What Are Fails-to-Deliver?

Why options traders care

Persistent FTDs on a name signal hard-to-borrow conditions, which shift put-call parity (synthetic long stock trades below frictionless parity by the borrow rebate), elevate options market-maker hedging cost, and frequently precede or accompany short-squeeze unwinds.

What It Is

Under U.S. equity settlement rules (SEC Rule 15c6-1, transitioned to T+1 effective 2024-05-28), the seller of equity securities must deliver the shares to the buyer's clearing account within one business day of the trade date. When delivery does not occur on settlement date, the resulting unsettled obligation contributes to the fails-to-deliver figure. The publicly reported FTD quantity is the aggregate net balance in NSCC's Continuous Net Settlement (CNS) system as of the settlement date - net of intra-day buy/sell offsets across clearing participants, not a gross trade-level count.

Three structural sources produce FTDs:

• Short-sale failures. A short-seller without a confirmed locate, or whose locate evaporates between trade date and settlement, fails to deliver. This is the most common interpretation.
• Long-sale settlement failures. A long-seller broker fails to deliver because the broker has pending settlements on the long position itself (an upstream chain of settlements). Common in ETF creation/redemption arbitrage where the AP is creating shares while simultaneously selling components.
• Buy-side failures (rare). The buyer broker fails to take delivery on settlement date. Generally rare; categorized separately under the SEC stock-settlement-failure regime.

How It Is Reported

The SEC publishes FTD data under FOIA semi-monthly. First-half data (settlement dates from the 1st through the 15th of a given month) is typically published at the end of that month; second-half data (settlement dates from the 16th through month-end) is typically published around the 15th of the following month. The most recent FTDs are therefore 2-6 weeks stale at any given check.

Each line in the FTD file contains:

• Settlement date. The date on which delivery should have occurred.
• CUSIP and ticker. Identifies the security.
• Failed-to-deliver quantity. The aggregate net balance in NSCC CNS for that security on that settlement date - the net unsettled position across all clearing participants after intra-day buy/sell offsets, not a gross trade-level count.
• Price. The reference closing price on the settlement date.

The Threshold Securities List, published daily by each U.S. exchange, identifies securities with FTDs of at least 10,000 shares per day for five consecutive settlement days where the FTD count is at least 0.5% of total shares outstanding. Names on the Threshold List are subject to the Reg SHO close-out requirement: the broker-dealer must close the failing position by purchasing or borrowing the shares within the prescribed window.

How to Read the Data

FTD data carries four interpretive layers:

• Magnitude vs float. A 100K FTD count on a small-cap with 5M float is qualitatively different from 100K FTDs on a mega-cap. Normalizing FTD count by float (or by daily volume) is the cross-sectional comparison metric.
• Persistence. A single-day FTD is operational noise (a clearing-system reconciliation issue). A series of consecutive FTDs is a borrow-tight signal that indicates locate constraints in the lending market.
• Threshold-list status. Persistent threshold-list status confirms structural HTB conditions and compels close-out activity that ripples back into options pricing through changed put-call parity dynamics.
• Coupling with short-interest direction. Rising FTDs alongside rising short interest is a directional-bear thesis being expressed despite borrow tightening. Rising FTDs alongside falling short interest can indicate forced-cover activity hitting tight borrow.

How FTDs affect options pricing and hard-to-borrow constraints

FTDs and the hard-to-borrow rebate together reshape options pricing on persistent-FTD names. The mechanic: in a frictionless borrow market, put-call parity sets C - P = S - PV(K). Under HTB conditions, the rebate paid to lenders can spike (annualized rates of 20-100% are not rare in extreme HTB names), and the synthetic-long-stock combo (long call + short put at the same strike) trades below the frictionless-parity price by roughly the present value of the forgone lending revenue. The combo is cheap versus frictionless parity but not a free discount - the gap equals the borrow cost an actual-stock holder would capture by lending shares. Equivalently, puts trade rich and calls trade cheap relative to vanilla-borrow parity.

