Investment Process

Our investment process is based around a constantly evolving alpha model, which ranks stocks in our investment universe across four quadrants: valuation, price & earnings momentum, profitability & growth, and quality. We implement a bespoke model for each European sector, using the latest insights from our own research and that of academia. 

How the model ranks stocks

Over 1000 stocks are monitored, tracking amongst others: value, growth, estimate revisions, price trends, and quality. The output of the models is combined with market knowledge to build a portfolio with low risk characteristics and good return potential.

Our process steers us towards stocks with either superior long or inferior short characteristics, so that we can benefit from either upward or downward stock price movement.

As a result, every day 1000 European stocks get a rank from 0 to 100. Stocks with a rank from 80 to 100 are the long candidates, from 0 to 20 are the short candidates.

Portfolio Construction

Subsequent to the alpha generation process by the multifactor model, we proceed to a portfolio optimizer that calculates risk characteristics for each stock. The optimizer constructs a portfolio that maximizes the expected alpha, subject to a custom level of volatility, gross and net exposure, and additional diversification and holdings constraints. Holding restrictions are implemented to deal with stocks that are experiencing litigation risk, political risk, impending earnings reports, and other idiosyncratic conditions that might be overlooked by a quantitative model. The Fund is run with low beta-adjusted net exposure, and will be predominantly market-neutral over time.

Risk Management

Risk management is an integrated and central part of our investment process. We diversify our risk by taking positions in a large number of companies and imposing limits on the size of any single position. We also believe there are potential risks which need to be monitored and controlled at the levels of sectors and countries. We limit our exposure to specific quant factors by using a multi-factor approach but also by paying attention to the correlation structure between factors. To manage liquidity we apply additional limits on specific companies where necessary. We place additional stock-specific risk overlays for companies where we believe there are short-term issues which are not captured in our current model. All these diverse risk concerns are centrally managed via an integrated optimization process which is re-run on a daily basis.