The Earth rotates around the Sun at a speed of 67,000mph. When I go out for my occasional run, my own speed is in the tens of thousands of miles per hour. Should I take credit for this amazing performance? I wouldn’t be completely lying if I bragged about this with friends (which I do); but it would be more transparent if I mentioned that my speed record is in the frame reference of the Sun. In this frame of reference, my speed is indistinguishable from Usain Bolt’s. This factoid obscures the vast difference in skill between the two of us. To really understand the difference, we need to change the frame of reference. Another way to interpret the decomposition of returns is a method to change the frame of reference in investing. Total returns – and a portfolio’s total PnL – live in the Sun’s frame of reference. It is easy to fool ourselves with the belief that we beat birds, airplanes and supermen at their own game. Idiosyncratic returns and PnL live in the Earth’s frame of reference. If we want to compare our performance to that of our peers, or to our very own past performance, we need to move to this frame. Factor-based performance attribution makes it possible.
– Giuseppe Paleologo (via Advanced Portfolio Management)
When I think of the “heyday” of hedge funds in the early 2000s I picture a bunch of cowboys who became generationally rich riding a steed named Greenspan. “Hedge” funds? How about beta boys?
I’m writing in between sips of hatorade because I remember the contrast of working in trading vs seeing peers in asset management. They had “points” in the bonus pool. Meanwhile traders had “I know you made all this extra money but we think your pit was more lucrative then expected. We don’t pay extra for good luck”. And to be fair, I also saw the flipside where traders got paid well despite having a tough year because they made good decisions that had a lot of noise (an amount of noise the firm was willing to underwrite and not penalize you for — the whole “not resulting” thing isn’t just marketing — it’s load-bearing).
[Side note: cultures like that are hard to build and rest on constant communication and buy-in for situations where the opportunities might outsize your specific trading assignment and you need to “recruit” the mothership’s approval either implicitly or literally by storing some of the trade in an account whose p/l you don’t need to stare at every day. The old-school “back book” except you know about it because you were the one who alerted management to the situation.
The other thing such cultures rest on is “permanent capital”.]
The triumph of pod shops has been to operationalize trading firm epistemology, then maximize the fee they charge for blue meth. The job of a PM is now as hard as Walter White’s life for the same $10mm in comp you could have gotten 20 years ago.
When it comes to the retail investor, the conventional wisdom gets it pretty correct — almost everyone should be using low cost indices to construct diversified portfolios and get back to the competitive advantages in their daycrafts.
The retail world can be further divided into retail traders (the more sophisticated ones are sometimes called “prosumers”) and retail investors who “sin” by trading in haphazard ways as if NVDA earnings was the point-spread of the big game on Sunday. In both categories, there are no external demands for retail to be honest with themselves about their returns on effort in trading.
Which is basically, well, fine.
I don’t want my tone to be misconstrued — I’m not here to wag a finger at anyone. Serious traders, the ones who depend on edge to eat, get this. If you trade actively but less seriously then presumably you have some other means to knock out the rent so it’s hard to muster solemn concern for you.
But you can still upgrade your thinking massively by stepping through attribution.
On Sunday, I published a slutty post-mortem on a GLD trade that worked (and continues to work this week). I also promised to step through a trade that was not flattering because I think it’s loaded with lessons.
Let’s go through an option trade I did in IWM back on 7/17/24, a few days after the “small cap rotation” pushed the Russell up 10%.
On July 17th, with IWM trading about $222.50 after a 10% rally over the prior days, I got a hankering to rebalance out of my shares. I consulted the mowing lines the gardener left in the grass and their pattern said “no need to buy something just trim net portfolio length.”
I pulled up moontower.ai and several views told me the vol seemed high.
Cross-sectionally:
The 30-day IV was elevated and with 1m-6m term slope “in line” other names with high implied vols I simply zero’d in on the 3m or October expiry.
