The most important object in modern geometry is the manifold. This is a space that looks locally like n-dimensional Euclidean space -- 1-dimensional manifolds are curves, 2-dimensional manifolds are surfaces, and higher dimensional manifolds are simply called n-manifolds. All of physics takes place on manifolds. Differential equations correspond to vector fields on manifolds. The manifold hypothesis says that much of the high-dimensional data we see actually lives on much lower-dimensional manifolds (partially explaining the unreasonable effectiveness of deep learning on very high-dimensional datasets).
The most important object in algebra is the group. The collection of symmetries of any object (e.g. a Rubick's cube, a piece of paper, or three-dimensional space) forms a group under composition. A group that is also a manifold is called a Lie group. These are everywhere -- n-dimensional rotations form groups, fundamental particles correspond to representations of Lie groups, invertible matrices form a group. Spherical harmonics and Fourier series are both naturally viewed in terms of representations of Lie groups.
The most important object in analysis is the limit. Limits first appear in the construction of the real line by adjoining limits of Cauchy sequences to the rational numbers. Using the real line, one can measure volumes, probabilities, and distances in geometric spaces such as manifolds, but also in spaces of functions, sequences, and more abstract objects. The proof of the fundamental theorem of calculus (that derivatives and integrals are roughly inverse operations) requires rigorous analysis of the definitions of derivative and integral as limits.
To learn math, you should begin by understanding what a proof is. All of mathematics is based on proving theorems. A mathematical proof is a sequence of statements that explains the logical steps required to use the assumptions of the theorem to verify the result. Just as a computer program cannot "almost output" the correct answer, there is no such thing as an "almost correct" proof. A proof either describes a correct chain of logic to reach the conclusion, or it does not. The reason math is based on proofs is because more advanced math and science builds upon more basic math. An error in a mathematical theorem or an imprecise definition will lead to bigger problems down the line, so every step must be carefully validated. For an individual student as well, only through proving theorems can one deeply understand a mathematical subject, and a solid understanding of basic subjects is required to understand more advanced topics.
Fortunately, you can learn to prove theorems at the same time as learning the foundations of math. The first books you should work through are "Principles of Mathematical Analysis" by Walter Rudin, and "Linear Algebra" by Georgi Shilov. This will be hard, not for an arbitrary reason, but because assimilating new math into your brain is intrinsically difficult, especially at the beginning. If possible, try to find a teacher.
The reason racing through a math curriculum can be problematic is… what’s the goal? If it’s not “look as advanced as possible to a non-mathematician to get into a tier 2 college” and instead something like “expose kid to as much math as possible because they enjoy it/find it challenging” or “be a top mathematician for their age so they get into a tier1 college because mathematicians see promise in them” you don’t actually want to cram in subjects like typical community college or undergrad calculus, stats, and linear algebra at all. Those are not nearly as helpful for pursuing advanced mathematics as learning how to prove things, apply theorems to problems/reduce problems to theorems, or just generally becoming excellent at “lower” math like in contest math. In fact it might turn a kid off of math to get that far and still be doing mostly rote computational problems, and it won’t help that much in becoming a mathematician because those classes typically focus on the applied aspect (outside of particularly selective math courses at certain universities).
Re: goals —- the goal is to let the kid learn as fast as they want assuming they have solid foundations. If they like proofs let them do proofs, if they like applications let them do that. Just don’t force them to sit in a classroom doing busywork for the most formative years of their lives.
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First point: a lot of students get "accelerated" by their parents as a way of improving their academic performance and aiming the toward an elite college. Of course you look outstanding in school if you have covered the material a year before at the local cram center. These "accelerated by rote" students memorized the multiplication tables early, so they were put in "advanced math"... but their rate of comprehension is ordinary. Their problem solving skills are ordinary. They took "advanced math" in summer school so when they take the course in the ordinary school year they have a leg up. I don't think this has to be bad, but it's not the "gifted acceleration" and can be tough on these students if expectations are that they are "fast".
A second point: acceleration traditionally means moving through the same material faster. If you have a gifted child PLEASE work with them on a breadth of things, don't just race them through multivariable calculus. Math contests are a good source of broader problems. Art of Problem Solving gets a huge shout-out for what is now years and years of acceleration and enrichment material. Look at them if you are a parent in this situation. (Actually, they are suitable for self-study.)
Edit: I am all in favor of kids learning new things as fast as they want. I don't see racing through the standard curriculum (in any country) as a route to happiness.
Random brain-stimulating math book: Donald Knuth, "Surreal Numbers".
Kids intuitively understand this -- they like doing what they're good at. Unfortunately, most schools are not good at serving this need. A very important part of being a parent is to encourage kids to start compounding positive habits/learning early, and to prevent the schools from dragging them back to the median.
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Markets need participants, capital, liquidity, effort, etc. to become efficient. A lot prediction markets suffer from the fact that volatility in them is limited and that the outcome is not of interest to many people, so the markets cannot really do what markets are supposed to do.
If markets are aggregating crummy data and information, no useful market will form. And that is observable even in much more developed financial markets, where some things really have trouble on price formation. And then you might use auction methods, for example.
Similarly, if stuff happens rarely and you only get very limited shots at being right, then averaging and aggregation or not so useful because you cannot get an average (e.g., can do one thing for the next five years and better be right, for example).
It's not clear to me that prediction markets usually have natural hedging participants (maybe political operatives, but the tx costs are probably too high relative to the value at stake).