The Opportunity Equation
Vol #113: January 19th, 2023
This morning I downloaded six hundred eighty one thousand, nine hundred and sixty three strikes of options data. That’s more minutes than in a year, those moments so dear.
But none of it was exactly right. It didn’t tell me what or where to trade. Yet.
When you consider there’s a call and a put for each line, out of over one point three million different options quotes in the OCC listed universe (double that again for a bid and an ask prices), none of these closing market prices were directly the answers I needed.
The data that I use to track and analyze liquidity comes from a snapshot of the closing marks just before the bell. By taking a picture of the market a few minutes before closing time, you get the most accurate single view of where the day’s trading session settled the price of a specific probability.
The exact 4pm print isn’t used as a practical consideration with some small trade-offs. While you might miss the volume in the last six hundred seconds of the trading day, during this time market widths start to relax and don’t reflect the depth and texture of trading opportunities available during the day.
In the equities market, there is big volume on the close. Popular mechanisms introduced by the NYSE give large institutional players the opportunity to tie their orders to the closing print. Nearly $20b - 10% of the notional volume - trades here every day on the Big Board alone. If you have a large rebalance or end of day mark you’re trying to match, sending a “Market on Close” order lets you trade against all the other interest at a single settlement price.1
In options, it’s just the opposite - the open is when the fireworks jump off. Queued up overnight orders start percolating through proprietary data feeds an hour or so before the bell, and indications of interest jockey for position. When there have been 17.5 hours of closed markets (65.5 if it’s a weekend) people are willing to pay up for liquidity.
There are unique matching algorithms for the opening print that incentivize competitive bids. Crafty players will even mask interest with contraside orders canceled just before the open, revealing the true customer iceberg only a split second before they scoop it all for themselves. In low liquidity names there can be sumptuous berries of edge sitting out there.
The options market close looks more like the barkeep who sets his clock 15 minutes fast, sending late night revelers anywhere but here before the shift is over. You start sweeping up shop a little bit early, so that everything is tidy once that final bell rings.
Option market makers are constrained by hedging opportunities, and can’t risk a drunk barging in for tequila shots with seconds on the clock. Liquidity in the underlyings drives liquidity in the derivatives market. If a dealer can’t get a good stock fill, they’re going to post wider markets to compensate for this.
Getting planted with deep in the money calls in a thinly traded biotech only to hear the bell ring is a naked at school nightmare. Better to put your quotes $5 wide, or if you have the flexibility pull all together. A missed trade is a $10,000 burrito, but unhedged deltas into an FDA announcement are more expensive than finding the worm at the bottom of your Cuervo.
So when we use data to describe the options market, we have to be mindful of these considerations, and take a pre-close snapshot. But deciphering options data has more shimmers than just tracking for a dependency on underlying liquidity.
A stock is worth the market’s expectation of the future value of cash flows at any given moment. If time passes, the winds of change lie still, and there is no marginal supply or demand in either direction, the price will stay exactly the same. Options' most important feature is their expiration date, and price necessarily decays or changes with every passing second - even if all other inputs are exactly equal.
We can easily track how much the AAPL April 21, 150 strike call is worth over time. But those daily changes have limited meaning in isolation, it doesn’t reflect a changing stock price, term structure, or passage of time. To understand what inputs are really moving, we might ask more generally; how much does a 90 day, 10% out of the money call in AAPL cost over time? Is the skew relatively high or low right now?
Even with those millions of data points, the theoretically correct options price to track these values will practically never exist. In strike space it would be impossible to have every penny listed. In time space, while expirations every single day seem increasingly possible in the most liquid names, we’re a long way from having that everywhere.
We talked a bit before about the differences between interpolated values and actual markets. The VIX is one of the prime examples of very interesting and important data off the cable, but even with a complex of products the pure derived index isn’t tradeable. Explicitly listed securities with active participants will always provide the closest reflection of “true value”, but a little bit of math and estimation points us in the right direction.
Statistics describing the options markets are most interesting when they find ways to make money. The first step to identify shifting dynamics is to be able to track them consistently. When the price of skew drops, and the time spread cheapens, you might not be able to buy that time spread index, but you can take an informed look at the screen prices to structure a trade.
