Fibonacci EMA's with Bollinger Bands [Feniks]Many Fibonacci EMAs are calculated and then tracked using custom-colored candlesticks so that your chart remains very clean. This setup is mainly used for scalping on the 2min. Feniks uses gray candlesticks and then all of the custom-colored candlesticks to know when to react to price action.
WARNING: Do your own due diligence and try it out. Also, the script's default colors were determined with the chart's candlesticks being gray for both bullish/bearish candles. You'll probably have to change some of the colors to make use of the script if your chart's candlesticks are not similarly configured.
The main two strategies involve the 13/55 and 21/233.
The 13 EMA (blue) crosses above or below the 55 EMA (green).
- 13/55 Crossover is shown by the triggering candlestick being blue.
- 55/13 Crossunder is shown by the triggering candlestick being orange.
- (Alerts 1/2)
The 21 EMA (red) crosses above or below the 233 EMA (white).
- 21/233 Crossover is shown by the triggering candlestick being green.
- 233/21 Crossunder is shown by the triggering candlestick being red.
- (Alerts 3/4)
在腳本中搜尋"scalping"
[blackcat] L3 God Hunter ScalpingLevel 3
Background
An ultra-short scaler that I integrate with multiple custom function implementations. Because of its responsiveness it is suitable for small cycle applications.
Function
The first technical indicator to integrate is the stoch. By combining the stoch indicators of long and short periods, I can not only ensure its high-speed reaction speed, but also be compatible with stability.
The second is the improved KDJ indicator to further strengthen buying and selling conditions. Because the final trend output is relatively fast, I used a variety of long-short conditions to improve adaptability. and minimize noise. It is well known that price fluctuations in small cycles are more random.
The third feature is the classification of buying and selling points, not only through the reversal of the trend curve, but also several other buying and selling point conditions, oversold and overbought signals, signal divergence techniques, etc.
Finally, through the nested RSI, the momentum trend strength of the trend signal is represented by a gradient color to assist in judging whether the reversal point is approaching.
Remarks
For differnent instruments and time frames, overbought and oversold threshold should be adjusted accordingly, or it may not work well.
Feedbacks are appreciated.
Volume Weighted Reversal BandsThis is a vwap & vwma hybrid with upper & lower deviation bands that provide excellent price channels and reversal areas. It can be used on lower & higher timeframes, just increase the deviation % for higher timeframes. Try out the 1 minute timeframe with .5% deviation for great scalping levels.
Here is the calculation used for the main line.
(VWMA100 + VWMA500 + VWMA1000 + VWAP) / 4
So it combines 3 VWMAs with the VWAP and divides that number by 4 to give us a moving average. Then we add new levels above and below that moving average to get our channels. The channels are separated by the % deviation you choose in the settings. For tighter bands, lower the percentage deviation and for wider bands, increase the percentage deviation.
The fattest line in the middle is the main moving average and you can expect price to regularly return to this level. The thick lines are the main moving average plus or minus the percentage deviation you have set. There are 10 levels in each direction from the main moving average. The is also a thin short term moving average as well with a custom calculation. It takes 4 different length moving averages that are weighted and 4 more that are volume weighted and divides the total by 8.The lines will be green when price is above the line and red when price is below the line. The thin white line is the VWAP on its own.
These lines will act as dynamic support and resistance so you can scalp them back and forth. These levels work so well because they are volume weighted and the algos hedge their positions back and forth constantly.
For best results, use this indicator on tickers with the highest volume and trading action as the price will stick to these levels better when the big money players are hedging. Some great tickers for this indicator are APPL, SPY, BTC, ETH.
All colors and linewidths can be customized in the settings easily as well as turning off the VWAP or short moving average and adjusting the percentage deviation for the channels.
***MARKETS***
This indicator can be used on all markets, including stocks, crypto, futures and forex.
***TIMEFRAMES***
This indicator can be used on all timeframes.
***TIPS***
Try using numerous indicators of ours on your chart for extra confirmation. Our favorites to pair with these bands are the Scalper Ribbon and Trend Friend Signals. The 3 combined give you a lot of extra confirmation on whether the market is going to reverse at these levels.
Options Scalping by harsh gbychi this is my script.
