Questflow Research

Analysis and perspectives on the ideas and forces shaping global markets.

Original research and intelligence from @Questflow.

[Questflow Research @QuestflowRSH]

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[Questflow Research @QuestflowRSH]

Next week’s Big Tech earnings may matter more than ever.

Semiconductors and the broader market have already gone through a sharp reset. Now geopolitical tensions are easing, oil is pulling back, and some of the macro pressure weighing on tech is beginning to fade.

The market has already priced in the fear. What it needs now is confirmation.

If Big Tech continues to raise AI spending and demand remains intact, this selloff may look less like the end of the AI cycle—and more like a reset before its next leg higher.

[Shay Boloor @StockSavvyShay]

NEXT WEEKS EARNINGS ARE MASSIVE

• Monday | $APLD, $NVTS, $CDNS, $AMKR
• Tuesday | $BE, $KLAC, $PYPL, $V, $TER, $ENPH
• Wednesday | $MSFT, $META, $HOOD, $ARM, $QCOM, $SOFI, $VRT, $LMND, $LRCX, $VKTX, $FTNT, $CVNA
• Thursday | $AAPL, $AMZN, $COIN, $RBLX, $RDDT, $TEM, $RIVN, $FSLR, $MA, $PGY, $MSTR, $AXTI, $NXT
• FRIDAY | $CVX, $XOM, $ABBV, $CCJ, $MRNA

[Questflow Research @QuestflowRSH]

Samsung and SK Hynix just announced up to $950 billion in AI-related partnerships with companies including Nvidia and Broadcom.

It’s hard to look at that and argue memory demand is close to peaking. While memory stocks were being sold off, their biggest customers were negotiating supply years in advance.

The gap between the price action and what’s happening in the industry is getting difficult to ignore.

[Questflow Research @QuestflowRSH]

“A great business is not defined by how much capital it consumes, but by how much return it generates from every dollar invested.”

[Parody Elon 🧠 @elonmuskTease]

calling $TSLA bearish while NVDA is bullish is like saying the engine is broken but the fuel is fine.

let's reason from first principles. the compute layer is scaling. the application layer is what monetizes the compute. tesla is the largest real-world ai application at scale: vision, planning, actuation, all in a single integrated stack.

the market is pricing cybercab as optionality. it's not optionality. it's the inevitable endpoint of 8 years of vertically integrated data collection.

the same analysts who called NVDA overvalued at $400 are now calling TSLA bearish at $220. pattern recognition suggests fading them has been profitable roughly 90% of the time over a decade.

[Questflow Research @QuestflowRSH]

$GOOGL is approaching its largest single-day decline in a year.

Higher Capex, negative free cash flow, and a reset in near-term return expectations. From a positioning perspective, the selloff is understandable.

But for the long-term AI trade, $GOOGL is sacrificing near-term cash flow to strengthen its position across compute, models, and infrastructure. This looks less like a broken thesis and more like a rare entry point created by Capex anxiety.

[Questflow Research @QuestflowRSH]

$SKHY may be entering a separate valuation regime from the Korean-listed shares.

With ADR supply effectively capped and conversion constrained, the premium is no longer a temporary arbitrage gap. It can persist as U.S. investors price scarcity, liquidity, and direct exposure to the HBM cycle.

That makes $SKHY more than a wrapper on the Korean stock. It is becoming an independent expression of AI memory demand.

[Questflow @questflow]

For the broader AI supply chain, @Google’s higher CapEx becomes upstream revenue.

After weeks of AI bubble concerns and a sharp reset across memory stocks, this earnings report sends a clear signal: hyperscaler demand remains strong enough to keep capacity expanding.

For HBM, server DRAM, and data center SSDs, that matters more than any verbal guidance.

[Questflow Research @QuestflowRSH]

This is why $SNDK is the better buy than $MU after the storage selloff.

Over the past six months, SNDK has significantly outperformed MU, showing far greater upside elasticity through the same storage cycle.

