Should capital markets slow down?

I've been following the recent Knight Capital algorithm debacle for some time, and am a bit puzzled: what's the advantage of allowing all these algorithms to run amok in the capital markets? In particular, those algorithms that make hundreds of trades per second.

Brokerages and exchanges will want these algorithms in the market, since algos will allow them to earn commissions. With a global trend of declining commissions, most brokerages and exchanges need to increase the volumes to make up for the declining commission rates. Prop firms (including hedge funds and proprietary desks of investment banks) will want these "algos", since the algos supposedly give an "edge" (i.e. competitive advantage over the rest of the market). As my previous trading boss used to say, "no edge, no profit". 

However, if you look at the capital markets on the whole, it's hard to see how the advantages outweigh the risks involved. A rogue algorithm running amok in the market can react much more quickly than any human, causing markets to crash without any underlying economic basis: besides this Knight Capital incident, the Flash Crash of 2010 also comes to mind. This can spread fear through a market faster than you can swear "F----"... and fear (as an emotion) is a dangerous emotion to have spreading throughout a market. Worse, once a "situation" occurs, it's next to impossible to stop it without disrupting the entire market's function. High frequency trading basically raises the possibility of more negative black swans, without any real economic benefit.

It's also arguable if allowing milli- and micro-second trades helps in the price discovery process: is it really meaningful price discovery between a willing buyer and seller who can cognize the price and economic benefit/cost, or is it just "noise" between one algo and another? Can it really be meaningful price discovery if a human watching the exchange (even an experienced floor trader) won't be able to cognize the price, as it just happens far too quickly?

Perhaps as a policy, exchanges globally should consider limiting the speed of transactions, s.t. an algorithm cannot be faster than, say, the typical human reaction time on an electronic trading desk. Otherwise, we run a real risk that the Machines will overtake the markets, and leave us wondering what happened in the aftermath. 

Should Singapore focus more investment in "soft" science research?

Lately I've been toying with the possible idea of doing a graduate degree in behavioural economics, and started doing some online research on any programmes.

Not surprisingly, most of the graduate programmes available are in the US, with an additional programme in Nottingham, UK. But what surprised me was that there were next to no behavioural economics/finance research programmes here in Asia that was picked up by Google.

So this got me thinking, and I thought about what a great idea it will be for Singapore as a test-bed for behavioural economics: most of the research currently being done seems to focus primarily on test samples from the West, but nobody seems to yet have done a categorical study into the possible variations of key behavioural concepts (anchoring, frames, etc.) across different cultures. Given that Singapore is centrally located, and is a confluence point for both East-West, perhaps this is the best place for such inter-cultural behavioural studies to be done.

Also, instead of the Singapore government spending huge amounts of money on technological research programmes and fixed technological infrastructure that might or might not work (does anybody still remember the calls of Philip Yeo for Singaporeans to study engineering and biotech?), perhaps Singapore should increasingly focus on developing our "soft" research. "Soft" research areas in the social sciences are relatively cheaper: compare the amount of specialized equipment needed in a chemistry lab (mass spectrometers, lasers, NMRs, etc.) vs. a behavioural psychology lab (attractive female research assistants, hidden cameras, cookies, etc.).

As a consequence a large portion of investment in hard-science research facilities go into fixed costs (equipment), while investment in soft-research tends to go to variable costs (man-hours): the operational leverage of hard-science research is a lot higher.

Which logically means that perhaps the risks/rewards are higher if we put our research money into "soft" research than "hard" research. If Singapore puts more money and emphasis into "softer" research like psychology, economics, behavioural economics, sustainable development, etc., we might be able to boost our economy by creating niche industries and innovations that spinoff from such research.

We actually already have exported some behavioural economic innovations, albeit innovations that have come from our government. For example, congestion road pricing was first implemented in Singapore. Now, drivers in London curse and swear at their own road-pricing system, which was adopted by their Singa-phile ex-mayor Ken Livingstone. As another example, the Singapore Government's Central Provident Fund has been quoted in Akerlof and Shiller's latest book "Animal Spirits" to be a potential way to increase savings rates in the US.

Suppose that we invest in a research center focused on behavioural economics, and our research generates interesting findings of the different behaviours between, say, Chinese and American consumers. It's not unthinkable that our researchers will be able to setup consulting firms to advise foreign companies on the best ways to attract Chinese/Indonesian/Indian consumers.

Or if we setup a research institute on sustainable development, then Singapore could not unthinkably become a Southeast Asian hub for sustainable development research across different countries and regions.

This strategy of trying to improve one's academic standing by focusing on the "soft" sciences was adopted by New York University in 2003: New York University tried to revamp its reputation as a top liberal arts research institute by aggressively expanding its economics department , which seems to have been quite successful.

Having setup a Biopolis, perhaps it is time for us to look at a Behaviouropolis?