McGinley MACD

This week we continue to look at the McGinley Dynamic.  Obviously the most common and immediate thing one would think of doing with a moving average is to look at how to trade with it. The easiest thing we can do is to create a MACD using the McGinley Dynamic. To make comparison easier we will create a MACD using two McGinley average averages with the Dynamic tracking factors similar to the conventional MACD which is 12 and 26.  The McGinley MACD clearly much smoother and is less prone to whipsaws. It keeps one in trade for long catching big trends nicely. Of course there is always a price to pay for this. The McGinley MACD is lagging by a few bars compared to the conventional MACD. Well, it may be better than being whipsawed and losing money. Also the peak draw down because of the lag is much better than being thrown out of trade much earlier in most cases. I did not run a back test on the McGinley MACD. If somebody does care to do the back test it please let us know the results.  I am posting it here as it looks worth trying out. AFL posted here for anyone who cares to try it out.

Download the AFL here

McGinley Dynamic

My latest experiment was on the Mcginley dynamic. The claim that it is one of the most reliable indicators attracted my attention.  The McGinley Dynamic technical  indicator aims to overcome the lag of the traditional simple and exponential moving averages, the indicator automatically adjusting itself relative to the speed of the market. The McGinley Dynamic looks like a moving average line yet it is supposed to be a smoothing mechanism for prices that turns out to track far better than any moving average. It is also supposed to minimizes price separation, price whipsaws and hugs prices much more closely. And it does this automatically as there is a factor of the formula. Because of the calculation, the Dynamic Line speeds up in down markets as it follows prices yet moves more slowly in up markets. One wants to be quick to sell in a down market, yet ride an up market as long as possible.

The Formula

MD = MD_-1 + (Price – MD_-1) / (N * (Price / MD_-1 ) ⁴)

MD – McGinley Dynamic

N   -  Dynamic Tracking factor

Here the difference between the Dynamic and the price is divided by N times the ratio of the two to the 4th power. The numerator difference gives us a sign, up or down, and the denominator keeps us percentage-wise within bounds defined by N. The 4th power gives the calculation an adjustment factor which increases more sharply the greater the difference between the Dynamic and the current data. 

The McGinley Dynamic (MD) is supposed to avoid whipsaws because the Dynamic Line automatically follows prices in any market fast or slow, it is supposed be like a steering mechanism that stays aligned to prices when markets speed up or slows down.

Personally I do not find this indicator very useful. Maybe it is better as a tool to gauge the market instead of a regular indicator. Of course the MD performs better compared to the regular EMS in terms of closely tracking the stock and in terms of whipsaws. I am enclosing a chart with the MD (Yellow line) and to compare I have plotted a 20 EMA (Red Line).

For those interested to experiment I am enclosing the afl. Please let me know if you find any interesting aspect of the MD.

Download the AFL……

K-Bars Variations in charting Bars...

Also under consideration is a dream is a project to help and educate retail investors so that they do not easily lose their hard earned money in the market. The idea is to equip the small trader with the technical tools and education to save them from the sharks of the stock market and the snake oil vendors. The project has been given a pet name “Marar Foundation”.  Well, the seeds have been sown and we will wait for project to sprout and grow in to healthy and successful organization. I will be sharing more information on the same as the time goes.

Today I will be sharing some of the charting tricks I use. As a VSA enthusiast I more interested in how much easily the Smart Money would move the stocks or in other words what is the effort and the corresponding result. So I am more interested in the where the current stock price ended compared to the last bar close. In a EOD perspective how is today’s close compared to yesterday’s close. So I have special bars which have the current open adjusted to previous bars close. As a result we have a smoother chart without the Gap ups and Gap downs. I call it the K-Bars charts

The other chart I use is more interesting and the one with bars that reflect the buying and selling pressure. This chart helps us the easily understand the underlying market sentiment 

in terms of supply and demand. Let us look at it with an example.

In the Above chart the bars are coloured red and green. The green part represents the buying pressure / demand and the red part represent the selling pressure / supply. In the up move and down move the demand and supply is clearly indicated by the corresponding colour  However the utility of these bars are can be appreciated during the turning points. Look at the green box. After the down trend the demand /buying coming is very visible by dominating green colour  So the impending up move was very evident. In the same way in the red box the selling/supply was dominant and was clearly visible and the down is easily forecast.

I am sharing the code piece for Amibroker for those interested to experiment. You can upend the same to any other strategy code. The same can be down loaded here. Download the AFL code.

RSI with Dynamic levels

I am posting after a gap. Got hold of some original Wyckoff stuff and has been spending some time on it. More about it in a later post. Today I am presenting a Regular Classical Indicator RSI with a variation, a RSI with dynamic levels. No I am not talking about the RSI with Bollinger bands around it.

