Extreme Value Theory-Based Value At Risk

Compute the value at risk of a portfolio using extreme value theory to model the lower tail of the portfolio returns.

References

• Valerie Chavez-Demoulin, Armelle Guillou, Extreme quantile estimation for beta-mixing time series and applications, Insurance: Mathematics and Economics, Volume 83, 2018, Pages 59-74
• Mhamed-Ali El-Aroui, Jean Diebolt, On the use of the peaks over thresholds method for estimating out-of-sample quantiles, Computational Statistics & Data Analysis, Volume 39, Issue 4, 2002, Pages 453-475
• David E. Giles, Hui Feng & Ryan T. Godwin (2016) Bias-corrected maximum likelihood estimation of the parameters of the generalized Pareto distribution, Communications in Statistics - Theory and Methods, 45:8, 2465-2483
• de Haan, L., Mercadier, C. & Zhou, C. Adapting extreme value statistics to financial time series: dealing with bias and serial dependence. Finance Stoch 20, 321–354 (2016)