Zero-lag TEMA Crosses [Loxx]Zero-lag TEMA Crosses is a spinoff of a the Zero-lag MA as described by David Stendahl in the April 2000 issue of the journal "Technical Analysis of Stocks and Commodities". This indicator uses TEMA calculation mode in order to make the lag lesser compared to the original Zero-lag MA, and that makes this version even faster than the Zero-lag DEMA too. This indicator is the difference between a Fast and Slow Zero-lag TEMA. This indicator is very useful for lower timeframe scalping.
What is the Zero-lag MA?
The Zero-lag MA (Zero-Lag Moving Average) is a technical indicator that was introduced in the April 2000 issue of the journal "Technical Analysis of Stocks and Commodities" by David Stendahl.
The Zero-lag MA is a type of moving average (MA) that is designed to reduce or eliminate the lag that is typically associated with traditional moving averages. Moving averages are a widely used technical analysis tool that helps traders to identify trends and potential trading opportunities. They work by calculating the average price of a security over a given period of time, and then plotting that average on a chart. The most commonly used moving averages are simple moving averages (SMAs) and exponential moving averages (EMAs).
The problem with traditional moving averages is that they can be slow to respond to changes in market conditions. This lag can cause traders to miss out on potential trading opportunities, or to enter or exit trades at the wrong time. The Zero-lag MA was developed as a solution to this problem.
The Zero-lag MA is calculated using a combination of two EMAs and a subtraction formula. The first step in calculating the Zero-lag MA is to calculate two exponential moving averages: a fast EMA and a slow EMA. The fast EMA is calculated over a shorter period of time than the slow EMA. The exact period lengths will depend on the trader's preferences and the security being analyzed.
Once the two EMAs have been calculated, the next step is to take the difference between them. This difference represents the current market trend, with a positive value indicating an uptrend and a negative value indicating a downtrend. However, this difference alone is not enough to create a useful indicator, as it can still suffer from lag.
To further reduce lag, the difference between the two EMAs is multiplied by a factor derived from a third, slower EMA. This slower EMA acts as a smoothing factor, helping to reduce noise and make the indicator more accurate. The exact period length of the slower EMA will depend on the trader's preferences and the security being analyzed.
The final step in calculating the Zero-lag MA is to add the result of the multiplication to the fast EMA. This produces a final value that represents the current market trend with reduced lag. The Zero-lag MA can be plotted on a chart like any other moving average, and can be used to identify trends, potential trading opportunities, and support and resistance levels.
Overall, the Zero-lag MA is designed to provide traders with a more accurate representation of current market conditions by reducing the lag time between price changes and the moving average. By doing so, it can help traders to make more informed trading decisions and improve their overall profitability.
What is the TEMA?
The triple exponential moving average (TEMA) is a technical analysis indicator that was developed to reduce the lag of traditional moving averages, such as the simple moving average (SMA) or the exponential moving average (EMA). The TEMA was first introduced by Patrick Mulloy in the January 1994 issue of the "Technical Analysis of Stocks and Commodities" magazine.
The TEMA is a type of moving average that is calculated by applying multiple exponential smoothing techniques to price data. Unlike traditional moving averages, which apply a single smoothing factor to price data, the TEMA applies three smoothing factors to produce a more responsive and accurate indicator.
To calculate the TEMA, the following steps are taken:
Calculate the single exponential moving average (SMA) of the price data over a given period.
Calculate the double exponential moving average (DEMA) of the SMA over the same period.
Calculate the triple exponential moving average (TEMA) of the DEMA over the same period.
The formula for calculating the TEMA is:
TEMA = 3 * EMA(SMA) - 3 * EMA(EMA(SMA)) + EMA(EMA(EMA(SMA)))
where EMA is the exponential moving average and SMA is the simple moving average.
The TEMA is designed to reduce the lag associated with traditional moving averages by applying multiple smoothing factors to the price data. This helps to filter out short-term price fluctuations and provide a smoother indicator of the underlying trend. The TEMA is also less susceptible to whipsaws, which occur when a security's price moves in one direction and then quickly reverses, causing false trading signals.
