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In Show Time, Lee Ann Fujii asks why some perpetrators of political violence, from lynch mobs to genocidal killers, display their acts of violence so publicly and extravagantly. Closely examining three horrific and extreme episodes—the murder of a prominent Tutsi family amidst the genocide in Rwanda, the execution of Muslim men in a Serb-controlled village in Bosnia during the Balkan Wars, and the lynching of a twenty-two-year old Black farmhand on Maryland's Eastern Shore in 1933—Fujii shows how "violent displays" are staged to not merely to kill those perceived to be enemies or threats, but also to affect and influence observers, neighbors, and the larger society. Watching and participating in these violent displays profoundly transforms those involved, reinforcing political identities, social hierarchies, and power structures. Such public spectacles of violence also force members of the community to choose sides—openly show support for the goals of the violence, or risk becoming victims, themselves. Tracing the ways in which public displays of violence unfold, Show Time reveals how the perpetrators exploit the fluidity of social ties for their own ends.
The New York Times bestselling author of Sweetness delivers the first all-encompassing account of the 1980s Los Angeles Lakers, one of professional sports’ most-revered—and dominant—dynasties. The Los Angeles Lakers of the 1980s personified the flamboyance and excess of the decade over which they reigned. Beginning with the arrival of Earvin “Magic” Johnson as the number-one overall pick of the 1979 draft, the Lakers played basketball with gusto and pizzazz, unleashing their famed “Showtime” run-and-gun style on a league unprepared for their speed and ferocity—and became the most captivating show in sports and, arguably, in all-around American entertainment. The Lakers’ roster overflowed with exciting all-star-caliber players, including center Kareem Abdul-Jabbar, and they were led by the incomparable Pat Riley, known for his slicked-back hair, his Armani suits, and his arrogant strut. Hollywood’s biggest celebrities lined the court and gorgeous women flocked to the arena. Best of all, the team was a winner. Between 1980 and 1991, the Lakers played in an unmatched nine NBA championship series, capturing five of them. Bestselling sportswriter Jeff Pearlman draws from almost three hundred interviews to take the first full measure of the Lakers’ epic Showtime era. A dazzling account of one of America’s greatest sports sagas, Showtime is packed with indelible characters, vicious rivalries, and jaw-dropping, behind-the-scenes stories of the players’ decadent Hollywood lifestyles. From the Showtime era’s remarkable rise to its tragic end—marked by Magic Johnson’s 1991 announcement that he had contracted HIV—Showtime is a gripping narrative of sports, celebrity, and 1980s-style excess.
"Show Them a Good Time is a master class in the short story-bold, irreverent and agonizingly funny." Sally Rooney, Author of Normal People and Conversations with Friends Show Them a Good Time tells the stories of women slotted away into restrictive roles: the celebrity's girlfriend, the widower's second wife, the lecherous professor's student, the corporate employee. But these women are too intelligent, too ferociously mordant and painfully funny to remain in their places. In "Not the End Yet,” Flattery probes the hilarious and wrenching ambivalence of Internet dating as the apocalypse nears; in "Sweet Talk,” the mysterious disappearance of local women sets the scene for a young girl to confront the dangerous uncertainties of her own sexuality; in "Abortion, A Love Story,” two college students in a dystopian campus reconfigure the perilous stories of their bodies in a fraught academic culture to offer a subversive play that takes over their own offstage lives. Together, the stories in Show Them a Good Time provide a riveting, hilarious introduction to one of today's most original young writers.
This graphic novel adaptation of the definitive history of the Apollo brings the legendary Harlem theater to life. Since its inception as an African-American theater in 1934, the Apollo, and the thousands of entertainers who performed there, have led the way in the presentation of swing, bebop, rhythm and blues, jazz, gospel, soul, funk and hip-hop—along with the latest in dance and comedy. The Apollo has nurtured and featured thousands of artists, many of whom have become legends. The beauty they have given the world—their art—transcends the hatred, ignorance, and intolerance that often made their lives difficult. Today, the Apollo enjoys an almost mythical status. With its breathtaking art, this graphic novel adaptation of Showtime at the Apollo brings to life the theater’s legendary significance in music history, African American history, and to the culture of New York City.
Most financial and investment decisions are based on considerations of possible future changes and require forecasts on the evolution of the financial world. Time series and processes are the natural tools for describing the dynamic behavior of financial data, leading to the required forecasts. This book presents a survey of the empirical properties of financial time series, their descriptions by means of mathematical processes, and some implications for important financial applications used in many areas like risk evaluation, option pricing or portfolio construction. The statistical tools used to extract information from raw data are introduced. Extensive multiscale empirical statistics provide a solid benchmark of stylized facts (heteroskedasticity, long memory, fat-tails, leverage...), in order to assess various mathematical structures that can capture the observed regularities. The author introduces a broad range of processes and evaluates them systematically against the benchmark, summarizing the successes and limitations of these models from an empirical point of view. The outcome is that only multiscale ARCH processes with long memory, discrete multiplicative structures and non-normal innovations are able to capture correctly the empirical properties. In particular, only a discrete time series framework allows to capture all the stylized facts in a process, whereas the stochastic calculus used in the continuum limit is too constraining. The present volume offers various applications and extensions for this class of processes including high-frequency volatility estimators, market risk evaluation, covariance estimation and multivariate extensions of the processes. The book discusses many practical implications and is addressed to practitioners and quants in the financial industry, as well as to academics, including graduate (Master or PhD level) students. The prerequisites are basic statistics and some elementary financial mathematics.
Emma has her most challenging story yet -- and a real TV reporter helping her put it on the air! Can they find her dance group's special drum before showtime? This is Emma Perez, and I'm ON THE AIR! Today at dance class, Sophia, Shakira, and I found out the best news ever: Our dance group is going to be part of the Thanksgiving Day parade! But now our special drum is missing and we can't do our dance without it! Where could it be? Emma and her friends want to put their best foot forward at showtime, but first they'll have to solve their biggest mystery yet! It's time for a new edition of EMMA IS ON THE AIR!
Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.
