Momentum Trend Fusion (MTF)The Momentum Trend Fusion (MTF) is a composite indicator that combines the Awesome Oscillator and the Relative Strength Index to provide a unique perspective on market momentum and trend strength. The MTF is calculated by first running the Relative Strength Index (RSI) on the Awesome Oscillator (AO) and then applying an Exponential Moving Average (EMA) on the RSI value. The MTF is designed to help traders detect market phases and confirm trend direction by analyzing the cross of the EMA and RSI, as well as divergences between the AO and price. The MTF can be customized by the user by providing the lengths of the RSI and EMA calculations, making it an ideal tool for traders with different time frames and risk tolerances.
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GKD-C LSX on LMA [Loxx]Giga Kaleidoscope LSX on LMA is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is an NNFX algorithmic trading strategy?
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends.
4. Confirmation 2 - a technical indicator used to identify trends.
5. Continuation - a technical indicator used to identify trends.
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown.
7. Exit - a technical indicator used to determine when a trend is exhausted.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average as shown on the chart above
Volatility/Volume: Average Directional Index (ADX) as shown on the chart above
Confirmation 1: LSX on LMA as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
█ LSX on LMA
What is LSX on LMA?
LSX on LMA is an RSI-like momentum indicator that is smoothed using three stage moving average combining an adaptive EMA, a Kalman Filter, and a Kauffman adaptive filter.
Requirements
Inputs
Confirmation 1 and Solo Confirmation: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Outputs
Confirmation 2 and Solo Confirmation: GKD-E Exit indicator
Confirmation 1: GKD-C Confirmation indicator
Continuation: GKD-E Exit indicator
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
Multi SMI Ergodic OscillatorThe Multi SMI Ergodic Oscillator (Multi SMIEO) indicator can be used to identify potential buy and sell signals based on the relationship between the TSI and EMA lines.
The script is creating an indicator that plots multiple (3) sets of Time Series Indicator (TSI-Indicator) and Exponential Moving Average (EMA-Signal) lines as a single indicator.
The TSI is a momentum oscillator that helps identify overbought and oversold conditions. It is calculated using the close prices of an asset, a short-term moving average, and a long-term moving average. The script uses three different pairs of input values for the short-term and long-term periods, which can be adjusted by the user.
The EMA is a type of moving average that gives more weight to recent prices. It is calculated by applying a weighting factor to the most recent price, and then adding that weighted value to the previous EMA value. The script uses three different input values for the length of the EMA, which can also be adjusted by the user.
After calculating the TSI and EMA for each set, the script plots them on the same graph, with different colors and widths to differentiate them. The three sets of TSI and EMA lines are plotted to allow the user to compare the results of different periods. The script also plots a horizontal line at zero, which is used as a reference point for the oscillations of the indicator lines.
One way to use this indicator is to look for crossovers between the TSI and the EMA lines. A bullish crossover occurs when the TSI crosses above the EMA. This suggests that the buying pressure is increasing and a potential buy signal is generated. A bearish crossover occurs when the TSI crosses below the EMA. This suggests that the selling pressure is increasing and a potential sell signal is generated.
Some other ways that the indicator can be used include:
1. Identifying trends: The TSI and EMA lines can be used to identify the direction of the trend. An uptrend is present when the TSI and EMA lines are both trending upwards, while a downtrend is present when the TSI and EMA lines are both trending downwards.
2. Overbought and oversold conditions: The TSI can be used to identify overbought and oversold conditions. When the TSI is above the upper limit of the range, the asset is considered overbought and may be due for a price correction. Conversely, when the TSI is below the lower limit of the range, the asset is considered oversold and may be due for a price rebound.
3. Confirming price action: The Multi SMIEO indicator can be used to confirm price action. If a bullish divergence is present, it confirms a potential bullish reversal. If a bearish divergence is present, it confirms a potential bearish reversal.
4. Multiple time frame analysis: By using different periods for the TSI and EMA lines, the indicator can be used to analyze the asset on multiple time frames. It can be useful to compare the results of different periods to get a better understanding of the asset's price movements.
5. Risk management: This indicator can be used as an element of risk management strategy, it can help traders to identify overbought and oversold conditions to set stop loss or take profit levels.
