# Financial Model Types and Methods FAQs

Questions about three-statement models, valuation, forecasting, DCF, LBO, and quantitative modelling methods.

Canonical: https://finamodel.com/faq/financial-model-types-and-methods

## Questions and answers

### How do financial modelling and financial analysis work together?

Financial modelling builds the numerical representation; financial analysis interprets what that representation says. They work as a loop rather than two separate tasks:

- **Model:** translate operational assumptions into financial statements, cash flow, returns or value.
- **Analyse:** compare actuals with forecasts, identify the drivers of a variance and test alternatives.
- **Refine:** update assumptions or model logic when the analysis reveals a weak relationship.

For example, a model may assume 10,000 units at £50 each, giving **£500,000 of revenue**. Analysis might show that volume is 8% below plan but price is 3% above plan. The analyst then separates the volume and price effects instead of simply reporting a 5% revenue shortfall. That insight can feed a revised forecast and a new downside case.

A useful model therefore exposes its drivers clearly enough to be analysed. Outputs should include variances, ratios and sensitivities, not only a forecast profit figure. The [budget versus actual guide](/blog/budget-vs-actual-analysis) shows how this feedback loop works, while the [three-statement guide](/blog/3-statement-financial-model) explains the linked model underneath it.

### How do you model financial statements under standards such as FRS 102 and IFRS 18?

Start with the economics of the business, then add a **reporting and presentation layer** that maps model accounts to the required statement captions. FRS 102 and IFRS 18 are accounting frameworks, not forecasting methods: the model still needs operational drivers, but its outputs must use the appropriate recognition, classification, aggregation and disclosure logic.

A practical structure is:

1. Forecast detailed account balances and transactions.
2. Map each account to an income-statement, balance-sheet or cash-flow category.
3. Apply accounting-policy calculations, such as depreciation, leases or provisions, in transparent schedules.
4. Produce statements and reconciliation checks from the mapped balances.
5. Keep management views separate from statutory presentation adjustments.

For example, product revenue of £900,000 and service revenue of £300,000 may be modelled separately because their drivers differ, then aggregated or disaggregated in the presentation layer as the applicable standard requires. A mapping table should show exactly where each source account lands.

The [pro forma financial statements guide](/blog/pro-forma-financial-statements) and [three-statement template](/templates/3-statement-model) provide the modelling structure. The final accounting treatment should always be checked against the entity’s current policies and the applicable standard by a qualified accountant.

### How do you build a financial forecast?

A financial forecast converts a small set of defensible business assumptions into future revenue, costs, cash flow and financial position. Build it from the **operational drivers upwards**, rather than applying one growth percentage to every line.

A simple revenue build might be:

| Driver | Year 1 | Year 2 |
|---|---:|---:|
| Customers | 1,000 | 1,200 |
| Revenue per customer | £400 | £420 |
| Revenue | £400,000 | £504,000 |

The calculation is `customers × revenue per customer`. Costs should then follow their own logic: gross margin for variable costs, headcount and salary for payroll, payment days for working capital, and asset lives for depreciation. Link these schedules into the statements and add a cash or balance-sheet check.

Use at least a base case and a downside case, and compare forecasts with actual results each month. *A forecast is a decision tool, not a promise*: document what would make each assumption change. For a fuller method, see [financial forecasting methods](/blog/financial-forecasting-methods), the [cash-flow forecast guide](/blog/cash-flow-forecast-excel), or test a compact five-year model in the [company forecast tool](/tools/company-forecast).

### What is an LBO model?

An LBO, or **leveraged buyout**, model estimates the returns from acquiring a company using a combination of investor equity and debt. It links the purchase price, financing structure, operating forecast, debt repayment and exit value to the sponsor’s internal rate of return (IRR) and multiple of invested capital (MOIC).

