Pablo Fernández, Sofia Bañuls, Juan Fernández Acín, Lucía Fernández Acín
Spanish Abstract: En el periodo diciembre 2005 - diciembre 2020, la rentabilidad del IBEX 35 fue 50,2% (promedio anual 2,75%) y la de los bonos del Estado a 15 años 64,7% (promedio anual 3,38%). La rentabilidad media de los fondos de pensiones fue 30,5% (promedio anual 1,8%).
Entre los 416 fondos de pensiones con 15 años de historia, 64 superaron la rentabilidad del IBEX 35 y 34 la de los bonos del Estado a 15 años. 11 fondos tuvieron rentabilidad negativa.
Los 969 fondos de pensiones del sistema individual tenían (diciembre 2020) 7,5 millones de partícipes y un patrimonio de €81.790 millones. En diciembre de 2019 había 1.004 fondos.
English Abstract: During the last 15 year period (2005-2020), the average return of the pension funds in Spain (1.8%) was lower than the return of Government Bonds (3.38%). Only 34 funds (out of 416) had a higher return than the 15-year Government Bonds. Nevertheless, on December 31, 2020, 7.5 million investors had 81.8 billion euros invested in pension funds.
{"title":"Rentabilidad de los Fondos de Pensiones en España. 2005-2020 (Return of Pension Funds in Spain. 2005-2020)","authors":"Pablo Fernández, Sofia Bañuls, Juan Fernández Acín, Lucía Fernández Acín","doi":"10.2139/ssrn.3769952","DOIUrl":"https://doi.org/10.2139/ssrn.3769952","url":null,"abstract":"<b>Spanish Abstract:</b> En el periodo diciembre 2005 - diciembre 2020, la rentabilidad del IBEX 35 fue 50,2% (promedio anual 2,75%) y la de los bonos del Estado a 15 años 64,7% (promedio anual 3,38%). La rentabilidad media de los fondos de pensiones fue 30,5% (promedio anual 1,8%).<br><br>Entre los 416 fondos de pensiones con 15 años de historia, 64 superaron la rentabilidad del IBEX 35 y 34 la de los bonos del Estado a 15 años. 11 fondos tuvieron rentabilidad negativa.<br><br>Los 969 fondos de pensiones del sistema individual tenían (diciembre 2020) 7,5 millones de partícipes y un patrimonio de €81.790 millones. En diciembre de 2019 había 1.004 fondos.<br><br><b>English Abstract:</b> During the last 15 year period (2005-2020), the average return of the pension funds in Spain (1.8%) was lower than the return of Government Bonds (3.38%). Only 34 funds (out of 416) had a higher return than the 15-year Government Bonds. Nevertheless, on December 31, 2020, 7.5 million investors had 81.8 billion euros invested in pension funds.","PeriodicalId":208149,"journal":{"name":"Finance Educator: Courses","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121555376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Haitham Nobanee, Farah Altayr, Mariam Alhosani, Fatima AlShamsi, Dana Ali, Noura Mubarak, Siba Mahfouz, Maryam Mohammed
BMW and Daimler are both German international companies that deal with vehicles and motorcycles. In this article, we will analyze the two companies' financial performance and find out their positions. We will look at their financial data from 2016 to 2019 to determine their financial state, and include figures and tables for easier analysis, thus giving suggestions for potential improvement areas.
{"title":"Financial Analysis of BMW & Daimler (Mercedes-Benz)","authors":"Haitham Nobanee, Farah Altayr, Mariam Alhosani, Fatima AlShamsi, Dana Ali, Noura Mubarak, Siba Mahfouz, Maryam Mohammed","doi":"10.2139/ssrn.3766088","DOIUrl":"https://doi.org/10.2139/ssrn.3766088","url":null,"abstract":"BMW and Daimler are both German international companies that deal with vehicles and motorcycles. In this article, we will analyze the two companies' financial performance and find out their positions. We will look at their financial data from 2016 to 2019 to determine their financial state, and include figures and tables for easier analysis, thus giving suggestions for potential improvement areas.","PeriodicalId":208149,"journal":{"name":"Finance Educator: Courses","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133435479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The focal theme of the current research is to conduct comparative assessment of two firms in light of financial metrics will identify the strength and weaknesses of the respective firms. The comparative overview will allow one to understand the standards and practices that a firm can emulate to guarantee success. The firms under consideration are General Electrics and Siemens AG.
Extensive analysis found that the condition of General Electric is much better when it comes to liquidity and leverage. However, in terms of profitability and cash flow, the performance of SIE was found to be much better, which is consistent with the fact that firms with high WCM (GE) had low profitability.
