# Barbara Będowska-Sójka

> Barbara Będowska-Sójka focuses on cryptocurrency and critical metal markets. She examines volatility and liquidity measures built from high-frequency data, the coherence of liquidity proxies and the dependencies between volatility and liquidity. Related strands cover the hedging and safe-haven properties of assets under geopolitical and energy shocks, and machine-learning methods in asset pricing.

- Affiliation: Department of Econometrics, Poznań University of Economics and Business, Poznań, Poland
- Research interests: financial econometrics, financial markets, cryptocurrency markets, critical metal markets, liquidity, volatility, high-frequency data, hedging and safe-haven assets, machine learning in finance, network science, bank, fintech, time series modelling
- Google Scholar: https://scholar.google.com/citations?user=noyoyCYAAAAJ

## Research topics

- [Cryptocurrency markets](https://barbbs.github.io/topic-crypto-markets.html): Pricing, volatility, liquidity and network structure of cryptocurrency markets, studied with econometric, machine-learning and network methods. (18 publications · 22 conference talks)
- [Market liquidity and its measurement](https://barbbs.github.io/topic-market-liquidity.html): How to measure liquidity when only daily data are available, how liquidity proxies relate to each other, and how liquidity interacts with volatility. (24 publications · 5 conference talks)
- [Safe havens, hedging and geopolitical risk](https://barbbs.github.io/topic-hedging-geopolitical-risk.html): Which assets protect portfolios during wars, pandemics and energy shocks, and how geopolitical and uncertainty shocks move prices. (10 publications · 12 conference talks)
- [Critical metals and the energy transition](https://barbbs.github.io/topic-critical-metals.html): Financialization, speculative bubbles and links with energy markets in lithium, cobalt, copper and nickel – the metals of the green transition. (2 publications · 5 conference talks)
- [Volatility, high-frequency data and macroeconomic news](https://barbbs.github.io/topic-volatility-high-frequency.html): Realized volatility, Value-at-Risk forecasting and the intraday reaction of stock and currency markets to macroeconomic announcements. (15 publications · 2 conference talks)
- [Fintech and digital finance](https://barbbs.github.io/topic-fintech.html): Fintech development in Poland, relations between fintechs and banks, digital assets, regulation and AI in finance. (8 publications · 1 conference talk)
- [Gender and networks in academic publishing](https://barbbs.github.io/topic-gender-academic-publishing.html): The gender composition and network structure of editorial boards of finance journals. (2 publications · 4 conference talks)

## Research projects

- [NCN OPUS 13 (UMO-2017/25/B/HS4/01546)](https://barbbs.github.io/project-opus13.html): 10 publications, funder: Narodowe Centrum Nauki
- [NCN OPUS 21 (UMO-2021/41/B/HS4/02443)](https://barbbs.github.io/project-opus21.html): 6 publications, funder: Narodowe Centrum Nauki
- [NCN OPUS 22 (LAP z GAČR) (UMO-2022/45/B/HS4/00864)](https://barbbs.github.io/project-opus22.html): 1 publications, funder: Narodowe Centrum Nauki
- [NCN OPUS 27 (UMO-2024/53/B/HS4/03300)](https://barbbs.github.io/project-opus27.html): 1 publications, funder: Narodowe Centrum Nauki
- [COST Action CA19130 FinAI (CA19130)](https://barbbs.github.io/project-cost.html): 6 publications, funder: European Cooperation in Science and Technology
- [MSCA Doctoral Network DIGITAL (101119635)](https://barbbs.github.io/project-digital.html): 2 publications, funder: Komisja Europejska, Horizon Europe MSCA
- [NCN MINIATURA 3 (2019/03/X/HS4/01025)](https://barbbs.github.io/project-miniatura.html): 1 publications, funder: Narodowe Centrum Nauki
- [Regionalna Inicjatywa Doskonałości (MNiSW) (004/RID/2018/19)](https://barbbs.github.io/project-rid.html): 2 publications, funder: Ministerstwo Nauki i Szkolnictwa Wyższego

