The NOPE Brain Worm
A FAQ (of sorts) from an under-qualified observer
NOPE is dope.
The Net Options Pricing Effect (NOPE) is the sum of all call delta traded starting at 9:30 AM EST, minus the sum of all put delta traded, divided by the equity volume on the day (ignoring pre-market volume). When the price of the underlying changes the delta of options that were traded changes and so the entire thing must be recalculated. Beyond that small hitch it is an incredibly simple formula.
The NOPE Formula is Bad
Well “bad” in the same way that a kitchen knife would be bad for surgery. It gets the job done, but a scalpel would be better. The thing is, manufacturing scalpels is hard. Refining NOPE requires expensive data with terms of service that specify how that data can be used and shared.
To be clear, this is not a criticism of the discovery. The creator (@nope_its_lily) has said as much herself. My go to example is in opening option spreads. The current iteration of the formula only sees e.g. a SPY 395C and a 400C transacted. Even though one is long and one is short to the retail trader, the delta of both of these is added to the “call delta” end of the equation. It makes no distinction between Buy to Open (BTO), Sell to Open (STO), Buy to Close (BTC), Sell to Close (STC). Our discussion on hedging later will reveal why this would be a helpful distinction to make.
The formula works, and there is the exciting amount of room for improvement.
Static Windowing is Sub-optimal
The current backtests suggest the following intraday trading strategy is optimal:
Open Long at NOPE -60 — Close at -30
Open Short at NOPE +30 — Close at +15
These windows are based on backtests performed over NOPE values in 5 minutes intervals from February 2020 to November 2020 (a touch over 200 trading days).
Perhaps these windows only work during the current market regime, maybe we’re still in that regime and thats why they still work, maybe the window needs to be moved daily (there is a way-too-early-to-tell backtest that suggested Tuesday/Thursday required tighter windows and Friday should maybe not be traded at all). Point is there is a lot of reason to believe that these static values are less than stellar, and that more refinement is needed.
My belief is that NOPE windows for this intraday strategy should be readjusted daily based on some combination of volume, volatility, and liquidity. Further development of this strategy (which is strictly retail sized) is going to require very careful backtests finding correlations with optimal window sizing while avoiding over fitting.
With these first two points made I would like to take a break to point out that using NOPE in the most braindead simple way possible would still be alpha positive. This should get people very excited for the potential of further refinement.
NOPE is not Reliant on the Presence of Market Makers
NOPE works best in highly liquid markets, which is why we stick to indexes (SPX/ES/NQ), and potentially (but unconfirmed) some of the particularly liquid equities like AAPL or MSFT (not TSLA, stop suggesting TSLA, stop using NOPE on TSLA, please for the love of god). The point being that Market Makers help NOPE’s accuracy by providing liquidity on options and consuming liquidity in the underlying, but they are neither necessary or sufficient.
NOPE Works Because Option Hedging is a Liquidity Consuming Action
Options can be recreated in the underlying, this is how they are hedged. The image below shows this being done with a combination of options and stock, but just stock is sufficient.
Liquidity is the quantity of transactions a security can support at a given price. It is useful to picture liquidity as a skew/smile the way you would think about volatility.
If I sell a call with .5 delta I need to buy 50 shares to become delta neutral. At the current spot price I now have a risk-less position and have collected the premium of selling the call. Observant readers will notice that the action of buying shares consumed liquidity. Since I have consumed the ask side this will help move the price up. Unfortunately the call I am short has gamma, and so the delta of the call I am short moves a bit too. If the price continues to move I’ll have to hedge again and consume more liquidity by buying more shares.
Now again picture the liquidity curve. The hedging of the option has caused a perturbation that has moved the price to a less liquid level; the stock is losing its ability to support transactions. Price is liquidity-seeking, it wants to move away from areas of illiquidity. In cases where hedging of calls outweighs puts the price will eventually have to fall back down into a more liquid spot where transactions are supported, in the opposite scenario buyers will move the price back up to perform transactions. These are the reversions that NOPE excels at identifying.
NOPE is Unarbable
NOPE is just a formula, of course its unarbable…
NOPE is not an edge, and as the previous section says the formula reveals consequences that are based on fundamental properties of market structure. Changing this would be like taking the gravity out of physics. Let’s take a look at modifying these properties.
Liquidity
Removing liquidity you’ve removed the ability of the equity to support any transaction at any price. It is now completely untradeable.
Alternatively we can add infinite liquidity, where the stock can support an infinite number of transactions at any spot price. This is obviously ridiculous.
Options Hedging
To avoid the weeds I’ll leave the argument simple, removing hedging would likely entail one of the following.
First, removing options from the market completely. We know that market making options is profitable, and that options are an important tool for investors to hedge, so this option is untenable.
Second, make a likely-completely-unenforceable rule against hedging options. This would cause options pricing to become wildly incorrect due in part to the removal of the ability of market participants to enforce put-call parity. Further, hedging is an assumption made in many options pricing models.
What NOPE is attempting to measure is a fundamental friction in any system with finite liquidity that contains derivatives that are replicable in the underlying.
It is important that I make the distinction here that trading strategies that use NOPE to gain an edge are not fundamentally unarbable. The most popular trade with NOPE right now is the intraday scalping of index reversions. Based on the fact that this is a trade that doesn’t scale up passed retail sizing (I would struggle to think its possible with more than 50-100 /ES lots), and the deep liquidity of those markets, there is no compelling reason to believe it is a strategy that can get too crowded or be arbed away. So all of the small traders who have just discovered the free money tree and are worried about some tragedy of the commons, worry not, it is safe.
Some other thoughts that don’t deserve their own section
NOPE is dimensionless, i.e. it's just a number, since the units in the formula cancel each other out. An improved NOPE would likely want to maintain this property.
Intraday NOPE tracks the price of SPY really well, but price is not included in the equation. Technically because of gamma, the delta in the numerator is a function of price but I don’t believe its sensitive enough to explain the tracking entirely.
NOPE resets to 0 at the beginning of every day. The assumption here is that any market participant that cares to be delta neutral, is. This seems to work and currently there does not seem to be a compelling reason to roll any NOPE into the next day.
NOPE is a standard distribution. A decent mental model of NOPE is that the value is a snapshot of the odds that option hedging has caused a perturbation that result in a price reversion. Note that it is not bounded, the most extreme NOPE values in the intraday data-set are roughly +/-230.
Removing NOPE like properties from a market involves either removing liquidity or introducing skew between puts and calls, neither of which are particularly tenable.
NOPE seems to be able to predict correction windows in indexes. I would love to see more research on the mechanisms for why this is the case.