Computation Methodology

Ona Planner takes a goal amount (e.g. retirement fund, house deposit, education fund), a time horizon, and a risk profile, then works backwards to determine how much you need to save each month to have a high probability of reaching that goal.

The computation has three stages:

1. Adjust the goal for inflation so it reflects future purchasing power.
2. Solve for the fixed monthly deposit (PMT) that grows to the inflation-adjusted goal under expected returns.
3. Stress-test that plan under 1,000 randomised return paths (Monte Carlo) to estimate how often it succeeds.

Your goal amount is stated in today's money. We project it forward to its future nominal value using compound inflation, so your target preserves real purchasing power:

Future Value = Goal × (1 + i)ⁿ

  i  =  annual inflation rate (country-specific, see table below)
  n  =  time horizon in years

Country defaults (can be overridden in the form):

We solve for the fixed periodic payment that accumulates to the inflation-adjusted goal, accounting for savings you already have. This is a standard time-value-of-money formula:

PMT = (FV − PV × (1+r)ⁿ) × r
         ─────────────────────────────
                 (1+r)ⁿ − 1

  FV  =  inflation-adjusted goal value
  PV  =  existing savings (invested at month 0)
  r   =  blended monthly return
  n   =  time horizon in months

Existing savings are treated as a lump sum already invested at month 0, compounding at the same expected rate as new contributions. This directly reduces the required monthly deposit.

The PMT formula assumes constant returns. Real markets are volatile. Monte Carlo simulation adds realism by running 1,000 independent scenarios, each with randomly sampled monthly returns.

Monthly returns are drawn from a normal distribution:

r_month  ~  Normal(μ_monthly, σ_monthly)

  μ_monthly  =  (1 + annual_mean)^(1/12) − 1
  σ_monthly  =  annual_std / √12

Each month's portfolio balance is updated as:

Portfolio(t+1) = Portfolio(t) × (1 + r_month) + PMT

After all 1,000 paths complete, we extract three percentile bands at every point in time:

Returns are calibrated to 10-year historical averages (2014–2024) for each country and asset class. These are educational approximations, not forward forecasts.

Nigerian bonds show a higher expected return than equities net of volatility due to elevated sovereign yields in the local fixed-income market, not a global anomaly.

When asset type is set to mixed, the blended return is a weighted average of the equity and bond parameters for your country:

blended_mean  =  w_eq × mean_eq  +  w_bond × mean_bond
blended_std   =  w_eq × std_eq   +  w_bond × std_bond

If you choose equities only or bonds only, the risk profile is ignored and only that asset class's parameters are used.

Probability of success is the fraction of the 1,000 paths where the portfolio value at the goal date meets or exceeds the inflation-adjusted target:

P(success) = paths where Portfolio_final ≥ FV
             ─────────────────────────────────────────
                              1,000

For UK, US, and EU users saving toward a property purchase, Ona Planner includes a deposit calculator:

1. Enter the full property price.
2. Select your target deposit percentage (5–25%).
3. Ona Planner sets goal_value = house_price × deposit_pct automatically.

The simulation then runs identically — your deposit target is the financial goal.

Ona Planner is an educational planning tool only. It is not a financial product, investment adviser, or regulated service in any jurisdiction.

• Past performance of markets is not indicative of future results.
• Return assumptions are historical averages; actual future returns may differ significantly.
• Inflation defaults are indicative; your local experience may vary.
• The model does not account for taxes, platform fees, currency risk, or withdrawal strategies.
• Normal distribution assumptions underestimate the probability of extreme market events (fat tails).
• For large financial decisions, consult a regulated financial adviser in your jurisdiction.