Momentum Based Investment Strategies

Presented by Bruce Vanstonefor the Australian Shareholders Association

This material is presented for educational purposes only.

I am not a financial advisor, and this material is not advice.

In many cases, the material represents research findings.

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Disclaimer

Who am I?◦ Dr. Bruce Vanstone (Bond University)◦ Research Discipline

Computational Finance Algorithmic Trading

◦ Trader and Academic◦ Consultant to Fund Managers

Example: Porter Capital Management

What is this all about?◦ Momentum!

Overview

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What is it?◦ Momentum refers to stocks that have exhibited

past over-performance; it is a measure of that degree of over-performance

Is it credible?◦ Short answer: Yes◦ Long answer: …this presentation!

Why should I care?◦ It has very low correlation to how you probably

already invest

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Momentum

Academics focus on the EMH, and the RWT◦ Random Walk Theory

Theory of ‘independence’

◦ Efficient Markets Hypothesis Theory of ‘information’

Anything which doesn’t fit is labelled an ‘anomaly’ in finance

Momentum is classified as an anomaly

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Momentum: The ‘Short’ Answer!

‘discovered’ by DeBondt & Thaler (1985) Since then, it is one of the most widely

researched topics in academic finance◦ Rouwenhorst: demonstrated momentums

outperformance in every European market (80-95)◦ Griffin: demonstrated outperformance in over 40

countries ‘Globally, momentum profits are large and

statistically reliable in periods of both negative & positive economic growth’

Demonstrated in forex, commodities and even real estate markets

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Momentum: The ‘Short’ Answer!

Much of the remaining information in this presentation is based on simulations using reconstructed data concerning stocks, delistings, index memberships etc

We can use simulations to learn a lot about the markets we trade and invest in

For this presentation, I have focused on the ASX200

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Momentum: The ‘Long’ Answer !

Basic principle: stocks exhibiting out-performance tend to continue to do so for a while

How do we measure out-performance?◦ By ranking the degree of change over a pre-

defined period Example metric: % increase over 12 months

That's the metric I used in the rest of these slides, but the whole idea is actually very robust to choice of metric

Funds use different periods, and sometimes, things like change in growth rate etc instead of change in price

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Momentum: the basics

Basic momentum testing is normally built on the j/s/k methodology◦ j = past ranking

period◦ s = skip period

(if used)◦ k = future

holding period

Momentum: conceptually

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Basic assumptions of momentum are:◦ Stocks going up strongly are likely to continue for a

measurable time in the future◦ Stocks going down strongly are likely to continue

for a measurable time in the future

OK, lets stop right there!

For momentum to be valid, these ‘assumptions’ must be true◦ ... and interestingly enough, we can test them

easily!

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Underlying assumptions

Great!.... because we can test this with any credible definition of stocks going up or down…

For this example, I have used these rules:

◦ Stocks going up: price higher than the last 200 days◦ Stocks going down: price lower than the last 200

days

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Up/Down assumption

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Example: (‘Up’)

Example: (‘downs’)

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Create two tests:

UP : buy all stocks with price higher than for the last 200 days, sell after 1 year

DOWN: buy all stocks with price lower than for the last 200 days, sell after 1 year

For momentum assumption to be valid, these should be quite different outcomes

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Up/Down simulation

01/01/2000 -> 31/12/2014 Buy $5,000 worth of stock every time the

buy condition is true◦ Standard transaction costs, membership etc

included

What can we learn about our market?

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Up/Down Outcome

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Outcome – Up versus Down

‘UP’ rules

‘DOWN’ rules

(previously, slide 10)

Basic assumptions of momentum are ◦ Stocks going up strongly are likely to continue for

a measurable time in the future◦ Stocks going down strongly are likely to continue

for a measurable time in the future

Seems like the assumptions could be viable

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Back to momentum

Next ‘assumption’ is the stronger the stock is going up, the better◦ Why? Because momentum is about buying the

top group of stocks travelling in the required direction

◦ Example: top 20

Best way to do this is to go back to the j/s/k description

Example: 12/0/12

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Momentum

For these kinds of tests, we observe the difference between the top (example) 20 and the market (using an index)

Again, not too difficult to do using simulations

So…. What can we learn?◦ $1m, standard txn costs, membership etc

included

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12/1/12

Momentum versus market

MOM = rank stocks by last 12 months price change, skip, rotate, hold top 20◦ i.e. 12/1/12

MKT = buy XAORD at start of period, sell at end

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Momentum/Market simulations

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Outcome – MOM versus MKT

‘MOM’

‘MKT’

These simulations appear to support the two basic assumptions required, namely:

Assumption 1◦ Stocks going up strongly are likely to continue for

a measurable time in the future◦ Stocks going down strongly are likely to continue

for a measurable time in the future

Assumption 2◦ the stronger the stock is going up, the better

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Momentum Simulations

These simulation results are in line with previous research findings by other academics in different markets◦ Do a little searching on Google or Google Scholar!

These simulation results are also quite robust to the different “j/s/k” settings

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Momentum Simulations

Think of momentum as a general ‘principle’ rather than a measure

Then it makes sense to think about momentum on things besides price, like:◦ Earnings◦ Fundamental ratios

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Further thoughts on Momentum

Some Real Results – ASX200

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Some Real Results – S&P500

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30-Sep-13

29-Nov-13

31-Dec-13

31-Jan-14

28-Feb-14

31-Mar-14

30-Apr-14

31-May-

14

30-Jun-14

31-Jul-14

31-Aug-14

30-Sep-14

31-Oct-14

30-Nov-14

31-Dec-14

31-Jan-15

80000

90000

100000

110000

120000

130000

140000

S&P500 Prime Momentum Unaudited

$ 127,784

Thank you for your time!

If you are interested, you can follow my real results at www.vanstonetrading.com

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Questions