Michael Stanley Smith

Biographic Data

ID8920883
NAMEMichael Stanley Smith
GIVEN NAMESMichael Stanley
FAMILY NAMESmith
SIGNATURESMITH M S
AFFILIATIONSMelbourne Business School, University of Melbourne
VERIFIEDNo
TOTAL WORKS4
TOTAL CITATIONS0
WORKS AS AUTHOR4
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2020
LATEST PUBLICATION YEAR2025
H-INDEX0

  • Large Skew-t Copula Models and Asymmetric Dependence in Intraday Equity Returns

    Open AccessLin Deng, Michael Stanley Smith et al.ARTICLEJournal of Business and Economic…2025

    Skew-t copula models are attractive for the modeling of financial data because they allow for asymmetric and extreme tail dependence.We show that the copula implicit in the skew-t distribution of Azzalini and Capitanio allows for a higher level of pairwise asymmetric dependence than two popular alternative skew-t copulas.Estimation of this copula in high dimensions is challenging, and we propose a fast and accurate Bayesian variational inference …

  • Deep distributional time series models and the probabilistic forecasting of intraday electricity prices

    Open AccessNadja Klein, Michael Stanley Smith et al.ARTICLEJournal of Applied Econometrics2023

    Recurrent neural networks (RNNs) with rich feature vectors of past values can provide accurate point forecasts for series that exhibit complex serial dependence. We propose two approaches to constructing deep time series probabilistic models based on a variant of RNN called an echo state network (ESN). The first is where the output layer of the ESN has stochastic disturbances and a Bayesian prior for regularization. The second employs the implici…

  • Bayesian Inference for Regression Copulas

    Michael Stanley Smith, Nadja KleinARTICLEJournal of Business and Economic…2021

    We propose a new semiparametric distributional regression smoother that is based on a copula decomposition of the joint distribution of the vector of response values. The copula is high-dimensional and constructed by inversion of a pseudo regression, where the conditional mean and variance are semiparametric functions of covariates modeled using regularized basis functions. By integrating out the basis coefficients, an implicit copula process on …

  • Real-Time Macroeconomic Forecasting With a Heteroscedastic Inversion Copula

    Rubén Loaiza-Maya, Rubén Loaiza‐Maya et al.ARTICLEJournal of Business and Economic…2020

    There is a growing interest in allowing for asymmetry in the density forecasts of macroeconomic variables. In multivariate time series, this can be achieved with a copula model, where both serial and cross-sectional dependence is captured by a copula function, and the margins are nonparametric. Yet most existing copulas cannot capture heteroscedasticity well, which is a feature of many economic and financial time series. To do so, we propose a ne…