NZD/USD Moves to Yearly Highs on RBNZ News
- The NZD/USD breaks to yearly highs on RBNZ rate decision
- Historical Distributions Look Higher as Prices Retrace
- Bearish Reversals Begin for the NZD/USD under .7080
The NZD/USD continues to trade higher this morning after the RBNZ (Reserve Bank of New Zealand) kept key interest rates flat at 2.25%. Today’s initial breakout occurred when prices traded above the previous 2016 high at .7053. Now with prices trading firmly above this value traders are now watching to see if upward momentum can continue to push prices above the daily high that currently resides at .7147.
NZD/USD Daily Chart Breakout
(Created using Grid Sight Index)
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Displayed in the graph below, we can now see the NZD/USD trading in a short-term downtrend. However, despite of a series of short-term lower lows GSI has placed its closest historical distribution point higher. GSI reviewed 29,826,580 pricing points, and out of 135 matching events, prices rose 13 pips in 56% of previous instances. A move to this point would suggest a fresh bout of bullish momentum for the pair. At, which point, traders may look for new breakout opportunities back in the direction of the primary trend.
In the event that the NZD/USD reverses lower, traders should look for prices to test the first bearish distribution point. Out of the 135 matching events, GSI has pointed out that the market declined 12 pips in 34% of these events. This places the first bearish distribution at a price of .7116. A move to this point would be significant and potentially opens the NZD/USD to further declines in price. In this bearish scenario, traders should watch for a move towards the final distribution point at 7080. A decline of 48 pips occurred in just 4% of the represented 135 events, and would suggest a major shift in market momentum.
What is GSI?
Grid Sight Index is a powerful big data indicator that can help you determine whether short-term trends will continue or reverse. GSI takes a snapshot of current price action and uses that to find similar events by studying millions of historical data points. Then it studies those events to show you how often the trend continued or reversed in the past.
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