Liudas Giraitis

4.0k total citations
84 papers, 2.4k citations indexed

About

Liudas Giraitis is a scholar working on Finance, Economics and Econometrics and Statistics and Probability. According to data from OpenAlex, Liudas Giraitis has authored 84 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Finance, 48 papers in Economics and Econometrics and 26 papers in Statistics and Probability. Recurrent topics in Liudas Giraitis's work include Financial Risk and Volatility Modeling (58 papers), Complex Systems and Time Series Analysis (34 papers) and Statistical Methods and Inference (20 papers). Liudas Giraitis is often cited by papers focused on Financial Risk and Volatility Modeling (58 papers), Complex Systems and Time Series Analysis (34 papers) and Statistical Methods and Inference (20 papers). Liudas Giraitis collaborates with scholars based in United Kingdom, United States and Lithuania. Liudas Giraitis's co-authors include Донатас Сургайлис, Remigijus Leipus, Piotr Kokoszka, Hira L. Koul, George Kapetanios, Peter M. Robinson, Murad S. Taqqu, Gilles Teyssière, Tony Yates and Javier Hidalgo and has published in prestigious journals such as Journal of Econometrics, The Annals of Statistics and Journal of Applied Econometrics.

In The Last Decade

Liudas Giraitis

78 papers receiving 2.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Liudas Giraitis United Kingdom 25 1.7k 1.3k 591 492 228 84 2.4k
Fabienne Comte France 22 1.3k 0.8× 751 0.6× 863 1.5× 238 0.5× 99 0.4× 96 2.1k
Sangyeol Lee South Korea 27 1.2k 0.7× 606 0.5× 1.2k 2.1× 391 0.8× 71 0.3× 220 2.4k
Ernst Eberlein Germany 25 2.3k 1.3× 998 0.8× 324 0.5× 143 0.3× 235 1.0× 129 3.0k
Per A. Mykland United States 28 3.7k 2.1× 2.4k 1.8× 873 1.5× 784 1.6× 82 0.4× 82 4.5k
Remigijus Leipus Lithuania 20 1.1k 0.6× 769 0.6× 350 0.6× 251 0.5× 168 0.7× 89 1.5k
Liang Peng United States 27 1.7k 1.0× 740 0.6× 1.2k 2.0× 481 1.0× 68 0.3× 166 2.6k
H. Tong United Kingdom 16 801 0.5× 945 0.7× 463 0.8× 536 1.1× 59 0.3× 32 2.0k
Fred Espen Benth Norway 34 2.1k 1.2× 1.4k 1.1× 117 0.2× 207 0.4× 204 0.9× 199 3.5k
Oldrich A Vasicek United States 14 4.2k 2.4× 1.7k 1.3× 522 0.9× 1.1k 2.2× 144 0.6× 25 5.3k
Christian Francq France 26 2.0k 1.2× 1.3k 1.0× 892 1.5× 923 1.9× 52 0.2× 91 2.5k

Countries citing papers authored by Liudas Giraitis

Since Specialization
Citations

This map shows the geographic impact of Liudas Giraitis'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 Liudas Giraitis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liudas Giraitis more than expected).

Fields of papers citing papers by Liudas Giraitis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Liudas Giraitis. 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 Liudas Giraitis. The network helps show where Liudas Giraitis may publish in the future.

