Alpha is a measure of a fund’s over- or under-performance by comparison to its benchmark. It represents the return of the fund when the benchmark is assumed to have a return of zero, and thus indicates the extra value that the manager’s activities have contributed: if the Alpha is 5, the fund has outperformed its benchmark by 5% and the greater the Alpha, the greater the out performance.
A further aspect of Alpha emerges when it is taken in conjunction with Beta. Assuming that a strong R-Squared correlation exists, the Beta will show how volatile the fund is compared to its benchmark, and thus indicate how much extra risk the manager has taken on in order to get that high-Alpha performance. Negative Alpha in conjunction with 1+ Beta is an indication of poor performance: managers are subjecting funds to volatility that is higher than the benchmark, while achieving returns that are lower than the benchmark attained. So, if Alpha indicates better/worse performance compared with the index, Beta shows higher/lower risk. FE gives the choice of both Alpha and Annualised Alpha.
The rate of return of your investment on an annual basis.
Beta is a statistical estimate of a fund’s volatility by comparison to that of its benchmark, i.e. how sensitive the fund is to movements in the section of the market that comprises the benchmark. A fund with a Beta close to 1 means that the fund will move generally in line with the benchmark. Higher than 1 and the fund is more volatile than the benchmark, so that with a Beta of 1.5, say, the fund will be expected to rise or fall 1.5 points for every 1 point of benchmark movement.
If this Beta is an advantage in a rising market – a 15% gain for every 10% rise in the benchmark – obviously the converse is the case when falls are expected. This is when managers will look for Betas below 1, so that in a down market the fund will not perform as badly as its benchmark.
It’s important to stress that Beta is just an estimate: however, the stronger the R-Squared correlation between fund and benchmark, the more reliable this estimate becomes.
FE Crown Ratings
Outline of methodology
The FE crown ratings are a quant-based ratings system designed to highlight funds that have had superior consistent performance in relation to risk, relative to their peer groups. Peer groups are deemed to be the sectors as defined by the IMA and ABI.
2. The Crowns
All rated funds get a crown rating, one crown being the lowest rating, and five crown being the highest. No crown means the fund has not been rated.
3. Non rated funds
Funds are not rated for the following reasons
a) the fund is less than 3 years old
b) the sector is not meaningful for comparison purposes - e.g. the Specialist or Personal Pensions sectors
c) the sector has had too few members over 3 years to be significant
4. The constituents of the rating
The rating is made up of three constituents
a) Alpha relative to the sector, measured over 3 years but with a higher weighting given to the more recent rather than the more distant past
b) Volatility, measured over 3 years but with a higher weighting given to the more recent rather than the more distant past
c) Consistency, based on a fund's performance ranking within its sector in each quarter of the last 3 years. Each quarter is weighted equally.
5. Weighting the constituents
In most cases, each constituent carries equal weight within the overall rating, except in the following cases
a) Cash and Gilts - here the volatility constituent is excluded altogether, since in these areas, volatility is extremely low, and with very little difference between funds
b) Other bonds - here volatility is given half the weight of the other 2 constituents
6. Combining the constituents
For each sector, the best and worst raw scoring fund for each constituent is assigned a value of 100 and 0 respectively, and all intervening raw scores for that constituent are proportionately rescaled into this range. The rescaled scores for each fund's 3 constituents are then added to form an overall score (subject to the weighting constraints in section 5 above)
7. Allocating the crowns
Within each sector, the top 10% of funds (in terms of overall score) are awarded 5 crowns. The next 15% are awarded 4 crowns and the next 25% are awarded 3 crowns, tand he next 25% are awarded 2 crowns,with the bottom 25% getting 1 crown.
Gross Return (GTR) performance is calculated on a gross basis as opposed to total return which is calculated on a net basis.
Historic VAR (Value at Risk)
Historic Value at Risk is a technique used to estimate the probability of portfolio losses based on the statistical analysis of historical price trends and volatilities. VAR is able to measure risk while it happens and is an important consideration when firms make trading or hedging decisions
This involves running the current portfolio across a set of historical price changes to yield a distribution of changes in portfolio value, and computing a percentile (the VAR).
