‘Point-to-Point returns are the wrong measure for fund performance, and yet they’re endemic,’ says Insync Strategy Head, Grant Pearson. ‘They undeservedly grab pole position across platform and media reporting, researcher tables and software, and even on websites and slide decks.’
Point-to-Point returns measure performance from a specific set date point, for a specific duration, for example, 1,3, 5,7 or even 10 years.
‘The trouble with Point-to-Point returns is that they are only valid if an investor is investing on a specific month for the exact specified duration. Point-to-Point returns mislead advisers and clients because they infer these returns are typical, when often they are not.’
Mr Pearson says it is common practice to then review results ending in calendar or financial years.
‘While this sounds right, these singular dates are not necessarily any more or less relevant than any other start/end month. Few investors buy funds on New Year’s Eve or on 1 July, and sell exactly 1,3,5, 7, or 10 years later.’
By way of example, he says an investment might drop by double digits in January, do reasonably well for the next 10 months, and have a lacklustre return for December.
'The Point-to-Point result might thus infer the investment ‘performed poorly’. But if the Point-to-Point period started 1 February, and ended the following 31 January, it could have told a much better story,’ he says.
‘The truth is it may or may not be a good investment, but you can’t know unless you examine each single one-year period starting every month over a sufficiently comparable time period.’
Mr Pearson says Point-to-Point returns are dangerous used in isolation, or as the primary return measure, no matter the time frame. Using them for new funds that have only a few years under their belt are perhaps an exception.
‘We firmly believe Point-to-Point returns should only ever be used in ‘behind-the-scenes’ ways such as simple cross checking for extreme under/over performance, to check fund behaviour at certain points in the cycle or during a specific event – and then, only for shorter-term time frames and rarely for unsophisticated investors.’
According to Insync, the better way to measure returns is to examine them via ‘Rolling Returns’. This method calculates performance based on all months, not just January or July.
‘They more fully account for the fact that investors typically do not invest only in January or July but instead are investing and redeeming across all months. You can then calculate the average rolling returns over the time period in question.’
While not perfect, Rolling Returns offer a far more robust and more complete return assessment for advisers and their clients.
‘They are a more effective measure because they provide a more holistic picture of an investment’s returns,’ he says.
Crucially, the Rolling Return method allows an investor to evaluate the consistency of a fund’s performance over time, including the impact of ups and downs of events and market cycles, which is a more revealing test of a manager’s skill.
It also removes any possible ‘skewing’ of a measurement result. ‘Rolling returns provide a particularly robust analytical tool for evaluating managers during volatile periods. With rolling returns, you can’t simply shift the performance date range to paint a rosier picture,’ he says.
It’s also important to match the rolling period used to the time period the manager and asset class is focused upon. For Bonds it may be better to focus more upon 2 and 3 year rolling periods, for equities 5 and 7 years.
‘We also find it surprising and frustrating that the industry appears to pay scant attention to the written aims of each fund and how much trading they do, as this influences the buy/sell/hold calls managers make,’ Mr Pearson says.
Point-to Point measures often misrepresent the result. ‘Two managers can hold the same stock but with differing time frames in mind. This fact is lost in most analysis,’ he says. ‘Our industry owes it to advisers and their clients to get it right, so that they can make informed and appropriate investment decisions using better measurements.’
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