While many books talk about forecasting and decision making, this one is particularly engaging because of Kenneth A. Posner’s personal experience – and the honesty with which he discusses it. As a longtime analyst at Morgan Stanley, Posner had to make decisions about whether to invest in many recent high-profile, high-stakes “Black Swan” anomalies. He explains general models and approaches to dealing with uncertainty, sorting information, and developing your analytical skills and judgment. That alone is worthwhile, but the book is especially lively when Posner reviews his specific decisions. He shares his reasoning and exposes his successes and his failures to public view. The result is a knowledge-dense but very readable work that getAbstract recommends to all analysts, but also to those who want to deal with information overload and improve their decision making.
Dealing with Uncertainty
Predicting any future event is hard enough, but predicting a “Black Swan” is harder. Nassim Nicholas Taleb brought the term “Black Swan” into circulation as a metaphor for being blinded by past experience when you face surprising phenomena. He wrote of Europeans who were stunned to see black swans in Australia, since they thought Europe’s white swans were the only type in existence.
Black Swans symbolize anomalies that appear abruptly and don’t fit your worldview. No one can foretell all Black Swans, but “fundamental research” can help you predict some of them, recognize them faster than other people and respond to them more quickly.
While Black Swans occur in all fields, financial markets are especially vulnerable, since they combine the physical world, social interactions and complex organizational patterns. Sudden natural events, such as earthquakes and avalanches, are a reminder of forecasting’s volatile challenges. Weather also is subject to the “butterfly effect,” where small actions in one place may produce disproportionate reactions elsewhere. Because of this effect, weather predictions are often good in the short run, but diverge...