Hey, it's oji_ai_dev here!
I usually tinker with FX and Japanese stock short-term trading bots, but every now and then, I look for long-term holds. The thing is, standard stock screening metrics like P/E or ROE usually filter for established, profitable companies. Nothing wrong with that, but I crave something more: companies currently in the red, but sitting on next-gen tech that could be commonplace in a decade. It’s a moonshot, sure, but if it hits, it hits big.
So, I completely changed my approach. I started looking for these high-risk, high-reward companies, explicitly ignoring profitability. And man, did I get an education. Most of them were on the brink of running out of cash.
How Do You Value an Unprofitable Company? — Shifting from "Profit" to "Survival"
The first hurdle was valuation. Most unprofitable tech companies are valued by PSR (Price/Sales Ratio), but some are still in pure R&D, with no revenue yet. At that point, there's nothing quantitative to measure. You're left with qualitative factors: "the CEO has a great pitch" or "the tech sounds amazing."
Investing based solely on that is a gamble. As an engineer, I need quantitative criteria. So, I shifted my focus from "profitability" to "survival probability." No matter how groundbreaking the tech, if the company goes bust, the stock becomes worthless. To wait 10 years for a technology to mature, the absolute prerequisite is that the company must stay in business for those 10 years.
To measure this "survival probability," I built a screening script using three key metrics.
Survival Metric 1: Cash Runway
This is the simplest and most crucial: "How many years can the company survive?"
The formula is Cash & Equivalents ÷ Quarterly Cash Burn Rate.
For example, if a company has ¥1 billion in cash and burns ¥100 million per quarter, its runway is 10 quarters, or 2.5 years.
I aimed for a minimum of 2 years. Clinical trials, large-scale proof-of-concept projects, developing next-gen tech—it all takes time. A company that runs out of funding in less than 2 years is game over the moment its next fundraising round fails, no matter how promising the tech. I filtered these out first.
Survival Metric 2: Dilution Rate
Even with a long runway, there's a hidden trap: dilution.
Unprofitable companies can't get bank loans, so they typically raise capital by issuing new shares (equity financing). This dilutes the value of existing shares.
If a company's value stays the same but its share count doubles, the per-share value halves. Companies that issue shares aggressively every year might see their stock price stagnate or even fall, even if the business grows a little. They become a cash sink for existing shareholders.
So, I checked the historical annual share count increase. If it exceeded 20% annually, it's likely the company's business model relies on siphoning money from shareholders. These highly dilutive companies were also excluded.
Survival Metric 3: Real Customer Validation
Many tech companies release news like, "Started PoC (Proof of Concept) with a major corporation!" or "Signed MOU (Memorandum of Understanding) regarding X!"
While they sound good, these are often just "trial" stages and haven't generated a single yen in revenue. The true market need for a technology is only proven when someone is willing to pay serious money for it.
Therefore, I checked for "backlog" or "delivery contracts"—evidence of real, paying customers. Companies with only PoCs or MOUs are still in the dream-story phase. These were also filtered out.
Screening 107 Companies: The Results
I added one more condition: "Is the stock price overheated yet? (1-year return < +100%)." Then, I ran this combined screen on 107 companies in a specific next-gen tech sector.
Here's a simplified version of the logic:
// Survival Screening Logic for Unprofitable Tech
function screenCandidate(company) {
const runway_years = company.cash / company.quarterly_burn / 4;
const dilution_rate_pa = company.shares_yoy_growth;
const has_real_customers = company.backlog > 0 || company.has_delivery_contracts;
if (runway_years < 2.0) return 'FAIL: Runway too short';
if (dilution_rate_pa > 20.0) return 'FAIL: High dilution';
if (!has_real_customers) return 'FAIL: Customers are not real (PoC/MOU only)';
if (company.one_year_return > 100.0) return 'FAIL: Already hyped';
return 'PASS';
}
The results were far stricter than I imagined.
- Most companies failed on "Cash Runway less than 2 years." Their cash burn was simply unsustainable.
- Even those that passed the runway test, a significant number failed on "Dilution Rate exceeding 20%."
- Filtering further by "Real Customer Validation" left almost nothing.
Ultimately, only one company passed all the conditions.
Lesson Learned: This "Treasure Hunt" Was Really a Mine-Clearing Operation
Calling it a "hunt for the next 10x stock" sounds exciting, but what I was actually doing was a full-blown mine-clearing operation. Behind every glittering tech story were precarious financial situations, ready to explode at any moment.
This screening process hammered home how dangerous it is to invest based solely on qualitative "hope" and "stories." The correct sequence, I now believe, is to first use quantitative "survival metrics" to cut out the deadwood. Only then, with a pool of companies with a high probability of survival, can you begin to compare their technological advantages.
This script is still rough, but for individual developers like me to compete against big capital, we have to build these niche analytical tools ourselves and carve out our own edge.
No one knows if this one company will truly be a multi-bagger, but at least I can sleep soundly with this portfolio. I'll share more updates if anything develops.
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