Chinese New Year is an important celebration that necessary been celebrated by all the Chinese in the world. That is more than 1.3 million Chinese around the world (World Popolation 2012, 2013), therefore, Chinese New Year already be treat as a important festival that necessary be celebrated and be include as a public holiday for most of the Asia country such as Malaysia, Singapore, Taiwan, China, Hong Kong, and South Korea (Chinese New Year, 2013). Stock market will be always changes according to the variation of environment such as different holiday on different country will affect the stock price differently.
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Chinese New Year is one of the holidays that will affect the stock market in most of the Asia country such as Malaysia. The stock market exchange will become anomalies on before, during and after the Chinese New Year period, which is known as Chinese New Year effect (Chinese Lunar New Year: Year of the Snake, 2013). Chinese New Year effect that occur in banking industry, may because by the different demand and purchasing on the market in before, during, and after Chinese New Year. For example, before the Chinese New Year is coming, most of the company will award yearend bonus to their employees. Besides, preparation before Chinese New Year such as buying some traditional New Year decoration, food, drink, clothing, shoes, and accessory. That will relatively increase the demand and purchase ability in a period of time (Chinese New Year, 2013). In this research, two stocks in same industry will be selected and the data period for both stock price and market index shall starts from 1st January 2007 until 2nd February 2012. Those will using the up to date data to observe the relationship between Chinese New Year and stock returns. Literature Review
January effect or called turn-of-the-year effect is a good example of seasonal abnormal in security markets around the world. During turn-of-the-year, certain types of securities produce positive abnormal returns. Stock prices tend to rise during the starting of the last trading day in December and ending on the fifth trading day of January. Rozeff and Kinney (1976) found a seasonal pattern in the New York Stock Exchange (NYSE) index over the period of 1904 to 1974. The average monthly return in January was about 3.5 percent, while the average return in other months was just 0.5 percent. The average return in January appeared to be seven times higher than returns for other months (Lim, Ng, & Chong, 2010). Keim (1983) found that the abnormal return is related to the stock market capitalization. As such, small capitalization stocks outperform large capitalization stocks in January, as small capitalization stocks post a higher abnormal return than large capitalization stocks. Reiganum (1983) confirmed that the January effect is a small capitalization phenomenon (Su, Dutta, Xu, & Ma, 2011).
Doyle and Chen (2009) suggested a weekday effect that the day-of-the-week changes over time. As pointed out by Cross (1973), the weekend effect involves negative returns to stocks between Friday and Monday’s close has been analyzed in the literature. Several studies have investigated the reversal of the weekend effect. Brusa, Liu, and Schulman (2000) discovered that Monday returns for U.S. stocks were positive and the largest during 1990s. Brusa, Liu, and Schulman (2003) showed that weekend and reverse weekend effects exist in a wide range of industries and that the effects are similar across months. Brusa and Liu (2004) found that the positive Monday returns are concentrated in the first and third weeks of each month, while Brusa, Lui, and Schulman (2005) showed that the reverse weekend effect is correlated with the previous Friday return. Thus, positive Monday returns for large stocks are likely to be observed after positive Friday returns.
These seasonal abnormal include holiday effect, day-of-the-week effect, and month-end effect. Most of the interests are seasonality began in 1966 when a market technician, Arthur Merrill, identified an obvious trend of stock prices on certain days of the week, at certain times of the month, and around holiday seasons. MerrillâÃ¢â€šÂ¬Ã¢â€žÂ¢s (1966) work on literature aimed at both identification and explanation of these seasonal irregularities in asset returns. Several studies have studied the securities prices having abnormal returns over the weekend, that is, the day-of-the-week effect. French (1980) shows that US common stocks held over the weekend earn a small negative return (Does seasonality in the Kuala Lumpur Stock Exchange still exist). Gibbons and Hess (1981), and Keim and Stambaugh (1984) also provide empirical evidence that supports this weekly stock return. Ariel (1987) examines US. stock indices returns from 1961 to 1981 and finds stocks appear to earn positive average returns only around the beginning and during the first half of calendar months, and zero average returns during the second half.
According to the efficient market hypothesis (EMH) by Fama (1970), stock prices follow randomly and past information cannot be used to predict the future. Therefore, there should be no abnormal returns on special occasions such as holidays. Lakonishok and Smidt (1988) significant return before US public holidays. These pre-holiday returns are two to five times higher than returns before a weekend and 23 times higher than those on normal days. These results are confirmed by several other studies, such as Pettengill (1989) and Ariel (1990). These studies all focus on developed financial markets (Dodd & Gakhovich, 2011). A number of studies have also examined the post holiday effect. Lakonishok and Smidt (1988) find insignificant post-holiday returns until 1952 and significant positive returns afterwards. However, Kim and Park (1994) document negative post holiday returns for the UK, and Lee et al. (1990) for Korea and Singapore. The magnitude and statistical significance of pre holiday returns may vary on specific holidays. Returns prior to religious holidays tend to be higher than returns of other holidays. Chan et al. (1996) show significant pre-holiday effects before cultural holidays in Asia. Specifically, Malaysia sees abnormal returns before Chinese New Year.
