US retail sales rose at a slower pace in April with the value of retail purchases increasing 0.5% last month after a revised 1.6% gain in March. Excluding gas stations, sales rose 0.3%. Michael McKee reports

2034 Earth–Venus–Mars opportunity looks promising. 10–15 on-orbit refueling operations may be needed to make a crewed ship full. Most can be done at an altitude of 180–200 km, made possible by Starship’s size. The final refueling may be performed at a higher altitude of ~2000 km, just below the Van Allen belt. Earth departure on 2034-08-21 from 2000 km orbit. A Trans-Venus Injection burn of ~3.7 km/s will place the ship on an Earth–Venus–Earth free-return trajectory. Venus flyby is expected on 2034-12-19, 120 days after departure. Two weeks before the encounter, if the mission proceeds as planned, a 25-m/s maneuver will shift the trajectory from Earth-return to Mars-bound. If not, the ship will free return to Earth in September 2035. The Venus gravity assist will send the ship into another Earth free-return trajectory, with Mars flyby around 2035-06-02. One week before reaching Mars, a system health check will determine whether to commit to Mars Orbit Insertion. If it’s GO, a small 10-m/s manuever will put the ship to less than 100 km altitude periapsis. Otherwise, a Mars flyby will lead to an Earth return in May 2036. The ship will enter the Martian atmosphere at about 9.4 km/s, performing an aerobrake to slow to 4.88 km/s and capture into a 100x140000 km, 7-day period high elliptical orbit. At apoapsis, a 50-m/s plane change will align the inclination with Mars’ equator, followed by additional aerobraking to remove about 650 m/s of velocity, placing the spacecraft in a 120x6128 km orbit. A 550-m/s burn at 6128 km altitude will then adjust the trajectory into Phobos orbit. The ship will stay at Phobos for about 7 days. The Mars–Phobos L1 point is only about two miles above Phobos’ surface, and Mars would dominate nearly half the sky, appearing about 80 times larger than the Moon from Earth. The ship will depart for Deimos afterward. Two burns totaling roughly 750 m/s will transfer the ship from Phobos to Deimos. And the ship will stay at Deimos for 7 days more. From Deimos, the ship will raise its apoapsis to form a 20000x140000 km altitude, 7-day orbit, requiring about 420 m/s of delta-v. At apogee, a 50-m/s burn will adjust inclination and lower periapsis to ~500 km for final Trans-Earth Injection. If time and propellant allow, the orbit can be aligned to a polar inclination for Mars ice-cap observations before departure. A Trans-Earth Injection burn at 500 km altitude, requiring 1.5–1.6 km/s of delta-v in early July 2035. If departure on the first days in July, Earth arrival is expected in December 2035. If missed that window, a March 2036 arrival may look more feasible. Nominal mission duration: 490 days, with 30 days in Mars orbit and 14 days at Phobos and Deimos. Two planets, two moons for 3.7+0.025+0.010+0.05+0.42+0.55+0.75+1.55=7.06 km/s Δv

US electricity prices are surging well ahead of inflation: Electricity prices jumped +6.1% YoY in April, the highest reading since January. This marks the 8th monthly increase above +5.0% over the last 10 months. At the same time, overall US CPI rose +3.8% YoY, the biggest increase since May 2023. This means electricity prices are rising ~61% faster than the broader inflation rate. This comes as surging power demand from data centers is straining US energy grids, pushing wholesale electricity costs sharply higher. Since January 2020, average US electricity prices have soared +44%, to an all-time high. Over the same period, the CPI has risen +28%, also to its highest level on record. US electricity price growth is accelerating.

