In the aftermath of the recent financial crisis, the federal government has pursued significant regulatory reforms, including proposals to measure and monitor systemic risk. However, there is much debate about how this might be accomplished quantitatively and objectively—or whether this is even possible. A key issue is determining the appropriate trade-offs between risk and reward from a policy and social welfare perspective given the potential negative impact of crises.

One of the first books to address the challenges of measuring statistical risk from a system-wide perspective, Quantifying Systemic Risk looks at the means of measuring systemic risk and explores alternative approaches. Among the topics discussed are the challenges of tying regulations to specific quantitative measures, the effects of learning and adaptation on the evolution of the market, and the distinction between the shocks that start a crisis and the mechanisms that enable it to grow.

With the financial crisis continuing after five years, people are questioning why economics failed either to send an adequate early warning ahead of the crisis or to resolve it quickly. The gap between important real-world problems and the workhorse mathematical model-based economics being taught to students has become a chasm. Students continue to be taught as if not much has changed since the crisis, as there is no consensus about how to change the curriculum. Meanwhile, employer discontent with the knowledge and skills of their graduate economist recruits has been growing. This book examines what economists need to bring to their jobs, and the way in which education in universities could be improved to fit graduates better for the real world. It is based on an international conference in February 2012, sponsored by the UK Government Economic Service and the Bank of England, which brought employers and academics together. Three themes emerged: the narrow range of skills and knowledge demonstrated by graduates; the need for reform of the content of the courses they are taught; and the barriers to curriculum reform. While some issues remain unresolved, there was strong agreement on such key issues as the strengthening of economic history, the teaching of inductive as well as deductive reasoning, critical evaluation and communication skills, and a better alignment of lecturers' incentives with the needs of their students.

Some economic events are so major and unsettling that they “change everything.” Such is the case with the financial crisis that started in the summer of 2007 and is still a drag on the world economy. Yet enough time has now elapsed for economists to consider questions that run deeper than the usual focus on the immediate causes and consequences of the crisis. How have these stunning events changed our thinking about the role of the financial system in the economy, about the costs and benefits of financial innovation, about the efficiency of financial markets, and about the role the government should play in regulating finance? In Rethinking the Financial Crisis, some of the nation’s most renowned economists share their assessments of particular aspects of the crisis and reconsider the way we think about the financial system and its role in the economy.

"A movement is over when the news is out," so goes the Wall Street maxim. For thousands of years, technical analysis—marred with common misconceptions likening it to gambling or magic and dismissed by many as "voodoo finance"—has sought methods for spotting trends in what the market's done and what it's going to do. After all, if you don't learn from history, how can you profit from it?

In The Evolution of Technical Analysis, the director of MIT's Laboratory for Financial Engineering, Andrew Lo, and coauthor Jasmina Hasanhodzic present an engaging account of the origins and development of this mysterious "black art," tracing its evolution from ancient Babylon to the rise of Wall Street as the world's financial center. Along the way, the practices of Eastern technical analysts like Munehisa Homma ("the god of the markets") are compared and contrasted with those of their Western counterparts, such as Humphrey Neill, William Gann, and Charles Dow ("the father of technical analysis").

With deep roots in antiquity, technical analysis is part art and part science, seeking to divine trends, reversals, cycles, and other predictable patterns in historical market prices. While the techniques for capturing such regularities have evolved considerably over the centuries, the all-too-human predilection to extrapolate into the future using the past has been a constant driving force throughout history.

The authors chronicle the fascinating and unexpected path of charting that likely began with simple superstitions and coincidences, and has developed into widespread practices in many markets and instruments, involving sophisticated computational algorithms and visualization techniques. The Evolution of Technical Analysis is the story of how some early technicians failed miserably, how others succeeded beyond their wildest dreams, and what it means for traders today.

The Heretics of Finance provides extraordinary insight into both the art of technical analysis and the character of the successful trader. Distinguished MIT professor Andrew W. Lo and researcher Jasmina Hasanhodzic interviewed thirteen highly successful, award-winning market professionals who credit their substantial achievements to technical analysis. The result is the story of technical analysis in the words of the people who know it best; the lively and candid interviews with these gurus of technical analysis.

The first half of the book focuses on the technicians' careers:

• How and why they learned technical analysis
• What market conditions increase their chances of making mistakes
• What their average workday is like
• To what extent trading controls their lives
• Whether they work on their own or with a team
• How their style of technical analysis is unique

The second half concentrates on technical analysis and addresses questions such as these:

• Did the lack of validation by academics ever cause you to doubt technical analysis?
• Can technical analysis be applied to other disciplines?
• How do you prove the validity of the method?
• How has computer software influenced the craft?
• What is the role of luck in technical analysis?
• Are there laws that underlie market action?
• What traits characterize a highly successful trader?
• How you test patterns before you start using them with real money?

Interviewees include:
Ralph J. Acampora, Laszlo Birinyi, Walter Deemer, Paul Desmond, Gail Dudack, Robert J. Farrell, Ian McAvity, John Murphy, Robert Prechter, Linda Raschke, Alan R. Shaw, Anthony Tabell, Stan Weinstein.

The hedge fund industry has grown dramatically over the last two decades, with more than eight thousand funds now controlling close to two trillion dollars. Originally intended for the wealthy, these private investments have now attracted a much broader following that includes pension funds and retail investors. Because hedge funds are largely unregulated and shrouded in secrecy, they have developed a mystique and allure that can beguile even the most experienced investor. In Hedge Funds, Andrew Lo--one of the world's most respected financial economists--addresses the pressing need for a systematic framework for managing hedge fund investments.

This major collection presents a careful selection of the most important published articles in the field of financial econometrics. Starting with a review of the philosophical background, the collection covers such topics as the random walk hypothesis, long-memory processes, asset pricing, arbitrage pricing theory, variance bounds tests, term structure models, market microstructure, Bayesian methods and other statistical tools.

Read Andrew Lo's Introduction to the International Library of Financial Econometrics

For over half a century, financial experts have regarded the movements of markets as a random walk--unpredictable meanderings akin to a drunkard's unsteady gait--and this hypothesis has become a cornerstone of modern financial economics and many investment strategies. Here Andrew W. Lo and A. Craig MacKinlay put the Random Walk Hypothesis to the test. In this volume, which elegantly integrates their most important articles, Lo and MacKinlay find that markets are not completely random after all, and that predictable components do exist in recent stock and bond returns. Their book provides a state-of-the-art account of the techniques for detecting predictabilities and evaluating their statistical and economic significance, and offers a tantalizing glimpse into the financial technologies of the future.

The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory.

The efficient markets hypothesis is one of the most controversial and hotly contested ideas in all the social sciences. It is disarmingly simply to state, has far-reaching consequences for academic pursuits and business practice, and yet is surprisingly resilient to empirical proof or refutation. Even after three decades of research and literally thousands of journal articles, economists have not yet reached a consensus about whether markets - particularly financial markets - are efficient or not.