Now I wanted to look cross-sectionally at how the options were “carrying”. I was looking for high VRP.
Cross-sectionally or relative to other names, the VRP didn’t stand out as excessive. It’s smack dab in the center of the chart. But there are 2 pieces of context swirling in my head:
- The entire VRP map is elevated. The mean VRP shows that on average IVs are trading at a 25% premium to realized vols. If you look at a chart like this every day, you know it’s more typical for that premium to be closer to 10%. If IVs were clustered towards the low end then a fatter VRP for the market could be expected but this isn’t that kind of clustering (toggle summer 2023 vols to see what low vol world looks like).
- This IWM VRP already incorporates the large move from the prior week in the denominator
On a relative basis I’m satisfied that IWM vol looks rich.
Let’s now examine IWM compared to its own history:
Getting confirmation.
That VRP is on the high end not just absolutely but also relative to the RV percentile.
Let’s look at the time series:
The 90d vol was a tad high relative (the October options were about 21% vol even a bit higher than what you see in this snapshot) to the realized vol sustained over rolling 3-month periods over the past year. This is not strongly confirming but it definitely doesn’t detract from the case we’ve built thus far.
One last check…what about if we zoom out to a 3-year lookback:
Selling vol at 21% is not attractive from this view with the IV being below the median rolling 3-month realized vol since 2021.
The trade looks good on 1 year lookbacks but not on a 3 year look. Insert the Larry David indecision meme.
Well, I never buried the lede…I told you I sold October IWM options. This tells you my bias is to discount old info heavily. 2021 might as well have been a different decade. I’m more inclined to look further back if I’m considering a high duration trade but we’re talking a 3-month option here.
Pulling the trigger
Instead of selling my IWM shares, I fully covered them by shorting the Oct24 220 strike calls at $11.82 on 7/17/24 (94 DTE). The stock was trading $222.22
On 8/23/24, 37 days later, I revisited the trade and that’s what inspired this post.
The calls were marked at $7.94 and the stock was at $220.38.
A walk in the park, right? $3.88 of profit and the stock is only down $1.84
Let’s really understand how to think about this.
First, looking at what I call the unhedged version of the trade — sell the calls, go on vacation.
$1.07 of the p/l is due to delta. It’s not pertinent to evaluating an option trade because you could have generated directional or delta p/l by selling shares.
$2.81 of the p/l comes from the fact that 37 days have elapsed and the option is worth less. Implied vol was basically unchanged point-to-point from 7/17 to 8/23.
So this $2.81 gain is due to theta purely. But this is naive way to look at the trade because are inspecting the result when the stock happens to close to the price it was back at the start. If we chose a different time, and we will, you can see the folly in resulting from point-to-point outcome. And even the “different” snapshot we choose will be arbitrary, it will just show a totally different result. The point is this entire approach of opening our account and looking at the p/l teaches us nothing about whether an option trade was “good” or not.
The chassis for properly understanding vol p/l is laid out by platonic example in:
Dynamic Hedging & Option P/L Decomposition
and by simulation in:
Simulating Dynamically Hedged Option Positions.
But here we will simulate daily delta-hedged p/l for the trade IWM calls I actually sold and the daily prices that ensued.
This table is straightforward.
- stock and option marks come from the market
- option greeks and vols come from moontower.ai
- p/l data assumes you hedge daily based on the marks and greeks
General observations before we discuss p/l
- The IV on the 220 strike started and ended very close to 21%
- The sample realized vol is 1.82% per day or 28.9% annualized (nearly 50% higher than the implied vol that was sold). This is based on 27 daily return observations.
- Based on the realized vols, a 2 standard deviation move larger than 3.64% (ie 2 * 1.82%) would be expected at least once. There were zero. It’s therefore not surprising that the MAD or mean absolute deviation was greater than 80% of the standard deviation. (When the ratio is less than 80% it indicates a fat-tailed or skewed distribution). This observation isn’t central to this post but just thought I’d point it out. The topic is covered further in 👿The MAD Straddle
P/L
On a daily delta-hedged basis, this trade lost $1.60 per contract. Considering that the extrinsic portion of the call option was $9.60 when I sold it, this was a terrible trade.