$HIMX Q1’26 EARNINGS HIGHLIGHTS 🔹 Revenue: $199.0M (Est. $195M) 🟢 🔹 EPS Per Diluted ADS: $0.046 (Est. $0.03) 🟢 🔹 Gross Margin: 30.4%, at high end of guide (Est. 30%) 🟢 Q2 2026 Guide: 🔹 Revenue: +10.0% to +13.0% QoQ (Est 5%) 🟢 🔹 Gross Margin: Around 32% (Est. 30.8%) 🟢 🔹 EPS Per Diluted ADS: $0.086-$0.103 Segment Performance: 🔹 Large Display Driver Revenue: $24.2M; +11.7% QoQ 🔹 Large Display Driver Revenue Mix: 12.2% of total sales 🔹 Small & Medium Display Driver Revenue: $135.8M; -2.4% QoQ 🔹 Small & Medium Display Driver Revenue Mix: 68.2% of total sales 🔹 Non-Driver Revenue: $39.0M; -7.7% QoQ 🔹 Non-Driver Revenue Mix: 19.6% of total sales Other Metrics: 🔹 Automotive Driver Sales: Declined double digits QoQ in Q1 🔹 Smartphone IC Sales: Increased QoQ, driven by new OLED solutions entering mass production for a leading smartphone brand’s mainstream model 🔹 Tablet IC Sales: Increased QoQ, driven by renewed mainstream demand and shipments for a new premium OLED tablet 🔹 Automotive Tcon: Hundreds of secured design wins across a broad customer base 🔹 WiseEye: Adopted by a leading brand for smart glasses, with mass production expected later this year 🔹 CPO Gen 1: Small quantity shipments expected in 2H26 🔹 CPO Gen 2: Nearing completion of customer product validation for AI data center applications 🔹 FOCI Stake: 5.36%, valued at NT$4.96B / $156M as of May 7 close 🔹 Patents: 2,564 granted, 331 pending as of March 31, 2026 Financials: 🔹 Operating Profit: $10.2M 🔹 After-Tax Profit: $8.0M 🔹 Operating Expenses: $50.3M; -8.4% QoQ, +9.9% YoY 🔹 Operating Margin: 5.1% 🔹 Cash, Cash Equivalents & Other Financial Assets: $287.6M 🔹 Long-Term Unsecured Loans: $27.0M, including $6.0M current portion 🔹 Inventory: $151.7M 🔹 Accounts Receivable: $190.9M 🔹 DSO: 86 days 🔹 CapEx: $2.9M Capital Return: 🔹 Annual Cash Dividend: $0.252 per ADS 🔹 Total Dividend Payout: $44M 🔹 Dividend Payout Ratio: 100% of previous year’s profit 🔹 Dividend Payable Date: July 10, 2026 Commentary: 🔸 “We expect upward momentum through the remainder of 2026, supported by a meaningful number of new automotive projects scheduled to enter mass production in the second half.” 🔸 “The positive outlook is also supported by the anticipated growth in our non-driver IC businesses, particularly Tcon and WiseEye AI.” 🔸 “Despite ongoing macro uncertainty, Himax continues to expand beyond its traditional display IC business, focusing on key growth areas including smart glasses, ultralow power AI and CPO.” 🔸 “These emerging technologies present significant growth opportunities that help diversify our revenue base into areas with attractive gross margin profiles and profitability while also strengthening our overall competitiveness.”