The TEMA can be used in a variety of ways in technical analysis. It can be used to identify trends, determine support and resistance levels, and generate trading signals. When the TEMA is rising, it is generally interpreted as a bullish signal, indicating that the price is trending higher. When the TEMA is falling, it is generally interpreted as a bearish signal, indicating that the price is trending lower.
In summary, the TEMA is a more responsive and accurate indicator than traditional moving averages, designed to reduce lag and provide a smoother representation of the underlying trend. It is a useful tool for technical analysts and traders looking to identify trends, support and resistance levels, and potential trading opportunities.
Extras
Alerts
Bar coloring
Signals
Loxx's Expanded Source Types, see here:
Macrossover
RedK TrendBeads: 3 x MA Crossover Signal with Preset TemplatesRedK TrendBeads is a super simple 3 x Moving Average Crossover Signal (Long/Short/Break) script that provides a simple and effective way for traders to identify potential trading opportunities. By combining three moving averages and only exposing a simple signal, the script helps filter out noise and focus on the trend and the trade execution.
Background
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A 3 x Moving Average Crossover strategy is a popular trading method in technical analysis . It uses the relationship between a fast, medium, and slow moving averages to generate buy or sell signals.
The approach usually utilizes three moving averages to track the average price of a financial instrument over different time periods. By comparing the fast, medium, and slow moving averages, we can generates a signal to trade long or short
If the fast moving average crosses above the medium moving average and the medium moving average is above the slow moving average, we have a probability of an up-trend forming, and we generate a signal to go long. Conversely, if the fast moving average crosses below the medium moving average and the medium moving average is below the slow moving average, we have a probability of a down-trend forming, and we generate a signal to go short. When the moving averages are not in the right order (above or below each other), we have a trend break, usually on consolidation or base forming.
in TrendBeads, the fastest MA is called "Price Proxy MA" and will be used with a relatively short length to represent the price itself - then there are the Fast MA, Slow MA and a Filter MA (usually with the longest/slowest length) which is the main line that will be used to plot the TrendBeads - So the TrendBeads will represent the state of the other 3 Moving Average lines (Proxy, Fast and Slow) and how they are aligned - and it will also be common to use the Filter / Beads line itself as a main filter, i.e., take long positions *only* when the price action is above the Filter MA, and short positions *only* when the price is below the Filter MA.
So what is different with TrendBeads:
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Simplicity, No Clutter: I put this together to provide a super simple mechanism to track trend on the price chart without so much noise as i also wanted to have other top-chart indicators (like LadderTrader) - so TrendBeads only shows the "beads" on the chart - they act like "traffic lights" with little distracting information - Simplicity here was deliberately part if the idea
Presets, What others are Watching: The other feature I needed was the ability to track price action against "different sets" of Moving Averages quickly - for example, when executing short-term trades, I needed to use Moving Averages with shorter length and want to utilize my RSS_WMA MA type - but when assessing big breakout opportunities, I need to analyze price action against a different set of MA's with (usually) longer length and mainly SMA's (hint, The Minervini template) - This is where the built-in Preset Templates become very useful.
Having these preset templates quickly available (thru the dropdown in indicator settings) provides time saving, convenience and the confidence that we're looking at what other traders are using in their analysis - so not missing out on key-level breakouts or reversals
TrendBeads v1.0 includes the following 5 preset MA templates
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Preset 1 : RedK_1: 8RSS / 15RSS / 21RSS / 30SMA
Preset 2 : RedK_2: 5WMA / 10SMA / 20SMA / 40SMA
Preset 3 : SWNG_1: 7EMA / 21EMA / 30EMA / 50SMA
Preset 4 : SWNG_2: 10EMA / 21EMA / 50SMA / 100SMA
Preset 5 : SWNG_3: 10EMA / 21EMA / 100SMA / 200SMA
The above presets represent some of the most common sets of MA's traders use in various scenarios (Short-term/day trading, Swing, Long term / growth). Well, except for the first one since it utilizes my own RSS_WMA :) which I use in many charts
I may add some more presets in future.
below chart shows an example of different presets against AAPL for the same time range / window
There's also the ability to manually set different MA source price, MA type and length for each of the 4 MA lines. Supported MA types are SMA , EMA , WMA , HMA and my RSS_WMA
TrendBeads Usage Tips:
=====================
*If you have used any MA crossover (2 lines or 3 lines) on your chart, your should find TradeBeads very easy to use. TrendBeads works the same way except that the signal will show as colored beads on the Filter MA line instead of showing multiple crossing lines .. and that is by design.
