Yesterday, the Reserve Bank of New Zealand (RBNZ) lowered rates by 25bps. This decision was widely anticipated, with the market fully pricing the move before the meeting.
In contrast to the overwhelming consensus, Prattle called for a hold from the RBNZ in this week’s Macrocast, citing the neutrality of the bank’s recent sentiment data* as the primary reason for this call.
While RBNZ ended up cutting, the statement had a curious effect on the market. Instead of the kiwi dropping, as one might expect on the heels of an easing announcement, it actually rose as a result of the release. In fact, the news prompted the NZD to hit its highest point in a year.
If you had been forecasting price movement based on market expectations or analysts’ predictions, you would likely have been surprised. If you were acting on Prattle’s data, however, the market’s fluctuations would only have confirmed your suspicions.
The data leading up to the decision and our scores of the release itself (residual** 0.04; raw 0.71) indicated that the market would react as if the bank would hold, and that is exactly what happened.
(Prattle’s momentum score for the bank)
Prattle’s sentiment data was designed to help predict market reaction, not to forecast specific policy moves. In this case the data correctly signalled that the market would react to the RBNZ statement as though it was slightly hawkish.
An excerpt from a recent study we wrote about the Bank of Japan perfectly outlines the key takeaways from these events:
“While Prattle’s data can be used (and quite effectively at that) to forecast policy, it’s actually designed to do something even more powerful: forecast market reaction
In the end, what investors care about aren’t the specific moves a central bank chooses to make, but, instead, the effects those moves are going to have on the markets. The foreknowledge of policy is just a means of forecasting market reaction. By building each bank’s lexicon of scored expressions from the history of each bank’s language and the market’s reaction, Prattle, in short, cuts out the middle man and gives its clients what’s really needed to trade: a clear, evidence-based picture of how they can expect the market to react.”
The bottom line: while announcing a cut, the RBNZ release impacted the market exactly how Prattle’s data indicated it would.
The Signal Team
* Prattle’s models are based on the historical relationship between central bank language and market reaction, which is used as basis of evaluation for future communications. The scores are normalized around zero and range between -2 and 2, negative numbers indicating dovishness and positive numbers indicating hawkishness.
** The momentum is the average of the last ten residual scores. Residual scores represent the tone of a communication compared to the rolling, 12-month average for that individual communication type or speaker. Raw scores represent the tone of a communication compared to the average of all communications.