One of the most challenging problems in economics is how to measure the financial market effects of policy decisions halfway around the world. For instance, how will U.S. tariffs on Chinese goods impact the Australian economy? Standard economic data does not provide a clear answer, but alternative data can offer valuable insights into the effects of these policies that are currently the subject of much speculation.
In particular, specialized sentiment analysis of central bank communications can be used to identify the impact U.S. trade policy—and the resulting uncertainty in China—has had on the tone of the Reserve Bank of Australia’s communications.
For years, the language of central bankers has been viewed as incredibly nuanced, veiled, and opaque—often purposefully so—and consequently has not been able to be measured or quantified in any way.
Advanced linguistic mapping designed to identify sentiment solves this problem by using algorithmic processes to analyze the relationship between central bank language patterns and market reactions. A unique lexicon is maintained for each central bank, and new communications are assigned sentiment scores that capture the likely market reaction based on previous patterns. Scores are normalized around zero, with negative numbers indicating a dovish outlook and positive numbers indicating a hawkish outlook.
Applying Sentiment Analysisto Australia and China
In early 2018, the Trump administration began raising trade barriers in a protectionist effort to bolster U.S. business, particularly manufacturing. This policy change has had myriad effects on the global economic stage and has cast doubt on trade relationships far and wide. One such relationship is between China and Australia.
As trade tensions between the U.S. and China have increased throughout the course of 2018, so have Australian concerns over the reliability of the country’s trade relationship with China. This is due to China being largely dependent upon U.S. consumption of its manufactured goods, which in turn rely heavily upon a steady stream of raw materials from Australia. In other words, decreased U.S. consumption of Chinese goods could equate to substantial setbacks for the Australian economy.
While these concerns have not had much of an impact on the Australian economy to date—GDP is growing at 3.1% with inflation around 1.9% and unemployment holding steady at around 5.6%—they have been evident in communications from the Reserve Bank of Australia (RBA).
The table below identifies how the Australian economy has fared in recent years:
% Change Consumer Price Index
Sources: Federal Reserve Economic Data (FRED), Australian Bureau of Statistics
* indicates 12 month trailing figures
Such strong economic conditions would normally suggest that the Reserve Bank of Australia should be moving to an increasingly hawkish policy position, but the exact opposite has been the case since the start of 2018. In recent months, RBA sentiment has plummeted from hawkish to neutral, indicating that policymakers have a less optimistic economic outlook:
This drop in sentiment and continued neutral posture appears to be tightly correlated with Chinese economic data and concerns about trade. These ongoing concerns are dragging on possible future Aussie growth and have cast a dark shadow over otherwise bright economic conditions.
As is evident from the data, the Australian economy is being influenced by factors other than its currently strong fundamentals. The closest link between the Chinese and Aussie economies—future Chinese demand for Australian raw materials—may not be adequately represented in the traditional economic data above, but it is concisely captured in central bank sentiment analytics.
Utilizing alternative data has allowed us to shed new light on this situation. We can see that uncertainty over Chinese manufacturing growth has caused the RBA to become more neutral and adopt a wait-and-see approach while trade tensions play out. With the Australian economy dependent upon international factors outside of its control, sentiment data provides unique insight into this complicated economic interplay.
Evan A. Schnidman is the founder and CEO of Prattle. Prattle is a financial research automation company that specializes in generating tradable quantitative signals from market-moving communications. Launched in 2014, Prattle analyzes the content of market moving communications from central banks, corporations and regulators. Prattle’s proprietary sentiment analysis methodology maps linguistic patterns to market response to identify likely future outcomes.