## Journal articles

- [Tracing financialisation in critical metal markets: Correlations, bubbles, and dynamic linkages](https://barbbs.github.io/iaj2026-financialisation.html): Będowska-Sójka, B., Kasperek, M. (2026), Investment Analysts Journal. DOI: 10.1080/10293523.2026.2739157. The shift toward a net-zero economy has intensified demand for copper, cobalt, lithium and nickel. This paper tests four hypotheses on their financialisation across sixteen price series, from July 2021 to July 2025. We find no significant association between bubble intensity and series-level illiquidity. Cointegration does not track market maturity: copper, the most established market, converges least, while lithium converges most despite the highest bubble intensity. Short-run co-movement separates lithium and cobalt from copper and nickel, and once speculative episodes are filtered out, price discovery rests with Chinese exchanges in every metal where a leader can be identified. Financialisation is therefore uneven and multidimensional: the reliability of a price benchmark depends more on its source than on the metal it tracks.
- [Digital assets: risks, regulations, mitigation](https://barbbs.github.io/fi2026-digitalassets.html): Teng, H.-W., Härdle, W.K., Osterrieder, J., Pele, D.T., Baals, L.J., Papavassiliou, V., Bolesta, K., Kabašinskas, A., Filipovska, O., Thomaidis, N.S., Moukas, A.-I., Goundar, S., Nasir, J.A., Weinberg, A.I., Arakelian, V., Truică, C.-O., Akar, M., Kabaklarlı, E., Apostol, E.-S., Iannario, M., Będowska-Sójka, B., Skaftadóttir, H.K., Yildirim, O., Shala, A., Pisoni, G., Coita, I.F., Korba, S., Hafner, C.M., Schwendner, P., Molnár, B., Xhumari, E. (2026), Financial Innovation. DOI: 10.1186/s40854-025-00848-y.
- [Environmental awareness and infrastructure – A path to sustainable transport in Central and Eastern European Countries](https://barbbs.github.io/cstp2026-transport.html): Kliber, A., Łęt, B., Řezáč, P., Będowska-Sójka, B., Frič, J. (2026), Case Studies on Transport Policy. DOI: 10.1016/j.cstp.2025.101675. Reducing the use of combustion cars is one of the crucial aspects of the current environmental policy of the European Union. This article analyses how environmental awareness and the perceived quality of public transport and cycling infrastructure influence daily mobility mode choice in the Visegrad Group economies. We collected the data through surveys run in these countries from December 2023 to January 2024. We estimated a multilogit model with latent attitudinal variables. We demonstrate that ecological awareness is one of the key factors influencing consumers’ decisions about choosing transport modes other than a car. However, commuting remains predominantly car-based in all countries studied. Our results suggest that, when planning infrastructure that will encourage residents to use sustainable transport, decision-makers should prioritise creating good public transport connections with shopping centres, while cycling infrastructure should be linked to workplace and school locations.
- [The synergy of statistical and fuzzy logic approaches in mining patterns from the peer-to-peer lending data](https://barbbs.github.io/eswa2026-p2p.html): Hudec, M., Molnár, B., Pisoni, G., Vučetić, M., Barčáková, N., Będowska-Sójka, B., Öztürkkal, B., Perri Shkurti, R., Skaftadóttir, H.K., Iannario, M. (2026), Expert Systems with Applications. DOI: 10.1016/j.eswa.2025.129308. Statistical measures, such as correlation, compute numeric values. However, it is not always the best option for domain experts. A promising way is to augment these measures linguistically. Therefore, the main objective of this work is the synergy of statistical and fuzzy logic approaches in mining and interpreting valuable information from financial lending data. The correlation reveals whether attributes are related while exhibiting relatively low computational costs. Fuzzy functional dependencies recognize the direction of influence but are demanding in terms of computational cost. Finally, linguistic summaries explore and interpret dependencies between the subdomains of the considered attributes. These two approaches are less influenced by a smaller vagueness in the data. In addition, the support for decision making validated by diverse approaches and explained from different points of view is more reliable. These approaches are integrated and applied to peer-to-peer (P2P) anonymized lending data consisting of 266,483 loans. Among other things, a significant correlation between loan amount and loan duration (r = 0.25) is explained further, indicating that the direction of influence is slightly stronger from loan duration to loan amount than the opposite case. At the same time, the dependency is very strong from low duration to low amount, but relatively weak from high duration to high amount. Finally, further research and application directions are outlined.
- [Cross-sectional interactions in cryptocurrency returns](https://barbbs.github.io/irfa2025-crosssectional.html): Mercik, A., Będowska-Sójka, B., Karim, S., Zaremba, A. (2025), International Review of Financial Analysis. DOI: 10.1016/j.irfa.2024.103809. We investigate interaction effects in cryptocurrency markets by constructing and evaluating double-sorted portfolios based on 40 different characteristics. Using a dataset of over 500 major coins and tokens from 2017 to 2023, we identify numerous significant interactions. The most pronounced effects arise from the interplay of liquidity, risk, and past return measures. An out-of-sample long-short strategy that selects the top and bottom interactions achieves a Sharpe ratio exceeding 1. However, network graph analysis and additional tests reveal that low liquidity, which raises transaction costs, can dampen trading activity and contribute to the persistence of these anomalies.
- [Early warning systems for cryptocurrency markets: Predicting ‘zombie’ assets using machine learning](https://barbbs.github.io/najef2025-zombies.html): Będowska-Sójka, B., Wójcik, P., Pele, D.T. (2025), The North American Journal of Economics and Finance. DOI: 10.1016/j.najef.2025.102543. The cryptocurrency market harbours a hidden risk: assets that silently disappear from trading, leaving investors stranded. These 'zombie' cryptocurrencies technically exist but become temporarily untradable on exchanges, ranging from weeks to permanent delisting. This study predicts which cryptocurrencies are at risk of becoming zombies using predictors derived from return statistics, trading volume, market capitalisation, and asset-specific features. Our sample includes cryptocurrencies listed for at least 210 days between January 2015 and December 2022. We employ various machine learning algorithms and novel explainable AI (XAI) tools, including permutation-based feature importance and partial dependence plots (PDPs), to identify and analyse key factors influencing zombification risk. Our machine learning models achieve 84\% out-of-time balanced accuracy in predicting whether a cryptocurrency will become a zombie within the next 28 days. Tree-based approaches, particularly random forests, significantly outperform traditional econometric methods. Trading volumes and past returns emerge as the most influential predictors.
- [Editorial boards of finance journals: The gender gap and social networks](https://barbbs.github.io/jbe2025-editorialboards.html): Będowska-Sójka, B., Tarantola, C., Mare, C., Paccagnini, A., Öztürkkal, B., Pisoni, G., Shala, A., Perri, R., Skaftadóttir, H.K. (2025), Journal of Business Ethics. DOI: 10.1007/s10551-024-05830-9. We investigate gender disparities and network linkages among editors of Finance journals at the end of 2022. The role of journal editors in shaping academic disciplines is crucial, yet gender imbalances and the geographic concentration of editors remain poorly understood. Ethical considerations arise when examining the representation of women on editorial boards, as these imbalances can impact academic equity and the diversity of perspectives. We examine the gender composition of editorial boards and uncover the network structures among editors, seeking to shed light on the concentration of editorial power and its implications for diversity and inclusion. Our findings reveal that women account for an average of 20% of all editors, with notable variations across countries. Additionally, editorial affiliations are heavily concentrated in the United States and the United Kingdom. Through typological metrics, we identify highly connected editors with significant board memberships. While gender ratios remain consistent in substructures involving highly central editors or those serving on multiple boards, men consistently outnumber women.
- [Has bitcoin been dethroned too quickly? The cryptocurrency return networks](https://barbbs.github.io/nws2025-networks.html): Będowska-Sójka, B., Wójcik, P., Giordano, S. (2025), Network Science. DOI: 10.1017/nws.2024.17. This study aims to explore the dependencies on the cryptocurrency market using social network tools. We focus on the correlations observed in the cryptocurrency returns. Based on the sample of cryptocurrencies listed between January 2015 and December 2022 we examine which cryptos are central to the overall market and how often major players change. Static network analysis based on the whole sample shows that the network consists of several communities strongly connected and central, as well as a few that are disconnected and peripheral. Such a structure of the network implies high systemic risk. The day-by-day snapshots show that the network evolves rapidly. We construct the ranking of major cryptos based on centrality measures utilizing the TOPSIS method. We find that when single measures are considered, Bitcoin seems to have lost its first-mover advantage in late 2016. However, in the overall ranking, it still appears among the top positions. The collapse of any of the cryptocurrencies from the top of the rankings poses a serious threat to the entire market.
