R-squared Adaptive T3 [Loxx]R-squared Adaptive T3 is an R-squared adaptive version of Tilson's T3 moving average. This adaptivity was originally proposed by mladen on various forex forums. This is considered experimental but shows how to use r-squared adapting methods to moving averages. In theory, the T3 is a six-pole non-linear Kalman filter.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis. Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD, Momentum, Relative Strength Index) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA (simple moving average) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA(n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA.
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE/2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE/2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE/2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA, popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE/2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA(3) has lag 1, and EMA(11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA(3) through itself 5 times than if I just take EMA(11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA(3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA(7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA(n) = EMA(n) + EMA(time series - EMA(n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA. The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA(n) + EMA(time series - EMA(n))*.7;
This is algebraically the same as:
EMA(n)*1.7-EMA(EMA(n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD(n,v) = EMA(n)*(1+v)-EMA(EMA(n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA, and when v=1, GD is DEMA. In between, GD is a cooler DEMA. By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD(GD(GD(n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA(n)) to correct themselves. In Technical Analysis, these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included:
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Komut dosyalarını "signal" için ara
Nyquist Moving Average (NMA) MACD [Loxx]Nyquist Moving Average (NMA) MACD is a MACD indicator using Nyquist Moving Average for its calculation.
What is the Nyquist Moving Average?
A moving average outlined originally developed by Dr . Manfred G. Dürschner in his paper "Gleitende Durchschnitte 3.0".
In signal processing theory, the application of a MA to itself can be seen as a Sampling procedure. The sampled signal is the MA (referred to as MA.) and the sampling signal is the MA as well (referred to as MA). If additional periodic cycles which are not included in the price series are to be avoided sampling must obey the Nyquist Criterion.
It can be concluded that the Moving Averages 3.0 on the basis of the Nyquist Criterion bring about a significant improvement compared with the Moving Averages 2.0 and 1.0. Additionally, the efficiency of the Moving Averages 3.0 can be proven in the result of a trading system with NWMA as basis.
What is the MACD?
Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average (EMA) from the 12-period EMA.
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the security when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence (MACD) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
Included
Bar coloring
2 types of signal output options
Alerts
Loxx's Expanded Source Types
ALMA cross signal by hk4jerry<< ALMA CROSS signal >>
*NONE REPAINT STRATEGY*
--As a result of testing for a month, using alma does not result in repainting--
--ALMA 크로스 결과는 한달간의 테스트 결과, 리페인팅되지 않습니다--
(ENGLISH description O)
==NOTE==
1. MA 크로스 지표는 잘못된 신호들이 자주 등장합니다. 정확성을 더 높일수 있는 방법은 없을까 고민을 해봤습니다. 더 낮은 가격에 매수하고, 더 높은 가격에서 매도하는 것이 중요했습니다. 우리가 흔히 저점, 고점을 알아내기 위한 지표이자, 선행지표인 RSI를 추가하는 방법을 연구했습니다.
2. 예를 들어, MA 크로스 매수 신호가 발생했을때, rsi값이 50이면 가격이 더 떨어질 가능성이 큽니다. 하지만, rsi값이 30이하인 경우에만 매수 신호가 발생한다면, 그 가격이 저점일 확률이 매우 높아지는 원리 입니다.
3. 신호는 확률입니다. 트레이딩에 100%는 없습니다. 그 확률을 높이는 것은 리스크 관리 입니다. 분할 매수 관점으로 포지션을 잡으시거나, 단기 매매로 가져가시는걸 추천드립니다.
==rsi ma source 설정==
1. 'rsi ma' 값의 소스입니다.
2. 'rsi 길이' 는 값이 클수록 더욱 정확한 시그널이 발생합니다.
3. EMA 길이가 짧을수록 더 많은 시그널이 발생합니다. 그러나, 정확도는 떨어집니다.
==rsi ma 설정==
1. rsi를 source로한 EMA입니다.
2. rsi와 유사한 성격을 가집니다.
