BEST BUY $BBY JUST REPORTED Q2 EARNINGS - Revenue: $9.8B, beating est. of $9.59B 🟢 - Adj EPS: $1.47, beating est. of $1.38 🟢 - Comparable Sales: +4.1% - Operating Margin: 4.3%; +160 bps YoY RAISES FY27 GUIDANCE - Revenue: $42.3B-$42.8B, above est. of $42B 🟢 - Adj EPS: $6.70-$6.90, above est. of $6.58 🟢 - Comparable Sales: +1.9% to +3.0%, raised from -1.0% to +1.0% - Adj Operating Income Rate: 4.4% to 4.5%, raised from 4.3% to 4.4% - CapEx: ~$750M, unchanged Q3 GUIDANCE - Comparable Sales: +1.0% to +3.0% - Adjusted Operating Income Rate: 4.1% to 4.2%

BEST BUY $BBY Q2’27 EARNINGS HIGHLIGHTS 🔹 Revenue: $9.8B (Est. $9.59B) 🟢; +4% YoY 🔹 Adj. EPS: $1.47 (Est. $1.38) 🟢; +15% YoY 🔹 Comparable Sales: 4.1%; +160 bps YoY 🔹 Oper Margin: 4.3%; +160 bps YoY Raises FY27 Guide: 🔹 Revenue: $42.3B-$42.8B (Est. $42B) 🟢 🔹 Adj. EPS: $6.70-$6.90 (Est. $6.58) 🟢 🔹 Comp Sales: 1.9% to 3.0%; from -1.0% to 1.0% 🔹 Adj. Oper Income Rate: 4.4% to 4.5%; from 4.3% to 4.4% 🔹 Adj. Effective Income Tax Rate: 25.5%; unchanged 🔹 CapEx: ~$750M; unchanged Q3 Guide: 🔹 Comparable Sales: 1.0% to 3.0% 🔹 Adjusted Operating Income Rate: 4.1% to 4.2% Segment Net Revenue: 🔹 Domestic: $9.1B; +4% YoY 🔹 International: $709M; -4% YoY Other Q2 Metrics: 🔹 Domestic Online Revenue: $3.0B; +5.1% comparable 🔹 Domestic Gross Profit Rate: 24.0%; +60 bps YoY 🔹 International Gross Profit Rate: 22.3%; +50 bps YoY Comments: 🔸 “outperformed expectations in the second quarter with comparable sales growth of 4.1% and a higher-than-expected adjusted operating income rate” 🔸 “We are raising our annual financial guidance due to the strong first half performance and our momentum as we enter the second half of the year.”

World Currencies vs. the U.S. Dollar One-Year Change As of June 30, 2026: 🇨🇴 Colombian peso: +19.2% 🇮🇱 Israeli shekel: +13.2% 🇭🇺 Hungarian forint: +8.9% 🇿🇦 South African rand: +8.1% 🇲🇽 Mexican peso: +7.7% 🇨🇳 Chinese yuan: +5.6% 🇦🇺 Australian dollar: +5.2% 🇧🇷 Brazilian real: +5.2% 🇲🇾 Malaysian ringgit: +3.1% 🇳🇴 Norwegian krone: +1.8% 🇨🇱 Chilean peso: +1.0% 🇪🇬 Egyptian pound: +0.8% 🇭🇰 Hong Kong dollar: +0.1% 🇦🇪 UAE dirham: 0.0% 🇶🇦 Qatari riyal: 0.0% 🇸🇦 Saudi riyal: -0.2% 🇷🇺 Russian ruble: -0.4% 🇨🇿 Czech koruna: -1.1% 🇸🇬 Singapore dollar: -1.7% 🇨🇭 Swiss franc: -1.8% 🇹🇭 Thai baht: -2.3% 🇸🇪 Swedish krona: -2.4% 🇪🇺 Euro: -3.0% 🇩🇰 Danish krone: -3.1% 🇬🇧 Pound sterling: -3.4% 🇨🇦 Canadian dollar: -4.1% 🇵🇱 Polish złoty: -4.2% 🇳🇿 New Zealand dollar: -6.8% 🇹🇼 Taiwan dollar: -8.2% 🇵🇭 Philippine peso: -8.2% 🇮🇩 Indonesian rupiah: -9.3% 🇮🇳 Indian rupee: -9.4% 🇯🇵 Japanese yen: -11.3% 🇰🇷 South Korean won: -12.6% 🇹🇷 Turkish lira: -14.6% 🇦🇷 Argentine peso: -18.9% Source: Deutsche Bank, Bloomberg Finance LP.

