Sam Bankman-Fried—better known as SBF—was at the top of the world and lauded as a leading figure in cryptocurrency, an industry whose popularity has exploded over the past few years. He was being compared to the legendary financier J.P. Morgan and sometimes even rumored to have the potential to become the world’s first trillionaire. He built a crypto empire with trading firm Alameda Research and crypto exchange FTX, which became one of the world’s largest. He attracted leading investors and walked the corridors of power in Congress. Then, seemingly within days, everything collapsed. FTX went bankrupt, and SBF was arrested, extradited from the Bahamas to the United States, and charged with multiple counts of fraud and other criminal offenses. The world was gripped but left wondering: How did SBF burst onto the scene and take the crypto world by storm only to come crashing down? What makes his case so special? And what does effective altruism have to do with it? Crypto Crackup explores his early days—his road from traditional finance to setting up Alameda and FTX, to the massive crash that swept both away and left SBF potentially facing decades in prison. Crypto Crackup will help you better understand SBF’s spectacular journey, even if you know little to nothing about crypto. If you want to understand more about SBF, how FTX’s bankruptcy left a mess that’s been described as “worse than Enron,” and why so much of this played out on Twitter—this book is for you.
Since the Global Financial Crisis, the structure of financial markets has undergone a dramatic shift. Modern markets have been “zombified” by a combination of Central Bank policy, disintermediation of commercial banks through regulation, and the growth of passive products such as ETFs. Increasingly, risk builds up beneath the surface, through a combination of excessive leverage and crowded exposure to specific asset classes and strategies. In many cases, historical volatility understates prospective risk. This book provides a practical and wide ranging framework for dealing with the credit, positioning and liquidity risk that investors face in the modern age. The authors introduce concrete techniques for adjusting traditional risk measures such as volatility during this era of unprecedented balance sheet expansion. When certain agents in the financial network behave differently or in larger scale than they have in the past, traditional portfolio theory breaks down. It can no longer account for toxic feedback effects within the network. Our feedback-based risk adjustments allow investors to size their positions sensibly in dangerous set ups, where volatility is not providing an accurate barometer of true risk. The authors have drawn from the fields of statistical physics and game theory to simplify and quantify the impact of very large agents on the distribution of forward returns, and to offer techniques for dealing with situations where markets are structurally risky yet realized volatility is low. The concepts discussed here should be of practical interest to portfolio managers, asset allocators, and risk professionals, as well as of academic interest to scholars and theorists.
Since the Global Financial Crisis, the structure of financial markets has undergone a dramatic shift. Modern markets have been “zombified” by a combination of Central Bank policy, disintermediation of commercial banks through regulation, and the growth of passive products such as ETFs. Increasingly, risk builds up beneath the surface, through a combination of excessive leverage and crowded exposure to specific asset classes and strategies. In many cases, historical volatility understates prospective risk. This book provides a practical and wide ranging framework for dealing with the credit, positioning and liquidity risk that investors face in the modern age. The authors introduce concrete techniques for adjusting traditional risk measures such as volatility during this era of unprecedented balance sheet expansion. When certain agents in the financial network behave differently or in larger scale than they have in the past, traditional portfolio theory breaks down. It can no longer account for toxic feedback effects within the network. Our feedback-based risk adjustments allow investors to size their positions sensibly in dangerous set ups, where volatility is not providing an accurate barometer of true risk. The authors have drawn from the fields of statistical physics and game theory to simplify and quantify the impact of very large agents on the distribution of forward returns, and to offer techniques for dealing with situations where markets are structurally risky yet realized volatility is low. The concepts discussed here should be of practical interest to portfolio managers, asset allocators, and risk professionals, as well as of academic interest to scholars and theorists.
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