Empirical findings and analysis
This part presents the results of the statistical investigations. Day-of-the-week effects are first identified and analysed, which is followed by a similar investigation of month-of-the-year effects. Finally, the findings are used to develop two investment strategies, a day-of-the week strategy and a month-of-the-year strategy.
Investigation of day-of-the-week effects 1993-2011
Figure 4.1 shows the average daily returns over the full sample period, stretching from January 1st 1993 to December 31st 2011. Negative returns are recorded in the first two days of the week with Monday returns of -0.0074% being the lowest. With positive re-turns concentrated to the last three trading days of the week, a positive trend can be identified as the weekend approaches, with a Friday return of 0.0089% being the highest of the week.
The return distribution found in this investigation largely support the findings of Cross (1973), French (1980), Gibbons & Hess (1981) and Keim & Stambaugh (1984), who all found evidence of negative Monday returns and high Wednesday and Friday returns in the US markets. The study also support the findings of Hui (2005) who found evidence of particularly low Monday and Tuesday returns, and high returns on Wednesdays and Fridays in his study of the Singapore markets between 1998 and 2001.
Table 4.1 summarizes the average returns, standard deviations and t-statistics of each weekday over the full sample period, and the only statistically significant day-of-the-week effect is a negative Monday effect. While a weekend effect cannot be statistically confirmed, the existence of a negative Monday effect supports the idea that individual investors are more active sellers of stocks on Mondays. Behavioural finance offers one possible explanation to such behaviour in the latent selling need that arises partially from negative news releases after the market close on Fridays (Kumari & Raj, 2006). Over the weekend, investors have more time to reflect over bad news and analyse their portfolios, and consequently, a large number of investors are waiting for the stock ex-change to open on Mondays to alter their holdings after the weekend.
The day-of-the-week effect 2006-2011
Table 4.2 summarizes the average returns, standard deviations and t-statistics for the most recent sub-period in which there is no evidence of a significant day-of-the-week effect.
The day-of-the-week effect 2000-2005
Table 4.3 summarizes the average returns, standard deviations and t-statistics for the pe-riod 2000 to 2005, which is the only sub-period in which day-of-the-week effects are proven. Just as over the full sample period, a negative Monday effect is present in this sub-period, while there is also evidence of a positive Friday effect. Consequently, the well-documented weekend effect is proven. Interestingly, the negative Monday effect is also associated with the highest volatility, while the positive Friday effect occurs on the day with the least volatile returns.
The day-of-the-week effect 1993-1999
Table 4.4 summarizes the average returns, standard deviations and t-statistics of the earliest sub-period in which there is no evidence of a day-of-a-week effect.
Summarizing analysis: day-of-the-week effects 1993-2011
Over the full sample period, a negative Monday effect is present in the STI. While Fri-days historically yield the highest returns and Mondays the lowest, the weekend effect is only statistically proven during the period between 2000 and 2005. By confirming the existence of a day-of-the-week effect, this study suggests that the Singapore stock mar-ket is not as efficient as suggested by the EMH, and an irrational trading pattern may exist amongst both individual and institutional investors. Behavioural finance offers a possible explanation to such behaviours, suggesting that sales volumes increase on Mondays as a result of a latent selling need amongst investors after a trading-free week-end. Cross (1973) along with a number of other researchers has found evidence of a negative Monday effect in US markets, while in Singapore, Hui (2005) found a similar effect over the period 1998 to 2001. The EMH suggests that market anomalies should disappear over time (Fama, 1998), and the fact that this study has confirmed the existence of a persistent negative Monday effect over a 19-year period raises further doubts about the validity of the EMH.
This study shows that the presence of day-of-the-week effects in the STI varies over time. While the accumulated results of the full 19-year sample period show evidence of a significant negative Monday effect, only one of the three sub-periods shows evidence of significant day-of-the-week effects. In the second sub-period, 2000 to 2005, both a negative Monday effect and a positive Friday effect are identified and consequently, the weekend effect is present in the Singapore stock market. However, no day-of-the-week effects are confirmed in the first sub-period, 1993 to 1999, nor in the most recent sub-period 2006 to 2011. Despite the varying presence of day-of-the-week effects in the in-dividual sub-periods, the fact that a negative Monday effect is documented over the full sample period is interesting for investors with a long-term investment horizon.
Investigation of month-of-the-year effects 1993-2011
Figure .2 shows the average monthly returns over the full sample period, stretching from January 1st 1993 to December 31st 2011. Negative returns occur in five months of the year, and historically, the period in August and September is a particularly bad peri-od to hold stocks. Interestingly, in contrast to most studies of western markets, a nega-tive January effect is apparent, while other negative returns are recorded in March and May. Seven months offer positive returns, with November and December being two es-pecially good months for investors. April returns of 3.03% are by far the highest, while positive returns are also observed in February, June, July and October.
2 Theoretical background
2.1 The Singapore Exchange
2.2 The Straits Times Index
2.3 Price development of the Straits Times Index 1993-2011
2.4 Seasonal anomalies
2.5 Mainstream finance theory
2.6 Behavioural finance
2.7 The link between behavioural finance and seasonal anomalies
2.8 Review of previous studies on seasonal anomalies
3.1 Delimitation and selection
3.2 Data collection
3.3 Empirical method
4 Empirical findings and analysis
4.1 Investigation of day-of-the-week-effects 1993-2011
4.2 Investigation of month-of-the-year effects 1993-2011
4.3 Development of investment strategies
6 Suggestions for further research
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