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Examples

Examples are ordered from simplest to most research-specific. Start with package examples before running paper-specific agents.

Custom Dataset

Run:

python examples/custom_dataset_example.py

This example creates an in-memory FinsaberDataset, runs BuyAndHoldStrategy, and prints total return.

Use it to learn the required dictionary shape before writing a custom loader.

Research Experiment Launchers

These scripts are repository examples and are not included in the package wheel.

python examples/experiments/run_baselines_exp.py --setup selected_4 --include BuyAndHoldStrategy

python examples/experiments/run_llm_traders_exp.py \
  --setup selected_4 \
  --strategy FinMemStrategy \
  --strat_config_path strats_configs/finmem_config_normal.json

Minimal Package Usage

from finsaber import FINSABERBt, FinsaberParquetDataset
from finsaber.strategy.timing import BuyAndHoldStrategy

data = FinsaberParquetDataset("path/to/sp500_2000_2025_parquet")
config = {
    "data_loader": data,
    "tickers": ["AAPL"],
    "date_from": "2024-01-02",
    "date_to": "2024-01-10",
    "setup_name": "minimal",
    "save_results": False,
    "silence": True,
}
results = FINSABERBt(config).run_iterative_tickers(BuyAndHoldStrategy)
  1. Run the minimal package usage example with one ticker.
  2. Enable save_results=True and inspect run_summary.csv.
  3. Add slippage_perc and liquidity_cap_pct.
  4. Replace BuyAndHoldStrategy with a simple moving-average strategy.
  5. Replace FinsaberParquetDataset with your own TradingData implementation.
  6. Only then run LLM or RL research launchers.