By providing a better way to identify mutual funds that are most likely to generate positive risk-adjusted returns in the future, mutual fund investors can use the results of this model to make better investment decisions.
Arlington, Virginia (PRWEB) March 5, 2009
MUTUALdecision, the definitive online source for predictive mutual fund models, today announced it has launched the site's fourth academic model - Forecasting Alphas - which generates a better alpha measure so that investors can identify mutual funds most likely to deliver positive risk-adjusted returns in the future.
Alpha measures the return of a mutual fund above (or less than) the market or a benchmark. It is viewed by many as the most effective way to gauge the value of the active management provided by a mutual fund manager.
The Forecasting Alphas Model is based on a highly respected academic paper that uses a statistical procedure and back testing to generate a more precise alpha measure. The authors find strong evidence that the funds with the highest alphas (i.e. the top decile) generate consistent positive abnormal returns of over 4% annually. The authors conduct a variety of tests to ensure that their results are not due to statistical anomalies, and the results continue to hold.
"This model demonstrates that future mutual funds performance can be predicted when performance models are applied only to the appropriate set of funds," said George Comer, chief academic officer at MUTUALdecision and Associate Professor of Finance, Georgetown University. "By providing a better way to identify mutual funds that are most likely to generate positive risk-adjusted returns in the future, mutual fund investors can use the results of this model to make better investment decisions."
Improved Forecasting of Mutual Fund Alphas and Betas, by Harry Mamaysky (Old Lane LLP), Matthew Spiegel (Yale University), and Hong Zhang (INSEAD), published in the Review of Finance, developed a statistical procedure to better determine mutual fund alphas and identify the funds most likely to generate positive risk adjusted returns in the future. The authors argue that the wide variety of investment strategies, objectives, and styles call into question the accuracy of traditional measures of mutual fund alpha and the value being added by fund managers. Using 32 years of data and making monthly observations, the authors back test specific performance models against individual funds.
"The most important result of this study for mutual fund investors is that its back testing procedure improves the models' ability to predict funds that will have positive alphas in the future," added William G. Byrnes, founder and chief executive officer at MUTUALdecision.
MUTUALdecision, founded in 2006, aggregates predictive mutual fund models created by leading academicians, mutual fund rankings, academic research and other tools for investors to make better mutual fund investment decisions. In addition to hosting leading academic models, with results for over 3,000 equity mutual funds, the Web site offers several free components:
- The top mutual funds ranked by each model
- Fund Rank, a new tool providing a snapshot of where a fund ranks in each of the models
- Abstracts of leading academic articles
- Mutual fund profiler and screener
- The MUTUALdecision blog featuring commentary on mutual funds, the models' top performing funds, the economy and financial markets
The four academic models are available for free during a two week trial period for those who sign up, after which site visitors will be able to access all hosted academic models and site tools through a monthly ($9.95), quarterly ($23.85) or annual ($71.40) subscription.
Based in Arlington, Va., MUTUALdecision is the only Web site for predictive mutual fund models based on academic research. It also features mutual fund rankings, academic research, mutual fund related commentary, and tools for investors to make better mutual fund investment decisions and easily identify top mutual funds. MUTUALdecision is the first to bring leading mutual fund academic research models directly to investors and financial advisors so that they can easily identify tomorrow's best mutual funds. For additional information, please visit http://www.MUTUALdecision.com.