Detection of Seasonality Patterns in Equity News Flow

In order to apply News Analytics efficiently in quantitative trading models, it is necessary to consider certain adjustments or normalizations of time series representing news flow. Such normalizations may be relevant as particular seasonality patterns characterize the data. To identify those times at which news flow is especially relevant to the market, it may be necessary to distinguish true bursts of positive or negative information from mere seasonal peaks in volume. Having prior knowledge of such seasonality effects, allows for proper adjustments before conducting data analysis, and thus prevents a wrong interpretation for instance of the impact of increased News Flow on volatility and trading volume predictions.

In the paper “Detection of Seasonality Patterns in Equity News Flow” (contact RavenPack for a copy), I conducted a study focusing on the seasonality patterns in equity news flow. This was done over different time horizons covering the period 2005 through 2008. The research was conducted on the average news flow in a set of pre-specified news aggregation windows ranging intra-day from one- to sixty-minutes; while a daily aggregation window was applied for the intra-week and intra-month analysis. Finally, a monthly aggregation window was used in the intra-year analysis.

The key findings of the seasonality study can be summarized as:

• Strong seasonality exits on the intra-day, intra-week, and intra-year horizons with median sector-correlations above 73%, 99%, and 98%, respectively.
• Sector-correlations, on an intra-month level, are somewhat lower with a median of 40%. Still, 25% of the cross-sectional correlations are above 62%.
• Applying a cross-sectional linear regression model, it is possible to explain 91.6% of the daily news flow variability using the identified seasonality patterns (including a year-effect and a holiday schedule).
  

Fig. 1 presents an example of the intra-day seasonality pattern based on a 60 minute aggregation window.

The following graphs present examples for each of the intra-week, intra-month, and intra-year seasonality patterns for news flow covering Sector 001 for the period January 2005 to December 2008:

Intra-Week

Intra-Month

(For the Intra-Month pattern, deviations from the zero-line indicates deviations from the intra-week expected pattern.)

Intra-Year

Average Intra-Year