fund-r9alpha-evaluation

To generate a standardized fund evaluation report, you can automate the aggregation of local holdings, risk metrics, and East Money data to populate a 10-dimension scoring framework. This process outputs both Excel evaluation drafts and structured Markdown deep analysis reports.

Comprehensive fund analysis requires calculating core risk and performance indicators directly from raw NAV data, including the Sharpe ratio, Sortino ratio, max drawdown, recovery days, and monthly win rate to fulfill due diligence requirements.

Yes, you can automatically pull missing data from public East Money fund pages. The workflow aggregates this public data with your local fund holdings and risk metrics to complete the evaluation framework.

You calculate the Sharpe ratio and max drawdown from raw NAV data by applying automated computational scripts to your dataset. This automated metric calculation removes manual errors and standardizes the risk assessment process.

Yes, this fund evaluation approach works with existing Excel templates by automatically populating them with calculated metrics and aggregated data. It uses openpyxl to format and fill your local R9Alpha-compliant evaluation drafts.

The best way to format a 10-dimension fund scoring framework is to automate the population of scoring metrics into predefined Excel templates and generate structured Markdown deep reports containing SWOT analysis and investment recommendations for clients.