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How I'm Getting My Fair Share Of This Bubble, While Managing Risk (NYSEARCA:SPY)

  //stocks-investing.news-articles.net/content/202 .. his-bubble-while-managing-risk-nysearca-spy.html
  Published in Stocks and Investing on Monday, October 20th 2025 at 21:05 GMT by Seeking Alpha

How I’m Getting My Fair Share of This Bubble While Managing Risk

In a recent article on Seeking Alpha, the author lays out a practical, disciplined framework for capitalizing on the current market surge—referred to colloquially as “the bubble”—while keeping downside exposure in check. The piece is a blend of market analysis, portfolio construction principles, and risk‑management tactics that can be applied by both seasoned investors and newcomers.

Defining the Bubble

The author begins by clarifying what he means by “bubble.” It’s not a single stock but an entire sector that has seen a rapid rise in valuation. He cites the explosive growth of AI, semiconductor, and cloud‑based businesses as the current example, noting that these companies have experienced double‑digit price increases over the past year with earnings still lagging behind market expectations. While the author acknowledges the possibility of a correction, he argues that the fundamentals—such as increasing demand for AI workloads, a global shortage of advanced chips, and the expansion of digital infrastructure—justify a continued upside if approached with caution.

He links to a CNBC feature that outlines the AI boom: [ AI‑driven growth and its risks ]. The article provides a deeper dive into how AI is reshaping industries and offers context for the author’s focus on this space.

Getting a Fair Share

The central thesis is that “fair share” is achieved by investing in high‑quality companies that drive the bubble, rather than chasing price pumps. The author emphasizes:

1. Fundamental Analysis – Concentrating on companies with solid balance sheets, high free‑cash‑flow margins, and a strong competitive moat.
2. Valuation Discipline – Using a multiples‑based approach (P/E, EV/EBITDA, and price‑to‑sales) adjusted for growth prospects.
3. Growth Potential – Targeting firms with a clear trajectory toward becoming industry leaders, such as those that can capture a sizable portion of the AI infrastructure market.

He cites several case studies, including NVIDIA (NVDA), Advanced Micro Devices (AMD), and Palantir Technologies (PLTR), illustrating how each company aligns with the criteria. For each, the article provides a concise snapshot of financials, recent news, and the author’s estimated upside range. The author links to a detailed analysis of NVIDIA’s recent quarterly report: [ NVDA Q2 2024 earnings ].

Risk Management Framework

To protect capital, the author lays out a risk‑management blueprint that centers on three pillars:

1. Position Sizing Based on Volatility
   Using the volatility‐adjusted Kelly criterion, the author calculates the optimal trade size so that the probability of a ruin event remains low. He demonstrates the calculation using a sample stock and shows how the size changes when volatility spikes.
   The article links to a Investopedia guide on volatility and the Kelly Criterion: [ Understanding the Kelly Criterion ].

2. Stop‑Loss Policies
   A dynamic stop‑loss is employed, triggered at 15% below the entry price for most stocks, but the author also shows how he uses a trailing stop of 10% on highly volatile names.
   He references a chart that tracks the performance of his stop‑loss strategy over the past 18 months: [ Stop‑loss performance chart ].

3. Diversification Across Sub‑Sectors
   By allocating no more than 10% of the portfolio to any single AI‑related name, the author mitigates idiosyncratic risk. He further diversifies into ETFs that hold a basket of tech stocks, such as ARKK (ARK Innovation ETF) and QQQ (NASDAQ 100 ETF).
   A side note explains the benefits of sector rotation and links to a Bloomberg article on ETF diversification: [ Why ETFs Matter for Diversification ].

Practical Implementation Steps

The article walks readers through a step‑by‑step process:

1. Identify the Core List – Start with a shortlist of 5–7 high‑quality AI names based on the author’s criteria.
2. Quantify Risk Per Trade – Use a fixed‑percentage rule (e.g., 1–2% of portfolio per trade).
3. Deploy the Position Size Formula – Apply the volatility‑adjusted Kelly rule to determine the exact number of shares.
4. Set Stops and Alerts – Place stop‑loss orders and set price alerts to monitor key levels.
5. Review and Rebalance Quarterly – Adjust allocations based on changing fundamentals and risk exposure.

The author emphasizes the importance of documentation: maintaining a trade log that captures rationale, entry/exit points, and post‑trade analysis. He shares a sample log template: [ Trade Log Template ].

Lessons Learned

Throughout the piece, the author recounts real‑world missteps—such as over‑concentration in a single high‑profile stock during a rally and the psychological trap of “anchoring” to the latest news headline. He stresses that a disciplined approach to risk management can transform these pitfalls into learning opportunities.

He also notes that while the current bubble offers significant upside, it is not a “free lunch.” The key takeaway is that a combination of rigorous fundamentals, disciplined position sizing, and proactive risk controls enables investors to claim a meaningful slice of the upside without surrendering their downside protection.

Conclusion

The Seeking Alpha article offers a comprehensive, actionable playbook for investors who want to participate in the high‑growth AI sector without compromising their risk tolerance. By marrying fundamental quality with a structured risk‑management protocol, the author demonstrates that it’s possible to obtain a fair share of the bubble while safeguarding capital—a principle that extends beyond any single sector or market cycle.