Core Viewpoint - The A-share market experienced a strong start to the new year, particularly in the cyclical sectors, with the oil and petrochemical sector leading the gains at 5.53% [1] Group 1: Market Performance - The oil and petrochemical sector topped the Shenwan first-level industry rankings with a 5.53% increase, while the basic chemical sector ranked third with a 3.45% increase [1] - Institutional consensus indicates a positive outlook for cyclical assets post-holiday, with expectations of a market rebound supported by policy expectations and liquidity [1] Group 2: Investment Opportunities - Key investment themes include the "anti-involution" concept driven by improved supply-demand dynamics and industry profit recovery, with a focus on sectors benefiting from price increases such as precious metals, oil and petrochemicals, and basic chemicals [1] - The global landscape shows increased macro risks due to geopolitical tensions and tariff policies, prompting a focus on "weak dollar assets" like precious metals, non-ferrous metals, and oil and gas [1] Group 3: ETF Performance - Penghua Fund's oil ETF (159697) is the first in the market to track the National Oil and Gas Index, covering key companies in the oil and gas industry, with a one-year increase of 31.43% compared to the 19.34% rise of the CSI 300 index [2] - The chemical ETF (159870) tracks a refined chemical industry index, achieving a one-year growth of 51.79%, effectively capturing structural opportunities in the transition from traditional capacity to high-end and new energy materials [2] Group 4: Liquidity and Market Acceptance - As of February 13, 2026, the oil ETF (159697) and chemical ETF (159870) ranked first in their respective categories with sizes of 1.828 billion and 35.533 billion, indicating strong liquidity and market recognition [3] - These ETFs provide investors with low-cost, high-transparency, and risk-diversified investment tools, addressing the complexities and risks associated with direct investments in cyclical stocks [3]

- The report discusses the rotation strategy for micro-cap stocks, highlighting the relative net value of micro-cap stocks to the "Mao Index" at 2.41, which is above its 243-day moving average of 1.91. Additionally, the 20-day closing price slope for micro-cap stocks is positive at 0.30%, while the Mao Index slope is negative at -0.08%[2][19][28] - The rotation strategy includes two sub-strategies: one based on the relative net value and slopes of micro-cap stocks and the Mao Index, and another based on the M1 indicator's 6-month moving average, which has declined, leading to a mid-term allocation shift from micro-cap stocks to the Mao Index[2][19][28] - Timing indicators for micro-cap stocks include the 10-year government bond yield (threshold 0.3) and micro-cap stock volatility crowding (threshold 0.55). If either indicator reaches its threshold, a closing signal is triggered. Current values show the volatility crowding at -48.18% and the 10-year bond yield at 9.68%, indicating manageable mid-term systemic risk[19][22][28] - Short-term divergence monitoring indicates no signals of upward momentum exhaustion for micro-cap stocks, suggesting continued stability in the short term[19][26][28] - The macro timing model recommends a 70% equity allocation for February, with signal strengths of 40% for economic growth and 100% for monetary liquidity. The model's year-to-date return is 14.59%, compared to Wind All A's return of 26.87%[58][60][61] - Eight major stock selection factors were analyzed, with growth (IC mean 14.04%) and consensus expectations (IC mean 11.33%) performing well, while value and market capitalization factors showed weaker performance. Growth and consensus expectations factors are expected to continue performing strongly in the post-holiday period[61][63][66] - Convertible bond selection factors were constructed based on the relationship between convertible bonds and their underlying stocks, using factors like parity, floor price, and premium rate. Last week, stock value and convertible bond valuation factors achieved high IC mean values[70][72][74]