Papers for

crypto exchange operators

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Token marks improve crypto treasury fund measurement outside market hours

NEST: Stale-Robust Tokenized-Stock Measurement for a Crypto-Treasury LETF Stack

Abstract: Tokenized equities trade while listed markets are closed, so their marks could improve off-hours measurement along layered exposures that link Bitcoin, crypto-treasury stocks, and leveraged ETFs. A token return and the next opening gap, however, share the price move from the previous close to the token mark, so part of their apparent fit is mechanical. We develop NEST, a stale-robust protocol that separates this shared-history fit from conditional measurement value. A shared-history identity and a variance-clock bound show how much fit timing alone can generate. The partial determination index (PDI), the squared partial correlation between token and gap given public controls, measures what remains, and a finite-sample frontier expresses the partial-F decision in PDI units. Product, provenance, timestamp, and execution audits decide whether an informative mark is admissible. For MSTRx, a tracker certificate on MicroStrategy (MSTR), a token-only $R^2$ of 0.916 shrinks to a modest increment once Bitcoin, mark age, and a pre-09:00 MSTR premarket proxy are controlled: the token explains 15.7% of the remaining gap variation (1% frontier 0.031), and 14.0% to 17.0% under stricter clock variants, including one in which every token mark precedes 09:00. A trade-level reconstruction on Gate gives 25.2%; NVDAX and AAPLX clear their frontiers, whereas TSLAX does not. An admitted mark updates, rather than replaces, BTC-unit exposure diagnostics for the BTC-MSTR-LETF chain.

Thu 15 OctCryptography and Security
The gist
Tokenized stocks can trade even when regular stock markets are closed, offering new ways to measure investments that mix Bitcoin and related stocks. The authors show that some of the correlation between token prices and next-day stock price moves is automatic because both rely on earlier prices. They develop a method, called NEST, that separates this automatic correlation from truly useful information about price changes. Their tests on real token products show that token prices add measurable, though limited, insight beyond what is already known from traditional data.
Open → 2610.21491v1