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La economía argentina se ha caracterizado históricamente por sucesivos periodos de inestabilidad reflejado en comportamiento volátiles de las principales variables macroeconómicas. Si bien esto ha generado numerosos inconvenientes en distintos aspectos, se destaca como una consecuencia positiva, el surgimiento de incipientes proyectos de inversión en cabeza de personas humanas, configurando el ecosistema de emprendedores de nuestra economía argentina. El objetivo de este artículo es analizar las principales alternativas disponibles en el mercado de capitales local para financiamiento de proyectos de inversión por parte de emprendedores, repasando las ventajas de dichas herramientas y los principales requisitos, como así también el rol dinamizador que cumplen las Sociedades de Garantía Recíproca. Argentine economic scenarios have historically been characterized by successive periods of instability reflected in volatile behavior of its main macroeconomic variables. Although this has generated numerous inconveniences in different aspects, a positive consequence has been the emergence of incipient investment projects headed by human beings or small companies, consequently enabling a positive development of the entrepreneurial ecosystem of our economy. The purpose of this article is to analyze the main alternatives available in our local capital market for entrepreneurs, investment projects financing while reviewing the advantages of such tools and its main operative requirements, including the dynamiting role played by Mutual Guarantee Companies. Padován, Alex. Universidad Nacional de Rosario. Facultad de Ciencias Económicas y Estadística. Rosario, Argentina

The aim of this study is to examine the relationship of consumer confidence indices representing investor sentiment with capital markets and the direction of this relationship in MIST (Mexico, Indonesia, South Korea and Turkey) countries. The period of 2010 June – 2020 February was considered. It has been concluded that there is a cointegration relationship between consumer confidence indices, indicator stock market indexes of countries and 10-year indicator bond interest rates in MIST countries with cointegration test. This finding shows that consumer confidence index and capital markets move together in the long run in MIST countries. When the short-term relationship between the variables is investigated, a significant short-term relationship is found between consumer confidence and capital markets in Indonesia and Turkey. The causality analysis indicates that the direction of these relations is from the consumer confidence index to the 10-year bond interest rates in Indonesia and Turkey; from consumer confidence index to stock market index in Mexico and Indonesia; In South Korea, it has been determined that the consumer confidence index is from the stock market index and from the stock market index to the consumer confidence index. It has been concluded that consumer confidence affects capital markets in MIST countries grouped among emerging economies., Bu çalışmanın amacı MIST (Meksika, Endonezya, Güney Kore ve Türkiye) ülkelerinde yatırımcı duyarlılığını temsil eden tüketici güven endekslerinin sermaye piyasaları ile ilişkisini ve bu ilişkinin yönünü incelemektir. Çalışmada 2010 Haziran – 2020 Şubat dönemi ele alınmıştır. Eş bütünleşme testi ile, MIST ülkelerinde tüketici güven endeksleri ile ülkelerin gösterge borsa endeksleri ve 10 yıllık gösterge tahvil faiz oranları arasında eş bütünleşme ilişkisinin olduğu sonucuna ulaşılmıştır. Elde edilen bu bulgu, MIST ülkelerinde tüketici güven endeksi ve sermaye piyasalarının uzun dönemde birlikte hareket ettiğini göstermektedir. Değişkenler arasındaki kısa dönemli ilişki araştırıldığında ise Endonezya ve Türkiye’de tüketici güveni ve sermaye piyasaları arasında anlamlı kısa dönemli ilişki tespit edilmiştir. Nedensellik analizi ise bu ilişkilerin yönünün Endonezya ve Türkiye’de tüketici güven endeksinden 10 yıllık tahvil faiz oranlarına; Meksika ve Endonezya’da tüketici güven endeksinden borsa endeksine; Güney Kore’de ise tüketici güven endeksinden borsa endeksine ve borsa endeksinden tüketici güven endeksine doğru olduğu belirlenmiştir. Yükselen ekonomiler arasında gruplandırılan MIST ülkelerinde tüketici güveninin sermaye piyasalarını etkilediği sonucuna ulaşılmıştır.

This paper examines the implicit impact of an individual company financial parameters on dividends payments. The empirical research is conducted within the environment that cross-examines fifteen European transition economies with shared traits of frontier to emerging capital markets development stage and exposure to exogenic global volatility from 2007/8 and Covid-19 economic crises spilling over at magnitude. The purpose of this paper is to test whether companies establish stable dividend policy. Dividends payments are sensitive to earnings and hence adjust imminently. The reason stems from uncertainty on future financial performance and on investor protection. Results yield negative link between solvency and dividends based on the fact that the weaker solvency position decreases the priority of dividends likelihood. Comparably dividends are less desirable if competing with company growth opportunities although investors are less willing to wait for future profits. Altogether transitioning markets are less responsive and structurally feature fewer corporate events.

We provide data for an empirical measure of metering problems, i.e., the difficulties of measuring productivity and rewards in firms. We build on the insight that these metering problems are reflected in the intensity with which firms apply Generally Accepted Accounting Principles when preparing their financial statements to capture economic transactions. We adapt a simple computational linguistics algorithm to identify textual patterns that uniquely signify heightened use of accounting measurement in preparation of accounting reports. The measure has been extensively validated and offers time-varying, firm-level scores of Accounting Measurement Intensity.

The role of liquidity in the banking industry is increasingly under the spotlight since the Global Financial Crisis (GFC) in 2007. Prior evidence offers contrasting findings on the role played by liquidity in banks: whilst it ensures systemic financial stability, at the same time it raises agency costs. Notwithstanding this, European banks benefited from a generous liquidity injection following the launch of the Quantitative Easing (QE) programme by the European Central Bank (ECB) in 2015–2016. We leverage on the release of the QE and investigate whether investors’ reactions to the announcements of new liquidity injections vary according to bank-level characteristics of the European banks: namely, their financial soundness, asset portfolio quality and the level of transparency. Our findings document an overall negative market reaction to the QE announcements; at a more fine-grained level of analysis we highlight that banks falling short of the regulatory requirements are not expected to benefit from additional liquidity. This study contributes to the literature on the role of liquidity in banks by showing important boundary conditions to the beneficial role of liquidity in banks, that is—because of the regulatory capital requirements—liquidity is only valuable to investors if it can be reinvested once constraints are overcome.