3. 'rsi ma' 값이 30이하이면 과매도, 70이상이면 과매수 입니다.
4. ' rsi ma long value' 이 30이면 매수 신호가 rsi ma 값이 30 이하인 경우에만 발생함을 의미 합니다.
5. "rsi ma short value' 가 70이면 매도 신호가 rsi ma 값이 70 이상인 경우에만 발생함을 의미 합니다.
==rsi 설정==
1. 실제 rsi(14,close) 값을 의미합니다.
2. rsi ma value와 비슷한 기능입니다.
3. rsi 길이가 14이므로, 값은 40~50 사이가 적당합니다.
4. 30 또는 70으로 설정할 시, 신호가 거의 발생하지 않습니다.
(ENG)
==NOTE==
1. MA cross indicator often shows false signals. I was wondering if there is a way to increase the accuracy further. It was important to buy at a lower price and sell at a higher price. We studied how to add RSI, which is a leading indicator and an indicator to find lows and highs, often.
2. For example, when a buy MA cross signal occurs, if the rsi value is 50, the price is more likely to fall. However, if a buy signal occurs only when the rsi value is below 30, the probability that the price is at the bottom is very high.
3. A signal is a probability. There is no 100% in trading. Increasing that probability is risk management. It is recommended to hold a position from the perspective of a split buy or take it as a short-term trade.
==rsi ma source option==
1. The source of the 'rsi ma' value.
2. The larger the 'rsi length' value, the more accurate the signal is generated.
3. Shorter EMA lengths produce more signals. However, the accuracy is reduced.
==rsi ma options==
1. EMA with rsi as the source.
2. It has similar characteristics to rsi.
3. If the 'rsi ma' value is below 30, it is oversold, and if it is above 70, it is overbought.
4. If 'rsi ma long value' is 30, it means that a buy signal will only occur when the rsi ma value is less than or equal to 30.
5. If "rsi ma short value' is 70, it means that a sell signal will only occur when the rsi ma value is above 70.
==rsi option==
1. It means the actual rsi(14,close) value.
2. This function is similar to rsi ma value.
3. Since the rsi length is 14, a value between 40 and 50 is appropriate.
4. When set to 30 or 70, almost no signal is generated.
[JL] How Many Signals last N barsGot this idea after I found Multiple Indicators Screener from QuantNomad.
This script learnt some codes from QuantNomad's great script. Thanks to him.
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This table show how many signals happened during the last N bars.
I only take care Forex, so this table only has 28 symbols. Feel free to change it.
Calculate the following signals:
RSI cross over/under 50
Short Moving average cross over/under long moving average
Stochastic k cross over/under d
MACD hist cross over/under 0
Williams Fractals: Up and Down fractals happened.
The concept is simple: Range period will always happen more cross signals than the trend period.
When the counter is less than median of all symbols, will be set green color. So more green mean more chance to be trend.
Directional Movement w/Hann Slope Change SignalModified version of
Presented here is code for the "Directional Movement w/Hann" indicator originally conceived by John Ehlers. The code is also published in the December 2021 issue of Trader's Tips by Technical Analysis of Stocks & Commodities (TASC) magazine.
John Ehlers is continuing to revamp old indictors with Hann windowing. The original script uses zero line cross to signal buy/sell in this modified version buy/sell is signaled based on slope change, where signal is generated on with previous value is greater/less than current value
If current > previous = buy and if current < previous = sell
EneX SignalEneX is signal that give recommendation signals for entry and exit on spot market. This indicators not suitable for leverage trading in futures market.
EneX signal consider several indicators and has entry and exit rules.
EneX signal is suitable for investors who believe in trend following strategy (disclaimer on).
This script composed by Yohan Naftali for educational purpose only. Reader who will use this signal must do own research.