- [The effects of adopting the anti-smog resolution on air quality – the case study from Krakow](https://barbbs.github.io/ee2025-antismog.html): Herman, S., Będowska-Sójka, B., Paccagnini, A. (2025), Economics and Environment. DOI: 10.34659/eis.2025.93.2.931. We evaluate the impact of Krakow’s Anti-Smog Resolution, which was passed on January 15, 2016, and prohibits the use of coal and wood within the city. We use random forest, interrupted time series, and Bayesian structural time series models to assess air quality gains in terms of PM10, PM2.5, and benzo(a)pyrene concentrations, predicting pollution levels if the legislation had not been implemented. The results show significant reductions in pollutant concentrations: PM10 fell by 23% to 39%, PM2.5 by 23% to 36% and benzo(a)pyrene in PM10 by 39% to 41%, with the highest declines occurring during the heating season. These findings indicate the efficacy of Krakow's legislative strategy, offering evidence-based benchmarks for policymakers and public health officials in other cities considering similar residential heating restrictions to achieve measurable air quality improvements.
- [Do investors in dirty and clean cryptocurrencies care about energy efficiency in the same way?](https://barbbs.github.io/frl2024-dirtyclean.html): Będowska-Sójka, B., Kliber, A. (2024), Finance Research Letters. DOI: 10.1016/j.frl.2024.105852. This paper examines the environmental awareness of cryptocurrency investors. We study cryptocurrencies of different consensus protocols, categorised as clean and dirty. Within the non-linear autoregressive distributed lag model (NARDL), we verify whether short- or long-run dependency exists between cryptos’ prices or volatility and the Index of Cryptocurrency Environmental Attention, ICEA. We find that the volatilities of cryptocurrencies react stronger to the changes in ICEA than the prices do and that the former respond more to the decrease of the index than to its increase. The reaction is more pronounced for dirty cryptocurrencies.
- [Machine learning and the cross-section of cryptocurrency returns](https://barbbs.github.io/irfa2024-ml.html): Cakici, N., Shahzad, S.J.H., Będowska-Sójka, B., Zaremba, A. (2024), International Review of Financial Analysis. DOI: 10.1016/j.irfa.2024.103244. We employ a repertoire of machine learning models to investigate the cross-sectional re-turn predictability in cryptocurrency markets. While all methods generate substantial economic gains—unlike in other asset classes—the benefits from model complexity are limited. Return predictability derives mainly from a handful of simple characteristics, such as market price, past alpha, illiquidity, and momentum. Contrary to the stock market, abnormal returns in cryptocurrencies originate from the long leg of the trade and persist over time. Furthermore, despite high portfolio turnover, most machine learning strategies remain profitable after trading costs. However, alphas are concentrated in hard-to-trade assets and critically depend on harvesting extreme returns on small, illiquid, and volatile coins.
- [Proof-of-work versus proof-of-stake coins as possible hedges against green and dirty energy](https://barbbs.github.io/eneco2024-powpos.html): Kliber, A., Będowska-Sójka, B. (2024), Energy Economics. DOI: 10.1016/j.eneco.2024.107820. This article examines whether high- and low-environmental impact cryptocurrencies play a role as hedging instruments for green and non-green energy instruments. We differentiate between cryptocurrencies with two types of consensus mechanisms, proof-of-work and proof-of-stake, which reflect the energy demand used for the coins’ confirmation. We obtain volatilities and dynamic conditional correlations from stochastic volatility models and apply them to calculate hedge ratios. Based on the sample from 15 January 2019 to 15 September 2022, we find that clean coins provide equally good protection, measured by the hedge effectiveness, as compared to dirty coins. Yet, in each case, such effectiveness was time-varying and insignificant in some periods. Overall, cryptocurrencies are more effective hedges for oil than for clean energy assets.
- [Uncertainty and cryptocurrency returns: A lesson from turbulent times](https://barbbs.github.io/irfa2024-uncertainty.html): Będowska-Sójka, B., Górka, J., Hemmings, D., Zaremba, A. (2024), International Review of Financial Analysis. DOI: 10.1016/j.irfa.2024.103330. This paper examines the impacts of uncertainty indices on cryptocurrencies, and vice versa. We focus on instantaneous dependency in returns and volatility spillover effects among various indices proxying risk, namely geopolitical events, economic policy, commodity, stock and bond markets, and ten widely traded cryptocurrencies. Examining data from April 2018 to December 2022, we find that pairings of cryptocurrencies with the Volatility Index and the Crude Oil Volatility Index have dynamic correlations for returns that are different from zero and negative, but correlations with other uncertainty indices examined are non-significant. In the case of volatility spillovers, we consistently observe transmission from uncertainty indices to cryptocurrency prices to be generally rather weak, yet accelerates during turbulent periods such as the Covid-19 outbreak or the beginning of the Ukraine war. Overall, we conclude that while cryptocurrency pricing is largely disconnected from economic risk, the ability of the asset class to serve as a 'safe haven' may be limited. This paper explores the interplay between economic uncertainty and cryptocurrency behavior. Using data spanning from April 2018 to December 2022, we examine the relationship between ten major cryptocurrencies and a repertoire of uncertainty measures covering geopolitical events, economic policy, and commodity, equity, and bond markets. Cryptocurrency returns exhibit dynamic and positive correlation with stock market and oil volatility, but no significant association with other uncertainty proxies. In terms of volatility spillovers, the transmission from uncertainty indices to cryptocurrency markets is weak, but intensifies during turbulent periods such as the Covid-19 outbreak or the Ukraine war. Overall, the pricing of cryptocurrencies remains largely disconnected from economic risks, which casts doubt on their alleged "safe haven" properties.
- [Has the pandemic changed the relationships between fintechs and banks?](https://barbbs.github.io/ord2023-fintechbanks.html): Będowska-Sójka, B., Kliber, A., Laidroo, L. (2023), Operations Research and Decisions. DOI: 10.37190/ord230402. We examine the impact of COVID-19 on the banking and fintech sectors based on the relationships of the respective stock indices from December 2017 to April 2022. We analyse dynamic correlations within multivariate GARCH models and relationships in tails with the quantile coherency approach. Returns of fintech and banks dropped simultaneously at the beginning of the pandemic, but the analysis of cumulative returns and draw-downs reveals that the former recovered faster. Banks and fintechs experienced sharp declines together and fintech experienced extreme growth during the downfalls in the banking sector. However, the latter relationship disappears when we analyze only the banks from the USA and Eurozone. Thus, integrating with fintech may be especially beneficial for banks outside those regions. The ability of fintech to resurface and continue to grow demonstrates its importance in the financial system and confirms the shift toward a digital economy in financial markets
- [Can cryptocurrencies hedge oil price fluctuations? A pandemic perspective](https://barbbs.github.io/eneco2022-oil.html): Będowska-Sójka, B., Kliber, A. (2022), Energy Economics. DOI: 10.1016/j.eneco.2022.106360. The article aims to verify whether cryptocurrencies can hedge extreme price movements in Brent crude oil. The COVID-19 pandemic revealed that oil prices are heavily influenced by economic uncertainty and the mobility factor. We analyse Brent crude oil prices from February 10, 2020, to February 10, 2022. We consider Bitcoin, BNB, Ether, Tether, and USD Coin, the top five cryptocurrencies by market capitalization, as possible hedges. We explore their potential to protect oil investments using two approaches. The first focuses on price movement, and the second one on minimizing portfolio volatility. We use three modelling techniques: asymmetric causality in prices, a threshold vector-autoregressive model for returns, and dynamic conditional correlation analysis. We show that while stablecoins provide the best protection against downward movements in oil prices, they do not reduce investment volatility.
- [Do mixed-data sampling models help forecast liquidity and volatility?](https://barbbs.github.io/pss2022-midas.html): Będowska-Sójka, B., Kliber, A. (2022), Przegląd Statystyczny. DOI: 10.5604/01.3001.0016.0363. This paper aims to contribute to the existing studies on the Granger-causal relationship between volatility and liquidity in the stock market. We examine whether liquidity improves volatility forecasts and whether volatility allows the improvement of liquidity forecasts. The forecasts based on the mixed-data sampling models, MIDAS, are compared to those obtained from models based on daily data. Our results show that volatility and liquidity forecasts from MIDAS models outperform naive forecasts. On the other hand, the application of mixed-data sampling models does not significantly improve the performance of the forecasts of either liquidity or volatility based on a univariate autoregressive model or a vectorautoregressive one. We found that in terms of the forecasting ability, the VAR models and the AR models seem to perform equally well, as the differences in forecasting errors generated by these two types of models are not statistically significant.
