By Dr Carsten Grosse-Knetter and Thierry Misamer, ODDO BHF Asset Management

Blind trust in computers – this is an often-heard prejudice regarding quantitative investment strategies. Computers are indeed an essential tool in analysing prices of hundreds of stocks. They also help you keep a cool head and choose the best stocks for your portfolio on the basis of objective data. Our more than 10 years of experience shows that added value can be generated with our in-house stock-picking model, which is a quantitative approach that is not based on our own forecasts. Our track-record also demonstrates that outperformance is possible even on highly efficient markets.

As with discretionary management, quantitative management features many different approaches to investing on the equity markets. There are both highly focused concepts that concentrate on a single factor such as momentum, and highly diversified, multi-factor variations. As varied as they might be, all these approaches share in common the specific advantages of quantitative management.

Its first advantage is its ability to systematically cover a large investment universe. Let’s take the European equity market as an example, as represented by the Stoxx 600 index. A quant manager is able to track and analyse the price performances and fundamentals of all 600 stocks in this index at all times and to make his selections backed by the information produced by his model. He can thus address a broad investment universe and enhance his opportunities for selecting attractive stocks and taking on successful exposures. A discretionary manager, in contrast, can research only a limited number of companies in depth and is therefore limited in his selection opportunities. This lessens his probability of outperforming. In our portfolio we select 100 stocks from the Stoxx 600. This gives us greater opportunities to find attractive stocks while allowing us to be better diversified, which limits losses as much as possible.

The second advantage of quantitative management is that stock-picking is based on prescribed rules that are presented to investors in detail and that can be disclosed transparently. Moreover, the systematic use of these rules makes it possible to measure their efficiency in a precise manner. The fund manager is thus able at all times to analyse and explain the results achieved. Seen from this angle, quantitative management is fundamentally far more transparent than discretionary management. However, there are also differences here among quant managers. When investment decisions are made on the basis of complex mathematical models it is difficult or impossible to illustrate in a detailed manner the various factors underlying investment decisions and to explain the logic behind each one of them. This “black box” phenomenon is often encountered in models that are based primarily on mathematical or statistical optimisation.

There is a third advantage to quantitative management – the almost complete elimination of “emotions”. Studies in behavioural finance have found that emotions play an important role and can ultimately be counterproductive, particularly in times of market stress. To hedge this risk, the quant manager takes a systematic approach and applies it in a consistent and disciplined manner. Trend-following momentum strategies can even achieve outperformance by systematically taking advantage of market participants’ irrationality (this part can be cut out or put into a footnote if it is essential). During the 2008 financial crisis our portfolio suffered relatively steep losses compared to the market as a whole. At the time, the temptation was great to flout our own rules. And yet, we stuck to the guidelines of our model, a decision that ultimately paid off. Our portfolio had no problem in making up its underperformance in the following year. This is in no way an exception. In a very tense market our discipline almost always pays off, as phases of underperformance can very quickly be made up through outperformance. Our portfolio also tends to underperform when market prices are being driven by macroeconomic factors, such as in the aftermath of the election of Donald Trump or the Brexit referendum. However, as these phases do not usually last very long, we quickly make up the ground we have lost.

In both discretionary and quantitative management the choice of fund manager is decisive and must correspond to the investor’s risk profile. That’s why it is important to assess the robustness of the fund manager’s model. Several aspects are decisive here – the model must be based on clear market regularities and the sources of potential outperformance must be laid out clearly.

The individual steps leading to investment decisions must be spelled out as clearly as the stock-picking criteria.

The model’s investment track-record must also be tested thoroughly. The period under review must be long enough to cover various market phases, including bearish markets (for example, during a macroeconomic shock). As investment decisions under a quantitative approach are made on the basis of a model’s guidelines, past performance is a good indicator of the quality of the model used and for the disciplined implementation of the investment process. The fund manager must be able to explain the various phases of out- and underperformance.

Investors who prefer steady performance should opt for a multi-factor model, which is more stable than a single-factor model, as it takes advantage of diversification between lowly or even negatively correlated investment styles. The entire portfolio is market-neutral and has a far lower active risk than one that follows a single investment style. A single-factor model also results in longer or steeper phases of underperformance, which are phases in which the other factors could have made positive contributions. For example, during the 2008 financial crisis fundamental factors such as “valuation” and “growth” fared poorly, while technical factors such as “momentum” and “low risk” performed very well. In 2009 it was the opposite, with fundamental factors producing considerable outperformance.

In conclusion, it can be said that quantitative management differs from traditional fund management through its extremely systematic, consistent and disciplined market approach. However, keep in mind that both management styles are subject to the risk of loss of capital.

Ultimately, our investment decisions, too, are based on fundamentals such as corporate earnings and technical indicators such as price performance, i.e. exactly the variables taken into consideration also by traditional fund managers.