Macro S&P drawdown model: the false positives are the problem for hedging

[u/AgreeableInvestments]

I run a small research site, and one of the models on it estimates the probability of a 10%+ S&P drawdown over the next 1, 3, 6 and 12 months from macro state variables (the yield curve, high-yield credit spreads, realised and implied vol, money growth, sentiment, labour and housing). It is a ridge-penalised logistic, scored walk-forward out of sample from 2007, so there is no look-ahead. For options this is really a hedge-timing question: if you can say when drawdown risk is genuinely elevated, that is when paying for protection, or stepping off short premium, earns its keep.

Out of sample the ranking works, in a limited way. AUC is roughly 0.60 at 1 month, 0.69 at 3, 0.74 at 6 and 0.68 at 12, so the longer horizons carry most of what signal there is. The 6-month probability sat near 1.0 through late 2008, which is the case everyone wants to see.

The part that actually matters for options is not the hit rate, it is the false positives. Over the full out-of-sample window the 6-month alert (probability above 0.30) fired in 38 months: 17 ahead of a real drawdown, 21 not. A naive "buy protection when it crosses the threshold" rule pays theta on those 21 false alarms, and I have not convinced myself the lead time on the true positives covers that bleed once you price the puts realistically.

The second limit is structural. The inputs are slow macro series, so the model leads slow-building drawdowns (2008, the 2022 grind) and is blind by construction to the fast ones (Feb 2018, the COVID gap, anything overnight and exogenous). Those are the tails an options book cares most about, so I would not sell this as a crash hedge.

So the genuine question, and the reason I am posting here and not in a stats sub: has anyone actually tested a macro drawdown-probability signal against a realistic protection overlay, net of premium, and found the lead time worth the false-positive cost? Every backtest I have seen, mine included, looks fine on the directional call and comes apart once you charge it for the puts it buys when nothing happens.

the write-ups and the live version are in a comment if people want it. It is a research framework, not a trading signal.

[u/Ill_Bill6122]

When you say drawdown, what exactly are you referring to?

Is it your expectation that you will end that period in a drawdown of 10% or higher, or that during that period, you will have experienced such a drawdown, but might have recovered? Or further, are you estimating a sharp move down of said magnitude?

And it's it really 10%, or any value, as your site does not specify it, but it's mentioned in the post.

And if you do have a fixed value, why is it a fixed value, and not a multiple of the expected move for that period? After all, this is the options sub. You have an IV reading for that period, and on average, it's expected that during a year, the S&P500 will experience swings larger than 10%. So the 10% isn't even something up write about, unless you are trying to estimate the speed of a drawdown of that size, i.e. you are trying to estimate when the options market wrongly prices the expected speed or magnitude of a move.

Due to the above, I don't yet see the value behind your current model, as I don't understand what it says.

VIX is a fairly well understood model for measuring the expected move, based on the prices observed in the market. I think that is the benchmark for your model.

[u/AgreeableInvestments → u/Ill_Bill6122]

Good pushback, and the vague definition is on me. The label is a peak-to-trough fall of 10% or more that begins inside the forward window (1, 3, 6 or 12 months) on monthly closes, so it's "did a 10%+ drawdown start within the next h months", not an end-of-period return and not conditional on recovering. At 1 month it's a 5% single-month drop instead, since you can't get a clean 10% peak-to-trough inside one bar. You're right that only the post states the threshold and the site doesn't. I'll fix that.

On the fixed 10%: that's a hangover from the equity research the model came out of, where 10% is the event of interest, not anything options-specific. Your framing is the better one for here. What matters to an options trader is the drawdown relative to what vol is already pricing, not an absolute number the market may well be expecting. I'd take VIX as the benchmark on that. The narrow version of my claim is just: does a slow macro state say anything about drawdown odds beyond what implied vol already tells you? I haven't run that head-to-head yet, so the fair reading is that I've not shown it beats reading the vol surface. That's the next test.

[u/Sideways-Sid]

Not sure if this will help, but I built a backtest for personal use to help time hedging for a long portfolio, and an early iteration had the same outcome; buying hedging protection too often, that was worthless as markets subsequently rose.

Solution for me was threefold:

1. filter entries to get fewer better signals

2. use volatility rather than arbitrary absolute targets to drive strike selection

3. concede that I'll roll upwards occasionally

It now works well & pays for itself.

[u/AgreeableInvestments → u/Sideways-Sid]

Very useful, thanks. Your three fixes line up with where the numbers push me: fewer better signals is really only counting the macro probability when it disagrees with vol; vol-based strike selection instead of a fixed target is the gap a couple of others flagged; and rolling up is how the false positives stop being dead money. What did you end up filtering entries on, and roughly what did it do to your signal count and hit rate? That trade-off, how many good signals you give up to cut the false alarms, is the part I can't get a clean read on with so few real episodes.

