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Manager research - our approach

The Bestinvest MRI has been designed to separate the monkeys from the geniuses.

Fund managers change jobs, on average, every four years - so the past performance records of most funds can be disregarded as a reliable indicator of the future. The solution to this problem is to track the performance of the manager, NOT the fund.

Manager Statistical Research Methodology

Our statistical analysis comprises a series of steps:

  • 1 Career record

    We try to look at the record of a manager, for the entire duration of their career, in each sector (we split out different sectors because some benchmarks can be much easier to beat than others). If a manager runs more than one fund in a sector for any period of time, the results of those funds for that period are averaged.

  • 2 Relative performance

    We look at the returns on a monthly basis, both in absolute terms and, more importantly, relative to a benchmark index.

  • 3 Cumulative performance

    We then carry out a number of calculations on this dataset so that we can look at performance in each of the past five years and cumulatively over the past 3 and 5 years. In cases where the manager has taken gardening leave, or a sabbatical, the periods will not be continuous, in which case the records for the past 3 years and 5 years may be incomplete.

  • 4 Risk control

    As part of our process to try and understand the style of the manager we calculate the Maximum Loss (in both absolute and relative terms) over the manager's career. Every manager goes through periods of underperformance, but some operate with strict risk controls to limit the downside. Statistically, it is to be expected that managers with long track records will also have incurred larger losses, although this is not inevitable.

  • 5 Statistical analysis

    Then, we look at the probability that these results could have been generated simply by chance. Remember that if you allowed 1,000 monkeys to run funds on a random basis you would expect 31 of them to beat the Index every year for five years (assuming nil charges), at which point they would be accorded the status of investment geniuses by many.

How we calculate the MRI

Our Bestinvest MRI (Manager Record Index) has been designed to try to separate the monkeys from the geniuses.

First, we add back to the performance figures the monthly running costs of the funds, so that we can assess the performance on a pre-charges basis. We then calculate the Information Ratio:

((Relative Performance + Charges) / Standard deviation of returns)

The Bestinvest MRI is then derived from plotting the Information Ratio on a normal distribution curve (on the assumption that the returns are, in statistical terms, normally distributed) and taking this probability away from 100.

Values for the Bestinvest MRI over 99% indicate very strongly that the manager is adding value and over 95% is also a strong indicator. Low values (under 10%) indicate that it is highly likely the manager is destroying value (i.e. they would probably do better by picking stocks out of a hat!). Any manager with a positive average monthly return (after adding back the running costs) will have an MRI of greater than 50%.

Funds which operate with a strong style bias (e.g. most Equity Income funds) can go through sustained periods of under and over performance which does not directly reflect the input of the manager. We suggest that a track record of at least five years should generally be used to demonstrate how a manager has fared in different market conditions.

We believe that data for shorter periods than 30 months is unlikely to be statistically significant and so we do not calculate the Bestinvest MRI in these cases.

Joint Managers and Team Track Records

Dealing with joint managers or management teams with a number of staff is problematic. In the case of joint managers we could either attribute the fund's record to each of the managers individually or treat them as a unit. In cases where the managers are taking joint decisions on stock selection (rather than individually running parts of the portfolio) we take the latter approach. Where teams are responsible for managing funds we will usually treat the team as one unit but identify the key decision makers within that team and what their roles are. As a result the departure of one member of a team or management pair can be significant for our rating of a fund.

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