Options market-makers compensate by adjusting their market-making in two ways. First, they widen spreads on calls in HTB names because their hedge (short stock) is not a free lunch; the borrow cost is a friction the dealer must price into the call. Second, they avoid carrying delta-neutral books on names with high HTB rebates because the cost-of-carry compounds over the position lifetime. The result is a structural premium that long-call, short-put, or long-call-spread strategies on persistent-FTD names can capture relative to vanilla-borrow regimes.

Operationally, traders should observe the SEC Threshold Securities List and screen across the chain when those names are flagged. Calendar spreads in HTB names sometimes show idiosyncratic curvature reflecting time-varying borrow expectations; vertical spreads tend to compress because the dealer cannot freely arbitrage between expirations.

Trading Applications

For options traders, FTD data informs three kinds of decisions:

• Hard-to-borrow setup detection. Persistent FTDs (especially threshold-list status) precede or accompany HTB conditions. Names rotating onto the threshold list are candidates for premium-collection strategies on the put side, because put protection becomes structurally bid.
• Synthetic-stock pricing in HTB regimes. Long-call-short-put combos at the same strike trade below frictionless parity in HTB names by roughly the borrow rebate. The apparent discount is not free - it equals the lending revenue an actual-stock holder would earn. Use the combo as a directional-long expression only when forgoing that lending revenue is acceptable; price the combo against the prevailing borrow rebate before comparing to actual stock.
• Squeeze-risk amplification. Names accumulating consecutive-day FTDs while short interest stays high are squeeze-prone. The structural setup (overpositioned shorts unable to cover at reasonable cost) is the same one that produced the GameStop and AMC episodes.

Common Misinterpretations

• "FTDs are evidence of naked shorting." Some FTDs result from naked short-selling, but most arise from operational settlement failures, ETF creation-arb timing mismatches, and ordinary locate-evaporation events. The SEC enforcement focus is on persistent FTDs above the threshold, not on every daily FTD.
• "FTDs always indicate bearish positioning." Long-side and ETF-arbitrage failures contribute to the net CNS balance reported as the FTD figure. Reading FTDs as a purely bearish-positioning signal conflates directional-short failures with operational and ETF-arbitrage settlement frictions.
• "Threshold-list status means the stock is uninvestable." Threshold-list status is a regulatory categorization, not an investment thesis. Many threshold-list names have outsized future returns either direction; the categorization adjusts settlement procedures, not market quality.

Limitations

• Multi-week reporting lag. First-half settlement dates publish at month-end; second-half settlement dates publish around the 15th of the following month, leaving the most recent FTDs 2-6 weeks stale at any given check. Real-time FTD analytics require building separate indicators (consecutive-day-on-threshold-list flags, observed borrow rebate spikes).
• Net balance, not per-participant detail. The published figure is an NSCC CNS aggregate net balance, not a per-clearing-participant breakdown. Decomposition by source (directional short, long-side fail, ETF arb) is not directly available in the public file.
• Cross-sectional comparison needs normalization. A 100K FTD on a 5M-float small-cap is meaningful; the same count on a mega-cap with 4B float is operational noise. Cross-sectional comparison without normalization produces false positives.

Related Concepts

Short Interest · Short Volume · Market Structure · Gamma Squeeze · Liquidity · Dealer Gamma

References & Further Reading

• SEC Regulation SHO. Rule 203 (locate requirement) and Rule 204 (close-out requirement). Originally adopted 2004; close-out amendments effective 2008.
• Boni, L. (2006). "Strategic delivery failures in U.S. equity markets." Journal of Financial Markets, 9(1), 1-26. Empirical evidence that pre-Reg SHO settlement failures were strategic rather than purely operational; foundational study connecting FTDs to short-sale economics.
• Evans, R. B., Geczy, C. C., Musto, D. K., and Reed, A. V. (2009). "Failure Is an Option: Impediments to Short Selling and Options Prices." Review of Financial Studies, 22(5), 1955-1980. Direct empirical link between settlement failures and options-pricing distortions; the canonical FTD-to-options reference.
• SEC Rule 15c6-1 (Standard Settlement Cycle for Broker-Dealer Transactions). T+2 effective 2017-09-05; T+1 amendment effective 2024-05-28.

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