|Title:||Tail-risk protection trading strategies|
|Authors :||Packham, Natalie|
|et. al :||No|
|Publisher / Ed. Institution :||Social Science Research Network|
|License (according to publishing contract) :||Licence according to publishing contract|
|Subject (DDC) :||332: Financial economics|
|Abstract:||We develop dynamic portfolio protection trading strategies based on econometric methods. As a criterion for riskiness we consider the evolution of the value-at-risk spread from a GARCH model with normal innovations relative to a GARCH model with generalised innovations. These generalised innovations may for example follow a Student t, a Generalised hyperbolic, an alpha-stable or a Generalised Pareto (GPD) distribution. Our results indicate that the GPD distribution provides the strongest signals for avoiding tail risks. This is not surprising as the GPD distribution arises as a limit of tail behaviour in extreme value theory and therefore is especially suited to deal with tail risks. Out-of-sample backtests on 11 years of DAX futures data, indicate that the dynamic tail-risk protection strategy effectively reduces the tail risk while outperforming traditional portfolio protection strategies. The results are further validated by calculating the statistical significance of the results obtained using bootstrap methods.|
|Departement:||School of Management and Law|
|Organisational Unit:||Institute of Wealth & Asset Management (IWA)|
|Publication type:||Working Paper – Expertise – Study|
|Appears in Collections:||Publikationen School of Management and Law|
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