The article explores the key factors that make the securities criminal law of the United States (US), as one of the integral building blocks of the capital markets and securities regulatory system, efficient. This includes the role and characteristics of sectoral (blanket) all-embracing securities crimes enshrined into the federal securities statutes, their nexus with general crimes, the close cooperation of the Securities Exchange Commission (SEC) and prosecutorial offices, the applicable evidentiary standards, and the fundamental policies undergirding these laws. The rich repository of US experiences should be instructive not only to the Member States of the European Union (EU) striving to forge deeper capital markets but also to those endeavoring to accede the EU (e.g., Serbia), or to create deep capital markets for which efficient prosecution of securities crimes is inevitable.

Historically uncontrollably growing debt obligations of Latin American countries were the source of the risk of global crisis. Given the strategic importance of a number of Latin American countries as suppliers of key commodities to the global market, the issue of the region’s debt sustainability is of particular importance in international economic relations. The purpose of the article is to reveal the level and nature of debt risks of Latin American states based on an examination of trends of their development. The relationship between a high level of public debt and low rates of economic growth as a factor of investor distrust in the region’s debt obligations was revealed, which negatively affects the cost of raising borrowed capital. The factors of economic and political instability in Latin American countries were generalized, including the prerequisites for the formation of a new debt crisis due to the annual increase in the volume of borrowed funds, mainly to cover the chronically growing budget deficits of Latin American countries, which, against the background of large-scale systemic shocks, makes their economies increasingly vulnerable. It has been substantiated that exposure to debt risk negatively affects the effective functioning of the state apparatus of Latin American countries due to the tendencies of a multiple increase in budgetary expenditures for servicing and repaying public debt. The authors analyze practice of a number of Latin American countries to compensate for the increase in the cost of servicing debtobligations at the expense of funds provided for social security of citizens, which provokes an aggravation of conflicts in the region. The prospects of economic stabilization in the region were discussed in the context of changes in the current model of income generation, oriented to the export of raw materials.

Due to its very nature, globalization undermines the government control. This paper focuses on the impact of globalization on developed states. In particular, it analyzes how globalization has affected each of the following four institutions: (i) governance, (ii) capital markets, (iii) welfare state, and (iv) labor market. This can be summarized as follows: governments have become limited in their decision making, domestic capital markets have transformed into branches of the global market and thus have not been able to freely promote domestic interests, the welfare state serves capitalism rather than protects the society and reduces inequality, and the labor market experiences the migration of workers to developed states, whereas industries moved offshore to developing states. Ze względu na swój charakter globalizacja podważa kontrolę rządu. W artykule skupiono się na wpływie globalizacji na kraje rozwinięte. W szczególności analizuje, w jaki sposób globalizacja wpłynęła na każdą z czterech następujących instytucji: (i) zarządzanie, (ii) rynki kapitałowe, (iii) państwo opiekuńcze oraz (iv) rynek pracy. Można to podsumować następująco: rządy ograniczyły się w podejmowaniu decyzji, krajowe rynki kapitałowe przekształciły się w gałęzie rynku globalnego i tym samym nie były w stanie swobodnie promować interesów wewnętrznych, państwo opiekuńcze służy raczej kapitalizmowi niż chroni społeczeństwo i zmniejsza nierówności, a rynek pracy doświadcza migracji pracowników do krajów rozwiniętych, podczas gdy branże przeniosły się za granicę do krajów rozwijających się.

RESUMEN. El presente artículo busca analizar el concepto de 'valor' desde una perspectiva de derecho comparado. Con dicho objetivo, el análisis propone una evaluación de la regulación estadounidense sobre el concepto de 'valor', así como un estudio de la misma idea en el derecho colombiano, todo con miras a analizar los posibles aprendizajes que, desde la experiencia extranjera pueden hacerse en la regulación colombiana en esta materia. ABSTRACT. This article aims to assess the securities notion from a comparative law point of view. It proposes an assessment over the U. S. securities regulation, as well as an evaluation of such regulation within the Colombian rules. With that aim, the article seeks to identify the possible lessons to learn from the foreign securities regulations, specifically, within the Colombian securities market regulation.

Purpose – The Brazilian government approved regulations to foster the corporate bond market. In 2009, Instruction 476 of the Comissão de Valores Mobiliários (the Brazilian capital market regulator) relaxed the requirements for issuing bonds. In 2011, Law 12,431 created infrastructure bonds, which give individuals tax exemptions. Since then, aggregate proceeds have more than tripled. We describe the Brazilian bond market and the characteristics of issues and issuers; and critically evaluate this evolution. Design/methodology/approach – Descriptive analysis. Data on aggregate issuances; bond characteristics (proceeds, maturity, yields, underwriting); issuer characteristics; secondary market (trading); performance (default and renegotiation rates); and allocation of issues. Findings – Bond issues are small and bonds present a short maturity. International agencies are the main ratings providers, using a Brazilian-adjusted rating scale. Fixed-yield bonds are rare. The vast majority of regular bonds are linked to the interbank offered interest rate (DI or CDI). Only two local universal banks dominate the underwriting activity. These banks and their related parties receive more than half of the aggregate allocation. Less than half of issues have an investment grade, and more than half are not rated at all. The incidence of ex-post credit events is most frequently in the form of renegotiations of bond terms. Strict defaults are also high. Liquidity for bonds in the secondary market is low. Originality/value – To our knowledge, this is the first article to describe the microstructure of the Brazilian bond market. Objetivo – O governo brasileiro aprovou regulamentos para promover o mercado de títulos privados. Em 2009, a Instrução 476 da Comissão de Valores Mobiliários relaxou as exigências para a emissão de títulos. Em 2011, a Lei 12.431 criou os títulos de infraestrutura, que permitem a isenção de impostos para pessoas físicas. Desde então, os proventos totais mais que triplicaram. Descrevemos a evolução do mercado de títulos brasileiro, as características das emissões e os emitentes, e avaliamos essa evolução de maneira crítica. Metodologia – Análise descritiva. Dados sobre o total de emissões; características dos títulos (proventos, vencimentos, rendimentos, subscrição); características dos emitentes; mercado secundário (negociação); desempenho (taxas de inadimplência e renegociação); e problemas de colocação. Resultados – As emissões de títulos são pequenas e apresentam vencimento no curto prazo. As agências internacionais são as principais fornecedoras de classificação de risco, utilizando uma escala de classificação ajustada ao Brasil. Os títulos de renda fixa são raros. A grande maioria dos títulos regulares está atrelada à taxa de juros interbancária (DI ou CDI). Apenas dois bancos universais locais dominam a atividade de subscrição. Esses bancos e suas partes relacionadas recebem mais da metade da alocação total. Menos da metade das emissões recebeu a classificação de grau de investimento e mais da metade sequer possui classificação. A incidência de eventos de crédito ex-post, mais frequentemente na forma de renegociação dos prazos dos títulos. A inadimplência estrita também é alta. A liquidez dos títulos no mercado secundário é baixa. Contribuições – Até onde sabemos, este é o primeiro artigo que descreve a microestrutura do mercado de títulos brasileiro. Objetivo – O governo brasileiro aprovou regulamentos para promover o mercado de títulos privados. Em 2009, a Instrução 476 da Comissão de Valores Mobiliários relaxou as exigências para a emissão de títulos. Em 2011, a Lei 12.431 criou os títulos de infraestrutura, que permitem a isenção de impostos para pessoas físicas. Desde então, os proventos totais mais que triplicaram. Descrevemos a evolução do mercado de títulos brasileiro, as características das emissões e os emitentes, e avaliamos essa evolução de maneira crítica. Metodologia – Análise descritiva. Dados sobre o total de emissões; características dos títulos (proventos, vencimentos, rendimentos, subscrição); características dos emitentes; mercado secundário (negociação); desempenho (taxas de inadimplência e renegociação); e problemas de colocação. Resultados – As emissões de títulos são pequenas e apresentam vencimento no curto prazo. As agências internacionais são as principais fornecedoras de classificação de risco, utilizando uma escala de classificação ajustada ao Brasil. Os títulos de renda fixa são raros. A grande maioria dos títulos regulares está atrelada à taxa de juros interbancária (DI ou CDI). Apenas dois bancos universais locais dominam a atividade de subscrição. Esses bancos e suas partes relacionadas recebem mais da metade da alocação total. Menos da metade das emissões recebeu a classificação de grau de investimento e mais da metade sequer possui classificação. A incidência de eventos de crédito ex-post, mais frequentemente na forma de renegociação dos prazos dos títulos. A inadimplência estrita também é alta. A liquidez dos títulos no mercado secundário é baixa. Contribuições – Até onde sabemos, este é o primeiro artigo que descreve a microestrutura do mercado de títulos brasileiro.

