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Evaluate returns predictability - Coursework Example

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Fama (1998) explains it as investment returns from a security or portfolio that exceeds a benchmark or an index that has a similar level of risk. In other words, it is a portfolio’s…
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Evaluate returns predictability
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"Evaluate returns predictability"

Download file to see previous pages This paper has two sections; in the first section it discusses empirical evidence on the predictability of excess of returns by the technical analysis method, the second section is devoted to evaluating whether return predictability is a good test for market efficiency.
Gustafsson (2012) conducted a research on how the stock market performed relatively to the predictions by the technical analysis method in the Swedish stock market. According to technical analysis assumed that successive returns were related. In other words, positive returns in a given time period would be followed by equally positive returns in the same period of the subsequent year. On the basis of the above assumption, Gustafsson (2012) wanted to test the hypothesis that successes in the stock market were independent. Among other tests, the research summarized results from various trading rules to test whether a technical analysis would have been used to accurately predict recurring price patterns and hence returns. The research found out that the comparison between 2001-12-28 and 2011-12-30, the average daily return was 0.0184% for the buy and hold strategy, with a standard deviation of 0.016 and the total number of trading days was 2517. With this statistic, the t-statistic for the buy and hold strategy was 0.58.
This study made reached some interesting conclusions from the data. Interestingly, it found out that the introduction of RSI and the RSIstoch that indicates the directional strength of price changes had an impact on the return predictability. Further, the findings lend to the support of the assumption that technical analysis can be used to predict future price movements. This is because; average daily buy-day returns were significantly larger than average daily-sell returns. As such, it meant that the technical trading rules also had a ...Download file to see next pagesRead More
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