Smoothed CandlesHello Traders,
This is " Smoothed Candles " script to get rid of noises and to get a smoothed chart to figure out breakouts and price movements easily.
There are three scaling methods: User Defined, Dynamic (ATR) and Percentage
Optionally you can add 2 Simple Moving Averages and 2 Exponential Moving Averages
Optionally you can hide the Wicks, example:
You can add moving averages:
Easily find breakouts:
Enjoy!
Smoothed
Multi Smoothed Moving AverageAn indicator that shows multiple Smoothed Moving Averages, with buy/sell signals on the second and third moving averages crosses
SMMA 5-13 crossCrossing the Smoothed Moving Averages with settings 5 & 13 give you confident signal for selling or buying.
IMPORTANT: Signal is always late.
SELL : Short SMMA (5) cross the Long SMMA (13) from top
BUY : Short SMMA (5) cross the Long SMMA (13) from down
Normalized Smoothed MACDMACD normalized with its highest and lowest values over the last “Normalization period”
- includes alerts
MTF Smoothed Moving Averages x4A set of smoothed moving averages that stay at a fixed timeframe, regardless of the timeframe of the chart but don't have nasty jaggedy lines. Instead, they are smooooooooooooth...
Volume Effectiveness [BigBitsIO]This Volume Effectiveness indicator is designed to allow users to try and identify how effective volume is on each candle, and smoothing those values over time to try to find trends.
Volume Effectiveness is the % change in price for each single unit of volume on the associated candle. The value can be positive or negative, but there is an option to just monitor an absolute value.
Features:
- Volume Effectiveness
- Toggle if Volume Effectiveness should be an absolute value
- Toggle visibility of bars
- Smoothed moving average of Volume Effectiveness
- Adjustable period on the smoothed moving average
- Several moving average types available to use for the smoothed moving average
- Toggle visibility of smoothed moving average
Buying and Selling Smoothed with HistogramBuying and Selling Smoothed with Histogram
Smoothed version with version with a red line representing the selling pressure and a green line which represents the Buying pressure.
If the green line is above the red line it would mean that the Buying pressure is more and vice versa.
The difference between the two is plotted as a Histogram. This is a cumulative value of the buying and selling pressure and provides a easy visual presentation of the dominating pressure.
Modiied Elder Ray Index(Bull or Bear)Here's a modified version of the Elder Ray Index created by the famed Dr.Alexander Elder. This indicator has proven to be especially helpful lately given the crazy state of crypto.
Slow Moving Average :
The top chart shows the moving average used to filter trends. I recommend using a higher window length(can be adjusted with the 'lenSlowMA' input option). I wanted this to be a very smooth moving average, so I used the following formula:
slow MA = ema(vwma(close, 64), 64)
This resulted in a pretty smooth line that still detects major price movements very well.
-The background and bar colors both change in response to the Slow MA's value. The background and bars change to green when a bullish trend is detected and red when bearish.
Bear and Bull Power :
To balance things out a little, I included two histogram's based on Elder's Ray. Here, a more responsive EMA with a shorter window length is used to calculate the bull and bear power values and track short-term price fluctuations.
NOTE: The length of the EMA used here can be adjusted in the input menu.
Bull Power = current high - EMA(close, 13)
Bear Power = current low - EMA(close, 13)
1LC-LSMA (1 line code lsma with 3 functions)Even Shorter Estimation
I know that i'am insistent with the lsma but i really like it and i'm happy to deconstruct it like a mad pinescript user. But if you have an idea about some kind of indicator then dont hesitate to contact me, i would be happy to help you if its feasible.
My motivation for such indicator was to use back the correlation function (that i had putted aside in the ligh-lsma code) and provide a shorter code than the estimation using the line rescaling method (see : Approximating A Least Square Moving Average In Pine) .
The Method
Fairly simple, lets name y our estimation, we calculate it as follow:
y = x̄ + r*o*1.7
where x̄ is the price moving average, r the correlation between the price and a line (or n) and o the standard deviation. If plotted against a classic lsma the difference would be meaningless at first glance so lets plot the absolute value between the difference of the lsma and our estimation of both period 100.
The difference is under 0.0000 on eurusd, its really low.
In general the longer the period of the estimation, the lower the difference between a normal lsma, but when using shorter period they can differ a little bit.
Why 1.7 ?
We need to multiply the standard deviation by a constant in order to match the overshoot and the rise-time of the original lsma. The constant 1.7 is one that work well but actually this constant should be dependant of the length period of the filter to make the estimation more accurate.
More About Step-Response
Most of the time when a filter have less lag, it mean that he induce overshoot in order to decrease the rise-time . Rise-time is the time the output take to match the target input, its related to the lag. Overshoot mean that the output exceed the target input, you can clearly see those concept in the image above.
Conclusion
I've showed that its possible to be even more concise about the code it take to estimate an lsma. I've also briefly explained the concept of rise-time and overshoot, concepts really important to signal processing and particularly in filter design. I'm sure that it can be even more simplified and i have some ideas for such estimate.
Thanks for reading !