* Feel free to expose any or all of the individual MA lines - for example, i find that exposing the Proxy Line helps in quickly finding famous chart patterns ( cup & handle , H&S ..etc)
* Experiment with the different presets depending on the type of trade you're working on (swing, long term growth candidates, day trades..etc)
* Note that in a long trend up (Aqua Beads), usually the first gray + orange sequence will usually act as a "reversal sign" - and are usually not actionable - always look for the "second" color sequence to action/trade .. Same thing for a long trend down -- get used to how the beads change color against the trend changes and play with various timeframes.
* As usual - we should have other indicators that track strength, volume , etc and ensure proper confirmation before trade execution - A good signal is only a small part of a trade - risk management and good trade execution are key to winning.
Hope some fellow traders will find this useful - feel free to leave me any comments or feedback - Good luck!
Acrypto - Weighted StrategyHello traders!
I have been developing a fully customizable algo over the last year. The algorithm is based on a set of different strategies, each with its own weight (weighted strategy). The set of strategies that I currently use are 5:
MACD
Stochastic RSI
RSI
Supertrend
MA crossover
Moreover, the algo includes STOP losses criteria and a taking profit strategy. The algo must be optimized for the desired asset to achieves its full potential. The 1H and 4H dataframe give good results. The algo has been tested for several asset (same dataframe, different optimization values).
Important note:
Backtest the algorithm with different data stamps to avoid overfitting results
Best,
Alberto
Buff Averages [CC]The Buff Averages were created by Buff Dormeier (Stocks and Commodities Feb 2001) and this is another hidden gem that is a combo of a volume weighted indicator and a moving average crossover system. It uses a special method to calculate the weighting based on volume. The colored line (fast buff) will follow the price closely and you use the other line to act as a trend confirmation. I have included strong buy and sell signals in addition to normal ones so strong signals are darker in color and normal signals are lighter in color. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators or scripts you would like to see me publish!
RedK Smooth And Lazy Moving Average (SALMA)Here's a quick and simple script that produces yet another Smooth and Lazy Moving Average - SALMA - that helps hide noise caused by extreme price fluctuations to enable better trend visualization and tracking
Concept:
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SALMA is based on a simple concept - we calculate a standard deviation channel of a user-selected width - then correct the price value so that it is restricted within the boundaries of the SD channel - effectively adjusting against high-volatility, sudden price moves - which acts as a pre-smoothing of the price values - then we calculate our moving average and apply extra smoothing as needed.
Since only "persistent" price moves will have an effect on the direction of this MA, it will be suitable to use as an additional trend guide with other indicators, and to consider only long positions when the price is above the SALMA, and short positions only when the price is below
Notes:
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- for the time being, i'm using Weighted Moving Average (WMA) for the calculation of the base price MA and the SD channel - we can add other MA types as options in a future versions based on feedback
- will add alerts in a future update
- SALMA can be used with any timeframe. can also be set to a higher timeframe against a lower timeframe chart
i have also added couple of standard moving average lines (choose between SMA, EMA and WMA) of selectable lengths - to enable utilizing this in a Moving Average cross-over setup - or to simply monitor other common MA's that other traders are using.
here's how the settings look like when you add SALMA to your chart
Please feel free to play around with SALMA and share feedback :)
RedK Magic RibbonRedK Magic Ribbon is simple script that combines a fast and a slow moving averages to create a 2-Moving Average Cross-over / trend visualization tool.
