Cumulative Delta Volume by LonesomeTheBlue
Trend Magic consists of two main indicators to validate momentum and volatility. It uses an ATR like a trailing Stop to determine the overarching momentum and CCI as a means to validate volatility. Together these are used as the primary indicator in this strategy. When the CCI is above 0 this is confirmation of a volatility event is occurring with affirmation based upon current momentum (ATR).
The CCI volatility indicator gets confirmation by the the Cumulative Delta Volume indicator which calculates the difference between buying and selling pressure. Volume Delta is calculated by taking the difference of the volume that traded at the offer price and the volume that traded at the bid price. The more volume that is traded at the bid price, the more likely there is momentum in the market.
And lastly the Squeeze Momentum indicator which uses a combination of Bollinger Bands, Keltner Channels and Momentum are used to again confirm momentum and volatility. During periods of low volatility, Bollinger bands narrow and trade inside Keltner channels. They can only contract so much before it can’t contain the energy it’s been building. When the Bollinger bands come back out, it explodes higher. When we see the histogram bar exploding into green above 0 that is a clear confirmation of increased momentum and volatile. The opposite (red) below 0 is true when there are low periods. This indicator is used as a means to really determine when there is premium selling plays going on leading to big directional movements again confirming the positive or negative momentum and volatility direction.
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.
Trading Rules
1 - 3 min candles
FOREX or Crypto
Stop loss at swing high/low | 1.5 risk/ratio
Long Condition
Trend Magic line is Blue ( CCI is above 0) and above the current close on the bar
Squeeze Momentum's histogram bar is green/lime
Cumulative Delta Volume line is green
Short Condition
Trend Magic line is Red ( CCI is below 0) and below the current close on the bar
Squeeze Momentum's histogram bar is red/maroon
Cumulative Delta Volume line is peach
Stochastic Moving Average Convergence Divergence (SMACD)This is my attempt at making a Stochastic MACD indicator. To get this to work I have introduced a DC offset to the MACD histogram output. I figured that if theirs a Stochastic RSI their might as well be a Stochastic everything else! lmao enjoy. Honestly, from what I can tell it's even faster than Stochastic Smooth RSI.
The Stochastic Oscillator (STOCH) is a range bound momentum oscillator. The Stochastic indicator is designed to display the location of the close compared to the high/low range over a user defined number of periods. Typically, the Stochastic Oscillator is used for three things; Identifying overbought and oversold levels, spotting divergences and also identifying bull and bear set ups or signals
MACD is an extremely popular indicator used in technical analysis. MACD can be used to identify aspects of a security's overall trend. Most notably these aspects are momentum, as well as trend direction and duration. What makes MACD so informative is that it is actually the combination of two different types of indicators. First, MACD employs two Moving Averages of varying lengths (which are lagging indicators) to identify trend direction and duration. Then, MACD takes the difference in values between those two Moving Averages (MACD Line) and an EMA of those Moving Averages (Signal Line) and plots that difference between the two lines as a histogram which oscillates above and below a center Zero Line. The histogram is used as a good indication of a security's momentum
[blackcat] L3 Banker Fund AttackLevel 3
Background
This indicator is used to capture the movement of the banker fund. The buying and selling point is determined according to whether the momentum of the banker fund and the price momentum resonate.
How to use the indicator:
The red column line indicates that the banker fund accumulation signal appears, and the following 2 conditions are all satisfied to buy; (both above the green line of the banker fund attack threshold)
1. The yellow line and the purple line all cross the red accumulation histogram signal;
2. The yellow and purple trend lines are up
Key point: If the yellow line crosses the green line of the banker fund attack threshold, it will be pulled up or the big market will open! The main thing is to see the red accumulation histogram signal, or the green line that crosses the banker fund attack threshold. If there is a red accumulation histogram signal, it means that there are main low-acquisition chips, and start trading on the left to open a position. The area above the green line of the banker fund attack threshold belongs to the main force pulling stage. When the green line of the banker fund attack threshold is not broken upwards, there is still a lot of profit space, but if it can be effectively broken through, it is highly profitable!
Remarks
This indicator only effective for instruments that contains banker fund. If there is no obvious large fund inside, the indicator is not as meaningful as it is called.
I verified it worked well for > 4H or 1D timeframe. For the other time frames, you may need to check and verify by yourself.
Feedbacks are appreciated.
HMA Slope Variation [Loxx]HMA Slope Variation is an indicator that uses HMA moving average to calculate a slope that is then weighted to derive a signal.
The center line
The center line changes color depending on the value of the:
Slope
Signal line
Threshold
If the value is above a signal line (it is not visible on the chart) and the threshold is greater than the required, then the main trend becomes up. And reversed for the trend down.