Bank Nifty Live OI Change Chart can give very useful clues for intraday support and resistance levels for Bank Nifty. If there is more addition in Open Interest at 12200 Calls, that would mean most market players are comfortable writing call options at this level because they believe it to be a strong resistance. That would be bearish indication for BankNifty.
Similarly is there is highest writing in 12000 Puts that would indicate strong intraday support at that level.
Third Scenario: There is good amount of Open Interest increase in 12000 PE and 12200 CE –> this means we should expect a range bound session for the day, as both bears and bulls are comfortable holding the 12200 and 12000 levels respectively.
Following factors could improve reliability of BankNifty OI Change analysis:
1) Put Call Ratio: Higher PCR means bullishness. If there is more writing at 12000PE and PCR is high and increasing during the day that would add to bullish scenario
If the PCR is declining for the day and more writing happening at 12200CE then this adds to bearishness.
2) Close to expiry: The closer to expiry we are, the more reliable the ‘Open Interest’ analysis. Early in the series, the OI analysis is less reliable.
3) More Players: As the number of players increase, the OI analysis become more reliable.
4) Bid-ask Spread: The lower the bid-ask spread the more reliable the OI analysis.
5) Technical Indicators: The best trades are found by combining OI analysis with other technical indicators. MACD, RSI, Channel lines and EW count give best results with Open Interest Analysis.
Current Market StrengthThe **CMS** allows people to understand the current market strength by looking at the last candles and creating an analysis alongside the RSI (Relative Strength Index).
It works by looking at x amount of candles. Default 10.
Then checks how high the current open candle is in comparison to the last candles. Checking through all those candles. Creating a placement.
Once the placement has been found then this indicator will get the RSI / 10, and add that onto the placement.
The end result will look similar to the RSI, just more volatile to detect more precise scalping points.
Feel free to change the value of 'x' stated in above in the setting menu.
Open High Low StrategyThis is a very simple, yet effective and to some extend widely followed scalping strategy to capture the underling sentiments of the counter whether it will go up or down.
What is it?
This is Open-High-Low (OLH) strategy.
As you already aware of Candlestick patterns, there is patterns called as Marubozu patterns where the sell wick or buy wick either ceases to exists (or very small). This is exactly in the same principle.
In OLH strategy: The buy signal appears when the Open Price is the Low Price. It means if you draw the candlestick, there is no bottom wick. So after the opening of the candle, the demand drives the price up to the level, some selling may or may not come and closes in green. This indicates a strong upward biasness of the underlying counter.
Similarly, a sell signal appears when the Open price is the High Price. It means there is no upper wick. So there is no buying pressure, since the opening of the candle, sellers are in force and pulls down the price to a closing.
This strategy generates the signal at the close of the candle (technically barstate.isconfirmed). Because until the bar is real-time there is no option to know the final closing or high. So you will see the bar on which it generates the buy or sell signal is actually indicates the previous bar as OLH bar.
To determine the Stop-Loss, it uses the most widely known SL calculation of:
For buy signal, it takes the low of the last 7 candles and substract the ATR (Average True Range) of 14-period.
For sell signal, it takes the high of the last 7 candles and add it to the ATR (Average True Range) of 14-period.
One can plot the SL lines as dotted green and red lines as well to see visually.
Default Risk:Reward is 1:2, Can be customizable.
What is Unique?
Of course the utter simplistic nature of this strategy is it's key point. Very easy and intuitive to understand.
There are awesome strategies in this forum that talks about the various indicators combinations and what not.
Instead of all this, in a 15m NSE:NIFTY chart, it generates a good ~ 47% profit-factor with 1:2 Risk Reward ratio. Means if you loose a trade you will loose 1% of account and if you win you will gain 2%. Means 3 trades (2 profits and 1 loss) in a trading session result 3% overall gain for the day. (Assuming you are ready with 1% draw down of your account per trade, at max).
Disclaimer:
This piece of software does not come up with any warrantee or any rights of not changing it over the future course of time.
We are not responsible for any trading/investment decision you are taking out of the outcome of this indicator.
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.
Aggregated Rolling VWAP +Edit of TradingView's original Rolling VWAP
Edit log:
Added Volume Aggregation Capabilities to the Script
- Price Action is impacted by volume executed in all exchanges. Even though a single exchange RVWAP can be useful, using aggregated data makes it more accurate and saves time in symbol switching.
