Computational aspects of portfolio risk estimation in volatile markets: a survey

Abstract

Portfolio risk estimation requires appropriate modeling of fat-tails and asymmetries in dependence in combination with a true downside risk measure. In this survey, we discuss computational aspects of a Monte Carlo based framework for risk estimation and risk capital allocation. We review different probabilistic approaches focusing on practical aspects of statistical estimation and scenario generation. We discuss value-at-risk and conditional value-at-risk and comment on the implications of using a fat-tailed Monte Carlo framework for the reliability of risk estimates including model risk and Monte Carlo variability.

Pairs trading in cryptocurrency market: A long-short story

“…Contemporary valuation models often characterize portfolio optimizations as a function of price correlations in asset markets (Fabozzi et al, 2013). Hence, in financial literature, a considerable amount of efforts has been giving focus to understand the trading correlations and outline strategies to manage risks (Meissner, 2016).…”