Adaptive StochasticAdapt To The Right Situation
There are already some Adaptive Stochastic scripts out there, but i didn't see the concept of using different periods highest/lowest for their calculations. What we want
for such oscillator is to be active when price is trending and silent during range periods. Like that the information we will see will be clear and easy to use.
Switching between a long term highest/lowest during range periods and a short term highest/lowest during trending periods is what will create the adaptive stochastic.
The switching is made thanks to the Efficiency Ratio , the period of the efficiency ratio is determined by the length parameter.
The period of the highest and lowest will depend on the slow and fast parameters, if our efficiency ratio is close to one (trending market) then the indicator will use highest and lowest of period fast , making the indicator more reactive, if our efficiency ratio is low (ranging market) then the indicator will use highest and lowest of period slow , making the indicator less reactive.
The source of the indicator is a running line ( lsma ) of period slow-fast .
it is also possible to switch the parameters values, making the indicator reactive during ranging market and less reactive during trending ones.
Hope you enjoy
For any questions/demands feel free to pm me, i would be happy to help you
Karobein OscillatorDeveloped by Emily Karobein, the Karobein oscillator is an oscillator that aim to rescale smoothed values with more reactivity in a range of (0,1)
Calculation
The scaling method is similar to the one used in a kalman filter for the kalman gain.
We first average the up/downs x, those calculations are similar to the ones used for calculating the average gain/loss in the relative strength index.
a = ema(src < src ? x : 0,length)
b = ema(src > src ? x : 0,length)
where src is a exponential moving average of length period and x is src/src in the standard calculations, but anything else can be used as long as x > 0 .
Then we rescale the results.
c = x/(x + b)
d = 2*(x/(x + c*a)) - 1
How To Use
It is better to use centerline-cross/breakouts/signal line.
In general when we use something smooth as input in oscillators, breakouts are better than reversals, you can see this with the stochastic and rsi.
So a simple approach could be buying when crossing over 0.8 and selling when crossing under 0.2.
Here is the balance of a strategy using those conditions, length = 50 .
20 trades have been mades since the 29 oct we made 341 pips with eur/usd, of course this backtest was made during good trends period,
this result is not representative of how the strategy work with other conditions/markets.
For any questions/suggestions feel free to contact me
Squam's top shelfThis is a means to find the highest triple moving average input from an array of triple moving averages. The effect is to dampened the impact of price changes and look for a critical level to qualify a good or bad trades. If the price closes above a rising red line the odds probably favor a long. If the price closes below a declining red line the odds probably favor a short. There is another script that will cover the opposite priority for the highest triple moving average input from an array of triple moving averages.
-Squam
Squam's bottom rungThis is a means to find the lowest triple moving average input from an array of triple moving averages. The effect is to dampened the impact of price changes and look for a critical level to qualify a good or bad trades. If the price closes above a rising green line the odds probably favor a long. If the price close below a declining green line the odds probably favor a short. There is another script that will cover the opposite priority for the highest triple moving average input from an array of triple moving averages.
-Squam
MTF SROC v1 by JustUncleLDescription:
This study plots Smoothed Rate of Change (SROC) indicators for up to 4 different time frames. The indicator does not use higher time frame data, so will not re-paint. The SROC is a momentum indicator and can be used in ranging or trending markets, please refer to the reference for further details of how to use the indicators.
References:
www.incrediblecharts.com
ROC and SROC v1 by JustUncleLDescription:
This study plots a combination Rate of Change Indicator (ROC) and Smoothed Rate of Change (SROC) indicators.
The ROC and SROC are momentum indicators and can be used in ranging or trending markets, please refer to the references for further details of how to use the indicators.
References:
www.incrediblecharts.com
www.incrediblecharts.com
Heikin Ashi Smoothed (yasinipek) by KIVANC fr3762Heikin Ashi Smoothed Strategy
A trend trading forex system composed of the Smoothed Heiken Ashi candlestick indicator and moving averages. It works best on the 1 hour charts and higher time frames.
buy when blue line crosses above red
conversely sell when red line crosses above blue
Author: Yasin İpek @yasinipek83 on twitter / www.yasinipek.com & KıvanÇ @fr3762 on twitter (tweets are only in TURKISH)
Ehlers DSMA by Tim D.The Deviation-Scaled Moving Average from July 2018 TASC. "In “The Deviation-Scaled Moving Average” in this issue, author John Ehlers introduces a new adaptive moving average that has the ability to rapidly adapt to volatility in price movement. The author explains that due to its design, it has minimal lag yet is able to provide considerable smoothing."
Smoothed Rate of ChangeSmoothed Rate of Change indicator script.
This indicator was originally developed by Fred G. Schutzman.
Smoothened Williams A/D Strategy Accumulation is a term used to describe a market controlled by buyers;
whereas distribution is defined by a market controlled by sellers.
Williams recommends trading this indicator based on divergences:
Distribution of the security is indicated when the security is making
a new high and the A/D indicator is failing to make a new high. Sell.
Accumulation of the security is indicated when the security is making
a new low and the A/D indicator is failing to make a new low. Buy.
WARNING:
- This script to change bars colors.