- [False safe haven assets: Evidence from the target volatility strategy based on recurrent neural network](https://barbbs.github.io/ribaf2022-falsesafehaven.html): Kaczmarek, T., Będowska-Sójka, B., Grobelny, P., Perez, K. (2022), Research in International Business and Finance. DOI: 10.1016/j.ribaf.2021.101610. This paper examines which safe haven assets should be used when improving out-of-sample portfolio performance. We define a market state with recurrent neural network (RNN) volatility predictions and construct an investment strategy that dynamically combines equity, cash, and safe havens. The equity is allocated by targeting the volatility, and investing in safe havens depends on the predicted market state. We consider the S&P500 index with 13 safe haven assets, such as long-term government bonds, commodities, gold, and other precious metals. Other indices, NIKKEI225, NIFTY50, and STOXX50, are examined for robustness. With analysis conducted over a 20-year sample period, we find that RNN delivers sound predictions to construct the volatility targeting strategy. Among considered assets, only long-term Treasury bonds act as a safe haven and improve the strategy performance. Other considered assets have no such potential. Our findings are relevant to portfolio managers and investors actively managing portfolio risk.
- [Hedging geopolitical risks with different asset classes: A focus on the Russian invasion of Ukraine](https://barbbs.github.io/frl2022-hedging-ukraine.html): Będowska-Sójka, B., Demir, E., Zaremba, A. (2022), Finance Research Letters. DOI: 10.1016/j.frl.2022.103192. We examine the hedging properties of different asset classes as impacted by the Russian invasion of Ukraine in 2022. We employ wavelet coherence analysis to study the impact of geopolitical risk on various types of securities. We found that different asset classes exhibited unequal risk sensitivity in both magnitude and timescale. Bonds and stocks displayed strong coherence for multi-week horizons, whereas currencies were affected at shorter periods. The green bonds, gold, silver, Swiss franc, and real estate proved the most resistant to geopolitical risk fluctuations. Hence, they may serve as the best hedge against geopolitical risk.
- [Is geopolitical risk priced in the cross-section of cryptocurrency returns?](https://barbbs.github.io/frl2022-geopolitical-crypto.html): Long, H., Demir, E., Będowska-Sójka, B., Zaremba, A., Shahzad, S.J.H. (2022), Finance Research Letters. DOI: 10.1016/j.frl.2022.103131. We examine the role of geopolitical risk in the cross-sectional pricing of cryptocurrencies. We calculate cryptocurrency exposure to changes in the geopolitical risk index and document that coins with the lowest geopolitical beta outperform those with high geopolitical beta. Our findings suggest that risk-averse investors require additional compensation as motivation to hold cryptocurrencies with low and negative geopolitical betas, and they are willing to pay a premium for assets with high and positive geopolitical betas. The effect cannot be explained by known return predictors and is robust to many considerations.
- [The asymmetry of the Amihud illiquidity measure on the European markets: The evidence from Extreme Value Theory](https://barbbs.github.io/jifmim2022-amihud.html): Będowska-Sójka, B., Echaust, K., Just, M. (2022), Journal of International Financial Markets, Institutions and Money. DOI: 10.1016/j.intfin.2022.101563. This paper explores the extreme illiquidity for a sample of stocks listed on the European stock markets. The extreme value theory tools such as an extremal index as a measure of illiquidity dependence and a return level as a measure of illiquidity risk are applied. We obtain Amihud illiquidity separately for positive and negative returns and verify if there is an asymmetry in the extreme illiquidity. This study finds that the extreme illiquidity clusters more for negative returns than positive ones. Moreover, the clustering of extreme illiquidity is observed more often on the emerging markets than on the developed ones. For stocks listed on the emerging markets, the risk of extreme illiquidity is higher in the case of negative returns than of positive ones, while for stocks listed on developed markets no such phenomena is found. Our robustness check conducted with volatility over volume as an illiquidity measure confirms results obtained for the extremal indices, but not for the return level.
- [The lithium and oil markets – dependencies and volatility spillovers](https://barbbs.github.io/resourpol2022-lithium.html): Będowska-Sójka, B., Górka, J. (2022), Resources Policy. DOI: 10.1016/j.resourpol.2022.102901. Lithium is one of the rare raw materials needed to produce high-capacity batteries. Electric cars, said to be the future of automobility, have already begun to replace oil and gasoline-powered cars. This paper analyzes price sensitivity of the world’s largest lithium producers in U.S. and China to the Brent crude oil price changes. Since there are no direct ways to invest in lithium commodity, investors might gain exposure to lithium prices thorough investments into lithium mining companies. We focus on the time-varying dependency between returns of lithium producers and Brent crude oil as well as the potential volatility spillover effect between lithium and oil. We find that returns of American lithium mining stocks are in general weakly correlated to the changes of oil prices, but they are still more strongly correlated than the returns of Chinese companies. The dynamics of correlations are similar within a market, but different across markets. The tail dependence is the strongest for the pairs of American and pair of Chinese companies, but no dependence is found for oil and lithium producers. From the portfolio management perspective oil and lithium stocks are good diversifiers, but as the correlations are time-varying such outcomes are temporary.
- [Information content of liquidity and volatility measures](https://barbbs.github.io/physa2021-information.html): Będowska-Sójka, B., Kliber, A. (2021), Physica A: Statistical Mechanics and its Applications. DOI: 10.1016/j.physa.2020.125436. This paper aims to compare the mutual information shared by various liquidity and volatility estimators within each group separately. Our sample covers forty one blue-chip companies from the Warsaw Stock Exchange. In terms of their information content, volatility measures are much more coherent, while liquidity ones are more dispersed. The Garman–Klass volatility estimator seems to be the broadest measure of volatility, while Amihud illiquidity and Volatility over volume share the highest amount of mutual information among liquidity proxies. The latter proxy shares approximately the same amount of information with both volatility estimates and liquidity proxies. The possibility to forecast volatility or liquidity, measured by the transfer entropy, with the help of the other volatility or liquidity proxies is limited.
- [Is Bitcoin still a king? Relationships between prices, volatility and liquidity of cryptocurrencies during the pandemic](https://barbbs.github.io/entropy2021-bitcoinking.html): Będowska-Sójka, B., Kliber, A., Rutkowska, A. (2021), Entropy. DOI: 10.3390/e23111386. We try to establish the commonalities and leadership in the cryptocurrency markets by examining the mutual information and lead-lag relationships between Bitcoin and other cryptocurrencies from January 2019 to June 2021. We examine the transfer entropy between volatility and liquidity of seven highly capitalized cryptocurrencies in order to determine the potential direction of information flow. We find that cryptocurrencies are strongly interrelated in returns and volatility but less in liquidity. We show that smaller and younger cryptocurrencies (such as Ripple’s XRP or Litecoin) have started to affect the returns of Bitcoin since the beginning of the pandemic. Regarding liquidity, the results of the dynamic time warping algorithm also suggest that the position of Monero has increased. Those outcomes suggest the gradual increase in the role of privacy-oriented cryptocurrencies.
- [Is liquidity wasted? The zero-returns on the Warsaw Stock Exchange](https://barbbs.github.io/anor2021-zeroreturns.html): Będowska-Sójka, B. (2021), Annals of Operations Research. DOI: 10.1007/s10479-020-03849-5. The purpose of our study is to examine the dynamics of various liquidity proxies around specific price formation within intraday data. We examine the behavior of the measures representing price impact, depth of the market, its width and elasticity around intraday zero-return observations. Our sample is based upon quotations of blue chip stocks listed on the Warsaw Stock Exchange, one of the European emerging markets. This paper identifies an incoherent behavior of liquidity measures from different dimensions around intraday zero-returns. Although the transaction costs are lower and zero return configurations seem to offer better liquidity, this potential is not exploited as the trading activity measures decrease. The stock market is characterized by high resiliency as the observed changes in liquidity measures are short-term.
- [Is there one safe-haven for various turbulences? The evidence from gold, Bitcoin and Ether](https://barbbs.github.io/najef2021-safehaven.html): Będowska-Sójka, B., Kliber, A. (2021), The North American Journal of Economics and Finance. DOI: 10.1016/j.najef.2021.101390. This paper aims to investigate the safe-haven properties of gold and two cryptocurrencies, Bitcoin and Ether. Safe havens are the financial assets that allow investors to protect their portfolios within the market turmoil. The research sample covers five years and includes several downturns on the financial markets, starting from the Chinese stock market turbulences in 2015/2016 and ending up with the recent pandemic outbreak in 2020. We find that only gold used to be a strong safe-haven against the stock market indices. Yet, this property evaporated during the crisis caused by the COVID pandemic. Occasionally, cryptocurrencies could have been considered weak safe-havens against the examined instruments. Ether acted more often as a weak safe-haven against DAX or S&P500, while Bitcoin played this role against FTSE250, STOXX600 and S&P500.
