/vectorbt-expert

Position Sizing

Size Types

Default: size=np.inf with Amount = invest all available cash.

Percent Sizing (Most Popular)

pf = vbt.Portfolio.from_signals(
    close, entries, exits,
    size=0.5,              # 50% of portfolio equity per trade
    size_type="percent",
    init_cash=1_000_000,
    fees=0.00111, fixed_fees=20,
    min_size=1,
    size_granularity=1,
    freq="1D"
)

Value Sizing (Fixed Capital Per Trade)

pf = vbt.Portfolio.from_signals(
    close, entries, exits,
    size=200_000,          # Deploy 2L per trade
    size_type="value",
    init_cash=1_000_000,
    fees=0.00111, fixed_fees=20,
    min_size=1,
    size_granularity=1,
    freq="1D"
)

Target Percent (Portfolio Rebalancing)

pf = vbt.Portfolio.from_orders(
    close=close_panel,          # DataFrame with multiple asset columns
    size=target_weights,        # DataFrame of target weights (0.0-1.0)
    size_type="targetpercent",
    group_by=True,
    cash_sharing=True,
    fees=0.00111, fixed_fees=20,
    init_cash=1_000_000,
    freq="1D",
)

Whole Shares Only (Realistic)

Always use min_size=1 and size_granularity=1 for equity backtesting to avoid fractional shares:

pf = vbt.Portfolio.from_signals(
    close, entries, exits,
    size=0.75,
    size_type="percent",
    min_size=1,             # Minimum 1 share
    size_granularity=1,     # Round to whole shares
    init_cash=1_000_000,
    freq="1D",
)

Best Practices

• Equity intraday/swing: Use percent with 0.5-0.75 (50-75% deployment)
• Futures: Use value with lot-aware min_size and size_granularity (see futures-backtesting)
• Multi-asset portfolio: Use targetpercent with cash_sharing=True
• Accumulation/pyramiding: Use accumulate=True with smaller percent per entry
• Always set min_size=1 and size_granularity=1 for realistic equity simulation