The Multi SMI Ergodic Oscillator (Multi SMIEO) is a versatile indicator that can be used in a number of ways to analyze the price movements of an asset. It can be used to identify potential buy and sell signals, trends, overbought and oversold conditions, and to confirm price action. By using different periods for the TSI and EMA lines, the indicator can also be used to analyze the asset on multiple time frames. However, it is important to remember that indicators are based on historical data, and past performance does not guarantee future results.
It is important to use the indicator as part of a comprehensive trading strategy that includes risk management and other analysis techniques, such as fundamental and technical analysis. It is also important to keep in mind that indicators are not a standalone solution for trading, they should be used in conjunction with other market analysis and research techniques to generate better results.
Lastly, it is important to keep in mind that trading in financial markets comes with a certain level of risk and it is crucial to always have a proper risk management plan in place. Never invest more than you can afford to lose.
Point Of ControlStrategy and indicators are explained on the Chart.
Here's how i read the chart.
Entry:
1. Let the price close above the Ichimoku cloud
2. Price is above Volume Support zone
2. Make sure that momentum indicated with Green Triangles for Long Position
Exit:
1. Orange cross at the bottom of the candle indicates price is about to weaken
2. Best time to exit is Volume Resistance + Bearish(Hammer or Engulf )
PS: Use it along with R-Smart for better results
MTF TMOTMO - (T)rue (M)omentum (O)scillator) MTF (Higher Aggregation) Version
TMO calculates momentum using the DELTA of price. Giving a much better picture of the trend, reversals & divergences than most momentum oscillators using price. Aside from the regular TMO, this study combines four different TMO aggregations into one indicator for an even better picture of the trend. Once you look deeper into this study you will realize how complex this tool is. This version also produce much more information like crosses, divergences, overbought / oversold signals, higher aggregation fades etc. It is probably not even possible to explain them all, there could easily be an entire e-book about this study.
I have been using this tool for a couple of years now, and this is what i have learned so far:
Favorite Time Frame Variations:
1. 1m / 5m / 30m - Great for intraday futures or options scalps. 30m TMO serves as the overall trend gauge for the day. 5min dictates the longer term intraday moves as well as direction of the 1min. 1min is for the scalps. When the 5min TMO is sloping higher focus should be on 1min buy signals (red to green cross) and vice versa for the 5min agg. sloping down.
2. 5m / 30m / 60m - Also an interesting variation for day trading the 3-5 min charts. Producing more cleaner & beginner-friendly signals that lasts couple of minutes instead of seconds.
3. 120m / Day / 2 Day - For the 30m to 1H or 2H timeframes. Daily & 2 Day dictates the overall trend. 120 min for the signals. Great for a multi-day swings.
4. Day / 2 Day / Week - Good for the daily charts, swing trading analysis as the weekly dictates the overall trend, daily dictates the signals and the 2 day cleans out the daily signals. If the daily & 2 day are not aligned togather, daily signal means nothing. Weekly dictates 2 day - 2 day dictates daily.
5. Week / Month / 3 Month - Same thing as the previous variation but for the weekly charts.
TMO Length:
The default vanilla settings are 14,5,3. Some traders prefer 21,5,3 as the TMO length is litle higher = TMO will potenially last little longer which could teoretically produce less false signals but slower crosses which means signals will lag more behind price. The lower the length, the faster the oscillator oscillates. It is the noice vs. the lag debate. The Length can be changed, but i would not personally touch the other two. Few points up or down on length will not drastically change much. But changes on Calc Length and Smooth Length can produce totally different signals from the original.
Tips & Tricks:
1. Observe
- This is the best tip & trick I can give you. The #1 best way to learn how any study operates is to just observe how it works in certain situations from the past. MTF TMO is not
an exception.
2. The Power of the Higher Aggregation
- The higher aggregation ALWAYS dictates the lower one. Best way to see this? Just 2x the current timeframe aggregation = so on daily chart, plot the daily & two day TMOs and you will notice how the higher agg. smooths out the current agg. The higher the aggregation is, the smoother (but slower) will the TMO turn. The real power kicks in when the 3 or 4 aggregations are aligned togather in one direction.
3. Position of the Higher Aggregation in Relation to the Extremes
- Overbought / oversold signals might not really work on the current aggregation. But pay attention to the higher aggregations in relation to the extremes. Ex: on the daily chart - daily TMO inside the OB / OS extremes might not mean much. But once the higher aggregations such as 3 day or Weekly TMO enters OB/OS zone togather with the daily, this can be a very powerful signal for a TMO reversion to the zeroline.
