ConvexityIQ

ConvexityIQ

VNDA - A Case Study in Persistence-Aware Alpha

How ConvexityIQ™ Classified VNDA as Carry Before a +15% Repricing December 2025

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ConvexityIQ
Dec 26, 2025
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Executive Summary

In early December 2025, Vanda Pharmaceuticals Inc. (VNDA) was identified by the ConvexityIQ™ engine as a Carry-regime underlying at approximately $6.23. At the time, VNDA did not present as an urgent momentum opportunity. Price action was constructive but contained, and the advance appeared incremental rather than explosive.

From a structural convexity perspective, however, VNDA already exhibited the defining characteristics of persistent convexity: extended α-Half-Life, maximum Convexity Quotient, and multi-window ROI reinforcement. What followed was not a regime transition or volatility event, but the orderly monetization of convexity that had already survived time and decay.

As of the most recent observation, VNDA trades near $7.16, representing an advance of roughly +15% from the level at which ConvexityIQ™ had already classified the structure as fully qualified Carry.

This case reinforces a core ConvexityIQ™ principle:

Alpha is not defined by immediacy.
It is defined by persistence.

The Market’s View vs. the Structural Reality

Conventional Interpretation

From a traditional technical or momentum-based lens, VNDA’s setup in early December could be interpreted as:

  • A developing uptrend with intermittent consolidation

  • Improving but uneven follow-through

  • A “working trade” rather than an urgent opportunity

There was no obvious breakout imperative and no requirement that price resolve immediately.

Convexity-Persistence Interpretation

From a ConvexityIQ™ perspective, the same conditions reflected something more important:

  • Convexity was already reinforced across time windows

  • Persistence was extended, not fragile

  • The structure was ridge-qualified, not transitional

The distinction matters. One view waits for acceleration; the other explains why acceleration can occur without destabilization.

What ConvexityIQ™ Saw in Advance

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