Dependence patterns across financial markets: a mixed copula approach

By Lingfang Hu. 2006

425 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/50df43dddc0025938c186f354d36af8367fadc0c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Finance

Citations in the corpus

Statistical arbitrage pairs trading strategies: Review and outlook (2017, positive): “Copulas are an adequate way of modeling such complex dependence structures and thus have the potential to identify better trading opportunities. The key issue inherent to this approach is the complete loss of time structure of the data. When calibrating trading opportunities with the copula method, ”
Measuring reproducibility of high-throughput experiments (2011, methodology): “For example, the mixed copula model [Hu (2006)] in economics uses a mixture of copulas [Cmix (u1, u2 | (θ1, .”
COPULA-BASED CHARACTERIZATIONS FOR HIGHER ORDER MARKOV PROCESSES (2009, methodology): “Motivated by applications in the study of the mechanism of human vision, Rosenblatt and Slepian (1962) constructed stationary N−th order Markov processes consisting of discrete r.”
Copula-Based Models of Systemic Risk in U.S. Agriculture: Implications for Crop Insurance and Reinsurance Contracts (2015, neutral): “Much of the work on copulas has been motivated by their applicability to the issues in risk management, insurance and financial economics (see, among others, Rodriguez (2003), Cherubini et al. (2004), Hu (2006), Patton (2006), and Jondeau and Rockinger (2006)).”
The Structure and Degree of Dependence - A Quantile Regression Approach (2012, positive): “Hu (2006) and Rodriguez (2007) among many others specify the mixture of copulas to obtain a joint distribution that provides the best fit to the data. Despite the fact that the copula joins the marginal distributions to build a joint distribution the focus of most papers in the empirical finance lit”
Copula-Based Models for Financial Time Series (2009, methodology): “Results for general classes of univariate nonlinear processes are presented in Carrasco and Chen (2002) and Meitz and Saikkonen (2004), however similar results for the multivariate case are not yet available.”
Asymmetries in Stock Returns: Statistical Tests and Economic Evaluation (2007, positive): “To formally quantify the deviations from symmetry, we, following Hu (2004), use a contingency table approach.”
Simple Tests for Models of Dependence between Multiple Financial Time Series, with Applications to U.S. Equity Returns and Exchange Rates (2004, background): “…Costinot, et al. (2000), Li (2000), Frey and McNeil (2001), Schonbucher and Schubert (2001), Cherubini and Luciano (2001, 2002), Duan (2002), Hu (2002), Junker and May (2002), Mashal and Zeevi (2002), Patton (2002a, b, 2004), Rockinger and Jondeau (2002), Dias and Embrechts (2003),…”
Inhomogeneous Dependence Modeling with Time-Varying Copulae (2009, positive): “equity data, rejecting multivariate normality at daily, weekly, and monthly frequencies; and Hu (2006) models the”
A revisit to the dependence structure between the stock and foreign exchange markets: A dependence-switching copula approach (2013, positive): “A number of previous studies have applied copulas to model the co-movements across international financial markets (Cherubini et al., 2004; Patton, 2006; Hu, 2006; Ning, 2010).”
Practical methods for measuring and managing operational risk in the financial sector: a clinical study (2008, result): “By contrast, the LDA model lends itself to quantifying the impact of active operational risk management actions, and justifying (potentially substantial) capital reductions.”
Multivariate non-normally distributed random variables in climate research - introduction to the copula approach (2008, positive): “In fact, mixture models and copulas can be combined as shown in Diday and Vrac (2005); Vrac et al. (2005); Hu (2006).”
A new approach to modeling co-movement of international equity markets: evidence of unconditional copula-based simulation of tail dependence (2009, background): “Asymmetric correlations have been observed by several studies (see e.g., Ang and Chen 2002; Longin and Solnik 2001; Hu 2006; Hong et al. 2007) that show stocks tend to have greater correlations in downside markets than in upside markets.”
Portfolio optimization in the presence of dependent financial returns with long memory: A copula based approach. (2013, background): “…between stock market returns (Costinot et al., 2000; Patton, 2004; Canela and Collazo, 2006; Kole et al., 2005; Jondeau and Rockinger, 2006; Hu, 2006; Rodriguez, 2007; de Melo Mendes and Kolev, 2008; Sun et al., 2009; Ignatievay and Platen, 2010; Aloui et al., 2011; Chollete et al., 2011;…”
Characterizations of joint distributions, copulas, information, dependence and decoupling, with applications to time series (2006, methodology): “Hu [32] used copulas to study the structure of dependence across financial markets.”