Aim/purpose – The aim of the paper is to compare and create a ranking of alternative trading systems and to investigate if there is a relationship between Gross Domestic Product (GDP) and stock indices of those markets and correlation between GDP and turnover value. Design/methodology/approach – The paper presents a comparative analysis of 13 European trading systems in such categories as: capitalisation, value of share trading, number of listed companies, number of new companies and companies removed from the market between the years 2016 and 2018. In addition, the paper includes a ranking of alternative trading systems in Europe which was created on the basis of the variables mentioned. The paper examines the correlation between GDP and indices of alternative trading systems and also between GDP and turnover value. Pearson’s correlation coefficient was used to examine the correlation. Findings – The ranking shows that the 1st place was taken by the British AIM market, which turned out to be the best in all categories under the comparison, the next two positions were occupied by the markets whose characteristic feature is that they cover several countries of the western Europe; these are the markets of First North and Alternext. The Polish market was at a fairly high 5th position among the 13 compared markets. The Greek and Russian markets came last. The relationship between the impact of GDP and index value as well as GDP and turnover value has also been examined. The research regarding the first aspect of the study confirmed the hypothesis about the correlation of GDP with the index. However, in the second case of the GDP and turnover value there is a very weak correlation. Research implications/limitations – The limitation in the correlation study was the difficulty in obtaining data for all 13 alternative trading systems taken for the study, thus comparing four markets in the GDP correlation and the value of the index and three markets in the relation GDP and turnover value. Originality/value/contribution – The added value of the paper is the ranking of alternative trading systems and study of correlations between Gross Domestic Product and stock indices of Alternative Trading Systems and turnover value of these markets.

This paper assesses the extent to which carry trade operations affect the performance of equity and bond markets in a target country, South Africa, by considering the US and the euro area as the funding countries. A two- and three-factor capital asset pricing model (CAPM) is employed to assess whether the pricing of equity and bond markets in South Africa depends on the US dollar/rand and euro/rand carry trade returns. Moreover, the paper uses the quantile regression technique to assess whether this pricing varies with the distribution of the equity and bond returns. The findings support that the US- and euro-funded carry trade are essential factors for the pricing of equity and bond markets in South Africa. Moreover, the results of the two-factor model show a negative relationship between the equity excess return and the US-carry trade returns at lower quantiles of the equity market returns. The positive relationship is observed in the upper quantiles of the equity market. The negative relationship means that carry trade activities reduce equity market returns during a bear market as investors close out their position when conditions in the equity market become unfavourable. The results of the three-factor model, controlling for the global volatility or uncertainty, show that carry trade investors exit the equity market to invest in the bond market when global uncertainty rises. This finding shows that carry trade investors choose less risky assets during rising global uncertainty.

During the past 20 years, due to climate change, the government and the private sector have significantly focused on relying on non-fossil fuel-based methods for their energy needs. Climate change-related events, such as unusual weather conditions, abnormal temperature spikes, etc., have an adverse influence on clean energy-based investments. In the given study, we intend to focus on how an incremental temperature rise could affect investors’ perceptions of clean energy assets. To understand the investor-based sentiment on climate change, we utilize prominent clean energy ETFs (exchange traded funds) and consider the temperature’s effect on them. The daily average temperatures of the three most dynamic international financial centers: New York, London and Tokyo, are taken as predictors. Deep learning-based neural networks are applied to understand both the linear and non-linear relationships between the desired variables and identify the causal effects. The results indicate that in almost all the cases with desired lags, there is some sort of non-linear causality, irrespective of linear causality effects. We hope this occurrence can help portfolio managers and environmental professionals in identifying novel climate change-related factors when considering the temperature-related risks.

More voices are calling for a quicker transition towards clean energy. The exploration and exploitation of clean energy such as wind energy and solar energy are effective means to optimise energy structure and improve energy efficiency. To provide in-depth understanding of clean energy transition, this paper utilises a combination of multiple bibliometric mapping techniques, including HistCite, CiteSpace and R Bibliometrix, to conduct a systematic review on 2,191 clean energy related articles obtained from Web of Science (WoS). We identify five current main research streams in the clean energy field, including Energy Transition, Clean Energy and Carbon Emission Policy, Impact of Oil Price on Alternative Energy Stocks, Clean Energy and Economics, and Venture Capital Investments in Clean Energy. Clearly, the effectiveness of policy-driven and market-driven energy transition is an important ongoing debate. Emerging research topics are also discussed and classified into six areas: Clean Energy Conversion Technology and Biomass Energy Utilisation, Optimisation of Energy Generation Technology, Policy-Making in Clean Energy Transition, Impact of Clean Energy Use and Economic Development on Carbon Emissions, Household Use of Clean Energy, and Clean Energy Stock Markets. Accordingly, more and more research attention has been paid to how to improve energy efficiency through advanced clean energy technology, and how to make targeted policies for clean energy transition and energy market development. This article moves beyond the traditional literature review methods and delineates a systematic research agenda for clean energy research, providing research directions for achieving low-carbon development through the clean energy transition.