Indicator and Plot Involved
1. Williams Fractals with default periods = 2
2. William Alligator Indicators with default simple moving average 8, 13, and 21
3. Exponential Moving Averages with default value EMA 50, 100, and 200
4. Relative Strength Index with default overbought level = 80 and oversold level = 20
5. Williams Fractals are joined to create support and resistance line and fill area between support and resistance lines.
Entry signal conditions
1. Entry on Weakness when bullish fractal appear on n/2 period
2. Entry when price break resistance line
All entry condition must above EMA and alligator signal and not in overbought RSI
Exit signal conditions
1. Lowest price is below Exponential Moving Average
2. Lowest price is below William alligator lines
You can easily find entry and exit points by using Entry (E), Exit(X) signals
How to use
1. Monitor chart and wait until E or X signals
2. Entry if Entry Signal (E) appear (green colored label)
3. Exit if Exit Signal (X) appear (red colored label)
4. Change indicators setting when necessary
Best Practice
1. Entry only when entry signal (E) appear
2. Never entry when price below William alligator signal
3. Exit when exit signal (X) appear
4. Not exit when exit signal appear when you believe or you have information that price will be rebound
5. Exit if you believe that current price meet your target price
6. Always wise when use EneX signals
Disclaimer
Do your own research and consider fundamental price of asset.
The indicators provided on this script is for educational purposes only.
Author does not offer advisory or brokerage services, nor does it recommend or advise users to buy or sell particular stocks or securities.
Please examined script and give feedback for further improvement.
Williams Fractals BUY/SELL signals indicatorThis indicator made with using Williams Fractals, 20 50 100 Moving Averages and Relative Strength Index. You can easily find entry points by using Long (L), Short (S) signals.
This is a 15min scalping strategy for BTC:USDT Perpetual pair. For use different pairs or TFs you may need to change settings.
How to use
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When flashing Long (L) or Short (S) signal you should wait until the candle closing for the confirmation.
After that candle closed with the signal, you can enter a trade in next candle opening.
Your SL should be 3.1% from etnry and TP should be 0.5% from entry for best results. (You can use Long Position / Short Position tool in Prediction and Measurement Tools in drawing pannel to calculate this. This settings only for BTC:USDT Perp 15 min TF. For other TFs or Pairs settings may vary. You can easily change these settings and backtest your own.)
After entering a trade you can be ignored next signals until close the trade.
To learn more about this strategy, please try the "Williams Fractals Strategy" I coded. Thank you!
Zendog LONG DCA Trigger RSI+StochRSIThis is a script that generates a BUY signal by combining RSI and Stochastic RSI into the same script and that can easily be integrated into an external Backtester like the one I published.
The script uses default values for RSI and Stochastic RSI oversold conditions.
They should be adjusted for specific assets and timeframes so they better match the current trend. Please beware you might overfit settings to match a short timeframe trend (like a few days or hours). If this is the case once the trend changes the signals will not be accurate.
The purpose of this script is to provide some pine code that can be used to further combine multiple indicators into a LONG Deal Start signal.
Integration with the Zendog Backtster:
- add the backtester on the chart
- add this script on the chart
- in the Zendog backtester Deal start type select "External indicator"
- in the Zendog backtester Indicator source and value select "Zendog LONG DCA Trigger RSI+StochRSI: SIGNAL"
vol_signalNote: This description is copied from the script comments. Please refer to the comments and release notes for updated information, as I am unable to edit and update this description.
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USAGE
This script gives signals based on a volatility forecast, e.g. for a stop
loss. It is a simplified version of my other script "trend_vol_forecast", which incorporates a trend following system and measures performance. The "X" labels indicate when the price touches (exceeds) a forecast. The signal occurs when price crosses "fcst_up" or "fcst_down".
There are only three parameters:
- volatility window: this is the number of periods (bars) used in the
historical volatility calculation. smaller number = reacts more
quickly to changes, but is a "noisier" signal.
- forecast periods: the number of periods for projecting a volatility
forecast. for example, "21" on a daily chart means the plots will
show the forecast from 21 days ago.
