Dr. Gibson's Table of Contents
     in chronological order

• Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities
  by Michael S. Gibson
  April 2006
   
• Measuring Counterparty Credit Exposure to a Margined Counterparty
  by Michael S. Gibson
  November 2005
   
• Incorporating Event Risk into Value-at-Risk
  by Michael S. Gibson
  February 2001
   
• Improving Grid-Based Methods for Estimating Value at Risk of Fixed-Income Portfolios
  by Michael S. Gibson & Matt Pritsker
  August 10, 2000
   
• Is corporate governance ineffective in emerging markets?
  by Michael S. Gibson
  April 17, 2000
   
• The Implications of Risk Management Information Systems for the Organization of Financial Firms
  by Michael S. Gibson
  December, 1998
   
• 'Big Bang' Deregulation and Japanese Corporate Governance: A Survey of the Issues
  by Michael S. Gibson
  September 1998
   
• Information Systems for Risk Management
  by Michael S. Gibson
  July 1997
   

Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities
by Michael S. Gibson
Federal Reserve Board
April 2006

Abstract
This paper proposes a method for constructing a volatility risk premium, or investor risk aversion, index. The method is intuitive and simple to implement, relying on the sample moments of the recently popularized model-free realized and option-implied volatility measures. A small-scale Monte Carlo experiment confirms that the procedure works well in practice. Implementing the procedure with actual S&P500 option-implied volatilities and high-frequency five-minute-based realized volatilities indicate significant temporal dependencies in the estimated stochastic volatility risk premium, which we in turn relate to a set of underlying macro-finance state variables. We also find that the extracted volatility risk premium helps predict future stock market returns.

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Measuring Counterparty Credit Exposure to a Margined Counterparty
by Michael S. Gibson
Federal Reserve Board
November 2005

Abstract
Firms active in OTC derivative markets increasingly use margin agreements to reduce counterparty credit risk. Making several simplifying assumptions, I use both a quasi-analytic approach and a simulation approach to quantify how margining reduces counterparty credit exposure. Margining reduces counterparty credit exposure by over 80 percent, using baseline parameter assumptions. I show how expected positive exposure (EPE) depends on key terms of the margin agreement and the current mark-to-market value of the portfolio of contracts with the counterparty. I also discuss a possible shortcut that could be used by firms that can model EPE without margin but cannot achieve the higher level of sophistication needed to model EPE with margin.

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Incorporating Event Risk into Value-at-Risk
by Michael S. Gibson
Federal Reserve Board
February 2001

Abstract
Event risk is the risk that a portfolio's value can be affected by large jumps in market prices. Event risk is synonymous with "fat tails" or "jump risk". Event risk is one component of "specific risk", defined by bank supervisors as the component of market risk not driven by market-wide shocks. Standard Value-at-Risk (VaR) models used by banks to measure market risk do not do a good job of capturing event risk. In this paper, I discuss the issues involved in incorporating event risk into VaR. To illustrate these issues, I develop a VaR model that incorporates event risk, which I call the Jump-VaR model. The Jump-VaR model uses any standard VaR model to handle "ordinary" price fluctuations and grafts on a simple model of price jumps. The effect is to "fatten" the tails of the distribution of portfolio returns that is used to estimate VaR, thus increasing VaR. I note that regulatory capital could rise or fall when jumps are added, since the increase in VaR would be offset by a decline in the regulatory capital multiplier on specific risk from 4 to 3. In an empirical application, I use the Jump-VaR model to compute VaR for two equity portfolios. I note that, in practice, special attention must be paid to the issues of correlated jumps and double-counting of jumps. As expected, the estimates of VaR increase when jumps are added. In some cases, the increases are substantial. As expected, VaR increases by more for the portfolio with more specific risk.

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Improving Grid-Based Methods for Estimating Value at Risk of Fixed-Income Portfolios
by Michael S. Gibson & Matt Pritsker
Federal Reserve Board & Board of Governers of the Federal Reserve
August 10, 2000

Abstract
Jamshidian and Zhu (1997) propose a discrete grid method for simplifying the computation of Value at Risk (VaR) for fixed-income portfolios. Their method relies on two simplifications. First, the value of fixed income instruments is modeled as depending on a small number of risk factors chosen using principal components analysis. Second, they use a discrete approximation to the distribution of the portfolio's value.

