In April, Fabozzi, Focardi, and Jonas published the results of a survey of trends in quantitative equity management. The survey participants are 31 asset managers. 15 are US-based, and 16 are located in Europe. They manage $2.194 trillion in equities. Two types of investment processes are distinguished. First, the fundamental, or judgmental, investment process, which is based on human decisions. Second, the quantitative, or automated, investment process, in which decisions are computer-driven. The survey deals first with the optimal balance between the two types of investment process, fundamental and quantitative. Second, it scrutinises the motivations for implementing a quantitative process, the points that are underlined for marketing quantitative products, and barriers to entrance. Third, it examines how quantitative processes are implemented. Fourth, it explores market opportunities, the market environment, and performance issues. Fifth, it looks into risk management.

Only 26% of respondents think that the most effective equity investment process combines quantitative and fundamental approaches; 68% disagree. Respondents have mixed views of full automation, in other words, the elimination of human intervention in, say, forecasting and trading. Respondents who anticipate that quantitative asset management will move toward full automation and those who do not are evenly matched at 38%; 24% express no opinion.

Factors that are the most frequently mentioned as a reason to adopt a quantitative process are tighter risk, more stable returns, a performance increase, diversification, and the in-house culture. Cost stabilisation, the increase of the cost-to-revenue ratio, and the decrease of management costs are mentioned less frequently. According to the survey participants, the main barriers to entry to the quantitative equity management industry are the prevailing in-house culture, the difficulty of recruiting qualified personnel, the difficulty of gaining investor confidence, and existing large players. Indeed, 77% of respondents believe that a small number of large players will continue to dominate this space. The top-rated arguments for marketing quantitative products are alpha generation, enhanced investment discipline, better risk management, transparent processes, and rule-based processes. The main factors holding back investment in active quantitative equity products are the lack of acceptance by investors, and the lack of understanding by consultants; appearing as a black-box is not considered a major factor. 48% of the respondents think that recent poor performance in the equity quantitative sector puts pressure on managers to disclose more about their processes, versus 26% who disagree.

A large majority of the survey participants (71%) use a numerical-only modelling approach, while 6% use a rule-based-only modelling approach. 23% combine both approaches. According to the respondents, the model-building and backtesting process is mainly conducted by the portfolio manager. It is followed by a process conducted by the corporate research centre. A process in which the model is built by the portfolio and backtested by the corporate research centre seems rarer.

52% of respondents believe that the disappearance of market inefficiencies engenders more difficulties in generating excess returns, as opposed to 32% who disagree. 74% think that profit opportunities will not disappear, but quantitative managers will find it increasingly hard to profitably exploit them, while 23% disagree. Recent market conditions that are most often mentioned as factors penalising quantitative management are rising correlation, style rotation, insufficient liquidity, and fundamental market shifts.

When general factors challenging the quantitative approach are examined, the five most important factors are the use of similar models, the use of the same data, the activity of hedge funds, the need to update models continuously, and the fund capacity. The unwinding of positions by hedge funds is viewed as the major factor contributing to the losses incurred by some quantitative equity funds in the summer of 2007, ahead of the investment management process itself, the high global ratio of short-to-long positions, the overreaction of risk models, undetermined risk factors, and the misaligned equity derivatives behaviour. It differs from the factors supposed to explain these losses, mainly the reduction of spreads by deleveraging and by outflows from long-short funds.

On the assumption that everyone uses the same data and similar models, 62% consider that quantitative managers need a proprietary informational edge to outperform, while 32% disagree. Focusing on the informational edge, respondents are divided on whether it can be provided by high-frequency data: 38% agree, 27% disagree, and 35% express no opinion.

68% of the survey participants think that today’s risk models cannot predict severe events, such as those of July-August 2007, because they do not take into consideration global systemic risk factors, while 16% disagree. 63% believe that risk models don’t amplify catastrophic events, and 15% express no opinion.