Co-authorship network of co-authors of Liudas Giraitis

This figure shows the co-authorship network connecting the top 25 collaborators of Liudas Giraitis. A scholar is included among the top collaborators of Liudas Giraitis 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 Liudas Giraitis. Liudas Giraitis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Giraitis, Liudas, et al.. (2025). Testing Mean Stability of Heteroskedastic Time Series. Journal of Time Series Analysis. 47(1). 182–200.
2.
Bailey, N. T. J. & Liudas Giraitis. (2015). Spectral approach to parameter-free unit root testing. Computational Statistics & Data Analysis. 100. 4–16. 1 indexed citations
3.
Giraitis, Liudas, George Kapetanios, & Simon Price. (2013). Adaptive forecasting in the presence of recent and ongoing structural change. Journal of Econometrics. 177(2). 153–170. 46 indexed citations
4.
Giraitis, Liudas, Hira L. Koul, & Донатас Сургайлис. (2012). Large Sample Inference for Long Memory Processes. IMPERIAL COLLEGE PRESS eBooks. 167 indexed citations
5.
Novak, S. Y., et al.. (2007). Evaluating Currency Risk in Emerging Markets. Acta Applicandae Mathematicae. 97(1-3). 163–175. 2 indexed citations
6.
Bhansali, R. J., Liudas Giraitis, & Piotr Kokoszka. (2006). Estimation of the memory parameter by fitting fractionally differenced autoregressive models. Journal of Multivariate Analysis. 97(10). 2101–2130. 13 indexed citations
7.
Giraitis, Liudas & Peter C.B. Phillips. (2006). Uniform Limit Theory for Stationary Autoregression. Journal of Time Series Analysis. 27(1). 51–60. 15 indexed citations
8.
Bhansali, R. J., Liudas Giraitis, & Piotr Kokoszka. (2006). Approximations and limit theory for quadratic forms of linear processes. Stochastic Processes and their Applications. 117(1). 71–95. 22 indexed citations
9.
Giraitis, Liudas, Javier Hidalgo, & Peter M. Robinson. (2001). Gaussian estimation of parametric spectral density with unknown\n\t\t\t pole. Project Euclid (Cornell University). 72 indexed citations
10.
Giraitis, Liudas & Peter M. Robinson. (2001). Parametric Estimation under Long-Range Dependence. London School of Economics and Political Science Research Online (London School of Economics and Political Science). 1 indexed citations
11.
Giraitis, Liudas, Piotr Kokoszka, & Remigijus Leipus. (2001). Testing for long memory in the presence of a general trend. Journal of Applied Probability. 38(4). 1033–1054. 23 indexed citations
12.
Giraitis, Liudas, Piotr Kokoszka, Remigijus Leipus, & Gilles Teyssière. (2000). Semiparametric Estimation of the Intensity of Long Memory in Conditional Heteroskedasticity. Statistical Inference for Stochastic Processes. 3(1-2). 113–128. 11 indexed citations
13.
Giraitis, Liudas, Peter M. Robinson, & Alexander Samarov. (2000). Adaptive Semiparametric Estimation of the Memory Parameter. Journal of Multivariate Analysis. 72(2). 183–207. 26 indexed citations
14.
Giraitis, Liudas, Piotr Kokoszka, & Remigijus Leipus. (2000). STATIONARY ARCH MODELS: DEPENDENCE STRUCTURE AND CENTRAL LIMIT THEOREM. Econometric Theory. 16(1). 3–22. 165 indexed citations
15.
Giraitis, Liudas, Peter M. Robinson, & Донатас Сургайлис. (1999). Variance-type estimation of long memory. Stochastic Processes and their Applications. 80(1). 1–24. 16 indexed citations
16.
Giraitis, Liudas & Hira L. Koul. (1997). Estimation of the dependence parameter in linear regression with long-range-dependent errors. Stochastic Processes and their Applications. 71(2). 207–224. 21 indexed citations
17.
Giraitis, Liudas. (1990). Central limit theorem for polynomial forms. I. Lithuanian Mathematical Journal. 29(2). 109–128. 2 indexed citations
18.
Giraitis, Liudas. (1985). Central limit theorem for functionals of a linear process. Lithuanian Mathematical Journal. 25(1). 25–35. 17 indexed citations
19.
Giraitis, Liudas & Донатас Сургайлис. (1985). CLT and other limit theorems for functionals of Gaussian processes. Probability Theory and Related Fields. 70(2). 191–212. 118 indexed citations
20.
Giraitis, Liudas. (1983). Convergence of certain nonlinear transformations of a Gaussian sequence to self-similar processes. Lithuanian Mathematical Journal. 23(1). 31–39. 9 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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