Every report The Venture Analyst publishes follows the same framework. This page explains the key terms, what each one means in practice, and how the desk applies each concept — with links to published reports that demonstrate it.
The framework is straightforward: start with the filings, build the model from scratch, construct an explicit thesis, and require a credible bear case before anything is published. If a concept below sounds like jargon, that's intentional — every term on this page corresponds to a specific, verifiable step in the analytical process, not a marketing claim.
Every engagement starts from source documents — SEDAR+ filings for Canadian companies, SEC filings for cross-listed names. That means financial statements, MD&As, Annual Information Forms (AIFs), material change reports, and management information circulars. Not press releases. Not IR decks. Not management presentations. The filings.
The reason: IR materials are written to sell the stock. The filings are written to satisfy legal disclosure requirements. They contain things management would prefer you not look at closely — off-balance sheet items, related-party transactions, working capital changes, accrual ratios, footnotes on revenue recognition. The filing is where the analysis actually lives.
Every covered name starts with a three-to-five-year filing review. Segment disclosures are reconstructed line by line. Revenue recognition policies are read and compared year-over-year. Capital allocation history is pulled directly from the statements — not from management commentary about it. If the filing says something different from what management says, the filing wins.
A DCF values a business by forecasting its future free cash flows and discounting them back to present value using a rate that reflects the riskiness of those cash flows (the WACC — weighted average cost of capital). The output is an intrinsic value per share that can be compared to the current market price.
DCF models are the most rigorous valuation tool available, and the most abused. The danger is that small changes to assumptions — terminal growth rate, discount rate — produce dramatically different outputs. A DCF without explicit, scrutinized assumptions is worse than no DCF at all, because it gives false precision to a guessed number.
Every DCF is built with three scenarios: a base case (the most likely operating path), a bull case (the upside if key catalysts execute), and a bear case (the downside if the primary thesis is wrong). All assumptions are stated explicitly — revenue growth rates, margin trajectory, capex intensity, terminal multiple or growth rate. Sensitivity tables show how the valuation moves with the two or three assumptions that matter most. The DCF output is weighted across scenarios to arrive at a blended price target.
Comparable company analysis (comps) values a business by comparing it to publicly traded peers on standardized multiples. EV/EBITDA (enterprise value divided by earnings before interest, taxes, depreciation, and amortization) is the most common — it allows apples-to-apples comparison across companies with different capital structures. Revenue multiples (EV/Revenue) are used when EBITDA is negative or not meaningful, common in earlier-stage or high-growth names.
The challenge in Canadian small-cap is that true peer sets are often thin. The work is in identifying which comparables are actually comparable — not just the same sector, but the same business model, growth profile, and margin structure. Using the wrong peer set produces a misleading multiple.
Peer sets are sourced from public market data and built from the filings — not from screeners that group companies by SIC code. Each comparable is reviewed for similarity of business model, size, and margin structure. Where the covered company is meaningfully different from peers (better margins, faster growth, higher or lower leverage), that premium or discount is explicitly justified rather than assumed. The comps output is used as a cross-check on the DCF, not as the primary valuation.
Net Asset Value (NAV) is the sum-of-the-parts value of a portfolio or asset base — what the underlying holdings are worth, minus liabilities. It is the primary valuation framework for closed-end funds, investment holding companies, royalty companies, and asset-heavy businesses. NAV per share is then compared to the current market price to determine whether the company trades at a premium or discount to NAV.
An NAV discount is the percentage by which the market price sits below the per-share NAV. Persistent discounts can reflect illiquidity, poor management track records, complex structures, or simply neglect. When those discount drivers are mis-assessed by the market, the re-rating thesis is built on discount compression — the stock re-rates toward NAV as the quality of the underlying portfolio is recognized.
NAV builds are constructed from disclosed portfolio positions — fair values sourced from the filing, not management estimates where external pricing exists. Fee structures, carried interest, and incentive fees are modeled explicitly. The thesis identifies what is causing the discount, why that cause is either temporary or mis-understood, and what the catalyst is for compression. If there is no credible compression catalyst, the discount isn't a thesis — it's just a cheap stock.
Free cash flow (FCF) is the cash a business generates after paying for capital expenditures needed to maintain and grow the business. It is the truest measure of earnings power because it reflects actual cash in the door — not accounting profits, which can be manipulated through accruals, depreciation policy, or revenue recognition timing. FCF yield is FCF per share divided by the stock price — analogous to a bond's yield, but for equity.
A high FCF yield means the business is generating a lot of cash relative to its market cap. Whether that's attractive depends on whether the FCF is sustainable, growing, and being deployed intelligently. A declining FCF yield on a growing business can be more attractive than a static high yield on a business in structural decline.
FCF is rebuilt from the cash flow statement — capex is pulled directly from investing activities, working capital changes are analyzed year-over-year, and maintenance capex is distinguished from growth capex where the filings allow. FCF yield is then compared to peers and to the company's own historical range. For mature, capital-light businesses — specialty financials, software, asset managers — FCF yield is often the primary valuation anchor rather than a supplementary check.
The bear case is the scenario in which the thesis is wrong. Not a list of generic risks — "macro uncertainty," "competition," "key-man risk" — but a specific, modeled account of how the investment loses money. If the business has $10M in annual revenue, what specific set of conditions produces $6M? What does that do to the model and the implied price?
Generic risk sections exist to satisfy disclosure requirements. A real bear case exists to test whether the analyst actually understands the business well enough to know how it breaks. If it can't be constructed — if the downside can't be articulated in specific, financial terms — the thesis isn't understood well enough to publish.
The bear case is built before the bull case is finalized. It identifies the two or three assumptions most likely to be wrong — typically revenue growth rate, margin trajectory, or the key catalyst — and models the financial impact of each failing. The resulting downside price is the floor the investment is risked against. If the downside isn't acceptable relative to the upside, the report doesn't get published. This is the standard that makes the research worth reading — and worth commissioning.
A catalyst is a specific, identifiable event that is expected to close the gap between the current price and the assessed intrinsic value. Catalysts can be operational (a major contract win, a product launch, a margin inflection quarter), financial (a debt repayment, a buyback, a dividend initiation), or external (a regulatory decision, a sector re-rating, a peer M&A transaction that reprices the group). Without a catalyst, a thesis is just an opinion that a stock is cheap.
Catalyst tracking is the process of monitoring whether the events the thesis depends on are happening, delayed, or failing — and updating the thesis accordingly. A thesis that was correct on the business but wrong on the catalyst timing is a different situation from a thesis where the underlying business has changed. Those distinctions matter for whether the investment still makes sense.
At initiation, up to three key catalysts are explicitly identified with estimated timing. Each reporting period, the earnings review assesses whether catalysts are tracking, delayed, or no longer operative — and updates the model and price target accordingly. Under ongoing coverage, clients receive these updates same-day or next-day after earnings releases. The thesis check is the most important deliverable in ongoing work — it is what distinguishes coverage from noise.
Every concept on this page is demonstrated in published research. The sample reports below are the real deliverables — not summary sheets.