The Imperial College Algorithmic Trading Conference was Saturday.
Massoud gave a great talk on “Algo Evolution”. It started with a historical review of how trading used to be done “by hand”. It culminated in a phylogenetic tree of trading algorithms. There was an herbivore branch and a carnivore branch.
Robert talked about risk. He put it into a 2-by-2 table:
- Are you measuring or controlling?
- Are you thinking of normal times or extreme times?
Measuring for normal times is easy. Easy in quotation marks.
Controlling risk in normal times is possible, but there are some tricky bits.
Measuring extremes is too hard. We can get estimates but the variability of those estimates is extremely high. To get practical value we have to impose prior beliefs.
Controlling extreme risk is: “Err …” It is basically impossible. On the other hand it is essential for civilization to continue. In Robert’s words, “If the ATMs stop working, things are going to get rough.” Robert also pointed out that it is very easy to do things in the name of controlling extreme risk that will make it worse.
Panos talked on “Multiscale Stochastic Volatility”. Stochastic volatility is the continuous-time cousin of garch (see below). However, the trail to stochastic volatility was hard to see. I found the talk interesting because I saw some mathematics and computing that I know nothing about.
Keith talked about 130/30 funds. These in his view solve a few problems. In particular, they allow the fund manager to be more active, and allow bets on stocks going down (which tend to work better than positive bets) to be fully realized.
He emphasized that 130/30 is a portfolio construction device, it is not an alpha generator. In fact, if you don’t have alpha and you do 130/30, you get a whole lot more of nothing.
The 130/30 form has fallen out of favor with investors because performance has happened to be not so great. Keith thinks that a restart is called for.
I talked about “3 realms of garch modelling” (pdf). A companion to the talk is the blog post “A practical introduction to garch modeling”. This points to another blog post on variance targeting, which is also discussed in the talk. The talk concludes with an argument for doing financial research in R.
High Frequency Trading Panel
There was a lively debate about the topic:
- Do we know what “high frequency trading” means? No.
- Does it provide liquidity? Maybe, maybe not.
- Is it dangerous? Various opinions.