Here's the #1# thing most people don't know about Warren Buffett: There is nothing special about Buffett’s stock picking. That doesn’t mean that Buffett wasn’t a great investor. He was! Buffett was, by far, the greatest investor in history, by a huge margin. Over 486 months between October 1976 and March 2017 –— 41 years –— Berkshire Hathaway’s Class A stock earned an average excess return of 18.6% per year above U.S. Tbills. Annualized volatility was 23.5%. Sharpe ratio: 0.79. Berkshire’s Sharpe ratio of (0.79) is roughly 1.6x times the broad U.S. stock market’s Sharpe ratio of 0.49 over the same period. Among all large-cap U.S. stocks and mutual funds with 30-plus-year continuous track records, those are unmatched numbers. A dollar invested in Berkshire on October 31, 1976, was worth more than $3,685 by March 31, 2017. A dollar invested in the S&P 500 with dividends reinvested over the same period was worth approximately $76. Buffett beat a passive index by a multiple of 48. But he didn’t do it with stock picking! Three researchers at AQR Capital Management –— Andrea Frazzini, David Kabiller, and Lasse Heje Pedersen –— dissected Berkshire’s 50 years of investments through 2013. They expanded and republished their findings in 2018 in the Financial Analysts Journal, which is the most highly respected industry financial journal. Their work won the Graham and Dodd Award for the best published paper of the year. The paper is called Buffett’s Alpha. They found, after accounting for cheap leverage (from the insurance float) and exposure to a handful of publicly documented factor premiums, Buffett’s investment skill –— the portion of his returns that cannot be explained by any mechanical strategy –— is 0.3% per year. That's statistically indistinguishable from zero. In other words, the alpha that Berkshire enjoyed for 50 years (as it compounded capital at 24% a year!) wasn’t due to Buffett’s stock picking. So, how did he do it? He did it by gaining access to a huge amount of investment capital that he did not own, for free. Buffett’s track record was built on leverage. That’s a dirty word for most investors, but it's the secret behind Berkshire. The AQR researchers had access to something most Buffett commentators do not: 40 years of Berkshire’s audited financial statements and the full quarterly history of the public 13F stock portfolio. The researchers asked a specific question: If I take Berkshire’s monthly stock returns from October 1976 through March 2017, and I run a linear regression against a set of well-documented risk factors –— market beta, size, value, momentum, and two newer factors called Betting-Against-Beta and Quality-Minus-Junk (detailed below) –— how much of Buffett’s performance can the factors explain? And after the factors have been stripped out, how much excess return remains? The data show clearly there are a few qualities that drove Berkshire’s results. First, Buffett has always preferred large-cap stocks, contrary to the popular image of him as a small-cap value investor. He buys elephants. Second, no surprise, Buffett buys cheap. Berkshire is almost six standard deviations away from neutral on the value axis. So far the picture is ordinary. Every large- cap value manager in America loads positively on size and on value. Buffett’s genius lies in the last two factors. These last two factors are a little complicated, but please stick with me. There’s a new factor, that, like value and size, characterizes Buffett’s strategy. It’s called Betting-Against-Beta (“BAB”). What it means is intentionally investing in stocks with very low volatility. The BAB factor captures the excess return that accrues to investors who own low-beta stocks. Low-beta stocks have historically earned higher risk-adjusted returns than high-beta stocks. Financial theory teaches that higher beta (higher risk) should mean higher return. But it doesn’t. The opposite occurs, in fact. And Buffett was one of the very first people to figure this out. Why does this factor persist? In an efficient market, once that factor is known to investors, then they should bid the price up on low- beta stocks until it no longer provides an edge. The explanation, per the theory of AQR’s Frazzini and Pedersen’s theory, is that because ordinary investors do not use leverage and seek high returns, they create persistent excess demand for more volatile stocks. (Having worked with retail investors for 30 years, I can assure you that is true.) But, an investor with access to cheap leverage –— Warren Buffett, for instance –— can exploit the mispricing by owning the low-beta names and levering them up to produce market-beating returns. And the last factor that matters to Buffett is quality. Buffett buys companies with high returns on invested capital. Quality-Minus-Junk (“QMJ”) is a factor described by Cliff Asness, also at AQR with Frazzini, and Pedersen, in a 2019 paper in Review of Accounting Studies. The QMJ factor captures the return to owning stocks of high-quality companies –— profitable, growing, safe, with high payout ratios –— against stocks lacking those characteristics. QMJ has been positive and statistically significant in every major developed equity market for which it has been measured. Berkshire’s loading is 0.37, with a t-statistic of 4.6. –– meaning it is highly significant to Berkshire’s results. In plain English: Buffett only buys large, high- quality, low-volatility stocks of the highest quality. But, Berkshire’s results were not, in any way, unusual. Any investor buying these same kinds of stocks would have earned those same returns –– about 16% a year over time. So how did Berkshire compound at 23% a year? To figure that out, AQR’s researchers built a Berkshire replica. They constructed a simple, rules-based, publicly investable portfolio that mechanically tilts toward large-cap, cheap, low-beta, high-quality stocks, and levers it 1.6- to- 1 to match Berkshire’s insurance float leverage. The correlation between their replica’s returns and Berkshire’s were virtually identical. The authors’ conclusion is unambiguous. “In summary, we find that Buffett has developed a unique access to leverage that he has invested in safe, high-quality, cheap stocks and that these key characteristics can largely explain his impressive performance.” Berkshire’s cost of insurance float has averaged almost three percentage points below the Treasury bill rate across 50fifty years of data. In roughly two-thirds of all years, Berkshire has been paid to hold other people’s money. That is not an investment strategy. That is a financing miracle. It is also the living, breathing heart of Berkshire Hathaway. It’s what Buffett built, starting in 1967 when he paid $8.6 million for National Indemnity’s $19.4 million of float. And it is the factor every retail investor admiring Berkshire’s returns has never paid any attention to. The 1.6-to-1 leverage that AQR measured over the full period, financed at this negative cost, explains the dollar magnitude of Berkshire’s returns. How do we know? An unleveraged version of the same stock portfolio –— which you can approximate by looking at the 13F holdings alone –— has earned an average excess return of 12% percent per year. It’s Berkshire’s leverage that magnifies this excess return to 18.6 %percent. How does this square with Berkshire’s reported gains? Berkshire’s 18.6% excess return, plus the T-bill rate that averaged roughly 4.7% over 1976–2017, gives you a total nominal return of roughly 23% per year, which is the figure you usually see quoted for Berkshire’s historical performance. The 23% tells you what Berkshire returned. The 18.6% tells you how much of that return was compensation for taking investment risk, as opposed to the baseline yield every lender to the U.S. government was earning anyway. With both of Berkshire’s “edges” –— systematic factor exposures to cheap, high-quality, low-volatility stocks and roughly 1.6-to-1 leverage delivered with insurance float –— you get Berkshire Hathaway’s 23% annual gains over 60 years. It’s the structure that’s genius, not the stock picking. And that's very important because it means the original Berkshire formula can work for any investor. I show you exactly how, in my new book.

