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Chapter 25, Part II. Buying and Selling the News. Page 5

Discussion in 'Complete Trading Education- Forex Military School' started by Sive Morten, Dec 26, 2013.

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  1. Sive Morten

    Sive Morten Special Consultant to the FPA

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    Directional data trading


    Commander in Pips: Let’s speak a bit more about the first type of trading, that assumes a directional view on some macro data, and hence, on its new release. For simplicity let’s discuss the same retail sales. As we’ve said we have to have some predefined view on expected data. But that is not enough. As we’ve said, even if retail sales will be good, there will appear the other question – how good, and why? We know that the “growth of economy” is good, while “recession in economy” is bad, the same we can say about retail sales – growth in retail sales is good while reducing of retail sales is bad. But not all things are so simple.


    In fact, it is just called “directional data trading”, while in reality this data trading is mostly based on fundamental analysis. Sometimes when we see that some data, let it be the same retail sales, comes in better than expected, we do not see any positive reaction on dollar. Instead of solid down EUR/USD move it turns to some flat action or showing an unconfident move down. Why? It could happen, because even positive current retail sales data does not change the overall trend of the US economy. Particularly this number can’t prove to investors that the US economic environment has changed. This is almost like a move in parallel channel. In bearish parallel channel there are moments when price shows an upward move, but it does not change the overall bearish direction. The same is here.

    Second reason is a period itself. For instance, we look at November and December retail sales releases. Even tremendous growth could be not sufficient for a solid reaction on markets, since Thanksgiving day, Black Friday shopping and the Christmas shopping rush could lead to a significant splash in retail sales. Such nuances exist for most data.
     
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