New Horizons Investment

Institutional Anomalies and The Contrarian Playbook Q1 2026

This podcast discusses significant investment shifts among prominent hedge funds and institutional managers during the first quarter of 2026. These records highlight aggressive portfolio expansions into volatile sectors, such as artificial intelligence infrastructure and distressed retail stocks. Key players like Oaktree and Greenlight Capital executed massive percentage increases in specific positions, signaling a strong contrarian investment strategy despite broader market skepticism. Some firms performed strategic liquidations in major tech and media companies to mitigate risk or lock in profits. This episode serves as a comprehensive overview of how elite institutional investors are navigating a landscape of high-stakes momentum trades and deep-value opportunities. The podcast illustrates a period of bold asset reallocation characterized by high-conviction bets on unloved or emerging market entities.

Adobe: The Infrastructure Layer of AI Creativity

This episode argues that the market is misjudging Adobe’s future by viewing artificial intelligence as a threat to its core business. Instead of succumbing to creative commoditization or pressure from open-source models, the company is positioned to become the essential infrastructure layer for an impending surge in global content. By integrating the Firefly engine into existing professional workflows, Adobe provides the governance, legal safety, and coordination that large enterprises require to manage thousands of AI-generated assets. This thesis suggests that the transition from a software provider to an enterprise AI operating system could lead to a significant financial re-evaluation. While risks like new competitors and shifting monetization trends remain, the primary thesis holds that Adobe will thrive by solving the complex management problems created by the AI-driven content explosion.

Strategic Equity Deep Dives: Analysis of Market Moats and Asymmetry

This episode provides a comprehensive analysis of 20 public companies, evaluating their business models, market positioning, and financial health. The podcast examines established technology and service platforms like Airbnb, Salesforce, and Uber, categorizing them by their ability to generate consistent cash flow and leverage network effects. Each profile highlights a "variant perception," contrasting general market consensus with a specific investment thesis centered on structural shifts or mispriced assets. Beyond individual deep dives, the records include a comparative ranking of various stocks based on value and growth potential. Detailed downside risks, such as regulatory hurdles or competitive pressures, are analyzed to establish clear criteria for exiting a position. The podcast serves as a strategic guide for identifying high-conviction opportunities across diverse sectors like fintech, software, and consumer staples.

The Quality Stack: A Comparative Investment Hierarchy

This episode provides a comprehensive investment analysis of high-quality software and retail businesses, focusing on their long-term durability and current market sentiment. The podcast categorizes elite technology firms like Adobe and Salesforce as essential infrastructure, evaluating how artificial intelligence and shifting enterprise budgets impact their pricing power and growth potential. Beyond the software sector, the podcast examines companies like Airbnb and JD.com, distinguishing between temporary cyclical challenges and permanent structural decay. Each deep dive uses a rigorous framework to assess risk-adjusted returns, looking for mispriced assets where the business's fundamental quality exceeds the market's current narrative. This podcast serves as a strategic guide for identifying reliable compounders and asymmetric opportunities within a changing global economy.

Intelligence as Energy Optimization: The Cost of Thinking

This podcast explores a paradigm shift in artificial intelligence from raw computational power toward a biological model of metabolic efficiency. By implementing a "digital chemistry" layer, AI can move away from intensive brute-force processing and toward a system that utilizes internal states to regulate energy use. Key signals such as curiosity, fatigue, and uncertainty allow the software to dynamically allocate resources, choosing when to think deeply and when to conserve power. This architectural change introduces low-power cycles similar to sleep, enabling the system to optimize its memory and structure during downtime. The episode argues that the future of intelligence is defined by decision-making under limits, where the most successful systems are those that spend energy wisely rather than simply scaling upward.