Stock market returns are predictable from a variety of financial and macroeconomic variables and have long been an attraction for equity investors. Recently increasing attention has shifted on the market index as a method of measuring a section of the stock market. The stock market index is regarded as an important indicator by the investing public at large and can be used as a benchmark by which investor or fund manager compares the returns of their own portfolio.In this study, attempts are made to model the Nigerian stock market index using a structural model. The procedure is based on the relationship between the state space and the autoregressive moving average (ARMA) model. The time series procedure from S-PLUS software is used in the analysis. The result obtained shows that the Nigerian stock market price index is an autoregressive model (AR) of order 1. It is also found that the AIC is at minimum at lag 1which corresponds to the same model identified for the series by using the sample ACF and PACF.

This work provides a new statistical distribution named Cubic rank transmuted Inverse Weibull distribution which was developed using the cubic transmutation map. Various statistical properties of the new distribution which includes: hazard function, moments, moment generating function, skewness, kurtosis, Renyl entropy and the order statistics were studied. A maximum likelihood estimation method was used in estimating the parameters of the distribution. Applications to real data set show the tractability of the distribution over other distributions and its sub-model.