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Reconciliation efforts soon derailed, as this chapter shows. Conflicting interests between the U.S., the Taliban, and the Karzai government meant that the reconciliation process was lacking progress. While a Strategic Partnership Agreement seemed to realign the U.S. and Afghan governments, poor coordination of the opening of the Doha office and the transition ceremony from ISAF to Afghan forces set back the relationship. By continuing the drawdown, the U.S. was losing negotiating leverage.

Desert Storm generated significant support for defense reform. This momentum was due in part to the timing of the war and the celebrity status General Schwarzkopf enjoyed following the US victory. With the end of the Cold War on the horizon and domestic pressure building to embrace the “peace dividend,” the conditions were set for policy makers and national security organizations to be more receptive to change. Schwarzkopf’s popularity ensured that any critiques he made were taken seriously and their legitimacy little questioned. Despite Schwarzkopf’s complaints being misplaced and later partially recanted, his words were embraced by policy makers and were influential in building the momentum for change. In this regard, Schwarzkopf can be both criticized for his uninformed criticism of the Intelligence Community and credited for the change his comments helped generate.

This chapter provides evidence that large financial crashes are “outliers.” It first considers the limitation of standard analyses for characterizing how crashes are special before explaining what abnormal returns are. It then discusses the results of a study of the frequency distribution of drawdowns, or runs of successive losses, and shows that large financial crashes form a class of their own that can be seen from their statistical signatures. It also examines the expected distribution of “normal” drawdowns, along with the drawdown distributions of stock market indices such as the Dow Jones Industrial Average and the Nasdaq index. The chapter argues that the presence of outliers is a general phenomenon and concludes by describing how large drawdowns and crashes that result from a run of losses over several successive days affect the regulation of stock markets.

A diverse set of measures allow investors to evaluate hedge fund portfolio managers’ performance across different dimensions. The various measures quantify the effectiveness of security selection; account for investor flows, operating risk, and worst-case investment scenarios; net out benchmark and peer-fund performance; and control for risk factors that are unique to hedge fund investment strategies. Hedge fund return information in published databases is usually self-reported, which is a conflict of interest that produces several reporting biases and inflated published average returns. After adjusting for these biases, hedge fund average returns trail equity market returns and in fact almost exactly equal U.S. Treasury bill average returns between January 1994 and March 2016. Yet, after risk adjustment, the hedge fund performance picture brightens. In the aggregate, hedge funds have higher Sharpe ratios and multifactor alphas, and lower maximum drawdown levels than equity market benchmarks.

The financial crisis of 2007–2008 reopened the debate about the need for identifying a correct risk measurement in financial time series. Different risk measurements give rise to different risk-adjusted performance values. The most used and best known measurement is the Sharpe ratio, although other risk-reward ratio specifications attempt to correct for its shortcomings. This chapter describes the most popular ratios in the academic literature beyond the mean-variance approach and discusses their advantages and disadvantages. This chapter also provides an analysis of results when calculating risk ratio-based rankings.