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.
Chỉ báo Xung lượng (MOM)
Strategy Myth-Busting #6 - PSAR+MA+SQZMOM+HVI - [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 sixth one we are automating is " I Tested ''7% Profit Per Day" Scalping Strategy 100 Times ( Unexpected Results ) " from " TradeIQ " which claims to have made 175% profit on the 5 min chart of BTCUSD with a having a 61% win rate in just 32 days.
Originally, we mimicked verbatim the indicators and settings TradeIQ was using however weren't getting promising results anything close to the claim so we decided to try and improve on it. We changed the static Parabolic SAR to be adaptive based upon the timeframe. We did this by using an adjustable multiplier for the PSAR Max. Also, In TradeIQ's revised version he substituted Hawkeye's Volume Indicator in lieu of Squeeze Momentum. We found that including both indicators we were getting better results so included them both. Feel free to experiment more. Would love to see how this could be improved on.
This strategy uses a combination of 4 open-source public indicators:
Parabolic Sar (built in)
10 in 1 MA's by hiimannshu
Squeeze Momentum by lazybear
HawkEYE Volume Indicator by lazybear
Trading Rules
5m timeframe and above. We saw equally good results in the higher (3h - 4h) timeframes as well.
Long Entry:
Parabolic Sar shifts below price at last dot above and then previous bar needs to breach above that.
Price action has to be below both MA's and 50MA needs to be above 200MA
Squeeze Momentum needsd to be in green or close to going green
HawkEYE Volume Indicator needs to be show a green bar on the histagram
Short Entry:
Parabolic Sar shifts above price at last dot below and then previous bar needs to breach below that.
Price action needs to be above both MA's and 50MA needs to be below 200MA
Squeeze Momentum needsd to be in red or close to going red
HawkEYE Volume Indicator needs to be show a red bar on the histagram
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.
Conversion Range Candles// Conversion Range Candles
// Compares price action range with that of the value currency (e.g. ETHBTC compared to BTCUSD).
// Public Domain
// by JollyWizard
Normalized Velocity [Loxx]Velocity (which is often called a "smoother momentum" since it is much smoother than momentum without lagging at all) with an addition of ATR normalization
Since velocity is (even when normalization is applied) is not an indicator with fixed bounds, this indicator is uses floating levels for what is usually called overbought and oversold levels (+ a floating "zero" line is added). Something that would look like a "fixed levels" is easily achieved if you use long floating levels period in which case those levels are quite similar to fixed levels.
This indicator can be used like any momentum indicator (in that case recommended coloring mode is to use either slope coloring or "zero" middle level crossing coloring) or it can be used as a "trending" indicator in which case it is better to use coloring on outer level cross, and longer calculation periods are advised in that case.
Included:
Bar coloring
3 signal variations w/ alerts
Loxx's Expanded Source Types
Alerts
Trend Surfers - Momentum + ADX + EMAThis script mixes the Lazybear Momentum indicator, ADX indicator, and EMA.
Histogram meaning:
Green = The momentum is growing and the ADX is growing or above your set value
Red = The momentum is growing on the downside and the ADX is growing or above your set value
Orange = The market doesn't have enough momentum or the ADX is not growing or above your value (no trend)
Background meaning:
Blue = The price is above the EMA
Purple = The price is under the EMA
Cross color on 0 line:
Dark = The market might be sideway still
Light = The market is in a bigger move
OMA-Filtered Kase Permission Stochastic [Loxx]OMA-Filtered Kase Permission Stochastic is a special implementation of Kase Permission Stochastic by Kase StatWare.
What is Kase StatWare?
Kase StatWare has been around since 1992 and is a technical analysis trading indicator package developed by the acclaimed market technician and former energy trader Cynthia A. Kase. StatWare’s self-optimizing indicators help professional and individual traders to form a precise and systematic approach to discretionary trading and trade risk management.
Kase StatWare creates subscription-based technical analysis tools mainly for Stocks and Futures trading which can be subscribed to at a monthly cost.