{"title":"Working Capital Management: A Comparative Study of Siemens AG and General Electric","authors":"Zayed Sultan Alqubaisi, Khalid Sead Alqubaisi, Syed Ashraf Pasha, Rami Afach, Bilal Daher, Abdulrhman Almarzooqi, Bashar Garba, Salah Rabee, Haitham Nobanee","doi":"10.2139/ssrn.3765696","DOIUrl":"https://doi.org/10.2139/ssrn.3765696","url":null,"abstract":"The focal theme of the current research is to conduct comparative assessment of two firms in light of financial metrics will identify the strength and weaknesses of the respective firms. The comparative overview will allow one to understand the standards and practices that a firm can emulate to guarantee success. The firms under consideration are General Electrics and Siemens AG. <br><br>Extensive analysis found that the condition of General Electric is much better when it comes to liquidity and leverage. However, in terms of profitability and cash flow, the performance of SIE was found to be much better, which is consistent with the fact that firms with high WCM (GE) had low profitability.<br>","PeriodicalId":208149,"journal":{"name":"Finance Educator: Courses","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129646672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Haitham Nobanee, Hamdan Alzaabi, A. Alremeithi, Mohamed Abdulla, Dunia Azim, N. Ismaili
The report is about the working capital management of the two renowned companies Tesla and NIO. Tesla is now recognized as a strong supporter for electric car development. In 2015 it became the best-selling switch car in the world, with the legendary vehicle Tesla Model. NIO, on the other hand is a revolutionary and fast-growing electrical (EV) maker in China. In order to do the analysis, ratio analysis has been done to compare the performance of both Tesla and NIO. In order to transform the data in an understandable form, use of graphs have been done understand it in a more appropriate way. The data for the analysis has been taken from the annual reports of Tesla and NIO. The analysis showed that the profits of the company has been noted to increase with time. NIO has also been able to improve its profits but it’s comparatively lower as compared to Tesla. This shows that Tesla has been successfully able to manage its liquidity and profitability, however NIO has filed to manage its profits.
{"title":"Working Capital Management Ratios: A Comparative Study between Tesla and NIO","authors":"Haitham Nobanee, Hamdan Alzaabi, A. Alremeithi, Mohamed Abdulla, Dunia Azim, N. Ismaili","doi":"10.2139/ssrn.3763482","DOIUrl":"https://doi.org/10.2139/ssrn.3763482","url":null,"abstract":"The report is about the working capital management of the two renowned companies Tesla and NIO. Tesla is now recognized as a strong supporter for electric car development. In 2015 it became the best-selling switch car in the world, with the legendary vehicle Tesla Model. NIO, on the other hand is a revolutionary and fast-growing electrical (EV) maker in China. In order to do the analysis, ratio analysis has been done to compare the performance of both Tesla and NIO. In order to transform the data in an understandable form, use of graphs have been done understand it in a more appropriate way. The data for the analysis has been taken from the annual reports of Tesla and NIO. The analysis showed that the profits of the company has been noted to increase with time. NIO has also been able to improve its profits but it’s comparatively lower as compared to Tesla. This shows that Tesla has been successfully able to manage its liquidity and profitability, however NIO has filed to manage its profits.","PeriodicalId":208149,"journal":{"name":"Finance Educator: Courses","volume":"1577 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127447774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arnoud Boot, P. Hoffmann, L. Laeven, Lev Ratnovski
Abstract We study the effects of technological change on financial intermediation, distinguishing between innovations in information (data collection and processing) and communication (relationships and distribution). Both follow historical trends towards an increased use of hard information and less in-person interaction, which are accelerating rapidly. We evaluate more recent innovations, such as the combination of data abundance and artificial intelligence, and the rise of digital platforms. We argue that the rise of new communication channels can lead to the vertical and horizontal disintegration of the traditional bank business model. Specialized providers of financial services can chip away activities that do not rely on access to balance sheets, while platforms can interject themselves between banks and customers. We discuss limitations to these challenges to the traditional bank business model, and the resulting policy implications.
