1、Dynamic Value-at-Risk   author:Andrey Rogachev

Contest
1. INTRODUCTION...................................................................................................................2
2. RISK MEASUREMENT IN PORTFOLIO MANAGEMENT ...........................................................3
2.1. Definition of the problem ...........................................................................................3
2.2. Objectives and research questions..............................................................................4
3. THE ECONOMIC IMPORTANCE OF VALUE-AT-RISK..............................................................6
4. VALUE-AT-RISK CALCULATIONS IN A PRAXIS ....................................................................7
4.1. The Estimations by one Swiss Private Bank ..............................................................7
4.2. Wegelin Value-at-Risk Scenarios ..............................................................................9
5. EMPIRICAL RESEARCH ......................................................................................................10
5.1. Value-at-Risk and Limitation...................................................................................10
5.2. The First Empirical Results......................................................................................12
5.3. Conclusion................................................................................................................14
6. DYNAMIC STRATEGY OF VALUE-AT-RISK ESTIMATION....................................................16
7. OUTLOOK.........................................................................................................................17
BIBLIOGRAPHY.....................................................................................................................18

2、EÆcient Monte Carlo Methods for Value-at-Risk

Abstract
The calculation of value-at-risk for large portfolios presents a tradeo between speed and
accuracy, with the fastest methods relying on rough approximations and the most realistic
approach|Monte Carlo simulation|often too slow to be practical. This article describes meth-
ods that use the best features of both approaches. The methods build on the delta-gamma
approximation, but they use the approximation not as a substitute for simulation but rather as
an aid to it. We use the delta-gamma approximation to guide the sampling of market scenarios
through a combination of importance sampling and strati ed sampling. This can greatly reduce
the number of scenarios required in a simulation to achieve a desired precision. We also describe
an extension of the method in which \vega" terms are included in the approximation to capture
changes in the level of volatility.

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Contest
1. INTRODUCTION...........................................................................................2
2. RISK MEASUREMENT IN PORTFOLIO MANAGEMENT ...............................3
2.1. Definition of the problem ..........................................................................3
2.2. Objectives and research questions............................................................4
3. THE ECONOMIC IMPORTANCE OF VALUE-AT-RISK..............................6
4. VALUE-AT-RISK CALCULATIONS IN A PRAXIS ..........................................7
4.1. The Estimations by one Swiss Private Bank ..........................................7
4.2. Wegelin Value-at-Risk Scenarios .............................................................9
5. EMPIRICAL RESEARCH .............................................................................10
5.1. Value-at-Risk and Limitation...................................................................................10
5.2. The First Empirical Results....................................................................
5.3. Conclusion......................................................................................................4
6. DYNAMIC STRATEGY OF VALUE-AT-RISK ESTIMATION...................................16
7. OUTLOOK.........................................................................................................................17
BIBLIOGRAPHY.....................................................................................................................18

2、EÆcient Monte Carlo Methods for Value-at-Risk

Abstract
The calculation of value-at-risk for large portfolios presents a tradeo between speed and
accuracy, with the fastest methods relying on rough approximations and the most realistic
approach|Monte Carlo simulation|often too slow to be practical. This article describes meth-
ods that use the best features of both approaches. The methods build on the delta-gamma
approximation, but they use the approximation not as a substitute for simulation but rather as
an aid to it. We use the delta-gamma approximation to guide the sampling of market scenarios
through a combination of importance sampling and strati ed sampling. This can greatly reduce
the number of scenarios required in a simulation to achieve a desired precision. We also describe
an extension of the method in which \vega" terms are included in the approximation to capture
changes in the level of volatility.

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[此贴子已经被作者于2009-6-12 0:51:53编辑过]