📈 economics

Fast-Entry Funding Pressure and Incumbent Liquidity: Evidence from the SpaceX Nasdaq-100 Inclusion

This paper provides robust evidence that a model-implied funding pressure metric, derived from SpaceX's 2026 Nasdaq-100 inclusion, significantly predicts a sharp, capacity-scaled increase in implementation-day trading volume for incumbent stocks, with effects that decay rapidly after the event.

Original author: Fuli Yang

Published 2026-11-06

📖 6 min read🧠 Deep dive

CC BY 4.0

Original author: Fuli Yang

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the author. For technical accuracy, refer to the original paper. Read full disclaimer

The world of finance relies on massive, automated investment funds that track specific lists of stocks, known as indices. These funds do not pick winners and losers; they simply hold every company on a list in exact proportion to its size. When a new company is added to such a list, the funds must buy shares of that new company to match the index. To pay for this purchase, they must sell shares of the companies they already own. This creates a predictable chain reaction: a new entry forces a sale of existing holdings. For decades, researchers have studied how the price of a stock changes when it is added to a list, but they have paid less attention to the other side of the transaction. They have rarely asked how the act of selling existing stocks to fund a new purchase affects the daily trading volume of those older companies, or which specific older companies feel the most pressure to sell.

A recent study by Fuli Yang at the GARCH Institute investigates this hidden side of the equation using a real-world event that occurred in the summer of 2026. On June 26, the Nasdaq stock exchange announced that Space Exploration Technologies Corporation, widely known as SpaceX, would be added to the Nasdaq-100 index, a major list of the 100 largest non-financial companies traded on the Nasdaq exchange. The official addition was scheduled to take effect before the market opened on July 7. This created a specific deadline for the automated funds tracking the index. To prepare for the new composition, these funds had to execute their trades on the previous trading day, July 6. The researcher used this event to measure how the need to raise cash for SpaceX affected the trading activity of the 93 other companies that were already on the list.

The core of the research involves a simple but powerful calculation. When a fund needs to buy a new stock, it must sell a portion of its existing holdings. The amount of money a fund needs to sell from any single existing company depends on how large that company's share is within the index. A company that makes up a larger slice of the index must sell more dollars of its stock to raise the necessary cash. However, the study argues that the size of the sale is not the only thing that matters. What truly matters is how large that sale is compared to how much of that stock is usually traded on a normal day. If a company is huge but trades very little every day, a required sale of even a moderate amount of money could overwhelm its normal trading capacity. The researcher built a measure of this "funding pressure" by taking the predicted amount of money each company would need to sell and dividing it by that company's average daily trading volume before the announcement. This created a ranking of the 93 companies, from those facing the lightest burden relative to their normal activity to those facing the heaviest.

The study found a clear and strong link between this calculated pressure and the actual trading volume on July 6. Companies that were predicted to face higher funding pressure relative to their normal trading capacity saw significantly higher trading volumes on the implementation day. Specifically, for every standard increase in this pressure score, the trading volume on July 6 rose by approximately 12.1 percent compared to what would normally be expected. This result was not a fluke. The researcher tested the finding using several different statistical methods to ensure it was robust, and the result held up every time. Furthermore, the effect was tightly timed. The surge in trading volume happened specifically on July 6, the day the funds had to prepare for the change. When the researcher looked at the data for July 7, the day the new stock officially entered the index, the effect had largely disappeared. The trading volume on the second day did not show the same pattern, proving that the surge was a direct response to the funding requirement and not a random fluctuation or a long-term trend.

To be certain that this result was not caused by other factors, the study ruled out several alternative explanations. The researcher checked whether the effect was simply due to companies that were already volatile or had unusual trading patterns in the weeks leading up to the event. By using only data from the twenty trading sessions immediately before each test date, the study ensured that the results were not driven by recent market noise. The analysis also showed that the effect was not concentrated in the final hour of trading, which might have suggested that funds were rushing to finish their orders at the last minute. Instead, the increased volume was spread throughout the entire trading day. Additionally, the study found no evidence that the companies facing the highest pressure saw their stock prices drop significantly more than others. This suggests that the market absorbed the extra selling activity through increased volume rather than through sharp price declines.

The findings offer a new way to understand how large financial events ripple through the market. They show that when a massive new company joins a major index, the cost of that addition is not just paid by the new company, but is distributed across the existing members. The burden falls most heavily on those existing members whose normal trading capacity is small relative to the amount of money they are forced to sell. This creates a predictable map of where trading activity will increase. The study confirms that the market has a measurable capacity to absorb these large, forced trades, but that capacity is not infinite. When the required sale is large compared to the usual daily flow, the trading volume spikes to accommodate it. This insight helps explain the mechanics of how passive investment funds operate and how they interact with the broader market when the composition of their portfolios changes.