In the Stocks & Commodities V15:7 Leo Zamansky and David Stendahl talked about dynamic zones. They said that oscillator driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Typically the set of buy and sell zones for a bull market will be substantially different zones for a bear market. We need to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system. The idea of their system was to create a distribution of the signals in the given look back period. Then we have to find the value which is equal to the desired probability.

First of all the assumption is the distribution is normal distribution is a little far fetched actually. On that assumption we need to do the laborious calculation of the making the distribution and calculating the probability. But I would like to keep things simple. Trading is art and not complicated science. Precise calculation will not immensely improve your trading system.  In order to simplify the matters we can just assume uniform distribution and calculate the probability accordingly. I knew people will find it difficult to accept this. However even this simplification will provide a adequately dynamic zones.  Here I am presenting the conventional RSI with Dynamic Levels. Also in order not to confuse with widely available Dynamic Zone indicator with Bollinger bands I will call this indicator RSI with Dynamic Levels.

Download the afl from here 

Volume Wave

Of late I have not been able to find much time for the experiments. My latest interest has been on the Weis Volume waves. Maybe it is a commercial not much material is available. I tried Davis weis’s book “Trades about to Happen”. Frankly not very impressed with the book.  In the chapter on tape reading he does talk about the volume waves.  Somehow the explanation is very much lacking. Either he is not good teacher or he prefers not to explain as he is selling the stuff. Frankly I have not been able to find much use for the volume wave and the reasons are as follows

1. The waves is based on based on percentage or pips which he calls as waves size or reversal and it is in terms of pips. If the reversal percentage is changed then it could present a different picture. What is the ideal wave size? The wave size could change from instrument to instrument. How do you arrive at the ideal wave size?
2.      I fail to see discernible pattern on the waves. I am still experimenting.
3.      I do not know how the commercial program works but I feel that the concept calls for use of the zig-zag like functions to work out the waves.  The zig-zag function obviously looks to the future and this could lend the effort unreliable.

I have implemented the Volume wave in Amibroker. Please share your ideas about the Volume waves as I continue to experiment with it.

Sharing the AFL to you to experiment …..

The Volume Wave AFL...

Effort Index AFL

Finally here it is ... the Effort Index AFL...

The afl provides many options which are selectable from the Parameter window.
First option is to plot either the Raw Effort Index or the the Effort Index.

The Raw effort index provides the effort and the result in the same chart. The Result is plotted above the zero line and the Effort is plotted below the zero line. This makes comparison of the Effort and the corresponding Result on a Bar by Bar basis.

The Effort index is the ratio of the Result to Effort which in effort the Result per unit effort..

Also there is an Option for calculating the effort index either the Bar to Bar  or the Spread..

Bar To Bar  Calculation

Spread Calculation

Download the AFL...

Video On "Effort Index"

My latest video on the latest Indicator "Effort Index"

Afl will be available soon.

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

Adaptive Indicators - 2 . Adaptive Stochastics

Last week we looked at an Adaptive CCI. Now let us look at extending our experiments in creating a adaptive stochastic. As you are aware the stochastic indicator calculates the difference between the current close and the lowest value in a range as a ratio of  the entire range. This ratio is converted to a percentage and then a small smoothing is applied.

%K = (Current Close - Lowest Low)/(Highest High - Lowest Low) * 100

The Lowest low and Highest High is calculated over a specified look back period. Here we will calculate these values on the Dominant cycle (DC) period. The  DC is again calculated using the Hilbert transform of John Ehler.  The DC period is a varying parameter depending on the market condition and the Stochastic calculation is automatically adjusted as per the varying DC period making it adaptive to the Market condition.

You can see in the chart below that the adaptive Stochastic is giving less whipsaws and is smoother. The afl is also provided for you to experiment. Do share your finding and thoughts.

The KStochastic afl

ADAPTIVE INDICATORS - 1 - Adaptive CCI

All of us who use technical analysis are used to Indicators with fixed period of calculation. Also certain periods like 9 and 14 are taken for granted. These indicators do not taken into account the market conditions. Sometimes the market is volatile and not at other times. The velocity and acceleration also differs at different times. The indicators are oblivious to all these are mainly static. For example for CCI most people use 14 as the period whereas the inventor of this indicator Donald Lambert has suggest one third of cycle period.

I always have been a fan of John Ehlers. . Ehlers suggest that making the indicators adaptive to the cycle period of the concerned market would be a better solution. However he suggested using fraction of the cycle part in adaptive formulas. One of my first trials on this concept was an adaptive CCI which I called as KCCI. Of course many of you who had visited my web site (Now almost defunct) would be aware of this. I am enclosing a image of the adaptive CCI(KCCI) with the conventional CCI. You can notice that the whipsaws are lesser in the KCCI compared to the conventional one. You can experiment with it by optimizing the cycle part.