4. Crosses
- Yes, crosses do work. Personally, I never really focused on them. The thing about the crosses is that it is crucial to pick the right higher aggregation to the combination of the current one that would be reliable but also print enough signals. The closer the cross is to the OB / OS extremes, the more bigger move can occur. Crosses around the zero line can be considered as less quality crosses.
5. Divergences
- TMO can print awesome divergences. The best divergences are on the current aggregation (TMO agg. same as the chart) since the current agg. oscillates fast, it can usually produce lower lows & higher highs faster then any higher aggregations. Easy setup: wait for the higher aggregation to reach the OB / OS extremes and watch the current (chart) aggregation to print a divergence.
6. Three is Enough
- I personally find more than three aggregations messy and hard to read. But there is always the option to turn on the 4th one. Just switch the TMO 4 Main, TMO 4 Signal and TMO 4 Fill in the style settings.
Hope it helps.
Retail & Banker Net PositionsIn any market there are two major sets of participants, Retail traders (like you & I) who command relatively small amounts of capital and typically enter and exits positions quickly, and then Institutional Traders (sometimes referred to as whales) who command large amounts of capital and dictate the overall trend of the market but enter and exit positions slowly.
In this indicator we look at the distinct volume of these two sets of traders and use the net positions of this volume to determine if they are net long (Buying) in the market or net short (Selling).
When each set of traders are on opposite sides of the market (Retail are selling & Institutions are buying for example) it usually results in a battle and choppy price action... the majority of these battles are won by the Institutions as their large sums of money dictate the overall direction markets move.
Some of the best opportunities are when both sets of traders are on the same side of the market & this is where we see real momentum enter the market with quick price moves.
Happy trading =)
T3 Velocity Candles [Loxx]T3 Velocity Candles is a candle coloring overlay that calculates its gradient coloring using T3 velocity.
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.
MA SLope Potential Divergence - FontiramisuIndicator showing potential momentum divergences on Moving Average's Slope.
The problem with the classic divergence is that when the signal appears, it is sometimes too late to enter a trade .
The potential divergence corrects this problem by signaling the beginning of a potential divergence .
Moving average slope is a momentum indicator that offers relevant insights with divergences
Potential divergences are indicated with the letter B and a red color for Bearish Div or Green color for Bullish Div .
Potential divergence is confirmed when the line and the label "Bear"' or "Bull" appear.
You can either show fast slope's divergences or slow slope's divergences or slow/fast diff's divergences.
Stacked EMAsStacked Daily & Weekly EMAs + Labels
Pretty much self-explanatory indicator that shows the current momentum based on the key exponential moving averages.
Three stages of the EMAs:
1. Stacked Positively (Bullish) - EMAs are stacked on top of each other which represents a healthy bullish uptrend (green Label).
2. Stacked Negatively (Bearish) - EMAs are stacked below each other meaning the trend is bearish (red label).
3. Stacked Neutral (Neutral) - EMAs are crossing each other without any clear direction = chop (yellow label).
Hope it helps.
TMA-LegacyThis is a script based on the original TMA- RSI Divergence indicator by PhoenixBinary.
The Phoenix Binary community and the TMA community built this version to be public code for the community for further use and revision after the reported passing of Phoenix Binary (The community extends our condolences to Phoenix's family.
The intended uses are the same as the original but some calculations are different and may not act or signal the same as the original.
Description of the indicator from original posting.
This indicator was inspired by Arty and Christy .
█ COMPONENTS
Here is a brief overview of the indicator from the original posting:
1 — RSI Divergence
Arty uses the RSI divergence as a tool to find entry points and possible reversals. He doesn't use the traditional overbought/oversold. He uses a 50 line. This indicator includes a 50 line and a floating 50 line.
The floating 50 line is a multi-timeframe smoothed moving average . Price is not linear, therefore, your 50 line shouldn't be either.
The RSI line is using a dynamic color algo that shows current control of the market as well as possible turning points in the market.
2 — Smoothed RSI Divergence
The Smoothed RSI Divergence is a slower RSI with different calculations to smooth out the RSI line. This gives a different perspective of price action and more of a long term perspective of the trend. When crosses of the floating 50 line up with the traditional RSI crossing floating 50.