In the custom report tool you have numerous options that you can select in order to obtain a VAR value that suits you. The first thing that you need to select is your confidence level (90%, 95% or 99%). Then you need to select your period at risk (daily, weekly or monthly).
To view data items in your chosen report format, first retrieve or add items to your active list. Select ‘Run Table’ in the Custom Report section, where you can choose the report layout and the data view. Click the Go button to view your custom report.
So called because it assesses the degree to which a manager uses skill and knowledge to enhance returns, this is a versatile and useful risk-adjusted measure of actively-managed fund performance. It is calculated by deducting the returns of the fund's benchmark from the fund's overall returns, then dividing the result by its Tracking Error (which is a measure of the volatility of those excess returns). In this way, we arrive at the value, per unit of extra risk assumed, that the managers decisions have added to what the market would have delivered anyway.
The higher the Information Ratio the better. It is generally considered that a figure of 0.5 reflects a good performance, 0.75 very good, and 1.00 outstanding. This is particularly useful when comparing a group of funds with similar management styles and asset allocation policies. If two funds have near-identical Alphas, the higher Information Ratio identifies the manager who has been more skilful in betting on stock-picks that deviated from the benchmark or index, while the lower denotes gains that have more to do with market movements than active management. However, this comes both with a caveat, and a means of using it creatively. As ever, the R-squared correlation between the fund and its benchmark must be strong if any discrete reliance is to be placed upon the Information Ratio. Its versatility, though, comes from the point that added value does not necessarily mean value added to the fund's own benchmark. Analysts can decide which benchmark or index they wish the fund to outperform, and run the statistics accordingly.
This is a risk-adjusted measure used to gauge the extent to which a manager has added value to the returns that could have been expected from a benchmark portfolio, while taking into account the fund's sensitivity to that benchmark.
The calculation runs like this: take the benchmark’s average return in excess of a notional risk-free rate (the rate that could have been earned from ‘safe’ investments like Gilts, or cash equivalents); then adjust that benchmark return by multiplying it by the fund’s Beta – this adjustment compensates for the fund’s sensitivity, or lack of, to movements in the market. The result is the Expected Rate: what could be expected from the fund, in that market, and with that degree of sensitivity to the market, with no active intervention from the Manager. Now take the fund’s return over the risk-free rate, and subtract the Expected Rate – this is Jensen.
So this is a test of whether a fund has achieved a better performance than its Beta would suggest: a positive Jensen Alpha indicates an active management style with superior stock-picking ability; a negative figure is produced if returns are falling short of the adjusted benchmark return. It can be useful to investors seeking funds with low sensitivity to the market, e.g. to minimise downward movements in Bear conditions. If two funds have similar lower Betas, then the one with the better positive Jensen's Alpha is making superior returns for the same reduced level of downside risk.
Finally, since Jensen’s Alpha is calculated by reference to a fund’s Beta, a strong R-squared correlation between the fund and its benchmark is important if the measure is to have any significance.
Represents the best possible investment period.
Represents the worst possible investment period.
Indicates number of negative monthly returns.
Indicates number of positive monthly returns.
Price Return shows capital return of the instrument i.e. with no income reinvested.
The R-Squared measure is an indication of how closely correlated a fund is to an index or a benchmark. It can be treated as a percentage, showing what proportion of a fund’s movements can be attributed to those of the benchmark. Values for R-Squared range between 0 and 1, with 0 indicating no correlation at all, and 1, rarely, showing a perfect match. Values upwards of 0.7 suggest that the fund’s behaviour is increasingly closely linked to its benchmark, whereas the relevance diminishes as R-Squared descends towards 0.5, and starts to disappear altogether below that.
R-Squared is a key ratio, in that other measures of a fund’s performance – such as Alpha and Beta - will have been calculated by reference to its benchmark. The weaker the R-Squared correlation, the more unsuitable the benchmark is, and the more unreliable these measures will be in assessing the fund.
Statistics showing the proportionate out performance (or underperformance) of a fund relative to its Benchmark.
This is a commonly-used measure which calculates the level of a fund’s return over and above the return of a notional risk-free investment, such as cash or Government bonds. The difference in returns is then divided by the fund’s standard deviation – its volatility, or risk measurement. The resulting ratio is an indication of the amount of excess return generated per unit of risk.
