This paper examines the volatility of the daily returns of Nigerian insurance stocks. Using empirical analysis, the study shows that the Exponential Generalized Autoregressive Conditional Heteroskedastic (EGARCH) model is more suitable in modelling stock price returns as it outperforms the other models in model-estimation evaluation and out-of-sample volatility forecasting. Given the cardinal role of insurance in Nigeria's risk management system the present findings can be useful in

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... g insurance industry's stock risk. The policy implications are also considered. 1. Introduction Volatility modelling and forecasting have attracted much attention in recent years in emerging stock markets. For instance, many asset-pricing models used volatility estimates as a simple actuarial risk measure. In Nigeria volatility modelling and forecasting has not attracted the deserved attention possibly because the stock market is largely under-developed. This phenomenon is more pronounced in the insurance sector where many of the players appear to deliberately avoid listing on the stock exchange because no information would then need to be disclosed to their shareholders. However, changes are being observed as the last two decades have seen accelerated growth of insurance markets. Arena (2006) reports that "emerging markets have recently experienced significantly faster real growth of their insurance sectors than industrialized countries reflecting liberalization and financial integration, usually following the implementation of structural reforms". Recapitalization of the insurance industry in Nigeria has no doubt recorded a huge volume of business, the sector was able to pull an aggregate gross premium income of N90 billion in 2006, over 18% more than 2005. Moreover, Nigerian investors' attitude and perception of insurance stocks are dramatically changing positively. In fact, discerning investors have since identified insurance stocks as a very important investment line since most of the insurance stocks are having impressive returns (Ibiwoye and Adeleke, 2008). Hence, there is currently a high level of investors' interest for insurance stocks in the market and subsequently a high level of volatility. Therefore, hedging against risk and for portfolio management, reliable risk volatility estimates and forecasts of these stocks are quite useful and need to be investigated. In Nigeria, volatility modelling and forecasting have not attracted much attention for the simple reason that the stock market is largely undeveloped. The few exceptions have been the study by Ologunde et al (2006) which fitted a regression model to the relationship between market capitalization and interest rate, Ibiwoye & Adeleke (2008) who analysed price movements in insurance stocks pre-and post-2005 consolidation and that of Olowe (2009) on the impact of the 2005 re-capitalization of the insurance industry on the stock market. This paper fills the gap in the emerging economy literature by investigating the volatility of Nigerian insurance stocks returns using heteroskedastic conditional volatility models. Literature Review The pervasive daily return volatility in equity stock markets has attracted considerable attention in the literature in recent times (Galeotti and Schiantarelli, 1994; Mankiw et al 1991; Kumar and Makhija, 1986, Schwert, 1989; Eraker, 2004). Mathematical models are usually employed to predict the future behavior of stock prices because most transactions in stocks, whether to buy or sell, are activities that take place in the future (Chauvin, 2006). In the International Business Research Vol. 3, No. 2; April 2010 107 Akaike, H. (1978). A Bayesian analysis of the minimum AIC procedure.