- Aggregation is preset to be done for Bitcoin Spot Pairs. However this can be changed to Aggregate Volume from any other symbol at the bottom of the setup menu.
Added Symmetrical Deviations to the Script
- Symmetrical deviations create range of "tolerance" around the RVWAP at a fixed % distance. This helps in situations when price does not respect the exact RVWAP level and goes slightly above/under.
- Adding multiple Symmetrical Deviations at different percentage values can give relevant levels for scalping, entries and range trading.
Switched default option to manual TF instead of automatic TF
Added TF Presets for quick switching between different settings. (Feature intended for mobile charting)
Added ON/OFF Switch to all individual deviations to make it easier, faster and cleaner to display different data. (Feature intended for mobile charting)
Moving Average Directional IndexMADX is ADX-inspired indicator with moving averages that determines strength of a trend, as well as its direction. Indicator works following:
As the value of MADX increases, so does the strength of a trend
If MADX+ ( green line - bullish MADX ) crosses above MADX- ( red line - bearish MADX ) we consider trend as bullish and vice versa..
There will be situations where MADX- and MADX+ cross multiple times in a short period of time -> that will mean that market indecision is happening and big move will most likely happen after it.
For the calculation of MADX+ and MADX- we need Moving Averages or Exponential Moving Averages with three specific sources ( high, close, low ).
Now, the calculation of each MADX will differ
=> for MADX+: Moving Average (high) / Moving Average (close)
=> for MADX-: Moving Average (close) / Moving Average (low)
Length of Moving Average is editable.
[Old] TL with K/K and CustomizationThe old version of Trap Light before the most recent update. In order to facilitate the table functionality that is currently available for Trap Light, I had to make some values that are used in calculations hard-coded. By request, I'm quickly making this version available.
Trap Light
Description
Trap Light is an indicator that uses the K value of the Stochastic RSI to indicate potential long or short entries. It was designed to operate like a traffic stop light that is displayed near the current candle so that you don't have to look away from the candlesticks while trading.
Kriss/Kross is simply a cross over/under strategy that utilizes the 10 EMA and the 50 EMA .
Signals and Available Alerts:
1. Max Sell (Red Sell Label)
When K is equal to 100.00.
This is the strongest sell signal, remember that you only need to make sure that the trend is reversing before you make an entry, because several of these signals can appear in a row if a strong trend hasn't yet reversed.
2. Sell (Red Sell Label)
When K is equal to or greater than 99.50.
A sell signal.
3. Close to Sell (Red Down Arrow)
When K is equal to or greater than 95.00.
A sell signal may be produced soon.
4. Not Ready (Yellow Circle)
When K is less than 95 and greater than 5.00.
This indicates that neither a sell nor buy signal are close to being produced.
5. Close to Buy (Green Up Arrow)
When K is equal to or less than 5.00.
A buy signal may be produced soon.
6. Buy (Green Buy Label)
When K is equal to or less than 0.50 and greater than 0.00.
A buy signal.
7. Max Buy (Green Buy Label)
When K is equal to 0.00.
Strongest buy signal, remember to make sure that the trend is reversing before making an entry.
8. Kriss (Buy)
A buy signal when the 10 EMA (Blue) crosses above the 50 EMA (Yellow). This is also illustrated by the triggering candle being colored blue.
9. Kross (Sell)
A sell signal when the 10 EMA (Blue) crosses below the 50 EMA (Yellow). This is also illustrated by the triggering candle being colored yellow.
Customization of many different options is available, and the code is open-source for your reference, etc.
Remember to do you own due diligence and feel free to leave a comment with questions, etc.
VWAP Push StrategyThis strategy is unfortunately not finished yet.
A pretty simple strategy. If price broke through VWAP and had three consecutive candles following the breakthroughs trend, the high of the third candle will be drawn. If this happened after a crossover of the vwap and price breaks through the high of the third candle, strategy will go long. Short will be the same after crossing under the vwap. A long or short will be closed after crossing the vwap in the opposite direction, so the vwap is kind of a trailing stop.
