However, there’s also a point where we go down too many rabbit holes and try to overly refine a tool for a bottle of filter to the point of making it too fine. A lot of time it comes down to a combination of Analytics and good old human judgment.
Instead of using VIX term structure, why not just look at IV term structure. If you're selling vol 0dte isn't looking at IV term structure of SPY directly better than the 30 day out VIX measurement? Also, looking at puts vs calls by delta term structure could be informative of tail risk pricing on the shorter timescale. Backwardation of 0dte vs 1dte or 2dte would be interesting to add as a feature.
I’ve been building this one variable at a time — VIX + time first, then layering complexity. These are exactly the candidates for Engines 5 and 6!
IV term structure (0DTE vs 1DTE vs 2DTE) instead of VIX futures curve is more direct for a 0DTE strategy. Starting with VIX keeps data simple (free, no surface reconstruction needed). But once we validate the regime classifier itself works, moving to SPY's actual IV surface would be the next step. Also, I think put/call skew by delta is a direct tail-risk measure that should refine/sharpen what Engine 2 (convexity) is trying to do. This could be Engine 5, where we could replace GEX with actual skew measurement.
And I also think 0DTE/1DTE backwardation ratio as a cleaner transition signal than VIX1D alone. It might be even better for catching the mid + negative failure mode.
So my methodology here is to lock in VIX + time as the core (my next part validates it works), then systematically test IV surface structure, skew, and front-month ratios as upgrades.
Yes thats good methodology start with the easier data to verify. I think put/call skew is probably more concrete than GEX in terms of dealer positioning because prices are also reflective. Thats a good upgrade interested to see how it turns out. Going to the vol surface is a lot more data to handle but I think its probably worth it. When you get vol surface data I'd also suggest calculating a trailing historical volatility risk premium. HVRP=IV_straddle-RV for the last day's trading session to look at 0dte volatility pricing and then also a simple vol forecaster like a GARCH or just the day before's realized variance and look at the ATM IV from the straddle to quantify the VRP of the session you want to trade. I'd guess a positive VRP of the day before and the trading day is a far better regime to be short expected move using the spreads and it's probably a better regime gate than just pure VIX levels. It's more nuanced since Volatility/VIX can be super high but if RV is relatively low you're missing trades.
This entire 0DTE series is absolutely phenomenal! I love it =) I have been diving deep into this exact topic for over two years now.
The critical blind spot in the "Engine 4" model—the catastrophic Mid VIX + Negative GEX failure mode—is not a statistical anomaly.
It is the direct mathematical result of institutional Vanna (second order greek) and Dealer Delta-Hedging cascades forcing the volatility surface to invert.
I actually discovered this dangerous Vanna regime when I started using my own developed / coded volume template (optimized for detailed analysis via AI) to analyze SPY and ES futures volumes in combination with SPX and SPY optionschain positionings, changes and optionsflows.
The AI could anticipate that this Regime is comming, just with the detailed volume metrics out of my template!
So i would say, the failure mode in Engine 4—specifically the Mid VIX + Negative GEX regime where the strategy's win rate collapses to 17.6%—is caused by relying on reactive, lagging metrics. To survive, algorithmic models cannot wait for the GEX Flip Point to be officially breached. By synthesizing ES futures volume with SPX/SPY options flow, we can detect the structural divergence of the volatility surface 24 to 48 hours before the Vanna cascade wipes out short-premium sellers.
Engine 4.1 should upgrade the system from a reactive 2D filter to a predictive 3D early-warning matrix, ensuring capital preservation against forced institutional liquidity withdrawals.
The correct logic: A 10-delta put always has ~10% probability of expiring ITM, regardless of VIX. But the dollar distance from spot changes with vol.
actually, that’s not accurate using Delta as a shorthand for a percent expiring will not give your accurate results. Close enough, but do we want close enough?
However, there’s also a point where we go down too many rabbit holes and try to overly refine a tool for a bottle of filter to the point of making it too fine. A lot of time it comes down to a combination of Analytics and good old human judgment.