The way dealers analyze liquidity and trading opportunities is not all that different from what is interesting to retail traders. Liquidity increases with rising volumes and open interest. This begets tighter lit markets, supporting the ability to get in and out of a trade at a reasonable price. Pricing inputs change with uncertainty. Buyers and sellers speculating on the unknown push relative pricings to and fro.
Liquidity + Uncertainty = Opportunity.
It’s important to track the right changes for your strategy. If you’re a defensive investor, you might care about how much protection costs relative to the upside you sell to finance it. When you’re looking for leverage, the short put / long call price of skew is interesting.
Beyond just the flavor of exposure, how you define the inputs matters. “Tell me when vol is expensive” is as general as asking “what temperature is it in the morning?” You can use the thermometer in a couple of different ways here.
One answer to that question is checking the reading every day at 8am. Knowing the average temperature at 8am in Brooklyn would be very useful to a business traveler who will be commuting to the office at that time, and needs to know what jacket to bring.
Another way to answer this question would be to check the temperature each morning at sunrise. The clock time will vary greatly - 7:32am the day before standard time returns, or 5:25am in the glorious mornings leading into the summer solstice. The temperature when light first hits the earth is interesting both as a literal definition of “morning”, but also practically to someone whose day's work can only begin at the break of dawn.
The options equivalent here would be whether you define your values by delta or percentage range. Percents make intuitive sense, and provide a nice framework to design a portfolio such that on any given quarter the first 20% of your losses are covered. Deltas on the other hand have the benefit of being abstract, and incorporating implied volatility into their values. Selling the 15 delta call every month will result in a range of cash proceeds and upside caps depending on the volatility environment at the time of your trade.
Interpolating across time, delta, and percentage space is an exercise in data navigation. Good liquid markets will offer many different choices such that every ideal point will have some very close neighbors. SPY alone has just shy of 4000 strikes.
SPY scores the highest marks for pure liquidity, consistently topping volume and open interest metrics, with some of the tightest available markets. But even during Markets in TurmoilTM, the inputs only move so much relative to what happens in a name like Bed Bath and Beyond.
As BBBY tumbles towards bankruptcy, prices are moving around a lot. This scores very high in input movement for opportunity sleuths. As best you can shoehorn these quotes into a pricing model, it’s roughly 350% implied vol and -97% interest rate for options a month out. We’re going to hell in a handbasket, watch out for your puts.
A condor is a useful approximation for the price of volatility, because it represents a risk managed way that traders can practically implement short volatility strategies. When you’re short a put spread and a call spread, you can only lose on one, and your loss is capped. I get a lot of goose eggs when I try to run a condor price in BBBY.
CBOE has a condor index they track on the SPX that looks at 5 and 20 delta spreads here, short the near-the-money 20 delta call and put, while long the 5 delta wings to tourniquet the bleeding. NaN is the answer for a BBBY condor index, because thirty days out the highest strike on the board is 8 delta.
That 45 strike call is more than 10x the current stock price. Yet the quirks of perilously negative interest rates implying imminent bankruptcy with tempestuous levels of volatility makes for some funny pricing. As of yesterday’s close there’s a 25 lot bidding .07 for that call - sounds like a free $175, but do you really want to sell it?
Either way, things are moving quickly. The violent swings of skew, rates, and vol here means dollars are flying around. There’s a lot of risk, but also a lot of potential reward. Just the place for level headed nerves of steel to roll up their sleeves.
Opportunity comes in many different flavors. It’s a swirl of volume and spreads, with pricing inputs that ebb and flow. BBBY offers the lucre of a white dwarf - a densely packed mass of potential energy, while SPY brings the consistency and durability of the sun. No matter what you’re hunting for, there’s something for everyone when the bell rings.
Incidentally, this also provided a huge revenue boost for those primary listing venues. By carving out and marketing the benefits of these order types, they took back market share from the various secondary exchanges and alternative trading systems that had slowly eaten away at their volume with faster technology and more competitive fees.