There are almost always advantages and disadvantages of any path taken. Below is a summary of our analysis, Advantages of a Quantitative Approach, along with several potential disadvantages that can be controlled.
- Process can be time-tested to determine the significance of their edge
- Process can eliminate significant behavioral biases from the process
- Process can evaluate a large opportunity set
- Process can identify virtually all sources of risk in a portfolio
- Process can reduce operational risk
- Process can reduce the risk of being fooled by randomness
- Process can help investors to maintain confidence during the inevitable periods of underperformance
- Process can further diversify a multi-manager portfolio
- Management fees should be meaningfully below market averages
- Portfolio transaction and liquidity expenses should also be below average
- Data base(s) may have significant inaccuracies or omissions
- Data base(s) may lack relevant factors, or have unnecessary factors which can create noise
- Portfolio manager(s) lack sufficient experience in back-testing research and real-time analyses
- Portfolio optimization can result in very poor out-of-sample performance when inputs are estimated with significant error(s)
- Dependent on historically significant factors continuing to be successful
Midwest strongly believes that a well-designed and well-implemented quantitative process meaningfully increases your probability of success. Moreover, even if a process is simply “average,” the manager should be in the top one-third of its peers. This is because management fees should be significantly lower than most active managers.
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