Spinoff Arbitrage Strategy

The thesis

When a parent company spins off a division as a separately traded stock, the spinoff is distributed pro-rata to existing parent shareholders. That distribution event creates a temporary but predictable supply-demand imbalance: index funds tracking the parent must sell the spinoff (it’s not in their index), institutional holders with mandates pinned to the parent’s sector or market cap must sell (the spinoff often falls outside the mandate), and sell-side analysts who covered the parent typically don’t pick up the spinoff for weeks or months. The spinoff faces a wave of forced sellers and a vacuum of natural buyers.

The forced-selling pressure typically peaks 1–4 weeks after distribution. Once it abates, the spinoff often re-rates upward as fundamentals reassert themselves and natural holders accumulate. Cusatis, Miles, and Woolridge (1993) documented an average ~10–15% one-year excess return on US spinoffs over the 1965–1988 period. Joel Greenblatt’s practitioner book popularized the strategy with retail investors, and the documented effect has persisted in subsequent decades despite the publicity.

Academic basis

Cusatis, Miles, and Woolridge’s 1993 Journal of Financial Economics paper is the canonical reference. Their sample of 161 spinoffs from 1965–1988 produced a 33-month buy-and-hold abnormal return of roughly +25% for spinoffs and +18% for parents (relative to size-matched benchmarks). The effect was strongest in the smallest spinoffs, consistent with the forced-selling explanation: small spinoffs face the most acute mandate-mismatch and the least natural-buyer absorption.

McConnell and Ovtchinnikov (2004) replicated the effect on a 1965–2000 sample with the additional finding that the post-spin returns were predictable from the parent’s pre-spin characteristics — consistent with the “hidden value” thesis Joel Greenblatt advanced in You Can Be a Stock Market Genius (1997). McConnell, Ozbilgin, and Wahal (2001) further showed that activist involvement in the parent during the spin period predicts even higher post-spin returns, suggesting that spinoffs are sometimes used as catalysts to unlock value that conglomerates obscure.

How Alpha Suite implements it

• EDGAR 10-12B detection — the scanner queries for Form 10-12B and 10-12B/A filings (the SEC registration statements for spinoffs) in the last 180 days, plus 8-K filings containing “completion of spin-off”, “spin-off completed”, or “distribution of” language in the last 120 days.
• Ticker resolution — the spinoff entity ticker is extracted from the filing prose via regex on patterns like “(NYSE: TICKER)” or “(NASDAQ: TICKER)”. The parent ticker is filtered out so we never grab it as the spinoff. Filings without an extractable spinoff ticker are dropped.
• Distribution date parsing — from the filing text via regex (“distribution date ... March 15, 2026”); falls back to filing date or first available yfinance bar.
• Days-since-spinoff window — the score peaks at 7–30 days post-distribution (the forced-selling sweet spot), tapers through 30–60 days, and goes negative outside 7–120 days. Spinoffs less than 24 hours old are skipped (let initial price discovery happen).
• Size-relative-to-parent multiplier — spinoffs less than 10% of parent market cap get +10 (strong forced-selling effect; the classic Greenblatt setup); 10–25% gets +5; 25–50% gets 0; over 50% gets -5 (too big for parent index funds to ignore).
• Post-spin drawdown bonus — spinoffs trading more than 15% below their distribution-day open get +10 (heavy oversold = strong setup); 5–15% drawdown gets +5; flat-to-up gets 0 or -5 (already running, less edge).
• Market-cap floor of $200M — the strategy avoids micro-cap spinoffs where liquidity is thin and the bid-ask cost eats the edge.
• ATR-based take-profit and stop — with a 30% post-publication decay haircut consistent with McLean-Pontiff (2016).
• 90-day horizon — matches the empirical window where the forced-selling rebound completes most reliably; the longer-horizon Cusatis-Miles-Woolridge effect (33 months) is captured in part by the size and drawdown filters.

When it fires

The cleanest signals are small spinoffs (sub-10% of parent market cap) of mid-or-large parent companies, 7–30 days post-distribution, with a -10% or worse post-spin drawdown. These conditions converge most often when (a) a conglomerate spins off a non-core unit that doesn’t fit any major index, (b) the parent is in the S&P 500 (so passive funds are forced to sell the spinoff), and (c) the spinoff is in a different sector than the parent (so sector-specialist holders also sell).

Realistic signal volume: 0–3 active signals at any time. Spinoffs are rare events — maybe 20–40 per year market-wide, with only a handful within the optimal 7–90 day window at any given moment. The engine is designed to produce few high-conviction fires rather than constant noise.