🧩 Qwen3.8-Flash-Next: A 6B-Active Preview of the Qwen4 Architecture On the same night Zhipu's GLM-5.3-Flash took over the timeline, @Alibaba_Qwen open-sourced Qwen3.8-Flash-Next — explicitly positioned as a preview of the Qwen4 architecture. Zhihu contributor Kitt在进化 argues that for people who actually run models locally, this is the more practical release of the night. The local-deployment groups he is in are, in his words, on fire. His take: the model is called 3.8, but the architecture is really Qwen4 in preview — and it borrows the best ideas from across the field. 1️⃣ Smaller, cheaper, and realistic for local deployment Flash-Next has 125B total parameters with only 6B active — far smaller than the 300B-class GLM-5.3-Flash. The API is priced at ¥1 input, ¥3 output, and ¥0.1 per cached million tokens, roughly matching DeepSeek-V4-Flash's off-peak rates. His comparison, per 1M tokens in RMB — input / output / cache hit: 🔹 Qwen3.8-Flash-Next: 1.0 / 3.0 / 0.1 🔹 GLM-5.3-Flash: 0.4 / 1.4 / 0.115 (limited-time promo rate) 🔹 DeepSeek-V4-Flash (off-peak): 1.5 / 4.5 / 0.05 2️⃣ A Qwen4 preview wearing a Qwen3.8 name The author points out this is the same play Zhipu made: GLM-5.3-Flash's architecture is also completely different from GLM-5.3. Shipping the new architecture as open weights early is deliberate pathfinding. Inference frameworks like vLLM and SGLang, plus the quantization toolchain, all need lead time to adapt before Qwen4 proper arrives. 3️⃣ An architecture that borrows from everyone The author reads Flash-Next as a synthesis of the field's best recent ideas. 🔹 Attention: Qwen's in-house QSA, built to balance throughput and speed on long context. 🔹 Knowledge: it absorbs DeepSeek's Engram line of work, packing prior knowledge into 51B of N-gram side parameters — high knowledge density at minimal compute cost. 🔹 Training: the Muon optimizer, popularized by Kimi, scheduled together with AdamW. 4️⃣ Half the active parameters, still overtaking At 6B active, Flash-Next is nearly half the size of DeepSeek-V4-Flash — yet Qwen's reported benchmarks show it overtaking that model on multiple coding and agent leaderboards. The author says he is not worried about real-world experience: the recent Qwen3.8-27B already proved itself in daily use, and this sits on the same foundation. 🔗 Full Reading: #Qwen# #Alibaba# #Qwen4# #OpenWeights# #LLM# #AIInference# #MoE#

China macro is turning into an extreme dispersion trade. Headline GDP is becoming almost useless.. Japanification, but with geographic arbitrage both domestically and internationally is my closest mental model for what comes next Maybe this is what the last inning of industrial and geopolitical catch-up looks like: hyper-competitiveness abroad, household retrenchment at home. Export strength no longer translates cleanly into household income or confidence; youth unemployment remains elevated at ~16%, even after excluding students. China may be entering a long cycle of Japanification, but with much more room for geographic arbitrage, both within China and across its supply chains. Externally, China looks almost unstoppable: June exports +27% YoY, H1 high-tech manufacturing +13.3%, IC manufacturing +67.3%. Manufacturing PMI crawled back above 50. AI-linked demand and high-end exports are doing the heavy lifting. But some of this demand is borrowed from the future. AI capex is partly a game of musical chairs and future capacity lock-in, while the export surge contains tariff front-loading. Neither is a durable substitute for domestic consumption. Inside China, the picture is almost inverted. Retail sales fell 0.6% YoY in May and grew only 1.0% in June. H1 fixed-asset investment fell 5.7%, property investment fell 18%, and new-home sales value fell 13.6%. The price chain does not look good either: producer input prices +6.4%, factory-gate prices +4.1%, CPI only +1.0%. Costs are moving downstream much faster than consumer pricing power. Many downstream firms have to absorb the gap through thinner margins, intensifying the rat race. Even consumption itself is dispersing. Urban retail was -0.9% in May vs rural +1.5%; in June, +0.8% vs +2.1%. But rural outlets are only ~14% of total retail, and the rural print is policy-sensitive, wont be able to carry the entire economy Japan after the 1980s bubble offers a strong parallel: stagnation from the early 1990s, then persistent deflation from the late 1990s into the early 2010s. But China has a continental shock absorber Japan never had at this scale: a vast interior homeland where housing and daily life are far cheaper, while infra and digital services have narrowed the quality of life gap with tier 1 cities. The option to leave tier 1 cities and return home has become a popular choices for many, this can lower household burn rates and may soften the social transmission of stagnation Writing this, NF’s Hope started playing in my head: Thirty years of running, thirty years of searching Thirty years of hurting, thirty years of pain For China, make it almost fifty. Almost fifty years of running from scarcity since Reform and Opening, searching for modernity, and avg citizens absorbing the pain of remaking an entire society at impossible speed Maybe that is the eternal paradox of industrial catch-up: a country can arrive frontier before its people feel they have.

