Any securities expert

The January 31 abnormal return is not statistically significant

My event study finds that on January 31, 2020, the date of the Muddy Waters short-seller report, Luckin's ADS experienced an abnormal return of approximately negative 7.24 percent, but the associated t-statistic of negative 1.53 does not reach the 95 percent confidence threshold (p = 0.1261), meaning the price movement on that date is not statistically distinguishable from normal market noise under my model.

It therefore cannot be established as a corrective disclosure on price impact alone

Because the January 31, 2020 abnormal return is not statistically significant, the Muddy Waters report cannot be established as a legally cognizable corrective disclosure on the basis of price impact alone, and the defense position is reinforced by the fact that Luckin denied the allegations the same day and a prominent investor publicly rebutted the report.

The April 2 abnormal return is significant at any conventional threshold

My event study finds that on April 2, 2020, the date of Luckin's own board disclosure of fabricated transactions, the abnormal return was approximately negative 78.54 percent, with a t-statistic of negative 15.72 (p essentially zero), which is statistically significant at any conventional threshold.

But the April 2 decline is confounded and must be disaggregated

Although the April 2, 2020 abnormal return is statistically significant, the magnitude of that single-day decline, over 75 percent, reflects a confluence of value-relevant information beyond the fraud admission itself, including the simultaneous halt of trading, the prospect of NASDAQ delisting, and broader market conditions during a period of acute volatility, all of which must be disaggregated before the fraud-specific component of the price decline can be attributed to the alleged misrepresentations.

The event study is the right tool, applied under a principled protocol

An event study is the appropriate tool for assessing the loss causation aspect of a securities fraud claim, and the methodology I applied is consistent with that standard, but the selection and classification of event dates must follow a principled protocol grounded in the plaintiff's own allegations rather than post-hoc selection.

The low R-squared limits what a single-index model can attribute

The low R-squared values in my market model (0.123 for January 31 and 0.18 for April 2) indicate that the SPY benchmark explains only a modest fraction of Luckin's daily return variation, which is consistent with a thinly followed foreign private issuer whose price movements are driven substantially by firm-specific and China-market factors not captured by a US equity index, raising questions about the adequacy of any single-index model for this security.

Reasoning arc

I begin from the event study I conducted, which is the standard econometric tool for assessing price impact and loss causation in securities fraud matters. For the January 31, 2020 date, the data show a price decline that is directionally consistent with the plaintiff's theory but falls short of statistical significance at the 95 percent level; I cannot conclude that the Muddy Waters report caused a fraud-related abnormal return distinguishable from noise. For the April 2, 2020 date, the abnormal return is unambiguously significant, but statistical significance is a necessary condition for loss causation, not a sufficient one: the question is whether the entire decline, or only a portion of it, is attributable to the revelation of the alleged fraud as opposed to the trading halt, delisting risk, and contemporaneous market disruption. My opinion is that the evidence does not establish a clean, unconfounded corrective disclosure on January 31, and that the April 2 decline requires disaggregation before any damages figure derived from it can be accepted as reliable. I express no opinion on scienter, materiality as a legal standard, or ultimate liability; those determinations belong to the Court and the trier of fact.

Caveats and limits, stated by the witness

The expert states its own vulnerabilities before opposing counsel does, which is what makes the cross-examination section that follows worth reading:

• My market model uses SPY as the sole benchmark index. Luckin is a China-based issuer whose ADS price may be more closely correlated with Chinese equity indices or consumer-sector benchmarks; omitting a China-market or sector control is a model specification choice that opposing counsel may contest, and I acknowledge it affects the precision of the abnormal return estimates.
• The low R-squared values in my estimation regressions (0.12 to 0.18) mean that a substantial portion of Luckin's daily return variation is unexplained by the market model, which increases the standard error of the abnormal return estimates and reduces the power of the statistical tests, particularly for the January 31 event.
• I have not performed a full Cammer factor analysis on the record available to me; to the extent Luckin ADSs did not trade in an informationally efficient market during the class period, the foundational assumption of the event study and the Basic presumption of reliance would require further examination.
• The April 2, 2020 price decline occurred simultaneously with a trading halt and subsequent delisting proceedings; I have not yet quantified the independent price impact of those structural market events, and any damages model that attributes the full 78 percent abnormal return to the fraud disclosure alone without accounting for those factors would overstate recoverable loss.
• My opinion addresses statistical price impact and does not constitute a complete damages model; a workable, class-wide damages methodology consistent with the theory of liability would require additional analysis that I have not yet performed.