What is Kase Permission Stochastic?
The Kase Permission Stochastic is a momentum indicator that examines a synthetic longer bar length, that by default, is three (5x by default for this implementation here) times higher than the bar length it is plotted against.
Included
Alerts
Signals
Bar coloring
Market momentum catcherIs a tool used to catch market momentum. If the color is green it means the bulls are in momentum or the prices will continue to increase, if the color is red it means the bears are in momentum or the prices will continue to decrease and gray color means the market is consolidating.
This tool is made from moving averages and RSI.
You can place a buy order when the color is green, you can place a sell order when the color is red and if the color is gray do not trade.
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.
[HA] Heikin-Ashi Shadow Candles// For overlaying Heikin Ashi candles over basic charts, or for use in it's own panel as an oscillator.
// Enjoy the visual cues of HA candles, without giving up price action awareness.
// Good for learning and comparison.
// Aug 11 2022
Release Notes: * Bugfix: Candle color was based on classic direction not HA direction (did not update cover photo).
// Aug 12 2022
Release Notes: * Implemented true oscillator mode.
Provided as separate plot (styles tab) or mode switch option (Inputs tab). TV gets spazzy with "styles tab" "default hidden" plots, and will reset them if any variables are modified that affect them (i.e. wick color override). Mode switch should be sufficient for both users.
// Aug 21 2022
Republished because of typo in indicator name prevented search.
Munich's Momentum Wave V2MUNICH'S MOMENTUM WAVE VERSION 2 IS LIVE!!!
There are a few big things to note with this one.
I decided to upload this as an entirely new script due to the number of changes differing from the first version, but as the last one, this will still work on ANY TIMEFRAME, ANY ASSET CLASS, ANY PRICE! .
This momentum wave indicator now will give you data for when trend could turn, and two momentum indicators to help you decide when to take an entry.
First off,
*I have added an alma ma (alma) that will track momentum alongside price action and further lead the indicator consisting of the Munich waves.
* The background feature will track the price using a method derived from the Bollinger bands, after calculations, it will color the background based on the average of the momentum's ema's, the alma ma, and also the alma in comparison to the alma's value pre offset ( the offset is 3, following the basis).
*There are now 5 basis values given from the increase in ema samples.
If anyone has any questions feel free to pm me or comment below. Thank you guys for the support! :)
INDEX:BTCUSD TVC:NDQ AMEX:SPY BITSTAMP:ETHUSD BINANCE:BTCUSDT FX:USDJPY NASDAQ:AAPL
Dr. Mahdi Kazempour - Crypto Trade Dashboard and Indicator PanelA great panel for crypto traders all in one table:
Price, Volume, RSI, MACD, ADI, MOM
1) current symbol
2) BTCUSDT
3) NASDAQ
4) ETHUSDT
5) TOTAL2
München's Momentum WaveMUNICH'S MOMENTUM WAVE:
This momentum tracker has features sampled from Madrid's moving average ribbon but has differentiated many values, parameters, and usage of integers. It is derived using momentum and then creates moving averages and mean lengths to help support the strength of a move in price action, and also has the key mean length that helps determine HL/LH or rejections into trend continuation. This indicator works on ALL TIME FRAMES, ALL ASSET CLASSES ON ALL SETTINGS!!
HOW DO I USE IT?
*First off, I have arranged the input settings into groups based on the parts of the indicator it affects.
*You want to use the aqua/white/yellow (Munich's line) as your leading indicator, this is a combined average of the MoM indicator.
* When using Munich's line you want to look at the relation to the mean line (the flat line that adjusts based on price action. You will often see rejections of this line into trend continuation. I personally have caught perfect LH/HL bounce trades off of this indicator.
* Use the Background and other colored moving averages to help pre-determine moves based on the -3 offset value of Munich's line. This was by design not to create 'accurate' results, but to help predict momentum swings based on sharper moves in price action better than if all values lined up to the current bar.
