Core Viewpoint - The article discusses the construction of an ETF grid trading strategy based on the Average True Range (ATR), aiming to capture profits from price fluctuations by buying low and selling high [1][10][13]. Group 1: ETF Market Development - Since Q4 2018, the number of equity ETFs in the A-share market has increased from 133 to 1,043 by Q3 2025, with total assets rising from 0.27 trillion yuan to 3.71 trillion yuan [8]. Group 2: Single Index Grid Trading Strategy - A single index grid trading strategy is constructed using ATR, focusing on 28 large-scale sample equity indices. Historically, the strategy has shown limited returns during bull markets while effectively controlling drawdowns in bear markets [2][16]. - The ATR indicator reflects the true volatility of an index, with historical ATR values showing significant fluctuations during different market periods [18][20]. Group 3: Incorporating Timing Signals - The article introduces timing signals based on ATR trends to enhance the grid trading strategy's performance, particularly in bull markets, while reducing drawdowns in bear markets [34][35]. - Backtesting results indicate that incorporating timing signals significantly improves both returns and drawdowns compared to the original grid trading strategy [38][45]. Group 4: ETF Grid Trading Strategy Combination - A robust ETF grid trading strategy combination is constructed using a selection of liquid ETFs, with a historical annualized return of 12.57% and a maximum drawdown of 6.80% from December 31, 2018, to September 30, 2025 [54][57]. - The strategy consistently outperformed a fixed 30% equity allocation ETF combination across various years, demonstrating positive excess returns [63][64]. Group 5: Sensitivity Analysis of Parameters - The performance of the ETF grid trading strategy combination shows low sensitivity to the frequency of updating the selection pool, with minimal differences in returns across various update cycles [67]. - Shorter rebalancing periods (1-2 days) yield higher cumulative returns compared to longer periods, indicating a preference for more frequent adjustments [71]. - Increasing the upper limit of equity allocation enhances both returns and drawdown characteristics, providing different risk-return profiles [77]. Group 6: Broad-based Index ETF Strategy - A broad-based index ETF grid trading strategy, utilizing common indices, achieved an annualized return of 11.78% and a maximum drawdown of 11.50% over the same period [79][82].

Group 1 - The seventh "5 15-5 19 Small Investor Protection Publicity Week" event was held from May 15 to 19 in Beijing, Shanghai, and Shenzhen, focusing on promoting investment knowledge and advocating rational, value, and long-term investment principles [1] - The event featured discussions led by chief analysts from brokerage firms, public interest lawyers, and representatives from listed companies to enhance investors' risk awareness and self-protection capabilities [1] Group 2 - Dr. Cheng Jun from Hai Fu Tong Fund Management highlighted the growing popularity of ETFs as transparent and flexible investment tools, emphasizing the importance of scientific strategies to enhance ETF investment outcomes [2] - Common ETF investment strategies include allocation strategies such as constant stock-bond ratio models and risk parity models, as well as trading strategies that focus on market sentiment and short-term volatility [2][3] - The dollar-cost averaging strategy is noted as a simple and widely used method, which helps investors average their investment costs and reduce the impact of market volatility [2][3] Group 3 - The dollar-cost averaging strategy involves investing a fixed amount at regular intervals, which can lead to significant excess returns compared to buy-and-hold strategies [3] - Dr. Cheng suggested that a good exit point for profits could be when the holding return reaches a target, such as 30%, allowing for a cycle of continued investment [3] - The ETF grid trading strategy is suitable for investors with limited time to monitor fund fluctuations, allowing automated buy and sell operations based on pre-set parameters [3][4] Group 4 - The ETF arbitrage strategy capitalizes on price differences between the primary and secondary markets, leveraging the unique dual trading mechanism of ETFs [4] - In April, the total scale of the ETF market in China surpassed 4 trillion yuan, indicating a growing recognition of index investment tools among investors [4] - Factors such as favorable policies, reduced ETF fees, and increased institutional investment have contributed to the rising popularity of ETFs, which offer low costs, risk diversification, transparency, and trading flexibility [4]