Abstract:
his study examines calendar effect anomalies, particularly Day-of-the Week effect and Month-of-the-Year effect and stock returns volatility in Ghana
Stock Exchange (GSE) and Nairobi Stock Exchange (NSE). Daily closing prices
indices from the two stock markets for the period 2005 to 2014 was used. Using an
Ordinary Least Square (OLS) regression with autoregressive term, the findings
provide no evidence of day-of-the-week effect for GSE but there exist Friday effect
for NSE. However, the study provides no evidence of month-of-the-year effect
anomaly in either NSE or GSE. The study also documents that daily returns could
be predicted but monthly returns cannot be predicted in NSE. On the contrary, the
findings indicate that whiles daily returns are difficult to predict monthly returns
can be predicted using past price and returns information in GSE.
Furthermore, Generalised Autoregressive Conditional Heteroskedastic
GARCH (1, 1) Threshold GARCH (1, 1) and Exponential GARCH (1, 1) were
employed to examine stock returns volatility. The results of the GARCH model
suggest a high degree of persistent in the conditional volatility of daily and monthly
stock returns in NSE. The TGARCH, and EARCH models show significant
evidence for asymmetry (leverage effect) in monthly stock returns but no evidence
of asymmetry in daily returns was found in NSE. However, there was no evidence
of conditional volatility for Ghana Stock Exchange Composite Index (GSE-CI).
The study concludes that GSE and NSE are inefficient markets. It is recommended
that months are irrelevant in making investment decisions in GSE or NSE but days
of the week are relevant in NSE only