Cheat Code's Notes:
I hope you guys find this indicator to be useful, this is most likely the best indicator that I have written. Simply for the fact it is useful on any chart, any timeframe with any setting. If you guys have any issues with it, shoot me a pm or drop a comment. Thanks!
-CheatCode1
BINANCE:BTCUSDT BITSTAMP:ETHUSD BITSTAMP:BTCUSD PEPPERSTONE:JPYX TVC:DXY TVC:NDQ AMEX:SPY
Trend Friendly RSITrend Friendly RSI
Unlike the standard RSI, "Trend Friendly RSI" adapts to the trend. RSI and other momentum-based oscillators cannot give a buy signal in uptrends and a sell signal in downtrends because they do not take into account the momentum of the trend and behave as if the price is in a constant sideways trend. "Trend Friendly RSI", on the other hand, takes into account the momentum of the trend of your chosen length and subtracts it from the current momentum, thus giving more realistic buy and sell signals.
use it to identify your long-term investments and trading entry points for hodl. It would be wise to use this indicator for assets that you have done fundamental analysis and are sure of the trend direction. it doesn't know what the price will do, it just shows the points that are suitable for you.
remember this indicator will fail in horizontal trends.
Dap's Oscillator- Short Term Momentum and Trend. BINANCE:BTCUSDT BYBIT:BTCUSDT BYBIT:ETHUSDT BINANCE:ETHUSDT
DAP's OSCILLATOR:
WHAT IS IT?
This Oscillator was created to inspire confidence in the short-term trend of traders. This will work very well with a volatility metric (I recommend BBWP by @The_Caretaker)
WHAT IS IT MADE OF?
1. Consists of a series of equations (mainly the difference between simple to exponential moving averages) and Standard deviations of these moving average differences (length equivalent to the length of sampled ma's)
2. These equations are then boiled down through an averaging process array, after averaging the covariants are equated against the variants of the positive side of the array. This is what is presented as the aqua line.
3. The RC average (yellow) is the sma following the DAP'S Oscillator at a specified length
4. The most important part of this indicator is simply the momentum oscillator represented as a green or red line based on the value relative to the Oscillators.
HOW DO I USE THIS?
As I mentioned before mixed with a volatility metric, it should set you up for a good decision based on short-term trends. I would say to be careful for periods of consolidation, with the consolidation the momentum often meets hands with DAP's Oscillator and can cause fake-outs. You want to spot divergences from the price to the momentum difference, as well as room to work down or upward to secure a good entry on a position.
CHEAT CODE'S NOTES:
I appreciate everyone who has boosted my previous scripts, it means a lot. If you want to translate words to pine script onto a chart, feel free to PM me. I would be happy to help bring an indicator to life. I may take a quick break but will be back shortly to help create more cheat codes for yall. Thanks!
-Cheat Code
Heinkin-Ashi Shadow Candles// Public Domain
// By JollyWizard
// For overlaying Heikin Ashi candles over basic charts, or for use in it's own panel as an oscillator.
// Enjoy the visual cues of HA candles, without giving up price action awareness.
// Good for learning and comparison.
Synthetic EMA Momentum w/ DSL [Loxx]Synthetic EMA Momentum w/ DSL is a momentum indicator that is calculated with 5 different EMAs of increasing period to derive a final momentum value. This helps reduce noise and improve signal quality. Discontinued signal lines are uses to calculate signal values.
What are DSL Discontinued Signal Line?
A lot of indicators are using signal lines in order to determine the trend (or some desired state of the indicator) easier. The idea of the signal line is easy : comparing the value to it's smoothed (slightly lagging) state, the idea of current momentum/state is made.
Discontinued signal line is inheriting that simple signal line idea and it is extending it : instead of having one signal line, more lines depending on the current value of the indicator.
