The Tale of Two Risky Friends: A Portfolio Balancing Act (2 risky assets)

In the heart of Mumbai’s financial district, young portfolio manager Rohan stared at his two biggest investment choices—TechStorm Inc., a booming AI company, and GoldSafe Ltd., a well-established gold mining firm.

Both companies had the potential to make serious money. But both were risky. One depended on market trends, the other on gold prices. Rohan’s job? To combine them wisely in a portfolio that could generate maximum returns while keeping risk under control.

That’s when his mentor, Mr. Iyer, walked in. “Let me tell you something, Rohan. A smart investor doesn’t just pick stocks—they balance risk. Now, let’s build the perfect portfolio.”

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Act 1: Two Wild Horses – Understanding the Risk

Mr. Iyer placed two sheets of paper in front of Rohan.

1️⃣ TechStorm Inc. 🏢

• Expected Return: 12% per year
• Standard Deviation (Risk): 25%
• Volatile, high-risk, high-growth

2️⃣ GoldSafe Ltd. ⛏️

• Expected Return: 8% per year
• Standard Deviation (Risk): 18%
• Less volatile, but still risky

Rohan scratched his head. “Both are risky. If I put money into both, won’t I just double the risk?”

Mr. Iyer smirked. “That’s where correlation comes in.”

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Act 2: The Magic of Diversification – How Risks Offset Each Other

“Tell me, Rohan,” Mr. Iyer asked, “What happens when the stock market crashes?”

“Well… tech companies suffer,” Rohan replied.

“And what happens to gold?”

Rohan’s eyes widened. “Gold usually goes up when stocks crash!”

Mr. Iyer nodded. “Exactly! The correlation between TechStorm and GoldSafe is negative. When one struggles, the other thrives. That’s how we reduce overall portfolio risk.”

The formula for a two-asset portfolio’s risk is:

$$\sigma_P = \sqrt{w_1^2 \sigma_1^2 + w_2^2 \sigma_2^2 + 2w_1 w_2 \rho \sigma_1 \sigma_2}$$

Where:

• $w_1, w_2$ = Weights of the two assets
• $\sigma_1, \sigma_2$ = Standard deviations of each asset
• $\rho$ = Correlation coefficient between the two assets

If $\rho$ is negative (as with gold and tech stocks), portfolio risk decreases significantly!

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Act 3: Finding the Perfect Mix – The Efficient Frontier

Rohan began experimenting with different portfolio allocations.

💡 Scenario 1: 50% in TechStorm, 50% in GoldSafe

• Expected Return: 10%
• Standard Deviation: 17%

💡 Scenario 2: 70% TechStorm, 30% GoldSafe

• Expected Return: 10.8%
• Standard Deviation: 20%

💡 Scenario 3: 30% TechStorm, 70% GoldSafe

• Expected Return: 9.2%
• Standard Deviation: 15%

By adjusting the weights, Rohan realized he could maximize returns while minimizing risk.

Mr. Iyer pointed at a graph on his screen—the Efficient Frontier. It showed the best combinations of risky assets that provided the highest return for a given risk level.

“The goal, Rohan, is to get as close as possible to this curve. That’s how professional investors win.”

*Here is the graph illustrating the efficient frontier for a portfolio consisting of two risky assets—TechStorm Inc. and GoldSafe Ltd. It shows different portfolio combinations, highlighting an optimal portfolio mix.

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Act 4: The Final Decision – A Smart Portfolio Strategy

Rohan finalized his portfolio:
✔ 60% in TechStorm for strong growth potential
✔ 40% in GoldSafe for stability in downturns

This gave him:
✅ Expected Return: 10.5%
✅ Risk (Standard Deviation): 16% (lower than both individual stocks!)

By combining two risky assets strategically, he created a balanced, efficient portfolio—one that could weather market storms while still delivering strong returns.

Mr. Iyer patted his back. “Congratulations, Rohan. You’ve just mastered the art of diversification.”

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Key Takeaways from Rohan’s Journey:

✔ Risky assets don’t always increase total risk—if they are negatively correlated, they can balance each other out.
✔ The right mix of assets can lower portfolio volatility while maintaining high returns.
✔ The Efficient Frontier helps investors find the best risk-return combination.
✔ Diversification is the key to long-term investing success.

[Finance]