Calculateur DCA

from dataclasses import dataclass
from typing import List

@dataclass
class DCAResult:
    period: int
    contribution: float
    balance: float
    total_invested: float
    gain_loss: float
    gain_loss_pct: float

def dca_simulator(
    initial: float,
    periodic: float,
    annual_return: float,
    years: float,
    frequency: int = 12  # per year
) -> List[DCAResult]:
    """
    Simulate dollar-cost averaging investment.

    Parameters:
        initial       - lump-sum initial investment
        periodic      - periodic contribution amount
        annual_return - expected annual return rate (e.g. 0.07 for 7%)
        years         - investment duration in years
        frequency     - contributions per year (12=monthly, 52=weekly)
    """
    periodic_rate = annual_return / frequency
    periods = int(years * frequency)
    balance = initial
    total_invested = initial
    results = []

    for t in range(1, periods + 1):
        balance = balance * (1 + periodic_rate) + periodic
        total_invested += periodic
        gain = balance - total_invested
        results.append(DCAResult(
            period=t,
            contribution=periodic,
            balance=balance,
            total_invested=total_invested,
            gain_loss=gain,
            gain_loss_pct=gain / total_invested * 100
        ))

    return results

# Example: $5,000 initial + $500/month at 7% for 30 years
results = dca_simulator(5000, 500, 0.07, 30, 12)
final = results[-1]

print(f"Final balance:    ${final.balance:>12,.2f}")
print(f"Total invested:   ${final.total_invested:>12,.2f}")
print(f"Total gain:       ${final.gain_loss:>12,.2f}")
print(f"Return on invest: {final.gain_loss_pct:>10.1f}%")

# Yearly summary
print("\nYear | Balance     | Invested    | Gain/Loss")
for i in range(11, len(results) + 1, 12):
    r = results[i - 1]
    yr = i // 12
    print(f"{yr:4d} | ${r.balance:>10,.2f} | ${r.total_invested:>10,.2f} | ${r.gain_loss:>10,.2f}")