Reasonable ways for an average LW retail investor to get upside risk?
post by Randomized, Controlled (BossSleepy) · 2021-02-16T19:44:17.277Z · LW · GW · 6 commentsThis is a question post.
Contents
Answers 19 SimonM 5 Sierraescape 3 gilch 3 gilch 3 lifelonglearner 2 waveman 2 ChristianKl 1 benjaminikuta None 6 comments
By "upside risk" I mean: more upside risk than just holding the market.
By "reasonable" I mean: will not require an arbitrarily long education process to understand/carry out. I work a day job and have other commitments in my life, and I'm not that fundamentally interested in finance/investing. I'm not trying to get anywhere near an efficient frontier, I just want to be able to get upside risk more systematically than "some smart seeming EA/LWer drops a stock/crypto tip in a facebook group".
By "average": I assume I'm close to the LW median: I'm comfortable making kelly bets in the $1k - $100k range, depending on details. Mostly in the $10k range.
Are IPO ETFs a good candidate for this? SPACE SPAC ETFs? Buy and hold cryptocurrencies that aren't BTC/ETH? Buy and hold BTC/ETH? Sell random call and put options? Something else? Emerging markets ETFs?
Answers
TL;DR Leverage
"Upside risk" I am going to divide into two categories:
- Skewed returns - "Bets with a payoff which is either very large and positive; or small and negative"
- Outsized returns - "Bets with a higher mean return"
It seems to me that you're mostly thinking in terms 1. There are plenty of ways to do this systematically;
- buying options [Buying SPACs slightly above NAV is roughly equivalent to buying options]
- buying insurance
- buying early-stage growth stocks
- buying lottery tickets
- betting on dogs
They all have a range of distributions but largely they are money-losing (on average). The reasons for this are fairly straightforward. Everyone likes lots of upside, with limited downside, so those bets get bid up and their expected returns fall. Personally I think these are a bad thing to do systematically*. You need to be deriving some value from the "excitement" for these strategies to be compensating you for the average loss you're taking.
* Where you're hedging some personal risk and paying over the odds to do it (health/home insurance) then you should do it systematically.
More interesting to me is how can retail investors achieve 2. without losing their shirts. (You mentioned a few of these (selling options, EM equity)). Off the top of my head there are a few different ways to boost your returns systematically (roughly in order of how "good" I think they are for retail):
- Leverage
- Equity factors (momentum, value, etc)
- Vol risk premium
- FX/Rates carry, CDS premia, ...
- "Alpha"
People have already mentioned vol risk premium. (Mostly expounding it's virtues). To give a bear case on this. This strategy can definitely become crowded. Even before the March '20 sell-off, vol sellers had had a terrible run from 2018-2020. Personally I believe that VRP exists, but it's not a premium I'd want to collect as a retail account. The market is pretty sophisticated and most of the ways to express that trade are full of nasty gotchas.
There have also been a few discussions of alpha. (Or at least the idea that LW-ers can beat the market in some risk-adjusted sense). For someone uninterested in finance, I think this is extremely unlikely - and probably going to end badly.
I think leverage is broadly underrated by retail. Margin accounts are getting cheaper and cheaper, and running a leveraged (say) 60/40 portfolio is becoming increasingly viable. This will increase risk and returns. You will pay some cost for the leverage, but this is by far the cleanest way to boost your returns in my option.
Equity factors - momentum, value etc. There's hundreds of these factors now all with a range of "acceptance" within the finance community. Access to them is becoming much easier (factor ETFs are a thing).
Carry etc - ... There's a bunch of different strategies which fall into this bucket. I'm not going to say a huge amount about them because I think this is something which is really worth doing your own research on. They are accessible to smart retail investors, but you will need to think carefully about what your strategy is,
↑ comment by Annapurna (jorge-velez) · 2021-02-17T19:21:55.502Z · LW(p) · GW(p)
I came in here to say leverage. There are options outside of margin lending that are interesting to explore, such as:
Investment Loan (Although the rate is similar to that of a margin loan)
Home Equity Line of Credit (Cheaper than the above)
Borrowing to re-investing and pledging your assets as collateral has been used for decades by wealthy investors to increase their return.