- [Triggers and obstacles to the development of the FinTech sector in Poland](https://barbbs.github.io/risks2021-fintech.html): Kliber, A., Będowska-Sójka, B., Rutkowska, A., Świerczyńska, K. (2021), Risks. DOI: 10.3390/risks9020030.
- [Do aggressive orders affect liquidity? An evidence from an emerging market](https://barbbs.github.io/ribaf2020-aggressive.html): Będowska-Sójka, B. (2020), Research in International Business and Finance. DOI: 10.1016/j.ribaf.2020.101307. This paper investigates how aggressive orders affect spreads and trading activity measures on the stock market. Based on a sample of stocks listed on the Warsaw Stock Exchange this study finds that spreads and trading activity measures increase significantly when aggressive orders are executed, but quickly revert to initial levels. The reaction to these orders on the bid and ask side of the market is similar. The effect of aggressive orders differ depending on the size of the firms. Trading activity measures such as volumes or number of transactions increase stronger for bigger than for smaller stocks, while spreads increase more for smaller firms than for bigger ones. These findings enrich the understanding of liquidity dynamics especially on the emerging markets where liquidity is an important price formation factor.
- [Do liquidity proxies based on daily prices and quotes really measure liquidity?](https://barbbs.github.io/entropy2020-proxies.html): Będowska-Sójka, B., Echaust, K. (2020), Entropy. DOI: 10.3390/e22070783.
- [What is the best proxy for liquidity in the presence of extreme illiquidity?](https://barbbs.github.io/emr2020-proxy.html): Będowska-Sójka, B., Echaust, K. (2020), Emerging Markets Review. DOI: 10.1016/j.ememar.2020.100695. This paper aims to indicate the best daily proxy for unobserved liquidity in the presence of extreme movements on the market. We apply copulas to investigate the dependence between benchmarks based on intraday prices and proxies based on daily data. We focus on the tail dependence between both types of measures. Our results show that when the market experiences extreme illiquidity, the Closing Quoted Spread (CQS) based on daily closing bid and ask prices is superior to other percent-cost low-frequency proxies. We find the highest tail dependence coefficients for CQS and either the Percent Effective Spread or the Percent Quoted Spread.
- [Commonality in liquidity indices: The emerging European stock markets](https://barbbs.github.io/systems2019-commonality.html): Będowska-Sójka, B., Echaust, K. (2019), Systems. DOI: 10.3390/systems7020024.
- [Risk transmission between sovereign credit default swaps and government bonds during the global financial crisis. The case of the Czech Republic, Hungary and Poland](https://barbbs.github.io/cejeme2019-cds.html): Będowska-Sójka, B., Kliber, A. (2019), Central European Journal of Economic Modelling and Econometrics.
- [The causality between liquidity and volatility in the Polish stock market](https://barbbs.github.io/frl2019-causality.html): Będowska-Sójka, B., Kliber, A. (2019), Finance Research Letters. DOI: 10.1016/j.frl.2019.04.008.
- [The dynamics of low-frequency liquidity measures: The developed versus the emerging market](https://barbbs.github.io/jfs2019-lowfrequency.html): Będowska-Sójka, B. (2019), Journal of Financial Stability. DOI: 10.1016/j.jfs.2019.05.006.
- [Emerging and mature markets – behaviour of low-frequency liquidity measures. The case of the German and Polish stock markets](https://barbbs.github.io/pz2018-emerging.html): Będowska-Sójka, B. (2018), Problemy Zarządzania / European Management Studies. DOI: 10.7172/1644-9584.76.2.
- [Idiosyncratic volatility, returns, and mispricing: No real anomaly in sight](https://barbbs.github.io/frl2018-idiosyncratic.html): Zaremba, A., Czapkiewicz, A., Będowska-Sójka, B. (2018), Finance Research Letters. DOI: 10.1016/j.frl.2017.09.002.
- [Is intraday data useful for forecasting VaR? The evidence from EUR/PLN exchange rate](https://barbbs.github.io/rm2018-var.html): Będowska-Sójka, B. (2018), Risk Management. DOI: 10.1057/s41283-018-0038-z.
- [The coherence of liquidity measures. The evidence from the emerging market](https://barbbs.github.io/frl2018-coherence.html): Będowska-Sójka, B. (2018), Finance Research Letters. DOI: 10.1016/j.frl.2018.02.014.
- [Evaluating the accuracy of time-varying beta. The evidence from Poland](https://barbbs.github.io/dem2017-beta.html): Będowska-Sójka, B. (2017), Dynamic Econometric Models.
- [How jumps affect liquidity? The evidence from Poland](https://barbbs.github.io/fau2017-jumps.html): Będowska-Sójka, B. (2017), Finance a úvěr – Czech Journal of Economics and Finance.
- [Porównanie miesięcznych miar płynności akcji spółek notowanych na GPW wyznaczanych na podstawie danych niskiej częstotliwości](https://barbbs.github.io/pz2017-miesieczne.html): Będowska-Sójka, B. (2017), Problemy Zarządzania / European Management Studies. DOI: 10.7172/1644-9584.66.11.
- [Unemployment rates forecasts: Unobserved component models versus SARIMA models in Central and Eastern European countries](https://barbbs.github.io/cer2017-unemployment.html): Będowska-Sójka, B. (2017), Comparative Economic Research. Central and Eastern Europe. DOI: 10.1515/cer-2017-0014.
- [Liquidity dynamics around jumps: The evidence from the Warsaw Stock Exchange](https://barbbs.github.io/emft2016-jumps.html): Będowska-Sójka, B. (2016), Emerging Markets Finance and Trade. DOI: 10.1080/1540496X.2016.1216937.
- [Daily VaR forecasts with realized volatility and GARCH models](https://barbbs.github.io/ae2015-var.html): Będowska-Sójka, B. (2015), Argumenta Oeconomica. DOI: 10.15611/aoe.2015.1.06.
- [Unemployment rate forecasts: Evidence from the Baltic States](https://barbbs.github.io/eee2015-baltic.html): Będowska-Sójka, B. (2015), Eastern European Economics. DOI: 10.1080/00128775.2015.1033236.
- [Intraday stealth trading: Evidence from the Warsaw Stock Exchange](https://barbbs.github.io/ebr2014-stealth.html): Będowska-Sójka, B. (2014), Economics and Business Review. DOI: 10.18559/ebr.2014.1.822.
- [Badania reakcji na ogłoszenia makroekonomiczne w śróddziennych zwrotach z indeksów giełdowych](https://barbbs.github.io/sop2013-reakcje.html): Będowska-Sójka, B. (2013), Studia Oeconomica Posnaniensia. DOI: 10.18559/q6q5fk33.
- [Economic situation of the country or risk in the world financial market? The dynamics of Polish sovereign credit default swap spreads](https://barbbs.github.io/dem2013-cds.html): Kliber, A., Będowska-Sójka, B. (2013), Dynamic Econometric Models. DOI: 10.12775/DEM.2013.005.
- [Macroeconomic news effects on the stock markets in intraday data](https://barbbs.github.io/cejeme2013-macronews.html): Będowska-Sójka, B. (2013), Central European Journal of Economic Modelling and Econometrics.
- [Jumps in stock returns. Evidence from the Polish Stock Exchange](https://barbbs.github.io/ul2012-jumps.html): Będowska-Sójka, B. (2012), University of Lodz (materiały konferencyjne).
- [Zastosowanie zmienności zrealizowanej i modeli typu ARCH w wyznaczaniu wartości zagrożonej](https://barbbs.github.io/pnuew2012-var.html): Będowska-Sójka, B. (2012), Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu.
- [Analiza głównych składowych w modelowaniu struktury terminowej stóp procentowych](https://barbbs.github.io/ue2011-pca.html): Będowska-Sójka, B. (2011), Zeszyty Naukowe Uniwersytetu Ekonomicznego w Poznaniu.
- [Interdependence between the CAC40 and the DAX indices in intraday data](https://barbbs.github.io/ekon2011-cacdax.html): Będowska-Sójka, B. (2011), Ekonometria (UE we Wrocławiu).
- [Prognozowanie zmienności zwrotów z akcji z wykorzystaniem danych śróddziennych](https://barbbs.github.io/ue2011-prognozowanie.html): Będowska-Sójka, B. (2011), Zeszyty Naukowe Uniwersytetu Ekonomicznego w Poznaniu.
- [The impact of macro news on volatility of stock exchanges](https://barbbs.github.io/dem2011-macronews.html): Będowska-Sójka, B. (2011), Dynamic Econometric Models. DOI: 10.12775/DEM.2011.007.
- [Beta zrealizowana jako metoda pomiaru ryzyka systematycznego](https://barbbs.github.io/us2010-beta.html): Będowska-Sójka, B. (2010), Zeszyty Naukowe Uniwersytetu Szczecińskiego. Finanse, Rynki Finansowe, Ubezpieczenia.
- [Intraday CAC40, DAX and WIG20 returns when the American macro news is announced](https://barbbs.github.io/bik2010-intraday.html): Będowska-Sójka, B. (2010), Bank i Kredyt.
- [Macroeconomic announcements and volatility of intraday WIG and DAX returns](https://barbbs.github.io/ul2010-wigdax.html): Będowska-Sójka, B. (2010), University of Lodz (materiały konferencyjne).
- [Realized volatility versus GARCH and stochastic volatility models. The evidence from the WIG20 index and the EUR/PLN foreign exchange market](https://barbbs.github.io/ps2010-realized.html): Będowska-Sójka, B., Kliber, A. (2010), Przegląd Statystyczny. DOI: 10.59139/ps.2010.04.8.
- [Event study analysis with market model and GARCH modelling: Announcement of share repurchase on the Warsaw Stock Exchange](https://barbbs.github.io/ue2009-eventstudy.html): Będowska-Sójka, B. (2009), Zeszyty Naukowe Uniwersytetu Ekonomicznego w Poznaniu.
- [Announcement effects of dividend changes](https://barbbs.github.io/ul2008-dividend.html): Będowska-Sójka, B. (2008), University of Lodz (materiały konferencyjne).
- [Ogłoszenia danych makroekonomicznych i zmienność indeksu WIG](https://barbbs.github.io/us2008-wig.html): Będowska-Sójka, B. (2008), Studia i Prace Wydziału Nauk Ekonomicznych i Zarządzania US.
- [Modele logitowe polityki wypłat polskich spółek giełdowych](https://barbbs.github.io/ue2007-logit.html): Będowska-Sójka, B. (2007), Zeszyty Naukowe Akademii Ekonomicznej w Poznaniu.
- [Polityka stabilnej dywidendy: modele tobitowe i probitowe](https://barbbs.github.io/ue2007-tobit.html): Będowska-Sójka, B. (2007), Zeszyty Naukowe Akademii Ekonomicznej w Poznaniu.

