Event Study of Saic Stock Price

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

The strong form claims that asset prices fully reflect all of the public and inside information available, therefore no one can have advantage on the market in predicting prices. The introduction of the efficient market hypothesis marked a turning point in scholarly researches on security prices and many studies have been made since to test market efficiency. Many studies of the weak form of market efficiency have been made on technical analyses and how investors use them to predict about future security prices by looking at past prices. In 1969 Fama, Fisher, Jensen and Roll were the first to test the semi-strong form of market efficiency by using event studies. Their conclusion was that stock prices adjust very rapidly to new information. Many scholars since then have studied how new information affect the market by using event studies. Many articles about the strong form have also been published and most of them study professional investor performances in the stock market (Malkiel, 2003). Many of the studies on technical analyses, event studies and the performance of professional investors in the stock market have reached the conclusion that markets are efficient and therefore that stock prices are right (Malkiel, 2003). Before studies of behavioral finance became popular, evidences began to appear that were inconsistent with the hypothesis of market efficiency.

5. Average Excess Return (for the Event period) was calculated as: Average Excess Return (AER) = Total Excess Return / n (number of firms in the sample)

Despite the strong evidence that stock movements are largely random there have been a few data anomalies exposed that call into question whether share prices do incorporate all historic data. Fran Cross (1973) and Gibbons and Hess found statistically significant evidence that share prices tend to fall on Mondays and rise on Fridays. This is popularly known as day of the week effect. The January Effect noted by Keim (1983) is a calendar-related anomaly in the financial market where financial security prices increase in the month of January. This creates an opportunity for investors to buy stock for lower prices before January and sell them after their value increases. This type of pattern in price behavior in the financial market supports the fact that financial markets are not fully efficient. De Bondt and Thaler (1985 and 1987) found that stocks that have fallen most in price during the previous three to five years will tend to yield excess returns over the following three to

Through this year April, the USD weakened, and was the possibility that political policy of trade restriction on some countries; investors anticipated forecast that the Fed increase the interest rate from 1% to 1.25% on June. The Trust’s NAV of portfolio return is -0.9%, and the benchmark return is -1.4%. The portfolio is outperformed the benchmark on April when stock selection is the main driver. Stock selection in U.S. is helped for the positive return from the most impact performance of Balfour Beatty, Senior, Howden Joinery Group and Tyman among the top contributors. (Strategy, Fund, 2017). The rising inflation will support equities for the continued economic growth in U.S.. emerging markets debt rising since the beginning of 2017. Class F-2 shares may not reach the the prediction as result in the future period, so the share prices and returns is uncertain that investors may lose in this point, especially for the short-term investors. The EM is doing well in Asian market. EM still remains uncertain risk. A lot of the dollar-denominated debt becomes difficult to service. (Edwards, 2017). But EM local currency bonds may looks very attractive and a good choice to investors for the steeper EM yield curves and positive real rates in the condition of slowly rising interest rate in U.S. (Emerging Markets Debt, 2017). People should stay still and wait for a correction to buy stock

To begin with, in this paper, we assume the impact is unbiased, which means this market is efficient. In an efficient market, the market price should be an unbiased estimate of the true value of the stock. However, market efficiency does not require the price to be completely matched with true value. Due to randomness, the price can either be under-estimated or over-estimated at any point of time. When there is an announcement, the changing of prices related to the announcement does not mean the market is inefficient. Martingale property theory assumes that knowledge of past events cannot help to predict future winning’s stock price. Only when this condition is satisfied, then the market is a fair game. There are three versions of efficient market hypothesis: weak-form efficiency (contains all past price information), semi-strong efficiency (contains all public information), and strong efficiency (contains all public and insider information). The better the price signal, the more info-efficient the market. Event studies provide a direct test to market efficiency.

The Chinese stock market is celebrating its 25th anniversary later this year, and its first 25 years have been a fairly consistent story. There has been a history of large, government-driven rallies, followed by dramatic sell-offs that have left many investors angry. As of August 2, 2015, stocks are down 29% from their peak in June 2015. The current bear market—defined as a fall of 20% or more from a peak—is the 27th that investors have suffered in the past 25 years. It is the 21st worst in terms of losses . The government has intervened heavily during this most recent bear market, and although the intervention created some short-term relief, in the long term the heavy intervention is setting China up for future trouble.

BSE Sensex is one of the flagship stock price indices in Indian stock market. In this paper, it has been tried to estimate how much BSE Sensex, as the form part of Indian capital market, has grown during the period 1986 to 2016 and after this it has been tried to forecast in which way BSE Sensex will be going to move in the near future holding period 2017-2020.

Semi-strong form EMH is reflecting all publicy available information. It assumes stock adjust quickly to absorb new information. It also incorporate weak-form EMH. Stock prices reflect all new available information. And those investors will purchase stock after new information released. But the investor cannot benefit over market by trading on new information. And it is risk-adjusted return. Semi-strong form is mostly supported by empirical evidence. Notion of semi-strong efficiency are strongly supported by the evidence, but occasional studies as those identifying market anomalies including the small-firm effect and the January effect and events like stock market crash of October 19, 1987 are inconsistent with this form of market efficiency. Black suggests that most so-called "anomalies" result from data

In the analysis, S&P500, an index of 500 stocks chosen for market size, liquidity and industry grouping, among other factors commonly used benchmarks for overall U.S stock market. Consequently, the beta coming from Dow Chemical is more sensitive than eBay to the benchmarks, which implies the security will be expected significantly outperformed market when market is going up and significantly underperformed when market is going down. Dow Chemical is an American multinational chemical corporation, services including agricultural science, consumer solution, infrastructure solutions, performance material & Chemicals, and etc. Being as one of the most influential commodity company, Dow Chemical is affected by the world price of oil as well as its competitors and is also plagued by currency fluctuations since products are exported to all regions of the globe. For example, severe weather on August of 2010, resulting in big power cuts and dramatic drop in whole market especially for commodity industry such as Dow Chemical. In contrast, lower beta means less volatile to the market index, also may have lower returns for investors. eBay is an e-commerce company, which is more rely on the online trading and transactions in the globe. product turns less fluctuate in the whole market, especially compared with current retailer companies, internet retailer

China, arguably the most robust economy in the world, shocked everyone when it announced that its key stock market had crashed. When the facts came out it became clear that this was much more than just a blip on the radar, what it actually represented was a huge plunge. This plunge sent many traders into panic mode, as many key Chinese equities were trading at levels that many thought were once implausible. Making matters worse was the fact that the crash occurred at a time when China was looking to promote the strength of Chinese stocks. There is no other way to look at the situation; the crash of Chinese stocks resembles a global issue and one that has the potential to spread to other important global markets.

Hypothesis 2: The trend of stock price changes is proportional to the company’s performance absolutely, and the stock price changes only affected by operation.

Peng (2008) described the long run IPO performance, the Shanghai Stock exchange index was used as a benchmark. These studies analyzed the aftermarket performance by using the cumulative abnormal returns (CAR) and buy and hold abnormal return (BHAR). It showed that IPO over performance in six months ofter listing day and recorded under performance after six months of listing.

The two indices under study are the S&P Nifty and Sensex. This study conducts a statistical analysis of the daily and monthly data for both Nifty and Sensex for the period April 1, 2001 to December 31, 2012. The study found that the Day of the Week Effect and Monthly Effect Pattern did not appear to exist in the Indian Stock Market during the study period.