[下载]经济危机后的热点研究--金融风险VaR度量研究

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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.

[UseMoney=2]

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.

[UseMoney=2]

[/UseMoney]

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2009-6-12 00:43:00 上传

[下载]经济危机后的热点研究--金融风险VaR度量研究
需要: 2 个论坛币  [购买]

335829.pdf (283.86 KB, 需要: 2 个论坛币)

2009-6-12 00:44:00 上传

[下载]经济危机后的热点研究--金融风险VaR度量研究
需要: 2 个论坛币  [购买]

[/UseMoney]

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关键词：经济危机 金融风险 VaR Calculations introduction 金融 VaR 热点 经济危机 度量

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.

too expensive!

太贵了，楼主

too expensive

谢谢！O(∩_∩)O~