Welcome to Nofinity

This video argues that after a 17-year bull market with gains of over 1100% (S&P 500) and 2000% (NASDAQ), the market is extremely overvalued. The question is not how high it can go, but how low it can go. The speaker warns of a potential correction or crash, drawing on historical parallels and identifying possible triggers.

• Dividend Yield at Historic Low: The S&P 500 currently yields about 1%, compared to the historical average of 4%.
  • Example: A return to a 2% yield would imply a 50% price drop.
  • Problem: Compared to the safe 10-year US Treasury yielding 4%, stocks look unattractive.
• Shiller CAPE Ratio: The cyclically adjusted price-to-earnings ratio is far above the historical average of 16.
  • Calculation: At a CAPE of 30 (current vicinity), a -27% drop is possible; at a CAPE of 16, even -61%.
• Comparison to the Dot-Com Bubble: The NASDAQ fell 76% from 2000 to 2002—despite the "Internet changing the world" narrative.

• US Fiscal Deficit: High government spending supports the economy and liquidity.
• AI Investment Boom: Massive capital expenditures boost markets.
• Global Capital Inflows: 401(k) plans and international investors continue flowing into the S&P 500.
• Share Buybacks: $1 trillion annually artificially props up prices.

• Inflation and Rising Rates: Higher rates reduce stock attractiveness and the government's ability to borrow. Without government spending, the US economy would have stagnated over the last five years.
• Profit Decline and Overinvestment: If AI investments fail to yield returns, profit expectations could collapse.
• Demographics: Baby boomers retiring could trigger panic selling.
• Decline in Buybacks: If companies buy back fewer shares, demand drops.
• Foreign Investor Withdrawal: They invest for profit and may retreat in case of losses.

• Crash by 2030: A 60% decline in the S&P 500 to around 3,000 points is considered possible. (Note: Just four years ago, the index was near that level.)
• Historical Parallel: After a 17-year bull market, the market can lose 60% within a year.

1. Hedging and Dividend Strategy: The speaker himself uses hedges and dividend stocks to protect his portfolio.
2. Cash Out and Exit: Those who have profited over the last 17 years could shift into treasuries (e.g., $5 million at 4% = $200,000 annual interest) and enjoy life.
3. Stay Long but Hedged: Using options or structured products for protection.

The speaker emphasizes: "What we have experienced in the last 15–17 years is unlikely to repeat in the next 10–15 years." Investors should not anchor to recent euphoria but respect historical valuation patterns.

Summary follows...

In this video, Mario Lochner explains the Core-Satellite Strategy to build the perfect portfolio. He reveals why most investors fail (overconfidence, impulsiveness) and how to achieve long-term success through automation and psychological tricks.

• The earlier you start, the stronger the compound effect. Example: €1 at 10 % annual return grows to €647 by age 65 if you start at 0, but only €88 if you start at 20.

• A JP Morgan study shows the average investor earns only 1.9 % – worse than any asset class.
• Researcher Hendrik Bessenbänder found that only 2.4 % of all stocks create lasting net wealth. The rest underperform Treasury bills.

• Beta = market return (systematic), e.g. via an ETF like the MSCI World.
• Alpha = excess return (unsystematic) through individual stocks, crypto, or targeted bets.

A solid core (70–85 % of the portfolio) of broadly diversified ETFs captures market returns. Around it orbit satellites (15–30 %) for alpha – e.g. single stocks, gold, or crypto. This calms your psychology and prevents decision errors.

• Define the capital’s purpose (wealth building, retirement, etc.).
• Four conditions: reflects the desired return source, broadly diversified, cost-efficient, crisis-proof.
• Simplest solution: 100 % all-world ETF (e.g. Vanguard FTSE All‑World or SPDR MSCI ACWI).
• Avoid fake diversification: MSCI World, S&P 500, and Nasdaq 100 overlap heavily (many identical top holdings).

Each satellite must have a clear thesis. Before buying, answer 5 questions:

1. Strategic or tactical?
2. Primary mission?
3. Neutral alternative?
4. How to measure success?
5. What disproves the thesis, and what is the maximum acceptable loss?