A simplified example:

- Entry enterprise value: £100m
- Debt raised: £60m
- Sponsor equity: £40m
- Exit enterprise value after five years: £125m
- Debt remaining at exit: £35m
- Exit equity value: **£90m**

The sponsor’s gross MOIC is `£90m ÷ £40m = 2.25x`. IRR also reflects the five-year holding period and any interim cash flows. A proper model includes sources and uses, debt tranches, mandatory and optional repayments, cash interest, minimum cash, taxes and an exit sensitivity table.

The main value drivers are entry price, EBITDA growth, cash conversion, leverage, interest cost and exit multiple. These assumptions should be visible and independently adjustable. See the [LBO model tutorial](/blog/lbo-model-tutorial), explore the [LBO model template](/templates/lbo-model), or use the [IRR calculator](/tools/irr-calculator) to check a return stream.

### How are jump processes used in financial modelling?

Jump processes are used when a financial variable can change **discontinuously**, rather than moving only through small continuous steps. They are most common in quantitative models for asset prices, credit events, commodity shocks or insurance losses—not in ordinary budgeting and three-statement forecasts.

A jump-diffusion model combines a continuous process with occasional jumps. Conceptually:

`next value = continuous movement + random jump, if a jump occurs`

The modeller specifies three important jump assumptions:

- the expected number of jumps over a period;
- the average direction and size of a jump;
- the variability of jump sizes.

Suppose an asset begins at £100. Its normal monthly movement may be modest, but the model assigns a 2% monthly probability of a shock averaging −20%. A simulation could produce £102 in an ordinary path and £81 in a path where a jump occurs. Repeating the process builds a distribution of outcomes that better represents tail risk than a continuous-only model.

Results are highly sensitive to calibration, so use observed data where possible and disclose parameter uncertainty. Jump processes should support—not disguise—economic judgement. For the simulation workflow around such paths, see [Monte Carlo simulation in Excel](/blog/monte-carlo-simulation-excel).

### How is Monte Carlo simulation used in a financial model?

Monte Carlo simulation runs a model many times with uncertain inputs sampled from defined probability distributions. Instead of producing one answer, it shows a **range and likelihood of outcomes**. It is useful when several uncertain drivers interact, such as price, volume, margin and exchange rates.

For a simple project model, assume:

- annual volume is centred on 10,000 units;
- selling price is centred on £50;
- unit cost is centred on £32;
- price and volume are negatively correlated.

Each iteration samples those inputs and calculates `profit = volume × (price − unit cost) − fixed costs`. After 10,000 iterations, the outputs can show median profit, the 5th and 95th percentiles, and the probability of negative cash flow. A result such as “18% probability of loss” is more informative than a single base-case profit.

Choose distributions that reflect real constraints, model correlations explicitly and separate genuine uncertainty from poor assumptions. Validate that the underlying deterministic model works before adding simulation; otherwise repeated runs merely multiply an error. The [Monte Carlo simulation guide](/blog/monte-carlo-simulation-excel) explains the Excel implementation, while [scenario versus sensitivity analysis](/blog/scenario-vs-sensitivity) helps determine whether a simpler method is sufficient.

### Which numerical methods are used in financial modelling?

Financial models use numerical methods when a result cannot be obtained conveniently with a direct formula. The right method depends on whether the task is finding a root, optimising a decision, estimating uncertainty or valuing cash flows. Common methods include:

- **Iteration and root-finding:** solve for IRR, a circular interest balance or a break-even price.
- **Numerical integration:** approximate values derived from continuous probability or pricing functions.
- **Optimisation:** choose a product mix, capital structure or portfolio subject to constraints.
- **Simulation:** sample uncertain inputs to estimate an output distribution.
- **Regression and interpolation:** estimate relationships or fill values between known observations.

For example, IRR is the discount rate `r` that makes `NPV(r) = 0`. Because `r` appears at different powers across periods, software usually finds it iteratively rather than rearranging the equation. The result should be checked for multiple sign changes and compared with NPV at the required return.