3 — Momentum Divergence
This one will take a little bit of time to master. But, once you master this, and combined with the other two, damn these entries get downright lethal!
Trade Central TMV IndicatorT-M-V indicator uses combination of Trend , Momentum and Volume to determine the best time to go long or short on a security. As usual, there is no complex configuration required to use it. In fact, there is nothing to configure at all. Having said that, T-M-V indicator uses more than 10 indicators to identify entries based on Trend, Momentum and Volume signals.
In our observations, combining this with pivot points improves performance. You can use this on any timeframe though we recommend this system for intraday usage (5m/15m/30m).
Rules for going LONG
Go long on green candle high break by next candle. Wait for candle to complete before taking a position.
Exit when you see an orange candle. Wait for the candle to complete before exiting and if the candle color is not orange at closing then stay in position.
Always have a worst case SL in mind where you'll exit irrespective of whether you see exit signal (orange candle) or not. It could be signal candle low, previous swing low break or any other logical SL that you typically use.
Rules for going SHORT
Go short on red candle low break by next candle. Wait for candle to complete before taking a position.
Exit when you see an orange candle. Wait for the candle to complete before exiting and if the candle color is not orange at closing then stay in position.
Always have a worst case SL in mind where you'll exit irrespective of whether you see exit signal (orange candle) or not. It could be signal candle high, previous swing high break or any other logical SL that you typically use.
Disclaimer : Use this indicator at your own risk. We have backtested this only for select securities and for a short period of time. We are forward testing this currently on index futures and will share the data once we have at least 30 days data.
Momentum-based ZigZag (incl. QQE) NON-REPAINTINGI spent a lot of time searching for the best ZigZag indicator. Difficulty with all of them is that they are always betting on some pre-defined rules which identify or confirm pivot points. Usually it is time factor - pivot point gets confirmed after a particular number of candles. This methodology is probably the best when market is moving relatively slow, but when price starts chopping up and down, there is no way the ZigZag follows accurately. On the other hand if you set it too tight (for example pivot confirmation after only 2 or even 1 candle), you will get hundreds of zigzag lines and they will tell you nothing.
My point of view is to follow the market. If it has reversed, then it has reversed, and there is no need to wait pre-defined number of candles for the confirmation. Such reversals will always be visible on momentum indicators, such as the most popular MACD. But a single-line moving average can be also good enough to notice reversals. Or my favourite one - QQE, which I borrowed (and improved) from JustUncleL, who borrowed it from Glaz, who borrowed it from... I don't even know where Quantitative Qualitative Estimation originates from. Thanks to all these guys for their input and code.
So whichever momentum indicator you choose - yes, there is a pick-your-poison-type selector as in in-famous Moving Average indicators - once it reverses, a highest (or lowest) point from the impulse is caught and ZigZag gets printed.
One thing I need to emphasize. This indicator DOES NOT REPAINT. It might look like the lines are a bit delayed, especially when compared to all the other ZigZag indicators on TradingView, but they are actually TRUE. There is a value in this - my indicator prints pivot points and Zigzag exactly on the moment they have been noticed, not earlier faking to be faster than they could be.
As a bonus, the indicator marks which impulse had strength in it. It is very nice to see a progressing impulse, but without force - a very likely that reversal on a bigger move is happening.
I'm about to publish some more scripts based on this ZigZag algo, so follow me on TradingView to get notified.
Enjoy!
Trend Strength Directional IndicatorThis study was inspired by two famous Trading View contributors. Shout out to Lazy Bear and Crypto Face!
In this study you have a live view of the strength of direction the market is heading. The indicator that looks like a black wave is showing us the momentum of price action. When a green dot appears under the lower level it is a indication that we should consider buying, and if the red dot appears over the upper level we should sell. The custom MFI indicator determines how much money is flowing into the market. If it is green that means money is flowing into the market and if it shows red it means that money is flowing out of the market.
VuManChu MorpheusThis is our newest momentum based indicator. With this indicator, we have combined several oscillators including RSI and Stochastic to provide the user with best entries for your trading.
When the oscillator is above the over bought bands (white line at the top) and crosses down the signal (dotted lines), it is usually a good SELL signal. When the oscillator crosses above the signal when below the oversold band (white line at the bottom), it is a good BUY signal.
