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https://i.redd.it/3jvjmsc6x4yg1.gif
# TLDR
1. 16 minutes before the Truth Social post announcing a 90 day tariff pause, S&P 500 options-implied expectations showed two spikes toward a higher closing price. Relative to the same-day history from market open, the 1:02 p.m. and 1:08 p.m. spikes were >4 standard deviations above the mean, corresponding to roughly the 99.999th percentile.
2. Similar abnormalities appeared in Nasdaq and Russell 2000 options before 1:18 p.m. One hypothesis is that abrupt orders in SPY options can cause market makers to instantly update their quotes on related assets, which propagates information efficiently throughout the market.
3. I observed similar advanced price-jump expectations in the hour leading up to the announcement of the U.S. Strategic Bitcoin Reserve on Mar 2 of 2025
# Details
You might remember me from sharing the open source [Options Implied Probability](https://github.com/Open-Lemma/options-implied-probability) (OIPD) python library. Since option prices reflect the market's belief in the probabilities of their payoffs occurring, then we can mathematically back out the market's consensus for where the S&P 500 will end the day using 0DTE options.
I wanted to test it with some real events. Trump announced 90 day pause to his Liberation day tariffs, which caused the S&P to jump 9.5%. [Reuters ](https://www.investing.com/news/stock-market-news/welltimed-options-trades-ahead-of-trumps-tariff-pause-draw-questions-3980430)reported suspicious trades about 18 min before the announcement.
https://i.redd.it/ex059ue7x4yg1.gif
Panel 1 shows the SPY spot price, and panel 2 shows the implied probability distribution of SPY's EoD closing price.
Because we have the full distribution, we can inspect some interesting statistics. 2 observations stand out to me:
1. Panel 3 shows skew, a measure of asymmetry. Equity price distributions are typically negatively skewed because large crashes are more likely than large price jumps. Here, skew becomes even more negative. That is consistent with the center of the distribution shifting higher while the left tail remains anchored (see visual below).
2. In panel 4, we see the difference between the mean expected closing price minus the live spot price. Because these are 0DTE options, their mean expected closing price typically tracks the live price closely because there's only a few hours left before expiry. When both the implied mean and skew move abruptly, it seems to point to a sudden expectation of a higher SPY close.
https://preview.redd.it/3emahmlox4yg1.png?width=981&format=png&auto=webp&s=92a2883705d82354be30fc65585b2b6de1213e83
# Previous-day control: the same abnormalities were not observed in the same timeframe
https://i.redd.it/t55pdru8x4yg1.gif
The purpose of this section is to check whether the April 9 pattern was unusual, or whether similar signals appear simply due to noise. So some of my observations below:
* Markets were unusually noisy that week, following the April 2 Liberation Day tariff announcement. April 8 was especially so, with the [S&P 500 and Nasdaq falling around 2% intraday](https://www.businessinsider.com/why-stocks-are-up-today-tariffs-japan-trade-deal-trump-2025-4). Any useful signal should therefore be robust to noisy market conditions.
* Skew rises across all three tickers over the timeframe. That likely reflects the sell-off itself, as prices fell intraday, traders grew more fearful and placed more belief on lower closing prices, shifting the weight of the distribution.
* The difference between implied mean and live price is an interesting statistic. I have not run a formal statistical test here, but visually April 8 looks noisy without a clean break, so it would likely fail to reject a null hypothesis.
# Other notes
If you want to replicate this, the easiest way would be to give your AI the link to the OIPD [documentation](https://docs.open-lemma.com/) and ask it to replicate this analysis.
I've written some more details including Nasdaq and Russell 2000 tests and math footnotes [here](https://open-lemma.com/blog/tariff-pause-signal/).
If you're interested in using this to generate signals, this can be expanded into a systematic backtest across Trump-related events, or across other events like mergers.