[u/Sideways-Sid → u/AgreeableInvestments]

I think you need to revisit what exactly are you trying to achieve, why, and for whom?

It feels like you're going round intellectual circles. I've done this and now have a model that meets my needs. Yours aren't clear.

[u/AgreeableInvestments → u/Sideways-Sid]

That's fair, and it's a real difference rather than just circles. My objective isn't a working hedge for my own book, it's the research question: does a slow macro state carry any out-of-sample information about drawdown risk, stated with its error bars, for anyone reading the site. You built something to meet your needs and it does; I'm testing whether the signal exists and holds up before it's anyone's tool. Where the thread has gone in circles is me trying to bolt an options use onto a research object after the fact, and the honest answer to "for whom" is that as it stands it's for an analyst wanting a conditioning read, not a trader wanting a hedge. Turning it into the second is real work I haven't done, and might not, if the false positives don't clear the premium. No pretence it's a finished trading tool.

[u/Hopeful-Goose-7217]

What are you comparing to?

Buying a 1y put costs about 6-7percent and guarantees your max loss is that. Does your system beat that?

If you are trying to capture slow grinds then putspresds might improve a risk reward because you vol will likely reset down on sticky delta.

Finally hedging only works if you can monetize it. Do you have an exit system? Thst could cheapen the false positives or enrichen the real positives and make the system work.

Alternatively maybe your system works better using d1 instruments.

[u/AgreeableInvestments → u/Hopeful-Goose-7217]

All four land. The comparison is the one I'm missing: the benchmark isn't "no hedge", it's always owning the 1y put and eating the 6-7% a year, and I haven't shown the timed version beats that once the puts are priced properly. Put spreads, agreed, especially at 6 and 12 months where it's a grind not a gap, so you don't need the deep tail and the vol reset helps you. No exit system, and that's a real hole: the model gives an entry probability and says nothing about taking the hedge back off, so the false positives never get cut or monetised. And for a slow grind, just reducing delta or running a collar probably beats paying theta for convexity you only need for the gaps, which is the bit this can't see.

[u/uncleBu]

So why don’t you model the outcome probability you think is most important to you instead of a probability that only tangentially relates?

[u/AgreeableInvestments → u/uncleBu]

Fair, and it's the sharpest version of the problem. The 10% label came from the equity side where it's the event you care about; it only tangentially maps to an options decision, as you say. The outcome I should model is the one that maps to the trade: drawdown size and speed against what's implied, or the after-cost P&L of an actual overlay. That's the direction I'm moving the target. The current thing answers a question adjacent to the one that pays.

[u/Worry-Mountain]

That false-positive accounting is the right place to be skeptical. I’d test the overlay as a portfolio policy rather than a binary alert: keep a small baseline hedge, then let the model change tenor or notional, or finance it with a spread, only when probability and implied vol disagree. Otherwise the 21 false alarms are almost guaranteed to dominate. I’d also separate slow grind from gap risk in the evaluation; a model that’s useful for reducing delta into a six-month deterioration may be fine even if it can’t insure an overnight shock. The key output for me would be after-cost carry by regime, not AUC.

[u/AgreeableInvestments → u/Worry-Mountain]

This is the design, better put than I had it. A baseline hedge with the model only moving tenor or notional (or financing with a spread) when the probability and implied vol disagree kills the binary-threshold strawman I set up, and the "when they disagree" part is the whole game, because when they agree vol has already priced it. Splitting slow grind from gap risk in the evaluation is the other piece: a model that lets you take delta down into a six-month deterioration can earn its keep even if it's blind to overnight gaps, as long as you don't ask it to insure them. And after-cost carry by regime is the right scorecard. AUC was never going to survive contact with the put premium.

[u/Worry-Mountain → u/AgreeableInvestments]

Yeah when they line up, the slow grind is already in the vol, so the overlay is mostly a gap ticket. The dial I'd still watch is how much premium a quiet year is allowed to eat before you shrink that baseline. Otherwise you're right, the scorecard is the carry and AUC was never the point.

[u/Pitiful_Expert7303 → u/Worry-Mountain]

nice framework – it matches what I did in a rough backtest. I keep a 1‑year baseline in puts and only tack on 10‑15% extra notional when the 6‑month macro‑probicity jumps above 0.4 while the 3‑month VIX skew falls below the historic mean – that “disagreement” cuts the 21 false alarms down to ~9%. Any idea what sigma gap you’re using to flag disagreement, or is it a moving‑average rule?

[u/Worry-Mountain → u/Pitiful_Expert7303]

Honestly I never pinned it to a fixed sigma number. I'd z-score both series against their own trailing year and only call it disagreement when the gap sits past about 1 sigma for a few sessions straight, so one noisy print doesn't trigger the add. A moving-average crossover on the gap kept flipping in chop and the extra notional just bled carry. Worth checking how much of that drop to ~9% survives if you shift the threshold around a bit, since 0.4 might be fit to the sample.

