Browsing by Subject "Covid-19"

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Open Access
Covid-19 pandemic and tail-dependency networks of financial assets
(Elsevier, 2020-10) Le, T. H.; Do, H. X.; Nguyen, D. K.; Şensoy, Ahmet
This study provides evidence on the frequency-based dependency networks of various financial assets in the tails of return distributions given the extreme price movements under the exceptional circumstance of the Covid-19 pandemic, qualified by the IMF as the Great Lockdown. Our results from the quantile cross-spectral analysis and tail-dependency networks show increases in the network density in both lower and upper joint distributions of asset returns. Particularly, we observe an asymmetric impact of the Covid-19 because the left-tail dependencies become stronger and more prevalent than the right-tail dependencies. The cross-asset tail-dependency of equity, currency and commodity also increases considerably, especially in the left-tail, implying a higher degree of tail contagion effects. Meanwhile, Bitcoin and US Treasury bonds are disconnected from both tail-dependency networks, which suggests their safe-haven characteristics.
Open Access
Covid-19 pandemic merger wave
(2022-08) Ançel İlaslan, Zeynep
This thesis investigates whether the Covid-19 pandemic initiated merger waves at the aggregate and industry level. Recovery from the Covid-19 pandemic coincides with economic expansion, industry shocks and stock market boom, all potential triggers of restructuring activity. My sample covers 104,464 merger and acquisition deals of public and private US target firms from April 1, 2012, to March 31, 2022. In order to identify industry-level merger waves, I simulate the distribution of monthly deals. I then calculate the probability that the realized peak deal concentrations in any 24-month period are within the 95th percentile of the simulated distributions. I identify an industry as experiencing a merger wave if the realized deal concentration in any 24-month period is in the upper five percent of the simulated distribution of monthly deals. The method yields 37 industry-level merger waves between April 1, 2012, to March 31, 2022. 23 of these waves start during the Covid-19 pandemic period from January 1, 2020, to March 31, 2022. Deals in industry-level merger waves comprised around 80 percent of all deals in the Covid-19 pandemic period and formed an aggregate merger wave that started on April 1, 2020.
Open Access
Covid-19 SEIQR yayılım matematiksel modeli
(IEEE, 2021-07-19) Akman, Çağlar; Demir, Okan; Sönmez, Tolga
Bu bildiride Covid-19 salgınının nüfusta yayılımı EIQR matematiksel modeli ile formüle edilmiştir. Kesikli zamanlı yayılım modeli ile salgının bulaş hızı ve hasta tespit oranı kestirilmektedir. Kısıtlı optimal kontrol problemi olarak ifade edilen kestirim modeli Pontryagin minimum prensibi ile çözülmüştür. Yayılım ve kestirim modeli gerçek verilerin üzerinde test edilmiş, performans sonuçları sunulmuştur. Önerilen yöntemin başarılı bir şekilde salgın parametrelerinin kestirimini yaptığı gösterilmiştir.
Open Access
Development and preclinical evaluation of virus-like particle vaccine against COVID-19 infection
(Wiley-Blackwell Publishing Ltd., 2021-09-14) Yılmaz, İsmail Cem; İpekoğlu, E. M.; Bülbül, Artun; Turay, Nilsu; Yıldırım, Muzaffer; Evcili, İrem; Yılmaz, N. S.; Güvençli, N.; Aydın, Y.; Güngör, Bilgi; Saraydar, Berfu; Bartan, Aslı Gülce; İbibik, Bilgehan; Bildik, Tuğçe; Baydemir, İ.; Şanlı, H. A.; Kayaoğlu, B.; Ceylan, Yasemin; Yıldırım, Tuğçe; Abraş, İrem; Ayanoğlu, C.; Cam, S. B.; Dede, E. C.; Gizer, M.; Erganis, O.; Saraç, F.; Uzar, S.; Enul, H.; Adıay, C.; Aykut, Gamze; Polat, H.; Yıldırım, İ. S.; Tekin, S.; Körüklüoğlu, G.; Zeytin, H. E.; Korkusuz, P.; Gürsel, İhsan; Gürsel, M.
Background Vaccines that incorporate multiple SARS-CoV-2 antigens can further broaden the breadth of virus-specific cellular and humoral immunity. This study describes the development and immunogenicity of SARS-CoV-2 VLP vaccine that incorporates the four structural proteins of SARS-CoV-2. Methods VLPs were generated in transiently transfected HEK293 cells, purified by multimodal chromatography, and characterized by tunable-resistive pulse sensing, AFM, SEM, and TEM. Immunoblotting studies verified the protein identities of VLPs. Cellular and humoral immune responses of immunized animals demonstrated the immune potency of the formulated VLP vaccine. Results Transiently transfected HEK293 cells reproducibly generated vesicular VLPs that were similar in size to and expressing all four structural proteins of SARS-CoV-2. Alum adsorbed, K3-CpG ODN-adjuvanted VLPs elicited high titer anti-S, anti-RBD, anti-N IgG, triggered multifunctional Th1-biased T-cell responses, reduced virus load, and prevented lung pathology upon live virus challenge in vaccinated animals. Conclusion These data suggest that VLPs expressing all four structural protein antigens of SARS-CoV-2 are immunogenic and can protect animals from developing COVID-19 infection following vaccination.