- forecast stdev: the number of standard deviations in the forecast.
for example, "2" means that price is expected to remain within
the forecast plot ~95% of the time. A higher number produces a
wider forecast.
The output table shows:
- realized vol: the volatility over the previous N periods, where N =
"volatility window".
- forecast vol: the realized volatility from N periods ago, where N =
"forecast periods"
- up/down fcst (level): the price level of the forecast for the next
N bars, where N = "forecast periods".
- up/down fcst (%): the difference between the current and forecast
price, expressed as a whole number percentage.
The plots show:
- blue/red plot: the upper/lower forecast from "forecast periods" ago.
- blue/red line: the upper/lower forecast for the next
"forecast periods".
- red/blue labels: an "X" where the price touched the forecast from
"forecast periods" ago.
+ NOTE: pinescript only draws a limited number of labels.
They will not appear very far into the past.
Inverse Fisher Transform on RSI for backtest w/alertsThis version of the Inverse Fisher Transform on RSI comes with support for
1) Backtesting with Gavin's backtest script
2) Bypass, you can use another indicator to pause buy signals from this indicator. Just create another indicator that plots "1" whenever you want to activate the bypass on the IFTRSI signal.
3) Independent buy and sell level thresholds. Some tokens perform better with a higher sell level, even levels as high as 0.996, sometimes the buy level can also be relaxed to even 0.6 and get incredible results on the 5 minute chart.
4) alerts for Buy and Sell signals
Make sure you add Gavin's backtest and select external signal and this indicator as the source.
buy & sell signalSell signal:
when the fastest moving average is on the upper bound and intersects the other moving averages.
Buy signal:
when the fastest moving average is on the lower bound and intersects the other moving averages.
Fisher Transform with SignalsFisher Transform with Signals
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.1 The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
-The Fisher Transform is a technical indicator that normalizes asset prices, thus making turning points in price clearer.
-Some traders look for extreme readings to signal potential price reversal areas, while others watch for a change in direction of the Fisher Transform.
-The Fisher Transform formula is typically applied to price, but it can also be applied to other indicators.
-Asset prices are not normally distributed, so attempts to normalize prices via an indicator may not always provide reliable signals.
The Fisher Transform enables traders to create a Gaussian normal distribution, which converts data that isn't typically normal distributed, such as market prices. In essence, the transformation makes peak swings relatively rare events to help better identify price reversals on a chart.
This technical indicator is commonly used by traders looking for leading signals, rather than lagging indicators. The Fisher Transform can also be applied to other technical indicators, such as the relative strength index (RSI) or moving average convergence divergence (MACD).
How to Calculate the Fisher Transform
1.Choose a lookback period, such as nine periods. This is how many periods the Fisher Transform is applied to.
2.Convert the prices of these periods to values between -1 and +1 and input for X, completing the calculations within the formula's brackets.
3.Multiply by the natural log.
4.Multiply the result by 0.5.
5.Repeat the calculation as each near period ends, converting the most recent price to a value between -1 and +1 based on the most recent nine-period prices.
6.Calculated values are added/subtracted from the prior calculated value.
How can this script tell us to buy or sell?
- If the fisher is bigger then trigger background will be colored blue and this means you can buy
- If the trigger is bigger then fisher this means you can sell
ADX Momentum cross + MacD + HH LL + Buy/Sell Signals and alerts Hello, This is the first indicator I have made and would like to contribute to the community.
This strategy came from trying to replicate a previous ADX Cross Indicator that I loved on MT4 which I used successfully on EUR/USD on high and low time frames. Through the process of trying to replicate it I failed, I decided to take what I had written so far and create my own ADX cross strategy using the combination of 3 ADX's, their lag. Then also using Higher highs and lower lows with the MacD to further filter the signals.
There are two buy and two sell conditions , the difference between these are just the order in which the ADX crossing determines the entry. The MacD and higher highs and lower lows are the same for filtering the signal.