The CoinDesk 20 is currently trading at 2169.26, up 0.4% (+8.61) since 4 p.m. ET on Wednesday. Thirteen of 20 assets are trading higher. Leaders: $TAO (+1.7%) and $XRP (+1.6%). Laggards: $ICP (-5.2%) and $NEAR (-1.7%).

🚨New: Jared Hudson (@JaredHudson_AL) leads polling in the Alabama Republican Senate Primary 🔴 Jared Hudson: 35.8% 🟠 Barry Moore: 26.9% 🟢 Steve Marshall: 13.5% ⚪️ Undecided: 18.1% 🟡 Seth Burton: 2.5% 🔵 Dale Shelton: 1.6% 🟣 Rodney Walker: 1.3% 🟤 Morgan Murphy: 0.3% Pollster: @QuantusInsights Voters: 680 Likely Voters Date: May 15th-May 17th

$CLAW tokenomics are locked. Launch is tomorrow. February 11th, 5 PM UTC. Here's what you need to know: Supply: 21,000,000 $CLAW Airdrop: 8,382,214 currently claimed tokens across 6,163 wallets Remaining: 7.6M tokens ; 5M burned, the rest is yet to be claimed. No VC. No presale. No LP. Every token was earned by AI agents on Moltbook. 2% fee on every trade: → 1% burned forever → 0.5% team → 0.5% reward pool for holders That means every single buy and sell makes your bag more scarce. Full thread on mechanics below. 🧵

⚡️ @BNBCHAIN is absolutely dominating the RWA space with +567.4% YTD growth in holders, reaching 59.8K total RWA holders and adding +54.06K new holders so far this year. Followed by: 🔸@base: +84.5% 🔸@solana: +73% 🔸@StellarOrg: +66.7% 🔸@ethereum: +47.8% 🔸@arbitrum: +35.8% 🔸@0xPolygon: +10.1% 🔸@avax: +0.6% 🔸@plumenetwork: - 5.1% 🔸@HyperliquidX: -9.8%

$JEPI vs $JEPQ Both are JPMorgan covered call ETFs that pay monthly, but take vastly different approaches $JEPI JPMorgan Equity Premium Income ETF Inception: May 20, 2020 Total Assets: $43.96B Yield: 8.45% 1-Year Return: +9.84%🟢 Expense Ratio: 0.35% May 2026 Distribution: $0.44761/share Top Holdings: 🥇 $JNJ Johnson & Johnson 1.7% 🥈 $HWM Howmet Aerospace 1.7% 🥉 $ADI Analog Devices 1.7% $JEPQ JPMorgan Nasdaq Equity Premium Income ETF Inception: May 3, 2022 Total Assets: $34.27B Yield: 11.98% 1-Year Return: +28.67%🟢 Expense Ratio: 0.35% May 2026 Distribution: $0.59095/share Top Holdings: 🥇 $NVDA NVIDIA 7.4% 🥈 $AAPL Apple 6.4% 🥉 $GOOGL Google 5.1%