By Jacob Wolinsky. Originally published at ValueWalk.
Logica Capital commentary for the month ended May 31, 2022.
Logica Absolute Return (LAR) – Upside/Downside Convexity – No Correlation
- Tactical/dynamic balanced Put/Call allocation – Straddle
Logica Tail Risk (LTR) – Max Downside Convexity – Strong Negative Correlation
- Tactical/dynamic downside tilted Put/Call allocation – Ratio Straddle
The S&P 500 Index closed flat for the month, but the path there was anything but smooth. In fact, it broached its lowest point since March 2021 before recovering its losses during the final week of the month. And in terms of volatility, despite the S&P 500’s flatness on the month, VIX gave back materially with a more than 7 point decline. Our strategies successfully withstood this heavy implied volatility decline largely due to successful trading/scalping and overall delta positioning.
- Returns are net of fees and represent the returns of Logica Absolute Return Fund, LP and Logica Tail Risk Fund, LP, respectively. Past performance is not indicative of future results.
- Naïve Straddle Return: a 1.5 month out, S&P 500 at-the-money put and call bought on the final trading day of prior month and sold on the final trading day of current month. This return on premium is divided by a factor of 6 to be comparable to Logica’s typical AUM-to-premium ratio. For illustration purposes only.
- Naïve Ratio Straddle Return: a 1.5 month out, S&P 500 at-the-money put and at-the-money call (divided by 2) bought on the final trading day of prior month and sold on the final trading day of current month. This return on premium is divided by a factor of 6 to be comparable to Logica’s typical AUM-to-premium ratio. For illustration purposes only.
Commentary & Portfolio Return Attribution
* For illustration purposes only. Attribution returns are composed of daily returns, gross of fees
“Success is the sum of small efforts, repeated day-in and day-out.” – Robert Collier
As an overall feeling in May, we were very satisfied with our ability to preserve capital given what would generally be difficult market conditions for long volatility. As we can see above, our S&P Puts provided a strong positive contribution despite a flat underlying market (S&P 500 +1bps) and dramatically diminished implied volatility (VIX -7.2 points) MTD.We consider this success simply the other side of the coin from last month’s outcome, where our scalping/trading, following the very same process, simply “got it wrong” vs the market’s behavior. While we communicated our frustrations on this front in our April letter, we of course emphasized that one must stick with a strategy that one believes in and it will bear fruit (provided, of course, that the “believe in” comes from a backdrop of rigorous research and testing, infused with a blend of empiricism and experience.). A baseball player that’s struggling for a few games, but has a sound approach and is hitting the ball hard will eventually break out of that slump. We talk about baseball a lot because it’s a sport whose analytics really focus on “peripherals” rather than exclusively on outcome. Baseball tends to have a lot more randomness in its outcomes than other sports, which makes it a good analog for trading markets – all a batter can reasonably do is hit the ball hard; after that, he doesn’t have much control over what happens (whether it goes directly to a defender, or not). Similarly, all traders can do is go with the favorable odds and let the pieces fall where they may. Over time, given one has a probabilistic edge, one will come out ahead.
Calls were predictably flat across the board, while Gold detracted from our Macro Overlay performance on the month.
For a little more color on our scalping this month as compared to last, we can revisit a graphic we shared last month. This chart plots our overall delta notional positioning, separated into quadrants (we show the LAR strategy here, but as LTR is simply a direct derivation of LAR, the same outcome applies).
We can see many more successes in May than in April, and likewise fewer outcomes in the bad/very bad regions:
Not only was the hit rate positive in May (more “goods” than “bads”), we can also see that the magnitude of the misses were, on average, smaller than the magnitude of the wins. More extra base hits than strikeouts, you might say. Of note, in our prior month’s letter, in aims to highlight the anomaly of April’s outcome, we shared that this positive skew has been the case for us historically, wherein over the prior 18 months, we similarly demonstrate a higher hit rate alongside larger magnitude wins. And so, ironically, this “back to normal” for us in May further substantiates – and illuminates — the starkly contrasting outcome in April, and the value of sticking with what we “believe in.”