We utilize the Compound Ratio Weighted Average (CoRa Wave) as the fast MA line and the RedK Slow Smooth Weighted Moving Average (RSS_WMA) aka LazyLine as the slow MA line.
i put this script together when i found that i started using these 2 moving average lines in my trading charts most of the time. thought others may find it useful.
The simple idea is that when the 2 lines "agree" on direction, then this is possibly a confirmed trend in that direction.
Visually, when the 2 lines agree on a trend direction, Magic Ribbon gives either a green (up) or red (down) fill, when they disagree, it gives a gray fill - Gray areas are considered "no trade" or "get ready" zones depending on the situation.
This ribbon can be used to support trend-following trades, swing trading, or as a visual trend tracking tool
Suggested Usage Tips:
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* Position entry should be made as close to the RSS_WMA/LazyLine as possible to maximize gain.
* The RSS_WMA can act as a guide for Stop Loss
* An aggressive (or swing) trader may consider entries as soon as the CoRa Wave line changes color, but in context of the prevailing trend.
* if you intend to use this tool for trading, please test it using the PaperTrading or Rewind features of TV to get used to how it behaves and adjust accordingly.
* The Magic Ribbon should work on any timeframe.
* The basic settings are available - they enable adjusting the length and smoothness of the CoRa Wave and the Smoothness of the RSS_WMA - as well as the source price for each. Style settings enable to adjust color, line width, or hide/show various elements as needed.
* The most important tip for using the Magic Ribbon: when you first add it to your chart, is to fine-tune the length settings to your preference. start by adjusting the LazyLine (RSS_WMA) Smoothness value, so it tracks and barely touches the highs / lows of price bars - with the least amount of lag possible - then adjust the CoRa Wave length to make it as responsive as you need. Keep smoothness to the lowest you can use (i like 3 or 4 max) - the default settings are generic usable values based on my testing.
* as usual, please use this tool only as a guide - make your own detailed chart analysis and support your trading decision with signals and confirmations from other indicators .
*** This script does not repaint.
Triple Exponential Moving AveragesIn this above indicator, one can plot 3 indicators simultaneously
where, 200ema can be used to watch on-going long term trend, dynamic support levels for an instrument
50ema can be combined with 200ema forming a Golden Cross strategy, 50ema can be used as short term support and resistance as well.
Lastly, 20ema could be your swing entry, exit, pullback support/resistance, triple crossover for an Ambush entry, Retest entry, etc.
it is one of the most versatile setup where you can trade an instrument by crosschecking and confirming with multiple parameter
MA Crossover Alerts for Small Quick Profits on 3commas/DCA botDear fellow 3commas users,
This is a the most basic Moving Average crossover technique generating Buy Alerts.
This is especially written for those of you who want to link this basic crossover strategy with your 3commas DCA bot .
Buy Alerts
Moving averages available:
- Simple Moving Average (SMA)
- Exponential Moving Average (EMA)
- Weighted Moving Average (WMA)
- Hull Moving Average (HullMA)
- Volume Weighted Moving Average (VMWA)
- Running Moving Average (RMA)
- Triple Exponential Moving Average (TEMA)
Recommended settings for using with 3commas DCA bot:
Interval:
3m to 15m
3commas bot setup:
- TP/TTP: 0.3%/0.1%,
- Base Order: Your choice ,
- Safety Order: 1.2 * Base order
- Safety Order Volume Scale: 1.2,
- Safety Order Step Scale: 1.5,
- Max Active Deals: Your choice ,
- Price Deviation to Open Safety Order (% from initial order): 0.2%,
- Max Safety Trades Count: 7,
- Simulatenous Deals per Same Pair: 3
> Create Alert with Buy Alert and link it to your bot "Message for deal start signal"
Ultimate MA + MFIHey Folks, this is in indicator that generates buy and sell alerts using Ultimate Moving Average and Money Flow Index.
Buy Alerts
Multi Time Frame Moving Average trend reversal AND MFI < threshold
Sell Alerts
MFI crossing under overbought threshold
Recommended settings for 3commas
- Create Alert with Buy Alert and link it to "Message for deal start signal"
- Create Alert with Sell Alert and link it to "Message to close all deals at Market Price"
- Set Take Profit to 1.0% with trailing between 0.2% and 0.6%
- DO NOT USE STOP LOSS
Moving Average CrossNote: This is just an idea, I did not test this for trading.