Capital market is one of the wheels of the economy of a country, the function represented is as a means of business funding and as a means for companies to get funds from the financier community to develop businesses and increase working capital. It is undeniable that the COVID-19 pandemic is a major obstacle to economic activity in Indonesia. The investment sector also did not escape the adverse effects caused by this pandemic. The presence of Omnibus Law Create Jobs and discourse Omnibus Law Financial Sector becomes an expectation as an acceleration to the economy of the capital market sector in Indonesia. The method used in this writing is normative research method with statue approach and case study approach, as well as trace of legal materials related to capital market and investment in Indonesia which are analyzed qualitatively based on cases raised today in Indonesia. The results showed the existence of Omnibus Law in the Covid-19 period is now a strong legal basis in increasing investment so that it can compete at the ASEAN level. Furthermore, in order to strengthen the financial sector, in economic financing in Indonesia, omnibus law needs to be drafted as a strengthening of coordination and structuring of authority between institutions, including the establishment of an integrated banking supervision forum, structuring the authority of Bank Indonesia, the Financial Services Authority, the Deposit Insurance Agency in order to refresh the capital market climate and accelerate the economy in Indonesia

Research Question: One of the aims of this paper is to examine accounting conservatism using a robust set of data collected from the recent years to better understand how accounting conservatism affects the relations between stock returns and accounting variables. Motivation: Financial reporting is increasingly dependent on an in-depth understanding of the imperfections in the capital markets as well as the impact of the accounting standards on firm performance. Idea: The effect of accounting regulations on the firms’ reporting practices can be evaluated via a firm’s change in cash investments and its operating assets. Data: This study employs a robust set of data with different market to book ratios and corporate governance characteristics collected from Compustat North America Fundamentals Annual firm year observations for the time period of January 1998 to December 2015 fiscal years to better understand how accounting conservatism affects the relations between stock returns and accounting variables. Tools: Compared to the previous studies, any potential improvement in the research method is provided using a regression weight averaged over the years. Findings: There is an improvement in the explanatory power of the estimates of the coefficients on earnings levels and earnings changes when the variables associated with accounting conservatism are incorporated in the analysis. Contribution: Given the ample amount of research done in the international aspects of financial reporting, analyses of differences in results compared to the previous studies and future research opportunities will be provided.

Buy cheap and sell more expensive. This is the main principle to make a profit on capital markets for hundreds of years. The rule is simple but to apply it in practice has become a very difficult task nowadays, with very high price volatility in the financial markets. Once electronic trading was widespread released, reliable solutions can be found using algorithmic trading systems. This paper presents a data mining method applied to the time price series in order to generate buy and sell decisions using computational algorithms. It was found that an original data mining method based on the price cyclicality function gives us an important profit edge when it is about the capital investments on the short and medium term. The Cyclical Trading Method will be presented together with the main principles and practices to design and optimize trading software. Test results are also included in this article in order to compare the presented method with other known methodologies to trade the capital markets.

Buy cheap and sell more expensive is one of the basic ideas of trading the capital markets for hundreds of years. To apply it in practice has become difficult nowadays due to the high price volatility. The uncertainty in the price movements often leads to high-risk allocation. One main question is when the price is low enough for a low-risk entry? Once established an entry point, the second question is how long to keep the open trades in order to optimize the investment efficiency? This article will answer these questions. A general trading algorithm based on the price cyclical behavior will be revealed. The mathematical model is developed using the Price Cyclicality Function combined with other computational techniques in order to establish low-risk intervals. The algorithm will use multiple entry points in order to catch the best price opportunities. A simple empirical exit algorithm will be optimized in order to maximize the profit for a certain capital exposure level. The presented model uses a low number of functional parameters which can be optimized with a reasonable computational effort for any financial market. Trading results obtained for several markets will also be included in this paper in order to reveal the efficiency of the presented methodology. It was found that the Low-Risk Trading Algorithm can be used with good results for algorithmic trading in any financial market. With the right parameters set, this methodology can be wide range applied in the stock markets, currency and cryptocurrency markets, commodities and raw materials markets and even for the real estate investments. The simplicity of the presented model and the good efficiency level obtained will recommend it. This methodology can be used by any investor in order to manage the investment plan with multiple capital markets.

This study aims to determine the significant abnormal returns before and after the opening of the 2018 Asian Games in the stock of the Consumer Good Industry sector on the Indonesia Stock Exchange. The population in this study is the Good Industry Consumer sub-sector company on the Indonesia Stock Exchange. Determination of the sample using non-probability method with purposive sampling technique and obtained as many as 29 companies as samples in this study. Data were analyzed using one sample t-test and paired sample t-test. The results showed that there was a market reaction at t-4 and t-5, but it was suspected that there was information leakage indicated by the significance value at t-4 and t-5. The results of this study also indicate that there are significant differences before and after the opening of the 2018 Asian Games.

Using the equity market liberalization of 23 emerging market countries between 1996 and 2006, we examine how the degree of competition for a firm's shares affects the price of information asymmetry. We find evidence of a significant decline in the pricing of information asymmetry as countries remove regulatory restrictions on foreign ownership. Our study provides novel evidence on the link between the degree of competitiveness of equity markets and the price of information asymmetry. The work also furthers our understanding of the economic consequences of foreign stock ownership.

