Regularized Indicators - Part 2

Currently I am working on fine tuning my latest simple indicator the “Effort Index”. I am also planning a video just like the video on the buy and sell indicators. Making video is interesting and I realized that it is not very easy as just recording. To make a proper video one has to plan properly and prepare a lot in terms of a script and story board etc. Making the bits and editing them all together is quite interesting. And there are many interesting software available for each of these aspects. It has been a huge learning experience. Currently I am just doing the story board and it is going to take some time to complete and release the video and Indicator. Meanwhile we will continue with our experiments with regularization of indicators.

 The next indicator I took for Regularization was the RSI. The RRSI is much more responsive and leading compared to the conventional RSI. Since regularization tends to take values to extremes the chart a little more jagged than the conventional one. So we can apply a small filter to smooth the signal. I have applied a 5 bar Ehler Filer to keep the lag minimum.

Similarly a regularized stochastic Indicator is characteristically smoother and less proven to whipsaws.

Download the AFLs

Regularized RSI

Regularized Stochastic

VSA - Identifying weakness with Effort and Result..

I am writing something about VSA after a long time.  The last time I posted the buying and selling pressure indicator which is a good add on indicator for VSA. Now I am going to talk about indentifying hidden weakness in the bars.  Many times we see up bars closing near the top with good volumes.  Most would naturally assume there is strength in those bars as it is an up bar, closing in the top and has good volume, all traits of strength. However there could be hidden weakness in these bars. Obviously the question is why and how we identify these.

Let us take the nifty chart as example. In the chart I have plotted the chart in one pane, the volume in another. The third pane consists of a new indicator which I call as the Effort index.  This chart plots the effort (in effect volume) as bars below the middle line. The result is plotted above the middle line as bars.  Now let is look at the charts and focus on the three bars marked 1, 2 and 3.  In the Bar marked 1 we can see a wide spread “Effort to Move up Bar” with good volume. In the pane three we can see that the effort was high and the result was also equally high. In other words the effort produced the required result. Now look at the bars marked 2 and 3. These are up bars closing near the top and volume was high almost equal to the previous day’s volume. So it is natural to consider that there is strength in these bars as well. But when we look at the pane 3 we see that the effort was high but the result was poor.  So there is a mismatch between the effort and the corresponding result which indicates weakness. The reason could be that the smart money has been distributing without bothering for higher prices. So these two bars (marked 2 and 3) really indicates weakness rather than strength. As you can see the weakness manifested from the very next bar the market came down. So looking at the effort and the results can tell us more about the bars. This is helpful in bar to bar analysis.

I am planning to release the new indicator “Effort Index” soon. More about is soon.

Regularized Indicators

In the volume 21:7 of the TASC Chris Satchwell presented the concept of regularization in place of the conventional smoothing. The full article is available on the net for those who are interested. In the article Satchwell presents a regularized EMA. In conventional smoothing we have to deal with two things wiggle, which is the high frequency oscillations especially in short term smoothing and then the lag. We can reduce wiggle by increasing the smoothing period but we will much larger lag.  So it would be whipsaws or lag and often it is a compromise between the two.  Regularization has a factor “Lamda” by adjusting which we can control the wiggle. A Regularized EMA would be exactly the same when the lamda is set to zero. The calculation of Regularized EMA is as follows

             Rp + alpha*(close - Rp) + lambda*(Rp + (Rp-Rpp))

     REMA = ---------------------------------------------

                      1             +      lambda

alpha = N-day smoothing per EMA 
Rp = yesterday's REMA 
Rpp = day before yesterday's REMA 
Lambda is a factor controlling the amount of “regularization”.

