There can be many ways to make a simple moving average, you can either sum the current and the n-1 previous data points and divide the result by n , or you can do it more efficiently by first taking the cumulative sum of your data points, and subtracting the current cumulative sum result with the cumulative sum results n bars ago, then divide the result by n...
Fast smooth indicators that produce early signals can sound utopic but mathematically its not a huge deal, the effect of early outputs based on smooth inputs can be seen on differentiators crosses, this is why i propose this indicator that aim to return extra fast signals based on a slightly modified max-min normalization method. The indicator...
A study of moving averages that utilizes different tricks I've learned to optimize them. Included is Bollinger Bands, Guppy (GMMA) and Super Guppy.
The method used to make it MtF should be more precise and smoother than regular MtF methods that use the security function. For intraday timeframes, each number represents each hour, with 24 equal to 1 day. For daily,...
There are tons of filters, way to many, and some of them are redundant in the sense they produce the same results as others. The task to find an optimal filter is still a big challenge among technical analysis and engineering, a good filter is the Kalman filter who is one of the more precise filters out there. The optimal filter theorem state that :...
Here's my Dual-color Zero-Lag Moving Average indicator - with alerts - as a separate study
This is published in response to couple of requests i received. Please refer to previous posts on TA Basics on creating zero-lag MAs for more background.
This version adds couple of extras
- the ability to choose the price...
I inspired myself from the MACD to present a different oscillator aiming to show more reactive/predictive information. The MACD originally show the relationship between two moving averages by subtracting one of fast period and another one of slow period. In my indicator i will use a similar concept, i will subtract a quadratic least squares moving...
A derivation of the Kalman Filter.
Lower Gain values create smoother results.The ratio Smoothing/Lag is similar to any Low Lagging Filters.
The Gain parameter can be decimal numbers.
Kalman Smoothing With Gain = 20
For any questions/suggestions feel free to contact me
Impulse responses can fully describe their associated systems, for example a linearly weighted moving average (WMA) has a linearly decaying impulse response, therefore we can deduce that lag is reduced since recent values are the ones with the most weights, the Blackman moving average (or Blackman filter) has a bell shaped impulse response, that is mid term values...
This script is a crossing of eleven different MA, with alerts and SL and TP.
The simplest is what works best.
SMA --> Simple
EMA --> Exponential
WMA --> Weighted
VWMA --> Volume Weighted
SMMA --> Smoothed
DEMA --> Double Exponential
TEMA --> Triple Exponential
HMA --> Hull
TMA --> Triangular
SSMA --> SuperSmoother filter
ZEMA --> Zero Lag Exponential
The term "shapeshifting" is more appropriate when used with something with a shape that isn't supposed to change, this is not the case of a moving average whose shape can be altered by the length setting or even by an external factor in the case of adaptive moving averages, but i'll stick with it since it describe the purpose of the proposed moving average pretty...
This indicator is a collaboration between me and Himeyuri, i encourage you to check her profile and follow her www.tradingview.com
A lot of indicators include a "trigger" line, it can be a smoothed version of another input, in this case the trigger will generate signals from his crosses with the input. The purpose of this indicator is...
Source: Stocks and Commodities V38
Hooray! Another new John Ehlers indicator!
John claims this indicator is lag-less and uses the SPY on the Daily as an example.
This indicator is a slight modification of Reflex, which I have posted here
I think it's better for Stocks and ETFs than Reflex since it factors in long trends. It tends to keep you in winning trades...
John F. Ehlers introuced Zero-Lag Data Smoothers in Jul, 2002.
John Ehlers introduced "Zero-Lag Data Smoothers", the infinite impulse response (IIR) filter and finite impulse response (FIR) filter.
In his article this issue on zero-lag smoothing, John Ehlers notes that his favorite filter is the symmetrically weighted six-bar...
It is possible to use a wide variety of filters for the estimation of a least squares moving average, one of the them being the Kaufman adaptive moving average (KAMA) which adapt to the market trend strength, by using KAMA in an lsma we therefore allow for an adaptive low lag filter which might provide a smarter way to remove noise while preserving...
I already estimated the least-squares moving average numerous times, one of the most elegant ways was by rescaling a linear function to the price by using the z-score, today i will propose a new smoother (FLSMA) based on the line rescaling approach and the inverse fisher transform of a scaled moving average error with the goal to provide an...
Remember that we can make filters by using convolution, that is summing the product between the input and the filter coefficients, the set of filter coefficients is sometime denoted "kernel", those coefficients can be a same value (simple moving average), a linear function (linearly weighted moving average), a gaussian function (gaussian filter), a...