绝对收益产品及策略周报（260112-260116）：上周461只固收+基金创新高

Fund Performance - As of January 16, 2026, the total scale of fixed income + funds in the market reached CNY 21,743.24 billion, with 1,152 products available, of which 461 achieved historical net value highs last week[2] - The median performance of various fund types for the week (January 12-16, 2026) was as follows: mixed bond type I (0.13%), mixed bond type II (0.21%), partially bond mixed type (0.28%), flexible allocation type (0.14%), bond type FOF (0.21%), and mixed type FOF (0.34%) [2] - The median returns by risk level were: conservative (0.16%), stable (0.24%), and aggressive (0.25%) [2] Asset Allocation and ETF Rotation - The macro environment forecast for Q1 2026 indicates a "Slowdown," with the returns of major indices as of January 16, 2026: CSI 300 (2.20%), China Government Bond Total Wealth Index (0.03%), and AU9999 contract (6.10%) [3] - The recommended industry ETFs for January 2026 include: China Coal ETF, China Steel ETF, China Securities Company ETF, and China Bank ETF, with a combined return of -2.65% for the week and -0.36% for January [3] Absolute Return Strategy - The macro-timed stock-bond 20/80 rebalancing strategy yielded a return of -0.04% last week, with a year-to-date (YTD) return of 0.51% [4] - The small-cap value style within the stock-bond 20/80 combination showed the best performance with a YTD return of 1.64%, while PB earnings, high dividend, and small-cap growth yielded 0.34%, 0.17%, and 1.23% respectively [4] - The cumulative return for the small-cap value combination based on a macro momentum model was 2.43%, while the PB earnings combined with small-cap value yielded a YTD return of 0.86% [4] Risk and Performance Insights - A total of 461 fixed income + products reached historical net value highs, including 195 mixed bond type I, 123 mixed bond type II, 80 partially bond mixed, 22 flexible allocation, 8 bond type FOF, and 33 mixed type FOF[19] - The performance of absolute return strategies is subject to risks such as factor failure, model mis-specification, and historical statistical regularity failure[4]