Charted:
From the simplest perspective — I sold vol at 21% and it realized close to 29%. There’s no redeeming aspect to this. Was I unlucky? Sure, being short almost any option going into the August 5th volquake hurts.
But I’m less interested in the reason for the p/l versus the ridiculous framing where one looks at the result of making nearly $4 on shorting this call and thinking they were on the right side of vol history.
For people still early in their options learning, I can sympathize with what they are thinking — “Kris, this kinda makes sense, but you wanted to trim IWM length and selling calls worked…aren’t you just being pedantic? Does this even matter?”
My view is it not only matters, it’s all that matters. You chose an option as your weapon and the market wore exactly the right armor against your assault. That you happened strike a blow at all, based on when you looked at the outcome, is to not understand how badly you lost the fight. And without understanding that you can’t learn about the only thing that options depend on — they are always vol trades.
I’ll rattle off a more observations in hopes that one of them is the right key to turn:
1) The short call made $3.88 but $1.07 of that was delta p/l. You can think of the $1.07 as the counterfactual p/l if I just sold 60% of my shares.
2) Imagine how I felt on the 8/7/24 snapshot… my short option p/l is +$8.36 but I’ve lost $20.34 on my 100% of my IWM shares that I didn’t sell instead for a total loss of $11.98 (the RV would have been 29.6% from 7/17 to 8/7).
To measure more fairly in this 8/7/24 scenario, let’s assume instead of selling the calls I would have sold only 60% of my shares. I would have rode 40% of my shares back down to $201.88 for a net loss of $8.14
3) The cumulative delta-neutral p/l chart bottoms out in sync with the largest move (3 consecutive down days with a magnitude greater than 3% each). If you would have sold the 220 call on 8/5 when it was a 30d and hedged daily you would have made money for the next 2 weeks even though the stock rallied back nearly 10% back to the strike!
This is because the down leg saw the 220 call IV go from 21% to 29.6%, while the upleg saw the IV roundtrip back from 29.6% to 21% again.
The downleg option position suffered both due to IV expansion (vega p/l) and high realized vol, the upleg won to vega and realized vol (rv from 8/5 to 8/23 was 23.8%, but remember if you sold vol on 8/5 you sold IV at 29.6!)
I’m a broken record —> options are always about vol.
If the implied is the main driver, it’s vega p/l.
If the realized is the main driver it’s the tug-of-war between gamma and its cost, theta. The cost, in turn, is driven by the implied. IV sets the hurdle on whether you win or lose to an option trade.
In today’s example, I sold an IWM call. I happened to win to it even though it was a bad trade (not in the sense that it was bad when I put it on, just that it realized a bad outcome that was masked by when I happened to look at it).
To be less fooled by randomness you can compute a delta-hedged p/l stream to get a clearer picture of a trade’s results.
If you don’t have that, you can compare the IV you traded vs the RV that was realized. This will be lower resolution that a delta-hedged p/l stream because vanilla option p/ls are sensitive to path but it’s better than just resulting.
In moontower.ai we now have a toggle that lets you see the time series of IV vs RV but the IV is lagged (so for example I can compare the 1 month trailing RV today vs the 1 month IV that prevailed a month ago).
This uses 50d IV. You can still see how the RV ramped up above the IV (this is using 90d RV to compare to 90d IV so its not as dramatic as the analysis above which showed the impact of the shorter window 29% RV on a 3-month 21% vol option. Plus the option I sold was not “constant maturity” but a regular option that becomes a shorter maturity with time).
We have the ability in our backend to simulate a delta-hedged option through time using actual market prices. It’s on the roadmap to create a front-end GUI for everyone.