You can change the look back for HH and LL look back range, along with the DI Length & ADX Smoothing for all ADX's. The lag used for either the buy or sell strategy with the Lag_Buy/Lag_Sell inputs. Lag_mid setting will affect all 4 conditions.
From testing and based on the ADX cross logic you should follow this structure when changing the inputs for:
DI Length: Lowest DI value (I.E. 1)
DI Lengtha: Middle DI value (I.E. 2)
DI Lengthb: Highest DI value (I.E. 3)
ADX Smoothing: Lowest Smoothing value (I.E. 1)
ADX Smoothinga: Middle Smoothing value (I.E. 2)
ADX Smoothingb: Highest Smoothing value (I.E. 3)
I tested this on the EUR/USD, but mainly I have been using it on BTC/USDT(binance) and BTC/USDT Perpetual futures(binance) with the 5 minute chart. I suggest playing around with the settings depending on the Symbol and timeframe you use because the default settings are what I last found to be optimal for my self on the 5min BTC/USDT Perpetual futures(binance) chart.
A good starting point I found when using the indicator on other charts is to use the below values:
DI Length: 7
DI Lengtha: 14
DI Lengthb: 21
ADX Smoothing: 7
ADX Smoothinga: 14
ADX Smoothingb: 21
If you have any questions, suggestions, or requests for this indicator feel free contact me. You can either comment on here or Message me
If you like this indicator please like and comment where you found it useful.
Stochastic RSI+Applies signal values to significant changes in momentum and can be used in conjunction with other indicators and analysis to improve trade timing.
Both "Signal Up" and "Signal Down" can be used for alerts.
The magnitude of the signal is the difference between K and D.
(See the code for the logic and implementation.)
Signal Up occurs when momentum is within the band and moving upward.
Signal Down occurs when momentum is within the band and moving downward.
Interpretation Note:
The Stochastic RSI is known for false signals, so it should never be used as a pure buy or sell signal. It is useful as a warning or to help with trade timing.
A good example of this is: If you are bullish on a stock, and the signal is negative (signal down), then it may be wise to not buy until the recent change in momentum has dissipated.
Candlestick Pattern IdentifierMy script builds upon another user-submitted script by rebuilding the logic used to identify candlestick patterns. The logic in my script is a mix of strict and lax guidelines to mitigate false flags and present valid buy and sell signals.
-To use this indicator, simply add it to any chart. It will identify trends on any time frame although the lower you go, the more signals you'll see and the higher probability of those signals being false flags. You can also disable any candlestick patterns that you feel are not as useful.
- This indicator works best with Stocks and also with Forex markets to a lesser extent.
- This indicator works the best on the Daily chart and also works (with varying degrees of success) on any timeframe at or above 1 hour. I've found that this indicator works the best when used in tandem with the Daily and Hourly charts with the Hourly chart being used to determine an entry point while the Daily chart is used for long term trend analysis.
CDC ActionZone V3 2020## CDC ActionZone V3 2020 ##
This is an update to my earlier script, CDC ActionZone V2
The two scripts works slightly differently with V3 reacting slightly faster.
The main update is focused around conforming the standard to Pine Script V4.
## How it works ##
ActionZone is a very simple system, utilizing just two exponential moving
averages. The 'Zones' in which different 'actions' should be taken is
highlighted with different colors on the chart. Calculations for the zones
are based on the relative position of price to the two EMA lines and the
relationship between the two EMAs
CDCActionZone is your barebones basic, tried and true, trend following system
that is very simple to follow and has also proven to be relatively safe.
## How to use ##
The basic method for using ActionZone is to follow the green/red color.
Buy when bar closes in green.
Sell when bar closes in red.
There is a small label to help with reading the buy and sell signal.
Using it this way is safe but slow and is expected to have around 35-40%
accuracy, while yielding around 2-3 profit factors. The system works best
on larger time frames.
