CUSUM-Filtered News Sentiment for Tactical Stock-Bond Allocation

Summary

This research note describes a tactical asset allocation method that converts the tone of company and macroeconomic news into a slower-moving signal. News sentiment scores are aggregated weekly, then filtered with a two-sided cumulative sum (CUSUM) procedure to reduce noise and identify persistent positive or negative sentiment momentum. The proposed rule switches between global equities and intermediate-term U.S. government bonds according to the signal; a balanced stock-bond portfolio serves as the benchmark. The research also tests sentiment signals with regression analysis and uses rolling estimation to assess out-of-sample performance.

The document reports historical results from a study covering 2004–2013, including an information ratio of 0.8, a maximum drawdown of 11%, and an average of eight allocation changes per year. It says the signal was statistically significant and describes simulated live tracking from 2013. These findings are the authors’ reported backtest and simulation results, not a guarantee of future performance. They depend on a specific commercial news sentiment dataset, historical period, and portfolio design; the text does not fully establish how results would change with different data sources or implementation assumptions.

Key ideas

• Weekly aggregation and CUSUM filtering are used to extract persistent momentum from noisy news sentiment.
• The sentiment signal determines whether the portfolio holds global equities or government bonds.
• The study uses rolling estimation, out-of-sample testing, and regression analysis to evaluate the signal.
• The reported strategy averaged eight allocation changes per year and had an information ratio of 0.8.
• Results depend on the historical dataset and implementation choices and do not ensure future performance.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.