Theoretical Review of Effect of Firm Specific Factors on Performance of Initial Public Offering Stocks at the Nairobi Securities Exchange in Kenya

Abstract

During the period 1994 to 2020, a total of 18 firms in Kenya floated 16,530,781,060 shares at the Nairobi Securities Exchange (NSE) under Initial Public Offerings (IPOs) raising over Kshs 91 billion. These stocks were significantly over-subscribed with the highest hitting 830%. The NSE became fully automated in 2006. Similarly, in Africa between 2010 and 2019 there were a total of 215 IPOs raising over Kshs 1.6 trillion. This could be explained by divergence of opinion hypothesis. The initial returns were positive. However, in the long run, most of the firms underperformed. This under performance leads to losses incurred by investors and possible collapse of brokerage and investment firms leaving investors with a bitter taste. This study will undertake to establish the effects of firm specific factors on IPO stock performance at the NSE in Kenya. The specific objectives will be: to establish the effect of firm size on performance of IPO stocks at the NSE in Kenya, to determine the effect of age of firm on performance of IPO stocks at the NSE in Kenya, to evaluate the effect of firm board composition on performance of IPO stocks at the NSE in Kenya, to establish the effect of firm ownership structure on performance of IPO stocks at the NSE in Kenya, and to analyze the moderating effect of automation on the firm specific factors and performance of IPO stocks at the NSE in Kenya. The study will be built upon major theoretical streams: Random Walk theory, Winners curse theory, Dow Theory, Signaling theory and Agency theory and contextualize them to firm specific factors and performance of IPO stocks. More studies have previously been undertaken on the pricing of IPO at the NSE in Kenya and the few that studied on performance of IPO stocks at the NSE in Kenya have provided mixed findings depending on the methodology used. None of the studies asfar as research has shown have considered the automation of NSE in Kenya as a moderating effect of performance of IPO stocks. The sample size will be the same as population of 18 IPO firms between 1994 and 2020 with 8 IPOs during pre-automation and 10 IPOs post-automation period. This will be a longitudinal and event study that will adopt a descriptive study design. Data will be analyzed using the Econometric Views (Eviews). Hausman test, Augmented Dickey Fuller (ADF) test and other diagnostic tests will be applied to the panel data. The Capital Assets Pricing Model (CAPM) and the Nairobi 20 Share Index will be used as the benchmarks of performance of IPO stocks.