Jozef Baruník

3.6k total citations · 2 hit papers
64 papers, 2.1k citations indexed

About

Jozef Baruník is a scholar working on Economics and Econometrics, Finance and General Economics, Econometrics and Finance. According to data from OpenAlex, Jozef Baruník has authored 64 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Economics and Econometrics, 41 papers in Finance and 14 papers in General Economics, Econometrics and Finance. Recurrent topics in Jozef Baruník's work include Market Dynamics and Volatility (40 papers), Complex Systems and Time Series Analysis (34 papers) and Financial Risk and Volatility Modeling (34 papers). Jozef Baruník is often cited by papers focused on Market Dynamics and Volatility (40 papers), Complex Systems and Time Series Analysis (34 papers) and Financial Risk and Volatility Modeling (34 papers). Jozef Baruník collaborates with scholars based in Czechia, United Kingdom and United States. Jozef Baruník's co-authors include Lukáš Vácha, Evžen Kočenda, Ladislav Krištoufek, Tomáš Křehlík, Jiří Kukačka, Miloslav Vošvrda, Tiziana Di Matteo, Tomaso Aste, Ruipeng Liu and Nicholas Apergis and has published in prestigious journals such as European Journal of Operational Research, Expert Systems with Applications and The Review of Economics and Statistics.

In The Last Decade

Jozef Baruník

61 papers receiving 2.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers

2015 345 citations Jozef Baruník, Evžen Kočenda et al. profile →
Asymmetric volatility connectedness on the forex market

2017 212 citations Jozef Baruník, Evžen Kočenda et al. profile →

Peers

Jozef Baruník

EE

FINAN

GEEF

RESE

MSOR

Sung Y. Park South Korea

António Rua Portugal

Valentyn Panchenko Australia

Rania Jammazi Tunisia

Stan Hurn Australia

Yoon‐Jae Whang South Korea

Faruk Selçuk∥ Türkiye

Fulvio Corsi Italy

Zhiyuan Pan China

Dimitris Korobilis United Kingdom

Sung Y. Park South Korea

Jozef Baruník

946 ×0.5

EE

384 ×0.4

FINAN

340 ×0.7

GEEF

261 ×1.3

RESE

164 ×0.9

MSOR

Citations per year, relative to Jozef Baruník Jozef Baruník (= 1×) peers Sung Y. Park

Countries citing papers authored by Jozef Baruník

Since Specialization

Citations

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

Fields of papers citing papers by Jozef Baruník

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jozef Baruník

This figure shows the co-authorship network connecting the top 25 collaborators of Jozef Baruník. A scholar is included among the top collaborators of Jozef Baruník 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 Jozef Baruník. Jozef Baruník 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

1.

Baruník, Jozef & Lukáš Vácha. (2024). Predicting the volatility of major energy commodity prices: The dynamic persistence model. Energy Economics. 140. 107982–107982. 2 indexed citations

2.

Baruník, Jozef, et al.. (2024). Taming Data‐Driven Probability Distributions. Journal of Forecasting. 44(2). 676–691.

3.

Baruník, Jozef, et al.. (2023). Dynamic industry uncertainty networks and the business cycle. Journal of Economic Dynamics and Control. 159. 104793–104793. 5 indexed citations

4.

Baruník, Jozef, et al.. (2023). Learning Probability Distributions of Day-Ahead Electricity Prices. SSRN Electronic Journal. 4 indexed citations

5.

Baruník, Jozef, et al.. (2023). Persistence in financial connectedness and systemic risk. European Journal of Operational Research. 314(1). 393–407. 15 indexed citations

6.

Anatolyev, Stanislav & Jozef Baruník. (2019). Forecasting dynamic return distributions based on ordered binary choice. International Journal of Forecasting. 35(3). 823–835. 6 indexed citations

7.

Baruník, Jozef & Evžen Kočenda. (2019). Total, Asymmetric and Frequency Connectedness between Oil and Forex Markets. The Energy Journal. 40(2_suppl). 157–174. 57 indexed citations

8.

Baruník, Jozef, et al.. (2018). Are Bayesian Fan Charts Useful? The Effect of Zero Lower Bound and Evaluation of Financial Stability Stress Tests. International journal of central banking. 10(1). 159–188. 1 indexed citations

9.

Baruník, Jozef, et al.. (2017). Estimation of long memory in volatility using wavelets. Studies in Nonlinear Dynamics and Econometrics. 21(3). 2 indexed citations

10.

Baruník, Jozef, et al.. (2016). A semiparametric nonlinear quantile regression model for financial returns. Studies in Nonlinear Dynamics and Econometrics. 21(1). 81–97.

11.

Baruník, Jozef & Tomáš Křehlík. (2015). Measuring the Frequency Dynamics of Financial and Macroeconomic Connectedness. SSRN Electronic Journal. 30 indexed citations

12.

Baruník, Jozef & Jiří Kukačka. (2014). Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility. Quantitative Finance. 15(6). 959–973. 17 indexed citations

13.

Baruník, Jozef, et al.. (2014). An empirical model of fractionally cointegrated daily high and low stock market prices. Economic Modelling. 45. 193–206. 30 indexed citations

14.

Baruník, Jozef, et al.. (2013). Are Benefits from Oil - Stocks Diversification Gone? A New Evidence from a Dynamic Copulas and High Frequency Data. SSRN Electronic Journal. 1 indexed citations

15.

Baruník, Jozef, et al.. (2011). Neural Networks as Semiparametric Option Pricing Tool. RePEc: Research Papers in Economics. 18(28). 2 indexed citations

16.

Baruník, Jozef, Lukáš Vácha, & Miloslav Vošvrda. (2010). Tail Behavior of the Central European Stock Markets during the Financial Crisis. ASEP. 4(3). 281–294. 8 indexed citations

17.

Baruník, Jozef, Lukáš Vácha, & Miloslav Vošvrda. (2009). Smart predictors in the heterogeneous agent model. Journal of Economic Interaction and Coordination. 4(2). 163–172. 9 indexed citations

18.

Vácha, Lukáš, Jozef Baruník, & Miloslav Vošvrda. (2009). Smart Agents and Sentiment in the Heterogeneous Agent Model. Prague Economic Papers. 18(3). 209–219. 5 indexed citations

19.

Baruník, Jozef & Miloslav Vošvrda. (2009). Can a stochastic cusp catastrophe model explain stock market crashes?. Journal of Economic Dynamics and Control. 33(10). 1824–1836. 49 indexed citations

20.

Baruník, Jozef. (2008). How Do Neural Networks Enhance the Predictability of Central European Stock Returns. Czech Journal of Economics and Finance. 58. 358–376. 3 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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