Day-to-day internet congestion measurably delays how quickly stock prices absorb public news — creating systematic, predictable patterns that sophisticated investors can exploit.
KASPR Datahaus measures round-trip time (RTT) continuously across millions of U.S. IP addresses. The cross-sectional variance — LatencyVar — captures how unevenly internet quality is distributed on any given day.
62Peak LatencyVar index reading, March 2020. The COVID-19 lockdown triggered the largest latency spike in the sample — 70% above the high-latency threshold of 36.3.
Through 2021 multiple distinct spikes recurred — driven by infrastructure stress from sustained remote-work demand, winter weather events, and shifting network load patterns. This was not a COVID artefact.
4months in 2021 where mean LatencyVar exceeded the P75 threshold — including a sharp November spike reaching 41, nearly as elevated as the 2020 COVID period.
Six separate months in 2022 exceeded the P75 threshold, with Q4 seeing the most sustained elevation — coinciding with peak Fed rate-hiking intensity and heightened financial news volume.
47Peak LatencyVar reading, December 2022 — the highest reading outside the COVID period and evidence that market structure frictions intensify during macroeconomic stress.
Orange shading marks days above the P75 threshold across all four years of the sample. High-latency episodes are distributed across every market regime — bull, bear, and volatile — confirming this is a structural property of U.S. internet infrastructure, not an outlier phenomenon.
25%of all trading days in the 2020–2023 sample qualify as "high-latency days" by construction of the P75 threshold — roughly one in every four sessions.
LatencyVar: cross-sectional variance of RTT across U.S. Autonomous Systems, normalised to historical mean. Orange shading = days above P75 threshold (36.3). Source: KASPR Datahaus.
Using a firm-day panel of U.S. equities, RavenPack news sentiment, and KASPR latency data (2020–2023), the baseline is clean:
+1.95%same-day return on positive-news days under low latency. The negative-news mirror effect is −1.79pp.
When LatencyVar exceeds the P75 threshold, the same-day positive-news return falls from +1.95% to just +1.51% — a 0.44pp reduction.
−23%attenuation in same-day impact. Significant at p<0.01, robust to excluding COVID-19.
High latency attenuates the negative-news return by 0.25pp — a 14% reduction. The 23% vs 14% asymmetry is consistent with institutional sell-side desks partially absorbing the delay.
−14%attenuation in same-day negative-news impact.
On high-latency days, retail buy volume on positive-news events is significantly dampened — direct evidence that congestion physically delays retail investors from acting on good news.
Retail sell volume on negative-news days is amplified — consistent with over-weighting of negative signals under noisy transmission.
High-dimensional FE regressions, 2020–2023 U.S. equity panel. SE clustered two-way at stock-year and date.
When latency mutes day-zero price adjustment, the information isn't lost — it propagates over the next one to two sessions. The high-latency group shows a compressed day-zero return followed by persistent drift in the direction of the news.
Low-latency (blue/solid) shows strong day-zero jump then partial reversal. High-latency (light blue/dashed) shows muted day-zero reaction and upward drift over t+1 to t+3. CARs anchored at day −1 = 0. Source: author calculations, 2020–2023.
Low-latency (red/solid) shows sharp day-zero decline then partial reversal. High-latency (salmon/dashed) shows attenuated day-zero drop and continued downward drift. CARs anchored at day −1 = 0. Source: author calculations, 2020–2023.
68% recovery in two trading days for positive news. Delayed, not permanently lost price discovery.
Negative news continues to drift after day zero in the high-latency group — investors act on delayed bad news in the next session.
Investor implication: high-latency days create a predictable short-term continuation signal in both directions.
Reduction in same-day positive-news return (pp) on high-latency days, by firm segment. Subgroup regressions within the main specification.
The latency effect concentrates precisely where retail investors dominate and institutional co-location provides the least offset.
For small-cap stocks (bottom market-cap quintile), attenuation reaches ~1.5pp — roughly 10× larger than large-cap firms.
Stocks with above-median retail participation show 0.32pp attenuation. For low-retail stocks, the effect is near zero and statistically insignificant.
Bid-ask spreads: the normal spread-tightening after positive news is dampened under high latency — market microstructure is distorted beyond return means.
The research merges three firm-day datasets across the U.S. equity market 2020–2023. Identification relies on LatencyVar variation orthogonal to firm characteristics and news incidence.
Continuous RTT measurements across millions of U.S. IP addresses, aggregated daily to LatencyVar — cross-sectional variance across U.S. Autonomous Systems.
Machine-readable firm-day sentiment from 19,000+ sources in real time. Binary and continuous measures of positive and negative firm-specific news shocks.
Daily U.S. stock returns, trading volume, retail buy/sell fractions, and bid-ask spreads. Two-way clustered SE at stock-year and date level.
Placebo validation: a non-news-day placebo assigns random shocks on days with no RNA coverage. The latency interaction is precisely zero — confirming the effect is specific to actual news events. Results hold excluding COVID-19, with continuous latency measures, and under alternative clustering structures.
KASPR's daily LatencyVar data is the input signal behind this research. Contact us to discuss integration into your systematic or discretionary investment process.
Ackermann, K., Angus, S., Cui, B., & Raschky, P.A. (2026). News, Latency, and Stock Prices. Monash University / SoDa Labs.
Based on U.S. equity panel 2020–2023. Past patterns do not guarantee future results. For institutional and professional investor use only.