Technical Summary: Fast-Entry Funding Pressure and Incumbent Liquidity

Problem Statement
While the literature on index inclusion extensively documents the price and volume effects of the entrant security (the stock being added), it largely overlooks the "financing leg" of the trade. When a new security is added to an index, fully invested tracking portfolios must finance the purchase of the entrant. This necessitates selling incumbent securities. The paper posits that this financing burden is not distributed evenly; rather, it creates heterogeneous pressure across incumbent stocks based on their pre-event index weights and their ordinary trading capacity. The central research question is whether this model-implied funding pressure predicts a measurable increase in implementation-day trading volume for incumbents, and if so, whether this response is distinct from general market volatility or momentum.

Methodology
The study utilizes the inclusion of Space Exploration Technologies Corporation (SpaceX) into the Nasdaq-100 as a natural experiment. The event was announced on June 26, 2026, with an effective date of July 7, 2026, creating a specific implementation session on July 6, 2026.

Treatment Variable (Funding Pressure): The author constructs a "model-implied funding pressure" metric for 93 incumbent securities.
- First, an aggregate funding requirement ( $F$ ) is calculated based on a 1.3% entrant-weight scenario.
- This requirement is allocated across incumbents proportionally to their normalized pre-event weights ( $\tilde{w}_i$ ), yielding model-implied sale dollars ( $\hat{S}_i = F \tilde{w}_i$ ).
- The primary treatment variable is the ratio of these implied sale dollars to the security's pre-event Average Daily Dollar Volume (ADV), calculated from June 1–25, 2026. This scales the financing burden by the stock's ordinary trading capacity.
Outcome Variable: The primary outcome is the log ratio of July 6 volume to a "normal" volume baseline (estimated from the pre-event window).
Empirical Design:
- Cross-Sectional Regression: A linear model estimates the relationship between funding pressure and relative volume, controlling for log pre-event ADV and a securities-on-loan indicator.
- Robustness Checks: The study employs HC3 standard errors, a 20,000-draw Freedman-Lane residual randomization test, a 10,000-pair bootstrap, and leave-one-out regressions to ensure the slope is not driven by outliers or specific standard error assumptions.
- Placebo and Timing Tests: The author compares the July 6 coefficient against 38 pre-announcement dates (fixed baseline) and 19 dates in a "strictly lagged dynamic" design (where controls and baselines are constructed only from the preceding 20 sessions to avoid look-ahead bias).
- Mechanism Tests: The paper examines whether the volume response is concentrated in the final hour of trading or accompanied by abnormal price returns (market-model abnormal returns) to distinguish between liquidity absorption and price pressure.

Key Results

Significant Volume Response: A one-standard-deviation increase in model-implied funding pressure is associated with a 0.114 log point increase in implementation-day volume, equivalent to approximately 12.1% higher volume relative to normal. The coefficient is 8.6323 with a HC3 p-value of 0.0000283.
Robustness: The result holds across all inference methods (randomization, bootstrap, leave-one-out). The coefficient ranges from 8.077 to 9.367 in leave-one-out tests, with the maximum p-value remaining highly significant (0.000135).
Timing and Decay: The effect is sharply dated to the implementation session (July 6). On July 7, the coefficient drops to 3.4249 (p = 0.164). A stacked two-day model confirms a statistically significant decay interaction (-6.0506, p = 0.0107), ruling out the possibility that high-pressure stocks simply have persistently high volume.
Placebo Rankings: In the fixed-baseline design, the July 6 coefficient ranks first among 38 pre-announcement dates (exact p = 0.0256). In the stricter dynamic-control design (using only lagged data), the coefficient (6.0711) ranks first among 19 fully observed placebos (exact p = 0.050).
Capacity Scaling vs. Raw Dollars: A "denominator-light" specification using raw model-implied sale dollars (without dividing by ADV) yields a significant but less robust result (p = 0.0495) that becomes insignificant when richer trading-state controls (volatility, momentum) are added. This confirms that the ratio of burden to capacity is the economically meaningful driver, not just the absolute dollar amount of sales.
Mechanism: The volume increase is distributed across the full trading day, not concentrated in the final hour. There is no significant correlation between funding pressure and daily abnormal returns or post-event reversals, suggesting the market absorbed the turnover without a detectable price concession in the available data.

Significance and Claims
The paper claims to make the "financing leg" of an index addition measurable and testable. Its primary contributions to the literature are:

Cross-Sectional Identification: It converts a single index event into a cross-sectional test by varying the treatment (funding pressure) across incumbents based on their weights and liquidity.
Quantity Focus: It identifies trading quantity as the direct margin where financed rebalancing appears, rather than focusing solely on price effects.
Temporal Precision: It isolates the implementation-day response from general market dynamics through next-day decay analysis and strictly lagged controls.

The author concludes that the model-implied funding pressure provides a "sharply dated capacity-scaled quantity response." This suggests that for index providers and portfolio managers, the combination of entrant size, incumbent weights, and pre-event liquidity creates a predictable map of where trading capacity will be demanded during a rebalance. The paper validates this map in the specific case of SpaceX's fast-entry inclusion, noting that a historical panel using the same construction would be the necessary next step to test cross-event generality.

Technical Summary: Fast-Entry Funding Pressure and Incumbent Liquidity

More like this