The Roles of Corporate IT Infastructure and their Impact on IS Effectiveness

In the strategic alignment model of Henderson and Venkatraman (1993) [1] IT infrastructure has an important but only implicitly defined role. According to evolving literature, IT infrastructure serves many different purposes in large companies. We outline the main missions (roles) of the corporate-wide IT infrastructure and its contribution to IS effectiveness and study the relationship of IT infrastructure with alignment processes and strategic integration. Our empirical tests with data from almost one hundred large companies resulted in three IT infrastructure roles, which reflect the IS communality, strategic, and flexibility dimensions of the corporate-wide IT infrastructure. The roles were not symmetrically related to the IS effectiveness and alignment perspectives. IT infrastructure roles had a significant interplay with strategic integration in improving IS effectiveness. However, the interplay of IT infrastructure roles with alignment perspectives had only marginal effects. Implications of the results for research and practice are discussed

Can Zero-Coupon Bond Yield Curve Predict Economic Growth? – The Case of China

Since China's economic reform in 1978, the country's economic system has foreseen rapid evolvements, particularly in issuing debt securities by the Chinese central government to financing its drastic economic growth (Loo & Lqbal, 2019). This research study examines the zero-coupon bond yield curve's predictive power on China's GDP growth rate by adopting the Nelson-Siegel (1987) dynamic yield curve model. This research study adopts various approaches to refining the Nelson-Siegel (1987) model to enhance its predictive power on future economic activities, drawing upon the modifications undertaken by Diebold & Li's (2006) study to examining the constructed yield curve in accordance with the three latent factors of level, slope and curvature of the entire yield curve. A 67 period of zero-coupon bond yields is gathered between Q3 2002 and Q1 2019 quarterly from zero-coupon bond maturities of 1, 3, 5, 10, 20, and 30 years, finding that all types of zero-coupon bond maturities to exhibit similar yield curve movements across short, intermediary and long term durations. A multiple regression model was used to examine the correlation coefficient between the three latent factors and China's GDP, finding a significant relationship in the slope factor. A relationship was also found between the level and slope factors with a significance of 0.854, whereby the average rates between the two variables were calculated under the augmented Dicky Fuller test to ensure all factors are at stationary states to enhance the accuracy of future testing. The researcher also performed a least-squares equation (OLS) test to addressing the identified multicollinearity problem aforementioned, finding the R-squared value of 29.6%. Which suggested the level and curvature factors of the constructed yield curve would accurately explain 29.6% of China's GDP growth rates. To further examine the predictive power of the constructed yield curve in accordance to Nelson-Siegel's (1987) dynamic model, an out-of-sample forecasting method is employed with the out-of-sample size of 40 periods between Q3 2002 and Q2 2012 against 27 periods between Q3 and Q1 2019. The out-of-sample regression test founded an R squared value of 11.4,% suggesting that in sample forecasts contained higher predictive power to China's GDP growth based on the constructed yield curve. Furthermore, the out-of-sample forecast results show no significant relationship between the level and curvature factors, further reaffirming the argument that the yield curve in sample forecasts would better predict future economic activities. The research findings were consistent with findings from other studies conducted by Diebold & Li (2006); Hvozdenska (2015), and Campbell & Thompson (2008), whereby the spread of the yield curve constructed by the Nelson-Siegel (1987) dynamic model showed a strong relationship between China's GDP growth and the produced yield curve, representing strong predictive power and offers valuable insights to addressing the identified research gap where minimal research studies have explored the predictive power of China's zero-coupon bond yields in relation to the macroeconomic outlook. Keywords: Nelson-Siegel model, Yield curve, Zero-coupon bond, Maturity, Regression, Dynamic model. DOI: 10.7176/JEP/11-24-02 Publication date: December 31st 202

Machine Learning in Insurance

Machine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand and how any solution may affect the company and its customers. One aspect that has, perhaps, not been so well developed among actuaries is validation. Discussions among actuaries’ “preferred methods” were often without solid scientific arguments, including validation of the case at hand. Through this collection, we aim to promote a good practice of machine learning in insurance, considering the following three key issues: a) who is the client, or sponsor, or otherwise interested real-life target of the study? b) The reason for working with a particular data set and a clarification of the available extra knowledge, that we also call prior knowledge, besides the data set alone. c) A mathematical statistical argument for the validation procedure

Cartesian and complexity science in quantitative risk management in Zimbabwean banks

