Occam's razor ?

Now an as if approach might continue along the Lineraize and add R shocks framework

But what's so wrong with determined systems modeled by determined systems

Figure it out and agents can game it...as if they don't already game it

Albeit with a percentage of failures often big surprising ones even !

Yes once agents figure out the " workings " given really good initial readings

And periodic re readings for steerage ...

But they won't figure it out

it's too complex

Disregard this post

It's jumblicious

Can economic systems be chaotic ?

Perhaps not if agents can react to discovered patterns in say prices of stocks

Brock

"constant, the so-called Feigenbaum constant. It is so beautiful to play with these equations and that is what attracts me to it. It is tough though to find economic relevance of it. This is because a lot of economists, especially macro- economists, work with aggregate data. A lot of this stuff that might happen at a more micro-le- vel disappears when averaged out. Also, there are a lot of smoothing mechanisms in econo- mics."

"In the stock-exchange for example; if you think a stock is going up or down on a weekly

Farmer again and better

"Is it useful to approximate a complex system by a stochastic linear model. I personally think so. But it ultimately comes down to the ratio, in the data, of signal to noise. If an economy really does converge to a limit cycle, but the shocks that hit the system are large, the limits cycle will look like a point. If the shocks are small, relative to the underlying dynamics, we should be able to see that in data. Scatter plots of investment to GDP ratios at adjacent dates should, for example, should cluster around a doughnut. They don't.