The portfolio is made up of 100% individual stocks, with the top two positions (Rocket Lab and Robinhood) alone making up almost two thirds of the total value. The top three holdings are over 79%, which is extremely concentrated compared with broad benchmarks where a single position is usually under 5%. This matters because one or two bad outcomes could drive most of the portfolio’s performance. If the goal is to dial down “single company risk,” shifting a portion from the largest holdings into a wider mix of additional positions or broad funds could spread risk without abandoning a growth-focused approach.
Historically, the portfolio shows a massive compound annual growth rate (CAGR) of about 87%. CAGR is the “average yearly speed” of growth, like your average speed on a long road trip. That’s eye‑popping, but it comes with a max drawdown of around −42%, meaning at one point the portfolio was down that much from a prior peak. The fact that 90% of returns came in just 27 days shows how “all or nothing” this ride has been. It’s useful to enjoy strong gains but also to remember that past results, especially from short, speculative periods, can reverse quickly.
The Monte Carlo simulation, which runs 1,000 “what if” scenarios using historical patterns and volatility, shows highly skewed outcomes. In this case, the 5th percentile ends at −100% and even the median (50th percentile) scenario is around −98.6%, with only 226 simulations finishing positive. Monte Carlo is just a model, not a prediction, and it assumes the future looks statistically similar to the past. Still, the distribution here screams “lottery ticket” risk. Anyone keeping this style might think in terms of money they can truly afford to lose, or consider gradually blending in more stable holdings to improve survival odds.
All assets sit in a single class: common stocks. That single‑asset‑class focus can supercharge upside during bull markets but also leaves no cushion when markets fall. Balanced benchmarks usually hold a mix of stocks and lower‑volatility assets (like bonds or cash equivalents) to smooth the ride. Staying 100% in stocks is not “wrong,” especially for aggressive, long‑horizon investors, and the current approach is fully aligned with a speculative profile. However, if the roller‑coaster swings ever feel too intense, even a modest allocation to more stable asset types could reduce drawdowns without fully sacrificing growth orientation.
Sector-wise, the portfolio leans hard into Industrials (41%) and Financial Services (35%), with Communication Services at 20% and only small exposure to Consumer areas. This concentration means performance will be very sensitive to conditions affecting a few specific business themes, such as capital markets activity or demand for certain technologies. Many broad benchmarks spread more evenly across a wider range of sectors. The current tilt is fine if the aim is to make big, focused bets. If the goal shifts toward more stable, benchmark‑like behavior, gradually adding names or funds from underrepresented areas could reduce the impact of a downturn in any single sector.
Geographically, everything is in North America, which is common for many U.S. investors and has historically been rewarded as U.S. markets have done very well. This aligns with how many domestic-leaning portfolios look, so from a “home market” perspective it’s not unusual. The flip side is that there’s zero direct exposure to companies in other major economies, which can sometimes perform differently and help spread risk. If future goals include resilience against U.S.-specific shocks, introducing a modest slice of international exposure could be helpful, while still keeping the bulk of the focus on familiar markets and regulations.
By market cap, the portfolio is heavily tilted to large companies, with about 79% in big caps and 14% in mega caps. That provides some stability because large firms often have more diversified revenue and better access to capital than tiny startups. However, there’s still a small but meaningful slice in small and medium caps plus a few high‑volatility niche names, which raises overall risk. Relative to a typical broad index, this mix is roughly in line at the large end but punchier at the speculative small end. Scaling back the tiniest, riskiest positions could slightly lower volatility while keeping the growth tilt intact.
This chart shows the Efficient Frontier, calculated using your current assets with different allocation combinations. It highlights the best balance between risk and return based on historical data. "Efficient" portfolios maximize returns for a given risk or minimize risk for a given return. Portfolios below the curve are less efficient. This is informational and not a recommendation to buy or sell any assets.
Click on the colored dots to explore allocations.
Efficient Frontier analysis, which looks for the best risk‑return mix using the same ingredients, suggests there’s room to rearrange these holdings for more “efficiency.” Here, efficiency means getting the highest expected return for each unit of volatility, not necessarily being safer overall. The model indicates a portfolio with the same risk could target an expected return of about 58.3%, higher than the current expectation. It also pegs 58.3% as the optimal return at a risk level around 26.1%. If the goal is to stay speculative but smarter, tweaking position sizes—especially trimming oversized holdings—could push the portfolio closer to that efficient mix.
Income from dividends is minimal. Despite a couple of higher‑yield names like Ford and AT&T, the overall portfolio yield sits around 0.45%, which is very low compared with income‑oriented strategies. That lines up with a growth‑and‑speculation mindset where the focus is on capital appreciation rather than steady cash flow. Dividends can act like a “paycheck” from investments, cushioning returns during tough markets. If future needs include regular income or more stability, gradually shifting a slice of the portfolio into stronger dividend payers or more consistent cash‑generating businesses could make the total return profile less dependent on sharp price spikes.
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