Economic Indicators That Most Impact Markets

Assuming a normal distribution of surprises, approximately 68% fall within one standard deviation of the mean when standardized using z-scores. See appendix for more color around our use and calculation of z-scores.

The following charts present R Square values for different post-release windows, being the proportion of variance in trading volume explained by economic surprises for interest rate futures (Figure 1) and options (Figure 2). These data are further supplemented with tables detailing coefficients, t Stats, and P-values (Figure 3) for different post-release windows. For instance, our model accounts for 46% (R Square = 0.46) of the variation in interest rate futures trading volume within the first 5 minutes (8:30:00 - 8:34:59) following 8:30:00am ET data releases.

Figure 1 - Interest Rate Futures' R Squares (8:30:00am ET Data Releases)

Figure 2 - Interest Rate Options' R Squares (8:30:00am ET Data Releases)

Figure 3 - Interest Rate Futures and Options' R Squares, Coefficients, t Stats, P-values (8:30:00am ET Data Releases)

The intercept is the average daily trading volume on Mondays, assuming no surprises in economic data vs market expectations (i.e., releases matching market expectations), or on days with no releases. Mondays are, on average, the lowest volume days with about 286,000 to 921,000 fewer futures trades and 360,000 to 606,000 fewer options trades than the other days of the week. Wednesdays are typically the busiest day of the week in terms of volumes for both futures and options.

Which pieces of economic data generate the highest volumes?

Following the 8:30:00am ET release, surprises in labor, inflation, and retail sales data consistently showed statistically significant impacts on trading volumes in the first one, five, and 10 minutes. This significance was determined using a P-value threshold of 0.05 (5%). For example, there is a 3E-05 (0.003%) chance that the observed relationships between surprises in NFP and trading volume during the five minutes (8:30:00-8:34:59) was due to random chance (Figure 3).

The one-minute results were particularly striking. On days with no economic data releases or when data showed no surprises versus consensus, in the first minute after the report (8:30:00 - 8:30:59), typically about 20,663 interest rate futures contracts were traded (the intercept). A one standard deviation surprise in NFP in either direction led to 20,663 + 174,173 or about 194,836 futures contracts traded between 8:30:00 - 8:30:59 (Figure 4).

In the minute after the reports' release, surprises in related labor market data, such as the unemployment rate and average hourly earnings, also produced strong impacts on interest rate volumes, as did initial jobless claims, ranging from 80,000 to 145,000 in additional futures volumes for a one standard deviation miss from consensus (Figure 4). The impact on options volumes during the first minute after the releases were typically much smaller.

Retail sales have been the second most influential piece of data after the employment numbers. A one standard deviation surprise versus forecasts on retail sales typically produced an additional 80,000 contracts of futures volume in the minute after release (Figure 4).

Despite the post-pandemic surge in inflation, market reactions to surprises in CPI, core CPI and PPI, although still statistically significant, tended to be more muted, adding only 20,000 to 30,000 contacts to the futures trading volume within a minute of their release (Figure 4). They tended to have a mixed and negligible immediate impact upon options volumes.

Figure 4 - Additional Volume Traded over Intercept (20,663) 8:30:00 - 8:30:59 ET

Within five and 10 minutes of the release of the various data series, increases in trading volumes tended to produce results of similar statistical significance with the amount of additional trading volume increasing with time. In the 10 minutes between 8:30:00 and 8:39:59 ET, typically there would be 167,000 interest rate futures and 25,000 options contracts traded (Figure 5). On days with data surprises, that number can be much higher. In the 10 minutes after a one standard deviation surprise on employment related data, there were typically anywhere from 316,000 to 730,000 more contracts worth of futures trading volume (Figure 5) and 30,000 to 65,000 additional options contracts traded. Here too, surprises in retail sales were the second largest volume driver with a one standard deviation

By contrast, within 10 minutes of the release, a one-standard deviation surprise in inflation statistics such as CPI, core CPI, PPI, and core PCE tended to produce milder responses with 60,000 to 120,000 more contracts traded beyond the usual (Figure 5). For interest rate options, the excess volumes stemming from one standard deviation surprise ranged from 2,500 for PPI to 14,000 for core CPI.

Figure 5 - Additional Volume Traded over Intercept (167,339) 8:30:00 - 8:39:59 ET

Recognising that FOMC policy announcements can significantly influence trading activity, we included a dummy variable to account for these days. Interest rate options daily trading volume is, on average, 1,747,832 contracts higher on FOMC announcement days compared to non-FOMC days (Figure 6).

Figure 6 - Interest Rate Futures and Options' R Squares, Coefficients, t Stats, P-values (non-8:30:00am ET Data Releases)

Why the 2021-2025 Time Period?

Since 2021, financial markets have experienced significant uncertainty about future interest rates, mostly because inflation rose sharply after the pandemic. Core PCE, the Fed's preferred inflation measure, exceeded the 2% target, hitting 3.1% in May 2021 and peaked at 5.3% in March 2022. Core PCE was 2.9% in January 2025.

Figure 7 - To control inflation, the US Fed started raising interest rates from March 2022 onward and was followed by many of its peers around the world

Appendix

We calculated z-scores using a three-year rolling standard deviation to normalize the magnitude of surprise relative to historical volatility. For example, to calculate the z-score for the January 2021 data releases, we used the standard deviation from January 2018 to December 2021. This standard deviation is rolling, so the next would use February 2018 to January 2021, and so on. This reflects how the market's reaction to surprises evolved over time, ensuring we are not using future data to make inferences about past data.

We used dummy variables to account for the differences in trading volumes that structurally occur on different days of the week, using Monday as the baseline. This means Monday is not included in the regression, and when it's Tuesday, for example (Tuesday = 1, Wednesday = 0, Thursday = 0, Friday = 0), then the increase or decrease in volume is relative to Monday.

Similarly, we included a dummy variable for FOMC announcement days. This coefficient is the difference in average trading volume on FOMC days compared to non-FOMC days (FOMC day = 1, non-release day = 0).

All examples in this report are hypothetical interpretations of situations and are used for explanation purposes only. The views in this report reflect solely those of the author and not necessarily those of CME Group or its affiliated institutions. This report and the information herein should not be considered investment advice or the results of actual market experience.