This is a direct test of the QuantConnect / Quantpedia 'Asset Class Trend Following' mechanism (Faber 2007, 'A Quantitative Approach to Tactical Asset Allocation'). It runs on the commission-free USEQ venue, which has decades of split-adjusted daily history. The universe comes from the source's asset-class design and was not picked with hindsight. It holds one liquid ETF per asset class: US equities (SPY.USEQ), developed ex-US equities (EFA.USEQ), US 7-10y Treasuries (IEF.USEQ), broad commodities (DBC.USEQ) and gold (GLD.USEQ). The source's fifth sleeve is REITs (VNQ), but VNQ is not in our USEQ universe or catalog, so GLD replaces it as a real-asset sleeve whose data is present. That swap is the only deviation from the source. On the last trading session of each calendar month, each ETF's 10-month SMA is the mean of its last 10 month-end closes. It is maintained incrementally: one month-end close is appended per month to a 10-slot deque. Per-bar cost is O(1) with no history rescans, which keeps the run inside the 300s sandbox limit. If the month-end close is above its 10-month SMA, the sleeve is held at 1/5 of equity (20% target weight); otherwise the sleeve sits in cash. There is no leverage (1.0x on the margin account), no shorting, and no other filter or gate: the mechanism runs ungated, exactly as published. Flat state: a sleeve is in cash whenever it is below its SMA. Historically each sleeve spends about 25-40% of months in cash, and the whole book is fully in cash in about 5-10% of months (late 2008, for example). SPY.USEQ is the primary instrument (bar_type SPY.USEQ-1-DAY-LAST-EXTERNAL); the other four come in through extra_instruments / extra_bar_types at 1-DAY. The mechanism with instrument and timeframe removed: each asset follows its own slow monthly moving-average trend, is either long or in cash, and gets an equal budget across uncorrelated asset classes. That is different from the factory's crypto cross-sectional rotation and crypto daily TSMOM runs: different asset class, different venue, a monthly clock, and no ranking. source_ref: QuantConnect Tutorials, 04 Strategy Library / 12 Asset Class Trend Following, section 'Method' (commit 4a341890).