Investing in capital markets is a common task today. An impressive number of traders and investors, companies, private or public funds are buying and selling every day on the free markets. The current high price volatility in the financial markets gives everyone a tremendous number of speculative opportunities to make a profit. Sometimes the price makes no significant movement, however. The majority of the trades initiated in those periods will conclude to losses or will need a very long time to become profitable. To avoid these cases, a mathematical algorithm was developed in this paper: The Silent Market Indicator. This article will present the general principles and the mathematics behind the indicator and how it can be applied in financial trading to improve capital investment efficiency. It was found that the model generates a very reliable filter to avoid entry into the silent markets intervals, when the price action conducts to small amplitude price movements and when the profit expectation is lower. In order to reveal the efficiency of the Silent Market Indicator usage, some comparable trading results will be presented in the last part of this article together with the functional parameters optimized for several known capital markets. As a conclusion, it will be proved that the presented methodology is an excellent method to stay away from the market risk. In addition, being exclusively a mathematical model, it can be applied in any algorithmic trading system, combined with any other trading strategy in order to improve capital efficiency

This study investigates the reaction of stock markets to the Covid-19 pandemic and the Global Financial Crisis of 2008 (GFC) and compares their influence in terms of risk exposures. The empirical investigation is conducted using the modified ICSS test, DCC-GARCH, and Diebold-Yilmaz connectedness analysis to examine financial contagion and volatility spillovers. To further reveal the impact of these two crises, the statistical features of tranquil and crisis periods under different time intervals are also compared. The test results show that although the outbreak’s origin was in China, the US stock market is the source of financial contagion and volatility spillovers during the pandemic, just as it was during the GFC. The propagation of shocks is considerably higher between developed economies compared to emerging markets. Additionally, the results show that the COVID-19 pandemic induced a more severe contagious effect and risk transmission than the GFC. The study provides an extensive examination of the COVID-19 pandemic and the GFC in terms of financial contagion and volatility spillovers. The results suggest the presence of strong co-movements of world stock markets with the US equity market, especially in periods of financial turmoil.

We examine how the offer size of initial public offerings (IPOs) and the market return on their issue date are related to the pricing of 314 IPOs issued by firms in Denmark, Finland, Norway and Sweden at the one-day, one-week and four-week horizons using latent class analysis, which is a structural equation methodology. We identify four latent classes at each time horizon, where classes (i)-(ii) include a greater number of IPOs: (i) large-sized and underpriced IPOs; (ii) small-sized and overpriced IPOs; (iii) small-sized and severely underpriced IPOs; and (iv) large-sized IPOs that are overpriced at the one-day horizon but underpriced at the four-week horizon. The market returns are normal in latent classes (i)-(iii) and weak in class (iv). Approximately half of the IPOs in the technology sector are in the latent class with small-sized and overpriced IPOs, and most of the IPOs in the class with small-sized and severely underpriced IPOs are in the healthcare sector. Finally, the underpricing of IPOs is not corrected after one or four weeks of trading. Instead, the mean return and the standard deviation of returns increase with the time horizon.

With the development of ecological paradigm coupled with the relentless implementation of myriad environmental policies in China, the rapid development of carbon emission trading and carbon trading market has had a vital impact on the financial performance of enterprises at the microlevel. This study has sampled the A-share listed companies in China, from 2009 to 2018, and adopted the difference-in-difference (DID) method to investigate the effect of the carbon emission trading on corporate financial performance from the microlevel. Evidence showed that the implementation of carbon emission trading effectively improved the total asset-liability ratio of enterprises, though it reduced the value of the current capital market. Moreover, in the regions under strict legal environment, the enhancement effect of the total asset-liability ratio was more obvious, whereas in the regions under loose legal environment, the reduction effect of the value of the capital market was more obvious. Further analysis showed that the implementation of carbon emission trading could not promote Chinese enterprises to increase R&D investment. Hence the implementation of carbon emission trading has improved the level of non-business income of enterprises incorporated into the trading system, but its impact on the investment income of enterprises was not significant.

Research background: Financial globalization has opened international capital markets to investors and companies worldwide. However, the global financial crisis has created big volatility in the stock prices that induces a restriction in the reflection of full information. We explore ten EU Member States (France, Germany, The United Kingdom, Belgium, Bulgaria, Romania, Greece, Portugal, Ireland, Spain), and the USA. The explored period is 03.03.2003 - 30.06.2016, as it includes the effects of the global financial crisis of 2008. Purpose of the article: To determine if there is a contagion effect between the Bulgarian stock market and the other examined stock markets during the crisis period and whether these markets are efficient. Methods: Argument Dickey-Fuller Test, DCC-GARCH Model, Autoregressive (AR) Models, TGARCH Model, Descriptive Statistics. Findings & Value added: Our results show that a contagion across the Bulgarian capital market and eight capital markets exist during the global financial crisis of 2008. We register the strongest contagion effects from US and German capital markets to the Bulgarian capital market. The Bulgarian capital market is relatively integrated with the stock markets of Germany and the United States. That is the explanation of why the Bulgarian capital market is exposed to financial contagion effects from the US capital market and the capital markets of EU member states during the crisis period. We register statistically significant AR (1) for the UK, Greece, Ireland, Portugal, Romania, and Bulgaria, and we can define these global capital markets as inefficient.

In five experiments (N = 3,828), we investigate whether people prefer investment decisions to be made by human investment managers rather than by algorithms (“robos”). In all of the studies we investigate morally controversial companies, as it is plausible that a preference for humans as investment managers becomes exacerbated in areas where machines are less competent, such as morality. In Study 1, participants rated the permissibility of an algorithm to autonomously exclude morally controversial stocks from investment portfolios as lower than if a human fund manager did the same; this finding was not different if participants were informed that such exclusions might be financially disadvantageous for them. In Study 2, we show that this robo-investment aversion manifests itself both when considering investment in controversial and non-controversial industries. In Study 3, our findings show that robo-investment aversion is also present when algorithms are given the autonomy to increase investment in controversial stocks. In Studies 4 and 5, we investigate choices between actual humans and an algorithm. In Study 4 –which was incentivized–participants show no robo-investment aversion, but are significantly less likely to choose machines as investment managers for controversial stocks. In contrast, in Study 5 robo-investment aversion is present, but it is not different across controversial and non-controversial stocks. Overall, our findings show a considerable mean effect size for robo-investment aversion (d = –0.39 [–0.45, –0.32]). This suggests that algorithm aversion extends to the financial realm, supporting the existence of a barrier for the adoption of innovative financial technologies (FinTech)., PLoS ONE, 15 (9), ISSN:1932-6203

This study tests the weak form of the efficient capital markets theorem in five transition economies in Southeast Europe between 2005 and 2016. A panel pooled mean group estimator is used to examine the relationship between macroeconomic indicators and the performance of stock market indexes. This is a suitable estimator for these young frontier markets, given that they have yet to develop the breadth and depth of an advanced market—such as ample liquidity and traders—to aggregate cross-country data and use level series prime data instead of differentials of the same. These frontier capital markets are found to be weak form inefficient, meaning that stock prices do not reflect available current public information. In other words, when a market is transparent and investor behavior is rational, the macroeconomic data should be included in the value of the stock indexes. The five countries may benefit from bringing their capital markets legislation in line with those of developed countries and by improving corporate governance and transparency. This would boost investor trust and liquidity. The coverage of this research can be extended to find more standardized data values and develop additional factors not captured by this model.

