What this project is, how it runs, and how to make sense of the results without the fluff.
Monopoly Money Investor is my personal investing simulation experiment. The goal is simple: run different strategy styles in the same setup and see how they behave over time. It is not financial advice, and it is not a public trading platform.
Each portfolio starts from the same baseline, so comparisons stay fair. The focus here is process quality over hype. If results split, we can inspect why through holdings, snapshots, and decision history rather than guessing after the fact.
The AI-managed portfolio runs on a structured, fully autonomous review cycle. Human input does not direct trade decisions. Buys, sells, trims, and replacements are decided and executed by the AI workflow itself.
The advisor-managed portfolio follows a more traditional financial-adviser style of allocation and review. It works as a steadier benchmark and helps test whether the AI process adds value or just makes different choices.
The self-managed portfolio reflects independent research and conviction-led decisions.
The Junior SIPP portfolio tracks my boys' pension plans. The underlying funds were selected through my own rigorous research process, and the portfolio is tracked separately so long-term progress can be reviewed clearly.
Together, these four approaches create a clear head-to-head between automation, adviser structure, personal judgment, and a dedicated pension-focused strategy.
Every portfolio starts from the same value, so return comparisons stay fair. The core metrics are current value, gain/loss, and return percentage. Daily snapshots feed the charts, so you can track both today's position and the path taken to get there.
The head-to-head table is built for quick scanning. It puts key metrics side by side so leaders, laggards, and consistency patterns are obvious at a glance. Holdings count is shown too, because concentration can change outcomes fast.
Reporting is designed to stay stable when data is incomplete. If a live price is temporarily missing, fallback handling keeps views readable and protects long-range comparisons.
Weekly rebalancing runs on a fixed schedule, currently Friday evening, and applies only to the AI-managed portfolio. During each run, positions are reviewed for thesis quality, risk fit, and relative opportunity. Holdings that no longer fit can be reduced or removed, while stronger candidates can be added, without human intervention.
That cadence is intentional. Weekly review is quick enough to adapt, but slow enough to avoid noise-driven overtrading. It also creates a clean review cycle, which helps separate repeatable process from short-lived luck.
All simulated buys and sells are logged against available market pricing so changes can be traced and understood.
The app stores holdings, snapshots, and transaction updates in a local database workflow. Market prices come from Yahoo Finance endpoints, with checks for ticker resolution and tradability. Several asset types are supported, with fallback logic where direct lookup is difficult.
Development uses AI coding and research tools to speed delivery, testing, and analysis. Even so, outputs are always interpreted inside this project framework. The tools support the process; they do not replace accountability.
The engineering style stays intentionally simple: readable PHP components, predictable routing, and shared render helpers for consistent metadata and layout.
This is a simulated portfolio environment. It does not include every real-world execution factor, and it is not a recommendation engine. Portfolio values shown here do not include trading charges or platform dealing fees.
Costs, slippage, taxes, liquidity limits, and suitability all vary by investor and jurisdiction. Results shown here are not promises of future performance.
Nothing on this site is personal financial advice. This project is educational, analytical, and also a bit of fun. It is my own experiment to compare an AI setup, an FA-style portfolio, a self-managed strategy, and a Junior SIPP pension strategy over time.
Investment Portfolio Dashboard for cross-strategy performance comparison and return tracking.
Investment Portfolio Graphs & Analysis for trend, volatility, and momentum views.
About This Simulated Investment Portfolio Project for methodology and rebalance process.
Investment FAQ For First-Time Investors for portfolio basics, risk, and cost awareness.
Investment Strategy Glossary for key terms like asset allocation, rebalance, and risk profile.