The last decade has witnessed a phenomenal surge of interest in cryptocurrencies and Decentralized Finance (DeFi) from the general public, businesses, and financial markets alike. Starting as niche technological innovations, these digital assets have grown rapidly, driven by investors searching for alternative opportunities in a low-yield environment. This growth, however, has been characterized by high market volatility and record-high market valuations. The massive capitalizations achieved by cryptocurrencies like Bitcoin (BTC) and Ethereum (ETH) have raised crucial questions about their overall "footprint" on the existing global financial system. Are traditional financial giants—the banks—embracing this new technology, or are new, less-regulated entities taking over?

The modern financial market, once dominated by human brokers shouting orders on exchange floors, is now a hyper-speed landscape ruled by algorithms and Artificial Intelligence (AI). This massive shift, accelerating since the introduction of electronic trading in the 1970s and algorithmic trading in the 1990s, has transformed the behavior, liquidity, and risk profile of global stock markets. Today’s AI-powered microstructure offers undeniable benefits, making trades cheaper and execution faster. However, this new automated efficiency comes with a crucial caveat: while AI improves the average, day-to-day quality of the market, it dramatically elevates "tail-risk"—the rare but severe potential for sudden, massive dislocations. The net effect of AI on the market is therefore conditional.

Corporate financial strategy hinges on the ability of management to make optimal investment decisions, typically defined by two primary rationales: maximizing profit and/or maximizing market value. An asset should only be acquired if the expected rate of return surpasses the interest rate (profit maximization) or if the cost of acquisition is less than the value it adds to the corporation’s market value