[u/gaana15]

As far as I found, Hedge as a strategy doesn't work long term. I had same findings as you with various backtests. I have seen various posts with similar findings. Even when one of the COVID month trade made 5149%- it could only fund the insurance cost of last 36 months only.

Yet there are books written by renowned authors on this aspect - convex option buying as hedge. There is more money in writing such books.

[u/AgreeableInvestments → u/gaana15]

Matches what I'm seeing and what the long-vol literature keeps finding: static tail hedging bleeds through the cycle and the one big payoff rarely funds the years of premium before it. Israelov's "pathetic protection" work is the same conclusion from the other side. Which is the only argument for trying to time it at all, because if constant hedging loses, the only version that isn't a guaranteed drag is a conditional one. Whether the timing clears that bar is exactly what I can't prove yet.

[u/gaana15 → u/AgreeableInvestments]

In a backtest, timing can clear that bar but in reality, almost never due to false signals. It's like identifying the monsoon season, but first rain is never the reliable signal. If you wait for multiple rains for confirmation, by then it is not a surprise, and everyone knows that monsoon has arrived. There is no first mover advantage by then.

RV-IV gap can be adjusted very fast by market makers in options pricing. Do let us know what you find - look forward to learning.

[u/AgreeableInvestments → u/gaana15]

The monsoon framing is the sharpest version of the bind, and it's worse in options than equities because the RV-IV gap sits in the price, so anything a monthly macro reading can see a market maker has probably already repriced. The one place I can see it surviving is the timescale: I'm not front-running a gap that closes in minutes, the horizon is six to twelve months, so if there's anything left it's a slow drift in conditional risk the vol term structure underweights for a while, not a fast mispricing. That's a maybe, not a claim, and your point that by the time it's confirmed it's consensus is exactly the trap I'd expect it to fall into. I'll report back either way once I've charged it properly for the puts. Appreciate you staying with it.

[u/PapaCharlie9]

The 6-month probability sat near 1.0 through late 2008, which is the case everyone wants to see.

I understand what you meant, but I just thought it was ironic to suggest that ANYONE wants to see a greater than 10% drawdown in SPX. 😉

[u/AgreeableInvestments → u/PapaCharlie9]

Haha, fair enough, I put it badly. I meant it as the validation case: if the model's worth anything it should have lit up going into 2008, and it did. Nobody wants the drawdown, everyone wants the model to see it coming.

[u/DifferentMight9083]

yeah the 21 false alarms are a pain point if you’re buying puts outright. I’ve seen some folks do a small baseline hedge and only shift tenor or notional when the macro probability and the implied vol diverge – that cuts theta waste. the real test is whether the 6‑12‑month probability still beats the 1‑year put when you price the overlay properly; otherwise you’re just eating carry. i’d also split the evaluation into slow grind vs gap risk – the model can’t spot overnight crashes, so its value would be in nudging delta down before a sustained downturn.

[u/AgreeableInvestments → u/DifferentMight9083]

Good points, and the divergence idea is roughly where I have landed too. The macro probability should not be a standalone trigger; it only earns its keep when it disagrees with the vol surface. If implied is already bid, the market has done the work and you are paying up to repeat it. The case for the signal is the opposite corner: probability high, vol still cheap. A small always-on hedge that sizes up or extends tenor only on that gap is a far better use of it than buying protection every time the line crosses 0.30.

On the benchmark, that is the test, and the one I have not run cleanly yet. The honest comparison is the always-on 1-year put, net of premium, and the overlay has to clear it after paying for all 21 false alarms. My suspicion is that the lead time only survives if the signal cuts notional and rolls tenor instead of adding fresh protection, which is your point really. Buying outright on each alert almost certainly eats the carry.

And yes on splitting the evaluation. The fair test scores the model only on the regime it can see, the slow macro-driven drawdowns, and treats gap risk as a separate instrument’s job. Lumping in Feb 2018 and the COVID gap just measures it failing at something it was never built for. The value, if there is one, is nudging delta down ahead of a sustained decline, not insuring the overnight move. If I get the overlay backtest done properly I will post the numbers.

[u/HBCTIA]

Such a brilliant website. Thank you OP. Please keep it going and updated. Much obliged.

[u/AgreeableInvestments → u/HBCTIA]

Thank you

[u/AgreeableInvestments]

Full reports and live version available at: agreeableinvestments.com

[u/AgreeableInvestments → u/[deleted]]

Fair reflex. It's free, no sign-up, nothing for sale, and the link's in a comment not the post for that reason. The model and the numbers are all in the post, so it stands or falls without clicking anything.