Today we are going to discuss about Zero Lag EMA 15min strategy for Nifty and Bank Nifty and how effective it is in terms of generating returns and smoothing your equity curve. Almost all smoothing filters and moving averages have lag because smoothing is done using past data.
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Zero Lag is a new concept in adaptive technical analysis. Here in Zero lag EMA we show you the effects of lag removal in a indicator and then how to use the filter in a very effective way. The picture shows the simple ZeroLag EMA strategy over the 15min Nifty Charts. The thick yellow line is nothing but the Zero lag EMA and the red line is the normal EMA.Since minimization of lag is crucial to the effectiveness of indicators,several authors have devised ways to make the EMA smoothing factor vary with volatility in price.
http://www.youtube.com/watch?v=A5lWR0PhG3c
The first relationship between the lag of an EMA and the length of a Simple Moving Average (SMA) is
alpha = 2/(Length+1)
We call the new filter EC (for Error Correcting) i.e Zero Lag EMA instead of EMA. So the equation for the EC filter is:
EC = alpha*(Price + gain*(Price–EC[1])) + (1-alpha)*EC[1];
The equation is simple, but its results are profound. If the gain is zero, the EC becomes just an EMA. If the gain is sufficiently large the error term causes EC to exactly track the price for all practical purposes. That is, there is virtually no lag and virtually no smoothing. Therefore, we seek a value of gain that is a happy medium between tracing out the price and tracing out the EMA. We do this by limiting the maximum amount of allowable gain. If the difference between the price and the previous value of EC is small we do not want a large value of gain. Further, the previous value of EC can be either greater than or less than the current price. Therefore, to properly apply the error correction the gain must swing both positive and negative.
Download ZERO EMA Amibroker AFL Code
ZL EMA Backtesting results for 4 Years of Nifty and Bank Nifty Spot
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