Smart Swarm is a book about decision-making. Fund management is all about decision-making. Hence this book is about fund management. Indeed financial examples crop up several times.
Smart Swarm: Using animal behavior to change our world is interesting because it:
- describes many extraordinary decisions of animals.
- suggests a number of lessons that can be taken from that behavior.
- provokes thoughts of many more possible lessons.
The book is divided into 5 chapters: Ants, Honeybees, Termites, Birds of a feather, Locusts.
The main take-away from ants is that they are self-organizing. Decisions are all made independently, but the result is order rather than the chaos that we might expect.
An ant hill sends out soldiers in the morning to check the state of the outside world. When the soldiers are satisfied, then foragers go out to gather food. How do the foragers know when it is safe to go out?
Hint: there is no central command. Every ant has to decide for herself what to do.
It turns out that they decide by the rate at which they see soldiers come back home. If not many come in, then either it’s not time yet or something bad is happening to the soldiers. If lots of soldiers come in at once, then certainly something bad is happening out there.
The ant world is not devoid of pranksters. Ants that work the night shift have been known to put shutters over the nests of day workers so they’ll sleep in and miss foraging opportunities.
The chapter has a brief discussion of the ant swarm algorithm. This is quite a natural choice for solving traveling salesman type problems.
The key set of lessons of honeybees is:
- Seek a diversity of knowledge
- Encourage a friendly competition of ideas
- Use an effective mechanism to narrow your choices
When a hive splits, the group leaving needs to find a suitable new home. In my experience selecting a new house is really, really hard. But bees do it efficiently.
One place where markets tend to go wrong relative to the wisdom of bees is part of the knowledge bit. A bee is not going to vote for a location that she doesn’t have personal knowledge of. There is no reporting of what others have reported of what others have reported without checking the facts.
This chapter not only describes the cleverness of bees, it also describes the tedium that some scientists were willing to go through to learn about the cleverness of bees.
Termites are predisposed to add to a pile of dirt. This seems to me to be the perfect description of the phenomenon of open source software.
Once upon a time there was a pile of software called R. Jeff Ryan added to that pile with the xts package for time series (aimed at finance). Brandon Whitcher added to the pile with packages for analyzing MRI’s in medicine. I suspect that Brandon and Jeff don’t know each other, they might not even know of each other. But that is not a problem at all. The bigger the pile, the more others are prompted to add to the pile.
An interesting part of the chapter is where it discusses the structure of networks. Some networks have a few nodes that connect to lots of other nodes while most only connect to a few — the internet is an example. In other networks no node has very many connections. Which topology you’d like to have depends on what you want the network to do.
Birds of a feather
This chapter is not only about birds in flocks, but fish in schools and mammals in herds. The set of herding animals includes a peculiar species known as Homo sapiens.
How do birds flock together? How does the flock change direction with no one running into each other?
At least in the case of starlings each bird keeps track of its 6 or 7 nearest neighbors.
The basic role of grouping together is for protection. Someone on their own has to spend a lot of time looking for risk — that leaves less time for eating. In a group risk management not only takes less time for the individual, it is also more effective.
Markets can be a problem for us herding animals. If you are content with average results, then going with the herd is the thing to do: buy an index fund or a low volatility fund. But if you are seeking outperformance, then you want to go against the herd. If you try to outperform and stay with the herd, you’re going to get eaten.
The chapter describes an experiment with fish that is very reminiscent of human behavior. There was a fake predator in the fish tank. The fish that volunteered for the study would of course not go past the predator. If there was a fake subject fish that went past the predator, the real fish wisely wouldn’t follow. If two fake fish went past the predator, then the fish would follow.
Herds are good, crowds are bad. Crowds can crush you in a stadium or trample you in the Hajj.
Scientists have figured out what is going on in a locust swarm. Each locust is trying to snack on the one in front and trying not to get eaten by the one behind. Sounds like a description of markets to me.
The chapter ends with a discussion of the collapse of Iceland banks in 2008, tulip mania and relatives.
Pretty much all of the mechanisms described in the book involve some sort of contagion. Often, though, there is a governor on the contagion. Ant soldiers coming in slowly induce foragers to go out, but if they come in too fast, the foragers do not go out. Termites block up a hole in their tower, but they don’t block it up solidly — there remain tunnels for the tower to breathe.
I’m almost completely ignorant of brain science (except for having read Brain Rules) so my speculations here are not worth much. However, it seems to me that how insects cooperate must be quite similar to how the neurons in our brains cooperate with each other.