Surprising the markets, the BOJ engaged in tepid stimulus on Thursday, July 28. The BOJ did not cut rates or buy bonds, but, instead, chose meek measures: ETF purchases and increased dollar lending.
On Monday, July 25, Prattle correctly predicted the hold. We did not, however, anticipate modest stimulus measures. The market did not predict modesty either; it went the other direction, predicting bold stimulus. With bold easing built into market expectations, the BOJ’s restraint was viewed as hawkish.
The market reaction to the BOJ statement was perfectly in line with Prattle’s data*–and its projection. This study explains how Prattle used its algorithmic analysis to go against the grain to anticipate market response to this vital BOJ communication.
Prattle’s out-of-consensus prediction was based on the wide dispersion of the scores our algorithm had given BOJ communications since the bank’s last policy meeting. Over that period, residual scores** ranged from -4.16 to 2.06.
Figure 1: Recent BOJ Trend Data
While there was a discernible dovish bias in the spread, the BOJ had trended dovish since February without taking stimulative action, and this led us to conclude that the recent chatter about rate cuts and bond buying was likely another head fake. We were right.
Easing isn’t always dovish
Although Prattle correctly called the rate hold, we did not predict the modest stimulus measures. While we were slightly surprised by these tepid easing moves, the markets were even more surprised–but for the opposite reason.
The majority of economists–32 out of 41 according to Bloomberg–called for stimulus, and two-thirds of those polled predicted a rate cut. These projections primed the market for a full-scale stimulus move, and, consequently, the BOJ’s meek easing measures were interpreted by investors as hawkish. As a result, the JPY/USD jumped 1.9% on the news of the BOJ’s decision.
Figure 2: JPY/USD, 7.29.16
This market reaction, however, did not catch Prattle users off guard. Prattle scored the announcement as somewhat hawkish compared to all BOJ communications (0.52) and even more hawkish when compared to other BOJ policy statements (0.86).
In stark contrast to those relying on market consensus, those acting on our projections and data would have been well-positioned to benefit from the fluctuations caused by the BOJ’s policy decision.
Market reaction: what our data means
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.
This is the beauty and simplicity of Prattle’s data. This is the incredible advantage it provides its users.
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.
** Raw scores represent the tone of a communication compared to the average of all communications. Residual scores represent the tone of a communication compared to the rolling, 12-month average for that individual communication type or speaker.