This thesis aims to examine critically the extent of Zimbabwean banks’ compliance to cartesian (Basel II/III) and complexity science theories in Quantitative Risk Management. Traditionally, Quantitative Risk Management in banks is examined within the dichotomy of cartesianism and interpretivism where probability and subjective tools are applied respectively. However, the emergence of complexity science from natural and engineering sciences, offers a new perspective. Quantitative Risk Management in Zimbabwean banks is an unexplored field. Mixed methods are employed to answer objectives of testing and examining critically the usefulness of cartesian and complexity science theories’ adoption in Zimbabwean banks. Data are collected from sixteen banks with structured questionnaires completed by 120 Risk Managers, and archival analysis on 112 annual audited financial statements and 20 reports from past surveys. Data analysis is done with descriptive statistics and hermeneutic methods for triangulation, complementarity, better evidence, and to obtain a holistic picture. The study empirically discovers that to a large extent Zimbabwean banks have adopted Basel II/III and complexity science with the same speed and in the same direction. However, there is an unbalanced implementation of both theories due to information asymmetries. For instance, Basel II/III implementation reveals stronger compliance to calculative idealism (Pillar 1) than supervision (Pillar 2) and market discipline (Pillar 3). Similarly, complexity science shows stronger adoption of dynamic risk management framework than modeling methods. While all banks in Zimbabwe are compliant to Basel II/III capital modeling methods regardless of size thus creating a level plain field of competition, its usefulness in promoting financial stability is refuted because of diverging regulatory and economic capital. Furthermore, complexity science is found to be more useful where pattern-based management is a prerequisite. This thesis contributes to knowledge in four specific ways. First, it provides empirical confirmation to laissez-faire theory that cartesian regulation is not useful in bank capitalisation. Second, it pioneers the application of complexity science theory from natural sciences to Quantitative Risk Management of banks within developing country settings. Third, it proposes a dynamic risk management framework and lastly, offers national policy recommendations to improve capital management in Zimbabwean banks

Default Predictors and Credit Scoring Models for Retail Banking

This paper develops a specification of the credit scoring model with high discriminatory power to analyze data on loans at the retail banking market. Parametric and non- parametric approaches are employed to produce three models using logistic regression (parametric) and one model using Classification and Regression Trees (CART, nonparametric). The models are compared in terms of efficiency and power to discriminate between low and high risk clients by employing data from a new European Union economy. We are able to detect the most important characteristics of default behavior: the amount of resources the client has, the level of education, marital status, the purpose of the loan, and the number of years the client has had an account with the bank. Both methods are robust: they found similar variables as determinants. We therefore show that parametric as well as non-parametric methods can produce successful models. We are able to obtain similar results even when excluding a key financial variable (amount of own resources). The policy conclusion is that socio-demographic variables are important in the process of granting credit and therefore such variables should not be excluded from credit scoring model specification.credit scoring, discrimination analysis, banking sector, pattern recognition, retail loans, CART, European Union

A preliminary investigation into the performance of ethical investment funds

Bibliography: leaves 107-116.A common argument against ethical investment is that it earns lower returns than conventional portfolios and is thus contrary to the fiduciary responsibility of fund trustees. The theoretical base for this assertion is that ethical investment reduces the investment universe. Little, if any, importance has been attached to the financial performance of socially responsible firms, and whether superior performance negates the reduction in investment possibilities. This study shows that ethical funds do not necessarily underperform, and in fact, in many cases have outperformed similar conventional funds. The criteria applied by these funds are examined and some economic justifications for the success of such funds are suggested. Successful funds could form the basis for RDP targetted investments in South Africa

Mining Rehabilitation Planning, Mining Heritage Tourism, Benefitsand Contingent Valuation

This article approaches the values underpinning derelict mining rehabilitation plans, their assessment in monetary terms, and reviews the empirical studies literature on this theme. The paper correspondingly contains four main aims. The first involves putting into perspective the thematic content on the rehabilitation of derelict and depressed mining areas, transforming them into mining heritage tourism products designed to trigger sustainable regional development. The second aim, concerns defining the range of benefits and values potentially arising. The third seeks to demonstrate and discuss why and how the theoretical frameworks of Total Economic Value (TEV) and economic valuation, taken together with the contingent valuation approach, enable the monetary estimation of the range of non-market individual values, through eliciting the individual’s willingness to pay (WTP) for the rehabilitation. And the fourth objective incorporates reviewing the literature on empirical studies estimating the monetary values of mining rehabilitation plans through recourse to the Contingent Valuation (CV) approach. We proceed by demonstrating that TEV, the economic valuation concept and CV are approaches appropriate to estimating the aforementioned benefits; we defend their utility as important inputs to raising the efficiency of political decision making processes and ensure local populations actively comply and participate in the rehabilitation process. Finally, we conclude that the empirical studies hitherto applied for estimating the monetary values of mining rehabilitation and remediation through recourse to CV remain very few despite the fact that this estimation type is increasingly recognised as an important tool in decision making processes on the rehabilitation of industrial cultural heritage in general, and mining heritage in particular