ETF视角下的股指期货择时

1. Report Industry Investment Rating No relevant content provided. 2. Core Views of the Report - Different risk - stratified ETF trading data shows certain timing effects on stock index futures [3]. - Incorporating ETF share and market trend changes can effectively improve the deficiencies of trading volume factors [4]. 3. Summary by Relevant Catalogs 3.1 Risk - type and Low - risk ETFs - Stock - type ETFs are divided into risk - type (including industry, theme, strategy, and style ETFs) and low - risk type (represented by scale - type ETFs). Their trading reflects market risk preference, and the report explores using this to time stock index futures [11]. - As of 2025/12/11, there were 1,073 stock - type ETFs, with scale - type ETFs having 367 (34.2%) in quantity, 9,189.9611 billion shares (42.7%), and an asset net worth of 24,072.5461 billion yuan (66.3%) [12]. 3.2 Weekly Factor Testing 3.2.1 Volume Factor - Compare the weekly average daily volume change rates of risk - type and low - risk ETFs. If the low - risk change rate is greater, go long on stock index futures on Monday; otherwise, go short. - Back - testing shows that the volume factor has different performances on different stock index futures. For example, IH has an annualized return of 8.81%, an annualized volatility of 20.77%, a Sharpe ratio of 0.42, a maximum drawdown of - 43.48%, a Calmar ratio of 0.20, and a turnover rate of 11.39% [22]. - The performance of the volume factor on IH and IF changed significantly from 20 - 21, with the strategy curve turning from downward to upward [24]. 3.2.2 Turnover Factor - Calculate the weighted average of daily turnover rates of different segments. Compare the weekly average daily turnover rate changes of risk - type and low - risk ETFs. If the low - risk change rate is greater, go long on stock index futures on Monday; otherwise, go short. - Back - testing shows that the turnover factor also has different performances on different stock index futures. For example, IH has an annualized return of 2.89%, an annualized volatility of 20.78%, a Sharpe ratio of 0.14, a maximum drawdown of - 54.68%, a Calmar ratio of 0.05, and a turnover rate of 11.45% [30]. - The turnover factor also showed a style shift in 21, with a more obvious inflection point [36]. 3.3 Double - Factor Superposition Testing - Incorporate the daily frequency share factor based on the relative changes in weekly average daily volume and daily turnover. Reverse the volume or turnover signal according to the share change rate comparison. - After incorporating the share change rate, the performance of IH, IF, and IC strategies improved, and the drawdown before 2021 was also improved. For example, the "volume + share change rate" strategy for IH has an annualized return of 15.95%, an annualized volatility of 20.76%, a Sharpe ratio of 0.77, a maximum drawdown of - 29.35%, a Calmar ratio of 0.54, and a turnover rate of 14.19% [50]. - The combination of turnover and share change performed well before 2025 but had large drawdowns in 2025, possibly due to changes in the relationship between ETFs and the market [63]. 3.4 Three - Factor Combination Testing - Incorporate the market trend factor based on the double - factor framework. Reverse the volume or turnover signal when the low - risk ETF share change rate is less than the risk - type and the target price is falling. - After adding the turnover factor with share change rate and market trend, the drawdown in 2025 was partially corrected, but the drawdown from 20 - 21 could not be fully repaired. The volume factor did not show obvious improvement after adding two factors [75]. 3.5 Four - Factor Combination and Factor Optimization - Combine and optimize the volume and turnover factors. First, superpose the two original factors, and then filter with share change rate and market trend. - After optimization, the factor effect improved significantly. With a low turnover rate, the strategy still performed well after deducting slippage and fees. For example, the optimized four - factor strategy for IH has an annualized return of 23.64%, an annualized volatility of 20.69%, a Sharpe ratio of 1.14, a maximum drawdown of - 19.59%, a Calmar ratio of 1.21, and a turnover rate of 15.35% [97]. 3.6 Summary - The report discusses the application of stock - type ETF data in stock index futures timing. The four - factor strategy constructed by ETF volume, turnover, share change, and market trend has good timing effects on various stock index futures [98].