市场稳步上行，IC及IM主力合约贴水幅度收窄

• The report introduces a quantitative model for estimating dividend points in stock indices, which is crucial for accurately assessing the premium or discount in stock index futures contracts. The model incorporates factors such as component stock weights, dividend amounts, total market capitalization, and index closing prices[38][44][46] - The model calculates the dividend points for a stock index during the period from the current date (t) to the futures contract expiration date (T) using the formula: $\text{Dividend Points} = \sum_{n=1}^{N} \left( \frac{\text{Dividend Amount of Stock n}}{\text{Total Market Cap of Stock n}} \times \text{Weight of Stock n} \times \text{Index Closing Price} \right)$ This formula ensures that only stocks with ex-dividend dates between t and T are included[38][44] - Component stock weights are dynamically adjusted using the formula: $W_{n,t} = \frac{w_{n0} \times (1 + r_{n})}{\sum_{i=1}^{N} w_{i0} \times (1 + r_{i})}$ Here, $w_{n0}$ represents the weight of stock $n$ at the last disclosed date, and $r_{n}$ is the non-adjusted return of stock $n$ between the last disclosed date and the current date[45] - The model estimates net profit for stocks without disclosed data by categorizing companies into stable and unstable profit distribution groups. Stable companies are predicted based on historical patterns, while unstable ones use the previous year's profit as a proxy[47][50] - Dividend payout ratios are estimated using historical averages. If a company paid dividends in the previous year, that ratio is used; otherwise, a three-year average is applied. Companies with no dividend history are assumed not to pay dividends[51][53] - Ex-dividend dates are predicted using a linear extrapolation method based on historical intervals between announcement and ex-dividend dates. Default dates are applied if historical data is insufficient or inconsistent[51][56] - The model's accuracy was validated by comparing predicted dividend points with actual values for the Shanghai 50, CSI 300, and CSI 500 indices in 2023 and 2024. The Shanghai 50 and CSI 300 predictions showed errors within 5 points, while the CSI 500 had slightly larger errors, around 10 points[57][61][66]