Unfortunately, I could not manage to stop the script from entering multiple times into one drawn high or low. Of course, if a high was crossed the script should wait for a new formed high before entering a new long. If someone would find a solution to this, it would be great, because I think it is a nice strategy .
Should work great scalping 5min charts (when scripting, I used the SPX for reference).
Higher Time Frame EMAs and 1% volatility indicatorSet the "higher time frame" (HTF) from which the EMAs will be calculated in all timeframes.
Example: I chose timeframe 1D and I will see the EMAs from TF 1D also in smaller TF as 1, 5, 30, 60 minutes.
There are 4 EMAs. The default values are 5, 10, 60 and 223 periods from "Scalping the Bull" indicator.
You can change the periods of each EMA.
The indicator have also a volatility indication, showing -1% and +1% price levels.
Strategy Myth-Busting #3 - BB_BUY+SuperTrend - [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 third one we are automating is one of the strategies from "The Best 3 Buy And Sell Indicators on Tradingview + Confirmation Indicators ( The Golden Ones ))" from "Online Trading Signals (Scalping Channel)". No formal backtesting was done by them so wanted to validate their claims.
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.
This strategy uses a combination of 2 open-source public indicators:
BB_Buy and Sell by guikroth (default settings)
SuperTrend from TradingView's Technicals (default settings)
Trading Rules
15 min candles
Long
Long condition when BB_BUY indicates buy signal and SuperTrend is green
Short
Short condition when BB_BUY indicates Sell signal and SuperTrend is red
V Bottom & V Top Pattern [Misu]█ This indicator shows V bottom & V top patterns as well as potential V bottom & V top.
These V bottom & V top are chart powerful reversal patterns.
They appear in all markets and time-frames, but due to the nature of the aggressive moves that take place when a market reverses direction, it can be difficult to identify this pattern in real-time.
To address this problem, I added potential V pattern as well as the confirmed one.
█ Usages:
You can use V top & V bottoms for reversal zones.
You can use it for scalping strategies, as a main buy & sell signal.
Potential V patterns can be used to anticipate the market, in addition to volatility or momentum indicators, for example.
█ How it works?
This indicator uses pivot points to determine potential V patterns and confirm them.
Paramaters are available to filter breakouts of varying strengths.
Patterns also have a "max number bars" to be validated.
█ Why a Strategy type indicator?
Due to the many different parameters, this indicator is a strategy type.
This way you can overview the best settings depending on your pair & timeframe.
Parameters are available to filter.
█ Parameters:
Deviation: Parameter used to calculate parameters.
Depth: Parameter used to calculate parameters.
Confirmation Type: Type of signal used to confirme the pattern.
> Mid Pivot: pattern will confirm on mid pivot breakout.
> Opposit Pivot: pattern will confirm on opposit pivot breakout.
> No confirmation: no confirmation.
Lenght Avg Body: Lenght used to calculate the average body size.
First Breakout Factor: This factor multiplied by the "body avg" filters out the non-significant breakout of potential V pattern.
Confirmation Breakout Factor: This factor multiplied by the "body avg" filters out the non-significant breakout for the confirmation.
Max Bars Confirmation: The maximum number of bars needed to validate the pattern.
EMA scalping - PapamallisEma of highs and low and macd.
Can be used as
*macd filter
*breakout
*range market filter
BBSS - Bollinger Bands Scalping SignalsModified Bollinger Bands Indicator
Added:
- color change divergence (green) and narrowing (red) of the upper and lower bands
- color change of the moving average - upward trend (green) and downward trend (red)
- the appearance of a potential signal for long and short positions when the candle closes behind the upper or lower bands.
How to use the indicator:
Long conditions:
- the price breaks through the upper band
- Bollinger bands are expanding and should be green
- the mid-line is green
- the trigger candle should be green
Short conditions:
- the price breaks through the lower band
- Bollinger bands are expanding and should be red
- the mid-line is red
- the trigger candle should be red
Stochastic Rsi+Ema - Auto Buy Scalper Scirpt v.0.3Simple concept for a scalping script, written for 5 minute candles, optimized for BTC.
1st script I've created from scratch, somewhat from scratch. Also part of the goal of this one is to hold coin as often as possible, whenever it's sideways or not dropping significantly.
