Read the signals
We examine macro markets in a systematic and quantitative way
using machine-readable news from the Financial Times.
Using news to trade financial markets is not new but today there is simply too much of it for any human to read.
There are countless instances where Financial Times reporting has caused market prices to jump, but what if we were to apply quant methods and machine learning to distill the message of what is written in the FT in a systematic way?
This research explores how trading signals can be extracted from FT stories in a machine-readable format.
I remember back to my graduate days on a trading desk. Copies of the FT and its distinctive pink sheets were ubiquitous on the trading floor. These days the paper version is perhaps less visible, with many subscribers switching to the FT online. What has remained the same, however, is the ability of the FT to move markets.Founder of Cuemacro and author of this report
How does a trading strategy derived from FT sentiment perform?
The report presents a trading model which actively trades S&P 500 futures based on FT news articles. In practice, investors could seek to apply the same approach to trading a portfolio of assets.
The chart below shows an active strategy trading S&P 500 futures based on signals gathered from FT news against a static long only S&P 500 futures position. The report discusses this trading strategy in more detail.
Trading S&P 500 futures with an FT news based trading strategy vs. long only S&P 500 futures
How can FT news data be used from a macro-based perspective?
Understand how trading signals can be extracted from machine-readable FT stories for macro-based investors. Various indicators are created in the report using natural language processing to track general macro market themes such as economic growth, inflation and Brexit.
Alongside our UK sentiment index, we can plot recent GBPEUR returns. It’s notable that going into the EU referendum in June 2016, sentiment in UK news in the FT had already begun to decline.
We created a sentiment indicator of news articles written in the FT tagged with the "Global Economy" topic and aggregated it within a 3 month window. Our Global Economy sentiment score can then be plotted alongside an inverted VIX index, which is often used by investors as an indicator of risk appetite.
News sentiment associated with Global Economy articles in FT vs. inverted VIX