Deus Ex Macchiato

Here’s something I would like to do – it is far too much work for me (or I suspect less than a team of 30) to actually do, but never mind that, let’s just run with it.

First, build a mini model of the banking system as a set of autonomous agents. You’ll need a variety of banks and brokers, securities markets and lending, central banks and monetary policy, treasury activities and trading, investment managers and hedge funds. The simulation does need not be hugely complex: a few different securities will probably do for instance, but prices should be set by real market activity, and there should be analogues of government bonds and corporate bonds. You will need the interbank markets, too, with credit risk being taken in a variety of ways. Financial institution bankruptcy can happen due to either liquidity or solvency crises, and if a financial firm goes bankrupt, its portfolio is sold to the market. Demand for credit is set by the economic cycle, and there are fundamentals bubbling along too with random defaults of entities issueing bonds and taking loans.

Next, set some rules for the banks and brokers. We can start with the current regulatory capital rules. Banks will have a capital structure with both a term structure of debt and equity, and they will have to capitally adequate at all times. The same goes for brokers, but they can have different reg cap rules in general to model the SEC vs. FED divide.

Now the game. There are two classes of players. The first class is the bankers: they define trading rules for an individual bank. They can’t dictate transactions; rather, they write rules which determine what transactions a bank will do, depending on market conditions. There can be as many bankers as there are banks, but balance sheet size and initial capital is allocated randomly to players at the start of the game subject to plausible distributions.

The game proceeds by the simulation being run through time; this is then repeated many times. The banker’s payoff is the average of the positive part of the bank’s profit averaged across all the simulations. So, like the real world, these guys score higher if their banks make a lot of money in a variety of conditions.

The second class of players is the regulator. This player rewrites the rules that the banks must obey. Their score is based on the number of bankruptcies and both the volatility and level of credit supply: basically they score highly if there are no bank failures and credit grows slowly but steadily.

With sufficient (= a lot of) computing power, you could have a number of people playing as regulators, each simultaneously facing all the bankers. You could even use genetic algorithms or any other adaptive strategy you like as the regulator. It would be fascinating to see what rules emerged as winners.

There is a lot more you could do, too. For instance, you could impose a change on fundamentals and see what happened. You could road test new rules and see how players game them. You could with a bit of work find out what market dynamics lead to most bankruptcies, or the biggest systemic crises. You could see what bank strategies are most profitable but lead to high tail risk. It might not be a popular as world of warcraft, but I bet if you got the user interface slick enough, quite a few financial services people would play, and all that expertise could be used to improve the capital rules. The key point is that even if you don’t believe the results of the simulation are realistic, having something that suggests financial system vulnerabilities on the basis of actual dynamics and attempted gaming of the system could be quite useful.

Posted in: Emergence, Rules by David /