Findings to Date
The three contributions of this research are, first, the market expectation is derived from economic derivative prices that allow a full distribution for the market expectation to be derived. Economic derivatives data better predict financial market movements and also allow for testing whether there is information in the high moments of the distribution. Second, high frequency financial data allows us to test for the optimal window and discover how long it takes financial markets to digest and react to news. Finally, by using a
I have found that high frequency financial data leads to a much bigger and more significant news announcement effect over previous studies that used end-of day data. Further financial markets react very quickly to news. Unlike other studies that have assumed a 25-30 minute window, I have demonstrated that the announcement window is often just one minute. Using the richness of the economic derivatives-based expectations data I determine when higher moments of the expectations distribution are useful in determining the announcement effect. I also show in which markets, and for which announcements, good news and bad news have asymmetric effects; and, in which markets are most responsive to which announcements. Finally, I have highlighted some of the interesting results that traders or risk managers might want to delve into in more detail.
In the coming weeks I plan to explore some more financial markets (especially more currency pairs), focusing on the most promising economic announcements, and working on finding the best models for explaining movements in returns following economic news releases.Labels: Summary
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