The more advanced method uses the zones to switch between different
trading system and biases, or in conjunction with other indicators.
example 1:
Buy when blue and Bullish Divergence between price and RSI is visible,
if not Buy on Green and vise-versa
example 2:
Set up a long-biased grid and trade long only when actionzone is in
green, yellow or orange.
change the bias to short when actionzone turns to te bearish side
(red, blue, aqua)
(Look at colors on a larger time frame)
## Note ##
The price field is set to close by default. change to either HL2 or OHLC4
when using the system in intraday timeframes or on market that does not close
(ie. Cryptocurrencies)
## Note2 ##
The fixed timeframe mode is for looking at the current signal on a larger time frame
ie. When looking at charts on 1h you can turn on fixed time frame on 1D to see the
current 'zone' on the daily chart plotted on to the hourly chart.
This is useful if you wanted to use the system's 'Zones' in conjunction with other
types of signals like Stochastic RSI, for example.
Simple EMA Trading SignalUse it on:
1. Heiken Ashi, Bitstamp: BTCUSD , M15
2. Heiken Ashi, Bitstamp: BTCUSD, D1
3. USOIL Candlesticks H1
4. EURUSD Daily Candlesticks
5. GBPUSD Daily Candlesticks
6. SPX W1 Candlesticks
7. SPX H1 Heiken Ashi
8. XAUUSD Daily
Experimental Entry Interface (Buy Arrows with TP & SL)This script provides high probability entry points and includes Take Profit and Stop Loss targets.
It attempts to predict when the market conditions are set to move up, and prints long positions.
In addition to Long Entry Arrows, it will print Take Profit / Stop Loss targets.
This indicator is highly adjustable. Hence the name 'Experimental' in the title. Experiment with it to find the results you want.
Designed for use on the 1H timeframe in Forex, but could possibly be useful elsewhere. Do your own testing.
This indicator can repaint. It is best used with alerts set for once per bar close, so that your alerts do not repaint and your trades are solid.
Not ever signal is a winner. Backtest thoroughly. Adjust accordingly.
Arrows
Four sets of colored arrows are included.
💵 💶 Green and Blue Entry Arrows are formed when the market is in an uptrend, and has a momentary pullback.
💴 💷 Yellow and Purple Entry Arrows are formed when the market is just starting to recover from being severely oversold.
Backtest Mode
Turn on Backtest Mode to easily see if an entry ended up as a winner or loser. A Take Profit and Stop Loss line will be drawn to show results.
Take Profit & Stop Loss Targets
You have two options for this.
Price will show you where your TP/SL exits should be placed. These values will show up under the arrow, based on your Risk/Reward ratio.
Pips are much more simple, and will only show you the market entry point and how many pips up/down to place your SL/TP. Warning: This is fixed at a 1:1 RRR .
Risk/Reward Adjustment
Each entry arrow color allows custom risk/reward ratio adjustment.
Dollar Amounts Displayed
Change your account value and leverage to see how much you would have won on each trade.
How to trade with it?
(Forex, 1H) Open the settings, and turn on all the arrow entries. Turn on Backtest mode to see how past trades would have played out. Turn on TakeProfit/StopLoss Targets to see where to set your targets, for each arrow. Set an alert to notify you once per candle close when there is an Entry. Trade happy!
Bill Williams Alligators are also included, if you want. Not necessary though. Some of the calculations depend on them for trend direction analysis.
Relative Volume RVOL AlertsRelative Volume or RVOL is an indicator used to help determine the amount of volume change over a given period of time.
It is often used to help traders determine how in-play a ticker is.
General rule of thumb is the higher the RVOL, the more in play a stock is.
I myself like to use it as a substitute of the volume indicator itself.
Basic Calculation:
Relative Volume = Current Volume / Average Volume
Crossover Signals:
Any time there is a volume spike which causes a crossover of the user set 'Smoothed Moving Average' or 'Threshold' a green/red dot will appear at the top. The color of the dot is dependent on closing of the candle. Therefore it does not necessarily mean price will continue in that direction since volume spikes often happen in peaks or valleys.