## Book chapters and conference papers

- [Investigating gender gap in editorial boards of finance journals: A social network perspective](https://barbbs.github.io/sis2025-gendergap.html): Tarantola, C., Będowska-Sójka, B., Mare, C., Paccagnini, A., Öztürkkal, B., Pisoni, G., Perri, R., Shala, A., Skaftadóttir, H.K. (2025), Methodological and Applied Statistics and Demography (Italian Statistical Society Series). DOI: 10.1007/978-3-031-64350-7_111.
- [Liquidity of the European indices: The developed versus the emerging markets](https://barbbs.github.io/spbe2020-europeanindices.html): Będowska-Sójka, B. (2020), Finance and Sustainability (Springer Proceedings in Business and Economics). DOI: 10.1007/978-3-030-34401-6_21.
- [Volatility and liquidity in cryptocurrency markets—The causality approach](https://barbbs.github.io/spbe2020-cryptocausality.html): Będowska-Sójka, B., Hinc, T., Kliber, A. (2020), Contemporary Trends and Challenges in Finance (Springer Proceedings in Business and Economics). DOI: 10.1007/978-3-030-43078-8_3.
- [Commonality in liquidity measures. The evidence from the Polish stock market](https://barbbs.github.io/hed2019-commonality.html): Będowska-Sójka, B. (2019), Hradec Economic Days. DOI: 10.36689/uhk/hed/2019-01-003.
- [Financial Engineering: Methods and Cases (rozdział)](https://barbbs.github.io/book2019-fineng.html): Kliber, P. (red.); Będowska-Sójka, B. (współautorka) (2019), Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu.
- [Liquidity on the capital market with asymmetric information](https://barbbs.github.io/spbe2019-asymmetric.html): Będowska-Sójka, B., Garsztka, P. (2019), Effective Investments on Capital Markets (Springer Proceedings in Business and Economics). DOI: 10.1007/978-3-030-21274-2_26.

