In this article, we attempt to quantify the potential impact of hedge funds on systemic risk by developing a number of new risk measures for hedge funds and applying them to individual and aggregate hedge-fund returns data. These measures include: illiquidity risk exposure, nonlinear factor models for hedge-fund and banking-sector indexes, logistic regression analysis of hedge-fund liquidation probabilities, and aggregate measures of volatility and distress based on regime-switching models. Our preliminary findings suggest that the hedge-fund industry may be heading into a challenging period of lower expected returns, and that systemic risk is currently on the rise. This is a redacted version of our paper "Systemic Risk and Hedge Funds".

We document the empirical properties of a sample of 1,765 funds in the TASS Hedge Fund database from 1994 to 2004 that are no longer active. The TASS sample shows that attrition rates differ significantly across investment styles, from a low of 5.2% per year on average for convertible arbitrage funds to a high of 14.4% per year on average for managed futures funds. We relate a number of factors to these attrition rates, including past performance, volatility, and investment style, and also document differences in illiquidity risk between active and liquidated funds. We conclude with a proposal for the U.S. Securities and Exchange Commission to play a new role in promoting greater transparency and stability in the hedge-fund industry.

Despite the collapse of Long-Term Capital Management less than five years ago, the memories of those troubled times are apparently gone, replaced by concerns about the economic climate and the dearth of attractive investment opportunities. Not surprisingly, interest in alternative investments has skyrocketed. Along with opportunities for the alternative investments industry, institutional investors bring new challenges, underscoring the gap between them and hedge fund managers. The challenges revolve around risk  management — after all, outsized returns are usually accompanied by outsized risks — and fall into three categories: determining investors’ risk preferences, developing risk models for alternative investments, and blending quantitative and qualitative approaches to manager selection and capital allocation. Any complete risk management protocol should address each of these.

A longstanding controversy in economics and finance is whether financial markets are governed by rational forces or by emotional responses. We study the importance of emotion in the decision making process of professional securities traders by measuring their physiological characteristics, e.g., skin conductance, blood volume pulse, etc., during live trading sessions while simultaneously capturing real-time prices from which market events can be detected. In a sample of 10 traders, we find significant correlation between electrodermal responses and transient market events, and between changes in cardiovascular variables and market volatility. We also observe differences in these correlations among the 10 traders which may be systematically related to the traders' levels of experience.

Although risk management has been a well-plowed field in financial modeling for over two decades, traditional risk management tools such as mean-variance analysis, beta, and Value-at-Risk do not capture many of the risk exposures of hedge-fund investments. In this article, I review several aspects of risk management that are unique to hedge funds - survivorship bias, dynamic risk analytics, liquidity, and nonlinearities - and provide examples that illustrate their potential importance to hedge-fund managers and investors. I propose a research agenda for developing a new set of risk analytics specifically designed for hedge-fund investments, with the ultimate goal of creating risk transparency while, at the same time, protecting the proprietary nature of hedge-fund investment strategies.

Typical value-at-risk (VAR) calculations involve the probabilities of extreme dollar losses, based on the statistical distributions of market prices. Such quantities do not account for the fact that the same dollar loss can have two very different economic valuations, depending on business conditions. We propose a nonparametric VAR measure that incorporates economic valuation according to the state-price density associated with the underlying price processes. The state-price density yields VAR values that are adjusted for risk aversion, time preferences, and other variations in economic valuation. In the context of a representative agent equilibrium model, we construct an estimator of the risk-aversion coefficient that is implied by the joint observations on option prices and underlying asset value.

Current risk-management practices are based on probabilities of extreme dollar losses (e.g., measures like Value at Risk), but these measures capture only part of the story. Any complete risk-management system must address two other important factors: prices and preferences. Together with probabilities, these comprise the three P's of Total Risk Management. This article describes how the three Ps interact to determine sensible risk profiles for corporations and for individuals, guidelines for how much risk to bear and how much to hedge. By synthesizing existing research in economics, psychology, and decision sciences, and through an ambitious research agenda to extend this synthesis into other disciplines, a complete and systematic approach to rational decision-making in an uncertain world is within reach.

The regulation of financial markets has for years been the domain of lawyers, legislators, and lobbyists. In this unique volume, experts in industrial organization, finance, and law, as well as members of regulatory agencies and the securities industry, examine the securities industry from an economic viewpoint.

Ten original essays address topics including electronic trading and the "virtual"stock exchange; trading costs and liquidity on the London and Tokyo Stock Exchanges and in the German and Japanese government bond markets; international coordination among regulatory agencies; and the impact of changing margin requirements on stock prices, volatility, and liquidity.

This clear presentation of groundbreaking research will appeal to economists, lawyers, and legislators who seek a refreshingly new perspective on policy issues in the securities industry.

A securities transactions tax is likely to have far-reaching and profound implications for the financial systems and institutions. We evaluate the effect that a transactions tax will have on the financial system's role in transferring resources over time and in allocating risk efficiently across individuals and sectors. In particular, we examine the impact of a transactions tax on individual investors due to the reduction in the rate of return on savings, the reduction in trading, and the likely reduction in the value of stocks. We also consider the possible effects of a transactions tax on market liquidity. By reducing the informational role of prices and reducing market liquidity, a transactions tax may result in higher market volatility. We provide a simple numerical example that illustrates the enormous impact such a tax will have on the derivatives markets, where participants rely heavily on dynamic trading strategies to control risk. This sector of the financial system, along with its jobs, revenues, and risk-management capabilities are likely to move offshore in response to the tax.

A simple large-sample Chow test for stability of coefficients in a linear simultaneous equation is proposed. It is shown that the appropriate test statistic may be formed conveniently from particular sums of squared residuals.