The 30-day SEC standardized yield represents net investment income earned by a fund over a 30-day period, expressed as an annual percentage rate based on the fund's share price at the end of the 30-day period. The formula for calculating this yield is specified by the U.S. Securities and Exchange Commission (SEC) and assumes all portfolio securities are held until maturity. The formula translates the bond fund's current portfolio income into a standardized yield for reporting and comparison purposes.
A statistical measurement used to quantify the value added or subtracted by a portfolio manager. Specifically, alpha measures the portfolio's actual return against the portfolio's expected return given the risk of the portfolio as defined by its beta. Alpha is one of the three MPT (Modern Portfolio Theory) statistics and is derived by a linear regression of the portfolio's returns against the returns of a benchmark.
An important observation when using alpha is to know how accurately the portfolio beta reflects the market risk of the portfolio. The confidence with which one can have in an alpha (and beta) depends entirely on how strong the linear relationship is between the portfolio and the benchmark. A strong relationship is characterized by a high R2. As the value of the R2 decreases, the alpha for a portfolio becomes meaningless.Annualized Return
Returns are calculated for each fund or composite by geometrically linking either monthly or quarterly performance for a specific period. This compounded total return is then annualized.Beta
A statistical measurement of a portfolio's relative sensitivity to the benchmark, which acts as a proxy for market risk. The beta between a portfolio and its benchmark is the amount of units the portfolio will move when the benchmark moves one unit. By definition, the beta of the market (benchmark) is one. Beta is one of the three MPT (Modern Portfolio Theory) statistics and is derived by a linear regression of the portfolio's returns against the returns of a benchmark.
For example, if a portfolio has a beta of 1.15, it is expected that the portfolio will perform 15% better than the benchmark in an up market. However, in a down market it is expected that the portfolio would perform 15% worse than the benchmark.
It is important to note that beta is only an estimate. For a beta to be most accurate, a perfect linear correlation (in the form of an R2 equal to 1) must exist between the portfolio and the benchmark. As the value of the R2 decreases, the beta for a portfolio becomes immaterial.Downside Risk
A statistical measurement of a portfolio's dispersion below the mean return of a benchmark. In other words, downside risk is the standard deviation of those returns for a specific period, which fall below the average return of the benchmark.
Since standard deviation measures both positive and negative returns, some believe it is not a good measure of the true risk of a portfolio. If one defines risk as under-performing the portfolio's benchmark, then a large positive gain should not be included in the calculation describing the risk of the portfolio. Thus, the downside risk statistic attempts to isolate and quantify those returns which negatively affect the portfolio.Net Asset Value (NAV)
NAV per share is computed once a day based on the closing market prices of the securities in the fund's portfolio. All mutual fund's buy and sell orders are processed at the NAV of the trade date.R2
A statistical measurement that shows the percentage of a portfolio's movements that can be explained by the movement in the benchmark. The numerical value of a portfolio's R2 is always between 0 and 1. An R2 of 1 (or 100%) means that there is perfect correlation in the movement between the portfolio and the benchmark. Conversely, an R2 of 0 means that there is no relationship in movement between the portfolio and the benchmark. R2 is one of the three MPT (Modern Portfolio Theory) statistics and is derived by a linear regression of the portfolio's returns against the returns of a benchmark.
For example, a portfolio has an R2 of .23, a beta of 0.93 and an alpha 1.04. According to the statistics, it appears that the portfolio manager is doing a good job adding value. The alpha of 1.04 implies that the manager produced a return 1.04% higher than its beta would predict. However, the very low R2 suggests that only 23% of the movements in the portfolio are explained by the benchmark. Thus, there is very little confidence that the beta and alpha have any significance. Note that this does not imply that the manager is doing a poor job, merely that one cannot use these particular statistics to say that the manager is doing a good job.Return On Invested Capital (ROIC)
A calculation used to assess a company's efficiency at allocating the capital under its control to profitable investments. The return on invested capital measure gives a sense of how well a company is using its money to generate returns. Comparing a company's return on capital (ROIC) with its cost of capital (WACC) reveals whether invested capital was used effectively.Sharpe Ratio
A statistical measurement of the risk adjusted performance of a portfolio. The ratio is calculated by dividing a portfolio's excess return over the risk-free rate by the standard deviation of its excess returns. This shows a portfolio's reward per unit of risk and is useful when comparing two similar portfolios. As the Sharpe ratio of a portfolio increases, the better its risk adjusted performance.Sortino Ratio
The Sortino Ratio measures the ratio of the difference between a fund's average return and a benchmark's average return divided by the downside risk. The larger the Sortino Ratio, the less the likelihood of large losses occurring.Standard Deviation
A statistical measurement of dispersion about the mean return of a portfolio. Standard deviation shows how widely the portfolio return varied over a specific period. Consequently, it is often used to describe the risk or volatility of a portfolio.
Standard deviation assumes that if the portfolio returns are normally distributed, then 68% of the time the return falls within one standard deviation from the mean, 95% of the time the return falls within two standard deviations, and 99% of the time the return falls within three standard deviations. For example, a portfolio has an average return of 15% and standard deviation of 8%. Based on these historical measures, we would expect that 68% of the time the portfolio's return would fall between 7% and 23%, and 95% of the time the portfolio's return would fall between -1% and 31%.