After forming the larger wave, the “anchor wave” can be used for a secondary confirmation to enter a Sell or a BUY
The yellow and red line in the middle is the dynamic VWAP
Rocket ships are Divergences
Grey rocket ships are hidden divergences
Blood drops are divergences
Grey blood drops are hidden divergences
Trend Indicator A-V2 (Smoothed Heikin Ashi Cloud)"Trend Indicator A-V2" and "Trend Indicator B-V2" are updated and improved versions of my initial trend indicators. Totally rethinking the code, adding highs and lows in the calculations, including some more customisation through colour schemes.
In practice, this indicator uses EMAs and Heikin Ashi to provide an overall idea of the trend.
The "Trend Indicator A-V2" is an overlay showing “Smoothed Heikin Ashi” .
The "Trend Indicator B-V2" uses the same values in a different way to measure the momentum of the trend and identify potential trend rejections.
Please, take into account that it is a lagging indicator.
Momentum Rotation Indicator [CC]I have developed this custom indicator very loosely based on the Sector Rotation Model (Giorgos E. Siligardos. Technical Analysis of Stocks & Commodities, August 2012) and I called it the MRI because this is essentially a brain scan of any particular stock. This will not only tell you when a stock is breaking out over the market at large but also how the stock is doing compared to its own history. Buy when the line turns green and sell when the line turns red.
Let me know if there are any other indicators you would like to see me publish!
Momentum PBless"A mean is a moving average of price. And if we measure price action in relation to its own moving average, the nominal price is no longer our primary concern. We’re looking at a market’s relationship to its own moving averages and the structures it forms around them. That way, we have a unit of measure that’s primarily a function of a market’s action, not so much the constant distortions in the money metric. When we oscillate the price of a market around a mean, previously unseen trends and structures emerge." - www.olivermsa.com
The momentum is calculated with the price ratio to its SMA. On the short term it is used as a variation of the price to the SMA 15 days (equivalent 3 weeks). The middle term it is used as the weekly price vs the SMA 12 weeks (equivalent 3 months) and on the long term as the monthly price vs the SMA 36 months (equivalent 3 years).
Momentum Cloud HashesYellow Cloud Showing Uptrend Momentum cloud based on Upper half of Upper Bollinger Band (Std Deviation 1 to Std Deviation 2).
Include :
Upper Keltner Channel line - price need to be above this to be uptrend
EMA 5 and EMA 10
Use VWMA 10 - immediate support for an uptrend line
Black Traingle - Price Closed under VWMA 10
Red Diamond - EMA 5 closed under Std Deviation 1
Edit it as you wish.
TMO with TTM SqueezeApplication of the TTM squeeze and the short-term momentum TTM Wave A in action. This is an example where the short-term wave will react faster than the TTM to give you a signal to start building your positions.
This indicator needs to be combined with "TTM Wave A" (add to existing pane).
The TTM Squeeze works like a better MACD. There is a zeroline and histogram bars above / below represent positive and negative momo. As the height of the bar decreases when above the zeroline, that is called decreasingly positive momo and as the height of the bar decreases when below the zeroline, that is called decreasingly negative momo. The dots on the TTM Squeeze: Red dots represent consolidation where Bollingers are inside the Keltner Channels and green dots represent a move out of consolidation or "squeeze fire". As price action comes out of consolidation there is a bigger move up/down depending on where momo is heading and where prices are (key support/resistance levels, fib areas). You want to use the TTM Squeeze and A wave TOGETHER - TTM Squeeze is your main momo and your A wave is a short-term momo wave that reacts faster and works as a leading gauge. You need to use them TOGETHER to gauge where price action may be heading. When the TTM Squeeze and A wave move lockstep together, let's say both are decreasingly positive, there is a good probability it continues to move in that direction to the next support levels. TWO bars on the TTM Squeeze of different heights is confirmation that in most cases means it will move in the direction of those bars. So if decreasingly positive, you'll see two darker bars. By the time you get your 2nd bar on the TTM Squeeze, it is often too late or you're losing profit. Way to counter that is after you get one darker bar in the opposite direction of current trend, use A wave to "predict" the next wave, the more A wave histogram bars going towards the other direction, the higher the certainty it will hit. Lastly, using these waves together works best when you look at it on MULTIPLE TIME FRAMES. (Credit for this details goes to Brady from Atlas).