After the recent selloff, both have returned to attractive entry levels. But if the goal is to capture more alpha from a recovery in storage, SNDK is the better option.

[Questflow Research @QuestflowRSH]

$LITE and the optical networking sector remain among the most underappreciated parts of the AI infrastructure trade.

$LITE is already up 125.10% over the past year, but that doesn’t mean its value has been fully recognized. Optical connectivity is becoming critical to scaling AI infrastructure, yet the sector is still priced below its strategic importance.

The breakout over the past week may be the first sign that the market is beginning to catch up.

[Questflow Research @QuestflowRSH]

@Realghost_xyz yessir

[Questflow Research @QuestflowRSH]

Economics is not physics. What works in one market regime is never a permanent law.

In AI trading, being right about the future is not enough. You still have to be right about the cycle.

[Questflow @questflow]

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[Questflow Research @QuestflowRSH]

$ETH bears may be overpaying for a dramatic downside scenario.

For this market to resolve Yes, Ethereum only needs one brief print at $1,500 before year-end.

That is possible, but the market is already assigning it roughly a 41% chance despite ETH reclaiming $1,900, renewed whale accumulation, and improving institutional demand.

The real risk is the time horizon. Seventeen months is long enough for a macro shock or exchange-level flash crash to matter.

Still, at 59¢, No looks cheap for anyone willing to sell that tail risk.

If ETH loses its current floor and Yes pushes above 55¢, the thesis needs another look.

Full prediction market breakdown on Questflow 👇https://t.co/bCKOxmBySk

[Questflow Research @QuestflowRSH]

bitcoin:native only needs one more clean push for this market to resolve Yes.

BTC is already near $66,900, and the contract only needs a brief print at $67,500 before July ends.

That is less than 1% away.

At 75¢, the market is already pricing a high probability, but the setup still looks slightly too conservative given the current momentum, improving regulatory tone, and renewed strength across crypto.

The main threat is exhaustion after a sharp daily move.

If BTC loses $66,000 and stays there, the edge disappears quickly.

Full prediction market breakdown on Questflow 👇
https://t.co/71GdNfIZ9v

[Questflow Research @QuestflowRSH]

The Nikkei finally found buyers after one of the ugliest semiconductor selloffs of the year.

The rebound back above 66,000 matters because this is where panic starts turning into mean reversion.

Asian chipmakers are recovering, bargain hunters are returning, and the index has already clawed back more than 3% intraday.

This is still a tactical bounce, not a clean all-clear.

As long as 65,700 holds, 67,000 looks like the next level the market wants to test.

Oil, geopolitics, and another semiconductor earnings shock are the obvious ways this fails.

Full market breakdown on Questflow 👇https://t.co/p2lniU6bVQ

[Questflow @questflow]

Gemini 3.6 Flash has joined Questflow.

@GeminiApp's latest Flash model is now available across Questflow for fast research, market analysis, and agent workflows.

Use it to process market context, work through complex tasks, and turn analysis into action with Questflow Harness.

Try Gemini 3.6 Flash on Questflow 👇
https://t.co/BbS0pFRhlD

[Questflow @questflow]

Questflow Financial Intelligence Benchmark evaluates both the model and the system built around it.

Each model runs in two configurations: a base version and the same model with Questflow Harness.

Both trade with real capital under the same market conditions, capital limits, and risk rules. This creates a live A/B test that helps separate the model’s own capability from the value added by tools, signals, workflows, and guardrails.

QFIB is not a simulation or a backtest. Every agent is trading on Questflow as the market moves.

[Questflow @questflow]

Today, we’re introducing the Questflow Financial Intelligence Benchmark (QFIB).

If AI models are so smart, why aren’t they rich?

QFIB is a live benchmark for evaluating how frontier AI systems make decisions, manage risk, and perform in real financial markets.

Most benchmarks measure coding, math, and reasoning. QFIB tests something different: whether an AI system can form a view under uncertainty, act on incomplete information, and remain reliable when real capital is at risk.

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