Presented by Bruce Vanstone for 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. Bruce Vanstone2

 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! 3Bruce Vanstone

 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 Bruce Vanstone4

 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 Bruce Vanstone5

 ‘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 Bruce Vanstone6

 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 Bruce Vanstone7

 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 Bruce Vanstone8

 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 Bruce Vanstone9

 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! Bruce Vanstone10

 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 Bruce Vanstone11

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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 Bruce Vanstone14

 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? Bruce Vanstone15

Bruce Vanstone16 ‘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 Bruce Vanstone17

 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 Bruce Vanstone18

 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 Bruce Vanstone19

 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 Bruce Vanstone20

Bruce Vanstone21 ‘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 Bruce Vanstone22

 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 Bruce Vanstone23

 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 Bruce Vanstone24

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 Thank you for your time!  If you are interested, you can follow my real results at Bruce Vanstone27