With the development of recent years, the field of deep learning has made great progress. Compared with the traditional machine learning algorithm, deep learning can better find the rules in the data and achieve better fitting effect. In this paper, we propose a hybrid stock forecasting model based on Feature Selection, Convolutional Neural Network and Bidirectional Gated Recurrent Unit (FS-CNN-BGRU). Feature Selection (FS) can select the data with better performance for the results as the input data after data normalization. Convolutional Neural Network (CNN) is responsible for feature extraction. It can extract the local features of the data, pay attention to more local information, and reduce the amount of calculation. The Bidirectional Gated Recurrent Unit (BGRU) can process the data with time series, so that it can have better performance for the data with time series attributes. In the experiment, we used single CNN, LSTM and GRU models and mixed models CNN-LSTM, CNN-GRU and FS-CNN-BGRU (the model used in this manuscript). The results show that the performance of the hybrid model (FS-CNN-BGRU) is better than other single models, which has a certain reference value.

This study presents a field experiment we conducted in which media articles for a random sample of firms with earnings announcements are promoted to a one percent subset of Yahoo Finance users. The promoted firms have similar fundamental and earnings-news characteristics as control firms, yet we find that promoted firms have higher abnormal returns on the day of the earnings announcement, and some evidence of lower bid-ask spreads. Moreover, these results are more pronounced for less visible firms, negative earnings news, and on days with fewer promoted firms. We do not find evidence of significant increases in trading volume, or of information acquisition by users subject to the promotion. These findings suggest that investor attention affects the pricing of earnings and that retail investors buy stocks that catch their attention, in a setting where attention is randomly assigned.

Nowadays, the capital markets have an increasing role and weight in the modern financial systems. Economic (and financial) integration should allow companies to access more sophisticated and competitive capital markets for accelerating the economic development. The purpose of this paper is to investigate the impact of the capital markets’ integration on economic growth in the EU countries and identify the main factors through which capital markets’ development influences economic growth, especially in an economic (and monetary) union. In this article we had used the Autoregressive Distributed Lag model for the EU countries during 2004-2016. According to the results, we can say that the integration of capital markets has a positive impact on economic growth, and the main factors in which the capital market positively affects economic growth are stock market capitalization, capital mobility, value traded, stock indices, immigrants, and, to a greater extent, small, foreign portfolio investment. Policymakers in this area should pay attention reducing external debt, which is a significant proportion of foreign capital inflows, and encouraging the foreign portfolio investments to stimulate stock market development and growth, reducing extreme stock price volatility, fostering a good correlation of savings with investment (i.e. capital mobility), boosting volume growth transactions on stock markets, they should guarantee full employment through fiscal policy, monetary policy and trade policy as stated, by counteracting private sector or trade investment volatility, and reducing inequality, and stimulating increased labor mobility from developed countries to the least developed to balance the economy.

Since the 1970s, the world has embarked on a new financial globalization era. Cross-country capital flows have significantly increased in developed and developing countries. However, the characteristics of financial globalization differ from what was originally expected. Various examples illustrate this point. Although the literature predicted large gains from financial globalization (such as additional funding, broad diversification, and deeper financial systems), the positive effects have been more limited. In developed and developing countries, financial globalization has manifested in increasing gross capital flows (inflows and outflows) rather than larger net flows. Capital markets are segmented and only a few large firms access international markets. International institutional investors do not seem to have played a stabilizing role, helping to exacerbate and transmit crises across countries. Although financial globalization has brought several beneficial changes, its net effects and spillovers to the overall economies participating in it have yet to be understood.

This article investigates the activities of noblemen on the annuity market of the city of Antwerp at the end of the fifteenth century. In postwar historiography, the consumption of credit by noblemen was often considered as an indication that those noblemen were in dire straits, whereas more recent interpretations suggest that noblemen were important creditors to both princes and towns. The analysis of the activities of twenty-eight noble lineages on the Antwerp credit market reveals that noblemen appear more often as buyers than as sellers of credit, but also that they were considered creditworthy, and that noblemen were careful to avoid using estates that were important for the family’s noble status as collateral. The nobility's annuity traffic cannot be understood from a one-sided perspective, such as that of the overarching grand narrative of the perpetual crisis of the pre-modern nobility, or that of the nobleman-banker.

We developed a dual-reputational rating shopping model to introduce public and institutional reputations. Investor’s and regulator’s penalty rates are described as public and institutional reputations, respectively. We achieved the available conditions of single-rating and dual-rating regulations to prevent rating inflation in this model. To examine the regulatory effects of different types of regulations on Chinese corporate bond ratings, we utilize panel ordered logit models. Theoretical analysis and empirical tests show that, when the reputation effect is low, the single-rating regulation is better at improving rating quality, and when the reputation effect is high, the dual-rating regulation induces rating agencies to provide more accurate ratings. Compared to the regulatory effects of the single-rating and the multi-rating regulations, the dual-rating regulation most effectively improves the rating quality of corporate bonds and prevents rating inflation.

Using a sample of all U.S. firms listed on the U.S. major stock exchanges for the period covering 1988 through 2014, we investigate the relation between firm earnings components and matching. Following the methodology of Hui et al. (2016), we decompose earnings into industry-wide and firm-specific earnings. Then, we partition them into cash flows and accruals, four earnings components. As our matching measure, we use the correlation between revenues and expenses over the five-year rolling period. We investigate how matching affects the persistence of each earnings component and our results indicate that matching enhances the persistence of earnings components. Furthermore, our study shows that the effect is more outstanding on firm-specific accruals, which are more prone to the management discretion, than cash flows.

There are two different concepts of corporate reputation grounded in individual and collective perceptions, respectively. The aim of this study was to identify how these two ways of conceiving of corporate reputation affect investors’ decisions about whether or not to buy stock in a given company. As this problem tackles individual decision-making processes, we designed and applied an incentivised economic experiment based on vignette studies and focused on individual decisions of single investors. Subjects took part in an online game that imitates stock exchange conditions and that concerns corporate reputation and investing. We found that the individual propensity to invest is not directly based on an investor’s perception (rooted in historical share price and other objective metrics) of a firm’s reputation but rather on an investor’s subjective recognition of collective corporate reputation in the market. This suggests a need to rethink the popular measures of corporate reputation in the context of studies of stock market investor decisions.