Complexity should be proportional to the decision. A transparent approximation is often better than an opaque algorithm with weak inputs. Use the [NPV calculator](/tools/npv-calculator) and [IRR calculator](/tools/irr-calculator) to compare the two measures, then see [NPV versus IRR](/blog/npv-vs-irr) for interpretation.

### How does scenario analysis work in a financial model?

Scenario analysis changes a **coherent set of assumptions** to represent different possible futures. A scenario is more than a single percentage adjustment: the inputs should tell a consistent story across revenue, margins, investment, working capital and financing.

For example:

| Assumption | Downside | Base | Upside |
|---|---:|---:|---:|
| Volume growth | −5% | 5% | 12% |
| Gross margin | 31% | 35% | 38% |
| Customer payment days | 60 | 45 | 35 |

The model applies one selected case across all linked schedules. The downside case therefore lowers profit *and* delays cash collection, which may reveal a funding requirement that a revenue-only adjustment would miss. Outputs might compare EBITDA, minimum cash, debt covenant headroom and valuation.

Keep case assumptions in one controlled area, use identical formulas across cases and avoid hard-coding “downside” results directly into output cells. Scenarios should be plausible and decision-relevant: ask what action management would take if each case occurred. The [scenario versus sensitivity guide](/blog/scenario-vs-sensitivity) explains the distinction, and the [three-statement model](/templates/3-statement-model) provides a linked structure in which operating and financing effects can flow together.

### How does sensitivity analysis work in a financial model?

Sensitivity analysis measures how an output changes when one or two assumptions move while other inputs remain constant. It answers questions such as *“What happens to value if WACC rises by 1%?”* or *“How much cash is required if payment days increase?”*

A two-way DCF table might vary WACC across columns and terminal growth down rows:

| Terminal growth / WACC | 8% | 9% | 10% |
|---|---:|---:|---:|
| 2% | £112m | £99m | £88m |
| 3% | £132m | £114m | £100m |

The table reveals both the range of values and which combinations create the greatest risk. Use assumption ranges that are economically credible, keep the base case visible, and make sure the output cell is linked to the actual model rather than copied.

Sensitivity analysis is different from scenario analysis: sensitivity isolates specific variables; scenarios change several related assumptions together. Both are useful, but they answer different questions. Avoid presenting an enormous grid as precision—the result is only as reliable as the model and ranges beneath it. See the [sensitivity analysis guide](/blog/sensitivity-analysis-excel), [scenario comparison](/blog/scenario-vs-sensitivity), and interactive [DCF calculator](/tools/dcf-calculator).

### What is three-statement financial modelling?

Three-statement financial modelling integrates the **income statement, balance sheet and cash-flow statement** into one forecast. A change in an operating assumption flows through profit, cash and the closing financial position without manual re-entry.

Consider a £100 sale on 30-day credit at a 40% gross margin:

- the income statement records £100 revenue and £60 cost of sales;
- receivables increase by £100 until the customer pays;
- inventory or payables reflect the £60 cost according to their timing;
- retained earnings increase by after-tax profit;
- cash changes only when the related receipts and payments occur.

The model normally contains dedicated schedules for revenue, working capital, fixed assets, debt, tax and equity. These feed the statements, which then close through cash or a financing mechanism. A balance check—`assets − liabilities − equity = 0`—should equal zero in every forecast period.

This structure is the foundation for budgeting, credit analysis and many valuation models because it captures both profitability and funding. The [three-statement modelling guide](/blog/3-statement-financial-model) explains the full build, [how the three statements link](/blog/how-three-statements-link) traces the connections, and the [Excel template](/templates/3-statement-model) provides an example structure.

### What is a three-statement model used for?

A three-statement model is used when a decision depends on **profit, cash flow and balance-sheet capacity together**. Typical applications include annual budgets, rolling forecasts, lender cases, acquisition plans, fundraising, covenant monitoring and the operating forecast that feeds a DCF or LBO.