Sharpe is useful, when comparing similar portfolios or instruments. There is no absolute definition of a ‘good’ or ‘bad’ Sharpe ratio, beyond the thought that a fund with a negative Sharpe would have been better off investing in risk-free government securities. But clearly the higher the Sharpe ratio the better: as the ratio increases, so does the risk-adjusted performance. In effect, when analysing similar investments, the one with the highest Sharpe has achieved more return while taking on no more risk than its fellows – or, conversely, has achieved a similar return with less risk.
TER (Total Expense Ratio)
TER (Total Expense Ratio) is a measure of the total costs associated with managing and operating an investment fund such as a mutual fund. These costs consist primarily of management fees and additional expenses such as trading fees and legal fees as well as any other operational expenses. The total cost of the fund is divided by the fund's total assets to arrive at a percentage amount, which represents the TER:
|Total Expense Ratio =
||Total Fund Costs
Total Fund Assets
The size of the TER is important to investors, as the costs come out of the fund, affecting investors' returns.
Total Return shows the total return of the instrument with all income reinvested and assuming income is taxed at basic rates of income tax.
This statistic measures the standard deviation of a fund’s excess returns over the returns of an index or benchmark portfolio. As such, it can be an indication of ‘riskiness’ in the manager’s investment style. A Tracking Error below 2 suggests a passive approach, with a close fit between the fund and its benchmark. At 3 and above the correlation is progressively looser: the manager will be deploying a more active investment style, and taking bigger positions away from the benchmark’s composition.
While zero Tracking Error would indicate a fund that was a perfect replication of its benchmark portfolio, this is hardly likely to be encountered in reality. The fund will not be fully invested at all times in its benchmark components, since an element of liquidity will need to be retained for redemptions, and the assumed reinvestment of dividends will not always be possible. Transaction costs dilute returns, and proportionately more so in smaller funds. Issues of timing and availability mean that changes in the benchmark’s constituents cannot be instantaneously mirrored in the fund’s portfolio. These factors will all produce greater Tracking Error – and be reflected in the Beta and R-squared ratios. But ultimately, of course, this is actually only an ‘error’ if the investment strategy goes unrewarded by out performance of the benchmark.
This is another risk-adjusted performance measure, similar in calculation and application to the Sharpe Ratio. The difference is that while Sharpe weighs a fund’s returns against total risk (standard deviation, or volatility), Treynor looks at excess return for each unit of systemic risk (the volatility, inherent in the market that cannot be diversified). The Treynor calculation, then, takes the fund’s excess return over a notional risk-free rate (what would be earned from, say, cash on deposit, or Government bonds), then divides it by the fund’s Beta. A Treynor Ratio greater than 1 shows that the fund has produced more units of return than of risk. So, in basing on market risk alone, the ratio assumes that non-systemic risk is capable of being eliminated by diversification across a wide range of investments, and measures whether the systemic risk has been rewarded.
Also known as the Volatility to Reward ratio, Treynor is useful in comparing funds that invest in similar market sectors and achieve similar returns. For example, when assessing a range of UK Equity funds, it is the one with the highest Treynor Ratio that is taking on the least market risk to achieve its level of performance. Also, since it factors out the manager’s ability from movements in the fund’s sector, Treynor may be used to compare fund performances adjusted for systemic risks in different market sectors – because, although intuitively the ratio should be higher for bond funds than for those investing entirely in equities, this is not necessarily true in every case. While not perfect, and not to be taken in isolation, the Treynor Ratio can be a pointer to the optimum risk- and sector-adjusted fund for a particular risk-aversion profile.
A measure which describes the fluctuation of a fund's price over time. Higher volatility is generally considered to equate to higher risk.
While volatility is specific to a fund’s particular mix of investments, and comparison to other portfolios is difficult, clearly, for those that offer similar returns, the lower-volatility funds are preferable. There is no point in taking on higher risk than necessary in order to achieve the same reward.
FE gives the choice of both Volatility and Annualised Volatility.
The yields are sent directly to FE from the individual Fund Managers.
Generally speaking, funds comprising mainly of bonds normally quote a gross redemption yield after charges but before taxes have been deducted. Funds mainly made up of Equities normally quote a yield representing the estimated annual payout net of tax for basic rate taxpayer.
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