M. Doumpos, K. Pentaraki, C. Zopounidis and C. Agorastos
Explains the importance of assessing country risk to lenders and investors, outlines previous research on techniques for doing this and describes a classification method: the…
Abstract
Explains the importance of assessing country risk to lenders and investors, outlines previous research on techniques for doing this and describes a classification method: the multi‐group hierarchical discrimination method (MHD). Applies this to 1978‐1995 data for 143 countries, subdivided into four income groups, and compares the results with those from multiple discriminant, logit and probit analyses using jackknife procedures. Finds MHD more accurate overall and for most income groups except the lower‐middle income economies. Briefly considers other applications for MHD and avenues for further research.
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This chapter presents the survey of selected linear and mixed integer programming multi-objective portfolio optimization. The definitions of selected percentile risk measures are…
Abstract
This chapter presents the survey of selected linear and mixed integer programming multi-objective portfolio optimization. The definitions of selected percentile risk measures are presented. Some contrasts and similarities of the different types of portfolio formulations are drawn out. The survey of multi-criteria methods devoted to portfolio optimization such as weighting approach, lexicographic approach, and reference point method is also presented. This survey presents the nature of the multi-objective portfolio problems focuses on a compromise between the construction of objectives, constraints, and decision variables in a portfolio and the problem complexity of the implemented mathematical models. There is always a trade-off between computational time and the size of an input data, as well as the type of mathematical programming formulation with linear and/or mixed integer variables.
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This chapter examines the impact of banking competition, bank regulation, and the global financial crisis (GFC) of 2008–2009 on banks’ productivity changes. For the empirical…
Abstract
This chapter examines the impact of banking competition, bank regulation, and the global financial crisis (GFC) of 2008–2009 on banks’ productivity changes. For the empirical analysis, I apply a semi-parametric two-step approach of Malmquist index estimates and bootstrap regression to a cross-country panel data of 8,451 commercial banks from 82 countries over the period 2004–2012. Empirical results show that (1) banking competition and capital regulation significantly enhance bank productivity, (2) a tighter bank supervision have a positive impact on bank productivity, and (3) bank productivity decreases during the GFC, but starts to increase as the GFC recovers. I also present consistent evidence that commercial banks in countries with better national governance have higher productivity growth before, during and after the GFC.
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Nikolaos Petrakis, Christos Lemonakis, Christos Floros and Constantin Zopounidis
This paper aims to address the following research questions: How do European banking stocks react; to the European Central Bank’s (ECB) expansionary policies? Additionally, which…
Abstract
Purpose
This paper aims to address the following research questions: How do European banking stocks react; to the European Central Bank’s (ECB) expansionary policies? Additionally, which types of expansionary measures (conventional vs. unconventional) exert the most significant influence on bank stock performance?
Design/methodology/approach
Utilizing an event study approach combined with panel regression analysis, this research evaluates the impact of 77 key ECB policy interventions on the stock prices of 14 large European banks from 2007 to 2020. The event windows focus on cumulative abnormal returns (CARs) over short-term and medium-term periods to capture stock reactions to both conventional and unconventional monetary measures.
Findings
The results indicate that European banking stocks respond positively to both conventional (e.g. interest rate cuts) and unconventional (e.g. asset purchases, liquidity provisions) expansionary policies. However, asset purchase programs seem to have the most substantial and sustained impact, generating stronger positive cumulative abnormal returns over longer event windows compared to other interventions.
Originality/value
This article contributes to the literature by providing a detailed analysis of how different types of ECB monetary interventions influence bank stock performance. It is the first study to analyze and compare the persistence and strength of these measures across various event windows, offering valuable insights for investors and policymakers in assessing the effectiveness of monetary policy on capital markets.
Highlights
- (1)
This paper explores how European banking stocks react to ECB’s expansionary policies.
- (2)
It uses an event study and panel regression to assess 77 policy interventions from 2007 to 2020.
- (3)
Asset purchases are found to have the strongest and most persistent positive effects on bank stock prices.
- (4)
The analysis highlights the differential impact of conventional versus unconventional monetary policies on European banks.
This paper explores how European banking stocks react to ECB’s expansionary policies.
It uses an event study and panel regression to assess 77 policy interventions from 2007 to 2020.
