What Does Calendar Anomaly Exist? Stock Market Of Both Developed And Developing Countries

The weekly performance of IBM stock presented a contestant growth. One highlight of the falling of stock price in the 6th week in the investment period was when IBM presented the 3rd quarter financial report. The investors weren’t satisfied with the profit report which they expected to be better especially when other IT companies were doing well in the 3rd quarter. One mistake I made was that I didn’t follow closely to the financial report of the company; therefore, I missed the peak of the stock price. From this experience, I learned that financial reports and current news are important indicators of the stock price. By following closely to the current event and analyzing the financial report, investors can maximize the profit and also become more familiar to the market.

Capital markets provide a function which facilitates the buying and selling of long-term financial securities to increase liquidity and their value, Watson & Head (2013). Hence, the Efficient Market Hypothesis (EMH) explains the relationship that exists with the prices of the capital market securities, where no individual can beat the market by regularly buying securities at a lower price than it should be. This means that in order to be an efficient market prices of securities will have to fairly and fully reflect all available information, Fama (1970). Consequently, Watson & Head (2013) believe that market efficiency refers to the speed and quality of how share price adjusts to new information. Nevertheless, the testing of the efficient markets has led to the recognition of three different forms of efficiency in which explains how information available is used within the market. In this essay, the EMH will be analysed; testing of EMH will show that the model does provide strong evidence to explain share behaviour but also anomalies will be discussed that refutes the EMH. Therefore, a judgment will be made to see which structure explains the efficient market and whether there are some implications with the EMH, as a whole.

Seasonal Affective disorder is a type of depression that happens when the seasons change. According to the Mayo Clinic, seasonal affective disorder starts at the same time each year normally in the fall and continuing through winter. Those who suffer from Seasonal affective disorder feel like their energy is being sapped out of them and becoming more moody. (Seasonal Affective Disorder (SAD)) People who have SAD will often have light depression in the spring and early summer. This will mostly impact people who do things for the holidays. This time of year is already stressful for most but for those who have seasonal affective disorder it will be ten times harder for them to get things

Given the event date and stock price data, the EP and TP can be constructed in order to estimate the normal returns and abnormal returns respectively.

Seasonal factors are defined as “the amount of correction needed in a time series to adjust for the season of the year” (Chase, Jacobs, & Aquilano, 2006, Chapter 13). The word seasonal does not always mean weather. Seasonal in business terms is usually classified as an activity of some sort. In my situation, I don’t have any seasonal factors that can affect my morning routine. My husband has already left the house and I am alone in a stable environment (my home).

Now, it is important to look to the future trends in order to predict seasonal factors. “A seasonal factor is the amount of correction needed in a time series to adjust for the season of the year.” (Chase, Jacobs & Anquilano, 533) Seasonal factors may affect the samples by taking into consideration factor based on seasons or time periods. The alarm clock that is used to wake me up in the morning is not dependent on any factors of time or season.

A great number of studies further identified several factors which particularly concerns market capitalisation, effective of stock market, etc., which explains the dynamic forces of stocks returns during the earnings announcements date in an organised manner. For instance, Atiase (1985) found that unexpected information pass on to the market by actual earnings report is inversely correlated to the company’s capitalisation. Grant (1990) observed that the market in which a company’s securities are traded often determined the behaviour of stocks return around the earnings announcements. Several other studies have aimed to organise for synchronise factors by using time series data such as intra-day and daily data. However, a fairly number of more robust studies has examined the information content of macroeconomics news releases. Elsharkawy and Garrod (1996), Pope and Inyangete (1992).

In the last three months of 2008, under the general decline in the global stock market, numerous Asian stock markets were in free fall. The key stock index such as Nikkei 225 in Japan, Hangseng in Hongkong and Sensex in India suffered significant drops. (Rose & Spiegel, 2009)

In early 2016, the U.S. stock market experienced its worst two week start in history, experiencing what is known as a correction, which is defined as a decline of at least 10% from recent highs. The major factor behind the correction was fear over the Chinese economy. China worried the world economy when its stock market was performing very poorly. In the summer of 2015, it took weeks for world markets to react to China’s market crashing. However, on January 4, 2016, the world felt the effects of China’s crash almost immediately. News from the private index of Chinese manufacturing data

In this article, “Is the efficient market hypothesis day-of-the-week dependent,”, Stephen Pop reveals significant evidence that the efficient market hypothesis is day-of-the-week-dependent. Overall, for only 62% of firms, the unit root null hypothesis is rejected on all the five trading days. He also discovers that when investors do not account for unit root properties in devising trading strategies, they obtain spurious

Due to the turbulence of global economic crash, the high volatility appeared in Woolworth’s share price returns from January 2007 to June 2009, the return rate is floating widely. The most serious market crash happened on 9th September 2008 （－13.50％）. During this period of time, the investors had a difficult time. By contrast, there is a low volatility clustering from Jan-11 to Jun-11

In this project we first checked consistency and seasonality of S&P500 index stock performance by splitting its recent twenty years historical data into ten two year data and built ARIMA and GARCH models for each sub-period. We found that the models are considerably consistent before 2007-2008 sub-period, and there exists some minor seasonality in several subperiods, but no particular pattern can be identified for the whole period. We then tried to predict future return, volatility and VaR using the model we built for the last sub-period based on rolling forecast procedure. Though the fitted values of 10th sub-period model are

Jegadeesh, Narasimhan , “Evidence of predictable behavior of security returns,” Journal of Finance 45, 881-898., 1990

This can be analysed using either the multiplicative or additive method. In the additive version, seasonality is expressed as a quantity to be added to or subtracted from the series average. For the multiplicative model seasonality is expressed as a percentage (seasonal relatives or seasonal indexes) of the average (or trend). These are then multiplied times values in order to incorporate seasonality.

In this research, we use Hongkong stock data to estimate Chinese stock market because most of the big Chinese business companies are listed in Hongkong stock market (Hongkong actual return data in the left hand was from Thomson Reuters’ Datastream). This actual return data was gathered for all firms listed in Hong Kong Research List (equity list name is HGKG). Moreover, there are many different portfolios in this data. We require the security which is traded on the country’s major exchanges and exclude real estate investment trusts, global depository receipts, and preferred stocks. Also, we decide that the returns from some months are set to missing if the total return index is unchanged for three months in a row. The reason why we do this is to