Conditional Scenario Generation with a GVAR Model
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Date
2016-12-15
Authors
Wang, Xinghao
Journal Title
Journal ISSN
Volume Title
Publisher
University of Waterloo
Abstract
The stress-testing method formed an integral part of the practice of risk management. However,
the underlying models for scenarios generation have not been much studied so far. In
past practice, the users typically did not model risk factors for portfolios of moderate size
endogenously due to the presence of "curse of dimensionality" problem. Moreover, it is almost
impossible to impose the expert views for a future outcome of macroeconomy on the
scenario generator without making ad-hoc adjustments.
In this thesis we propose a GVAR-based framework which allows an efficient simulation of
risk factors for a complex multi-currency portfolio of various classes of assets conditioning on
economic scenarios. Given reasonable sets of economic forecasts, the GVAR model anticipates
the trend and codependency of the future path of portfolio risk factors and supports the
production of meaningful results from risk analytics.
Description
Keywords
Stress-testing, Conditional Scenario Generation, High-dimensional Data, GVAR