Investor Allocates $75,000 Across 3 Startups: 8x Return on A, 3x on B, Loss on C After 40%, 35%, and 25% Weighting

A savvy investor recently diversified $75,000 across three promising startups, allocating funds strategically based on risk tolerance and expected returns. With 40% invested in Startup A, 35% in Startup B, and the remaining 25% in Startup C, this portfolio illustrates how geographic and stage diversification can shape investment outcomes — especially when one venture fails.

Allocation Breakdown:

  • Startup A: 40% of $75,000 = $30,000
  • Startup B: 35% of $75,000 = $26,250
  • Startup C: 25% of $75,000 = $18,750

Understanding the Context

Startup A delivers exceptional returns with an 8× multiple, meaning the $30,000 investment grows to $240,000. Startup B returns 3×, turning $26,250 into $78,750. However, Startup C fails entirely, returning $0.

Total Return Calculation:

  • From Startup A: $240,000
  • From Startup B: $78,750
  • From Startup C: $0
    Total Return = $240,000 + $78,750 + $0 = $318,750

Despite the $18,750 loss from Startup C, the investor still achieves a remarkable $318,750 total return on her original $75,000 investment — highlighting the powerful impact of high-growth startups in a diversified portfolio.

This case underscores the importance of balancing risk: while not all investments succeed, strong performers like Startup A and B can significantly amplify returns, offsetting losses in high-risk bets. For investors, thoughtful capital allocation across startups with varying risk profiles remains key to maximizing long-term growth.

An investor allocates $75,000 across 3 startups. She puts 40% in Startup A, 35% in B, and the rest in C. If Startup C fails, and A returns 8× and B returns 3×, what is her total return?

Key Insights

Return multiple calculations based on initial allocations:

  • A: $30,000 × 8 = $240,000
  • B: $26,250 × 3 = $78,750
  • C: $18,750 × 0 = $0
    Total: $240,000 + $78,750 = $318,750

#StartupInvestment #StartupReturns #DiversifiedPortfolio #HighRiskHighReward #FinancialStrategy #AngelInvesting

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But assuming the function is correct as stated, and the goal is to minimize \( P(x) = \frac{5000}{x} + 120 - 0.5x \), set:
P'(x) = -\frac{5000}{x^2} - 0.5 = 0 \quad \text{has no solution}
So no minimum — but this contradicts realistic models.

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