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Presented by Bruce Vanstone for the Australian Shareholders Association
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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
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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
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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 Bruce Vanstone4
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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
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‘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
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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
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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
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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
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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! Bruce Vanstone10
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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
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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
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Bruce Vanstone16 ‘UP’ rules ‘DOWN’ rules
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(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
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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
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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
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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
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Bruce Vanstone21 ‘MOM’ ‘MKT’
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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
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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
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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 www.vanstonetrading.comwww.vanstonetrading.com Bruce Vanstone27
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