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[04] The 90/10 Portfolio — Dividend Core + Growth Satellite with a Live Simulator

#python #finance #fire #javascript

[04] The 90/10 Portfolio — Dividend Core + Growth Satellite with a Live Simulator

This is Part 4 of a 6-part series: Building Investment Systems with Python

Two Engines, One Portfolio

In the manifesto, I described a 90/10 portfolio philosophy: 90% in dividend-growing core positions, 10% in a deep-value satellite aiming for 3-5x.

Today we build both sides — the dividend snowball model for the core, and a live interactive simulator for the satellite. The simulator is a tool I actually use. You can plug in your own assumptions and watch the numbers move in real time.

The Core: Dividend Snowball (90%)

The core holds companies with DOE (Dividend on Equity) or progressive dividend policies. DOE means dividends grow automatically as book value grows — programmatic, not discretionary.

# dividend_model.py
from dataclasses import dataclass

@dataclass
class DividendStock:
    ticker: str
    shares: int
    annual_dividend: float   # per-share
    growth_rate: float       # annual dividend growth

    def projected_income(self, year: int) -> float:
        return self.annual_dividend * (1 + self.growth_rate) ** year * self.shares

CORE = [
    DividendStock("A", 15000,  78, 0.05),  # Retail — progressive
    DividendStock("B", 50000,  24, 0.05),  # Auto dealer — progressive
    DividendStock("C", 20000,  60, 0.06),  # Education — DOE 6%
    DividendStock("D", 50000,  21, 0.06),  # Advertising — DOE 6%
]

for y in range(11):
    income = sum(s.projected_income(y) for s in CORE)
    fire = "🔥" if income > 9_600_000 else ""
    print(f"  {2026+y}  ¥{income:>10,.0f}/yr  {fire}")
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  2026  ¥ 5,220,000/yr
  2027  ¥ 5,525,200/yr
  2028  ¥ 5,848,712/yr
  ...
  2032  ¥ 7,637,548/yr
  2034  ¥ 8,571,892/yr
  2036  ¥ 9,620,423/yr  🔥
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The snowball alone reaches FIRE around year 10. Slow, but reliable. That's the point — the core doesn't need to be exciting.

The Satellite: Deep Value with PSR (10%)

The remaining 10% is a single deep-value position — a stock at PSR 0.11 with a restructuring catalyst.

Kenneth Fisher's framework: PSR below 0.75 = buy. PSR below 0.3 = exceptional. A company at PSR 0.11 is either going bankrupt or going 3-5x. That asymmetry is what we're buying.

CORE (90%)                    SATELLITE (10%)
├─ Generates yield            ├─ Generates capital gains
├─ Grows 5-6%/year            ├─ Binary: 3-5x or flat
├─ Covers living expenses     ├─ Accelerates FIRE timeline
├─ Shields against downside   ├─ Bounded loss (14% of portfolio)
└─ The snowball               └─ The slingshot
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Live Simulator: Satellite Position Analysis

Below is the actual tool I use to evaluate this position. It's a single HTML file — no server, no dependencies. Drag the sliders to model different scenarios.

It calculates target price from EPS × PER, Fisher PSR at current and target valuations, and the impact on the total portfolio.

This is built with real portfolio data. The four core holdings are fixed at current prices. Only the satellite moves.

The Asymmetric Payoff

This is why the 90/10 structure works:

Scenario Portfolio Impact FIRE Timeline
Satellite → 0 -14% (¥124M → ¥107M) Delayed ~1 year
Satellite → 3x +28% (¥124M → ¥159M) Accelerated ~2 years
Satellite → 5x +56% (¥124M → ¥194M) Essentially immediate

The core absorbs the downside. The satellite amplifies the upside. You don't need the satellite to reach FIRE — the snowball gets you there eventually. But if the turnaround thesis plays out, it compresses years of compounding into a single event.

Bounded loss. Unbounded gain. That's the whole strategy in one line.

What We Built

  • A dividend snowball model for the 90% core (DOE + progressive growth)
  • A live interactive PSR simulator for the 10% satellite — the actual tool I use
  • Portfolio impact analysis showing how core and satellite interact
  • The asymmetric risk framework: 14% max loss, 56%+ potential gain

Next week: [05] When to Pull the Trigger on FIRE — "FIRE isn't a number. It's a probability."

Series: Building Investment Systems with Python — Engineering financial independence with code.

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