Replies from: gilch↑ comment by gilch · 2021-02-17T21:35:11.901Z · LW(p) · GW(p)
Box spreads. [LW · GW] That's still margin though.
Leveraged ETFs.
Leverage is very important for maximizing returns, but too much is counterproductive. Sometimes even 1x is too much, or even 10x is not enough. The right amount is the Kelly fraction and it depends on the payoff distribution of your strategy, which you can only estimate. This is mostly what I was getting at in How to Lose a Fair Game [LW · GW]
↑ comment by gilch · 2021-02-17T21:27:49.770Z · LW(p) · GW(p)
They all have a range of distributions but largely they are money-losing (on average). The reasons for this are fairly straightforward. Everyone likes lots of upside, with limited downside, so those bets get bid up and their expected returns fall. Personally I think these are a bad thing to do systematically*.
This is basically what I was trying to say in The Wrong Side of Risk [LW · GW].
↑ comment by Randomized, Controlled (BossSleepy) · 2021-03-07T23:14:25.457Z · LW(p) · GW(p)
Hi, thank you for the comments! Do you have any preferred resources for learning about leverage investing/using a margin account?
Hi! I've made ~800% over the last 6 months with a basic strategy of selling options on highly volatile stocks (which I am confident in) and buying cheap OTM options on less volatile stocks to take advantage of any black swans. One of those black swans was GME, and without GME I'd be closer to a 250% or so increase (take that how you will).
A pretty safe strategy imo is to put most of your account into near-NAV SPAC's, then use margin to sell puts on stocks you would like to own. The SPACs have very little downside risk, and selling puts is fundamentally less risky than owning the stock itself, but you have potentially high returns if the SPACs do well or you are selling puts on highly volatile stocks.
In general, I believe the average less wronger to be more intelligent than the average trader (possibly even the average professional trader) and thus capable of achieving steady returns which beat the market. Maybe this is just survivorship bias talking, though.
↑ comment by SimonM · 2021-02-17T08:38:49.471Z · LW(p) · GW(p)
Kudos on your great returns. I don't have any particular quibbles with your strategy although I would caution other people to think hard about whether or not they have a good sense of what is "cheap" or "expensive" when it comes to single stock vol. Ending up on the wrong side of the next GME will be very painful.
In general, I believe the average less wronger to be more intelligent than the average trader (possibly even the average professional trader) and thus capable of achieving steady returns which beat the market. Maybe this is just survivorship bias talking, though.
The "average trader" is not a particularly good benchmark. Performance is very skewed, and the vast majority lose money. I am assuming by "average" you are referring to median. The mean trader breaks-even (mechanically) as we're talking about a zero-sum game.
"Intelligence" isn't the only relevant skill. The difficult parts of trading are not usually "being smarter than the market" but things like:
- Having high quality information
- Having high quality execution
- Temperament
Replies from: waveman
↑ comment by waveman · 2021-02-26T00:06:38.590Z · LW(p) · GW(p)
the average trader
The average retail trader underperforms the market by 4-5% per annum before costs. Far worse than this after costs. Yes they have negative skill.
The average professional fund manager outperforms the market by less than 1% before the costs they charge to the punters. After costs they underperform.
The average professional fund manager works very hard and has studied finance for years.
My point is you need to do a lot better than average to win.
Buy SVXY in small amounts [LW · GW], and keep your exposure to it balanced (i.e. regularly pull excess money out so you don't lose it all when it inevitably crashes hard). It's a short-VIX ETF, which makes it kind of similar to selling straddles on a big index, but you don't need a margin account since it's an ETF. It's also a lot less hassle than rolling options every month.
You can also manually apply something like the VXTH hedging algorithm that I mentioned in my other comment to this one.
↑ comment by Randomized, Controlled (BossSleepy) · 2021-03-08T23:46:18.615Z · LW(p) · GW(p)
What. In. The. World. Happened. In. 2018.
SVXY falling off the cliff looks like it was associated with a spike in VIX, but why didn't the previous, bigger spikes have the same effect, sooner?
