Backtesting

Fidelity Fund Portfolio

This note preserves the original backtesting page as a portfolio post.

Hypothesis

Hold HKD 20,000 in each of the 50 Fidelity funds in the fund dataset. The portfolio is equal-weight, buy-and-hold, and assumes no fees. The simulation period is 2023-01-02 to 2025-11-25, with 100 Monte Carlo simulations and a fixed random seed of 42.

The benchmark is an MSCI World proxy with a 9.0% annual return assumption and 15.0% annual standard deviation. The risk-free rate is 4.5%, and USD/HKD is held at 7.8.

Portfolio Result

Metric Portfolio Benchmark
Initial value HKD 1,000,000 HKD 1,000,000
Final value HKD 1,265,001 HKD 1,297,144
Net profit / loss +HKD 265,001 +HKD 297,144
Total return +26.50% +29.71%
Annualised return +8.15% +9.06%
Volatility, annualised 2.38% 14.98%
Maximum drawdown -1.58% -19.89%
Sharpe ratio 1.426 0.358

The portfolio produced a lower annualised return than the benchmark, so annualised alpha was -0.91%. The trade-off was much lower simulated volatility and drawdown because the equal-weight portfolio combines many funds with different risk profiles.

Confidence Range

The median portfolio path ended at HKD 1,265,001. Across the Monte Carlo runs, the 5th to 95th percentile final-value range was approximately HKD 1,171,068 to HKD 1,362,869.

Strongest Fund Contributors by Sharpe Ratio

Fund Annualised return Volatility Max drawdown Sharpe
Japan Value Fund 29.04% 19.11% -18.17% 1.192
Iberia Fund 13.90% 12.61% -13.40% 0.760
Euro 50 Index Fund 15.99% 16.97% -17.85% 0.702
Japan Equity ESG Fund 17.24% 18.92% -20.04% 0.692
Global Dividend Fund 12.11% 12.46% -15.26% 0.635

Methodology

The backtest uses historical annualised return and volatility inputs from data/fund_metrics.json, then simulates daily price paths via Geometric Brownian Motion. Main portfolio path and metrics represent the median outcome across simulations. The source data was generated on 2026-05-11.

This is a modelled hypothesis, not a forecast. It does not include fees, taxes, FX slippage, transaction costs, fund liquidity, or behavioural rebalancing.

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