Knightmare on Wall Street, The Rise and Fall of Knight Capital and the Biggest Risk for Financial Markets is a thrilling minute-by-minute account of the terrifying hours following Knight Capital’s August 1, 2012 trading debacle, with news-breaking research regarding the firm’s 17 years of tumultuous existence as an independent company. Knightmare on Wall Street is the definitive behind-the-scenes story of Knight Capital.
The firm, founded by Kenneth Pasternak and Walter Raquet in 1995, had seen its fortunes change as U.S. regulators made a series of changes in the structure of financial markets and computers were progressively expanding their share of trading. The Flash Crash, the infamous 1,000 point drop of the DJIA on May 6, 2010 (the largest one-day point decline in history), illustrated how market structure problems could almost instantaneously cascade from one market participant to the rest.
Thomas Joyce, CEO of Knight Capital since 2002 and an unapologetic advocate of electronic trading, had been scornful of those companies that struggled to keep up with ever-changing stock markets. So it was certainly shocking that at 9:30 A.M. on August 1, 2012, right after the markets opened for the day, Knight Capital began issuing an unprecedented number of erroneous orders into the market, due to an error in installing new software. No rogue trader or regulatory change; operational risk was passing the bill to Knight Capital and becoming the biggest risk in the financial markets.
Knight Capital announced later a staggering loss of $440 million. What followed after this shocking announcement were several rounds of desperate conversations with a number of vulture players who had smelled opportunity and were readying themselves to pick up bargain-priced pieces. On August 6, 2012, Joyce confirmed that Knight Capital had struck a deal with Jefferies, TD Ameritrade, Blackstone, GETCO, Stephens, and Stifel Financial, staving off collapse days after the trading mishap.
While Knight Capital was back in the game, its limping recovery quickly prompted hungry competitors to bid for the entire company. On December 19, 2012, the board decided to accept an acquisition proposal from GETCO rather than Virtu Financial. For GETCO, acquiring Knight Capital represented a gigantic fast forward step. For Knight Capital, it was the end of its wild ride as an independent entity.
Knightmare on Wall Street provides a fascinating account of what it took to elevate the firm to the cusp of the retail investing revolution of the late 1990s, to struggle through booms and busts, and to bring the firm down, to end up ultimately being ignominiously bought up by a competitor.
High-frequency traders have been called many things—from masters of the universe and market pioneers to exploiters, computer geeks, and even predators. Everyone in the business of investing has an opinion of speed traders, but how many really understand how they operate? The shadow people of the investing world, today’s high-frequency traders have decidedly kept a low profile—until now. In this new title, The Speed Traders, Edgar Perez opens the door to the secretive world of high-frequency trading (HFT). Inside, prominent figures of HFT drop their guard and speak with unprecedented candidness about their trade.
Edgar begins with an overview of computerized trading, which formally began on February 8, 1971, when NASDAQ launched the world’s first electronic market with 2,500 over-the-counter stocks and which has evolved into the present-day practice of making multiple trades in a matter of microseconds. He then picks the brains of today’s top players. Manoj Narang (Tradeworx), John Netto (M3 Capital), and Aaron Lebovitz (Infinium Capital Management) are just a few of the luminaries who decided to break their silence and speak openly to Edgar. Virtually all of the expertise available from the world of speed trading is packed into these pages.
The Speed Traders, published by McGraw-Hill Inc., is the most comprehensive, revealing work available on the most important development in trading in generations. High-frequency trading will no doubt play an ever larger role as computer technology advances and the global exchanges embrace fast electronic access. The Speed Traders explains everything there is to know about how today’s high-frequency traders make millions—one cent at a time.
埃德加•佩雷斯（Edgar Perez）先生曾任麦肯锡公司咨询师，UltraHF Capital（一个执行高频交易策略的对冲基金）首席营运官，Golden Networking（第一个商业主管、企业家和投资者的网络社区）的创建者。佩雷斯先生于2002年在哥伦比亚商学院获得MBA学位，并被选为 Beta Gamma Sigma荣誉社的成员。佩雷斯先生是公认的高频交易领域的杰出的专家，曾在包括哈佛商学院风险投资与私募研讨大会等多个全球性会议上发表演讲。佩雷斯先 生目前定居于纽约。
Artificial intelligence has been referred as the general ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term has indeed been frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, generalize, discover meaning, or learn from past experiences. Since the development of the digital computer in the 1940s, it has been demonstrated that computers can be programmed to carry out very complex tasks with great proficiency. Still, despite continuing advances in computer processing speed and memory capacity, there are as yet no programs that can match human flexibility over wider domains or in tasks requiring much everyday knowledge.
In 1945, British logician and computer pioneer Alan Turing predicted that computers would one day play very good chess. Just over 50 years later, in 1997, Deep Blue, a chess computer built by IBM beat the reigning world champion, Garry Kasparov, in a six-game match. Since then, a number of programs have attained the performance levels of human experts and professionals in performing certain specific tasks, so that artificial intelligence is now found in applications as diverse as medical diagnosis, computer search engines, and voice or handwriting recognition.
Indeed, deep learning has enabled many practical applications of machine learning and by extension the overall field of artificial intelligence. Deep learning breaks down tasks in ways that makes all kinds of machine aids seem possible, even likely. Driverless cars, better image recognition, even better movie recommendations, are all here today. Artificial intelligence is the present and the future.
The AI Breakthrough will provide a comprehensive review of the artificial intelligence breakthroughs of today and tomorrow and how these advancements will impact businesses and the human race in general for years to come.