.. _end_user_manual: End User Manual =============== Detailed instructions for configuring and operating every component of the Backtest Engine. Use this section as your in-depth reference once you have completed the :ref:`quick_start` and need to lock in the specifics of your data, your parameters and your execution workflow. If you are looking for ready-made recipes (commission sweeps, rolling windows) skip ahead to :ref:`use_cases`. Otherwise, work through this manual in order: start with **Data Formats** to understand what the engine expects, then with **Configuration Reference** to map your data to the engine's vocabulary, then choose one of the two execution workflows below. Choose your workflow -------------------- The engine supports two execution paths. Pick the one that matches how your team operates today; you can always switch later because both consume the same data and produce the same reports. .. list-table:: :widths: 25 75 :header-rows: 1 * - Workflow - Best fit when… * - :ref:`excel_workflow` - Parameters are tuned by analysts who edit ``Config/backtest_engine_parameters.xlsx`` directly. No Python needed; the run is launched from a terminal with ``python -m kaxanuk.backtest_engine autorun``. Output is a single Excel workbook per run. * - :ref:`programmatic_usage` - You need to script variations, sweep parameters, run batches of portfolios, or integrate the engine into a larger Python pipeline (CI, Jupyter notebooks, dashboards). The Excel template still works but is bypassed in favour of ``Configuration.with_overrides`` and ``BatchConfigParser``. What you'll find here: - :ref:`data_formats` — market data and portfolio file specifications. - :ref:`configuration` — full reference for every configuration parameter. - :ref:`excel_workflow` — step-by-step guide for the Excel-based workflow. - :ref:`programmatic_usage` — running backtests from Python. .. toctree:: :maxdepth: 1 :hidden: data_formats configuration excel_workflow running_from_python