A mixture of Gaussians approach to mathematical portfolio oversight: the EF3M algorithm

An analogue can be made between: (a) the slow pace at which species adapt to an environment, which often results in the emergence of a new distinct species out of a once homogeneous genetic pool and (b) the slow changes that take place over time within a fund, mutating its investment style. A fund's track record provides a sort of genetic marker, which we can use to identify mutations. This has motivated our use of a biometric procedure to detect the emergence of a new investment style within a fund's track record. In doing so, we answer the question: <italic>What is the probability that a particular PM's performance is departing from the reference distribution used to allocate her capital?</italic> The EF3M algorithm, inspired by evolutionary biology, may help detect early stages of an evolutionary divergence in an investment style and trigger a decision to review a fund's capital allocation.