A number of solutions have taken the passive route in order to reduce the Total Cost of Ownership (TCO). However, I would argue there is much more to the active/passive argument than cost. There is a more fundamental debate that divides investment management – ‘qualitative’ versus ‘quantitative’ analysis.
Advisers would be wise to reflect on these approaches, when considering selection (or maintenance) of a DFM service.
According to stereotype, ‘Quants’ are analytical personalities, happiest when poring over company reports and economic data. Qualitative investors on the other hand rely on people; they’re said to be more creative individuals who can assemble scenario analyses and consider themes, such that ‘left-field’ opportunities for growth can be identified.
They need peers, colleagues and especially corporate representatives – to help stimulate and confirm their thinking. However, that in turn leaves advocates open to the psychological biases humans exhibit.
Ben Graham, the ‘father’ of value investing and perhaps the first quant investor, considered his profession to be ‘security analysis’, indeed writing the primary text on the subject under the same title. He only used companies’ data that was available to everyone in order to make his decisions.
One of his most famous aphorisms was that the market was a voting machine in the short-term (who do you like?), and a weighing machine (ie the true worth of a company will dictate its price) in the long run.
In essence, his approach was to buy at the right price and the company (ie its equity) would look after itself – he felt no need to “meet the Boss”.
Qualitative investors on the other hand believe you should buy the right company and the price will take care of itself.
It is often said that Ben Graham’s star pupil, Warren Buffet, eventually eschewed quant, with proponents citing the quote, “…qualitative investment is really what makes the cash register sing”. In fact, Mr Buffet opined that he remained a firm advocate of quant analysis, but that the really “sensational” ideas he’d had came from what he called “high-probability insight” – it was this that extracted tunes from the tills.
However, he admitted these were rare events, both for him and investors at large, and since no insight is required from quant, the ‘sure’ money tended to be made by more obvious quant opportunities, while the ‘big’ money was made by the rare, successful qualitative approaches.
The same expectations apply in a top-down approach. At asset allocation level, quant analysis uses ‘algorithms’.
These are a series of ‘If, then’ computer calculations designed to identify changes in the vast array of global economic data and how these should influence subsequent market behaviour.
The results dictate and generate the ‘instant’ and automatic execution of trades, to gain an investment advantage.
Qualitative analysis on the other hand will have a more thematic, and hence ‘glacial’, approach that attempts to profit through longer-term forecasting of complex inter-relationships. It relies on insight and to a great extent ‘hunches’.
It can be exceptionally profitable when a contrarian view proves correct, but extraordinarily tough to do – it is indeed exceptional. Many a qualitative manager has been let down by the apparent ‘no-brainer’.
