Thesis On N Stock Market

In many cases, the findings have not supported the random walk hypothesis and are therefore not consistent with efficiency in the weak-form.

The key question investigated is whether successive share price returns on the Nairobi Stock Exchange are independent random variables so that price returns cannot be predicted from historical price returns.

Finally we perform intraday cases studies for the 2007 Quant Meltdown, first day of the 2008 Financial Crisis' worst week, and the 2010 Flash Crash respectively.

We use the number of trades within one minute as a proxy for trading frequency.

Moreover, current studies largely concentrate on price-based technical indicators.

In contrast, the widely used technical market indicators have drawn limited attention.

The findings suggests that with proper control over the quality of the data and the use of a larger number of data observations, the random walk model can be a good description of successive price returns in an emerging stock market.

This has been shown to hold irrespective of whether bid, ask, or transaction returns are used.

In a true out-of sample test, the first study finds no evidence that several well-known technical trading strategies predict stock markets over the period from 1987 to 2011.

Further analysis shows that this poor out-of-sample performance most likely is not due to the market becoming more efficient – instantaneously or gradually over time – but is probably a result of bias.

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