How Chaos Theory Beats Randomness - and Which Best Explains Market Unpredictability?

According to Chaos Theory, most systems in the real world should be unpredictable. But if Chaos Theory does make things unpredictable, does that mean that systems which contain chaotic dynamics behave as though they are random? And if not, when is randomness not a good approximation of chaos?
In part two of this series, we will dig further into chaos theory, and explore implications for modelling of the real world, and what it means for stock market predictability. Last time we touched on chaos theory and the so-called butterfly effect, and how this undermined our intuitive assumptions about mathematical predictability. In this episode we're going to discuss where and how chaos theory is an improvement on randomness to explain real world phenomena, using financial mathematics.
The Lorenz equations are useful because they are relatively easy to understand, with only a small number of variables, so we can see exactly what is going on. Yet these equations are very powerful for illustrating key concepts from Chaos Theory. Since they were introduced by meteorologist Edward Lorenz in 1963, they have become a classic example of deterministic chaos.
The Lorenz equations are a set of three coupled, non-linear differential equations that describe the behavior of a simplified model of atmospheric convection
Random Walk:
László Németh, CC0 (Public Domain), via Wikimedia Commons
creativecommons.org/publicdom...

[@user-pd4wq5jb3b]

Keep pushing out these great vids! Love it, good job!

[@fractalmanhattan]

Thanks heaps!! I'll definitely try to get some more out there!

[@yann9637]

Great content as usual !

[@fractalmanhattan]

Thanks so much!

[@lewiscoates1691]

Great videos, looking forward to the next ones

[@fractalmanhattan]

Thank you!

[@Ferrazi]

These videos are very good. Old-fashioned in style, but very good. There aren't many videos about the theories that the big players in the market take into consideration when building programs to make money.

[@fractalmanhattan]

Thank you! Loved your comment about them being old-fashioned - hee hee

[@Brumor]

This is amazing, thank you so much! :D

[@fractalmanhattan]

Thanks Brumor - you're always very generous with your comments!

[@Brumor]

@@fractalmanhattan They merely reflect the quality of your work.

[@vaguthun]

Thank you so much... lot of information..

[@fractalmanhattan]

Thank you! Really appreciate the feedback!

[@robertdinh3842]

thank you, you are wonderful!

[@fractalmanhattan]

Thank you, that's very kind!

[@TheCashiron]

Great stuff! Subscried

[@fractalmanhattan]

Thank you - appreciated!!

[@joshuaGmartin2023]

these are really great, but, if you care to know, I find the music detracting

[@fractalmanhattan]

Thanks Joshua - that's really great feedback. I'm still experimenting with how I put these together, and had wondered about how I'm using the music. The raw audio isn't perfect (e.g. hums and background noise) so some background music can be good to cover this, but too much I agree risks just being distracting - so this is really useful to know. Any other thoughts are welcome :)

[@ahmaddodo4270]

The Butterfly Effect: A Delicate Chaos (Chaos Theory)
ruclips.net/video/XF-U_UbURHk/видео.htmlsi=o7gGShvGtjzQG9se

[@AaBb-pp9bd]

if not, randomness not a good approximation of chaos. poor guy studying bad graphics