Source: QuantConnect Strategy Library #23 'Mean Reversion Effect in Country Equity Indexes' (Quantpedia), section 'Method'. Source rule: rank 19 country ETFs by 36-month return, long the bottom 4, short the top 4, rebalance every 36 months. AS WRITTEN IT IS NOT TESTABLE HERE: our USEQ universe has only 8 single-country ETFs (EWG, EWJ, EWT, EWU, EWY, EWZ, FXI, INDA), so bottom-4 plus top-4 is the whole universe, and a 36-month rebalance gives about 7 rebalances since 2000. The source's reported returns are treated as unverified. Adaptation that keeps the economic mechanism (long-horizon overreaction and valuation mean reversion at the country-index level): (1) drop the short leg, per L137 on neutral books and because the reversal premium in the literature sits mainly in the loser leg; (2) replace the single 3-year rebalance with 12 overlapping monthly cohorts in the Jegadeesh-Titman style, each held 12 months, which gives about 12x more independent formation dates; (3) the universe is defined by a point-in-time rule, not a list: every single-country ETF in the USEQ universe file that has at least 756 sessions of history at the formation date. INDA joins in 2015 and FXI in 2007. Each month, the cohort buys the 2 worst 36-month (756-session) total-price-return names, and only those with a NEGATIVE 36-month return; if fewer qualify, that cohort's slot stays in cash. Each cohort gets 1/12 of equity split equally across its names. Honest caveat for the analyst: this sits in the USEQ-daily family that L128 flags. It is proposed because the user's source mechanism cannot be expressed at 1H or on crypto (there are no country indexes, and a 36-month lookback on crypto's roughly 6-year history leaves almost no sample), so the priority is low and the predictions are modest. Implementation note, given the recent run of sandbox timeouts on 2400-day daily windows: keep a rolling deque or a precomputed close array per ETF and compute 756-session returns in O(1) per bar. Never rescan history in on_bar.