MAARS FUND MANAGEMENT ANALYTICS: INVEST IN A REAL SOLUTION FOR A REAL INVESTMENT PROBLEM
With uncertainty and low confidence in the financial markets, ensuring that the best mutual funds are being considered is critical. Discretionary and advisory investment managers, private banks and on-line investors find it challenging to select the "best" out of thousand possible funds. The problem faced by all is the number of funds and how to define the term "best". "Best" means different things to different people. Is it best absolute performance over the last 5 years best risk-adjusted returns, the external ratings from Morningstar or Lipper, lowest expense ratio or something else? In fact it is more complex than this. "Best" also means different things depending on whether the client's investment profile is aggressive, moderate or conservative. In reality it is a combination of all fund performance attributes but with different priorities. Assessing hundreds or even thousands of funds in a consistent manner taking into account all of these attributes and their priorities is beyond human capabilities in a sensible timeframe to make a decision.
MAARS Fund Management Analytics is a real solution to this problem. It is a decision support tool for asset/investment managers, private banks, fund rating agencies, fund supermarkets, financial intermediaries, pension funds, insurance companies and on-line customers that enables the users to prioritize and weight the different attributes according to their preferences. MAARS then applies these preferences and weights across all the potential funds quickly and efficiently. The result is that the user is always presented with a list of funds that are the closest fit to the preferences and weights. If there is an exact fit then it will be at the top of the list. If there is no exact fit then the closest fit will be at the top of the list. This is the key difference to existing selection systems available - MAARS never returns a null result but uses patent pending algorithms to apply "fuzzy" techniques to ensure the best fit is always found and it always appears at the top of the list.
Example with a set of dynamic parameters that can be used for funds (but not limited to existing list): - Performance: 1 Month, 6 Months, 1 Year, 3 Years, 5 Years - Ann. Alpha, Beta, r2, Ann. Volatility, Ann. Downside Risk, Ann. Jensen's Alpha, Sharpe ratio, Treynor ratio. MAARS FMA - beta (new) here