Liquidity-Shock vs Information-Shock Reversal in Japanese Large Caps: Buy a TSE Large Cap at the Next Open After a >=2.5-Sigma Market-Relative One-Day Drop on NON-Extreme Volume, Fixed 5-Session Clock (JPEQ 1-DAY, 100-name event panel, long-only, flat most of the time)

Original Research Lead hypothesis, first ever use of the JPEQ venue (3 prior experiments, 0.1% of corpus; 0 outcomes). Mechanism (Campbell-Grossman-Wang 1993, Cooper 1999, Llorente et al. 2002; the Japanese short-term reversal literature, e.g. Iihara-Kato-Tokunaga 2004, finds reversal far stronger in Japan than momentum): a large one-day drop in a stock RELATIVE TO THE MARKET is either a liquidity/inventory shock (non-informed selling absorbed by liquidity providers who demand a premium -> price reverts) or an information shock (news, earnings -> price drifts). Abnormal volume separates them: information shocks print extreme volume; liquidity shocks print ordinary-to-moderately-elevated volume. The strategy buys only the liquidity-type shocks. Universe: the 100 TSE Prime large caps in config/jp_equities_universe.txt (fixed list of current large caps: no point-in-time TOPIX membership file exists for Japan, so the universe carries survivorship bias, disclosed in risk_factors; names are eligible only once they have >= sigma_lookback+5 sessions of history, e.g. 285A listed 2024). Signal per stock i on session D close: r_i = ln(C_D/C_{D-1}); market proxy m_D = equal-weight mean of r_j over universe names with a bar on D; residual e_i = r_i - m_D; sigma_i = std of e_i over the previous sigma_lookback sessions (ending D-1, no lookahead); z_i = e_i / sigma_i; volume ratio vr_i = V_D / mean(V_{D-20..D-1}). Event: z_i <= -z_threshold AND vr_i < vol_ratio_max. Entry at the NEXT session open (platform next_open_fill on session venues, supported). Exit by market order decided at the close of the (hold_sessions-1)th session after entry, filling at the open hold_sessions sessions after entry (open-to-open holding of hold_sessions sessions). Pre-registration measured from catalog daily bars 2018-01 to 2026-10 with the baseline rule (z<=-2.5, vr<2.5, enter next open, exit open 5 sessions later): about 1,900 qualifying name-events on roughly 950 distinct entry dates (the z<=-2.5 & vr<1.5 bucket: 810 events/475 dates; 1.5<=vr<2.5: 1,204 events/704 dates); mean raw 5-session return ~+1.1% per event, market-adjusted (minus equal-weight universe forward return) +0.38% (vr<1.5) and +0.48% (1.5-2.5), while the excluded extreme-volume bucket (vr>=2.5) is market-adjusted -0.27%, which is the mechanism's own internal control. The same-day statistic is weak (date-clustered t ~1), so this is a genuine test, not a sure thing; one losing year (2021) in both kept buckets. Cost arithmetic: JPEQ commission 0, no transaction tax, modelled half spread 3 bp -> ~0.06% round trip plus impact; expected gross capture ~1.0% raw (~0.4% market-adjusted) per trade = more than 6x the round trip even on the market-adjusted figure. Long-only on the MARGIN account at 1x (no leverage; the long arm is used because the measured short arm of the mirror event was not robust and Lesson 230 warns against assuming it). Risk control route (b): signal/time exit plus capped sizing, 10% of equity per position, at most 8 concurrent (gross <= 80%, no leverage). Execution: all orders are market orders at session opens; positions sized in whole 100-share board lots via self.lot_size() (entries round down; skip if one lot exceeds the 10% cap); market orders into a locked daily price limit are refused by the venue and simply not filled (skip that event; for exits retry at the next open). Metrics in JPY.