Research
Articles
Nagy, Olivér, & Neszveda, Gábor (2025). Assessing geopolitical risk: Sovereign CDS insights from the Russo-Ukrainian War Economic Analysis and Policy, 85, 1995-2006.
This study investigates how sovereign Credit Default Swaps’ (CDS) reactions reflect a country’s financial resilience to military conflicts, specifically analyzing the Russo-Ukrainian War. We find that sovereign CDS offers unique insights compare to equity markets. Sovereign CDS spreads had already started to increase at least two weeks before the outbreak of the war. Second, prior to the war, abnormal sovereign CDS spreads is correlated with financial vulnerability such as the Debt-to-GDP ratio, while after the outbreak of the war NATO membership and distance from Moscow become the significant predictor of abnormal sovereign CDS spreads indicating a shift in risk assessment dynamics towards geopolitical considerations. This divergence between equity market and sovereign CDS responses highlights their ability to capture different aspects of market sentiment and risk, underscoring the importance of sovereign CDS in evaluating the financial implications of geopolitical instability.
Our paper examines how the Russia–Ukraine war changed perceptions of country risk in 47 countries. Concerns about risk were already rising before the invasion, so some escalation was expected. Before the war, countries with more financial weaknesses appeared riskier. After the invasion, especially as it became clear the conflict would continue, geopolitical factors mattered more. Countries that were farther from Moscow and those in NATO were generally seen as more resilient. We argue that these reactions differed from those in stock markets, showing that the two markets capture different aspects of geopolitical risk.
@article{nagy2025geopolitical, author = {Nagy, Olivér and Neszveda, Gábor}, title = {Assessing geopolitical risk: Sovereign {CDS} insights from the {Russo-Ukrainian War}}, journaltitle = {Economic Analysis and Policy}, year = {2025}, volume = {85}, pages = {1995--2006}, doi = {10.1016/j.eap.2025.02.027} }Chen, Chaoyi, Barkó, Tamás, & Nagy, Olivér (2025). Inflation and uncertainty: Evidence from GARCH-MIDAS-in-Mean modelling Financial and Economic Review, 24(3), 52-72.
We revisit the relationship between inflation and inflation uncertainty using a novel GARCH-MIDAS-in-Mean approach, which allows for the decomposition of inflation uncertainty into short-term and time-varying long-term components.
We test our model on UK data. Our findings indicate that macroeconomic and financial variables significantly influence the long-term component of inflation uncertainty. By enabling long-term uncertainty to vary over time through MIDAS filtering, we show that the evidence for past inflation raising short-run uncertainty weakens compared to results that assume a constant long-term inflation uncertainty component. However, our results support the Cukierman–Meltzer hypothesis, indicating that the impact of inflation uncertainty on inflation becomes more robust and pronounced when longer samples are used, although this effect is sensitive to structural breaks, such as the VAT cut and the Covid-19 pandemic.
Additionally, we find no evidence that changes in inflation feed back into short-run uncertainty.
The paper asks a simple question: Does higher inflation make future inflation harder to predict, and does that uncertainty itself contribute to higher inflation?
Our main finding is that long-term uncertainty matters more than short-term volatility. Once we allow long-term uncertainty to change over time, there is little evidence that a rise in inflation by itself makes inflation significantly more unpredictable in the short run.
The practical message for central banks is therefore to focus less on reacting aggressively to every temporary price spike and more on keeping longer-term inflation expectations stable.
@article{chen2025inflation, author = {Chen, Chaoyi and Barkó, Tamás and Nagy, Olivér}, title = {Inflation and Uncertainty: Evidence from {GARCH-MIDAS-in-Mean} Modelling}, journaltitle = {Financial and Economic Review}, year = {2025}, volume = {24}, number = {3}, pages = {52--72}, doi = {10.33893/FER.24.3.52} }Granát, Marcell P., Lehmann, Kristóf, Nagy, Olivér, & Neszveda, Gábor (2023). Expect the unexpected: Did the equity markets anticipate the Russo-Ukrainian War? Finance Research Letters, 58, 104301.
In 2022, Russian military operations began in Ukraine, which surprised some, while others might have expected it. We investigate whether the expectations began to be priced in the equity markets before the operations. To estimate the start of information incorporation, we use the adjusted returns of 62 country-level stock market data assuming informed traders using a non-linear model and rolling-window regressions. We find that the equity markets started to price the conflict at least 50 days before the invasion, and approximately one-third of the information was incorporated on the event day.