## Books and reports

- [FinTechs in Poland: Insights, trends and perspectives](https://barbbs.github.io/report2020-fintechs.html): Kliber, A., Będowska-Sójka, B., Rutkowska, A., Świerczyńska, K. i in. (2020), QuantFin.pl (raport).
- [Posiedzenie Naukowej Rady Statystycznej — październik 2016 r.](https://barbbs.github.io/ws2017-rada-pazdziernik.html): Będowska-Sójka, B. (2017), Wiadomości Statystyczne.
- [Posiedzenie Naukowej Rady Statystycznej — luty 2016 r.](https://barbbs.github.io/ws2016-rada-luty.html): Będowska-Sójka, B. (2016), Wiadomości Statystyczne.
- [Wpływ informacji na ceny instrumentów finansowych: analiza danych śróddziennych](https://barbbs.github.io/book2014-intraday.html): Będowska-Sójka, B. (2014), Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu.

## Working papers and preprints

- [When markets never sleep: Intraday liquidity patterns and macroeconomic announcement effects in cryptocurrency trading](https://barbbs.github.io/wp2026-neversleep.html): Mercik, A.R., Będowska-Sójka, B. (2026), SSRN Working Paper. DOI: 10.2139/ssrn.7434697.
- [When size matters: Volatility-to-liquidity transmission in cryptocurrency networks](https://barbbs.github.io/wp2026-sizematters.html): Będowska-Sójka, B., Mercik, A.R. (2026), SSRN Working Paper. DOI: 10.2139/ssrn.6233751.
- [White paper on cryptocurrency indices](https://barbbs.github.io/wp2026-indices.html): Gaman, S., Pele, D.T., Härdle, W.K., Będowska-Sójka, B. (2026), IDA-CL / Bucharest University of Economic Studies. DOI: 10.24818/ida-cl/2026.13.
- [Is there an impact of Ethereum Merge on the relationship between this cryptocurrency and energy portfolios?](https://barbbs.github.io/wp2025-merge.html): Będowska-Sójka, B., Kliber, A. (2025), SSRN Working Paper. DOI: 10.2139/ssrn.5719349.
- [Transmission dynamics in crypto markets: Comparing volatility and liquidity spillover networks](https://barbbs.github.io/wp2025-transmission.html): Będowska-Sójka, B. (2025), IDA-CL / Bucharest University of Economic Studies. DOI: 10.24818/ida-cl/2025.153.
- [AI-driven failed trials in investment strategies: A network data analysis approach](https://barbbs.github.io/wp-aifailedtrials.html): Bolesta, K., Akar, M., Coita, I., Tarantola, C., Iannario, M., Osterrieder, J., Sipos, C. i in. (2024), Working Paper.
- [Ethical artificial intelligence, fintech and data protection: A path forward for training in Europe](https://barbbs.github.io/wp2024-ethicalai.html): Moloney, M., Coita, I., Paschalidou, E.G., Svetlova, E., Mare, C., Stanca, L., Pisoni, G. i in. (w tym Będowska-Sójka, B.) (2024), SSRN Working Paper. DOI: 10.2139/ssrn.4885037.
- [FinTech, regulation, and cybercrime: Opportunities arising from new technologies](https://barbbs.github.io/wp2023-fintechcybercrime.html): Achim, M.V., Pisoni, G., Mare, C., Moloney, M., Korba, S., Molnár, B., Będowska-Sójka, B., Coita, I. (2023), SSRN Working Paper. DOI: 10.2139/ssrn.4620106.
- [Volatility forecasts based on data sampled at different frequencies](https://barbbs.github.io/wp2012-volforecasts.html): Będowska-Sójka, B. (2012), Advanced Risk & Portfolio Management Paper (SSRN). DOI: 10.2139/ssrn.2274710.

