When the former head of product development in the electronic client solutions group at none other than JP Morgan, Carl Carrie, was last quoted on Zero Hedge, he had some very nasty words for High Frequency Trading. Today, in a podcast transcript by algotradingpodcast Carl shares much more light in just why any reform movement against HFT and PT in general will be met by a huge pushback by exchanges, brokers, infrastructure providers, telcos, and all derivative market players:
Clearly, algorithmic trading is a huge factor. High-frequency trading for Arbitrage's, indexes, ADRs, pairs, ETFs, interlisted trading, as well as automation around auto-working, have all been factors contributing to the growth of algorithmic trading and trading on exchanges.
The exchanges themselves have also been contributing factors. They've invested heavily in capacity and throughput. And the allocations of assets to European equities has also been a minor factor.
Carl also touches on another, so far undiscussed issue - the industrial oligopoly and the economies of scale advantages to the select few:
In the electronic trading space, you're seeing the beginnings of a fallout, and you're seeing larger scale players, some of them become clear winners. Not that they can permanently sustain their competitive advantage, but for a period of time, there is an economic advantage in being the preeminent, top scale player, and probably the next two rungs below.
Hey Christine Varney - if you can look away from Google for longer than 10 seconds, maybe you can focus on where the next real fight for monopoly is ocurring, with materially greater consequences than Firefox being bundled in with Windows 7.
Most notably, Carl discusses the emerging risk types with this new technology. Not surprisingly as Joe Saluzzi would attest, and much to the chagrin of program trading specialist Irene Aldridge, the key risk is liquidity, and much more so to the downside, i.e., when it disappears.
There are new risk types. I think, it used to be about timing cost and market impact. Those were two twin pillars that most algorithmic trading has been based on.
And I think, if you look at what's happened recently in the credit markets, it hasn't opened our eyes to liquidity risk, but liquidity cost and liquidity risk is perhaps a different animal. It's not just about price volatility. It's about volume volatility. It's about timing of that volume volatility. It may be there today, and when you want to get out of your position, it may not be there tomorrow. And how do you reflect that into your own trading and into, not just your alpha generation, but on the risk side of the alpha generation? Most risk models don't really take into consideration the kinds of anomalies that we may see on a yearly basis.
It's not a Six Sigma event, typically, that happens when we have a liquidity crisis. And a liquidity crisis very easily moves across from one market, as a class, to another. So, you've got this contagion correlation effect that's massive. So, I think, it's important for all of us to develop new science and new tactics to really deal with that. And particularly, as you talk about emerging markets, there's no sphere that is as liquidity-sensitive as emerging markets is.
Curiously, when Carl left JPM his parting letter had this to say: Yes, I love equities but I think the biggest transformation in the market over the next couple of years will be in the OTC fixed income, credit and commodity markets that are both begging for more liquidity and transparency and are ripe for a major transformation. I want to be there at the genesis of that transformation. We at Zero Hedge completely agree with this statement and will be presenting some of our extended ideas on this matter over the next several weeks.