Project #634 - paraphrase

i need a paraphrase to the below work that should pass a plagiarism detect it is less than 1000 words if the work is good i have allot more. thank you market efficiency Lo and MacKinley (2001) believed that “the Efficient Market Hypothesis is not a well-defined and empirically refutable hypothesis” The test is based on the variance of returns and have good size and power properties against interesting alternative hypotheses and in these respects are superior to many other tests (Campbell et at., 1997). The event studies literature includes Ball and Brown (1968), Ball (1978), Fama, Fisher, Jensen and Roll (1969) and Scholes (1972). In this paper the reaction time of share prices to announcements of quarterly financial reports is analysed for shares traded on the FTSE 100. Finally using standard event study methodology, the research tests two individual random samples; one sample includes insider sales and the other insider purchases. Each sample group is comprised of different companies with different announcement dates to minimise selection bias factors. The sample groups are also analysed based on the risk adjusted rate of return of the firms stock prices to determine if insiders “buy low” and “sell high”. If the test results support the strong form market hypothesis, then no investor can earn an above normal return by acting on this information. According to Fama (1970) the market is said to be weak-form efficient if it fully and properly reflects all available past information about company in its stock prices. From that perspective, if the stock prices do follow random walk, the market is described as weak-form efficient. Since the seminal work of Lo and MacKinlay (1988), the variance ratio test has emerged as the primary tool for testing whether stock return series are serially uncorrelated. Charles and Darné (2009b) provide an exclusive and extensive survey on its recent developments. Although the variance ratio tests have been widely accepted as the standard tool, there are still some recent papers which rely solely on the conventional autocorrelation tests (Mollah, 2007; Mobarek et al., 2008). Variance ratio tests remain the firm favorites in the existent weak-form EMH literature. In contrast, despite numerous methodological refinements to existing serial correlation tests (Lobato et al., 2002; Horowitz et al., 2006) and spectral-based tests (Durlauf, 1991; Deo, 2000), we do not find any applications of these improved statistical tools on stock market data, with McPherson et al. (2005) and McPherson and Palardy (2007) being the only two studies identified. The recent methodological refinements to variance ratio tests have prompted a number of studies to conduct a re-examination of the stock market data in Asia (Hoque et al., 2007; Kim and Shamsuddin, 2008), Europe (Smith, 2009), Middle East and Africa (Al-Khazali et al., 2007; Ntim et al., 2007; Smith, 2007, 2008; Lagoarde-Segot and Lucey, 2008). These recent studies do report evidence of weak-form efficiency for emerging stock markets, for instance, Al-Khazali et al. (2007) for Bahrain, Egypt, Jordan, Kuwait, Morocco, Oman, Saudi Arabia and Tunisia; Smith (2007) for Israel, Jordan and Lebanon; Kim and Shamsuddin (2008) for Korea, Taiwan and Thailand; Smith (2008) for Egypt, Nigeria, South Africa and Tunisia; Smith (2009) for Poland and Turkey. Moreover the use of the variance-ratio test can be advantageous when testing against several interesting alternatives to the random walk model, most notably those hypotheses associated with mean reversion. In fact, a number of authors (e.g. Lo and MacKinlay, 1989; Richardson and Smith, 1991; Faust, 1992) found that the variance-ratio test had optimal power against such alternative. In order to check whether the values deviate enough to reject the random walk hypothesis, Lo and MacKinley (1988) introduced the standard test statistic Z(q): These tests usually study an event window of three or five days around news announcements regarding certain stocks. If news announcements convey new information to the market or if they remove uncertainty regarding rumours in circulation prior to the announcement, shares of the company affected by the news will exhibit abnormal returns (Damodaran, 2012). This abnormal return on a stock (?) on any given day is in some tests being calculated by subtracting the market turn on a broad-based index portfolio on that day (r_m) from the stock’s actual return (r): By calculating the abnormal returns on stocks for the days leading up to and following news announcements, conclusions can be drawn regarding the speed of price adjustment and the question whether information is leaked before announcements. If a company announces a dividend omission at date t, there should be an abnormal return at that date, but the return on the following trading day t+1 should not exhibit abnormal returns. Since many companies announce their news after the market closes, date t for them should be taken to mean the trading day following the announcement. If there are statistically significant abnormal returns at dates other than t, information about the dividend omission could have been leaked before the actual announcement day or the market observed could indeed be inefficient to the extent that the incorporation of new information into prices takes longer than one day. The first example of a technique of the type described above was undertaken by Fama, Fisher, Jensen and Roll (1969), though the first to be published was by Ball and Brown (1968). Using the market model or capital asset pricing model as the benchmark, these event studies provide evidence on the reaction of share prices to stock splits and earnings announcements respectively. In both cases, the market appears to anticipate the information, and most of the price adjustment is complete before the event is revealed to the market. When news is released, the remaining price adjustment takes place rapidly and accurately. The Fama, Fisher, Jensen and Roll study, in particular, demonstrates that prices reflect not only direct estimates of prospective performance by the sample companies, but also information that requires more subtle interpretation. In Scholes’ (1972) study of the price effects of secondary offerings, he examines stock price movements when the seller may be in possession of non-public information. On average, share prices fall by an amount that reflects the value of this information. The impact of a

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