The investment management business is currently experiencing a move towards more discipline, more process and more specification.

Perhaps the first indicator of this is BZW’s recent announcement that they are putting considerable funding behind a joint project with the Ministry of Defence to put advanced military computer technology to work in the financial markets. Interestingly, the results will at least in part be shared with other market participants.

Quantitative investment is traditionally seen as sterile and lacking in colour, compared with the tooth-and-claw stockpicking which still dominates the investment industry. However, while occasional flashes of brilliance from human decision makers may stir the blood, over time the systematic, dogged application of good programmes has a higher percentage chance of success.

Even with the best ordered input, it is questionable if the most talented individuals can synthesise all data effectively on a subjective basis and go on making decisions, that are right, time and time again.

Naturally, quantitative programmes also involve an amount of judgement and human decision making. That judgement, however, goes in at the front end of the process, at the model building phase, and not at the output or implementation phase. It is pointless to build a complex and sophisticated process to help tell when markets or individual stocks are cheap or dear and then second guess the process by trying to cherry pick the results. It is inadvisable to follow recommendations only when they “feel” right. For it is most likely that the process will be right when it “feels” intuitively most uncomfortable.

The branch of financial academia known as behavioural finance teach-es us that human decision making in the financial arena is inherently bias-ed, as well-defined tests can show. And even when people are aware of such bias, they can go on making the same errors time and again.

The investment decision maker has ever more amounts of information instantly available, but the speed at which it must be assimilated, assessed and used, if a competitive advantage is to be sustained, is accelerating as well. It seems unlikely that talented traditionalists, using subjective judgement, can in the longer term compete against the best combinations of strategists, programmers and state-of-the-art computing power brought together in real-time investment processes.

One key criticism of quantitative decison making has been that it is dependent on the future being broadly similar to the past and is a bit like driving with only a rear view mirror. What I say to that is, if the windscreen is opaque, a good rear view mirror is better than nothing. If there is a real sea-change for investment markets, which comes out of left-field, then traditionalists are likely to be caught as flat-footed as systematic investors. A very small number of subjective decision makers may spot the change in time and react accordingly, but it is difficult to build an investment strategy on the likelihood of that happening.

Quantitative investing offers two key advantages, both equally important. Firstly, huge quantities of data can be processed at ever increasing speed.

Secondly, is that, properly specified, it forces a consistency of implemenation that gainsays the comfort seeking, trend-following behaviour exhibited by the majority of investors. It is also less dependent on individuals than process. In a more risk conscious environment, that may look increasingly attractive.

Bill Goodsall is managing director of First Quadrant in London