Richard Gerlach

2.4k total citations
91 papers, 1.6k citations indexed

About

Richard Gerlach is a scholar working on Finance, Economics and Econometrics and General Economics, Econometrics and Finance. According to data from OpenAlex, Richard Gerlach has authored 91 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Finance, 41 papers in Economics and Econometrics and 27 papers in General Economics, Econometrics and Finance. Recurrent topics in Richard Gerlach's work include Financial Risk and Volatility Modeling (57 papers), Monetary Policy and Economic Impact (26 papers) and Market Dynamics and Volatility (25 papers). Richard Gerlach is often cited by papers focused on Financial Risk and Volatility Modeling (57 papers), Monetary Policy and Economic Impact (26 papers) and Market Dynamics and Volatility (25 papers). Richard Gerlach collaborates with scholars based in Australia, Taiwan and Hong Kong. Richard Gerlach's co-authors include Cathy W. S. Chen, Robert Kohn, Chris Carter, Frank Tuyl, Qian Chen, Edward M.H. Lin, Ralf Zurbruegg, Kerrie Mengersen, Zudi Lu and Patrick Wilson and has published in prestigious journals such as Journal of the American Statistical Association, Expert Systems with Applications and IEEE Access.

In The Last Decade

Richard Gerlach

88 papers receiving 1.5k citations

Peers

Richard Gerlach

FINAN

GEEF

MSOR

Benedikt M. Pötscher Austria

Fallaw Sowell United States

Marc S. Paolella Switzerland

K. S. Lim Singapore

Roberto Casarin Italy

Agustı́n Maravall Spain

Drew Creal United States

Ričardas Zitikis Canada

Hélio S. Migon Brazil

P. J. Harrison United Kingdom

Benedikt M. Pötscher Austria

Richard Gerlach

467 ×0.5

FINAN

631 ×0.8

496 ×1.3

GEEF

951 ×2.7

270 ×1.3

MSOR

Citations per year, relative to Richard Gerlach Richard Gerlach (= 1×) peers Benedikt M. Pötscher

Countries citing papers authored by Richard Gerlach

Since Specialization

Citations

This map shows the geographic impact of Richard Gerlach's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Richard Gerlach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard Gerlach more than expected).

Fields of papers citing papers by Richard Gerlach

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard Gerlach. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Richard Gerlach. The network helps show where Richard Gerlach may publish in the future.

Co-authorship network of co-authors of Richard Gerlach

This figure shows the co-authorship network connecting the top 25 collaborators of Richard Gerlach. A scholar is included among the top collaborators of Richard Gerlach based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Richard Gerlach. Richard Gerlach is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Gerlach, Richard, et al.. (2023). A Bayesian realized threshold measurement GARCH framework for financial tail risk forecasting. Journal of Forecasting. 43(1). 40–57.

Gao, Junbin, et al.. (2022). A survey of the application of graph-based approaches in stock market analysis and prediction. International Journal of Data Science and Analytics. 14(1). 1–15. 30 indexed citations

Gao, Junbin, et al.. (2021). Stock Ranking Prediction Using List-Wise Approach and Node Embedding Technique. IEEE Access. 9. 88981–88996. 14 indexed citations

Gerlach, Richard, et al.. (2021). Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators. Economic Modelling. 107. 105701–105701. 8 indexed citations

Gerlach, Richard, et al.. (2020). Time-varying parameters realized GARCH models for tracking attenuation bias in volatility dynamics. Quantitative Finance. 20(11). 1849–1878. 3 indexed citations

Caraballo, Tomás, et al.. (2020). Analysis of a stochastic distributed delay epidemic model with relapse and Gamma distribution kernel. Chaos Solitons & Fractals. 133. 109643–109643. 37 indexed citations

Fatini, Mohamed El, et al.. (2019). Stationary distribution and threshold dynamics of a stochastic SIRS model with a general incidence. Physica A Statistical Mechanics and its Applications. 534. 120696–120696. 24 indexed citations

Vasnev, Andrey L., et al.. (2018). Mixed interval realized variance: A robust estimator of stock price volatility. Econometrics and Statistics. 11. 43–62. 1 indexed citations

Choy, S. T. Boris, et al.. (2014). Analyzing return asymmetry and quantiles through stochastic volatility models using asymmetric Laplace error via uniform scale mixtures. Applied Stochastic Models in Business and Industry. 31(5). 584–608. 9 indexed citations

10.

Watkins, John G., Andrey L. Vasnev, & Richard Gerlach. (2013). MULTIPLE EVENT INCIDENCE AND DURATION ANALYSIS FOR CREDIT DATA INCORPORATING NON‐STOCHASTIC LOAN MATURITY. Journal of Applied Econometrics. 29(4). 627–648. 11 indexed citations

11.

Chen, Cathy W. S. & Richard Gerlach. (2012). Semi-parametric quantile estimation for double threshold autoregressive models with heteroskedasticity. Computational Statistics. 28(3). 1103–1131. 13 indexed citations

12.

Chen, Cathy W. S., et al.. (2009). Bayesian Estimation for Parsimonious Threshold Autoregressive Models in R. SSRN Electronic Journal. 8 indexed citations

13.

Chen, Cathy W. S., et al.. (2009). Multi-regime nonlinear capital asset pricing models. Quantitative Finance. 11(9). 1421–1438. 15 indexed citations

14.

Tuyl, Frank, Richard Gerlach, & Kerrie Mengersen. (2008). A Comparison of Bayes–Laplace, Jeffreys, and Other Priors. The American Statistician. 62(1). 40–44. 49 indexed citations

15.

Bird, Ron & Richard Gerlach. (2006). A Bayesian model averaging approach to enhance value investment. OPUS - Open Publications of UTS Scholars (University of Technology Sydney). 5(2). 111–127. 3 indexed citations

16.

Cheong, Chee Seng, Richard Gerlach, Simon Stevenson, Patrick Wilson, & Ralf Zurbruegg. (2006). PERMANENT AND TRANSITORY DRIVERS OF SECURITISED REAL ESTATE. RePEc: Research Papers in Economics. 1 indexed citations

17.

Chen, Cathy W. S., et al.. (2005). The asymmetric reactions of mean and volatility of stock returns to domestic and international information based on a four-regime double-threshold GARCH model. Physica A Statistical Mechanics and its Applications. 366. 401–418. 14 indexed citations

18.

Gerlach, Richard, et al.. (2005). Interest rates and the 2004 Australian Election. Australian Journal of Political Science. 40(4). 559–566. 2 indexed citations

19.

Gerlach, Richard, Ron Bird, & Anthony Hall. (2002). Theory & Methods: Bayesian variable selection in logistic regression: predicting company earnings direction. Australian & New Zealand Journal of Statistics. 44(2). 155–168. 10 indexed citations

20.

Gerlach, Richard, Chris Carter, & Robert Kohn. (1999). Diagnostics for Time Series Analysis. Journal of Time Series Analysis. 20(3). 309–330. 40 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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