Colors and style of the histogram
The colors and style of the histogram will be drawn if the value is at the right side, if the above described trend "agrees" with the value (above is green or below zero is red) and if the High is higher than the previous High or Low is lower than the previous low, then the according type of histogram is drawn.
What is the Hull Moving Average?
The Hull Moving Average ( HMA ) attempts to minimize the lag of a traditional moving average while retaining the smoothness of the moving average line. Developed by Alan Hull in 2005, this indicator makes use of weighted moving averages to prioritize more recent values and greatly reduce lag.
Included
Alets
Signals
Bar coloring
Loxx's Expanded Source Types
T3 Slope Variation [Loxx]T3 Slope Variation is an indicator that uses T3 moving average to calculate a slope that is then weighted to derive a signal.
The center line
The center line changes color depending on the value of the:
Slope
Signal line
Threshold
If the value is above a signal line (it is not visible on the chart) and the threshold is greater than the required, then the main trend becomes up. And reversed for the trend down.
Colors and style of the histogram
The colors and style of the histogram will be drawn if the value is at the right side, if the above described trend "agrees" with the value (above is green or below zero is red) and if the High is higher than the previous High or Low is lower than the previous low, then the according type of histogram is drawn.
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
Alets
Signals
Bar coloring
Loxx's Expanded Source Types
A_HMS_RSI_COMPOSITMy majic Macd Indicator with Ema base macd is My great Indicator that combine four ema base macd lines with its signal lines that show price gravity by best way , and one spatial chart that is the best part of this magic indicator that help you to trading without any problem
for better use note that:
green fill line is ema 66 and ema 199 macd and signal its name is macd very slow signal line
blue fill line is ema 19 and ema 66 macd and signal its name is macd normal signal line
red fill line is ema 9 and ema 19 macd and signal its name is macd very fast signal line
black line is ema 4 and ema 14 macd its name is macd main signal line
in all of this lines we can define divergence
when this lines crossing over and under from together each of this crossings give me some signals and because this signals very much we cant describe thats in some lines
but note that we in fact trade just by black line but short and long position determine by position of black line instead of other lines and positions of other lines from each ones
purple line is rsi line
red line is composite line
blue line is rmi line
red and Blue below line is Slow Stochastic lines
blue and orange line is Stochastic ema with ema12 - ema21
and third chart is a secret indicator that help more to determine best place to start trading
A_HMS_RSI is My great Indicator that RSI , RMI and , momentum of price movement by a histogram , that help you to trading without any problem
for better use note that:
blue line is rsi line with hl2 source and 14 length
low color line is rmi line with momentum 33
rmi of price with momentum 33 is a very good signal for long positions.
momentum histogram help us to define strong of price motion in each time
some futures is hidden by default:
composite red and green signal line
rmi of price with momentum 4
ema 13, 33 of rmi as signal line and rsi and composit
finaly u can change any colors from setting
in background we determine some filled zones for better use of Indicator
when composite line run away from histogram momentum increase rapidly
when composite and rsi line is in same way its time to get position .
rmi of price with momentum 20 is a very good signal for long positions.
some futures is hidden by default:
composite red and green signal line
rmi of price with momentum 20
ema 13, 33 of rmi as signal line
finaly u can change any colors from setting
and you can get stoch signals too
in background we determine some filled zones for better use of Indicator
Distance from Vwap// How it Works \\
Measuring the distance of the close price from a higher timeframe VWAP - Volume Weighted Average Price
There is a threshold which is calculated by looking back at the previous x amount of bars and storing the highest/lowest values
If the distance from the vwap stretches above that threshold, the histogram will go green if price is above VWAP and red if its below the vwap
If the distance from the vwap reaches below the low threshold you will see the histogram flashes orange
// Settings \\
In the settings you have the ability to change what timeframe the indicator is calculated on, as well as this you can change the timeframe the VWAP is calculated on.
I always recommend using a higher timeframe vwap as they tend to me more respected
e.g on the hourly timeframe, I use the weekly VWAP, on 1 minute timeframe you may want to use 4 hour timeframe but obviously feel free to experiment
// Use Case \\
When histogram is flashing green, prices is pulling far away from the vwap, obviously you don't want to be buying a falling knife but if you have levels of confluence this can help spot reversals.
I personally wait until the first candle after its been green to get confirmation of the fall weakening. Vica versa for reds and shorts/sells.
When you see orange flashes, this shows that price has been consolidating and the price is very close to the higher time frame VWAP which could be considered a safe entry point as they tend to lead to a big move to follow
// Suggestions \\
Happy for anyone to make any suggestions on changes which could improve the script,
// Terms \\
Feel free to use the script, If you do use the script could you please just tag me as I am interested to see how people are using it. Good Luck!
