5 citations · 15 across the 14 of their papers we have counts for
15 papers
Money Growth and Inflation: A Quantile Sensitivity Approach
Matteo Iacopini, Aubrey Poon, Luca Rossini +1
An innovative method is proposed to construct a quantile dependence system for inflation and money growth. By considering all quantiles and leveraging a novel notion of quantile se…
Hybrid unadjusted Langevin methods for high-dimensional latent variable models
Ruben Loaiza-Maya, Didier Nibbering, Dan Zhu
The exact estimation of latent variable models with big data is known to be challenging. The latents have to be integrated out numerically, and the dimension of the latent variable…
Distributional Vector Autoregression: Eliciting Macro and Financial Dependence
Yunyun Wang, Tatsushi Oka, Dan Zhu
Vector autoregression is an essential tool in empirical macroeconomics and finance for understanding the dynamic interdependencies among multivariate time series. In this study, we…
High-Dimensional Conditionally Gaussian State Space Models with Missing Data
Joshua C. C. Chan, Aubrey Poon, Dan Zhu
We develop an efficient sampling approach for handling complex missing data patterns and a large number of missing observations in conditionally Gaussian state space models. Two im…
Bayesian Mixed-Frequency Quantile Vector Autoregression: Eliciting tail risks of Monthly US GDP
Matteo Iacopini, Aubrey Poon, Luca Rossini +1
Timely characterizations of risks in economic and financial systems play an essential role in both economic policy and private sector decisions. However, the informational content…
Bivariate Distribution Regression with Application to Insurance Data
Yunyun Wang, Tatsushi Oka, Dan Zhu
Understanding variable dependence, particularly eliciting their statistical properties given a set of covariates, provides the mathematical foundation in practical operations manag…
Efficient Estimation of State-Space Mixed-Frequency VARs: A Precision-Based Approach
Joshua C. C. Chan, Aubrey Poon, Dan Zhu
State-space mixed-frequency vector autoregressions are now widely used for nowcasting. Despite their popularity, estimating such models can be computationally intensive, especially…
A Spatial Stochastic SIR Model for Transmission Networks with Application to COVID-19 Epidemic in China
Tatsushi Oka, Wei Wei, Dan Zhu
Governments around the world have implemented preventive measures against the spread of the coronavirus disease (COVID-19). In this study, we consider a multivariate discrete-time…
Predictive Risk Analysis in Collective Risk Model: Choices between Historical Frequency and Aggregate Severity
Rosy Oh, Youngju Lee, Dan Zhu +1
Typical risk classification procedure in insurance is consists of a priori risk classification determined by observable risk characteristics, and a posteriori risk classification w…
Stochastic comparisons of sample mean differences for multivariate random variables
Xuehua Yin, Dan Zhu, Chuancun Yin
In this paper, we establish the stochastic ordering of the Gini indexes for multivariate elliptical risks which generalized the corresponding results for multivariate normal risks.…
Indirect Inference with a Non-Smooth Criterion Function
David T. Frazier, Tatsushi Oka, Dan Zhu
Indirect inference requires simulating realisations of endogenous variables from the model under study. When the endogenous variables are discontinuous functions of the model param…
Joint mixability of elliptical distributions and related families
Chuancun Yin, Dan Zhu
In this paper, three different proofs to a result of Wang, Peng and Yang (2013) which related to the joint mixability of elliptical distributions with the same characteristic gener…
Sharp convex bounds on the aggregate sums--An alternative proof
Chuancun Yin, Dan Zhu
It is well known that a random vector with given marginal distributions is comonotonic if and only if it has the largest sum with respect to the convex order [ Kaas, Dhaene, Vyncke…
New class of distortion risk measures and their tail asymptotics with emphasis on VaR
Chuancun Yin, Dan Zhu
Distortion risk measures are extensively used in finance and insurance applications because of their appealing properties. We present three methods to construct new class of distor…
Finite-time ruin probabilities of bidimensional risk models with correlated Brownian motions
Dan Zhu, Ming Zhou, Chuancun Yin
The present work concerns the finite-time ruin probabilities for several bidimensional risk models with constant interest force and correlated Brownian motions.} Under the conditio…