My theory on stock prices

I would, if I weren't so lazy, look at earnings to price, and match that to the proper point on the corpoate yield curve. Earnings are variable, but some corporations have more stable earnings, some less. The time trend of earnings has a spectrum of movement, large stocks with stable stocks move down the curve, their shares looking more like cash. I can more easily trade $20 of AT&T shares for a bottle of whiskey than a lesser known, small cap stock. Stable stocks have high bandwidth when viewed as a spectrum, as a time series, that gives them inertia.

The Fourier way to think about it is: The GDP yield curve is a Fourier transform of the movements in GDP. The wider that spectrum, the more stable the time series. Stable earnings make higher price because the stock has high bandwidth, in the yield curve space.

But,but... this is not the way traders do it!! Yes, but I am not a trader, and yes I know they create an optimal flow, positive definite, asymmetric model in which Fibonacci is the basis set; and that conforms to Shannon equilibrium theory of portfolio. Yes, yes. I confess.

But I am going to look at the model in a macro sense, compared to two previous bubbles, and I am going to extract macro objective functions that are non heteroskedastic, in the DSGE sense, so I don't care about the information loss because the bubbles are too damn obvious.

Which gets us right back to Shannon. Why are two bubbles in a row so obvious? Why do we have to sample twice the bandwidth to recover information? Why is there a Pauli exclusion principle?