Quantitative Risk Management: Concepts, Techniques, and Tools

By Alexander J. McNeil, R. Frey, Paul Embrechts. 2005

1,064 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/b3877f996625ef0467a0a2843970b119bfecc5b3

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Citations in the corpus

Multivariate Pareto portfolios: TCE-based capital allocation and divided differences (2007, background): “The economic justification of the Euler allocation principle was well discussed in McNeil et al. (2005) Section 6.3.3, addressing issues regarding the signals for performance measurement of Tasche (1999), and the ‘fairness considerations’ of Denault (2001).”
Forecasting risk with Markov-switching GARCH models:A large-scale performance study (2018, background): “Among the various building–blocks of any risk management system, the specification of the conditional volatility process is key, especially for short–term horizons (McNeil et al., 2015).”
Stress-Testing Macro Stress Testing: Does it Live Up to Expectations? (2012, unknown): “As pointed out by Summer (2007), the model structure is rooted in the quantitative risk management framework that underpins the risk management models used by banks for business and regulatory purposes (McNeil et al (2005)).”
Extremes on the discounted aggregate claims in a time dependent risk model (2010, background): “A comprehensive reference on this topic is McNeil et al. (2005).”
Inhomogeneous Dependence Modeling with Time-Varying Copulae (2009, unknown): “Cherubini, Luciano, and Vecchiato (2004) and McNeil, Frey, and Embrechts (2005) provide an overview of copulae for practical problems in finance and insurance.”
Modeling frailty-correlated defaults using many macroeconomic covariates (2011, background): “In a firm value model, firm i defaults at time t when its asset value Vit drops below some threshold ci, see Merton (1974) and Black and Cox (1976).”
MULTIVARIATE RISK MEASURES: A CONSTRUCTIVE APPROACH BASED ON SELECTIONS (2013, unknown): “ Hamel et al. (2013). 1 Introduction Most studies of risk measures and utilities deal with the univariate case, where the gains or liabilities are expressed by a random variable. We refer to [11] and [23] for a thorough treatment of univariate risk measures. The main purpose of univariate risk measu”
Portfolio optimization in the presence of dependent financial returns with long memory: A copula based approach. (2013, background): “Indeed, VaR is not sub-additive, i.e., the risk associated with a given portfolio can be larger than the sum of the stand alone risks of its components when measured by the VaR (for more details, see Artzner et al. (1999), McNeil et al. (2005), and Gilboa (2009)).”
Value-at-Risk Bounds with Variance Constraints (2015, unknown): “Using Table 8.6 on page 365 of McNeil et al. (2005), we fix the default probability p = 0.049 and ̺D = 0.0157.”