Empirical evidence singles out weekends as primary factors of trading as the week starts. The weekend after the effect has become one of the most intricate contexts for stocks forecasts with fewer experts managing to have a comprehensive resolve to cap stocks volatility. The markets, according to empirical evidence fluctuate if the corporate weather and the sustaining environment resonate with elements of the market weather. This means, if politics, currency trading, banking, and regulatory issues become better, stocks gain, and the market weather becomes better. A weekend provides one of the longest market dormancy timeframes; hence, stocks coagulate and take up implicit positions that profoundly affect the trading trends for the rest of the next trading week. This dogma is what this paper tries to make sense of.
Elements of the stock market weather vary in how they affect trading weeks. The need to have a comprehensive understanding of the weekend effect allows one to approach the context more rationally. Such insight provides a very good guide to understanding and investigating how the weekend affects the stock market’s functions. Normally, stocks resume trading on Mondays. The week after can be classified as the ‘previous trading week’ and its overall weather determines the overall effect of the weekend on the coming week’s trading.
The Monday share price is often unattractive. This is attributed to the weekend reaction to economic weather and sustainers of market stability, especially socio-politics. It is phenomenal that in the financial markets the resumption of trading on Monday signals a completely different trading trend, which decides the overall market behavior for the rest of the trading week. The weekend effect on stocks is an interesting study. As a factor, the weekend has an asymmetrical effect on stocks volatility. According to longitudinal research around the subject, market factor asymmetry influences the day-of-the-week effects on stocks volatility. Volatility can be defined as the fluctuating market price. The aspect of fluctuating comes along since the factors affecting the stocks, a market can cause a downward effect on daily trading, and that the stocks value and an upward effect on stock market prices. Various models of forecasting the impact of the day-of-the-week effect in stock markets exist. Each differs from either in modality.
The weekend effect is attributed not only to factors like politics and socio-economics but corporate weather wind. Many companies release their financial reports then. In most cases, corporations that are having crises often make announcements of their bad news on weekends. Empirical research shows that, when stocks return Monday, the prices and market trends are significantly lower in prices and robustness than those proceeding the last weeks trading during closing are. Some theories that explain this dogma state that, corporate weather news released on weekends depress the markets causing traders to prospect doom in the coming week trading. This is how a depressed stock market is created on Monday.
Short selling, a tendency of traders during the closing of a week’s trading is also blamed on depressing the subsequent weeks trading. Short selling in fact has a larger effect on stocks, especially high-short interest proneness. Traders fading optimism is also a factor, which causes the weekend effect to debilitate Monday and subsequent trading. Between Monday and Friday, many traders might feel frustrated by low returns subsequently causing their gain optimism to fade throughout the weekend. Such traders will not trade in the coming week, rather will prospect, and watch the market. This has a downward effect on the market since the number of traders is lessened hence the number of shares traded is minimal.
According to Connolly (1989), the weekend effect is the tendency for Monday stock returns to be negative rather than vibrant in comparison with the closing of the trading in the previous week. Connolly (1989) supports his observation by explaining how earnings announcement behavior and outliers are factors of influence. Factors of influence denote elements of market weather. These factors account for much of the evidence of systematically negative Monday returns. In these circumstances, the posterior odds favor the weekend effect hypothesis. The Monday effect has been extensively documented. According to Cho, Linton, and Whang (2006), there is a decline in the effect of the weekend effect on trading. Observations made on Monday effects on the UK stocks show that there is less effect on stocks vibrancy after weekends in comparison to the past.
In the UK, stock market analysts have been reporting that the weekend effect is gradually disappearing. The FTSE 100 and S&P 500 are less inclined to weekend effects on the stocks and a certain level of market vibrancy is evident. Cho, Linton, and Whang (2006) argue that the weekend effect continues to diminish as stock traders devise new forecasting methodologies and successfully tap into the markets without using public means.
Brusa, Liu, and Schulman (2000) explain the origin of the weekend effect theory by contextualizing how it was discovered that Monday stock prices vary significantly to the week closing stocks prices. To quantify this theoretical assertion, Brusa, Liu, and Schulman suggest a close-knit examination of the FTSE 100 and S&P 500 stock prices gains before the weekend and after the weekend. The aim was to determine the degree of change in prices and percentage gain or loss after the weekend.
French (1980), Gibbons and Hess (1981), Rogalski (1984), and Keim and Stambaugh (1984) have comprehensively documented the weekend effect on stocks. On the other hand, Cho, Linton, and Whang (2006) insist that some recent papers present evidence that the Monday effect in the US and UK stock markets has gradually disappeared. The same sentiment is shared by Fortune (1998). Fortune (1998) argues that the weekend effect on stocks ebbed in 1987. However, Fortunes projection is an overview foretelling the time when the diminishing of the weekend effect on stocks began to manifest.
According to Mehdian and Perry (2001) in the 1987-1998 period, Monday returns are not significantly different from returns during the rest of the week for the SP-500 indexes as observed by Cho, Linton, and Whang (2006). There is a growing trend in the research findings concerning the effect on S&P 500. However, there are dissenting views on the same context, with much literature stating otherwise and slightly agreeing in context, that there is a slight variation in market behaviors.
