Investors are bombarded with information from a tremendous number of sources. It is extremely difficult to filter, categorize, analyze, correlate, and test information to make an informed, unemotional decision without utilizing a systematic time-tested approach to investing. We maintain a high standard when deciding providers to leverage for our quant infrastructure tools and data. Quality data is key to our QEVplus process.

The first step to Empiric’s QEVplus alpha score is to rank securities within a given index based on fundamental metrics for Quality, Efficiency and Valuation relative to industry peers in a region. The QEV score is plus catalyst factors where appropriate. Every month, stocks in a given universe are ranked based on their alpha score.

Identifying and adjusting for the appropriate risk level is equally important. Individuals and professional investors often take on an inappropriate level of risk, or overlook it all together. It is easy to identify this mistake in hindsight, but far more difficult to apply the appropriate levels of risk on a regular basis. Empiric has developed several computer models that take into account numerous risk factors. Each risk factor has a given weight which is compared to the portfolio and the universe of stocks in a given benchmark.

The second step to Empiric’s QEVplus alpha score is to optimize. This entails measuring the anticipated risk contribution that a position exposes the overall portfolio to relative to a predetermined risk allowance at the portfolio level. Each process comes with inherent biases, as systematic investors we can limit our exposure to common factor, country, currency, industry, sector, and size risk to focus our tracking error exposure primarily to stock selection.