I will discuss more about other adaptive indicators in the coming posts. The afl is shared here

http://www.4shared.com/file/nH9Ss4-p/KCCI_-_Adaptive_CCI_-_V20_.html

SUPER ADX !!

Finally we have the so called Super ADX, I mean a clone. I could get the time to finalize it after a long time. It is based on the MT4 super ADX indicator. First of all I wish to clarify that it is not the Holy Grail.  Of course we should understand that if one had the Holy Grail Indicator we would never share it any body at whatever price. Since he is not able to make enough money with that system from the market he is trying to make money by selling it. The newbie trader should first understand that there are always many people with their eye on his purse. Everyone wants a few bucks from his purse. Some take it legally by selling something and some steal it.

Coming back to the Indicator, Let us see what this does.  The indicator first calculates the difference between the moving average of the average price and the moving average of the close.  This is taken as a measure of the strength of the trend. The change of directions of this strength measure is a reversal point. However the validity of the reversal point is made when the ADX (Another measure of trend strength) is either above a value of 35 (normally end of a trend) and below a value of 10 (for starting of a Trend). It also looks at reversal of the MACD. Finally   it also looks at multiple reversals within the last 15 bars. Different signals are generated for different type of reversal signals.  The different signals are as follows.

1.       A red bar would indicate that a big move is imminent.

2.       A white bar would indicate that it is the end of the big move and hence exit.

3.       A yellow bar or a violet bar would indicate a possibility of a reversal of the current trend.

4.       A magenta bar would indicate that multiple signals have occurred and possibility of a reversal is very strong.

Also it should be noted that the exit signals is not generated in all cases. Similarly the Big Move indication is also not generated every time. But whenever it happens it will be a good opportunity. Also reversal signals are not generated every time reversal is imminent.

The super ADX also uses a indicator which they call Money line. This line is used as the exit point though I did not find it correct. Normally a Linear weighted Moving average of period 40 should be good enough as a money line. 

So try out the indicator and provide your feedback. I only hope that unscrupulous elements don’t take this and commercialize this as they have down with other my other indicators.

The Super ADX Indicator

The Money Line

The ADX Afls...

I have been experimenting a little on the volume biased ADX which I had propose in my last post. I found that volume spikes could drastically upset the the indicators. SO i had to use a little smoothing to overcome this. That is the reason for not releasing the afl. Now  I am ready to release it for those who would like to experiment. I am also posting my earlier work, a Gaussian smoothed ADX called KADX which is more responsive ans smoother than the classical ADX. Please share your opinion about these indicators.

1. Volume Biased ADX

2. Gaussian Smoothed ADX - KADX

A Volume Biased ADX

I am returning to blogging after a long hiatus.  It is usual in life that we face intervals of disturbing events and confused priorities.   Now that the dust is settling down I am slowly picking up the threads and I am coming back to my passion, Technical Analysis.

I am  sharing some thoughts on the ADX indicator. ADX is one of the very popular indicators and widely used by technical analyst. Dr. Charles Schaap’s  book “ADXcellence” deals with different strategies of trading with ADX. Then there a commercial product called Super ADX which the sellers claim is a leading indicator though the ADX by itself is a lagging indicator. Also I do not know how much of it is based on real ADX other than they have an indicator called supporting ADX. Anyway soon I will release a clone of the so called Super ADX.  I also had released a Gaussian smoothed ADX called KADX which was more sensitive and smoother than the conventional ADX. ADX is a useful indicator to measure the strength of a trend. ADX by itself is a non directional Indicator and does not indicate if the trend is up or down. We use two other indicators called the +DI and -DI to reveal which trend direction. I will not go into further details as most of you, readers of this blog, will be familiar with the ADX indicator.

As many of you may be aware the importance I provide for the volume in my analysis. Any move of a stock which is not aided by volume will not last. Volume is the fuel for any trend. So naturally any trend strength indicator without consideration of the volume cannot provide the real picture. The ADX calculation totally ignores volume and purely based on the price movement.  Price action combined with volume would be definitely provided a more realistic picture. This thought has inspired to experiment with the ADX to include the volume aspect.  The basis for the ADX calculation are the difference between the High of a day and the High of the previous day and also the difference between the low of the day and low of the previous day. In other words it uses the momentum of the Highs and Low. This momentum is fuelled by volume. So we will add a volume factor to this momentum. To calculate the volume factor we take the ratio of the current volume and the average volume. We will bias the momentum of the Highs and Lows with this volume factor. The remaining of the calculation will be based on these biased values and the final ADX, +DI and –DI values will be biased by volume. The result of this is quite evident from the chart below. The resultant +DI and –DI are much more responsive to the volume and they clearly indicate which moves are volume driven and which are not.  The ADX also quickly increase in values when the volume increases indicating increased trend strength.