The sustainability of stock price fluctuations indicated by many empirical studies hardly reconciles with the existing models in standard financial theories. This paper proposes a recursive dynamic asset pricing model based on the comprehensive impact of the sentiment investor, the information trader and the noise trader. The dynamic process of the asset price is characterized and a numerical simulation of the model is provided. The model captures the features of the actual stock price that are consistent with the empirical evidence on the sustainability of stock price fluctuations. It also offers a partial explanation for other financial anomalies, for example, asset price’s overreaction, asset bubble and the financial crisis. The major finding is that investor sentiment is the key factor to understand the sustainability of stock price fluctuations.

PRML, a novel candlestick pattern recognition model using machine learning methods, is proposed to improve stock trading decisions. Four popular machine learning methods and 11 different features types are applied to all possible combinations of daily patterns to start the pattern recognition schedule. Different time windows from one to ten days are used to detect the prediction effect at different periods. An investment strategy is constructed according to the identified candlestick patterns and suitable time window. We deploy PRML for the forecast of all Chinese market stocks from Jan 1, 2000 until Oct 30, 2020. Among them, the data from Jan 1, 2000 to Dec 31, 2014 is used as the training data set, and the data set from Jan 1, 2015 to Oct 30, 2020 is used to verify the forecasting effect. Empirical results show that the two-day candlestick patterns after filtering have the best prediction effect when forecasting one day ahead; these patterns obtain an average annual return, an annual Sharpe ratio, and an information ratio as high as 36.73%, 0.81, and 2.37, respectively. After screening, three-day candlestick patterns also present a beneficial effect when forecasting one day ahead in that these patterns show stable characteristics. Two other popular machine learning methods, multilayer perceptron network and long short-term memory neural networks, are applied to the pattern recognition framework to evaluate the dependency of the prediction model. A transaction cost of 0.2% is considered on the two-day patterns predicting one day ahead, thus confirming the profitability. Empirical results show that applying different machine learning methods to two-day and three-day patterns for one-day-ahead forecasts can be profitable.

The Chilean health authorities have implemented a sanitary strategy known asdynamic quarantineorstrategic quarantineto cope with the COVID-19 pandemic. Under this system, lockdowns were established, lifted, or prolonged according to the weekly health authorities’ assessment of municipalities’ epidemiological situation. The public announcements about the confinement situation of municipalities country-wide are made typically on Tuesdays or Wednesdays before noon, have received extensive media coverage, and generated sharp stock market fluctuations. Municipalities are the smallest administrative division in Chile, with each city broken down typically into several municipalities. We analyze social media behavior in response to the confinement situation of the population at the municipal level. The dynamic quarantine scheme offers a unique opportunity for our analysis, given that municipalities display a high degree of heterogeneity, both in size and in the socioeconomic status of their population. We exploit the variability over time in municipalities’ confinement situations, resulting from the dynamic quarantine strategy, and the cross-sectional variability in their socioeconomic characteristics to evaluate the impact of these characteristics on social sentiment. Using event study and panel data methods, we find that proxies for social sentiment based on Twitter queries are negatively related (more pessimistic) to increases in the number of confined people, but with a statistically significant effect concentrated on people from the wealthiest cohorts of the population. For indicators of social sentiment based on Google Trends, we found that search intensity during the periods surrounding government announcements is positively related to increases in the total number of confined people. Still, this effect does not seem to be dependent on the segments of the population affected by the quarantine. Furthermore, we show that the observed heterogeneity in sentiment mirrors heterogeneity in stock market reactions to government announcements. We provide evidence that the observed stock market behavior around quarantine announcements can be explained by the number of people from the wealthiest segments of the population entering or exiting lockdown.

Recently, there has been much attention in the use of machine learning methods, particularly deep learning for stock price prediction. A major limitation of conventional deep learning is uncertainty quantification in predictions which affect investor confidence. Bayesian neural networks feature Bayesian inference for providing inference (training) of model parameters that provides a rigorous methodology for uncertainty quantification in predictions. Markov Chain Monte Carlo (MCMC) sampling methods have been prominent in implementing inference of Bayesian neural networks; however certain limitations existed due to a large number of parameters and the need for better computational resources. Recently, there has been much progress in the area of Bayesian neural networks given the use of Langevin gradients with parallel tempering MCMC that can be implemented in a parallel computing environment. The COVID-19 pandemic had a drastic impact in the world economy and stock markets given different levels of lockdowns due to rise and fall of daily infections. It is important to investigate the performance of related forecasting models during the COVID-19 pandemic given the volatility in stock markets. In this paper, we use novel Bayesian neural networks for multi-step-ahead stock price forecasting before and during COVID-19. We also investigate if the pre-COVID-19 datasets are useful of modelling stock price forecasting during COVID-19. Our results indicate due to high volatility in the stock-price during COVID-19, it is more challenging to provide forecasting. However, we found that Bayesian neural networks could provide reasonable predictions with uncertainty quantification despite high market volatility during the first peak of the COVID-19 pandemic.

Since the financial system has illustrated an increasingly prominent characteristic of inextricable connections, information theory is gradually utilized to study the financial system. By collecting the daily data of industry index (2005-2020) and region index (2012-2020) listed in China as samples, this paper applies an innovative measure named partial mutual information on mixed embedding to generate directed networks. Based on the analysis of nonlinear relationships among sectors, this paper realizes the accurate construction of “time-varying” financial network from the perspective of risk spillover. The results are presented as follow: (1) interactions can be better understood through the nonlinear networks among distinct sectors, and sectors in the networks could be classified into different types according to their topological properties connected to risk spillover; (2) in the rising stage, information is transmitted rapidly in the network, so the risk is fast diffused and absorbed; (3) in the declining stage, the network topology is more complex and panic sentiments have long term impact leading to more connections; (4) The US market, Japan market and Hongkong market have significant affect on China’s market. The results suggest that this nonlinear measure is an effective approach to develop financial networks and explore the mechanism of risk spillover.

El presente artículo, luego de exponer brevemente el rol de la calificación crediticia en los mercados financieros, brinda una primera panorámica sobre la normativa delineada por el legislador europeo, en particular sobre aquellas normas relativas al tema de la responsabilidad civil de las agencias en caso de difusión de una calificación crediticia errónea, y pone al descubierto algunas de sus deficiencias. This article presents briefly the role of credit rating in the financial markets. After it provides a first overview of the legislation outlined by the European legislator, in particular on the rules on civil liability of agencies in the event of dissemination of an erroneous credit rating. At the end, it exposes some of its shortcomings.

