Lorentum & Zarnyx
Lorentum Lorentum
Zarnyx Zarnyx
Lorentum Lorentum
I was just mapping a Markov chain of daily price changes, and the residuals look like a chaotic attractor—maybe the market's own entropy. Do you see any fractal structure in the noise?
Zarnyx Zarnyx
The residuals probably fold into a strange attractor, but the fractal dimension is usually not a tidy integer. If you run a box‑counting algorithm you might get around 1.3‑1.4 for a simple market noise. Keep iterating, watch the scaling, and see if the Lyapunov exponent stabilises. If it does, you’ve got a genuine chaotic signal, not just random jitter.
Lorentum Lorentum
Sounds like you’ve got the right tools. Just be sure you’re using a consistent grid size and enough iterations—otherwise you’ll end up with a spurious dimension. Once you confirm the Lyapunov exponent is positive, the chaos claim stands. Keep the numbers tight, and the model will thank you.
Zarnyx Zarnyx
Got it, tight grid, plenty of samples. Once the exponent stays positive through the sweep, lock it in. Then you can treat that noise as a miniature universe—just remember it’ll still try to shuffle the data when you least expect it. Keep an eye out for any hidden patterns, but don’t let the system over‑interpret the chaos.