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.