Coutts and Hayes (1999) also show empirically that the Monday effect exists but is not as strong as has been previously documented for the UK stock indexes a fact that Cho, Linton, and Whang (2006) and Steeley (2001) agree with. Wang, Li, and Erickson (1997) show that the Monday effect (negative returns) occurs primarily in the last two weeks of the month for a number of stock indexes consistently over the period 1962-1993, while returns for the first part of the month are not statistically significantly different from zero. Cho, Linton, and Whang (2006) point out that, the magnitude of the Monday effect and whether it is sufficiently large to generate profits based on simple trading rules should be quantified to allow debate and subsequent use of it as empirical evidence, French (1980).
Cho, Linton, and Whang (2006) have insisted that FTSE 100 needs a more critical examination in relation to the Weekend effect on its Monday and subsequent days trading. In comparison to findings made by Brusa, Liu, and Schulman (2000), the effect on trading by the weekend factor is still significant. The magnitude of the effect is a very important aspect of the FTSE 100 and S&P 500 trading counters. Brusa, Liu, and Schulman (2000) explain this by theoretically and using calculus whereby the quantify Monday is significantly positive for the sub-periods 1992 and 1993, as well as for the full sample period of five years for all the indexes. The finding of consistently positive Monday returns is a reversal of the weekend effect, Brusa, Liu, and Schulman (2000). Brusa, Liu, and Schulman (2000) contrast, the mean return for Friday is negative over the entire sample period of five years for all four indexes as advised by French (1980). These results also indicate a weak reversal of the findings by French (1980) who reported positive Friday returns in earlier data just as Brusa, Liu, and Schulman (2000) hoped to prove.
To investigate whether the reverse weekend effect is related to firm size, Brusa, Liu, and Schulman (2000) broke down the entire CRSP portfolio into ten sub-portfolios according to the size of firms as measured by their market value at the beginning of each year. Brusa, Liu, and Schulman (2000) argue that previous studies such as Gibbons and Hess (1981), and Keim and Stambaugh (1984) report that the magnitude of the weekend effect varies cross-sectionally with firm size motivate breaking down the full sample into sub-samples by firm size. Brusa, Liu, and Schulman (2000) suggest that these results show that the weekend effects for equally weighted indexes (which are more influenced by small firms) are constantly stronger than the weekend effect for value-weighted indexes (which Kamara (1997) points out as more dominated by large firms).
These dissenting views on the effectiveness of the weekend effect on the stocks demand a critical examination of literature that supports the idea. If there are price variations in how the trading takes place beginning Monday throughout the week, then there is an effect on the market prices and the overall trading. Hsieh (1988) insists that It is also important to understand that some stocks might be dormant and relatively cold to market volatility. These stocks might suffer almost nothing in terms of what caused a stir during the weekend causing a slackness or a sharp rise in stocks prices.
Research developing around how the weekend effect is still existent and that it has a significantly robust effect on trading quantifies the supposition by providing genuine market scenarios. Brusa, Liu, and Schulman (2000) used real-time stock prices and indexes to single out a pattern of fluctuating market prices. Cho, Linton, and Whang (2006) used the French (1980) calculations of market volatility to quantify that the weekend had a relatively significant effect on trading when trading resumed on Monday. Whether the Monday effect determined the closing of that trading week is still a subject requiring a lot of research. Chang, Jain, and Locke (1995) examined closing prices in the S&P 500 and the price trends when the trading resumed on Monday. Chang, Jain, and Locke (1995) found out that the behavior of future market prices was obscure especially when a periodic pattern was used to assess trading patterns. The pattern is used to observe the futures market when the prices in the underlying asset market Chang, Jain, and Locke (1995).
To quantify their findings that the market reacted on Monday after the closing of trading Chang, Jain, and Locke (1995) used a detailed analysis in this context to predict the S&P 500 futures price volatility. Chang, Jain, and Locke (1995) found out that the S&P 500 drops significantly immediately after the NYSE closes hence their analysis shows that, indeed, the futures market leads the stock market concerning the weekend effect and that S&P 500 Stock Index futures have negative price changes after the NYSE close on Friday.
Brusa, Liu, and Schulman insist that there is a strong positive autocorrelation between Friday returns and the following Monday returns wherein when Friday returns are positive (negative), the following Monday returns also tend to be positive (negative). However, Cho, Linton, and Whang (2006) have attempted to t ascertain theoretically the existence of a significant effect of the weekend on Monday trading. They point out that, Monday trading has a far more serious impact on the week’s trading than may be suggested literary. The correlates show a pattern of increased activity as investors scramble to make quick sales and buy throughout Friday as observed by Davidson and Dulcos (2000). At the closing, the companies make an announcement and any shift in goals has a ripple effect that is felt starting Monday. This effect can determine how the weekly trading might be. As such, Monday can be used as a market trend forecast. This view has been strongly supported by longitudinal studies around the subject.
