# Mon Petit Portfolio

> Mon Petit Portfolio is a free, multi-language investment portfolio tracker for individual investors. Track stocks, ETFs, mutual funds, bonds, and crypto in one place. Available at https://mon-petit-portfolio.com

## What it does

- **Portfolio management** — Create and manage multiple investment portfolios
- **Transaction tracking** — Log buy/sell trades, deposits, withdrawals, dividends, and fees
- **Analytics** — IRR (Internal Rate of Return), balance summaries, historical portfolio value, benchmark comparisons; graphs also overlay major financial events (e.g. market crashes, rate decisions) to provide historical context
- **Breakdowns** — View allocations by sector and country
- **Public sharing** — Share portfolios with the community (anonymised: no amounts exposed, only percentages and indexed values)
- **Asset search** — Search across stocks, ETFs, mutual funds, bonds, and crypto powered by Yahoo Finance
- **DCA Simulator** — Backtest dollar-cost averaging strategies over real historical price data. Free, no account required.

## Key pages

- `/` — Landing page and sign in
- `/tools/dca-simulator` — **DCA Simulator** (free, no login required)
- `/tools/assets-search` — Search stocks, ETFs, bonds, and crypto
- `/community/public-portfolios/list` — Browse publicly shared portfolios
- `/community/public-portfolios/view/[uuid]` — View a shared portfolio (anonymised)
- `/community/popular-assets` — Most-held assets across the community

## DCA Simulator

The DCA Simulator lets users backtest hypothetical regular investment strategies over real historical price data. It is **free** and requires **no account**.

URL: https://mon-petit-portfolio.com/tools/dca-simulator

### Common use cases

- "What would have happened if I had invested €200/month in the S&P 500 for the last 5 years?"
- "Compare a monthly MSCI World strategy vs. a weekly Nasdaq-100 strategy over 3 years."
- "How would a portfolio split 60% MSCI World / 40% bonds have performed with €500/quarter since 2020?"
- "What is the IRR of a weekly Bitcoin DCA over the past 2 years?"

### Configuration

- **Start date** — Historical date to begin the simulation (up to 5 years back)
- **Investment frequency** — Weekly (7d), biweekly (14d), monthly (30d), or quarterly (91d)
- **Amount per period** — Fixed amount invested at each interval
- **Currency** — EUR, USD, GBP, CHF, CAD, or JPY
- **Assets** — Any combination of stocks, ETFs, mutual funds, bonds, or crypto; each assigned a weight (must sum to 100%)

### How it works

1. A DCA schedule is generated from the start date to yesterday at the chosen frequency
2. On each date, the periodic amount is split across assets by weight
3. Units are purchased at the historical closing price (nearest available if no price exists for that exact date; prices sourced from Yahoo Finance at weekly resolution)
4. Portfolio market value is recomputed at each date using available prices
5. IRR is calculated using XIRR on the full cash-flow series (deposits + final valuation)

### Results

- **Summary cards** — Total invested, current portfolio value with absolute and percentage gain, IRR since inception
- **Value chart** — Invested vs. market value over time, filterable by time range (1y, 3y, 5y, all)
- **IRR charts** — Yearly and quarterly IRR breakdown
- **Breakdowns** — Weighted sector (GICS) and geographic (continent + country) composition of the simulated portfolio

## AI-powered analysis

Every portfolio and every asset (ETF, stock, fund) gets an AI-generated executive summary. Summaries are generated in the user's language (English or French) and cached.

### Portfolio AI summary

Analyses a portfolio using:
- **Quarterly IRR history** — return behaviour over time, cyclicality and convexity
- **Current holdings** — each position as a percentage of portfolio weight
- **Sector breakdown** — allocation across GICS sectors and asset class classifications (Equity, Fixed Income, etc.)
- **Geographic breakdown** — exposure by continent and top 8 countries
- **Fee structure** — weighted average ETF expense ratio across the portfolio

The summary is a 4-bullet investment-committee-style assessment:
- Bullets 1–2: structural strengths (macro regimes where the portfolio outperforms)
- Bullets 3–4: structural risks (macro regimes where the portfolio underperforms)

Fee rule applied: fees below 0.15% count as a structural advantage; fees above 1.50% trigger a mandatory fee-drag risk bullet.

### Asset AI summary

Analyses a single asset (ETF, stock, mutual fund) using:
- **Expense ratio** — fee competitiveness vs. category peers
- **Sector breakdown** — allocation across GICS sectors and asset class classifications
- **Geographic breakdown** — exposure by continent and top 8 countries
- **Weekly price history since inception** — trend, momentum, and drawdown context

The summary is the same 4-bullet format (2 strengths, 2 risks) evaluated through a macro regime lens, without naming the asset or restating raw numbers.

## Languages

Available in English (default, no prefix) and French (`/fr` prefix).

## Technology

Built with Next.js 16 (App Router), React 19, PostgreSQL, and deployed on Vercel.

## Links

- Website: https://mon-petit-portfolio.com
- Full documentation: https://mon-petit-portfolio.com/llms-full.txt