Open Access
EU economic governance and Covid-19: policy learning and windows of opportunity
(Taylor and Francis, 2020) Ladia, S.; Tsarouhas, Dimitris
This article analyses the extent to which the Covid-19 pandemic crisis represents a window of opportunity towards fundamental change in the economic governance of the European Union (EU). Adopting a historical institutionalist (HI) perspective and drawing insights from the policy learning literature, we argue that contingent learning immediately took place and policy entrepreneurs took important decisions recognising the new crisis as an existential threat for the EU. Further, the pandemic crisis support fund and the ECB pandemic emergency purchase programme represent instances of single loop learning that leave the fundamentals of economic governance untouched. However, and in contrast to the Euro area crisis response, the adoption of the Recovery and Resilience Facility (RRF) represents a bold decision and suggests double-loop learning. It is argued that the Covid-19 crisis is a critical juncture for the EU. As a result, EU economic governance ceases to be limited to its regulatory function and is now complemented by a redistributive function as well.
Open Access
European closed-end fund discounts: effect of Covid-19
(2022-09) Çetin, Ferda
This thesis analyzes behavior of Closed-end fund discounts (CEF) under the novel circumstances of the global pandemic that crushed the financial markets starting from early 2020. As literature argues CEF discounts to be affected and explained by the investor sentiment, I expect discounts display the sentiment shifts in the market. Using the CEFs trading in European Exchange Markets, for the period of 2017-2021, I apply linear regression, and found that discounts significantly increase with risk factor (beta) and transaction costs proxy and decrease with dividend yield, turnover, size of the fund, and market returns including House Price Index, controlling for country and fund portfolio asset class focus fixed effects. Results of regression models indicate that CEF discounts widen after the first cases confirmed in the country, as Covid-19 pandemic create a negative shock on investor sentiment. The optimism in the market after the administration of vaccination started is also reflected through CEF discounts as they shrink with vaccination effect. Moreover, I find that new cases and new deaths of Covid-19 are significant predictors for CEF discounts, implying that investors are affected by the main Covid-19 related publicly available data.
Open Access
International trade and letters of credit: A double-edged sword in times of crises
(Palgrave Macmillan Ltd., 2022-01-05) Crozet, Matthieu; Demir, Banu; Javorcik, Beata
This study argues that the ability to mitigate risks associated with international trade is particularly important at times of heightened uncertainty, such as the economic crisis caused by the Covid-19 pandemic. Risk mitigation can be achieved through letters of credit (LCs), trade finance instruments providing guarantees to trading partners. As their use varies across products, exports of some products are more resilient than others during times of increased uncertainty. This situation reverses in times of financial crises when distressed banks may limit the supply of LCs. Our analysis using data on US and EU-15 exports during the Covid crisis and the Global Financial Crisis provides empirical support for these hypotheses. © 2021, International Monetary Fund.
Open Access
Jump forecasting in foreign exchange markets a high frequency analysis
(Wiley, 2023-01-30) Uzun, S.; Şensoy, Ahmet; Nguyen, D. K.
Using tick data for 14 emerging and developed market currencies covering the period from January 2018 until April 2021, we first detect jumps by Lee and Mykland methodology then apply various machine learning algorithms to forecast out of sample jump occurrences and their direction. Our results show that the arrival and the direction of intraday jumps in the foreign exchange market can be predicted with these algorithms combined with liquidity metrics and technical indicators, even for the Covid pandemic period where volatility in the foreign exchange market is very high. Among all the methods considered, multilayer perceptron has the highest average accuracy for jump prediction overall, followed by support vector machine and random forest methodologies with slightly less average accuracy results. Results are robust to alternative sampling schemes. Accordingly, central bankers can adjust liquidity injection timing with these jump prediction models in the foreign exchange markets where they can try to minimize jump strength if not completely eliminate its occurrence. For investors, having information regarding jump occurrence timings gives an opportunity to hedge against foreign exchange risks more efficiently.
Open Access
M&A activity during the COVID-19 pandemic
(Taylor&Francis, 2023-05-24) Ançel İlaslan, Z.; Tanyeri-Günsür, Başak
We investigate whether the COVID-19 pandemic initiated merger waves at the aggregate and industry levels. The COVID-19 pandemic coincides with economic shocks, wide adoption of new technologies, and volatility in stock and energy markets, all potential triggers of restructuring activity. Our sample covers 104,464 acquisition deals of US targets from 2012 to 2022. We identify 37 industry-level merger waves. Twenty-three merger waves start during the COVID-19 pandemic. Eighty percent of the deals during the pandemic were part of an industry merger wave. This concentration of industry waves drove an aggregate merger wave starting on April 2020.
Open Access
Regime type and data manipulation: evidence from the COVID-19 pandemic
(Duke University Press, 2024-12) Wigley, Simon
Context: This study examines whether autocratic governments are more likely than democratic governments to manipulate health data. The COVID-19 pandemic presents a unique opportunity for examining this question because of its global impact. Methods: Three distinct indicators of COVID-19 data manipulation were constructed for nearly all sovereign states. Each indicator was then regressed on democracy and controls for unintended misreporting. A machine learning approach was then used to determine whether any of the specific features of democracy are more predictive of manipulation. Findings: Democracy was found to be negatively associated with all three measures of manipulation, even after running a battery of robustness checks. Absence of opposition party autonomy and free and fair elections were found to be the most important predictors of deliberate undercounting. Conclusions: The manipulation of data in autocracies denies citizens the opportunity to protect themselves against health risks, hinders the ability of international organizations and donors to identify effective policies, and makes it difficult for scholars to assess the impact of political institutions on population health. These findings suggest that health advocates and scholars should use alternative methods to estimate health outcomes in countries where opposition parties lack autonomy or must participate in uncompetitive elections.