We show that their method has two serious shortcomings which imply it cannot accurately estimate VaR for some fixed-income portfolios. First, risk factors chosen using principal components analysis will explain the variation in the yield curve, but they may not explain the variation in the portfolio's value. This will be especially problematic for portfolios that are hedged. Second, their discrete distribution of portfolio value can be a poor approximation to the true continuous distribution.

We propose two refinements to their method to correct these two shortcomings. First, we propose choosing risk factors according to their ability to explain the portfolio's value. To do this, instead of generating risk factors with principal components analysis, we generate them with a statistical technique called partial least squares. Second, we compute VaR with a "Grid Monte Carlo" method that uses continuous risk factor distributions while maintaining the computational simplicity of a grid method for pricing. We illustrate our points with several example portfolios where the Jamshidian-Zhu method fails to accurately estimate VaR, while our refinements succeed.

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Is corporate governance ineffective in emerging markets?
by Michael S. Gibson
Federal Reserve Board
April 17, 2000

Abstract
I test whether corporate governance is ineffective in emerging markets by estimating the link between CEO turnover and firm performance for over 1,200 firms in eight emerging markets. I find two main results. First, CEOs of emerging market firms are more likely to lose their jobs when their firm's performance is poor, suggesting that corporate governance is not ineffective in emerging markets. Second, for the subset of firms with a large domestic shareholder, there is no link between CEO turnover and firm performance. For this subset of emerging market firms, corporate governance appears to be ineffective.

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The Implications of Risk Management Information Systems for the Organization of Financial Firms
by Michael S. Gibson
Federal Reserve Board
December, 1998

Abstract
Financial dealer firms have invested heavily in recent years to develop information systems for risk measurement. I take it as given that technological progress is likely to continue at a rapid pace, making it less expensive for financial firms to assemble risk information. I look beyond questions of risk measurement methodology to investigate the implications of risk management information systems. By examining several theoretical models of the firm in the presence of asymmetric information, I explore how a financial firm's capital budgeting, incentive compensation, capital structure, and risk management activities are likely to change as it becomes less costly to assemble risk information. I also explore the likely effects of the falling cost of assembling risk information on a financial firm's organizational structure. Two common themes emerge: centralization within the firm and increased disclosure of risk information outside the firm are both likely to increase.

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'Big Bang' Deregulation and Japanese Corporate Governance: A Survey of the Issues
by Michael S. Gibson
Federal Reserve Board
September 1998

Abstract
The "Big Bang" deregulation of Japanese financial markets focuses on financial modernization. I argue that financial modernization is of secondary importance for improving the performance of the Japanese economy. A key long-term issue facing Japan is to maintain its high level of per capita income in the face of an aging population and slower productivity growth. To achieve this, it is important to increase the return earned on Japan's large stock of wealth. I argue the low return on wealth reflects characteristics of the Japanese corporate governance system. The proper focus of the "Big Bang" should be on measures to strengthen corporate governance.

I identify three characteristics of the Japanese corporate governance system that lead Japanese managers to produce low returns for shareholders. First, insider stakeholders dominate corporate governance. Second, institutional investors are weak. Third, there is no market for corporate control. For each characteristic, I describe potential changes which would strengthen Japanese corporate governance. For each potential corporate governance change, I review empirical evidence on its effectiveness, its current status in Japan, and how it is addressed, if at all, in the "Big Bang." I conclude that the progress of the "Big Bang" reforms to corporate governance has been limited.

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Information Systems for Risk Management
by Michael S. Gibson
Federal Reserve Board
July 1997

Abstract
Risk management information systems are designed to overcome the problem of aggregating data across diverse trading units. The design of an information system depends on the risk measurement methodology that a firm chooses. Inherent in the design of both a risk management information system and a risk measurement methodology is a tradeoff between the accuracy of the resulting measures of risk and the burden of computing them. Technical progress will make this tradeoff more favorable over time, leading firms to implement more accurate methodologies, such as full revaluation of nonlinear positions. The current and likely future improvements in risk management information systems make feasible new ways of collecting aggregate data on firms' risk-taking activities.

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