Threshold:
The level at which custom alerts and signal can be set. The higher the value, the more volume required to trigger.
Built in Alerts:
You can set custom alerts for the crossovers of the adjustable threshold, or the average RVOL band.
MT4 MACD This is a plain macd similar to the one on the mt4
There are extra colors added for visuals
Primarily requested by user Sonja.
macd // signalline // macdmt4 // mt4macd
Smeared VCIThis indicator can be used to enter the market.
When the signal line crosses upwards the base line, enter short;
when the signal line crosses downwards the base line, enter long;
A filter can be used to enter short when in a downtrend or long in an uptrend.
A fair filter can be the ema(200) line defining an uptrend when price is above it or
a down trend when the price lies below.
Use at your own risk.
Hitting the like button is a free act of gratitude.
Have fun.
RSI/MFI - MTF - Entry signals/Trend colored bars - JD@version=2
This indicator is designed to give early entry signals as well as to follow trend moves, according to different settings.
The indicator shows a histogram of the RSI ro MFI in relation to an ema of the RSI or MFI.
The histogram is then smoothed to give early reversal/entry signals.
The actual RSI/MFI line with oversold/overbought indication can be displayed or omitted, as preferred.
in addition to the RSI/MFI line or as an alternative to it, the background colour can be set to change folowing the RSI/MFI signals.
The timeframe can be chosen. Higher timeframes (eg. 3h) tend to give less false signals.
version 5.
added support for custom Multiple Time Frame selection.
added option for choice of RSI or MFI as base indicator.
added option for price bar coloring according to the indicator. (deselecting "borders" in the "style" tab is recommended)
price bar coloring can be adjusted for different strategies:
1. following the slope of the histogram (for faster entry/exit signals)
2. according to positive or negative histogram (for longer moves)
3. according to pos. or neg. RSI/MFI (for longer term trend holds)
4. uptrend: biased towards faster buy signals and slower sell signals to stay in the uptrend
5. downtrend: biased towards faster sell signals and slower buy signals to stay in the downtrend
A longer timeframe (eg. 3x) is recommended for following trend moves.
try different strategies to see what works better for RSI or MFI.
JD.
SMMA Analyses - Buy / Sell signals and close position signals This script combines the usage of the SMMA indicator in order to provide signals for opening and closing trades, either buy or sell signals.
It uses two SMMA , a fast and a slow one, both configurable by the users.
The trigger of Buy and Sell Signals are calculated through the SMMA crosses:
Buy Signals : The fast SMMA crosses over the slow SMMA . They are highlighting by a green area and a "B" label.
Sell Signals : The fast SMMA crosses under the slow SMMA . They are highlighting by a red area and a "S" label
The trigger of Close Buy and Close Sell Signals are calculated through the close price crosses with the fast SMMA:
Close Buy Signals : The fast SMMA crosses under the close price and at the same time the trend is bullish , so the fast SMMA is greater than the slow SMMA . They are highlighted by a lighter green area
Close Sell Signals : The fast SMMA crosses over the close price and at the same time the trend is bearish , so the fast SMMA is lower than the slow SMMA . They are highlighted by a lighter red area
Few important points about the indicator and the produced signals :
This is not intended to be a strategy, but an indicator for analyzing the SMMA conditions. It gives you the triggers depending on the real time analysis of the SMMA and prices, but not being a proper strategy, pay attention about "fake signals" and add always a visual analysis to the provided signals
Following this indicator, the trade positions should be opened only when a cross happens. Either in this case, analyse the chart in order to see if the signals are a "weak" ones, due to "waves" around the SMMA . In these cases, you might wait for the next confirmation signals after the waves, when the trend will be better defined
The close trade signals are provided in order to help to understand when you should close the buy or sell trades. Even in this case, always add a visual analysis to the signals, and pay attention to the support/resistance areas. Sometimes, you can have the close signals in correspondence to support/resistance areas: in these cases wait for the definition of the trend and eventually for the next close trade signals if they will be better defined
