2,308 karma · joined August 6, 2014
> “Back in 2003-5 a memo was created within the IRS noting who was permitted to participate in ‘insider trading’,” says this whistleblower. “The memo noted that all IRS employees in the executive branch and those one step below (territory managers, etc.) were permitted to participate.”
This is not who decides what is 'permitted', which is of course within the purview of the SEC. The piece states:
> Why didn’t I bring these allegations to the proper authorities to investigate? I did and was essentially told to get lost
No, the author went to the IRS Inspector General, which is very much not the SEC. The SEC has a very popular (oversubscribed) whistleblower program which awards millions to those who provide material information or tips relating to such cases.
This article is, ahem, not credible.
Discussions can take you fairly far into the weeds but you learn a heck of a lot.
Most of that 60% for Fidelity's funds don't end up back in Fidelity's pockets either, but instead in the pockets of the people who borrowed stock from Fidelity investors in the form of rebates. You can understand this like: the borrower puts up 100-105% of the collateral and so should get some portion of the short-term rate on that cash. It's not clear why the disparity exists between Vanguard and Fidelity though.
iShares is truly different where they actually take 15-30% of profits for themselves.
Anyway, loans are marked to market daily with collateral required. Details are here: https://personal.vanguard.com/pdf/ISGSL.pdf
It is absolutely a risk, but I think you err by saying index funds are supposed to be low risk.
Also, Vanguard as a corporation is owned by its fund shareholders as opposed to external shareholders while Fidelity is owned by a private group. I don't trust any company enough to lock up my money with them and possibly have to pay capital gains tax to switch later, if they decide to raise fees or make the investment not align with shareholders in some respect. As whitepoplar says, they're a profit-seeking entity. Due to the inverted corporate ownership structure of Vanguard this is not a concern. This argument also applies to iShares.
This is untrue. Per iShares(https://www.ishares.com/us/literature/brochure/securities-le...):
> Q: How much of the securities lending proceeds are paid to iShares ETFs?
> A:. iShares ETFs receive 71.5-80% of the income generated from securities lending depending on the asset class held. For example, iShares ETFs that predominantly hold US equities receive 71.5% of the income from securities lending. All other funds (i.e., fund-of-funds and funds that invest predominantly in fixed income or international equities) receive 80% of the income from securities lending. Once the aggregate securities lending income exceeds a certain income threshold amount, each iShares ETF will receive an increased percentage of the income above original levels, i.e. from 71.5% to 75% for US equity iShares and from 80% to 85% for all other iShares, for the remainder of that calendar year.
By the way, Fidelity isn't making money off of securities lending on these funds, or at least has pledged not to. I still wouldn't use the funds, though.
> "Fidelity is not receiving any revenue from the Fidelity ZERO Index funds for securities lending. Nor is Fidelity currently receiving any portion of the income that is generated from securities lent out." --Fidelity August 1, 2018
However, their securities lending practice is significantly less efficient than Vanguard: their total stock market index fund returned only 40% of securities lending revenue to the fund while Vanguard returned 94%. The difference there is in broker rebates -- how much of the interest on loan collateral posted by the borrower goes back to the borrower. For some reason Vanguard seems to be doing a much better job on this (possibly Fidelity is much more aggressive in loaning out shares so receives less benefit).
I agree with much of your comment, but there is a great deal of serious numerics which doesn't use sparse linear algebra at all. In fact there are entire subfields of numerical analysis which involve fast algorithms for dense linear algebra.
You're correct that the innovation is really about sparse linear algebra (though not just solvers) done in hardware. However the advantages are exploited not just by way of solving linear systems for implicit time-stepping. They implemented a Jacobi iteration in hardware for solving a system arising from discretization of the Poisson equation, but they also used an efficient forward-map of the coefficient matrix to do explicit time-stepping for a wave solver. So they solve both a time-independent and time-dependent problem, but neither with implicit time-stepping (though there appears to be no technical limitation here, it's just what they focused on).
For others who want a comparison; the two papers are very different: the Nature paper uses entirely analog techniques to achieve high precision results while the newly-linked article is a mixed-precision approach. That is, the newly-linked article only uses analog to obtain a low-precision estimate which is fed back to a digital computing algorithm to produce the final high-precision result. The hope is that the overall time to solution is still faster because you do not need (hopefully eventually slower) digital computation to achieve the low-accuracy result. I am not an expert in this particular hardware field (I do applied math so I am used to solving the problems they do here in digital computers), but here is what the authors of the Nature article say:
> Recent theoretical and experimental studies have used memristor (including phase-change memory) arrays to generate an initial, low-precision guess (seed), and rely on an integrated high-precision digital solver to produce the required high-precision solutions from the seed solution. Such types of accelerators are certainly beneficial, as they reduce the number of iterations required by the digital solver. Determining whether memristor-based hardware can be used to directly perform high-precision computing tasks, however, will enable a better understanding of how broadly memristive hardware can be applied. Such knowledge will help pave the way to build more general memristor-based computing platforms, instead of special-purpose accelerators.
Past performance is no guarantee...
This is a very subtle question which is far from resolved[1] in the academic literature; it is nowhere close to the slam-dunk you state it is.
[1]: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3122326