"Signal" line is calculated the following way :
When a certain level is crossed into the desired direction, the EMA of that value is calculated for the desired signal line
When that level is crossed into the opposite direction, the previous "signal" line value is simply "inherited" and it becomes a kind of a level
This way it becomes a combination of signal lines and levels that are trying to combine both the good from both methods.
In simple terms, DSL uses the concept of a signal line and betters it by inheriting the previous signal line's value & makes it a level.
Included:
Loxx's Expanded Source Types
Alerts
Signals
Bar coloring
Related indicators
Smoother Momentum MACD w/ DSL
T3 Velocity
Smoother Momentum MACD w/ DSL [Loxx]Smoother Momentum MACD w/ DSL uses two different EMA calculations to derive momentum and then calculates the MACD between those momentum outputs. This indicator uses a variation of Discontinued Signal Lines for the breakout/breakdown/reversal signals . There are three different signal types: middle, levels, and slope. I've also added alerts and signals. The discontinued signal lines can be smoothed using EMA or Fast EMA.
What are DSL Discontinued Signal Line?
A lot of indicators are using signal lines in order to determine the trend (or some desired state of the indicator) easier. The idea of the signal line is easy : comparing the value to it's smoothed (slightly lagging) state, the idea of current momentum/state is made.
Discontinued signal line is inheriting that simple signal line idea and it is extending it : instead of having one signal line, more lines depending on the current value of the indicator.
"Signal" line is calculated the following way :
When a certain level is crossed into the desired direction, the EMA of that value is calculated for the desired signal line
When that level is crossed into the opposite direction, the previous "signal" line value is simply "inherited" and it becomes a kind of a level
This way it becomes a combination of signal lines and levels that are trying to combine both the good from both methods.
In simple terms, DSL uses the concept of a signal line and betters it by inheriting the previous signal line's value & makes it a level.
Included:
Loxx's Expanded Source Types
Alerts
Signals
Bar coloring
Other momentum indicators
CFB-Adaptive Velocity Histogram
Variety-Filtered, Squeeze Moving Averages
William Blau Ergodic Tick Volume Indicator (TVI)
DMI StrategyThis strategy is based on DMI indicator. It helps me to identify base or top of the script. I mostly use this script to trade in Nifty bank options, even when the signal comes in nifty . It can be used to trade in other scripts as well. Pivot points can also be used to take entry. Long entry is taken when DI+(11) goes below 10 and DI-(11) goes above 40 , whereas short entry is taken when DI-(11) goes below 10 and DI+(11) goes above 40.
For bank nifty , I take the trade in the strike price for which the current premium is nearby 300, with the SL of 20%. If premium goes below 10% I buy one more lot to average, but exit if the premium goes below 20% of the first entry. If the trade moves in the correct direction, we need to start trailing our stoploss or exit at the pre-defined target.
As this a strategy, there is one problem. While we are in the phase of "long", if again the "long" phase comes, it will not be shown on chart until a "short" phase has come, and vice versa. This has been resolved by creating an indicator instead of strategy with the name of "DMI Buy-sell on chart". Please go through that to get more entry points.
Please have a look at strategy tester to back test
Chiko-Span Momentum_PineScript_Version5This is Momentum indicator based on "Chiko-span" of Ichimoku Kinko-Hyo.
Differ from normal momentum indicator, this indicator is using "close" and "open" as default parameter which is based on 9 week-candle chart Invented by Ichimoku-Sanjin. And, It is located 26 period before to match chiko-span.
(Parameters can change as you like)
The usage is same as normal momentum indicator so please check momentum indicator usage. However, due to use this indicator, it may support to compare momentum of chiko-span movement and to predict effect 5 lines of ichimoku.
For example, when price break out tenkan-sen, you can measure slope or period of chiko-span momentum and compare previously chiko-span momentum. If momentum is stronger than previously price, we can think that price try to out kijun- sen, touch cloud or break out cloud.
I wish, this indicator helps ichimoku users.
