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Category: finance – Page 3

The Governance Case for Tesla Taking a Pre-IPO Stake in SpaceX

Elon Musk is considering Tesla taking a pre-IPO stake in SpaceX to integrate their businesses, accelerate ambitious projects, and increase the value of both companies ## ## Questions to inspire discussion.

Strategic Governance Alignment.

🔄 Q: Why should Tesla acquire a pre-IPO stake in SpaceX rather than waiting until after the IPO? A: A pre-IPO stake resolves governance and conflict risks before SpaceX’s planned $30B IPO in mid-2026, ensuring all transactions are recorded as part of the IPO and avoiding complications that could impact IPO pricing or create persistent post-IPO conflicts between the two companies.

🎯 Q: What is the core governance problem Tesla shareholders currently face with SpaceX? A: Tesla shareholders are exposed to SpaceX outcomes through dependencies on Starlink connectivity, orbital compute, and launch cadence without any ownership rights, governance rights, or downside protection as the companies converge operationally but not financially.

⚖ Q: How would a pre-IPO stake transaction affect Tesla’s ownership structure and Musk’s control? A: The transaction would dilute Tesla by 20% but could raise market cap to $1.62-2T, increasing Musk’s stake to 22.1–24% and his net worth approaching $1T, enabling him to achieve 25% control significantly earlier than under the compensation plan.

Capital Requirements and Infrastructure.

Continue reading “The Governance Case for Tesla Taking a Pre-IPO Stake in SpaceX” | >

A universal law could explain how large trades change stock prices

Financial markets are often seen as chaotic and unpredictable. Every day, traders around the world buy shares and sell assets in a whirlwind of activity. It looks like a system of total randomness—but is it really?

Scientists have long suspected that there is a hidden order under this noise, but it has been difficult to prove. Now, Yuki Sato and Kiyoshi Kanazawa of Kyoto University have provided some of the strongest evidence yet. By studying eight years of data from the Tokyo Stock Exchange (TSE), they have confirmed a long-standing hypothesis known as the square-root law (SRL) of price impact.

The Universal Law Behind Market Price Swings

Analysis of a large dataset from the Tokyo Stock Exchange validates a universal power law relating the price of a traded stock to the traded volume.

One often hears that economics is fundamentally different from physics because human behavior is unpredictable and the economic world is constantly changing, making genuine “laws” impossible to establish. In this view, markets are never in a stable state where immutable laws could take hold. I beg to differ. The motion of particles is also unpredictable, and many physical systems operate far from equilibrium. Yet, as Phil Anderson argued in a seminal paper [1], universal laws can still emerge at the macroscale from the aggregation of widely diverse microscopic behaviors. Examples include not only crowds in stadiums or cars on highways but also economic agents in markets.

Now Yuki Sato and Kiyoshi Kanazawa of Kyoto University in Japan have provided compelling evidence that one such universal law governs financial markets. Using an unprecedentedly detailed dataset from the Tokyo Stock Exchange, they found that a single mathematical law describes how the price of every traded stock responds to trading volume [2] (Fig. 1). The result is a striking validation of physics-inspired approaches to social sciences, and it might have far-reaching implications for how we understand market dynamics.

Cracking the code of Parkinson’s: How supercomputers are pointing to new treatments

More than 1 million Americans live with tremors, slowed movement and speech changes caused by Parkinson’s disease—a degenerative and currently incurable condition, according to the Parkinson’s Foundation and the Mayo Clinic. Beyond the emotional toll on patients and families, the disease also exerts a heavy financial burden. In California alone, researchers estimate that Parkinson’s costs the state more than 6 billion dollars in health care expenses and lost productivity.

Scientists have long sought to understand the deeper brain mechanisms driving Parkinson’s symptoms. One long-standing puzzle involved an unusual surge of brain activity known as beta waves—electrical oscillations around 15 Hertz observed in patients’ motor control centers. Now, thanks to supercomputing resources provided by the U.S. National Science Foundation’s ACCESS program, researchers may have finally discovered what causes these waves to spike.

Using ACCESS allocations on the Expanse system at the San Diego Supercomputer Center—part of UC San Diego’s new School of Computing, Information, and Data Sciences—researchers with the Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network modeled how specific brain cells malfunction in Parkinson’s disease. Their findings could pave the way for more targeted treatments.

Finding information in the randomness of living matter

When describing collective properties of macroscopic physical systems, microscopic fluctuations are typically averaged out, leaving a description of the typical behavior of the systems. While this simplification has its advantages, it fails to capture the important role of fluctuations that can often influence the dynamics in dramatic manners, as the extreme examples of catastrophic events such as volcanic eruptions and financial market collapse reveal.

On the other hand, studying the dynamics of individual microscopic degrees of freedom comprehensively becomes too cumbersome even when considering systems of a moderate number of particles. To describe the interface between these opposite ends of the scale, stochastic field theories are commonly used to characterize the dynamics of complex systems and the effect of the microscopic fluctuations.

Due to their overwhelming complexity, predicting outcomes by analyzing these fluctuations in living or active matter systems is not possible using traditional methods of physics. Since these systems persistently consume energy, they exhibit dynamical traits that violate the laws of equilibrium thermodynamics, not unrelated to the arrow of time.

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