Camradata fund performance data

Methodology The CAMRADATA IQ’s quantitative rankings reflect seven statistical factors for each product. Each factor generates a statistic which is converted into a Percentile Rank. The ranking process is designed to give a 1 for the best score on a factor, 0 the worst, and 0.5 the median. Products which share the same value for a factor are assigned the same Percentile Rank. To order products in the rankings, a master score is calculated. This is a simple average across all 7 factors. The highest scoring products appear at the top of the table. For presentational purposes we apply a ‘unique sort’ to pick out only the best product for each manager.
  • Excess Return is a measure of overall added value. The underlying factor is the annualised excess return over the benchmark.
  • Information Ratio - this is a measure of efficiency. This indicates how risk is being transformed into return. The underlying factor is excess return divided by excess risk.
  • Hit Rate - a measure of consistency. The underlying factor is the percentage of times the manager beats the benchmark.
  • Wins – Losses - a measure of the bet structure which a manager is taking. The underlying factor is calculated using the relative returns, it is the average positive return minus the average negative return. Consultants use this to identify managers with a low frequency of winning but with a high payoff when a product beats the benchmark. Consultants want to see that wins are greater than losses, even if the wins are infrequent.
  • Drawdown Strength - a measure of downside management. This compares a product’s worst observed 12 month relative return against an expected ‘bad drawdown event’. A bad drawdown in this instance is statistically what could have happened under some basic ‘normal’ assumptions.
  • Hurst - a measure of the persistency of manager returns. The underlying factor is the Hurst coefficient, which lies between 0 and 1. A Hurst score of less than 0.5 indicates a product which, over longer periods, tends to experience an erosion of short term gains, “mean reversion”. A score of greater than 0.5 indicates persistency in outperformance, a tendency to keep pushing out from the benchmark, “mean aversion”. By contrast a random walk in returns against the benchmark has a persistency of 0.5. Consultants will want evidence of persistency in returns and to see a score greater than 0.5, but an unusual score of 0.9 and above is an indication that further investigation is required. For this reason a Hurst greater than 0.9 is penalised in the rankings.
  • Gaussian noise - a measure of confidence that a manager is doing more than just random stock picking. Consultants want to ensure that they are not being fooled by randomness and they are short listing only products that can demonstrate active management. The underlying factor is a goodness-of-fit test. The test compares product returns against a statisticians bell curve with a mean of zero. For example if the test gives 90% it indicates that you can be 90% sure this manager is different from random noise. By contrast a 0% score indicates that the manager has not done enough to differentiate themselves from noise. The higher the score the more attractive a product is to a consultant; most consultants will screen around 85%, but this depends on the universe.
The six plots shown in the report are intended to provide a visual interpretation of the riskiness and return of the fund selected in comparison with the peer group of funds that it sits within (the Universe). The six boxes can be split into two blocks. The first three boxes are based upon absolute figures and the last three are based upon relative figures. This means that the last three show how the funds within the Universe have performed in direct relation to the Benchmark (figures for the Benchmark are found at zero within these plots). Within each block The first plot represents the percentage return from all funds within the Universe over the three year period. The second plot shows the percentage of risk inherent within these funds over the same period. The third plot combines the elements of risk and return to show the amount of reward provided for every unit of risk taken on within the fund. This shows how efficiently the risk within the fund is being translated into returns. Each plot contains two icons: one for the Benchmark and another for the selected fund. These are intended to give a clear indication of where they sit against the performance of the rest of the Universe. Camradata

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