Risk factor aggregation and stress testing

Packham, Natalie

arXiv.org Machine Learning 

Stress testing refers to a set of methods and tools that assess the impact of an adverse scenario on a financial portfolio. An adverse scenario could, for example, be described as a downturn of macroeconomic and financial risk factors. Typically, a factor model links the risk factors with asset returns, which in turn allows to calculate the impact of the stress scenario on a portfolio. Using techniques from statistics and machine learning, we extend the universe of risk factors by aggregating existing risk factors into higher-level risk factors, such as a global risk factor, broad geographic regions or cyclical and non-cyclical industries. The methods developed also allow to evaluate the strength or weakness over time of aggregated risk factors, such as the intensity of global risk, which changes substantially over time.

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