Example: Max satellite weight = acceptable portfolio damage (max 2 %) divided by conservative stress loss (50 %) → max 4 %.

• Core (70 % = €70,000)
  • North America: €32,200
  • Japan: €6,300
  • Europe: €16,100
  • Emerging Markets & Pacific: €15,400
• Satellites (30 % = €30,000)
  • Bitcoin: €6,000
  • Individual stocks: €15,000
  • Gold: €9,000

Free eBook „10 ETF Mistakes“ and „50 Money Mistakes That Keep You Poor“ – link in the description.

• BitMEX: Shuts down after 11 years, inventor of the perpetual swap. Daily volume fell to under $400k (0.01% of the market), squeezed by Binance and Hyperliquid.
• Storage: Decentralized storage network; parent company files Chapter 11 due to debt from acquiring GPU firm Valdi ($1-10M).
• Regulatory casualties: Ascend EX (due to MiCA), EXMO (UK sanctions) – insolvency and frozen funds.
• Runway problems: Projects like Odos, Dango, Leap Wallet, Entropy – simply ran out of money or gave up after exploits.

• 2022: Fraud and contagion (FTX, Celsius) – missing customer funds, systemic crises.
• 2026: Rationalization – independent, unprofitable companies close orderly. Withdrawals still work. No major scandals.

• Companies like Strategy (formerly MicroStrategy) had to sell Bitcoin for the first time to pay preferred dividends. The "Never Sell" doctrine is broken.
• Over $62B in market cap of such firms evaporated in June 2026.
• These are forced sales from buyers at the top – a classic bottoming signal.

• Crypto miners are pivoting to AI infrastructure providers. They sell Bitcoin to fund data centers for AI (e.g., Terawolf, Hut 8).
• Cost per megawatt for AI is 10-20x higher than for mining. This is capital rotation, not panic.
• Forecasts: AI could make up 70-80% of major miner revenue by end of 2026.

• Long-term holders (LTHs) realize 43% of all losses – a sign of capitulation.
• Exchange balances at 7-year low (2.21M BTC), coins moving to cold storage.
• Perpetual funding neutral – leverage is mostly purged.
• ETF outflows in June ($4.5B), but first inflows in July suggest exhausted sellers.

• The drawdown of 51% (from ATH at $126k) is still shallow compared to previous bear markets (78-84%).
• A final flush could still be ahead, but structural demand from ETFs and Treasury buyers cushions the fall.

• The death of many crypto firms and forced sales from treasury companies are part of a normal bottom formation process.
• Historically, buying at the bottom (2018, 2022) yielded massive returns (700-2000% over 24-36 months).

Scientists engineered an enzyme called CMLase that removes sugar-induced damage from proteins – a process previously considered irreversible. The study explains how the Maillard reaction (like toasting bread) creates Advanced Glycation End Products (AGEs), which drive inflammation and tissue stiffening. CMLase specifically targets Carboxymethyllysine (CML) and restores the native amino acid.

Key Results:

• In vitro: 52–97% removal of CML on model proteins.
• Ex vivo on human tissue:
  • Abdominal aorta (75-year-old donor): >70% reduction in CML damage.
  • Skin (75-year-old donor): Over 55% reduction – levels dropped below those of a healthy 31-year-old control.
  • Eye lens proteins (64-year-old donor): Reversal of CML modifications, restoring youthful chemical profile.

Practical Glycation Prevention:

• Diet: Avoid dry, high-heat cooking (grilling, air frying); use steaming, boiling, or acidic marinades (lemon juice, vinegar).
• Blood Sugar Control: Minimize post-meal glucose spikes.
• Enzyme Support: Boost glyoxalase-1 activity with sulforaphane (e.g., broccoli sprouts).

Caveats:

• CML is only an adduct, not a structural cross-link (like glucosepane). True tissue elasticity restoration must be proven in live organisms.
• Study funded by Revel Pharmaceuticals and Calico Life Sciences (Google) – commercial interests exist.
• Systemic therapies (e.g., for arterial stiffness) are distant; initial applications likely topical (creams, eye drops).

This work proves aging damage is reversible, but further trials are needed.

