Richard Gerlach
Biographic Data
| ID | 4373301 |
|---|---|
| NAME | Richard Gerlach |
| GIVEN NAMES | Richard |
| FAMILY NAME | Gerlach |
| SIGNATURE | GERLACH R |
| AFFILIATIONS | University of Newcastle Australia |
| ORCID | 0000-0002-5656-4556 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 2 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2005 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 1 |
Bayesian forecast of the basic reproduction number during the Covid-19 epidemic in Morocco and Italy
In a Covid-19 susceptible-infected-recovered-dead model with time-varying rates of transmission, recovery, and death, the parameters are constant in small time intervals. A posteriori parameters result from the Euler-Maruyama approximation for stochastic differential equations and from Bayes’ theorem. Parameter estimates and 10-day predictions are performed based on Moroccan and Italian Covid-19 data. Mean absolute errors and mean square errors i…
Semiparametric GARCH via Bayesian Model Averaging
As the dynamic structure of financial markets is subject to dramatic change, a model capable of providing consistently accurate volatility estimates should not make rigid assumptions on how prices change over time. Most volatility models impose a particular parametric functional form that relates an observed price change to a volatility forecast (news impact function). Here, a new class of functional coefficient semiparametric volatility models i…
Bayesian Time-Varying Quantile Forecasting for Value-at-Risk in Financial Markets
Recently, advances in time-varying quantile modeling have proven effective in financial Value-at-Risk forecasting. Some well-known dynamic conditional autoregressive quantile models are generalized to a fully nonlinear family. The Bayesian solution to the general quantile regression problem, via the Skewed-Laplace distribution, is adapted and designed for parameter estimation in this model family via an adaptive Markov chain Monte Carlo sampling …
Interest rates and the 2004 Australian Election
During the October 2004 Australian federal election campaign the expected or possible effect of the election outcome on interest rates was a key point of differentiation between the Australian Labor Party and the Liberal–National Party coalition. The purpose of this paper is twofold. First, we examine whether this effect was a significant factor in the election outcome, as measured by the percentage swing towards the coalition in each electorate.…
Interest rates and the 2004 Australian Election
During the October 2004 Australian federal election campaign the expected or possible effect of the election outcome on interest rates was a key point of differentiation between the Australian Labor Party and the Liberal–National Party coalition. The purpose of this paper is twofold. First, we examine whether this effect was a significant factor in the election outcome, as measured by the percentage swing towards the coalition in each electorate.…
Interest rates and the 2004 Australian Election
During the October 2004 Australian federal election campaign the expected or possible effect of the election outcome on interest rates was a key point of differentiation between the Australian Labor Party and the Liberal–National Party coalition. The purpose of this paper is twofold. First, we examine whether this effect was a significant factor in the election outcome, as measured by the percentage swing towards the coalition in each electorate.…
Bayesian Time-Varying Quantile Forecasting for Value-at-Risk in Financial Markets
Recently, advances in time-varying quantile modeling have proven effective in financial Value-at-Risk forecasting. Some well-known dynamic conditional autoregressive quantile models are generalized to a fully nonlinear family. The Bayesian solution to the general quantile regression problem, via the Skewed-Laplace distribution, is adapted and designed for parameter estimation in this model family via an adaptive Markov chain Monte Carlo sampling …
Bayesian forecast of the basic reproduction number during the Covid-19 epidemic in Morocco and Italy
In a Covid-19 susceptible-infected-recovered-dead model with time-varying rates of transmission, recovery, and death, the parameters are constant in small time intervals. A posteriori parameters result from the Euler-Maruyama approximation for stochastic differential equations and from Bayes’ theorem. Parameter estimates and 10-day predictions are performed based on Moroccan and Italian Covid-19 data. Mean absolute errors and mean square errors i…
Semiparametric GARCH via Bayesian Model Averaging
As the dynamic structure of financial markets is subject to dramatic change, a model capable of providing consistently accurate volatility estimates should not make rigid assumptions on how prices change over time. Most volatility models impose a particular parametric functional form that relates an observed price change to a volatility forecast (news impact function). Here, a new class of functional coefficient semiparametric volatility models i…
Bayesian probability (3 works) · Computer Science (3 works) · Econometrics (3 works) · Economics (3 works) · Mathematics (3 works) · Statistics (3 works) · Financial Risk and Volatility Modeling (2 works) · Markov chain (2 works) · Markov chain Monte Carlo (2 works) · Monetary Policy and Economic Impact (2 works)