{"title":"Fintech: What’s Old, What’s New?","authors":"Arnoud Boot, P. Hoffmann, L. Laeven, Lev Ratnovski","doi":"10.2139/ssrn.3756798","DOIUrl":"https://doi.org/10.2139/ssrn.3756798","url":null,"abstract":"Abstract We study the effects of technological change on financial intermediation, distinguishing between innovations in information (data collection and processing) and communication (relationships and distribution). Both follow historical trends towards an increased use of hard information and less in-person interaction, which are accelerating rapidly. We evaluate more recent innovations, such as the combination of data abundance and artificial intelligence, and the rise of digital platforms. We argue that the rise of new communication channels can lead to the vertical and horizontal disintegration of the traditional bank business model. Specialized providers of financial services can chip away activities that do not rely on access to balance sheets, while platforms can interject themselves between banks and customers. We discuss limitations to these challenges to the traditional bank business model, and the resulting policy implications.","PeriodicalId":208149,"journal":{"name":"Finance Educator: Courses","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116488499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Romanian Abstract: Costurile pot reprezenta un aspect important al deciziilor din afaceri. Cunoaşterea principalelor componente ale costurilor poate fi utilă în planificarea financiară. În plus, comparaţia dintre costul şi preţul unui produs facilitează studiul profitabilităţii acestuia. Această lucrare prezintă câteva tehnici simple ale analizei costurilor.
English Abstract: The costs could represent an important aspect of the business decisions. Knowing the major components of costs could be useful in the financial planning. Moreover, the comparison between the cost and the price of a product facilitates the study of its profitability. This paper presents some simple techniques of the cost analysis.
{"title":"Statistica Afacerilor: Aplicaţii, Partea a treia (Business Statistics: Exercises, Part 3)","authors":"R. Stefanescu, Ramona Dumitriu","doi":"10.2139/ssrn.3743710","DOIUrl":"https://doi.org/10.2139/ssrn.3743710","url":null,"abstract":"<b>Romanian Abstract:</b> Costurile pot reprezenta un aspect important al deciziilor din afaceri. Cunoaşterea principalelor componente ale costurilor poate fi utilă în planificarea financiară. În plus, comparaţia dintre costul şi preţul unui produs facilitează studiul profitabilităţii acestuia. Această lucrare prezintă câteva tehnici simple ale analizei costurilor. <br><br><b>English Abstract:</b> The costs could represent an important aspect of the business decisions. Knowing the major components of costs could be useful in the financial planning. Moreover, the comparison between the cost and the price of a product facilitates the study of its profitability. This paper presents some simple techniques of the cost analysis.<br>","PeriodicalId":208149,"journal":{"name":"Finance Educator: Courses","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122107852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Romanian Abstract: Datorită simplităţii, extrapolările trendurilor sunt adeseori preferate în prognoza economică. Această lucrare include exemple de extrapolare a trendurilor liniare şi quadratice. Sunt prezentaţi, de asemenea, câţiva indicatori ai acurateţei previziunii.
English Abstract: Because of their simplicity, the trends extrapolations are often preferred in the economic forecasting. This paper includes examples of linear and quadratic trends extrapolation. There are also presented some indicators of the prediction accuracy.
罗马尼亚文摘 要：在经济预测中，趋势外推是首选，因为它简单明了。我们可以举出线性和四分法趋势外推的例子。Sunt prezentaţi, de asemenea, câţiva indicatori ai acurateţei previziunii.English Abstract: Because of their simplicity, the trends extrapolations are often preferred in the economic forecasting.本文举例说明了线性和二次趋势外推法。文中还介绍了一些预测准确性指标。
{"title":"Statistica Afacerilor: Aplicaţii, Partea a doua (Business Statistics: Exercises, Part 2)","authors":"R. Stefanescu, Ramona Dumitriu","doi":"10.2139/ssrn.3723897","DOIUrl":"https://doi.org/10.2139/ssrn.3723897","url":null,"abstract":"<b>Romanian Abstract:</b> Datorită simplităţii, extrapolările trendurilor sunt adeseori preferate în prognoza economică. Această lucrare include exemple de extrapolare a trendurilor liniare şi quadratice. Sunt prezentaţi, de asemenea, câţiva indicatori ai acurateţei previziunii.<br><br><b>English Abstract:</b> Because of their simplicity, the trends extrapolations are often preferred in the economic forecasting. This paper includes examples of linear and quadratic trends extrapolation. There are also presented some indicators of the prediction accuracy.<br>","PeriodicalId":208149,"journal":{"name":"Finance Educator: Courses","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130102746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we examine time-varying correlations among stock returns of Apple, Microsoft, Amazon and Google. Employing a multivariate DCC-GARCH model, we find that there are strong linkages among these four assets. Starting from lower levels, correlation values for most asset pairs exhibit a stable ascending movement in recent upward trended markets to, in an exceptional case, almost hit the perfect positive correlation mark. We show that correlations among these assets jump during downturn market periods, suggesting limits in the diversification of risk within the segment of large cap U.S. technology stocks. Our results are helpful for portfolio management and asset allocation.
