Estimating value-at-risk: a point process approach

By V. Chavez‐Demoulin, A. C. Davison, Alexander J. McNeil. 2005

178 citations recorded by the source corpus.

Subfields: Applied Mathematics, Finance, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/238d1c2ea052b188be69ec328b49b2c4bea5b517

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Citations in the corpus

Hawkes processes and their applications to finance: a review (2018, methodology): “Other journal publications about that time include Chavez-Demoulin et al. (2005), Hewlett (2006) and Large (2007).”
Are Banks Too Big to Fail? Measuring Systemic Importance of Financial Institutions (2010, background): “In line with the second type of solution, Chavez-Demoulin, Davison, and McNeil (2005) consider a point process approach to decluster the financial return data.”
Extreme Value Theory for Finance: A Survey (2012, methodology): “33 This task, on the contrary, is explicitly undertaken by a point process approach introduced by Chavez-Demoulin et al. (2005).”
Non-parametric kernel estimation for symmetric Hawkes processes. Application to high frequency financial data (2011, background): “Applications can be found in the field of order arrival rate modeling [16,7,29], noise microstructure dynamics [2], volatility clustering [11], extreme values and VaR estimation [8] and credit modeling [12].”
Multivariate Hawkes processes: an application to financial data (2011, methodology): “For applications of Hawkes process models to finance, see, for instance, [1], [2], [5], [8], and the numerous references therein.”
An estimation procedure for the Hawkes process (2015, methodology): “et al. (2011), or joint models for orders and prices on a market microstructure level in Muzy and Bacry (2014). Early publications applying the Hawkes model in the nancial context are Bowsher (2002), Chavez-Demoulin et al. (2005) and McNeil et al. (2005). The paper is organized as follows: Section 2”
Modelling Time Series Extremes (2012, methodology): “The use of self-exciting process models for clustering of extreme events in financial time series is described by Chavez-Demoulin et al. (2005) and Embrechts et al. (2011).”
Frontiers in VaR forecasting and backtesting (2016, methodology): “There are two SEMPP models proposed in the literature: the Hawkes-POT model introduced by Chavez-Demoulin et al. (2005) and the ACD-POT model proposed by Herrera and Shipp (2013) who consider the time between exceedances as a stochastic process modeled as the ACD model of Engle and Russell (1998).”
Rough fractional diffusions as scaling limits of nearly unstable heavy tailed Hawkes processes (2015, methodology): “In the last years, the probabilistic and statistical analysis of Hawkes processes has known several interesting developments, driven by the recent use of Hawkes processes in various applied fields such as neurosciences [13, 33, 34, 36], sociology [9, 28, 41], criminology [30, 31], genome analysis [3”
Risk Processes with Non-stationary Hawkes Claims Arrivals (2010, methodology): “We model this feature by means of the so called self-exciting or Hawkes processes (Hawkes (1971a), (1971b); Daley and Vere-Jones (2003)).”
Limit theorems for nearly unstable Hawkes processes (2013, methodology): “y of (ultra) high-frequency data, ﬁnance has become one of the main domains of application of Hawkes processes. Theintroduction of Hawkes processesin ﬁnanceis probablydueto ChavezDemoulin et al. (see [14]), in the context of value at risk estimation, and to Bowsher (see [12]), who jointly studied tr”
Forecasting: theory and practice (2020, background): “our. For that purpose, A¨ıt-Sahalia et al. (2015) propose mutually exciting jump processes, where jumps (read: crashes as negative jumps) can excite new jumps, also across assets or markets (see also Chavez-Demoulin et al., 2005). Another successful approach is the Autoregressive Conditional Duratio”