Nvidia Q4 Earnings Tomorrow (25 February) - How will the Market React?
Nvidia has beaten expectations on revenues in all four quarters of 2025, yet the market has reacted with higher volatility, volume spikes ($28bn in November - two times daily levels) and price falls, indicating a disconnect between expectations and sentiment.
When such misalignment emerges, earnings announcement periods become liquidity events as big as expiries and rebalances. The question is not whether Nvidia will beat expectations (hopefully); it is how the market will adjust its position when it does, and how that will spill over into other related shares. The subsequent recovery in the NVDA price after each earnings report highlights the dynamics behind potential overshoots.
Figure 1: NVDA daily value traded (lit market only) and intraday volatility. Announcement day is coloured red, three days before are shown in pink and three days after are shown in green. The chart shows how long it takes for volumes and volatility to normalise after each announcement. Note the high volumes on Monday 23 February 2026.
Trading volumes and intraday volatility around earnings provide a window into this adjustment. Examination of the four earnings reports across 2025 reveals that when volatility peaks before the announcement (see May and August), trading volumes tend to return quickly to normal; but when volatility peaks after the announcement (see February and November), volumes trend higher for a few days. This points to a surprise. Perhaps we can use volatility and volume data to perform ex-poste testing on the quality of guidance and expectations.
What of the read through to related names? The impact of Nvidia announcements on the other MAG7 names is irregular and only mildly correlated. Some stocks respond sharply; others barely move. This pattern of selective reaction reveals the underlying structure of capital flows; investors’ objectives and constraints. In Figure 2, we see differences in the relative sensitivity of volumes to Nvidia earnings announcements as a market reaction. We note that AAPL seems to be indifferent, GOOGL has greater but very selective sensitivity and TSLA reacted the most. Liquidity analysis points to the cause of TSLA’s sensitivity.
Figure 2: Comparison of fellow MAG7 names - daily value traded using the same colour scheme as before.
In figure 3 below, we again see that there is only a mild correlation in intraday volatility between NVDA and the rest of the MAG7 during earnings announcements - by contrast with macro news such as the tariff skirmishes of 2025 when both volume and volatility spikes are simultaneous across the three example names.
Figure 3: Comparison of fellow MAG7 peers - daily intraday volatility using the same colour scheme as before.
Why does this matter? The asymmetric spillover to MAG7 peers reveals something critical: Nvidia earnings are not necessarily a sector-wide event even though it provides crucial information on competition, shifting tastes, and supply chains. Unlike index changes and expiries, earnings announcements are less systematic events. Correlations with companies like TSLA are as much about liquidity flows as fundamentals, reflecting the strongly overlapping investor bases with shared benchmark portfolios, margin constraints, and correlated hedging flows (NVDA and TSLA are the most traded stocks in the S&P).
For execution planning, this has direct implications. If you hold positions in TSLA, expect higher volatility and higher liquidity (often related) when Nvidia announces. This requires precision forecasting data and pre-trade models to take advantage of liquidity while navigating higher market risk. If you hold AAPL, your execution baseline stays normal. The same earnings event creates asymmetric liquidity shocks across related names.
Earnings periods now rival expiries and rebalances as structural liquidity events, but with a critical difference. Systematic events drain liquidity broadly and mechanically; earnings-driven flows are selective, concentrating on specific names based on capital structure, crowding, and investor overlap rather than index weights. The same capital rotates through a surprisingly narrow set of shared liquidity pools.
This is why understanding which stocks are connected by those pools matters as much as understanding fundamentals. Liquidity analysis reveals where positioning is crowded, where forced adjustment will land, and when the cost of trading spikes, things that expectations analysis alone cannot surface. Getting the earnings call right is only half the problem. Getting the timing and execution right is the other half.