Modeling Claim Sizes In Personal Line Non-Life Insurance

This paper uses claims data from the most prominent lines of non-life insurance business in Nigeria to determine appropriate models for claim amounts by fitting theoretical distributions to the various data. The risk premiums for each class of business are also estimated. The result of the study demonstrates that some lines of business are indeed better modeled with different distributions than had earlier been conjectured

Forecasting Nigeria Foreign Exchange Risk with Extreme Value Theory

Foreign exchange forecasting is important in all forms of foreign investments and transactions, the skills which compliments the field of finance and related disciplines. This paper uses extreme value theory to estimate the Value-at-Risk (VaR) and Expected Shortfall (ES), by fitting negative log returns of Nigeria Naira (NGN) against nine other regional and world currencies into the Generalized Pareto Model. In this paper VaR is being used to determine daily foreign exchange risk on investments and the ES is used to determine the average risk over a period of time. Excess distribution and the tail of the underlying distribution were obtained over a required threshold. Empirical analysis shows that parameter estimate of the underlying distribution can be used to describe the performance of the VaR and ES. The findings contributes to the knowledge on foreign exchange forecasting and helps investors and policy makers in Nigeria to measure daily and possible risk over a period of time on certain investments

Using Extreme Value Theory to Model Insurance Risk of Nigeria's Motor Industrial Class of Business

Extreme losses have been recorded in Nigeria insurance companies due to motor insurance class claims; Nigeria Insurance market being a developing one requires building the confidence of the public to subscribe to their products. Nigeria’s motor industrial insurance claim data for five insurance companies in a two year period is modelled in this paper with extreme value theory (EVT) to estimate the Value-at-Risk (VaR), where VaR gives estimate of the minimum amount of claims an insurance company would pay in a given period of time. The time series plot was obtained which aimed at capturing the trend of the claims over the two-year period, the mean excess plot was obtained which helped to determine threshold and the shape of the distribution in the tail area. The returns were then fitted in a Generalized Pareto model (GPD), a similar model that would have been used is the Generalized Extreme Value model (GEV) but the GPD is used in this study because it describes what happens in the tail area of the distribution and not just the maximum tail. A linear Q-Q plot reveals that parametric model fits the data well. VaR estimate was finally obtained using the extreme value method and other two methods of Historical and Gaussian at 5% confidence interval. The three methods of estimating VaR were compared and the empirical result shows that extreme VaR is most suitable to calculate VaR as compared to the Historical and Gaussian method

EXPLORING THE METHODS OF COINTEGRATION PROCEDURES USING STOCK PRICES

Stationary models are an essential class of stochastic models for describing time series data which have received a great attention. In reality, however, business and economic data are non-stationary multivariate time series that are often better understood by cointegration analysis. This study investigates the cointegration testing methods of Engle-Granger two-step estimation technique, Phillip-Ouliaris test, and Johansen's multivariate test. The stock prices of selected companies in Nigeria from 2008-2014 are used in the study. Findings revealed that the three techniques produced different results and that the Johansen's method and Engle-Granger two steps procedure exhibits higher efficiencies than Phillips-Ouliaris methods but their efficiency is dependent on the number of variables and correct selection

A Statistical Analysis Of The Performance Distance Learning Students And The Full-Time Students At The University Of Lagos

The study compares the performance of distance learning students with full-time students in a traditional face-to-face learning environment. This study is one aspect of a larger research project designed to gain insight into factors that may influence the performance of distance learning students. The data used in the study represent the graduating GPA (Grade Point Average) and CGPA (Cumulative Grade Point Average). The result showed that students of Distance Learning Institute (DLI) performed better in business administration than the mainstream students, while the mainstream accounting students perform better than the DLI accounting students. Results indicated that there was a statistically significant difference in final grades of these groups of students

Use of a Rule Tool in Data Analysis Decision Making

Without any doubt, research work is an integrate part of any educational pursuit. However, students engaging in researches often find it difficult to choose an appropriate statistical analysis instrument for their selected data. This paper presents Research Statistical Analysis – Expert (RSA-Expert) which can be employed in selecting appropriate statistical instrument for a desired purpose. The Visirule software was used as a decision supporting tool, in which the rules are basically and precisely presented using Logic Programming Model. The RSA-Expert discussed in this work can be of great use to researchers in making a firm decision in utilizing suitable statistical data analysis in researches. Keywords: Research, Visirule, Analysis, Univariate, Bivariat

Exploring Robust Methods for Testing Equality of Stock Price Variances

Assessment and test of equality of volatilities of stocks with similar returns is important for decision makers in their portfolio selection. Volatility estimation is equally important for pricing stocks and derivative securities. In this study, three robust tests for homogeneity of variance are considered in the selection of stocks under the conditions of high kurtosis and large skewness. Investigations involved the effectiveness of the Ballett’s test, robust methods of Levene's Test and Fligner-Killeen test in the test of homogeneity of variance of stocks. Simulated and insurance stock data were employed and empirical results findings show that the three test statistics are equally efficient in testing homogeneity of variance even as the datasets deviates from normality

Effects of Solution Matrix on Moringa oleifera Seeds and Banana Peel in Eliminating Heavy Metals, Fluoride and Turbidity from Synthetic groundwater samples

Plant-based biomass has become an environmental-friendly water purification agent in replacing conventional chemicals. In the previous study, Moringa oleifera (MO) seeds and banana peel (BP) have been selected based on their moderate to high effectiveness in removing lead, cadmium, nickel, arsenic, turbidity, and fluoride from synthetic groundwater samples. This study was aimed to investigate further the effects of solution matrix on the biomass effectiveness. Batch experiments were conducted by using coagulation technique and the initial pH of the solutions was controlled to be at pH 7. The results demonstrate that the removal rates for most of the pollutants in multi-contaminant solution were higher compared to the single-contaminant solution. The reason could be due to electrostatic or mutual interactions between contaminants present in the solution thus improved the removal rates of those contaminants. The findings are significantly important to understand the effects and removal behavior of the biomass in different solution matrix

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Macorvian characteristics of the Nigerian stock market

Stock Market prediction has been one of the active research areas that have enjoyed attention in the fields of actuarial science and quantitative finance. This article investigates the Markovian characteristics of the Nigeria Stock Market using weekly data on All Share Index (ASI) market, 30- Index and five sub-sectors of Nigerian stock exchange from October 4, 2013 to September 30, 2016. The Chapman-Kolmogorov’s principles of handling transition probabilities and limiting distributions methods were employed for predicting future market behaviour. The findings suggest that compounded returns of the indices for the sectors and the market are highly volatile. The long-run distribution forecasts established that the market converged to stationarity after six weeks, while industrial sector has the shortest stationarity step period of five weeks. It is also observed that it will take about 31 weeks for the market and the 30-Index to reach the best return state, while about 78 weeks period is required to revert to the worst performing state. Further analysis findings of the mean return time suggest that it will take only about two weeks period for the indices returns of the market and the sectors under study to transit to the average state irrespective of the current state. Generally, the findings established the volatile nature of the market and its rapid tendency for deterioration. Finally, it is important to note that the 30-Index and ASI exhibit similar Markovian characteristics. It is pertinent to ensure strict compliance of the 30-Index stocks to the regulatory risk management frameworks for the robustness and sustainability of the market.Keywords: Markov Process, Nigeria Stock Market, All Share Index, limiting distribution, Mean return and First Passage time, Predictio