Re:Investing Is More Luck Than Talent
by scottmsul on Saturday January 21, 2017 @10:07PM
(#13453385)
Right, power laws are extremely common, and all it says is that some aspect of the distribution is scale-invariant, but without saying why. For example, most companies are scalable, so it's no surprise that company valuations follow a power law. And since investors/founders own such large shares of companies, that would help explain why the 1% follows a power law. But as this article claims, if people gamble on log-scales, that would also create a power law. Power laws are so common and general, I find it difficult to believe that a power law is evidence of one way or the other.
Re:Investing Is More Luck Than Talent
by josephdviviano on Sunday January 22, 2017 @04:55PM
(#13457787)
Thanks -- does the fact that the top 1% and bottom 99% show different distributions not imply they are gambling on different scales though? Is it as simple as the 1% gamble on a log scale and the bottom 99% gamble on a linear scale?
> as I am no 1%er ;).
If you are usual HN demographic I can guarantee you actually are. 32k/year is all it takes: http://www.investopedia.com/articles/personal-finance/050615...
While it's always important to keep this in mind at the global scale, most Americans use "1%" colloquially to describe the top 1% of United States citizens.
I suspect the downvotes are from people who assume you are intentionally misunderstanding the parent
No sure I get it. It seems people don't like being reminded that whilst they're very keen for people richer than them to share their wealth, they're generally very reticent to share their own wealth with people poorer than they are.
I just thought your comment was off-topic, is all. The comment you replied to, and all of the comments before it, were referring to the American 1%er, not the global 1%.
However, I like to think of a downvote is paperwork, not an insult. It's a great point, I just think the conversation flows better without it.
This accounts for why socialists change their minds after making money.
Re:Investing Is More Luck Than Talent
by josephdviviano on Sunday January 22, 2017 @04:53PM
(#13457779)
That's interesting. I was referring to 1% w.r.t. the USA, where the cutoff is actually ~250 k after taxes and adding back transfers. http://www.economist.com/node/21543178
Really brings to light how bad global inequality really is!
So through a US lens, I'm guessing a certain percentage of HN readers who work in senior positions in the valley or NYC would be 1%, and of course a random assortment of other readers, but the vast majority of software engineers etc. would NOT be 1% on a single income.
Curious that there's such a sharp change in distributions. It seems like the top 1% participate in a very different sort of financial network than do the remaining 99%. Since the majority's wealth follows such a basic physical theory, their organization must be completely unstructured.
For the 1%, then, the question is what the structure is. It might be 'scale free' network [1], or fractal, so it could be due to preferential attachment [2], which would mean those who have lots of money find it easier to make more money (via things like investments or rent-taking), or due to competition between fit nodes [3], which would make sense in that those in the 1% are likely to be merging / acquiring others.
I guess what this means isn't too surprising: if you aren't in the 1% now, you need to claw your way in before you can take advantage of these network effects to grow your wealth in any meaningful way. If you aren't in the 1%, you might be successful, but it will be mostly due to luck.
But I wonder if the network effects can be taken advantage of without the wealth to start. Following this line of thinking [4], the wealth flows due to social networking, not due to financial networking. If you can connect with the 1%'s social sphere, you stand a much better chance at becoming a part of that financial class.
[1] https://en.wikipedia.org/wiki/Scale-free_network [2] https://en.wikipedia.org/wiki/Preferential_attachment [3] https://en.wikipedia.org/wiki/Fitness_model_(network_theory) [4] https://www.quora.com/What-is-the-most-effective-yet-efficie...