KINSKI Multi Trend OscillatorThe Multi Trend Oscillator is a tool that combines the ratings of several indicators to facilitate the search for profitable trades. I was inspired by the excellent indicator "Technical Ratings" from Team TradingView to create an alternative with a technically new approach. Therefore, it is not a modified copy of the original, but newly conceived and implemented.
The recommendations of the indicator are based on the calculated ratings from the different indicators included in it. The special thing here is that all settings for the individual indicators can be changed according to your own needs and displayed as a histogram and MA line. This provides an excellent visual control of your own settings. Alarms are also triggered.
Criteria for determining the rating
Relative Strength Index (RSI)
Buy - Crossover oversold level and indicator < oversold level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Relative Strength Index (RSI) Laguerre
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Noise free Relative Strength Index (RSX)
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Money Flow Index (MFI)
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Commodity Channel Index (CCI)
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Moving Average Convergence/Divergence (MACD)
Buy - values of the main line > values of the signal line and rising
Sell - values of the main line < values of the signal line and falling
Neutral - neither Buy nor Sell
Klinger
Buy - indicator >= 0 and rising
Sell - indicator < 0 and falling
Neutral - neither Buy nor Sell
Average Directional Index (ADX)
Buy - indicator > 20 and +DI line crosses over the -DI line and rising
Sell - indicator > 20 and +DI line crosses below the -DI line and falling
Neutral - neither Buy nor Sell
Awesome Oscillator
Buy - Crossover 0 and values are greater than 0, or exceed the zero line
Sell - Crossunder 0 and values are lower than 0, or fall below the zero line
Neutral - neither Buy nor Sell
Ultimate Oscillator
Buy - Crossover oversold level and indicator < oversold level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Williams Percent Range
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder Oversold Level and Indicator >= Oversold Level and falling
Neutral - neither Buy nor Sell
Momentum
Buy - Crossover 0 and indicator levels rising
Sell - Crossunder 0 and indicator values falling
Neutral - neither Buy nor Sell
Total Ratings
The numerical value of the rating "Sell" is 0, "Neutral" is 0 and "Buy" is 1. The total rating is calculated as the average of the ratings of the individual indicators and are determined according to the following criteria:
MaxCount = 12 (depending on whether other oscillators are added).
CompareSellStrong = MaxCount * 0.3
CompareMid = MaxCount * 0.5
CompareBuyStrong = MaxCount * 0.7
value <= CompareSellStrong - Strong Sell
value < CompareMid and value > CompareSellStrong - Sell
value == 6 - Neutral
value > CompareMid and value < CompareBuyStrong - Buy
value >= CompareBuyStrong - Strong Buy
Understanding the results
The Multi Trend Oscillator is designed so that its values fluctuate between 0 and currently 12 (maximum number of integrated indicators). Its values are displayed as a histogram with green, red and gray bars. The bars are gray when the value of the indicator is at half of the number of indicators used, currently 12. Increasingly saturated green bars indicate increasing values above 6, and increasingly saturated red bars indicate increasingly decreasing values below 6.
The table at the end of the histogram shows details (can be activated in the settings) about the overall rating and the individual indicators. Its color is determined by the rating value: gray for neutral, green for buy or strong buy, red for sell or strong sell.
The following alarms are triggered:
Multi Trend Oscillator: Sell
Multi Trend Oscillator: Strong Sell
Multi Trend Oscillator: Buy
Multi Trend Oscillator: Strong Buy
Selected MACD Areas CompareThis is a simple tool to compare two selected MACD histogram area. The MACD histogram area is sometimes used to determine trend reversal or trend strength. One may have difficulty with this when the compared MACD areas are of different shape or similar in size. This indicator/tool allows user to select two time periods on the chart and get a precise compare result.
To use the indicator, place a regular MACD indicator on the chart which shows the histogram, then add this indicator and select the two areas of which you want to compare the size. Please make sure that the regular MACD indicator this one have the same source.
Scalping Trading System ALERT Crypto and StocksThis is the alert version of the strategy with the same name.
Indicators
SImple Moving Average
Exponential Moving Average
Keltner Channels
MACD Histogram
Stochastics
Rules for entry
long= Close of the candle bigger than both moving averages and close of the candle is between the top and bot levels from Keltner . At the same time the macd histogram is negative and stochastic is below 50.
short= Close of the candle smaller than both moving averages and close of the candle is between the top and bot levels from Keltner . At the same time the macd histogram is positive and stochastic is above 50.
Rules for exit
We exit when we meet an opposite reverse order.
This strategy has no risk management inside, so use it with caution !
Scalping Trading System bot Crypto and StocksThis is a trend trading strategy scalping bot that can work with any type of market. However I concluded my tests so far with Crypto, Stocks and Forex, and with optimizations always could be found some profitable settings.