Gao and Kling (2005) also found a pattern of market return in both Shenzhen and Shanghai stock exchanges with the highest return in February, but it is insignificant as well. The explanation for the seasonal high return in February in China is that February is the turn-of-the-year in China, as the Chinese Lunar New Year usually begins in late January or sometime during February, rather than the calendar year. However, Zhang and Sun (2003) by examining the seasonal anomalies in China, reported that there is no January effect or a February Chinese New Year effect on the Chinese stock market. But a significant and positive March effect was found. The explanation is interesting that they consider that the March effect in China reveals the political nature of financial anomalies in the country. March is the political high season in China and in March political window-dressing is caused by political maneuvers (Chinese New Year, 2013). Methodology In order to examine the impact of Chinese New Year on the stock performance in 2012, we is required to select two stocks in the same industry and also searching for their daily stock prices from the yahoo finance. After that, download the daily market index of Malaysia such as FBM KLCI from the yahoo finance. The industry be chooses is financial industry and the two stocks be chooses is Hong Leong Bank and Public Bank. Next, the data period for both stock price and the market index are starts from 1st Jan 2007 until 2nd Feb 2012. The event window for these two stocks is -5 to +5 it is mean that is lags 5 days and leads 5 days are used for the detection of CNY effects. The event day is set as 0 and the period from 1st Jan 2007 to -6 serves for the estimation period. In terms of the calculation, we are required to estimate the daily returns for the both stocks that chooses and FBM KLCI. Second, regress the stock return against market returns in the estimation period (1st Jan 2007 until 2nd Feb 2012) in order to estimate alpha and beta coefficient for the companyâÃ¢â€šÂ¬Ã¢â€žÂ¢s stock ( Hong Leong Bank and Public Bank). Third, apply the estimated alpha and beta coefficient in the Capital Asset Pricing Model (CAPM) in purpose to compute the expected return of companyâÃ¢â€šÂ¬Ã¢â€žÂ¢s stock in the event window by using Capital Asset Pricing Model (CAPM) formula. Capital Asset Pricing Model (CAPM) formula as follow: Where: = risk free rate = Beta = return on market Then, subtracting expected return from the estimated return in order to calculate the abnormal return (AR). The formula as following: Where: R = estimated return E(R) = expected return Where: P = Price t = Period of year Analysis Table 1 Event window of Hong Leong Bank Hong Leong Bank Date R(i) R(m) AR 2012/1/16 -5 0 -0.00924 0.002544 2012/1/17 -4 0.0018365 0.006802 -0.00083 2012/1/18 -3 0 -0.0013 -3.2E-05 2012/1/19 -2 0.0091325 -0.00038 0.008799 2012/1/20 -1 0.0090498 0.003849 0.007346 2012/1/23 0 0 0 -0.00045 2012/1/24 0 0 0 -0.00045 2012/1/25 1 0.0178576 -0.00191 0.018021 2012/1/26 2 0.0262024 0.002694 0.024873 2012/1/27 3 0.0085837 -0.00194 0.00876 2012/1/30 4 -0.0172418 -0.00484 -0.01612 2012/1/31 5 -0.0122486 0.005101 -0.01436 Graph 1 The table 1and graph 1are showing the stock price flow of Hong Leong Bank in the pre-Chinese New Year until post-Chinese New Year. According to the graph, we can realize that the stock price is flowing downward before the 3 or 4 days of CNY. In the financial industry, that will be a normal situation will be form before the CNY. This condition may be cause by the large funds transfer before the CNY especially for the company. Normally, most of the company will award the yearend bonus to their employees before the CNY (Chinese New Year, 2013). Bonuses usually be given is 2 or 3 month or more than 3 month per person, therefore, there will be a large funds transfer between the company and bank. Besides, for the individual will many increase their funds transfer in order to make some preparation before Chinese New Year such as buying some traditional New Year decoration, food, drink, clothing, shoes, and accessory. That many because by the Chinese New Year effect however that also may be affect other effect such as holiday effect. The magnitude and statistical significance of pre holiday returns may vary on specific holidays. Returns prior to religious holidays tend to be higher than returns of other holidays. Table 2 Event window of Public Bank Public Bank Date R(i) R(m) AR 2012/1/16 -5 -0.00152 -0.00924 0.000724 2012/1/17 -4 0.00304 0.006802 0.000778 2012/1/18 -3 0.004542 -0.0013 0.004557 2012/1/19 -2 0.001509 -0.00038 0.001264 2012/1/20 -1 0.003012 0.003849 0.00158 2012/1/23 0 0 0 -0.00035 2012/1/24 0 0 0 -0.00035 2012/1/25 1 0.001503 -0.00191 0.001687 2012/1/26 2 0.005988 0.002694 0.00488 2012/1/27 3 0.002981 -0.00194 0.003176 2012/1/30 4 0.005935 -0.00484 0.006944 2012/1/31 5 0.001478 0.005101 -0.00031 Graph 2 The table 2 and graph 2 are showing the stock price flow of the public Bank in the pre-Chinese New Year until post-Chinese New Year. For the stock price flow of Public Bank we can realize that there are pretty similar with the Hong Leong Bank, however this similarity may because by the Chinese New Year period effect. However the stock price of Public Bank may also be affect by the announcement that announce before the CNY which is on January 11, 2012 (Gerenal Announcement, 2012). This announcement can be categories as a general effect and that will affect the performing of the stock market. General effect means that, this effect may be usually happen in any time anyway. Conclusion According to the two tables and graph above, we can realize that both of the graphs are showing the similes flowing in before, during and after the CNY. However, that is some different between this both stock that choose specially in middle of the CNY. In the middle of the CNY, the stock price of both bank are starting going upward. The stock price of Hong Leong Bank are direct climbed to a high point and then slipped. Public Bank stock price are starting going upward and slipped a little bit, after that direct climbed to a high point and then slipped. That may be related to the announcement that Public Bank announce on January 11, 2012.
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