Day of the Week Effect and the Returns of Stocks Listed at the Nairobi Securities Exchange in Kenya

Abstract

One of the major components of7 the7 financial7 markets are the securities markets7 of7 the7world. An efficient market is an indicator of market prices reflecting available information about the fundamental values of a company. A conventional distribution of returns to a financial asset indicates that anticipated returns for7 all7 days7 of7 the7week, known as the day7 of7 the7week, are the same. And investor at the NSE looks to getting a return on their investments. The studies moderating variable is the change in price of the daily volumes traded. This study sought to find out if there were significant deviations in the conclusions arrived at on the days that had highest positive returns at the NSE for the period starting January 1st 2012 and ending December 31st 2018. If the deviation in daily return are in accordance to observations made in past studies as no studies were done within the aforementioned period. The general objective7 of7 this7 study7 was to investigate the effects of the day-of-the-week effect and the returns of stocks listed at the Nairobi Securities Exchange in Kenya. The study was guided by the following specific objectives of the study: to establish the Mondays Effect and the returns of stocks listed on the7 Nairobi7 Securities7Exchange; to7 examine the Tuesdays Effect and the returns of stocks listed7 on7 the7 Nairobi7Securities7Exchange; to7 determine7 Wednesdays7 Effect and the returns of stocks listed7 on7 the7 Nairobi7Securities7Exchange; to7determine7 Thursdays Effect and the returns of stocks listed7 on7 the7 Nairobi7Securities7Exchange7and7to7 establish Fridays Effect exists and the returns7 of7 stocks7 listed7 on7 the7 Nairobi7Securities7Exchange. The study was under pinned by three theories which included the Behavioural Finance Theory, Efficient Market Hypothesis and Adaptive Markets Hypothesis. This study adopts the positivity philosophy. This study used a longitudinal descriptive research design. The population of this study comprised of the firms listed in the 20 Share Index at the NSE for7 the7 period7 January7 20127 to7 December72018. Out of the 20 listed companies at the 20 Share Index at the NSE, the study sampled, by use of purposive sampling, 10 companies. The data required was collected from7NSE. Data7 for7 the7 seven-year7 period7 1st7 January7 20127 to7 31st7 December7 2018 was sourced from the NSE website and NSE trading data vendors. The study used both descriptive statistics and inferential statistics. The study found a direct relationship between new information flow into the market and daily price volatility and daily volumes traded. It was observed that there was a direct link between large volumes and large price change, whether up or down price movement, and can be linked directly to information flow into the market. The study concluded that there was a direct link between large volumes and large price change, whether up or down price movement, and can be linked directly to information flow into the market. The study recommended that traders should ensure that they familiarize themselves with strategies that will maximize returns while reducing on transaction costs.