Good point
Instead of using VIX term structure, why not just look at IV term structure. If you're selling vol 0dte isn't looking at IV term structure of SPY directly better than the 30 day out VIX measurement? Also, looking at puts vs calls by delta term structure could be informative of tail risk pricing on the shorter timescale. Backwardation of 0dte vs 1dte or 2dte would be interesting to add as a feature.
Ahhh you pre-empted me!
I’ve been building this one variable at a time — VIX + time first, then layering complexity. These are exactly the candidates for Engines 5 and 6!
IV term structure (0DTE vs 1DTE vs 2DTE) instead of VIX futures curve is more direct for a 0DTE strategy. Starting with VIX keeps data simple (free, no surface reconstruction needed). But once we validate the regime classifier itself works, moving to SPY's actual IV surface would be the next step. Also, I think put/call skew by delta is a direct tail-risk measure that should refine/sharpen what Engine 2 (convexity) is trying to do. This could be Engine 5, where we could replace GEX with actual skew measurement.
And I also think 0DTE/1DTE backwardation ratio as a cleaner transition signal than VIX1D alone. It might be even better for catching the mid + negative failure mode.
So my methodology here is to lock in VIX + time as the core (my next part validates it works), then systematically test IV surface structure, skew, and front-month ratios as upgrades.
What are your thoughts?
Yes thats good methodology start with the easier data to verify. I think put/call skew is probably more concrete than GEX in terms of dealer positioning because prices are also reflective. Thats a good upgrade interested to see how it turns out. Going to the vol surface is a lot more data to handle but I think its probably worth it. When you get vol surface data I'd also suggest calculating a trailing historical volatility risk premium. HVRP=IV_straddle-RV for the last day's trading session to look at 0dte volatility pricing and then also a simple vol forecaster like a GARCH or just the day before's realized variance and look at the ATM IV from the straddle to quantify the VRP of the session you want to trade. I'd guess a positive VRP of the day before and the trading day is a far better regime to be short expected move using the spreads and it's probably a better regime gate than just pure VIX levels. It's more nuanced since Volatility/VIX can be super high but if RV is relatively low you're missing trades.
This entire 0DTE series is absolutely phenomenal! I love it =) I have been diving deep into this exact topic for over two years now.
The critical blind spot in the "Engine 4" model—the catastrophic Mid VIX + Negative GEX failure mode—is not a statistical anomaly.
It is the direct mathematical result of institutional Vanna (second order greek) and Dealer Delta-Hedging cascades forcing the volatility surface to invert.
I actually discovered this dangerous Vanna regime when I started using my own developed / coded volume template (optimized for detailed analysis via AI) to analyze SPY and ES futures volumes in combination with SPX and SPY optionschain positionings, changes and optionsflows.
The AI could anticipate that this Regime is comming, just with the detailed volume metrics out of my template!
So i would say, the failure mode in Engine 4—specifically the Mid VIX + Negative GEX regime where the strategy's win rate collapses to 17.6%—is caused by relying on reactive, lagging metrics. To survive, algorithmic models cannot wait for the GEX Flip Point to be officially breached. By synthesizing ES futures volume with SPX/SPY options flow, we can detect the structural divergence of the volatility surface 24 to 48 hours before the Vanna cascade wipes out short-premium sellers.
Engine 4.1 should upgrade the system from a reactive 2D filter to a predictive 3D early-warning matrix, ensuring capital preservation against forced institutional liquidity withdrawals.
https://de.tradingview.com/script/CGyGOAeG/
Gex + or - is a bit too broad
Typically there are larger- gex nodes locally embedded in a positive gamma structure and vice versa
The VIX1D is a pretty shitty measure because of how it’s calculated
Expected move is possibly better
VIX - VIX 9D (or a ratio ) I find to be an easy down and dirty user friendly way to get a sense
Now I’m not a coder so ..
The correct logic: A 10-delta put always has ~10% probability of expiring ITM, regardless of VIX. But the dollar distance from spot changes with vol.
actually, that’s not accurate using Delta as a shorthand for a percent expiring will not give your accurate results. Close enough, but do we want close enough?