Designed to buy on the stochastic bottoms (K>D and rising, and <17)
Then and sell after 1 of 3 conditions;
a. After the price goes back up at least 1 % and then 1-2 period ema reversal
b. After the rsi reversal (is dropping) and K<D Flip
c. Stop loss at -1.5%
2 Ema Pullback StrategyHi everyone!
CAUTION... This is only an indicator. Do not rely 100% on it.
I made this indicator hoping to help everyone with this specific Pull Back Scalping Strategy.
RULES:
Time Chart of 5minuts
LONG Condition - "EMA Red Line" below the "EMA Blue Line" and wait for a green long signal.
SHORT Condition - "EMA Red Line" below the "EMA Blue Line" and wait for a red short signal
Feel free to add any adjustments or give feedback so we can improve.
The strategy idea and guidelines came from "The Master" Juan Luis.
Autor: © Germangroa
EMA-Deviation-Corrected Super Smoother [Loxx]This indicator is using the modified "correcting" method. Instead of using standard deviation for calculation, it is using EMA deviation and is applied to Ehlers' Super Smoother.
What is EMA-Deviation?
By definition, the Standard Deviation (SD, also represented by the Greek letter sigma σ or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version is not doing that. It is, instead, using the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA. It is similar to Standard Deviation, but on a first glance you shall notice that it is "faster" than the Standard Deviation and that makes it useful when the speed of reaction to volatility is expected from any code or trading system.
What is Ehlers Super Smoother?
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a a Two-pole Butterworth filter combined with a 2-bar SMA (Simple Moving Average) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Things to know
The yellow and fuchsia thin line is the original Super Smoother
The green and red line is the Corrected Super Smoother
When the original Super Smoother crosses above the Corrected Super Smoother line, its a long, when it crosses below, its a short
Included
Alerts
Signals
Bar coloring
RSI Mean Reversion StrategyThis is a scalping strategy designed to be used for crypto trading. It uses an Exponential Moving Average with a default length of 100 in order to identify the trend of the market. If the price is trading above 100, it will only take long trades, and vice versa for shorts. It places long orders when the RSI value closes below 40, and the price is also above the 100 EMA. It places short orders when the RSI value is above 60, and the price is below the 100 EMA.
*Note: for custom alert messages to be read, "{{strategy.order.alert_message}}" must be placed into the alert dialogue box when the alert is set.
Strategy Myth-Busting #1 - UT Bot+STC+Hull [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 first one is an automated version of the " The ULTIMATE Scalping Trading Strategy for 2022 " strategy from " My Trading Journey " who claims to have achieved not only profits but a 98.3% win rate. As you can see from the backtest results below, I was unable to substantiate anything close to that that claim on the same symbol (NVDA), timeframe (5m) with identical instrument settings that " My Trading Journey " was demonstrating with. Strategy Busted.
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.
This strategy uses a combination of 3 open-source public indicators:
UT Bot Alerts by QuantNomad
STC Indicator - A Better MACD By shayankm
Basic Hull Ma Pack tinkered by InSilico
Trading Rules:
5 min candles
Long
New Buy Signal from UT Bot Alerts Strategy
STC is green and below 25 and rising
Hull Suite is green
Short
New Sell Signal from UT Bot Alerts Strategy
STC is red and above 75 and falling
Hull Suite is red
ADXVMA iTrend [Loxx]ADXVMA iTrend is an iTrend indicator with ADXVMA smoothing. Trend is used to determine where the trend starts and ends. Adjust the period inputs accordingly to suit your backtest requirements. This is also useful for scalping lower timeframes.
What is the ADXvma - Average Directional Volatility Moving Average?
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
Included
Bar coloring
Alerts
Signals
Loxx's Expanded Source Types
VHF-Adaptive T3 iTrend [Loxx]VHF-Adaptive T3 iTrend is an iTrend indicator with T3 smoothing and Vertical Horizontal Filter Adaptive period input. iTrend is used to determine where the trend starts and ends. You'll notice that the noise filter on this one is extreme. Adjust the period inputs accordingly to suit your take and your backtest requirements. This is also useful for scalping lower timeframes. Enjoy!
What is VHF Adaptive Period?
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
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.
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