@article{granat2023expect, author = {Granát, Marcell P. and Lehmann, Kristóf and Nagy, Olivér and Neszveda, Gábor}, title = {Expect the unexpected: Did the equity markets anticipate the {Russo-Ukrainian War}?}, journaltitle = {Finance Research Letters}, year = {2023}, volume = {58}, eid = {104301}, doi = {10.1016/j.frl.2023.104301} }Lehmann, Kristóf, Nagy, Olivér, Szalai, Zoltán, & H Váradi, Balázs (2020). Coordination (?) between the branches of economic policy across the euro area Financial and Economic Review, 19(1), 37-64.
In our study we present the coordination between the two main pillars of economic policy – monetary policy and fiscal policy – across the euro area. Growth in the euro area has noticeably decelerated in the past three decades, meaning the economy of the euro area has departed significantly from the logic of the Maastricht criteria. In addition, the lack of a common budget at euro area level and the fact that the oft-conflicting rules overlook sectoral interrelationships also point to the existence of a systemic problem. The difficulties have become increasingly evident in recent years as even the ultra-loose monetary policy has failed to stimulate economic growth significantly. This adverse process was intensified further by fiscal policy, which was intended to be consistent with the fiscal rules formulated in line with Maastricht criteria and can be considered tight, overall, at the euro area level. In recent months, even the policymakers of the European Central Bank have embarked on an open debate with regard to the role of policy branches. In the current political and legal framework, the ECB may be left with limited leeway for easing monetary conditions. In light of all these factors, there may be a need for a more active fiscal policy to stimulate the euro area economy, which, however, may sharpen the debate between the policymakers of individual Member States.
@article{lehmann2020coordination, author = {Lehmann, Kristóf and Nagy, Olivér and Szalai, Zoltán and {H Váradi}, Balázs}, title = {Coordination (?) between the Branches of Economic Policy across the Euro Area}, journaltitle = {Financial and Economic Review}, year = {2020}, volume = {19}, number = {1}, pages = {37--64}, doi = {10.33893/FER.19.1.3764} }Mérő, Balázs, Nagy, Olivér, & Neszveda, Gábor (2019). Testing new factors in empirical asset pricing Szigma, 50(4), 263-281. (In Hungarian).
@article{mero2019factors, author = {Mérő, Balázs and Nagy, Olivér and Neszveda, Gábor}, title = {Testing new factors in empirical asset pricing}, journaltitle = {Szigma}, year = {2019}, volume = {50}, number = {4}, pages = {263--281}, url = {https://journals.lib.pte.hu/index.php/szigma/article/view/3197/3001}, note = {In Hungarian} }
Book chapters
Chen, Chaoyi, Nagy, Olivér, & Neszveda, Gábor (2025). COVID-19 pandemic and stock volatility forecasts: A comprehensive evaluation and comparisons. In: Encyclopedia of monetary policy, financial markets and banking.
This study provides a comprehensive evaluation of stock return volatility forecasting using various GARCH-type models, analyzing their performance across the entire, pre-, during, and post-pandemic periods. We assess model performance using both the outperformance testing based on average results and winning ratios based on the best-performed frequency. Our overall findings reveal that no single model consistently outperforms others across all periods and forecasting horizons. Furthermore, we find that using winning frequency versus significance of outperformance leads to different conclusions. In terms of winning frequency, GARCH(1,1) consistently performs better than asymmetric GARCH models across both short-run and long-run horizons, particularly in the pre- and post-pandemic periods. However, based on the testing results, asymmetric GARCH models exhibit significant outperformance in pre- and post-pandemic periods.
@incollection{chen2025covid, author = {Chen, Chaoyi and Nagy, Olivér and Neszveda, Gábor}, title = {{COVID-19} Pandemic and Stock Volatility Forecasts: A Comprehensive Evaluation and Comparisons}, booktitle = {Encyclopedia of Monetary Policy, Financial Markets and Banking}, editor = {Apergis, Nicholas}, publisher = {Elsevier}, location = {Amsterdam}, year = {2025}, volume = {4}, pages = {62--78}, doi = {10.1016/B978-0-44-313776-1.00290-7} }