Showing posts with label Quant. Show all posts
Showing posts with label Quant. Show all posts

1 Oct 2008

* Equilibrium thinking?

An agent model being developed by the Yale economist John Geanakoplos, along with two physicists, Doyne Farmer and Stephan Thurner, looks at how the level of credit in a market can influence its overall stability.

Obviously, credit can be a good thing as it aids all kinds of creative economic activity, from building houses to starting businesses. But too much easy credit can be dangerous.

In the model, market participants, especially hedge funds, do what they do in real life — seeking profits by aiming for ever higher leverage, borrowing money to amplify the potential gains from their investments. More leverage tends to tie market actors into tight chains of financial interdependence, and the simulations show how this effect can push the market toward instability by making it more likely that trouble in one place — the failure of one investor to cover a position — will spread more easily elsewhere.

That’s not really surprising, of course. But the model also shows something that is not at all obvious. The instability doesn’t grow in the market gradually, but arrives suddenly. Beyond a certain threshold the virtual market abruptly loses its stability in a “phase transition” akin to the way ice abruptly melts into liquid water. Beyond this point, collective financial meltdown becomes effectively certain. This is the kind of possibility that equilibrium thinking cannot even entertain.

Detail: This Economy Does Not Compute

29 Sept 2008

* “Quant” investing

What is quantitative or “quant” investing? In short, it is where mathematical models rather than manager’s discretion make investment decisions.

What do quant managers do apart from running sophisticated computer programs? An analogy with cars may help here. No matter how sophisticated a car, it still needs a driver and sometimes a mechanic. The driver must know when to brake and when to accelerate. Quant managers provide both functions – they control risks as well as fix things such as data errors when they occur. Most importantly, every car needs to be designed and engineered in the first place – the most important part of a quant manager’s job.

In the case of a good quant, it should get better!” Ignore established and successful quants at your peril. However, behind any computer program there is always a human brain. Investing in a quant approach is the best way to profit from human ingenuity but without the danger of human error.

Detail: Why quant?