DMI StrategyThis strategy is based on DMI indicator. It helps me to identify base or top of the script. I mostly use this script to trade in Nifty bank options, even when the signal comes in nifty. It can be used to trade in other scripts as well. Pivot points can also be used to take entry. Long entry is taken when DI+(11) goes below 10 and DI-(11) goes above 40, whereas short entry is taken when DI-(11) goes below 10 and DI+(11) goes above 40.
For bank nifty, I take the trade in the strike price for which the current premium is nearby 300, with the SL of 20%. If premium goes below 10% I buy one more lot to average, but exit if the premium goes below 20% of the first entry. If the trade moves in the correct direction, we need to start trailing our stoploss or exit at the pre-defined target.
Please have a look at strategy tester to back test.
Squeeze Momentum Strategy [LazyBear] Buy Sell TP SL Alerts-Modified version of Squeeze Momentum Indicator by @LazyBear.
-Converted to version 5,
-Taken inspiration from @KivancOzbilgic for its buy sell calculations,
-Used @Bunghole strategy template with Take Profit, Stop Loss and Enable/Disable Toggles
-Added Custom Date Backtesting Module
------------------------------------------------------------------------------------------------------------------------
All credit goes to above
Problem with original version:
The original Squeeze Momentum Strategy did not have buy sell signals and there was alot of confusion as to when to enter and exit.
There was no proper strategy that would allow backtesting on which further analysis could be carried out.
There are 3 aspects this strategy:
1 ) Strategy Logic (easily toggleable from the dropdown menu from strategy settings)
- LazyBear (I have made this simple by using Kivanc technique of Momentums Moving Average Crossover, BUY when MA cross above signal line, SELL when crossdown signal line)
- Zero Crossover Line (BUY signal when crossover zero line, and SELL crossdown zero line)
2) Long Short TP and SL
- In strategies there is usually only 1 SL and 1 TP, and it is assumed that if a 2% SL giving a good profit %, then it would be best for both long and short. However this is not the case for many. Many markets/pairs, go down with much more speed then they go up with. Hence once we have a profitable backtesting setting, then we should start optimizing Long and Short SL's seperately. Once that is done, we should start optimizing for Long and Short TP's separately, starting with Longs first in both cases.
3) Enable and Disable Toggles of Long and Short Trades
- Many markets dont allow short trades, or are not suitable for short trades. In this case it would be much more feasible to disable "Short" Trading and see results of Long Only as a built in graphic view of backtestor provides a more easy to understand data feed as compared to the performance summary in which you have to review long and short profitability separately.
4) Custom Data Backtesting
- One of most crucial aspects while optimizing for backtesting is to check a strategies performance on uptrends, downtrend and sideways markets seperately as to understand the weak points of strategy.
- Once you enable custom date backtesting, you will see lines on the chart which can be dragged left right based on where you want to start and end the backtesting from and to.
Note:
- Not a financial advise
- Open to feedback, questions, improvements, errors etc.
- More info on how the squeeze momentum works visit LazyBear indicator link:
Happy Trading!
Cheers
M Tahreem Alam @mtahreemalam
Trend Momentum Divergence (TMD)Shout out to Lazy Bear, Bunghole, and Trading View for script code for this make.
In this study you will have a visual representation of the strength and momentum of a trend and possibilities of where the market is heading. You can use the Blue and White momentum waves to spot divergences in a up oe down trend for potential reversals. When a green dot appears under the lower level with divergence then it is a indication that we should consider looking to buy. If the red dot appears over the upper level with divergence we should be looking to short/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. You can spot divergences in the money flow as well as the RSI. The Blue and Green lines from the RCI3line indicator are used for higher timeframe momentum based on current chart timeframe and we can see when they cross over.
Dynamic Zones Polychromatic Momentum Candles [Loxx]Dynamic Zones Polychromatic Momentum Candles is a candle coloring, momentum indicator that uses Jurik Filtering and Dynamic Zones to calculate the monochromatic color between two colors.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included
Loxx's Expanded Source Types