Asset purchases are found to have the strongest and most persistent positive effects on bank stock prices.
The analysis highlights the differential impact of conventional versus unconventional monetary policies on European banks.
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Umar Muhammad Modibbo, Musa Hassan, Aquil Ahmed and Irfan Ali
Supplier selection in the supply chain network (SCN) has strategic importance and involves multiple factors. The multi-criteria nature of the problem coupled with environmental…
Abstract
Purpose
Supplier selection in the supply chain network (SCN) has strategic importance and involves multiple factors. The multi-criteria nature of the problem coupled with environmental uncertainty requires several procedures and considerations. The issue of decision-making in selecting the best among various qualified suppliers remains the major challenge in the pharmaceutical industry. This study investigated the multi-criteria multi-supplier decision-making process and proposed a model for supplier selection problems based on mixed-integer linear programming.
Design/methodology/approach
The concept of principal component analysis (PCA) was used to reduce data dimensionality, and the four best criteria have been considered and selected. The result is subjected to decision-makers’ (DMs’) reliability test using the concept of a triangular fuzzy number (TFN). The importance of each supplier to each measure is established using fuzzy technique for order preference by similarity to an ideal solution approach, and the suppliers have ranked accordingly.
Findings
This study proposes a mixed integer linear programming model for supplier selection in a pharmaceutical company. The effectiveness of the proposed model has been demonstrated using a numerical example. The solution shows the model's applicability in making a sound decision in pharmaceutical companies in the space of reality. The model proposed is simple. Readily commercial packages such as LINDO/LINGO and GAMS can solve the model.
Research limitations/implications
This research contributed to the systematic manner of supplier selection considering DMs’ value judgement under a fuzzy environment and is limited to the case study area. However, interested researchers can apply the study in other related manufacturing industries. However, the criteria have to be revisited to suit that system and might require varying ratings based on the experts' opinions in that field.
Practical implications
This work suggests more insights practically by considering a realistic and precise investigation based on a real-life case study of pharmaceutical companies with six primary criteria and twenty-four sub-criteria. The study outcome will assist organizations and managers in conducting the best decision objectively by selecting the best suppliers with their various standards and terms among many available contenders in the manufacturing industry.
Originality/value
In this paper, the authors attempted to identify the most critical attributes to be preserved by the top managers (DMs) while selecting suppliers in pharmaceutical companies. The study proposed an MILP model for supplier selection in the pharmaceutical company using fuzzy TOPSIS.
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Dominik Rozkrut, Malgorzata Tarczynska-Luniewska, Guru Asish Singh and Mateusz Piwowarski
Purpose: Sustainable and responsible business is strongly associated with activities that minimise negative environmental or social impacts. As a result, the utility of big data…
Abstract
Purpose: Sustainable and responsible business is strongly associated with activities that minimise negative environmental or social impacts. As a result, the utility of big data is becoming a reality, opening up exciting possibilities for ESG monitoring and assessment. This study systematises existing knowledge and provides recommendations for big data in ESG monitoring and assessment.
Methodology/approach: Theoretical and exploratory focusing on a literature review.
Conclusions: Results indicate different levels of progress and challenges related to ESG and big data. Awareness and adoption of ESG and big data practices is growing, accompanied by regulatory pressure.
Significance: Understanding the relationship between big data and ESG is critical to properly conducting sustainable and responsible business practices. The urgency and necessity of developing standards for constructing big data cannot be overstated for ensuring consistency between existing policies and the SDGs and for the effective use of big data in ESG monitoring and assessment.
Limitations: A lack of data quality and standardisation in reporting for ESG assessments. Standardisation efforts are growing as data challenges, especially data availability, are major constraints. Large data sets offer exciting opportunities, analysed mainly from the perspective of existing applications for measuring sustainability goals.
Future research: An in-depth analysis of case studies that combine ESG issues with big data infrastructure. Fundamental is knowledge and understanding of companies’ ESG practices and understanding big data issues. We can standardise approaches to using new data sources and move towards deepening our measurable dimension of sustainability assessment.
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Purpose: This chapter explores some of the difficult issues in financial regulation for financial stability. Noting the lack of prior academic work in the topic, this chapter…
Abstract
Purpose: This chapter explores some of the difficult issues in financial regulation for financial stability. Noting the lack of prior academic work in the topic, this chapter presents a discussion of some difficult issues in financial regulation for financial stability.