TTM Wave AApplication of the TTM squeeze and the short-term momentum TTM Wave A in action. This is an example where the short-term wave will react faster than the TTM to give you a signal to start building your positions.
This indicator needs to be combined with "TMO with TTM Squeeze" (add to existing pane).
The TTM Squeeze works like a better MACD. There is a zeroline and histogram bars above / below represent positive and negative momo. As the height of the bar decreases when above the zeroline, that is called decreasingly positive momo and as the height of the bar decreases when below the zeroline, that is called decreasingly negative momo. The dots on the TTM Squeeze: Red dots represent consolidation where Bollingers are inside the Keltner Channels and green dots represent a move out of consolidation or "squeeze fire". As price action comes out of consolidation there is a bigger move up/down depending on where momo is heading and where prices are (key support/resistance levels, fib areas). You want to use the TTM Squeeze and A wave TOGETHER - TTM Squeeze is your main momo and your A wave is a short-term momo wave that reacts faster and works as a leading gauge. You need to use them TOGETHER to gauge where price action may be heading. When the TTM Squeeze and A wave move lockstep together, let's say both are decreasingly positive, there is a good probability it continues to move in that direction to the next support levels. TWO bars on the TTM Squeeze of different heights is confirmation that in most cases means it will move in the direction of those bars. So if decreasingly positive, you'll see two darker bars. By the time you get your 2nd bar on the TTM Squeeze, it is often too late or you're losing profit. Way to counter that is after you get one darker bar in the opposite direction of current trend, use A wave to "predict" the next wave, the more A wave histogram bars going towards the other direction, the higher the certainty it will hit. Lastly, using these waves together works best when you look at it on MULTIPLE TIME FRAMES. (Credit for this details goes to Brady from Atlas).
Momentum Adjusted EMA TrendThe script draws a moving average which responds to trend changes extraordinary fast!
It's calculated using Momentum, Acceleration and Probability (Psychological Effect) by interfering the Golden Ratio!
I got the idea thanks to Tradingview user DGT (dgtrd) and his/her excellent descriptions.
The indicator is simplified for users and the default settings work great, so use it as you like specially as a trend indicator.
MAPS - LongShortThis script analyzes volume and momentum for different timeframes to spot opportunities for Longs or Shorts.
Please see below for access to indicators.
Spread for VSAЭтот индикатор сравнивает спрэд (расстояние от закрытия предыдущего бара до закрытия текущего бара или индикатор Momentum = 1) на периоде для сравнения.
На графике за 100 % принимается среднее значение спрэда за период для сравнения - красная линия. (по умолчанию период сравнения равен 3 - то есть три последних бара)
Размер бара на графике равен текущему спрэду по отношению к 100 %.
Если бар меньше 100 % то он ниже среднего, и наоборот если больше 100% то он больше среднего.
Если бар красный - спрэд отрицательный (текущее закрытие меньше предыдущего закрытия)
Если бар зелёный - спрэд положительный (текущее закрытие больше предыдущего закрытия)
Если бар меньше 75% то он будет окрашен в тусклый цвет (этот процент можно менять в настройках)
Если в настройках период спрэда указать больше 1, например 2, то спрэд будет равен закрытие мину закрытие через 1 бар назад. (это для экспериментов).
Примечание:
по умолчанию период для сравнения равен 3, но также интересен график и при значениях 15 и больше. Экспериментируйте.
По вопросам и предложениям пишите в комментариях.
Automatic translation google translate.
This indicator compares the spread (the distance from the closing of the previous bar to the closing of the current bar or the Momentum indicator = 1) on the period for comparison.
On the chart, the average spread value for the period for comparison is the red line, taken as 100%. (by default, the comparison period is 3 - that is, the last three bars)
The size of the bar on the chart is equal to the current spread with respect to 100%.
If the bar is less than 100%, then it is below average, and vice versa, if more than 100%, then it is more than average.
If the bar is red, the spread is negative (the current close is less than the previous close)
If the bar is green, the spread is positive (the current close is greater than the previous close)
If the bar is less than 75%, then it will be painted in a dull color (this percentage can be changed in the settings)
If in the settings the period of the spread is specified more than 1, for example 2, then the spread will be equal to closing mine closing after 1 bar back. (this is for experimentation).
Note:
the default period for comparison is 3, but the chart is also interesting for values of 15 or more. Experiment.
For questions and suggestions, write in the comments.