[ETA]: "For example, SVXY was crushed in the volatility run-up of 2018. The instrument has since reduced leverage to half exposure..." That may explain the shift in behavior since 2018, but not what happened leading up to it. Altho perhaps that might be sufficiently explained by the counter-intuitive behavior of leveraged/inverse ETFs -- this page on the SEC's site actually has a surprisingly good explain-it-like-I'm-twelve:
How can this apparent breakdown between longer term index returns and ETF returns happen? Here’s a hypothetical example: let’s say that on Day 1, an index starts with a value of 100 and a leveraged ETF that seeks to double the return of the index starts at $100. If the index drops by 10 points on Day 1, it has a 10 percent loss and a resulting value of 90. Assuming it achieved its stated objective, the leveraged ETF would therefore drop 20 percent on that day and have an ending value of $80. On Day 2, if the index rises 10 percent, the index value increases to 99. For the ETF, its value for Day 2 would rise by 20 percent, which means the ETF would have a value of $96. On both days, the leveraged ETF did exactly what it was supposed to do – it produced daily returns that were two times the daily index returns. But let’s look at the results over the 2 day period: the index lost 1 percent (it fell from 100 to 99) while the 2x leveraged ETF lost 4 percent (it fell from $100 to $96). That means that over the two day period, the ETF's negative returns were 4 times as much as the two-day return of the index instead of 2 times the return.
Still. Curious.
Replies from: gilch↑ comment by gilch · 2021-03-09T17:34:23.334Z · LW(p) · GW(p)
I think it's not so much the height of the spike that did it that time, but that combined with how low the VIX was just before that spike. Inverse ETFs are strange beasts. There's no hard limit to the upside of what they're tracking, but the inverse ETF can't drop below zero, and this is a good thing compared to shorting the underlying yourself, since it caps your losses. For daily-tracking inverse ETFs with 1x leverage, a one-day move of the underlying of 100% of its previous day's value would mean a total wipeout. For a 2x inverse ETF, it would only take a 50% move. Also remember that SVXY trades short-term VIX futures, not the VIX itself, which is just an index formula and can't be traded directly. The February futures went from about 16 in the morning to over 30 in the afternoon on February 5th, 2018. A similar ETF, XIV, gave up and liquidated itself at the same time.
SVXY is a great investment. In small amounts—small enough that you could tolerate it dropping to zero overnight, which could really happen someday! Leverage down!
[Obligatory disclaimer: I currently have a small SVXY position. I usually do.]
ARKK looks interesting. It's an ETF focusing on "disruptive innovation", so its upside is potentially pretty high. It's done quite well so far (its biggest holding is currently TSLA), but, as always, that's really no guarantee of future performance. It's hard to separate skill from luck, especially with so little data. I don't currently hold this one, but if I were looking for more "upside risk", it's one I'd consider adding to my portfolio.
For crypto:
- buy btc
- buy eth
- buy defipulse index
For even higher variance crypto:
- buy defi small cap
- get eth, turn it into st-eth/eth LP on curve.fi, and then stake into the harvest.finance st-eth pool for ~30% APY on your eth
Anatomy of a bubble.
1. People are not interested
2. People ask for advice on getting into the market.
3. People give experienced traders advice on trading.
4. Crash.
I'd say we are between (2) and (3) at this stage.
For a cryptocurrency I consider Filecoin to be potentially high upside. It makers focused on producing a technology that can do new things (effectively selling storage) instead of hyping it.
There's an accelerator for projects that build on Filecoin.
With Amazon deciding to withdraw hosting from Parler there a clear incentive to use decentralized hosting like that provided by Filecoin.
I was also wondering about this.
The economists behind Lifecycle Investing suggest deep ITM SPY LEAPS. This works as leverage in an IRA or similar account.
I also like to use a little bit of margin and I prefer to keep as much money as I can in my Interactive Brokers account, with the idea that I can use the margin loan in lieu of an emergency fund or other savings.
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comment by gilch · 2021-08-28T20:51:19.967Z · LW(p) · GW(p)
I recently stumbled across Taleb's barbell strategy. His thesis is that due to unknown unknowns (black swans), trying to manage a portfolio of (supposed) medium-risk investments is pointless; their true risk is impossible to compute, so you can't tell if you're overbetting or being compensated well. You can be ruined by a miscalculation. Instead, one should invest in a linear combination of extremely safe and extremely risky bets, which are both easier to quantify, to achieve a net medium-risk portfolio. You insulate yourself from the rare risks and expose yourself to the rare benefits, while avoiding the dangerous darkness of the middle ground.
