Advance Technology and Methods within Finance

A fund of funds is just a fund which invests in other funds. Just as a mutual fund invests in a number of different securities, a fund of funds holds shares of many different funds. These funds were designed to achieve even greater diversification than traditional funds, and also to put to work large amounts of capital. On the downside, expense fees on fund of funds are typically higher than those on regular funds because they include part of the expense fees charged by the underlying funds. In addition, since a fund of funds buys many different funds which themselves invest in many different stocks, it is possible for the fund of funds to own the same stock through several different funds and it can be difficult to keep track of the overall holdings.

Many mutual fund holders also suffer from being over-diversified. Some funds, especially the larger ones, have so many assets (i.e. cash to invest) that they have to hold literally hundreds of stocks and consequently, so are you. In some cases this makes it nearly impossible for the fund to outperform indexes – the whole reason you invested in the fund and are paying the fund manager a management fee. As the sage words of the “Oracle of Omaha”, Warren Buffett: “wide diversification is only required when investors do not understand what they are doing”.

When analyzing investment performance, statistical measures are often used to compare ‘funds’. These statistical measures are often reduced to a single figure representing an aspect of past performance. Alpha represents the fund’s return when the benchmark’s return is 0. This shows the funds performance relative to the benchmark and can demonstrate the value added by the fund manager; the higher the ‘alpha’ the better the manager. Alpha investment strategies tend to favor stock selection methods to achieve growth.  Beta represents an estimate of how much the fund will move if its benchmark moves by 1 unit. This shows the fund’s sensitivity to changes in the market. Beta investment strategies tend to favor asset allocation models to achieve out performance.  R-squared is a measure of the association between a fund and it’s benchmark. Values are between 0 and 1. 1 indicates a perfect correlation and 0 indicates no correlation. This measure is useful in determining if the fund manager is adding value in their investment choices or acting as a closet tracker mirroring the market and making little difference.  Standard deviation is a measure of volatility of the fund’s performance over a period of time; the higher the figure the greater the variability of the funds performance. High volatility is an indicator of increased investment risk in a fund.

A large Fund of funds has so much capital to put to work, efficacy becomes the defining bottle neck. In other words at some point of capital placement each incremental new placement does not improve the overall return and in a lot of cases diminishes the returns. Fund to funds conduct large complicated, recursive algorithms on each placement, and each position in each placement, to look at the alpha or beta of the scenario.

It may be interesting to model the Fund to Funds world as a network and determine if it is a well structured network or not. This may lead to less computationally intense ways to find capital placement opportunities and improve the efficacy of large funds.