For example, management may plan 20% sales growth and see EBITDA improve. A profit-only forecast could make the plan look attractive. A linked three-statement model also shows that extra inventory and receivables require £2m of cash before customers pay, potentially creating a funding gap. It can then test whether cash on hand, a revolving facility or slower expansion covers that gap.

Useful outputs include:

- revenue, EBITDA and net income;
- operating cash flow and minimum cash;
- net debt and covenant ratios;
- working-capital days and capital expenditure;
- the balance-sheet check.

Use a simpler model if the balance sheet has no bearing on the decision, but do not omit it merely because it is harder to build. The [three-statement template](/templates/3-statement-model) illustrates the complete framework, while the [cash-flow forecasting guide](/blog/cash-flow-forecast-excel) focuses on liquidity and the [debt schedule guide](/blog/debt-schedule-excel) covers financing mechanics.

### How do you build a three-way financial model?

A three-way financial model is another name for a linked three-statement model. Build it in a controlled sequence so the supporting schedules drive the statements rather than the statements becoming a collection of hard-coded plugs.

1. Import and standardise historical income statements, balance sheets and cash flows.
2. Create a assumptions section with units, sources and case selections.
3. Forecast revenue and operating costs from business drivers.
4. Build working capital, fixed assets, debt, tax and equity schedules.
5. Assemble the income statement and balance sheet.
6. Derive cash flow and resolve the cash or financing balance.
7. Add checks, sensitivities and decision-focused outputs.

A mini-linkage is: £500,000 of credit sales at 36.5 receivable days creates average receivables of `£500,000 × 36.5 ÷ 365 = £50,000`. If receivable days rise, the balance sheet asset increases and operating cash flow falls by the movement. *One assumption therefore affects all three statements.*

Do not force the model to balance with an unexplained plug. Trace differences to opening balances, cash-flow classifications or sign conventions. The [statement-linking guide](/blog/how-three-statements-link) shows these flows, and the [three-statement model template](/templates/3-statement-model) offers a worked layout.

### What are the main types and methods of financial modelling?

Financial models are best classified by the **decision they support**, then by the method used to reach the output. Common model types include operating forecasts, three-statement models, cash-flow models, budgets, DCFs, comparable-company valuations, LBOs, merger models, project-finance models and industry-specific operating models.

Methods cut across those types:

- driver-based forecasting links outputs to operational quantities and rates;
- scenario and sensitivity analysis test uncertainty;
- discounted cash flow converts future cash flows into present value;
- relative valuation applies market multiples;
- simulation estimates distributions rather than a single result;
- optimisation selects the best outcome subject to constraints.

For example, a subscription business might forecast customers as `opening customers + additions − churn`, calculate revenue from average customers and price, link that operating forecast into three statements, and then value its cash flows using a DCF. That is one model containing several techniques.

There is no universal taxonomy, so avoid choosing a format because its label sounds standard. Define the decision, outputs, time horizon and required level of detail first. The [comparison of DCF, LBO and three-statement models](/blog/dcf-vs-lbo-vs-3-statement) is a useful starting point, while [business valuation methods](/blog/business-valuation-methods) compares valuation approaches.

### What are the main steps in the financial modelling process?

There is no fixed rule that financial modelling must involve exactly three or six steps. A robust process can be summarised in **six practical stages**, with iteration between them:

1. **Define the decision:** users, outputs, time horizon and material risks.
2. **Collect and validate data:** reconcile historical figures and document sources.
3. **Design the structure:** inputs, calculations, schedules, statements and outputs.
4. **Build the forecast:** translate business drivers into financial results.
5. **Test the model:** formula checks, reconciliations, scenarios and reasonableness review.
6. **Communicate and maintain:** present conclusions, record versions and update actuals.

For a retailer, the forecast might start with stores × sales per store, apply gross margin and operating costs, calculate inventory from stock days, then produce profit and cash outputs. Testing should confirm that higher sales increase receivables or inventory consistently and that the balance sheet still balances.

