The risk profile, derived from past market volatility, reflects the level of risk the portfolio is exposed to. This assessment helps align your investments with your financial goals and comfort with market fluctuations.
The diversification assessment evaluates the spread of investments across asset classes, regions, and sectors. This ensures a balanced mix, reducing risk and maximizing returns by not concentrating in any single area.
Speculative Investors
This setup screams “high risk tolerance and easily bored.” It suits someone who wants aggressive growth, can stomach serious volatility, and doesn’t flinch at huge drawdowns on a screen. The mix suggests long time horizon and a strong belief in equities, plus a bit of a gambler streak with those tiny speculative positions and absurd historical stats. It fits a person more focused on upside stories than on sleep‑at‑night stability, and someone comfortable with the idea that returns might be lumpy, ugly, and highly dependent on a few big winners carrying a lot of dead weight. Patience and emotional resilience are absolutely mandatory here.
This thing looks like you started with three sensible ETFs then got bored and started throwing darts at a stock list. About a third in broad growth and international ETFs, then a messy pile of single names all jostling for attention. It’s labeled “broadly diversified,” but that’s being generous; it’s more like a concentrated stock buffet with some index wallpaper slapped on. Compared with a simple global stock index, this is way more complex for not obviously better balance. Cleaning this up into a clear core–satellite setup—core in broad funds, satellites as high‑conviction picks—would make the whole structure less of a guessing game.
That “CAGR 2,900.93%” with a max drawdown of –98.12% is comedy gold. CAGR (Compound Annual Growth Rate) is supposed to show average yearly growth over time, not look like a meme coin chart that died twice. A –98% drawdown means at some point this thing basically flatlined, then some tiny penny‑like positions probably spiked and made the math go nuts. “1 day makes 90% of returns” just confirms this is a lottery ticket history, not a stable track record. Past data is like yesterday’s weather: interesting, but not a prophecy. Treat these numbers as a warning label, not a flex.
The Monte Carlo stats here are hilariously broken—“nan%” everywhere is the spreadsheet version of shrugging. Monte Carlo just runs thousands of “what if” paths using past volatility and returns, like simulating thousands of alternate timelines. When the output is full of “not a number,” it usually means the underlying data is so extreme or messy that the model choked. The only useful bit: 504 out of 1,000 paths positive, so basically coin‑flip odds of ending ahead in those assumptions. Future projections for a portfolio this chaotic are highly fragile; simplifying positions and reducing wild outliers would make any forward modeling less of a math error generator.
Asset classes: 100% stocks, 0% everything else. Subtle. This is not a portfolio; it’s an all‑equity dare. No bonds, no cash buffer, no real diversifiers—just pure “hope the market gods are kind.” For a speculative profile that’s not insane, but it does mean every correction, recession, or market tantrum hits full force. A little bit of lower‑volatility ballast—short‑term bonds, cash, or other less correlated stuff—could keep this from feeling like riding a roller coaster with no seat belt. Right now, if stocks sneeze, this portfolio catches pneumonia.
Sector breakdown: heavy tech, chunky financials and healthcare, decent industrials, then everything else scraping in single digits. It’s like you tried to be diversified but couldn’t resist chasing “interesting stories.” A 24% tech tilt plus momentum and growth ETFs means you’re pretty wired into the “growth darling” side of the market. Fine when narrative stocks are hot, brutal when they fall out of fashion. Sector tilts are fine if intentional, but this feels more like accidental clustering. Periodically checking if any one theme (like tech + momentum + AI‑ish names) is dominating too much would help tame the drama.
Geographically, it’s “America and friends” with 73% in North America, 16% in developed Europe, and token exposure elsewhere. For a US‑based investor that’s normal home bias, but it still means your fate depends heavily on US policy, dollar strength, and US corporate earnings. The 7% in emerging Asia and Japan combined is fine but not really moving the needle. Surprisingly sensible international exposure for an otherwise chaotic stock mix, but it’s still pretty US‑centric. If the goal is true global balance, nudging more into broad ex‑US exposure via simple funds would do more than sprinkling random foreign stocks and ADRs around.
Market cap split—36% mega, 47% big, then 8% mid and 9% small—actually looks like you accidentally did something reasonable. Large caps dominate, which is pretty standard, but you still sprinkled in enough smaller names to add volatility spice. The issue is not the numbers; it’s that the small slice is full of very specific, sometimes obscure companies that can be wildly boom‑or‑bust. Tilting to small and mid is fine when done through diversified funds; doing it through a handful of niche picks is more like stock‑picking cosplay. If smaller caps are going to stay, keeping each position tiny and intentional would help avoid random landmines.
The total yield of 1.10% is basically coffee money, which is fine for a growth‑leaning setup, but let’s not pretend this is an income strategy. Most holdings are low yield or non‑payers, with one hilarious outlier: Horizon Technology Finance at ~18% yield, which screams “this is risky, not generous.” Yield that high is usually a “may not be sustainable” billboard. Dividends can be a nice stabilizer, like getting small paychecks while you wait, but they’re clearly not the point here. If income ever becomes important, this mix would need a serious tilt toward reliable, modest yielders instead of one or two yield circus acts.
On costs, you actually behaved like a rational human being: ETF fees at 0.05–0.18% are solidly cheap. Total TER of 0.03% looks off versus the listed fund fees, so something in the calculation is weird, but directionally, this is not where the problem is. You didn’t light money on fire with high‑fee products; you just decided to take that savings and spend it on extra stock‑specific risk instead. Keep costs low, absolutely, but pair that with cleaner structure. Low fees are great, but they don’t save you from a 98% drawdown or clownish volatility.
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.
From a risk–return angle, this thing is nowhere near “efficient.” The Efficient Frontier is basically the curve showing the best return you could get for a given level of risk; you’re paying full freight on risk but not clearly getting commensurate, stable returns. Huge drawdowns, lottery‑like return concentration, and redundant risk factors suggest you could probably get similar or better long‑term growth with fewer holdings and a more deliberate mix. Chasing both momentum and growth while stock‑picking around them is like stacking three turbo buttons on one car—you get speed, sure, but also spin‑outs. Trimming noise and focusing on a coherent plan would move you much closer to that efficient sweet spot.
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