Methodology: The chapter draws from real-world experiences in financial regulation and draws support from existing literature.
Findings and conclusions: Some of the difficult issues include: the difficulty in breaking too-big-to-fail financial institutions into small insignificant parts; the difficulty in regulating executive compensation in the financial sector without limiting the ability of financial institutions to offer competitive pay for executive talent; difficulty in instilling strict financial regulation and supervision without limiting the ability of financial institutions to exploit emerging profitable opportunities; difficulty in ensuring that financial institutions increase lending in bad times and during recessions; the rarity of having both a female CEO and Chair in a major financial institution; difficulty in making Central Banks independent from the Federal Government; difficulty in making financial institutions relevant in the midst of hostile technological innovation and disruption.
Practical implications: The implication of the findings is that financial regulation for financial stability is not an easy task. There will be issues that financial regulation can address, and there will be issues that financial regulation cannot address. Acknowledging that such difficulties exist on the path to financial stability is the first step to addressing these issues.
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Zacharoula Andreopoulou, Christiana Koliouska and Constantin Zopounidis
This paper aims to present and assess the EU energy policies regarding their dependence on Information and Communication Technology (ICT) implications and the level of complexity…
Abstract
Purpose
This paper aims to present and assess the EU energy policies regarding their dependence on Information and Communication Technology (ICT) implications and the level of complexity of the applied ICT implications using the Technique for Order Preference by Similarity of Ideal Solution (TOPSIS) method. The used criteria have been retrieved from the official “ICT Implication Assessment method of EU Legislation”.
Design/methodology/approach
The methodology approach deals with the ranking representation of EU energy policies according to the ICT exploitation. The data for the study were collected from the official website of the European Union (EU) (www.europa.eu). According to these data, the subtopics of the EU energy policies regard the internal energy market, the European energy policy, the energy efficiency, the nuclear energy, the security of energy supply, the external dimension, the enlargement and the renewable energy sources. The EU energy policies were assessed using the TOPSIS multicriteria analysis. The TOPSIS is widely used to solve real-world decision-making problems due to its characteristic to deal with different information types.
Findings
According to the results of the research, the EU energy policies achieve a good level of dependence on ICT implications and of complexity of the applied ICT implications but not the optimum. However, EU policy-makers should take into account the ICT factors while updating an existing one or while designing a new energy policy. The results of this research can provide an overview of the current situation regarding the current legislation while moving toward a sustainable eEurope. There is a need for stronger incubation efforts for a wide range of innovations to be ready in due time.
Originality/value
This is the first time that EU energy policies are presented and assessed regarding their dependence on ICT implications and the level of complexity of the applied ICT implications using the TOPSIS method.
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Jose Joy Thoppan, M. Punniyamoorthy, K. Ganesh and Sanjay Mohapatra
This paper aims to review prior studies and presents a synthesis of the takeover prediction literature spanning the period 1968–2018.
Abstract
Purpose
This paper aims to review prior studies and presents a synthesis of the takeover prediction literature spanning the period 1968–2018.
Design/methodology/approach
The paper adopts a narrative review approach. It explores prior studies on takeover target prediction from a historical perspective, focusing on the evolution and development of the literature over the 50-year period.
Findings
From a historical development perspective, prior studies in the area can be partitioned into four distinct eras. Studies in the first era (1968–1985) mainly established that takeover targets share common characteristics which can be captured with financial ratios. Studies in the second era (1986–2002) developed and extended formal target prediction hypotheses. These studies concluded that it was impossible to build a successful investment strategy around takeover target prediction. Studies in the third era (2003–2009) explored similar questions using alternative modelling techniques but arrive at similar results – targets can be predicted with limited accuracy and target prediction is unlikely to lead to abnormal returns. Studies in the fourth era (2010–2018) explore implications of M&A predictability on share valuation, governance and bond prices (amongst others), but most importantly, provide some evidence that takeover prediction can lead to abnormal returns when combined with appropriate screening strategies.
Originality/value
This presents the first in-depth review of the literature on takeover target prediction. It highlights the development of the literature over four distinct eras and identifies several limitations, research gaps and opportunities for future research. Given the recent decline in the literature (i.e. fourth era), this study may stimulate new research in the area.