{"title":"Apple, Microsoft, Amazon and Google - A Correlation Analysis: Evidence from a DCC-GARCH Model","authors":"Christoph Koser, Juergen Klaus","doi":"10.2139/ssrn.3718788","DOIUrl":"https://doi.org/10.2139/ssrn.3718788","url":null,"abstract":"In this paper, we examine time-varying correlations among stock returns of Apple, Microsoft, Amazon and Google. Employing a multivariate DCC-GARCH model, we find that there are strong linkages among these four assets. Starting from lower levels, correlation values for most asset pairs exhibit a stable ascending movement in recent upward trended markets to, in an exceptional case, almost hit the perfect positive correlation mark. We show that correlations among these assets jump during downturn market periods, suggesting limits in the diversification of risk within the segment of large cap U.S. technology stocks. Our results are helpful for portfolio management and asset allocation.","PeriodicalId":208149,"journal":{"name":"Finance Educator: Courses","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131007347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Expectations of risky bond payments are unobservable and recovery rates for sovereigns are hard to estimate because they have no contractual claims to defined assets and samples of defaults are limited. A geometric version of credit spread is used to derive expected payments, dependent on idiosyncratic risk and unrelated to interest rates. The expectations are used to define a measure of price sensitivity to credit risk perceptions, or credit duration, improving the ambiguity of modified yield duration.
{"title":"Sovereign Bond Spreads and Credit Sensitivity","authors":"Ricardo Schefer","doi":"10.2139/ssrn.3838104","DOIUrl":"https://doi.org/10.2139/ssrn.3838104","url":null,"abstract":"Expectations of risky bond payments are unobservable and recovery rates for sovereigns are hard to estimate because they have no contractual claims to defined assets and samples of defaults are limited. A geometric version of credit spread is used to derive expected payments, dependent on idiosyncratic risk and unrelated to interest rates. The expectations are used to define a measure of price sensitivity to credit risk perceptions, or credit duration, improving the ambiguity of modified yield duration.","PeriodicalId":208149,"journal":{"name":"Finance Educator: Courses","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121976302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose of the study: To critically analyse the financial growth pattern and the overall performance efficiency of industrial machinery companies in India. Design/Methodology/Approach: The data collected from the financial statement of the companies for 10 years from 2007-2008 to 2016-17 were analysed with the help of different accounting and statistical tools. Discriminant analysis has been adopted for analysing and interpreting the quantitative data was carried out using SPSS. Findings: The study reveals that good performance efficiency of the engineering industry over the period 2007-2017, most Indian engineering industries exist with high net profit. The poor performance companies need of the hour to increase profit by reducing costs. Practical Implications: The study has interesting policy implications. It is recommended to encourage foreign banks' presence to enhance the competitive condition of the banking sector thus making sure the exit and entrance of banks in the industry to raise the competition. The pursuit of modernization, in fully hardening the resources of information technology should be relentless. It is a field that demands great attention and expertise. Originality/value: This research work is one of its first kind as no study was conducted before focusing on the performance perspectives of the engineering industries in India.
{"title":"Performance Efficiency of Engineering Industries in India","authors":"B. Muthuraman","doi":"10.47259/IJREBS.125","DOIUrl":"https://doi.org/10.47259/IJREBS.125","url":null,"abstract":"Purpose of the study: To critically analyse the financial growth pattern and the overall performance efficiency of industrial machinery companies in India. \u0000 \u0000Design/Methodology/Approach: The data collected from the financial statement of the companies for 10 years from 2007-2008 to 2016-17 were analysed with the help of different accounting and statistical tools. Discriminant analysis has been adopted for analysing and interpreting the quantitative data was carried out using SPSS. \u0000 \u0000Findings: The study reveals that good performance efficiency of the engineering industry over the period 2007-2017, most Indian engineering industries exist with high net profit. The poor performance companies need of the hour to increase profit by reducing costs. \u0000 \u0000Practical Implications: The study has interesting policy implications. It is recommended to encourage foreign banks' presence to enhance the competitive condition of the banking sector thus making sure the exit and entrance of banks in the industry to raise the competition. The pursuit of modernization, in fully hardening the resources of information technology should be relentless. It is a field that demands great attention and expertise. \u0000 \u0000Originality/value: This research work is one of its first kind as no study was conducted before focusing on the performance perspectives of the engineering industries in India.","PeriodicalId":208149,"journal":{"name":"Finance Educator: Courses","volume":"13 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132969726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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