Our vega scalping was also nicely positive skew with some big wins alongside a hit rate of about 50%:
This kind of trading success is especially important in a month like May, where we saw truly historically bad/anomalous implied volatility/VIX outcomes.
At the risk of sounding like a broken record, IV levels continue to be incredibly muted:
This isn’t entirely unexpected, as realized volatility, even though it has been rising in 2022 YTD, has not approached the levels of other crises. In short, as everyone is likely tired of hearing by now: rather muted volatility accompanying a rather measured grind downward for the S&P 500.
“The central idea in The Black Swan is that rare events cannot be estimated from empirical observation because they are rare.” – Nassim Nicholas Taleb
Separate to that, there was one more data point that we found rather anomalous, and so worthy of sharing. As of May 20th, essentially the low point of the month (the 19th close was slightly lower, but the 20th had a lower intra-day mark), we saw a clear outlier, with both the S&P and Implied Volatility concurrently down solidly on the month.
At that point in the month, VIX was down about -4 points, and the S&P was also down more than -5.5%, per the red dot in the green box! And as per the black dot in the green box, there was only one historical comparable to this. And yet in this comparison is where it gets even more crazy: that black dot (in the green box) is November 2008, during which VIX was coming from nearly 60 – which, to state the obvious, is drastically higher than the 34 level from which we entered May! Historically, the higher implied volatility/VIX is, the more likely we are to experience this phenomenon where we see an average return for IV over the following days to be substantially negative, and more importantly, where we see things like market down in combination with implied volatility down. But rarely does this happen from the <35 level on VIX.Outside of the month’s low, we saw this pronounced on May 11th, with the S&P down -1.65% on the day, and VIX also down. Coming from a level of 32.99 the prior day, we can see that we’d expect VIX/IV to be up at least a couple points given an S&P move of the same magnitude:
[data points where the prior day VIX close was +/- 2 points from 32.99]
Unsurprisingly, as the S&P rallied over the final week of trading, VIX deteriorated. The S&P closing nearly exactly flat on the month gives us a nice look at what VIX has done historically when that has similarly been the case:
As may be evident, these charts are certainly all viewing the same phenomenon from numerous angles. We do so not only to lament the muted move in implied vol (though we certainly do that internally!), but also to provide a window into our processes and some of the things we look at in real-time. More broadly, all of these variables, and associated data points, are part of our models and discretionary decision-making processes, such that having these at our fingertips is both informative and essential.“A good tool improves the way you work. A great tool improves the way you think.” – Jeff Duntemann
We’ve said before that because we’re long-only in our expression of long volatility (gross long vs. spread trading to arrive at net long), we can think of our trading decision each day coming down to 2 main variables: delta and vega (and of course, their derivatives, including gamma and volga, etc..). But while 2 seems like such a small number, and just a tad more than 1, that second variable dramatically increases the complexity of potential outcomes. The assessment of direction (delta) is what millions of speculators and machines are focused on daily, leaving a straightforward “time” vs. “price” pnl plot to contemplate. In our world, we add a Z-axis to this 2-dimensional pnl graph to evaluate the “volatility” of the path over that “time” to get to that “price”. Fortunately, we have rigorous ways to process and visualize these variables and their complex interactions, and to output our risk/reward in real-time; and thanks to years of painstaking R&D, we have advanced tools to run scenario analyses and put boundaries around these paths. In short, we’re very proud of our level of preparation. Going back to our cherished baseball analogy, our goal is to put ourselves in the best position possible to hit the ball the hardest. Sometimes, like in April, it’s hit right at a defender (or, we strike out!). Other times, like in May, we hit doubles and home runs.
Finally, turning to take a look at our strategies vs the S&P 500 during May, despite a disappointing final day of trading, we see LAR nicely uncorrelated, and LTR nearly exactly negatively correlated.
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