$Meta Platforms, Inc.(META)$ SPX is getting close to some strong support levels. Short-term it looks bearish, but the medium-term setup still leans bullish. The $520-525 zone seems like a reasonable spot to add longs. I'm watching to see whether it can hold the $540-545 area.
$Meta Platforms, Inc.(META)$ Looking at the 6-month chart, META has recovered quickly all four times it dipped to these levels. I think we could see it above $600 within the next couple of weeks or less.
$Meta Platforms, Inc.(META)$ I was stopped out at 627.55 during that negative momentum event. It seems like momentum could be shifting positive, so I opened a new position at 587, a $40 discount. I can see the 50-day has been acting as resistance, but I think it eventually breaks through, so this feels like a reasonable place to start, in my opinion.
Looking at the $Meta Platforms, Inc.(META)$ 8-hour chart, option sweepers and block buyers are leaning bullish. Heavy buying hit LEAP $650 calls, including a $7.0M sweep that's now +8.5% to ITM, and a $901.5K block on Jan 2027 $680 calls that's +13.5% to ITM. On the flip side, there are large short-dated put hedges at the $607.5 and $602.5 strikes, with sweeps of $1.4M and $870.5K. The positioning seems to follow Q2 revenue beating estimates at $47.52B, up 22% YoY. The key bull level to watch is $612.50. A solid move above it would clear the local volume shelf resistance and the overhead wicks, which could open up room for a trend expansion. The bear level sits at $524.54, marking a structural support floor and the baseline bear target. Upsi
$Meta Platforms, Inc.(META)$ With Glimmer, Meta could pull value away from other AI models. If people stop buying tokens and shift to Glimmer instead, that's a pretty big strategic move from Meta.
$Meta Platforms, Inc.(META)$ If they end up making their own chips in-house, this could become the next trillion-dollar company and compete with OpenAI and Anthropic. $1,000 seems possible from here.
$Meta Platforms, Inc.(META)$ The idea seems to be about commoditizing large language models and making them broadly accessible, with the real play being the infrastructure layer that powers them.