Note: No imperial units were present in the transcript; no conversion needed.

This video analyzes Michael Burry's current investments and short positions, with a special focus on Flutter Entertainment. Burry sees the market in a massive bubble and predicts a crash similar to 1987. His bets hinge on regulatory intervention that could benefit established companies like Flutter.

1. General Market Assessment & Crash Prediction

• Dividend yield at historic low: At its lowest point in 145 years, this historically contributed 10% of market returns.
• Distorted earnings: Stock-based compensation inflates reported profits; real earnings power is weaker.
• Bubble risk: Only 1.92% of the time in the last 15 years has the market been over 20% below its peak—an unprecedented situation. Burry expects a 1987-style crash, triggered by artificial demand (e.g., AI boom) and leveraged positions.

  Key term: Momentum-driven market – Prices rise only through momentum, not fundamentals.

2. Burry's Current Bets & Shorts

• Shorts: Semiconductors (Oracle, Nvidia, Palantir, Tesla, Micron) and others (e.g., Caterpillar).
• Long positions (e.g., Lululemon, Adobe, JD.com, PayPal) have gained 20–43% since Burry's entry.

3. Focus: Flutter Entertainment – A Bet on Regulation

• Situation: Stock down over 60%; market cap at $111B (vs. expected $368B).
• Growth outlook: Online gambling market expected to nearly triple. But Flutter's revenue growth is weak at only 3%.
• Financial issues:
  • High debt (leverage ratio rising despite buybacks).
  • Goodwill & intangible assets: Bloated by over $20B from acquisitions.
  • Free cash flow low after adjusting for stock-based compensation and restructuring costs.
• Burry's thesis: A regulatory shock (e.g., stricter rules for challengers) could give Flutter a massive boost. This is not a value investment but a bet on political intervention.
• Risk vs. Reward: Upside of 2–3x (if successful) but high volatility. A worst-case scenario (company sale) provides a margin of safety of about $10B.

4. Conclusion & Takeaway

• The speaker himself avoids such bets ("not my style") but sees learning potential in Burry's analyses.
• Suitable for investors with high risk tolerance speculating on regulatory changes.

Metric Conversions: No imperial units in transcript; all figures in USD and percentages directly.

In this Bankless episode, Ilia Polosukhin, co-founder of NEAR, explains the latest development: By staking NEAR tokens, users gain access to AI inference on the NEAR AI Cloud. This is a significant upgrade that directly connects the NEAR token to the AI ecosystem.

What is NEAR AI Cloud?

• Vertically Integrated Stack: NEAR combines blockchain, cryptography, and AI into a cohesive unit.
• Confidential and Verifiable AI: Users can leverage AI models without their prompts or responses being seen or censored by third parties.
• Open Models: Supports open-weight models like DeepSeek or GLM.
• Verifiability: Every request is signed cryptographically, documenting the entire processing chain.

How Does the Staking Model Work?

• Staking Instead of Paying: Instead of directly paying for AI usage, users stake NEAR tokens. The staking rewards are allocated to compute providers.
• Proportional Access: The more NEAR staked, the more AI access. This is described as "Universal Basic AI."
• Economics: This mechanism allows consuming AI compute without selling tokens.

The Connection to Confidential Intents

• Holistic Ecosystem: NEAR connects AI with a marketplace for compute resources.
• Intents as Marketplace: Through Confidential Intents, GPU resources can be traded, bringing transparency and liquidity to an opaque market.
• Value Creation: Every transaction on these markets generates fees, partially burning the token and increasing NEAR's value.

Partnerships and Use Cases

• Venice.ai and Brave: These platforms use NEAR AI Cloud to offer private and verifiable AI to their users.
• Government of Bermuda and Abound: Usage for sensitive areas like financial information and remittances.
• Autonomous Companies: Ironclaw, an AI agent, demonstrates how staking-based AI hardware can operate long-term.

Future and Vision

• Compute Marketplace: NEAR aims for a transparent market for compute resources, akin to commodities.
• AI as Operating System: The vision is AI becoming the central interface, not just a tool.
• Scaling and Product Maturity: Focus on enhancing existing products and achieving market readiness.