MA Cross normally uses close as source in the moving averages, this script uses highs and lows as source.
In an uptrend you will see the 20 period high EMA and 50 period low EMA, once they cross, the indicator will switch to 20 period low EMA and 50 period high EMA. This gives it way less fake crosses as you see in the image on BTC.
As i said above, this is just an idea. If you change the settings, they might not cross at all.. so do your own testing.
Hope this code can help someone.
Uhl MA System - Strategy AnalysisThe Uhl MA crossover system was specifically designed to provide an adaptive MA crossover system that didn't committed the same errors of more classical MA systems. This crossover system is based on a fast and a slow moving average, with the slow moving average being the corrected moving average (CMA) originally proposed by Andreas Uhl, and the fast moving average being the corrected trend step (CTS) which is also based on the corrected moving average design.
For more information see :
In this post, the performances of this system are analyzed on various markets.
Setup And Rules
The analysis is solely based on the indicator signals, therefore no spread is applied. Constant position sizing is used. The strategy will be backtested on the 15 minute time-frame. The mult setting is discarded, the default setting used for length is 100.
Here are the rules of our strategy :
long: CTS crossover CMA
short: CTS crossunder CMA
Results And Data
EURUSD:
Net Profit: $ 0.08
Total number of trades: 99
Profitability: 35.35 %
Profit Factor: 1.834
Max Drawdown: $ 0.01
EURUSD behaved pretty well, and was most of time showing long term trends without exhibiting particularly tricky structures, the moving averages still did cross during ranging phases, since march 9 we can see a downtrend with more pronounced cyclical variations (retracements) that could potentially lead to loosing trades.
BTCUSD:
Net Profit: $ 4371.57
Total number of trades: 94
Profitability: 32.98 %
Profit Factor: 1.749
Max Drawdown: $ 1409.96
The strategy didn't started well, producing its largest drawdown after only a few trades, the strategy still managed to recover. BTCUSD exhibited a strong downtrend, the strategy profited from that to recover, signals still occurred on ranging phases, and where mostly caused by a short term volatile move, unfortunately the CMA can converge toward ranging/flat price zones where false signals might occur at higher frequency.
AMD:
Net Profit: $ 16.09
Total number of trades: 95
Profitability: 29.47 %
Profit Factor: 1.288
Max Drawdown: $ 20.11
On AMD the strategy started relatively well with a raising balance, then the balance quickly fallen, this downtrend in the balance lasted quite some time (almost 48 trades), the strategy finally recovered in Nov 2019 and the balance made a new highest high at the end of February. AMD had numerous trends during the backtesting period, yet results are poor.
AAPL:
Net Profit: $ -28.17
Total number of trades: 89
Profitability: 28.09 %
Profit Factor: 0.894
Max Drawdown: $ 63.21
AAPL show the poorest results so far, with a stationary balance around the initial capital (in short the evolution of the balance is not showing any particular trend and oscillate around the initial capital value).
AAPL had some significant retracements in its up-trend, which triggered some trades (of course), and the ranging period from Jan 24 to Feb 13 heavily damaged the strategy performance, generating 6 significant loosing trades. AAPL show the worst results so far, mostly due by ranging phases.
Conclusions
The Uhl MA crossover system strategy has been tested and based on the results don't show particularly interesting performances, and might even be outperformed by simpler MA systems that prove to be more robust against ranging markets. The total number of executed trades are on average 94, and the profitability is on average 31%. The strategy might prove more interesting if we can correct the behavior of the CMA, who sometimes converged toward ranging/flat markets.
Uhl MA Crossover SystemToday proposed indicator is based on the corrected moving average, an indicator originally proposed by Andreas Uhl professor at Salzburg University. This moving average is not the most well known, which is a pity since its design is extremely elegant.
