Meta’s post-Q2 2026 earnings reaction and ongoing AI infrastructure push remain the dominant drivers of trader sentiment for its weekly close. The July 29 report showed revenue beating estimates at $60.8 billion but an EPS miss, paired with narrowed Q3 guidance and sustained heavy capex—now centered on $130–145 billion for the year—to scale large language models and data centers. This followed the early-July release of the improved Muse Spark AI model, which closed capability gaps with rivals while introducing paid developer access. Institutional flows have been mixed amid broader tech volatility, with the stock recovering from an early-August low near $520 to trade near $590–594. Key near-term catalysts include sustained ad-platform engagement trends and any fresh competitive AI benchmarks that could shift sentiment on Meta’s open-weight strategy.
Riepilogo sperimentale generato dall'AI con riferimento ai dati di Polymarket. Questo non è un consiglio di trading e non ha alcun ruolo nella risoluzione di questo mercato. · Aggiornato530$
93%
540$
92%
550$
83%
$560
68%
$570
47%
580$
30%
590$
15%
600$
9%
610$
7%
$620
6%
630$
10%
640$
10%
650$
9%
$50 Vol.
530$
93%
540$
92%
550$
83%
$560
68%
$570
47%
580$
30%
590$
15%
600$
9%
610$
7%
$620
6%
630$
10%
640$
10%
650$
9%
If the two specified prices are exactly equal, this market will resolve to "No".
Closing prices will be used exactly as published by Pyth, without rounding.
If Meta Platforms, Inc. (META) does not trade at all during the regular session of the final trading day of the week, the market will resolve 50-50.
For a standard full trading session, the closing price refers to the Pyth "Close" value of the 1-minute candle corresponding to the final minute of regular trading hours on the primary exchange. If the relevant session is shortened (for example, due to a market-holiday schedule), the Pyth "Close" value of the 1-minute candle corresponding to the final minute of that shortened session will be used.
If the relevant day has no valid Pyth Close value for the 1-minute candle corresponding to the end of regular trading hours on the primary exchange, the market will use the last valid Pyth price achieved during the regular trading hours of the primary exchange as the effective closing price. If no valid Pyth price exists for that trading day due to a system outage, data failure, or other technical disruption, the official closing price published by the primary exchange on which the listed security trades will be used to determine the closing price for that day.
In the event of a stock split, reverse stock split, or similar corporate action affecting the listed security during the listed time frame, this market will resolve based on split-adjusted prices as displayed on Pyth. The target price will be adjusted proportionally to reflect any stock splits. Resolution will be based on the historical price data as shown on Pyth after any adjustments have been applied.
The resolution source for this market will be Pyth, specifically the "Close" values for the relevant 1-minute candle for Meta Platforms, Inc. (META) available at https://pythdata.app/explore/Equity.US.META%2FUSD.
Mercato aperto: Aug 16, 2026, 7:09 PM ET
Fonte di risoluzione
https://pythdata.app/explore/Equity.US.META%2FUSDResolver
0x65070BE91...If the two specified prices are exactly equal, this market will resolve to "No".
Closing prices will be used exactly as published by Pyth, without rounding.
If Meta Platforms, Inc. (META) does not trade at all during the regular session of the final trading day of the week, the market will resolve 50-50.
For a standard full trading session, the closing price refers to the Pyth "Close" value of the 1-minute candle corresponding to the final minute of regular trading hours on the primary exchange. If the relevant session is shortened (for example, due to a market-holiday schedule), the Pyth "Close" value of the 1-minute candle corresponding to the final minute of that shortened session will be used.
If the relevant day has no valid Pyth Close value for the 1-minute candle corresponding to the end of regular trading hours on the primary exchange, the market will use the last valid Pyth price achieved during the regular trading hours of the primary exchange as the effective closing price. If no valid Pyth price exists for that trading day due to a system outage, data failure, or other technical disruption, the official closing price published by the primary exchange on which the listed security trades will be used to determine the closing price for that day.
In the event of a stock split, reverse stock split, or similar corporate action affecting the listed security during the listed time frame, this market will resolve based on split-adjusted prices as displayed on Pyth. The target price will be adjusted proportionally to reflect any stock splits. Resolution will be based on the historical price data as shown on Pyth after any adjustments have been applied.
The resolution source for this market will be Pyth, specifically the "Close" values for the relevant 1-minute candle for Meta Platforms, Inc. (META) available at https://pythdata.app/explore/Equity.US.META%2FUSD.
Fonte di risoluzione
https://pythdata.app/explore/Equity.US.META%2FUSDResolver
0x65070BE91...Meta’s post-Q2 2026 earnings reaction and ongoing AI infrastructure push remain the dominant drivers of trader sentiment for its weekly close. The July 29 report showed revenue beating estimates at $60.8 billion but an EPS miss, paired with narrowed Q3 guidance and sustained heavy capex—now centered on $130–145 billion for the year—to scale large language models and data centers. This followed the early-July release of the improved Muse Spark AI model, which closed capability gaps with rivals while introducing paid developer access. Institutional flows have been mixed amid broader tech volatility, with the stock recovering from an early-August low near $520 to trade near $590–594. Key near-term catalysts include sustained ad-platform engagement trends and any fresh competitive AI benchmarks that could shift sentiment on Meta’s open-weight strategy.
Riepilogo sperimentale generato dall'AI con riferimento ai dati di Polymarket. Questo non è un consiglio di trading e non ha alcun ruolo nella risoluzione di questo mercato. · Aggiornato
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