## Conference talks

- Beyond the Median: Asymmetric Volatility Transmission Between Cryptocurrencies and Financial Risk Indices: World Finance Conference 2026, University of Limerick, Ireland, July 2026.
- Evaluating Countries' Efficiency in the Global Trade Network: A Two-Stage SNA-DEA Approach: IFORS 2026, Vienna, Austria, July 2026.
- The Fossil-Fuel Dependency of the Green Transition: EcoMod 2026 – International Conference on Economic Modeling and Data Science, Luxembourg, July 2026.
- When Wars Move Markets: Hedging Properties of Asset Classes Across Recent Geopolitical Conflicts: ISAFE 2026, Beijing, China, June 2026.
- Hedging Geopolitical Risks with Different Asset Classes: A Comparative Analysis of the Ukrainian and Iranian Conflicts: Forecasting Financial Markets (FFM) 2026, Milan, Italy, June 2026.
- Early Warning Systems for Cryptocurrency Markets: Predicting 'Zombie' Assets Using Machine Learning: Frontiers in DeFi – Decentralized Finance, HTW Berlin, Berlin, Germany, May 2026. Related paper: https://barbbs.github.io/najef2025-zombies.html
- How to Detect Bubbles in Metals Prices?: IX Wrocław Conference in Finance (WROFIN), Wrocław, Poland, May 2026.
- When Markets Never Sleep: Intraday Liquidity Patterns and Volatility Effects in Cryptocurrency Trading: IX Wrocław Conference in Finance (WROFIN), Wrocław, Poland, May 2026. Related paper: https://barbbs.github.io/wp2026-neversleep.html
- Banking on the Green Transition: The Financialization of Tomorrow's Essential Metals: 34th Annual Conference of the Southern Africa Finance Association (SAFA), Cape Town, South Africa, January 2026. Related paper: https://barbbs.github.io/iaj2026-financialisation.html
- A Network Analysis of Success at the Eurovision Song Contest: ARS'25 – Tenth International Workshop on Social Network Analysis, Naples, Italy, October 2025.
- Banking on the Green Transition: The Financialization of Tomorrow's Essential Metals: 2nd Modern Finance Conference (MFC 2025), Warsaw, Poland, September 2025. Related paper: https://barbbs.github.io/iaj2026-financialisation.html
- When Markets Never Sleep: Intraday Liquidity Patterns and Volatility Effects in Cryptocurrency Trading: 2nd Modern Finance Conference (MFC 2025), Warsaw, Poland, September 2025. Related paper: https://barbbs.github.io/wp2026-neversleep.html
- Transmission Dynamics in Crypto Markets: Comparing Volatility and Liquidity Spillover Networks: Future Finance Fest (3F) Conference, Vilnius, Lithuania, August 2025. Related paper: https://barbbs.github.io/wp2025-transmission.html
- Is There an Impact of Ethereum Merge on the Relationship Between This Cryptocurrency and Energy Portfolios?: World Finance Conference 2025, Valletta, Malta, July 2025. Related paper: https://barbbs.github.io/wp2025-merge.html
- Transmission Dynamics in Crypto Markets: Comparing Volatility and Liquidity Spillover Networks: ISAFE 2025 – Third Annual Meeting of the International Society for the Advancement of Financial Economics, Beijing, China, June 2025. Related paper: https://barbbs.github.io/wp2025-transmission.html
- Tail Risk Spillovers Between Cryptocurrency and Traditional Financial Markets: A Quantile VAR Approach: 4th CINSC/INFINITI 2025 Conference on International Sustainable and Climate Finance and International Financial Integration, Edinburgh, United Kingdom, June 2025.
- Transmission Dynamics in Crypto Markets: Comparing Volatility and Liquidity Spillover Networks: 4th CINSC/INFINITI 2025 Conference on International Sustainable and Climate Finance and International Financial Integration, Edinburgh, United Kingdom, June 2025. Related paper: https://barbbs.github.io/wp2025-transmission.html
- Liquidity Measures for Cryptocurrency Markets: Traditional Estimators and Machine Learning Approaches: 4th Yushan Conference, Hsinchu, Taiwan, December 2024.
- Liquidity Measures for Cryptocurrency Markets: Traditional Estimators and Machine Learning Approaches: Annual Financial Market Liquidity Conference (AFML), Budapest, Hungary, November 2024.
- Is There an Impact of the Ethereum Merge on the Relationship Between Ethereum and Energy Portfolios?: 1st Modern Finance Conference, Warsaw, Poland, September 2024. Related paper: https://barbbs.github.io/wp2025-merge.html
- Interaction Effects in the Cross-Section of Cryptocurrency Returns: ISAFE 2024 – International Society for the Advancement of Financial Economics Conference, Pattaya, Thailand, July 2024. Related paper: https://barbbs.github.io/irfa2025-crosssectional.html
- Spillovers Between Risk Indices and the Cryptocurrency Market: EURO 2024 Conference, Technical University of Denmark, Copenhagen, Denmark, June 2024.
- A Network Analysis of Cryptocurrency Returns: Women in Fintech and AI 4, Rethymno, Crete, Greece, June 2024. Related paper: https://barbbs.github.io/nws2025-networks.html
- Editorial Boards of Finance Journals: The Gender Gap and Social Networks: Closing the Gender Gap in Kosovo, University of Prishtina and UN Women Kosovo, Prishtina, Kosovo, May 2024. Related paper: https://barbbs.github.io/jbe2025-editorialboards.html
- Do Uncertainty Indices Affect Cryptocurrency Uncertainty: A Lesson from Turbulent Times: Allied Social Science Associations (ASSA) Annual Meeting, San Antonio, TX, USA, January 2024. Related paper: https://barbbs.github.io/irfa2024-uncertainty.html
- Do Uncertainty Indices Affect Cryptocurrencies? Lesson from the Turbulent Times: CFE-CMStatistics 2023, Berlin, Germany, December 2023. Related paper: https://barbbs.github.io/irfa2024-uncertainty.html
- Is Bitcoin Dethroned Too Quickly? The Connectedness Between the Cryptocurrencies: 1st Elsevier Finance Conference at FGV EBAPE, Rio de Janeiro, Brazil, November 2023. Related paper: https://barbbs.github.io/nws2025-networks.html
- The Connectedness of Cryptocurrencies in the Context of Volatility and Liquidity: Annual Financial Market Liquidity Conference (AFML) 2023, Budapest, Hungary, November 2023.
- Editorial Boards of Finance Journals: The Gender Gap and Social Networks: Gender Equality and Women's Economic Empowerment Conference, International School of Economics at TSU (ISET), Tbilisi, Georgia, October 2023. Related paper: https://barbbs.github.io/jbe2025-editorialboards.html
- The Connectedness of Cryptocurrencies: IFORS 2023, Santiago, Chile, July 2023. Related paper: https://barbbs.github.io/nws2025-networks.html
- PoW vs PoS Coins as Possible Hedges Against Green and Dirty Energy: 2nd Conference on International Finance, Sustainable and Climate Finance and Growth (CINSC), Ljubljana, Slovenia, June 2023. Related paper: https://barbbs.github.io/eneco2024-powpos.html
- Do Uncertainty Indices Affect Cryptocurrencies? Lesson from the Turbulent Times: 2nd Conference on International Finance, Sustainable and Climate Finance and Growth (CINSC), Ljubljana, Slovenia, June 2023. Related paper: https://barbbs.github.io/irfa2024-uncertainty.html
- Woman Editors in Finance Journals: Women in Fintech III, COST Action CA19130, Coimbra, Portugal, June 2023. Related paper: https://barbbs.github.io/jbe2025-editorialboards.html
- Do Uncertainty Indices Affect Cryptocurrencies? Lesson from the Turbulent Times: Sopot Conference on Modelling Contemporary Economies (Modelowanie i prognozowanie gospodarki narodowej), Sopot, Poland, May 2023. Related paper: https://barbbs.github.io/irfa2024-uncertainty.html
- Zombies on the Cryptocurrency Market: COST Action CA19130 Conference, Brussels, Belgium, May 2023. Related paper: https://barbbs.github.io/najef2025-zombies.html
- PoW vs PoS Coins as Possible Hedges Against Green and Dirty Energy: 2nd Workshop on Environmental Finance for the Common Good – Diversity Challenges for Sustainable Fintech, COST Action CA19130, Pavia, Italy, April 2023. Related paper: https://barbbs.github.io/eneco2024-powpos.html
- Zombies on the Cryptocurrency Market: WROFIN Conference, Gola Dzierżoniowska, Poland, November 2022. Related paper: https://barbbs.github.io/najef2025-zombies.html
- Does Geopolitical Risk Influence the Cryptocurrency Market?: Annual Financial Market Liquidity Conference (AFML), Budapest, Hungary, November 2022.
- Has the Pandemic Changed the Relationship Between Banks and Fintechs?: COST Action CA19130 Working Group 3 Meeting, University of Utrecht, Netherlands, October 2022. Related paper: https://barbbs.github.io/ord2023-fintechbanks.html
- Editorial Boards of Finance Journals: Gender and Social Connectedness: Women in FinTech, COST Action CA19130 Conference, University of Tirana, Albania, September 2022. Related paper: https://barbbs.github.io/jbe2025-editorialboards.html
- Which Cryptocurrency Leads the Market? The Evidence from the Dynamic Networks: EURO 2022 Conference, Espoo, Finland, July 2022. Related paper: https://barbbs.github.io/nws2025-networks.html
- Dynamic Dependence and Volatility Spillovers on the Lithium and Oil Markets: Future Finance Conference, Naples, Italy, June 2022. Related paper: https://barbbs.github.io/resourpol2022-lithium.html
- Can Cryptocurrencies Hedge Oil Price Fluctuations? A Pandemic Perspective: Euro Working Group for Commodities and Financial Modelling & XIX International Conference on Finance and Banking (FIBA 2022), online, May 2022. Related paper: https://barbbs.github.io/eneco2022-oil.html