MODELING THE VOLATILITY FOR LONG TERM INTEREST RATE RETURNS IN THE NIGERIA BOND MARKET USING CONDITIONALY HETEROSCEDASTIC MODELS

Investigating the volatility of financial assets is fundamental to risk management. This study used generalized Autoregressive Conditional Heteroscedastic Volatility models to evaluate the volatility of the long term interest rate of Nigeria's financial market. We also incorporated three innovations distributions viz: the Gaussian, the student-t, and the Generalized Error Distribution (GED) in the modeling process under the maximum likelihood estimation method. The results show that GARCH (GED) is the most performing model for describing the volatility of three and twenty-year interest rate returns while TARCH (GED) is the most suitable model for describing the volatility of five and ten-year interest rate returns in Nigeria. The preferred models will help in the development of tools for effective risk management by monitoring the behavior of long term interest rates. &nbsp

Using Information Technology In Teaching Of Business Statistics In Nigeria Business School

This paper discusses the use of Microsoft Excel software in the teaching of statistics in the Faculty of Business Administration at the University of Lagos, Nigeria. Problems associated with existing traditional methods are identified and a novel pedagogy using Excel is proposed. The advantages of using this software over other specialized statistical packages (SPSS, Minitab or Stata) are simplicity, universality, accessibility, increased acquisition of skills, and, more importantly, reduced cost for students and instructors alike particularly for those in developing economies. Several examples are introduced to illustrate the use of Excel in teaching statistics in a business school. Moreover, this proposition is partially motivated by an intervention program funded by the USAID that resulted in the acquisition of information and communication technology (ICT) laboratories

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