However Satchwell makes it very clear that the regularized indicators may not be suitable for trading strategies with crossover. These are more useful for strategies based on gradient or slope.  Satchwell Says “Regularization has an advantage in that it enables the gradients of regularized quantities to form part of the trading logic. However, the position of a regularized indicator is dependent on prior curvature; unlike conventional and exponential moving averages, there is no guarantee it will never trespass beyond the maximum or minimum function values on which it is based. This implies that conventional averages may be better for standard trading logic involving crossovers or threshold penetrations Regularization removes wiggle and associated gradient oscillations, so to exploit it fully, the consequences of having less-oscillatory gradients must be appreciated. This may not be as easy as it sounds, since conventional averaging usually fails to provide sufficiently consistent gradients, leaving a legacy of common trading logic (crossovers, threshold penetrations, and so on) that for the most part ignore gradients. Our expectations on how to use indicators tend to get in the way of appreciating that many trading decisions can be reduced to whether a price gradient is positive or negative. That is what regularization can do quite well.”

The regularization opens vast oppurtunities for fine tuning the conventional indicators. So the first indicator we will look at a Regularized MACD. So we will use two regularized moving averages instead of conventional EMA. The Regularized MACD is quite similar to the KMACD introduced recently. It is less prone to whipsaws and catches the big trends very well. However there is always a lag in catching the turning points. The little delay in entry does ensure more probable profitable trades. Drawdown can be reduced by proper trail stops.

Download Afl for Regularized MACD - RMACD

KMACD - A variation of MACD to catch big trends

Weekend again and time for my usual post. This week I want to share a new variation of the popular MACD Indicator.

Last week we had a look at the adaptive MACD. The adaptive MACD was built on the difference of two adaptive moving averages. This time I tested with a variation of MAVD with the difference between a non adaptive moving average and adaptive moving average. One was a conventional EMA of period 14. The other was an adaptive moving average whose period is adapted to the dominant cycle. Just to differentiate we shall christen the new indicator as KMACD. During long trends the dominant cycle gets longer and the adaptive moving average period also gets longer making it much smoother however at the expense of lag. Because of this the KMACD catches the long term trends fully without the whipsaws which the conventional MACD is prone too. However there is always a price we have pay which is the lag. However with proper exit strategies one should be able to catch the big trends fully without the usual peak draw downs.

Download the AFL - KMACD V.1.0

Adaptive Indicators 4 - Adaptive MACD

It is weekend and time for my experiments…on Technical Analysis. I am still stuck on the topic of Adaptive indicator. Of course I have been doing a little bit of reading on my favourite subject Volume. The little time I get during the week days have been spent on the book “Investing with Volume Analysis” by Buff Dormeier.  Now I am working on how the VPCI can help in VSA studies.

More on VPCI later. Right now let me continue with the current topic Adaptive Indicator. I have been experimenting with making the simple moving average adaptive to the dominant cycle. This adaptive moving average was used for smoothing in the ADX calculation to make it adaptive which was explained in the last post.  The next obvious move was to create a MACD of the adaptive moving average. The MACD is basically the difference between two moving averages one short and another long. However in case of the moving average adapted to the dominant cycle the period itself is not fixed and is varying. So I calculated the adaptive MACD with two adaptive moving averages, one adaptive to the dominant cycle and the other adaptive to twice the dominant cycle.   As the basic behind the MACD is the difference of two moving averages we cannot find much difference between the conventional MACD (12, 26) and the adaptive MACD. However the adaptive MACD is less prone for less whipsaws and the catch the trends very well at the same time the catches the turning points in time. The Adaptive MACD is definite one notch better than the conventional MACD.

The Afl -  Adaptive MACD V.1.0

Adaptive Indicators 3 - ADX Adaptive

I am continuing with my experiments with adaptive Indicators. The possibilities are extensive and exciting. The next indicator I was looking was the ADX. It is one of my favourite indicators and I had done some work on it already like the Gaussian smoothed  ADX and a Volume biased ADX.

If we look at the the calculation of the ADX, there are two places where we can make it adaptive. First in the calculation of MDI and PDI we have the smoothing of the UP move and down moves. Then we have the average true range. SO we can make the Smoothing period adaptive tot he Dominant cycle period. Also the averaging of the True Range would be based on the Dominant cycle period. Finally the smoothing in the calculation of the ADX itself will be made adaptive to the Dominant cycle. The images are provide below. We can notice that though the Adaptive ADX does not drastically change the ADX it  is more pronounced and the moves are swifter and faster. The AFL is provided for those who are keen to experiment with this Indicator.

The AFL - KADX - Adaptive