A barbell portfolio might keep 90% of in conservative low-risk investments designed only to preserve capital and use the remaining 10% on speculative bets, which usually fail but occasionally pay off big.
The conservative side might be things like FDIC-insured American savings accounts, Swiss bank accounts, short-term treasuries/T-bills, short-term TIPS, and maybe a basket of precious metals.
The speculative side might be things like index put LEAPS, cryptocurrency, memestonks (sic), biotech startups, etc.
comment by gilch · 2021-02-17T04:26:01.077Z · LW(p) · GW(p)
The random calls and puts was more of an existence proof of the option seller's edge than an actual strategy.
Still, selling puts on big index ETFs is a good strategy, but it's one with negative skew. When the market crashes (and it eventually will), you'll lose a lot of money. As always, don't bet over Kelly. It's been working well for me so far, but I'm also hedging with VIX calls so I don't get wiped out next crash. The VXTH index uses a straightforward algorithm you could do manually to defend your short index puts with VIX calls. You'll get the best returns by selling slightly in-the-money (ITM) puts. (I'm not comfortable with that much variance, so I use out-of-the money (OTM) puts and hedge more than that at the cost of profits, but you might be OK with it.)
Selling straddles on big index ETFs is arguably a better strategy (if you can stomach it), but in small amounts since it's even more skewed than puts alone. The advantage here is that only one side can expire in the money, so playing both sides doesn't affect your margin requirement much, but almost doubles your premium. You could also use the VXTH defense on these, plus maybe a cheap far-OTM call, since short risk is potentially unlimited otherwise. You still need a big enough account to handle that much skew without betting over Kelly.
Negative skew is easier to deal with the more your account is diversified, since it tends to not happen all at once that way. These shouldn't be your only strategies.
Replies from: SimonM↑ comment by SimonM · 2021-02-17T08:43:50.746Z · LW(p) · GW(p)
As always, don't bet over Kelly. [...] without betting over Kelly
You mention Kelly twice in the context of selling options on indices, but it's not clear to me how a "average LW retail investor" is supposed to calculate their edge.
Replies from: gilch↑ comment by gilch · 2021-02-17T18:15:48.399Z · LW(p) · GW(p)
In the case of a deep in-the-money cash-covered put, performance is pretty similar to simply holding the stock. (Less deep is synthetically equivalent to a covered call.) Historically, leverage of about 2x does better when holding the index, so as a rule of thumb, a 50% covered index put seems about right, but this can be adjusted based on current volatility levels.
I touched on Kelly a little bit in How to Lose a Fair Game [LW · GW]. To calculate Kelly properly, you need to know your payoff distribution. In practice, you can't know this, but you can estimate it from historical price data, which is better than pulling a number out of your nose, but still highly uncertain. If you under-bet a little, your returns are suboptimal. If you over-bet a little, your returns are suboptimal, and you have to endure much higher volatility. (And if you over-bet a lot, you'll wipe out.) Since the consequences of betting a bit under Kelly are less bad than betting over Kelly, and your return distribution is uncertain, it's best to think of the Kelly fraction as an upper bound, rather than a target.
In particular, for a single asset, the formula becomes
Where is the drift, is the risk-free rate, and is the volatility. Future volatility is much easier to predict than future price. Even a simple moving average of historical volatility over the last month is probably a good enough estimator for our purposes, but you can do better with a GARCH model or something.
Replies from: ErickBall↑ comment by ErickBall · 2021-02-19T15:07:27.673Z · LW(p) · GW(p)
The Kelly criterion is intended to maximize log wealth. Do you think that's a good goal to optimize? How would your betting strategy be different if your utility function were closer to linear in wealth (e.g. if you planned to donate most of it above some threshold)?
Replies from: SimonM↑ comment by SimonM · 2021-02-20T10:07:51.953Z · LW(p) · GW(p)
This isn't quite the right way to think about Kelly betting. Kelly maximises log-wealth after one bet. This isn't quite the same as maximising long-run log-wealth after a series of such bets. In fact, Kelly betting is the optimal betting strategy in some sense (leading to higher wealth than any other strategy).