In this paper, the optimal investment strategy for a defined contribution (DC) pension scheme was modeled with the assumption that the fund is invested partly in riskless assets and partly in risky assets. The market has a constant interest rate, a stochastic volatility that follows the Heston model, the salary is assumed constant over the entire career of the Pension Plan Participant (PPP) and the contribution is a constant proportion of the salary. The CRRA utility function was utilized to obtain a Hamilton-Jacobi-Bellman (HJB) equation. The resulting HJB equation was solved using the Prandtl Asymptotic Matching Method following the works in the literature.

In this paper, the relationship between some selected stocks in the Nigerian Capital Market was investigated using wavelet analysis. The selected stocks are Dangote Cement (Dans) representing the housing sector, Julius Berger (Jbger) representing the Construction industry, Nestle Nigerian Plc (Nese) representing the food and beverages sector and United Bank of Africa (Ubas) representing the banking sector. The goal is to find out how the different sector relate to each other, t also serve as a guide for investors in the Nigerian stock Market. The result shows that on low frequencies, the coherence between stocks are low but volatile. The cross wavelet showed that there is little or no covariability in the magnitude of the movement among the selected stocks but there are co-variability in the direction of the movement. The continuous wavelet transform (wavelet spectrum) shows that for all the stocks, there is high volatility at the low frequency scales and low volatility at high frequency scales. The discrete wavelet transform (DWT) suggests that in the absence of noise, Nese (representing the food and beverage industry is the most volatile stock.

Exchange rate is very pivotal in its role in the economy of any nation especially as a result of globalization. This paper seeks to model the Nigerian economy proxied by the log of Gross Domestic Product (LGDP) and its relationship with other variables in the economy. The variables used are NGN/USD exchange rate (NAIRA), log of oil revenue (LOILREV), log of government expenditure. We estimated the model using the Vector Autoregressive (VAR) model. We tested the presence or otherwise of causality among the variables using the method of Granger. The result reveals that the optimal lag for the model was 1. The exchange rate was found to Granger cause the economy (LGDP), LOILREV (Oil Revenue) and LGEXP (Government expenditure). We also discovered that the dynamics of NAIRA was not fully captured by the variables used. We also pointed out the shock persistence of NAIRA in time.