1. Report Industry Investment Rating No relevant information provided in the report. 2. Core View of the Report - OpenClaw demonstrates comprehensive task execution ability in constructing ETF fixed - investment strategies, including full - process execution from data extraction to strategy construction, code writing, and timed prompts, as well as good thinking ability in constructing fixed - investment strategies and risk indicators [3][57]. - Although OpenClaw has some minor issues such as low - level errors and data hallucinations, it can gradually meet user needs as it learns about the stock market, quantitative research logic, and investor habits. Some low - level errors can be corrected through skill solidification or dialog box instructions, while others require framework upgrades [57][58]. - After considering idle capital costs, the RSI oversold strategy outperforms the 60 - day moving average strategy in terms of annualized return, and the RSI fixed - investment strategy shows relatively better overall performance among the six strategies [40][43]. 3. Summary by Directory 3.1 OpenClaw's Typical Use Scenarios: Strategy Construction and Signal Prompting - OpenClaw can autonomously deploy the quantitative environment, extract data, and calculate quantitative strategies. It can also perform market tracking, execute timed tasks, and complete a series of process - based actions, which differentiates it from other platforms. The report attempts to use OpenClaw to construct a fixed - investment strategy and a signal timed prompt system based on the Cathay CSI A500 ETF (159338) [5]. 3.2 Using OpenClaw for Fixed - Investment Strategy Construction 3.2.1 Preparation: Data Extraction - Read relatively complete index data and save it locally. Connecting OpenClaw to the API interface of the data source makes the overall process smoother, eliminating the need for manual pre - processing of data [6][9]. 3.2.2 Initial Fixed - Investment Calculation: Guidance and Correction - Guide OpenClaw to perform initial fixed - investment calculations through the dialogue window, comparing the performance of simple one - time investment, ordinary monthly investment, and basic intelligent fixed - investment. After guiding OpenClaw to use the internal rate of return (IRR) as the core income assessment indicator, it can focus on using IRR for comparison in subsequent calculations. However, OpenClaw requires a long - time and high - degree of manual guidance due to inaccurate understanding of fixed - investment content and the exacerbation of hallucination phenomena after the DeepSeek large model is connected [10][13][15]. 3.2.3 Design and Income Comparison of Intelligent Fixed - Investment Strategies - Without providing clear strategy construction prompts, OpenClaw successfully constructs 6 types of complex intelligent fixed - investment strategies, using diverse technical indicators such as multiple moving averages and RSI. It also incorporates multi - level加仓 mechanisms, enhancing the flexibility and market adaptability of the strategies. After calculating the IRR of these strategies, the 60 - day moving average strategy performs well in terms of win - rate and income [19][20][30]. 3.2.4 Further Comparison of Fixed - Investment Strategies - Request OpenClaw to design exclusive risk indicators for fixed - investment strategies. By comparing the risk control and drawdown of each strategy, the 60 - day moving average strategy shows better comprehensive performance. After considering idle capital costs, the RSI oversold strategy becomes the one with the highest annualized return. Finally, parameter sensitivity tests are conducted on each strategy, and the RSI fixed - investment strategy shows relatively better overall performance [33][36][43]. 3.3 Construction of a Signal Prompt System Based on the Cathay CSI A500 ETF (159338) 3.3.1 Basic Information of the Cathay CSI A500 ETF - Ask OpenClaw to display the investment - related basic information of the Cathay CSI A500 ETF, including code, establishment date, fund manager, scale, tracking error, etc., providing comprehensive reference for investors [45]. 3.3.2 OpenClaw's Daily Tracking and Signal Prompting - Request OpenClaw to establish a timed task to track the performance of 6 types of fixed - investment strategies on the Cathay CSI A500 ETF daily and provide signals. OpenClaw successfully completes the establishment of this timed task, and an example of the monitoring and push results on March 17, 2026, shows that 4 out of 6 strategies issue buy signals [51][55][56]. 3.4 Thoughts and Summary - OpenClaw shows comprehensive task execution ability but has problems such as lack of basic market knowledge and model hallucinations, which affect the initial user experience. Some issues can be solved through learning and framework upgrades, and it is expected to significantly improve the efficiency of investment research in the future [57][58].