Drawdowns & Volatility

The AI Infrastructure Portfolio has experienced strong performance overall, but as a high-growth, semiconductor-heavy collection of stocks, it naturally carries elevated volatility and periodic drawdowns. This is not a managed fund but a thematic thesis example, illustrating both the potential rewards and risks of concentrated exposure to the AI infrastructure trend.

Volatility Profile:
The portfolio’s composition leans toward high-beta technology leaders such as NVIDIA, Micron, and TSMC, resulting in greater price swings than the broader market. Over the past year, short-term fluctuations have often exceeded 2–3% daily moves during earnings announcements or AI sector rotations.

Drawdown Behavior:
The largest drawdowns have historically occurred during broad tech sell-offs, particularly when interest rates rise or when investors rotate out of growth sectors. Despite these pullbacks, the portfolio’s strong long-term trajectory has offset most interim declines. Over the last year, peak-to-trough drawdowns ranged between 15–25%, compared to about 10–12% for the S&P 500.

Key Risk Factors:

• Cyclicality in semiconductors can amplify volatility during inventory corrections.
• AI spending slowdowns or delays in GPU supply can trigger sharp but temporary price drops.
• Geopolitical exposure, especially for TSMC and ASML, adds structural risk.
• Valuation sensitivity: high earnings multiples make the portfolio more reactive to macro headlines.

In essence, while the portfolio has delivered exceptional returns, it also exemplifies the tradeoff between high potential reward and higher volatility. Investors using this as a thesis example should view it as a long-horizon, high-conviction idea rather than a short-term or defensive allocation.