If someone describes three steps, they are usually combining these into planning, building and reviewing. The labels matter less than completing each control. Keep assumptions separate from formulas and make outputs traceable to their source. The [Excel modelling best-practices guide](/blog/excel-financial-modeling-best-practices) covers structure and controls, while [common modelling mistakes](/blog/common-financial-modelling-mistakes) shows where the process often fails.

### What are the four main types of financial models?

There is no official set of four financial-model types, but a useful high-level grouping is:

| Group | Primary question | Example |
|---|---|---|
| Operating and forecasting | What will the business produce? | Budget or revenue forecast |
| Integrated statements | How do profit, cash and the balance sheet connect? | Three-statement model |
| Valuation | What is the business or investment worth? | DCF or comparables |
| Transaction and financing | How will a deal or capital structure perform? | LBO or merger model |

These groups overlap. An LBO normally contains an operating forecast and linked debt schedule; a DCF often draws cash flows from a three-statement model. The classification is therefore a way to choose scope, not a rule that every workbook fits one box.

As a mini-example, a five-year revenue and margin forecast answers an operating question. Add working capital, debt and cash to create an integrated model. Discount its unlevered free cash flow to estimate enterprise value, or layer in acquisition financing to measure sponsor returns. Each added module should exist because the decision needs it.

See [DCF versus LBO versus three-statement models](/blog/dcf-vs-lbo-vs-3-statement) for a direct comparison and browse the [financial model templates](/templates) for practical examples across categories.

### What are the main types of financial models?

The main types of financial models depend on context. In corporate finance and investment work, you will commonly encounter:

- **Budget and forecast models** for planning revenue, costs and cash.
- **Three-statement models** linking profit and loss, balance sheet and cash flow.
- **Cash-flow and liquidity models**, including 13-week forecasts.
- **Valuation models**, such as DCF, comparable companies and precedent transactions.
- **Transaction models**, including LBO, merger and accretion/dilution analysis.
- **Project and asset models** for infrastructure, property or other ring-fenced investments.
- **Industry models** built around sector drivers such as subscribers, occupancy or production.

A hotel model, for example, may forecast occupied rooms as `available rooms × occupancy`, derive room revenue from the average daily rate, calculate operating cash flow, and value the property using a cap rate or DCF. The model type describes its purpose; the calculations reflect the business.

Select only the modules needed for the decision and expected users. A weekly liquidity decision may need a detailed cash forecast but no valuation. An acquisition may need all three statements, valuation and financing. Explore [business valuation methods](/blog/business-valuation-methods), [13-week cash forecasting](/blog/13-week-cash-flow-forecast), and the site’s [template catalogue](/templates) for examples.

### Which financial modelling techniques are used most often?

The most frequently used financial-modelling techniques are simple, transparent and closely linked to business drivers. They include historical trend analysis, unit-and-price builds, margin assumptions, headcount schedules, working-capital days, roll-forward schedules, scenario analysis, sensitivity tables and discounted cash flow.

A typical forecast combines several techniques:

- Revenue: `units × average selling price`
- Payroll: `average headcount × fully loaded cost per employee`
- Receivables: `revenue × debtor days ÷ 365`
- Fixed assets: `opening net book value + capex − depreciation`
- Value: forecast free cash flow discounted at the required return

Suppose customers grow from 1,000 to 1,150 and annual revenue per customer is £600. Revenue becomes £690,000. If gross margin is 70%, gross profit is £483,000; changing either customer growth or margin can then be tested in a sensitivity table. This approach makes the assumptions visible and auditable.

Choose a technique because it represents the economics—not because it makes the workbook look sophisticated. Advanced simulation or optimisation adds little if the underlying revenue build is weak. The [financial forecasting methods guide](/blog/financial-forecasting-methods), [working-capital guide](/blog/working-capital-modeling) and [Excel formula guide](/blog/excel-formulas-financial-modeling) cover the most reusable techniques.

