Edition

IFTA JOURNAL
2017 EDITION
Constructing Optimal Momentum Systems —
Optimize or Diversify?
By King Tong Choo
King Tong Choo
kingtongchoo@hotmail.co.uk
Society of Technical Analysts
Dean House, Vernham Dean
Hampshire SP11 0JZ
+44 (0) 20 7125 0038
Abstract
This article aims to present empirical evidence on the
application of a simple momentum strategy based on moving
averages to major equity market indices. This is done through
adjusting moving averages, and evidence is presented on whether
the bulk of the return comes from the long or short trades and
finally, whether it is better to optimize the parameters selected
or to diversify over many different combinations of parameters.
The research that has been found suggests that both long and
short trades generate significant returns and also suggests some
value in optimizing the parameters used in a momentum strategy
based on the recent past.
Introduction
The Momentum Strategy
The core concept in technical analysis is moving averages,
and it dates back to the 18th century, founded by a mathematics
historian, Jeff Miller. During the mid/late 18th century, moving
averages became popular in the finance sector for making
the prices of markets comprehendible by creating a single
flowing line to indicate the direction of a stock. This then was
incorporated with momentum pioneered by Richard Driehaus
(who is recognized as the father of momentum investing) and
quotes that “far more money is made buying high and selling at
even higher prices.” This reinforces the idea momentum is based
off, that is, once a trend is established, it is more likely that it
will carry on in that direction than move against the trend.
Key Research Questions
Throughout the research, the study has revolved around
three prime questions:
1. What timeframe when using moving averages works best to
generate the most returns?
As moving averages are a large facet of the momentum
strategy, we should outline the most effective speed
(timeframe) to use. This would be done through testing
different moving averages on historical prices, varying
the fast and slow speeds, and then picking the speeds that
generate the most returns.
2. Is longing/shorting making the most returns/losses, and
therefore is it better to enter trade to only long/short or in
tandem?
It may be that there is a pattern of long-term trading
with the profits gained from shorting and longing and
thus, it is questionable whether the combination or the
separation of the two is better. For example, taking long
signals may generate most of the profit, whereas taking
short signals reduces the returns, and thus it is wise to
only take the long signals.
3. Is it better to diversify the moving averages or to optimize
the few moving averages?
Upon filtering out the highest return generating moving
averages, the final question is whether we should place it
into different portfolios or concentrate it into a couple.
By diversifying we are reducing the risk and reducing the
reward, vice versa for when we optimize.
Application
A prominent use of momentum investing is in CTA funds/
hedge funds. About two-thirds of CTAs use momentum to
dictate whether they buy or sell. Namely, BarclayHedge said
that systematic trading (also momentum investing) is the most
commonly employed strategy, representing $269.33 billion in
AUM. As a concept, it is deemed as a reliable method to signal
and predict future trends; however, in practice, other indicators
are used in tandem with momentum.
Literature Review
Momentum as a concept has been appreciated since the 1990s
and has been utilized as a primary method for profits in many
funds, as highlighted in the application section. Developing the
strategy has occurred throughout the past decades, whereby
researchers have employed momentum in different situations
and in different manners to examine the best conditions to
apply momenºtum. The majority of the results are reassuring to
suggest that momentum is a method of return generation.
Jegadeesh and Titman (1993) were one of the first to explore
the effectiveness of momentum and to document it in their
Returns to Buying Winners and Selling Losers—Implications for
Stock Market Efficiency. The study reinforces that buying recent
winners and selling recent losers is rather an effective strategy.
The results collated depict that abnormal returns are realized
when a six-month timeframe is used to dictate whether to hold
or to sell for the next six months. This represented an average
of 12.01% of returns per annum. However, the following two
years reveals that the returns dissipate and reminds us that
momentum strategies that focus on recent winners and losers
make money over short horizons of 3 to 12 months.
Leading on from Jegadeesh and Titman, several studies
were conducted to explore momentum across foreign stocks
(Rouwenhorst, 1998), across industries (Moskowitz and
Grinblatt, 1999); across emerging markets (Rouwenhorst, 1999);
across countries (Liu et al., 1999; Griffin et al., 2003); across asset
classes (Okunev and White, 2003); and across equity styles (Chen
and De Bondt, 2004). The studies conducted over the decade
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