Nonparametric Risk Management and Implied Risk Aversion2000
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.
The Three P’s of Total Risk Management1999
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.
Securities Transaction Taxes: What Would Be Their Effects on Financial Markets and Institutions?1995
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 Large-Sample Chow Test for the Single Linear Simultaneous Equation1985
The practice of risk management starts with an understanding of the statistical behavior of financial asset prices over time. Models such as the random walk hypothesis, the martingale model, and geometric Brownian motion are fundamental to any analysis of financial risks and rewards, particularly for longer investment horizons. Recent empirical evidence has cast doubt on some of these models, and this article provides an overview of such evidence. I begin with a review of the random walk hypothesis and related models, including a discussion of why such models perform so poorly, and then turn to some current research on alternative models such as long-term memory models and stable distributions.