$Advanced Micro Devices(AMD)$ Not long ago, this was an $80 stock. Some probably wish they could have bought it at $2, like back in early 2016. When a quality company like $Nike(NKE)$ trades near a 10-year low, it is worth doing the homework and looking for opportunity while most others are fearful.
$Advanced Micro Devices(AMD)$ Data center is becoming a serious profit engine. Quarterly data center operating income just hit $2.1B, up from roughly $1B two years ago. Everyone talks about AI revenue and market share, but this is what I really care about. AMD isn't just selling more into data centers anymore. It's turning that growth into real operating profit.
$Advanced Micro Devices(AMD)$ Lisa Su told reporters in Taipei that chip demand is outpacing supply and should stay "very high" for the next few years, even as AMD increases output. The company will also raise its own production next year.
$Advanced Micro Devices(AMD)$ The AMD PT upgrade season has started. They were right before when the vast majority raised their price targets above $600, even though a lot of people laughed at the time. Now the same pattern is playing out again as another wave of AMD PT upgrades begins. The latest one from BNP is $960. When BNP recently raised them to $600 from $460, people laughed then too. Just saying.
$Advanced Micro Devices(AMD)$ AMD big million-dollar call buyers. $3.9M in November 20 $650 calls at ask, $1.7M in November 20 $630 calls above ask, $2.3M in October 30 $670 calls at ask. $9.9M total call flow versus $1.6M put flow. Aggressive call buying lighting up the tape.
$Advanced Micro Devices(AMD)$ AMD still looks like the bullish sequence has room to extend. The structure remains on the right side after completing wave ((iv)) near 596.06. The advance from that low is developing impulsively, and the current pullback looks like wave iv. The expected next move would be a push higher in wave v toward the 648 area to complete wave (iii), then a corrective pullback in wave (iv) toward roughly 634-636, followed by another move higher. Key level is 596.06.
Two key compute bottlenecks worth keeping in mind, one architectural and the other economic. Architectural: the memory wall. Compute capacity in FLOPS has gone up massively, but the speed at which data can be fetched from memory like HBM or GDDR has grown much more slowly. Around 55% of AI accelerator bill of materials is memory these days, because more and more has to be added just to keep up with the gap in FLOPS. Economic: tokens per watt. GPU power consumption keeps rising with each new chip generation. That creates a strong incentive for hyperscalers to raise token throughput using specialized CPUs built around heterogeneous computing. Under that setup, the traditional CPU focuses strictly on application logic and orchestration, while dedicated CPUs handle data movement, security, and