How Volaren values stocks

A stock is worth the present value of every cash flow it will ever produce for its owners, discounted for time and risk. Everything downstream — DCF, multiples, scenario analysis — is a different way of estimating that single number. Different methods are useful because none of them is reliable on its own.

The methods disagree because they make different assumptions about what's hard to know: the growth trajectory, the right discount rate, when a high-growth company stops being high-growth. Volaren shows you all of them, then blends them into one figure that reflects the relative reliability of each method for that specific company.

A DCF estimates the present value of a company's free cash flows over an explicit forecast period (typically 5–10 years), plus a terminal value capturing everything beyond that horizon. The discount rate reflects the company's cost of capital — the minimum return its investors expect given the risk.

The four assumptions that drive almost all of a DCF's output:

• Revenue growth — year-by-year forecast through the explicit horizon, then a fade toward a long-run rate
• Operating margin — what fraction of revenue becomes operating cash flow, with a similar fade toward an industry baseline
• Discount rate (WACC) — what return investors require, blending the cost of debt and equity weighted by capital structure
• Terminal value — either a perpetuity-growth model or an exit multiple applied to terminal-year metrics

Volaren computes all four from public disclosures, then lets you override any of them via your thesis. Your overrides propagate through the entire DCF — change the year-5 margin and the model re-cascades every downstream cash flow plus the terminal value.

A comps analysis values a company by looking at what the market is paying for similar companies right now. Pick the peers carefully — they should resemble the subject in business model, scale, growth profile, and capital intensity — then apply the median or mean of their trading multiples to the subject's metrics.

The multiples that matter most depend on the company's stage:

• EV/EBITDA — works for mature, cash-generative businesses with consistent capital structure
• EV/Sales — useful for growth companies where margins haven't normalized
• P/E — works for profitable mature companies; meaningless when earnings are negative or volatile
• P/Book — used for financials and asset-heavy businesses
• P/FFO — the standard for REITs

The discipline isn't picking the right multiple — it's picking the right multiple for this company at this stage, and using a defensible peer set. Volaren handles the peer selection via business-model classification; you can swap in your own peer set if you disagree.

A single price target from a single method is fragile. The number changes too much when a single assumption changes. The remedy isn't to pick a favorite method — it's to weight all of them by their empirical reliability for the company's stage.

An early-growth software company:

• DCF carries less weight (terminal value is most of the value, and terminal value is the most uncertain piece)
• EV/Sales and growth-adjusted multiples carry more weight (the market is paying for revenue trajectory, not current cash flow)
• Book value carries near-zero weight (intangible-heavy business; book value doesn't reflect economic reality)

A mature industrial company:

• DCF dominates (cash flows are predictable, terminal value is a smaller piece of the total)
• EV/EBITDA is reliable (margins are stable, capital structure is normal)
• Growth multiples carry less weight (growth is the wrong story for this business)

Volaren produces a stage-weighted blended price target that reflects this discipline. You see every individual method's output on the football field, plus the blended number that integrates them.

The baseline model runs on consensus assumptions — what the public information available about the company implies if you let the average view drive every input. That's a useful starting point. It's not your view.

Personalizing the model means changing the assumptions to reflect what you believe. Maybe you think the company's growth fades to 8% in five years, not 5%. Maybe you think margins compress more than the market expects. Each override propagates through the entire pipeline — DCF, comps, methodology blend — and the implied price target updates accordingly.

Volaren's thesis interpreter takes your view in natural language ("I think datacenter capex peaks in 2026, not 2025") and translates it into specific numeric overrides on the right driver. You can accept, edit, or reject each translation before it's applied. The model is yours; we just maintain it.

A point estimate is incomplete. Two analysts can agree on the methodology and still disagree by 30% because they made different assumptions about a single driver. The honest output isn't one number — it's a range plus the assumptions that produce each end.

Volaren's football field shows the full distribution of implied prices across every applicable methodology, plus the personalized range under your assumptions. When DCF and comps disagree materially, the chart shows it; you decide which signal you trust.

Volaren works exclusively from publicly available information. That means:

• Public regulatory filings — annual reports, quarterly reports, current event filings, proxy statements
• Public market data — traded prices, traded multiples, traded volumes
• Earnings calendars from publicly available sources
• Analyst consensus estimates from publicly available aggregators

We don't model insider information, non-public deal intelligence, or anything that isn't already discoverable by any investor with a web browser. The discipline is in synthesizing it well, not in finding sources others can't.

Knowing where a tool stops being useful matters as much as knowing where it works. Volaren doesn't:

• Price options or derivatives — we value equity, not contingent claims on equity
• Cover crypto, commodities, or FX as primary instruments — the framework doesn't translate
• Produce buy / sell signals — we produce valuations and let you decide whether the market price is wrong
• Predict short-term price moves — neither does any fundamental valuation framework
• Account for catalyst timing — we model the cash flow consequences of an event, not when the market will price them in
• Replace your judgment — the model converts your view into numbers; the view is still yours to form

A good fundamental valuation tells you what a stock should be worth if your assumptions are right. It says nothing about how long the market will take to agree with you, or whether your assumptions actually are right. Both are problems Volaren intentionally leaves to the investor.

The baseline model refreshes on a daily cadence and on every earnings event for stocks in your portfolio or watchlist. Your personalized overrides are preserved across refreshes — only the unchanged consensus inputs get updated. If a new disclosure changes a baseline input materially, you'll see the propagation immediately when you next open the analysis.

Methodology questions, peer-set disagreements, suggestions for additional methods — we read every message. support@volaren.ai.

For a deeper view of how the platform works end-to-end, see Security and Privacy.