daily-stock-analysis

# Daily Stock Analysis Perform market-aware, evidence-based daily stock analysis with prediction, next-run review, rolling accuracy tracking, and a structured self-evolution mechanism that updates future assumptions from observed forecast errors. ## Hard Rules 1. Read and write files only under `working_directory`. 2. Save new reports only to: - `<working_directory>/daily-stock-analysis/reports/` 3. Use filename: - `YYYY-MM-DD-<TICKER>-analysis.md` 4. If same ticker/day file exists, ask user: - `overwrite` or `new_version` (`-v2`, `-v3`, ...) - For unattended runs, default to `new_version` 5. Always review history before new prediction. 6. Limit history read count to control token usage: - Script mode: max 5 files (default) - Compatibility mode: max 3 files ## Required Scripts (Use First) 1. Plan output path + collect history: ```bash python3 {baseDir}/scripts/report_manager.py plan \ --workdir <working_directory> \ --ticker <TICKER> \ --run-date <YYYY-MM-DD> \ --versioning auto \ --history-limit 5 ``` 2. Compute rolling accuracy from existing reports: ```bash python3 {baseDir}/scripts/calc_accuracy.py \ --workdir <working_directory> \ --ticker <TICKER> \ --windows 1,3,7,30 \ --history-limit 60 ``` 3. Optional: migrate legacy files after explicit user confirmation: ```bash python3 {baseDir}/scripts/report_manager.py migrate \ --workdir <working_directory> \ --file <ABS_PATH_1> --file <ABS_PATH_2> ``` ## Compatibility Mode (No Python / Small Model) If Python scripts are unavailable or model capability is limited, switch to minimal mode: 1. Read at most 3 recent reports for the same ticker. 2. Use only a minimal source set: - one official disclosure source - one reliable market data source (Yahoo Finance acceptable) 3. Output concise result only: - recommendation - `pred_close_t1` - prior review (`prev_pred_close_t1`, `prev_actual_close_t1`, `AE`, `APE`) if available - one `improvement_action` 4. Save report with same filename rules in canonical reports directory. See `references/minimal_mode.md`. ## Minimal Run Protocol 1. Resolve ticker/exchange/market (ask if ambiguous). 2. Run `report_manager.py plan`. 3. Read `history_files` returned by script. 4. If `legacy_files` exist, list all absolute paths and ask whether to migrate. 5. Gather data using `references/sources.md` + `references/search_queries.md`. 6. Run `calc_accuracy.py` for consistent metrics. 7. Render report using `references/report_template.md`. 8. Save to `selected_output_file` returned by `report_manager.py`. ## Required Output Fields Must include: - `recommendation` - `pred_close_t1` - `prev_pred_close_t1` - `prev_actual_close_t1` - `AE`, `APE` - rolling strict/loose accuracy fields - `improvement_actions` ## Self-Improvement (Required) Each run must include 1-3 concrete `improvement_actions` from recent misses and use them in the next run. Do not skip this step. ## Scheduling Recommendation Recommend users set this as a weekday recurring task (for example 10:00 local time) to keep prediction-review windows continuous. ## References Default: - `references/workflow.md` - `references/report_template.md` - `references/metrics.md` - `references/search_queries.md` - `references/sources.md` - `references/minimal_mode.md` - `references/security.md` Deep-dive only (`full_report` mode): - `references/fundamental-analysis.md` - `references/technical-analysis.md` - `references/financial-metrics.md` ## Compliance Always append: "This content is for research and informational purposes only and does not constitute investment advice or a return guarantee. Markets are risky; invest with caution."