From the economists' perspective, the Capital Markets Union (CMU) represents a policy experiment that allows studying how legal conditions, economic incentives and financial activity interact. Recent papers provide economic support for the overall objective of CMU, but the robustness of this research is still to be established. Although harmonisation of legal frameworks can help overcome the information and competition problems that discourage market entry, it is difficult to identify which legal determinants are actually holding back the market development. The more detailed and granular the issue to be addressed, the more severe seem to be data gaps and limitations of analytical tools to identify the most effective policy measures and in consequence the stronger do policy directions rely on plausibility considerations. In the negotiation of concrete policy measures among the different policy actors in the EU, the still weak empirical foundations may hold up the realisation of the project's ambition. Die Kapitalmarktunion (Capital Markets Union, CMU) kann als Politikexperiment angesehen werden, in dem Sinne, dass sie es Volkswirten gestattet, die Zusammenhänge von rechtlichen Rahmenbedingungen, wirtschaftlichen Anreizen und Finanzaktivität zu analysieren. Die übergeordneten Ziele der CMU stehen in Einklang mit zuletzt veröffentlichten Forschungspapieren, auch wenn noch nicht endgültig geklärt ist, wie robust deren Ergebnisse sind. Zwar kann die Harmonisierung der rechtlichen Rahmenbedingungen helfen, die Informations- und Wettbewerbsprobleme zu überwinden, die die Kapitalmarktentwicklung zurückhalten. Allerdings ist es schwierig, die wirklich relevanten rechtlichen Rahmenbedingungen zu identifizieren. Insbesondere zeigt sich, dass je detaillierter und spezifischer die zu untersuchenden Fragen sind, umso schwerwiegender sind Limitationen aufgrund von fehlenden Daten und aussagekräftigen Analyseinstrumenten und desto stärker basiert daher die Herleitung effektiver Politikvorschläge und -richtungen auf Plausibilitätsüberlegungen. Die schwache empirische Fundierung steht dem Ehrgeiz dieses Projektes entgegen und kann sich als Hindernis erweisen, wenn konkrete Politikmaßnahmen auf EU-Ebene von den verschiedenen politischen Akteuren verhandelt werden.

The motivation for testing anomalies in the selected financial markets in the region was primarily to help investors to devise a viable investment strategy. Taking into account the difficult circumstances faced by the capital markets in developing countries, their efficient operation is under question. While the calendar anomalies in the developed capital markets have been studied intensively, emerging stock markets have received less attention. The aim of this paper is to test historical data on movements of stock exchange indexes in the region, and in that way the possibility of gaining beyond average yields on capital in certain calendar months during the year, also known as the January effect. The paper aims to test the efficient market hypothesis (in terms of the presence or not of the 'January effect') in the financial markets in the region by using daily data of regional stock market indexes. Panel data analysis includes daily data during the period from 2008 to 2014 for the stock exchanges in the emergent economies of Serbia, Bosnia and Herzegovina, Macedonia, Montenegro, Croatia, Romania and Bulgaria. However, in this study it has been proven that the traditional January effect is present only on the stock market in Macedonia. The obtained results on capital markets in selected countries in the region indicate weak sustainability of the efficient market hypothesis in most of the observed countries in the region and the presence of calendar anomalies.

Mutual funds report performance in the form of a holding period return (HPR) over standardized horizons. Changes in HPRs are equally influenced by new and previously reported stale returns which enter and exit the horizon. Investors appear unable to differentiate between the joint determinants, reacting with equal strength to both signals. Stale performance chasing is amplified for funds which promote performance via advertising and is more pronounced during periods of uncertainty in financial markets. Fund managers exploit this behavior by preferentially timing fee increases to align with periods of heightened investor demand resulting from stale performance chasing.

Does president Trump’s use of Twitter affect financial markets? The president frequently mentions companies in his tweets and, as such, tries to gain leverage over their behavior. We analyze the effect of president Trump’s Twitter messages that specifically mention a company name on its stock market returns. We find that tweets from the president which reveal strong negative sentiment are followed by reduced market value of the company mentioned, whereas supportive tweets do not render a significant effect. Our methodology does not allow us to conclude about the exact mechanism behind these findings and can only be used to investigate short-term effects. Publisher PDF

We examine the linkages between accounting information and credit default swap spread in Bulgaria. This paper employs a panel data approach including OLS model and VAR model. We use sovereign credit default swap spread data for the period reaching from the first quarter of 2009 to the fourth quarter of 2016. We apply 3 month Euribor rate as an indicator for risk- free rate. The final sample consists of twenty separate corporate entities from various industries in Bulgaria. The results reveal that accounting information is a relevant source of information to the credit markets. So we may conclude that accounting information is proved to provide incremental influence to the probability of default in Bulgaria. Moreover, CDS spreads has a significant relationship with other accounting and market variables.

The COVID-19 pandemic seems to be the most important phenomenon observed from March 2020 in virtually all countries of the world. The necessity to prevent the spread of COVID-19 and keep health care systems efficient resulted in the forced, drastic limitation of economic activity. Many service sectors were hit particularly hard with this but industry and agriculture were also affected. In particular, the pandemic substantially influenced financial markets and we can observe that some markets or instruments vary in stability since they have been affected in the different degree. In the paper, we present the problem of stability of stock markets during the COVID-19 pandemic. Due to the low number of works related to CEE countries during the pandemic, we analyze the Warsaw Stock Exchange, which is one of the most important markets in the CEE. Our main goal was to find how various industries represented by stock market indices have reacted to the COVID-19 shock and consequently which sectors turned out to keep stability and remained resistant to the pandemic. In our investigation, we use two clustering methods: the K-means and the Ward techniques with the criterion of maximizing the silhouette coefficient and six indicators describing stability in terms of profitability, volume, overbought/oversold conditions and volatility. The results of the research present that during the pandemic it was possible to identify 5 clusters of sector indices in the short term and 4 in the medium term. We found that the composition of the clusters is quite stable over time and that none of the obtained clusters can be univocally considered the most or the least stable taking into account all the analyzed indicators. However, we showed that the obtained clusters have different stability origins, i.e. they vary from each other in terms of the investigated indicators of stability.

Corporate governance is the way of governing a firm in order to increase its accountability and to avoid any massive damage before it occurs. The aim of this paper is to investigate the impact of capital structure, firms’ size, and competitive advantages of firms as control variables on credit ratings. We investigate the role of corporate governance in improving the firms’ credit rating using a sample of Jordanian listed firms. We split firms into four categories according to WVB credit rating. We use both the binary logistic regression (LR) and the ordinal logistic regression (OLR) to model credit ratings in Jordanian environment. The empirical results show that the control variables are strong determinants of credit ratings. When we evaluate the relationship between the governance variables and credit ratings, we found interesting results. The board stockholders and board expertise are moderately significant. The board independence and role duality are weakly significant, while board size is insignificant.