1️⃣ Some funds achieve capital efficiency in a tax efficient manner, and some do not.
e.g. $PSLDX buys bonds and overlays with S&P 500 futures. That's very tax inefficient, since those S&P 500 futures are taxed at a 60% long-term / 40% short-term rate.
NTSX, on the other hand, buys the S&P 500 and then overlays with U.S. Treasury futures. Those futures are also taxed at the 60/40 rate, which *can* be more tax advantageous than buy-and-hold bond exposure, where the majority of the return (yield) gets taxed at ordinary income.
2️⃣ We shouldn't overlook the value-add of asset location.
If we're willing to look at the combined portfolio achieved by holdings in taxable and qualified accounts, then we can put the least tax efficient holdings in accounts where taxes are not a concern.
3️⃣ Finally, while we should always seek to minimize taxes, we should consider that some of the taxes we may be paying are on returns we otherwise wouldn't be achieving.
It's like the 60/40 portfolio is a cake. Return stacking is the icing.
Even if taxes scrape some of that icing off, wouldn't we still want a cake with some icing rather than none?
Now, this assumes we're not paying *more* taxes to achieve the same underlying 60/40 exposure, and as we saw in 1️⃣ that may or may not always be the case. But, again, we can hopefully use 2️⃣ to our advantage.
In conclusion, taxes are one of the few levers we have control over. While we should strive to minimize taxes, we should also recognize that paying higher taxes is okay if it means we're achieving higher post-tax returns!
🛑
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2/ The expectation of low real returns going forward puts a significant burden on long-term investors striving to meet future needs.
e.g. Endowments who are making annual withdrawals, pensions that have future liabilities, and individuals who are saving for retirement.
3/ A phenomenon that we've witnessed over the last decade is investors moving up the risk curve by either (1) increasing equity exposure, (2) increasing credit risk (lower quality bonds), or (3) increasing liquidity risk (e.g. real estate, private equity or private credit).
I put $1 in $USDC.
You start a new project $COIN.
I buy 1 $COIN for 1 $USDC.
Someone else starts $TOKEN.
I buy 1 $TOKEN for 1 $COIN.
How much money is in crypto?
@John_Stepek So you’ve got a massive ball of “money” that bubbles up, but can’t ever really be removed. So it just rips around the space.
It’s L1 tokens one month, DeFi the next, NFTs the next...
@John_Stepek So unless (1) people can start to borrow fiat against their crypto / NFTs, (2) people try to move crypto into fiat en masse, or (3) businesses accept crypto as payment, I think you just get this risk of inflated bubble money.
I interpret @GestaltU’s point as reflexive: if everyone prepares for the last crash, then it’s almost impossible for a crash like it to occur!
@vixologist@AttainCap2@GestaltU I don’t disagree with either of those points. Adam’s point is one of the reasons that many on here – myself included – were saying that it would be hard to see a post-election crash last November.
@vixologist@AttainCap2@GestaltU I still think a lot of the same dynamics permeate the system (namely, excessive risk taken driven by low interest rates; adoption of systematic strategies; influence of options on underlying) – but the build up of risk that 🍋 alludes to may be gone for some time.
1/ Back in 2001, I used to play this game called Runescape (runescape.com)
(Which is still very much around, but looks nothing like it did when I played.)
2/ There was a whole world to explore, quests to complete, skills to learn, and players to meet.
3/ I sank hundreds of hours in the mines, clicking on rocks to mine ore, then hauling it back to town to smelt and then crafting it into armor to sell.
1/ I constantly get questions from people looking to go into graduate financial engineering (“FE”) programs.
I thought I’d compile my thoughts into a thread 🧵
2/ For context, I graduated from Carnegie Mellon’s MS in Computational Finance program in December 2010.
It was the world’s first FE program and, at the time, ranked #1.
Everything that follows is just my opinion based upon my experience.
3/ What are these degrees? They’re interdisciplinary studies (typically finance, mathematics, and computer science) that try to prepare someone for a career as a “quant.”