The corrected moving average (CMA) is an adaptive moving average based on exponential averaging and aim to correct common problems of classical moving averages such as crosses occurring during sideway markets, more details will be introduced in the calculation section. The CMA aim to act as a slow moving average in a moving average crossover system.
Here a new fast adaptive moving average named corrected trend step (CTS) based on the CMA is introduced in order to provide a full moving average crossover system based on A. Uhl design.
To Andreas Uhl
Calculation And Understanding The CTS
Even if the code is quite compact, the original idea behind the CMA can be blurry for some users, however it is actually relatively simple to understand. The CMA is based on exponential averaging and a smoothing variable is therefore required, in the CMA the calculation of the smoothing variable is based on the squared distance between the precedent CMA output and a simple moving average, and the rolling variance, where the rolling variance act as threshold.
The CTS work the same way but instead of using the squared error between a simple moving average and the previous CMA output, we use the squared error between the closing price and the previous CTS output, this allow the CTS to better fit with the closing price. As said before the rolling variance act as threshold, if the squared error is lower than the rolling variance this mean that the CTS is close to the price, which can indicate a sideway market, therefore we should filter the entirety of the current price, therefore on sideways market the CTS is equal to the precedent value of the CTS.
In trending/volatile markets we expect the price to go away from the CTS, thus having an high squared error, if the squared error is greater than the rolling variance, the smoothing variable is equal to 1 - variance/squared error , here variance/squared error < 1 since the squared error is greater than the rolling variance ( remember that the smoothing variable need to be in a (0,1) range ), however if the squared error is way higher than variance this ratio will be small, which would return a non reactive output, but thats not what we want ! This is why we subtract 1 by this ratio in order to make the CTS more reactive instead of less reactive.
In case the squared error is greater than the rolling variance during sideway markets we would not expect a huge difference anyway, that is squared error ≈ variance and therefore:
1 - variance/squared error ≈ 1 - 1/1 ≈ 1 - 1 ≈ 0
This is a beautiful way to make an adaptive moving average, the CMA is not a flashy indicator, but when we look at the details behind the design we can only get amazed, or maybe that its just me, truly a great adaptive moving average.
The System
length control the filtering amount of both moving averages, with higher values of length returning larger filtering amount. Mult multiply the rolling variance by an user selected value, this also allow a greater amount of filtering.
The CTS act as a fast moving average while the CMA act as a slow moving average.
Here the indicator with length = 200, we can see how a sideway market who could have generated a large amount of signals don't affect our system.
Unlike classical crossovers systems where the slow moving average will rarely produce a cross with the fast moving average and price at the same time, the Uhl system can actually do that:
Conclusion
A moving average crossover system based on the corrected moving average proposed by Andreas Uhl has been presented, a new moving average that aim to produce good fits with the price has been created especially for this system. The logic behind the CMA has also been explained. A possible strategy analysis could be presented in the future.
In conclusion i would say the CMA is a bit underrated, in a field where arrows, signals, alerts are the only things appreciated by peoples, original content is slowly dying, this actually make today technical indicators have a pretty bad academic reputations. I'am afraid that today haiku master is Uhl rather than me, i hope to see more indicators from him in the future.
Thanks for reading !
Original paper: www.buero-uhl.de
Instantaneous Trendline Strategy [ChuckBanger]Based on Instantaneous Trendline, by John Ehlers , identifies the market trend by doing removing cycle component. I think, this simplicity is what makes it attractive :) To understand Ehlers's thought process behind this, refer to the PDF linked below.
There are atleast 6 variations of this ITrend. This version is from his early presentations. You can find it here: www.mesasoftware.com
This is better then a regular MA cross over strategy
Simple Moving Averages Alert Scriptcan set alerts on 3 moving averages (crossovers) , experiment with different moving average lengths in the input settings menu, there is also a toggle switch which turns off the 3rd moving average being used as a stop.
will add a backtesting version at some point
McGinley Dynamic VWAP/MVWAP [NeoButane]The main concept for creating this was to completely remove the whipsaw nature of VWAP by introducing lag.
References:
www.investopedia.com
www.investopedia.com
www.investopedia.com