The dominance of the weekend effect on FTSE 100 and S&P 500 was at peak 1997 – 2004. The market volatility and economic weather factors were affecting trading and trader behavior. It was found out that, Mondays are days that traders develop cold feet especially if there were announcements about financial markets. Many traders still rely heavily on hype to make decisions and choices. Due to the lengthy-time difference experienced, traders are afraid to resume trading and allow the experienced traders to start trading and once the half-day results are available, many stock traders will resume trading. This has been deemed farfetched yet, a survey done by Cho, Linton, and Whang (2006) proves that many traders developed cold feet on Monday.
Cho, Linton, and Whang (2006) argue that, as far as there are fewer traders in the market, the market capitalization is low and the number of stocks traded is significantly low. If the demand for the stocks is low, it is obvious the prices will fall drastically. Such a situation is very attractive to smart traders who will buy more stocks for holding en-masse. However, half-day results might provide a very attractive trend and that is why the traders with the Achilles’ foot will resume trading once they find the volatility aspect becoming prevalent during the rest of the day trading.
Cho, Linton, and Whang (2006) who argues that Individuals are net sellers on Mondays, and individuals behave differently on Mondays versus other days of the week support this perspective. Or else, it could also be due to short selling activity -short sellers close their position on Fridays, as it is difficult to monitor over weekends. Cho, Linton, and Whang (2006) single out the fact they sell the stocks on Monday leading to a fall in prices.
The release of bad news tends to be delayed until the weekend, French (1980). Steeley (2001) argues that the Monday effect in the UK stock market is related to the systematic pattern of market-wide news arrivals that concentrates between Tuesdays and Thursdays. Many traders depend on information about the markets to make decisions about selling and buying. Cho, Linton, and Whang (2006) found stronger weekend effects on trading on Monday. This fact makes Monday a very culpable parameter for weekly trading.
FTSE 100 and S&P 500 are today affected by the weekend effect on Monday trading trends. This aspect is blamed on a complex referred to as the ‘stochastic dominance.’ Cho, Linton, and Whang (2006) argue that Mondays are stochastically dominated by all other days. This point quantifies our earlier supposition that Monday dominates and has an effect on the weekly trading as suggested by Levy (2006). The Monday effect on weekly trading is derived from the Friday market capitalization and weather as the markets close for the weekend. As such, while Monday dominates three days of trading in exemption of itself, it is dominated by Friday’s outcome, especially as the trading closes for the weekend.
Here a dominance trend is observed, not periodically and erratically, but consistently. Monday draws its functionality from the previous week’s trading with a specific function from Friday. Friday is important since the week’s trading closes on Friday. Small stocks depend on the large holding stocks closing quotes to make closing quotes. If the large holding stocks quote good closing quotes, small stocks quote their closing marks. This scenario is relayed to traders who then spend their weekend awaiting resumption of trading on Monday. If the market closing quotes were good, traders will shun the markets since they expect the prices to be high hence poor returns, but if the closing quotes were bad news, many traders will trade early Monday with the hope of buying cheap stock and sell later at a profit.
However, many studies have found Monday stock returns significantly lower than Fridays. As such, the weekend effect rather depresses the market the subsequent week rather than stir it positively. Osborne (1962) and Cross (1973) discovered empirical evidence demonstrating that Monday yields were lower than Friday ones for the S&P 500 Index as suggested by Apolinario, Santana, and Sales (2006). In FTSE 500 stochastic dominance criteria, Cho, Linton, and Whang (2006) confirm earlier findings of a Monday effect for many series over the full sample. The weekend effect has weakened for some large-cap series like the DJIA and the S&P500 in the recent past but has been observed after investors and stock traders started counting on stock closing quotes to be ready for Monday and next week trading. However, the weekend effect has remained very strong for more broadly based indexes like FTSE 100 as observed by Cho, Linton, and Whang (2006).
In conclusion, the view that there is a Monday effect in FTSE 100 and S&P 500 indexes is very significant. The evidence is drawn from various previous literature and theoretical frameworks that have been used to assess the markets and their reaction to the weekend effect. We have singled out market capitalization as one of the strongest role players where the weekend effect on Monday and subsequent weekly trading is involved. Various factors are attributed to the weekend effect on FTSE 100 and S&P 500. These factors include trader reaction to stock closing quotes and economic weather. Traders shy away from the Monday trading if the Friday closing quotes showed a volatile market or an upward effect on prices. The upsurge discourages traders from resuming trading fearing higher prices and low turnovers as other sellers withhold stocks waiting for market capitalization to shrink and allow price fall to stimulate buying and selling. Cho, Linton, and Whang (2006). Argue that the evidence of stochastic dominance of Monday returns by other weekdays could be combined with behavioral theories from the psychology literature to create new asset-pricing theories. These theories according to Cho, Linton, and Whang (2006) can combine economic equilibrium concepts with psychological concepts to create an improved asset-pricing model. The psychological context denotes the trader’s reaction to stock closing quotes and market capitalization. Also, economic weather and stock market weather reaction to the fluctuation of its elements.
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