Last wk, S&P/Nas/Mag7 +0.4%/+0.1%/-0.8%. Cooler inflation (CPI, PPI) & economic data (consumer sentiment, retail sales) but +5% oil steepened the yield curve but lowered odds of a rate hike. Looking forward, I continue to believe the impact of Agentic AI with the advent of OpenClaw on January 30th has at least a year to run: 1) Token production has gone up roughly ~7.5x from the end of January more than offsetting the nearly 50% token cost reduction seen since open-weight model usage started to take off in May. 2) Combined annualized run-rate revenues for OpenAI and Anthropic which ended last year at $29B seems to be around $100B currently with Anthropic getting profitable in Q2. 3) Capex from the Big6 hyperscalers accelerated from 84% y/y/ in CQ1 to 92% in CQ2 with forecasts for nearly 100% in Q3. But this is being supported by cloud revenue growth at the 3 Big Public cloud vendors of $AMZN $MSFT $GOOGL accelerating from 23% y/y in Q1:25 to 35% in Q1:26 to 43% in Q2:26. Arguable more important is public cloud operating margins expanded from 34% to 37% and 39% during those time periods. 4) The $500B financing deal backstopped by up to $125B from $NVDA adds even more lower cost money to fund AI capex spend for the non-hyperscaler players. Nvidia gained 0.5% last week. 5) The liquidation of Situational Awareness and retail accounts during July cleared out some of the frothiness in the AI related names In terms of negatives: 1) The cost of money (yields on government bonds) remain near the highest levels for the 30 yr tenor at 5.3% since 2007. 2) Given large scale offensive US military actions are seemingly off the tablein favor of financial sanctions, probably driven by current election polls, I now believe Iran is likely to hold the Strait of Hormuz hostage until past the US mid-terms. This would be akin to them releasing the US hostages in 1981 (they were held for 444 days) just hours after President Reagan was sworn in replacing Carter. There were severe financial sanctions then also. 3) Since 1990, which happens to be the Gulf War, from the end of July through November 9th, which covers the reaction to all mid-term results, the performance is worse than non mid-term years. For mid-term years the median S&P500 gain from 7/31-11/9 is 0.9% with gains 56% of the time but the median peak loss from 7/31 is 6.2% (intra-period median peak loss of 9.9%.) For non mid-term years the median gain is 2.7% from 7/31-11/9 with gains 59% of the time and the median peak loss from 7/31 is 3.5% (intra-period median peak loss of 5.2%.) This year with the momentum seen by the Socialists which are not big business friendly, I see more risk than normal. 4) The easy money on the AI technical rebound from oversold levels on 7/29 due to the forced sale by Situation Awareness is probably over. There were negative stock reactions to headline beat and raise earnings on both revs & EPS for AI infrastructure winners $CSCO (-8% for the week but still up +45% YTD), $AMAT (-6%/+97%) and $COHR (-14%/+77%). While negatives can always be found, their biggest crime was arguably their recent bounce from 7/29-8/7 of 8%, 24% and 71% respectively and their market beating YTD gains. In summary, I remain bullish. Even from the end of July through November 9th during mid-term years since 1990, the S&P has an additional median gain of 4.2% to its peak before giving some of that back closer to the election. Given some of the negatives, especially the reaction to solid earnings data, I would add some hedges back on further market gains and get more selective. Consumer discretionary hedges should also make sense if oil is higher for longer. I believe value should continue to accrue to the infrastructure layer which includes 1) the public cloud vendors such as Amazon, Microsoft, Google and 2) the semiconductor companies. $INTC, my favorite semi company, still gained 0.8% last week despite: 1) a $20B equity offering which causes ~5% dilution and 2) being up 178% YTD. This clears the funding overhang. All the best in the week ahead.

🇬🇧 England vs Norway 🇳🇴 – All Historical Football Matches 1937: Norway 0-6 England 1938: England 4-0 Norway 1949: Norway 1-4 England 1966: Norway 1-6 England 1980: England 4-0 Norway 1981: Norway 2-1 England 1992: England 1-1 Norway 1993: Norway 2-0 England 1994: England 0-0 Norway 1995: Norway 0-0 England 2012: Norway 0-1 England 2014: England 1-0 Norway England wins: 7 Draws: 3 Norway wins: 2