Unveiling trading patterns: iTraxx Europe financials from the great financial crisis to ECB monetary easing
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Author(s)Maria Alberta OliveiraLink to ORCID Index: https://orcid.org/0000-0003-2918-1354
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Carlos SantosLink to ORCID Index: https://orcid.org/0000-0002-5100-0794
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DOIhttp://dx.doi.org/10.21511/bbs.17(3).2022.16
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Article InfoVolume 17 2022, Issue #3, pp. 188-200
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- 449 Views
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139 Downloads
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Creative Commons Attribution 4.0 International License
Financial stability is a statutory concern of the European Central Bank. Spreads of bank credit default swaps (CDS) indices are a reference for financial stability, but the literature is scarce in this respect. This paper poses the novel research question of which characteristics of investors in these derivatives are implied by the volatility behavior of the returns of financial CDS indices. Daily spread returns for the 5-year maturity iTraxx Europe Financials (subordinated and senior), for the period between June 2004 and March 2015, are used to estimate a GJR-M model with Student t innovations, and two MGARCH models (one with constant and the other with dynamic conditional correlations). The results show that investors in the index referring to subordinated debt are risk averse (risk premium estimate of 0.688) and liable to leverage effects, while investors in the index for senior debt do not have such characteristics. The degrees of freedom of the Student t innovations are estimated to be 4 for both indices, implying that returns have distributions with very fat tails. Population excess kurtosis diverges to infinity. The results show that the conditional correlation between the indices is dynamic. Although correlations vary widely, most of that variation occurs before the Euro Area crisis. It is concluded that the inclusion of both indices in a portfolio would be misadvised for bear markets with distressed financial entities: the correlations are always positive, above 0.75 since 2010. Moreover, both indices prove to be sensitive to the varying surrounding conditions as investors share market sentiments.
Acknowledgments
NECE’s research is funded by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., Project UIDB/04630/2020
CEBER’s research is funded by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., Project UIDB/05037/2020
- Keywords
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JEL Classification (Paper profile tab)C58, E52, E58, G01, G21
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References45
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Tables1
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Figures2
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- Figure 1. Dynamic conditional correlations from MGARCH-DCC
- Figure 2. iTraxx Financials Europe spreads for subordinated and senior debt
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- Table 1. Estimation results for the GJR (1,1)_t-M model of the iTraxx returns
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The impact of the COVID-19 outbreak on the Indian stock market – A sectoral analysis
Rahul Kumar ,
Prince Bhatia ,
Deeksha Gupta
doi: http://dx.doi.org/10.21511/imfi.18(3).2021.28
Investment Management and Financial Innovations Volume 18, 2021 Issue #3 pp. 334-346 Views: 6776 Downloads: 3368 TO CITE АНОТАЦІЯThis paper aims to examine the impact of the COVID-19 outbreak on Indian firms listed on the NSE and analyze its impact on various sectors. In addition, a sub-sample analysis based on market capitalization was performed to understand the effect of size during extreme events. The sample consisted of 1,335 firms listed on the NSE India. A standard event study outlined by Brown and Warner (1985) was employed to analyze the price impact on the COVID-19 outbreak. The event windows from -10 days to +10 days were selected. The estimation window is 250 days. The Nifty 50 has been chosen as a proxy for market return. The sample firms witnessed a negative impact of the COVID-19 outbreak with a negative CAAR in different event windows. In addition, various sectors are classified according their responsiveness towards the COVID-19 outbreak into three groups: highly negatively affected, moderately negatively affected, and slightly negatively affected. The paper also points out that the pandemic substantially affects the above-median market capitalized firms than the below-median market capitalized firms, which contradicts the size effect phenomenon. The results assist shareholders in managing their portfolios and mitigate the systematic risk of their investments during extreme events such as a pandemic, wars, and others. This study is the first comprehensive analysis of the impact of the COVID-19 outbreak on different sectors in India. It is also the first study to investigate the size effect anomalies during extreme events.
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Justification of the list of indicators financial stability of the banking system
Nataliia Pohorelenko 
doi: http://dx.doi.org/10.21511/ed.17(3).2018.01
The generalization of scientific approaches to the assessment of the financial stability of the banking system has demonstrated the multivariance of views on structuring and listing of financial stability indicators and has made it possible to distinguish three main ones: on the basis of macroeconomic and macro financial indicators; on the basis of separate indicators; based on synthetic indicators. It is proved that the latter is most effective since the large number and variability of financial ratios used by different authors to assess the level of financial stability of banking systems does not allow for unambiguous results. A hierarchic structure of indicators of the stability of the banking system is proposed, which is characterized by the simultaneous existence of a certain number, not ordered in a heterarchic manner. In accordance with it, the integral index of financial stability of the banking system includes subindices: stability of the NBU, stability of system banks, banks with foreign capital, banks with private capital, financial vulnerability of the banking system. The expediency of accounting for the indicators of financial risk assessment: credit, liquidity risk, interest rate, investment risk, unstable resource base risk, which are characterized by such financial ratios as part of provisions for depreciation of loans in the loan portfolio, is justified in the composition of such a synthetic indicator of the financial stability of the banking system; the norm of instant liquidity; net interest margin; part of the provision for depreciation of securities in the securities portfolio; coefficient of instability of the resource base. Also, indicators for assessing the stability of the central bank were proposed: indicators of the adequacy of reserves; indicators of the effectiveness of monetary policy; indicators of the effectiveness of foreign exchange regulation; indicators of compliance of banking supervision with the main principles of efficiency. This approach will allow taking into account all the structural components of the banking system in the process of assessing financial stability, on the one hand, and in time to identify potential threats to the loss of stability, on the other.
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Investment motives and preferences – An empirical inquiry during COVID-19
K. Riyazahmed
doi: http://dx.doi.org/10.21511/imfi.18(2).2021.01
Investment Management and Financial Innovations Volume 18, 2021 Issue #2 pp. 1-11 Views: 1810 Downloads: 1861 TO CITE АНОТАЦІЯFollowing the COVID-19 breakout, investment in shares, mutual funds, and life insurance are witnessing a growing trend in India. Hence, examining the determinants of investor preferences is necessary to maintain a positive trend. This study analyzes the impact of investor motives and awareness on investor preferences using the data collected from 753 Indian investors in 2020. Factor analysis grouped the investment motives into six categories, namely Nature of investments, Future financial needs, Investor personal characteristics, Safety and stability of investments, Investor behavioral aspects, and Investor’s options. The regression model used to find the impact of the investment motives and the awareness on the investor preferences explains 52.3% of changes in investor preference. Investment factors like Nature of investments, Investor personal characteristics, Investor behavior, Investor options, Awareness of mutual funds, and shares have a significant impact on investor preferences. Further, the awareness level of mutual funds and the stock market are the major variables contributing to Investors’ preference rather than identified investment factors. Investors’ personal characteristics like knowledge, confidence, ability, responsibility, and belief negatively influence investor preferences. This study adds to the existing literature by analyzing investment motives and preferences during the pandemic.