Indicators
SImple Moving Average
Exponential Moving Average
Keltner Channels
MACD Histogram
Stochastics
Rules for entry
long= Close of the candle bigger than both moving averages and close of the candle is between the top and bot levels from Keltner. At the same time the macd histogram is negative and stochastic is below 50.
short= Close of the candle smaller than both moving averages and close of the candle is between the top and bot levels from Keltner. At the same time the macd histogram is positive and stochastic is above 50.
Rules for exit
We exit when we meet an opposite reverse order.
This strategy has no risk management inside, so use it with caution !
Full Swing Gold Vwap Macd SMO StrategyThis is a full strategy designed for gold market using 12h timeframe chart.
Its components are:
VWAP monthly
SMO oscillator
MACD histogram
Rules for entry:
For long: when enter when close of the candle is above vwap monthly, current histogram is higher than the previous one and SMO oscillator is above 0
For long: when enter when close of the candle is below vwap monthly, current histogram is lower than the previous one and SMO oscillator is below 0
Rules for exit:
We exit the trade if we get a reverse condition.
We also exit the trade based on a risk management system, both for SL and TP using % movements.
If you have any questions let me know !
Full Crypto Swing Strategy ALMA Cross with MACDThis is a full crypto swing strategy designed.
From my testing it looks like it perform the best on timeframes 4h +.
The below example has been adapted to BNB/USDT, using the entire period since 2017 until present day, with a comission of 0.03% ( which is the comission for the futures on binance).
Its components are :
ALMA Fast
ALMA Slow
MACD Histogram
Rules for entry
For long, we have a crossover of the fast alma with the slow one and the histogram is ascending.
For short, we have a crossunder of the fast alma with the slow one and the histogram is descending.
Rules for exit
We exit based on a risk management system for TP and SL, or when we receive an opposite condition than the initial one.
Regarding risk management
0.05 = 5% movement
2 = 200% movement
0.001 = 0.1% movement
If you have any questions, let me know !
Stock trending strategy This is a long only strategy designed maily for stock markets and futures. In general it works best with 1h, however it can be optimized with other timeframes as well.
Components:
VWAP
MACD histogram
EMA 9
Rules for entry
Long :
For VWAP: close is above the vwap daily
EMA: close is above the moving average
MACD histogram is above 0
Short:
For VWAP: close is belowthe vwap daily
EMA: close is below the moving average
MACD histogram is below 0
Rules for exit
This strategy does not have any risk management inside. Instead it exits whenver it receives an opposite signal form the original one used for entry.
If you have any questions let me know !
Ichimoku with MACD/ CMF/ TSIThis is a very powerful trend strategy designed for markets such as stocks market , stock index and crypto.
For time frames I found out that 1h seems to do the trick.
Components:
Ichimoku full pack
MACD histogram
CMF oscillator
TSI oscillator
Rules for entry
Long :
For Ichimoku:Tenkan part of cloud is bigger than kijun, Chikou is above 0 , close of a candle is above the Senkou
MACD histogram is above 0
CMF oscillator is positive and bigger than 0.1
TSI oscillator is above 0
Short:
For Ichimoku:Tenkan part of cloud is smaller than kijun, Chikou is below 0 , close of a candle is belowthe Senkou
MACD histogram is below 0
CMF oscillator is negative and below -0.1
TSI oscillator is below 0
Rules for exit
This strategy does not have any risk management inside. Instead it exits whenver it receives an opposite signal form the original one used for entry.
If you have any questions let me know !
Normalized Quantitative Qualitative Estimation nQQENormalized version of Quantitative Qualitative Estimation QQE:
Normalized QQE tries to overcome the problems of false signals due to RSI divergences on the original QQE indicator.
The main purpose is to determine and ride the trend as far as possible.
So users can identify:
UPTREND : when nQQE Histogram is GREEN (nQQE is above 10)
DOWNTREND : when nQQE Histogram is RED (nQQE is below -10)
SIDEWAYS: when nQQE Histogram is YELLOW (nQQE is between -10 and 10)
Calculation is very simple;
RSI based QQE oscillates between 0-100
nQQE is simply calculated as:
nQQE=QQE-50
to make the indicator fluctuate around 0 level to get more accurate signals.
Various alarms added.
Kıvanç Özbilgiç
MACD BeepBoop Indicator
The indicator flags long or blue when the macd histogram value > 0 and above the ema and short or red when the macd histogram value < 0 and below the ema
I have added confirmations in the form of eliminating all bars on the histogram unless they meet the long / short entry conditions two bars in a row
You can customize the length of the ema that determines the long/short entry conditions in the settings
I have also added a yellow highlight to the bar in the chart that you would enter on. You would enter at the open of the bar following the signal bar
Stop Loss would be placed at the nearest pivot point or ATR of your choice
Note - republishing this after taking out original links