### How do you choose the right financial model?

Choose the model by starting with the decision and the required output, not with a predetermined workbook. Ask four questions:

1. **What decision is being made?** Planning, liquidity, valuation, financing or a transaction?
2. **Which outputs matter?** Profit, minimum cash, covenant headroom, enterprise value or investor returns?
3. **What time horizon and frequency are needed?** Weekly cash, monthly operations or annual valuation?
4. **How much complexity is material?** Include detail only where it can change the decision.

For example, a company worried about payroll in the next quarter needs a 13-week cash-flow model. A board approving a five-year plan needs an operating or three-statement model. An investor estimating intrinsic value needs a DCF, while a private-equity buyer also needs debt repayment and LBO returns. These are not competing “best” models; they answer different questions.

Build the smallest model that faithfully captures the decision, then add modules as evidence requires. Validate historical data, document assumptions and agree outputs with users before building. The [DCF, LBO and three-statement comparison](/blog/dcf-vs-lbo-vs-3-statement) helps distinguish three common choices, and the [template catalogue](/templates) shows how models vary by purpose and industry.

### How are financial modelling and valuation connected?

Financial modelling creates the forecast and financial relationships; valuation converts selected outputs into an estimate of worth. The quality of a valuation therefore depends on the operating model beneath it. A DCF needs forecast free cash flow, comparables need correctly defined metrics, and an LBO needs cash available for debt repayment.

A simplified DCF bridge is:

`Revenue → EBITDA → EBIT → tax → NOPAT → free cash flow → present value`

If revenue is £10m, EBITDA margin is 20%, depreciation is £0.3m, tax on EBIT is 25%, capex is £0.4m and working capital increases by £0.1m, unlevered free cash flow is approximately **£0.775m**: `(£2.0m − £0.3m) × 75% + £0.3m − £0.4m − £0.1m`. That cash flow can then be discounted and combined with terminal value.

Valuation is not a separate percentage pasted onto a forecast. Assumptions about growth, margins, reinvestment and risk must be consistent across both parts, with sensitivity analysis around the key uncertainties. See [business valuation methods](/blog/business-valuation-methods), the [unlevered free-cash-flow guide](/blog/unlevered-free-cash-flow), and the interactive [DCF calculator](/tools/dcf-calculator).

### What does a financial modelling and valuation analyst do?

A financial modelling and valuation analyst turns business, market and accounting information into decision-ready forecasts and value estimates. The work may sit in investment banking, equity research, corporate finance, transaction advisory, private equity or consulting, and the exact emphasis varies by role.

Typical responsibilities include:

- cleaning and reconciling historical financial statements;
- researching operational and market drivers;
- building forecasts and supporting schedules;
- applying DCF, trading-comparable or transaction methods;
- running scenarios and sensitivities;
- reviewing formulas, documenting assumptions and presenting conclusions.

For example, an analyst evaluating a manufacturer might forecast volume and price by product, derive EBITDA, model capex and working capital, calculate unlevered free cash flow, then compare DCF value with peer multiples. The deliverable is not just a spreadsheet: it is a defensible explanation of *what drives the result and what could change it*.

Strong accounting, Excel, finance and communication skills matter more than any single certificate or “valuation school”. Practical training should include building models from raw statements and checking another person’s work. The [three-statement guide](/blog/3-statement-financial-model), [business valuation methods](/blog/business-valuation-methods), and [student and education resources](/solutions/students-education) provide relevant starting points.

### What is a DCF model?

A DCF, or **discounted cash flow**, model estimates the present value of expected future cash flows. It usually values the operations of a business using unlevered free cash flow, then bridges from enterprise value to equity value by adjusting for net debt and other claims.

The model has four core parts:

- an explicit forecast of revenue, margins, tax and reinvestment;
- unlevered free cash flow;
- a discount rate, usually WACC;
- terminal value for cash flows beyond the explicit forecast.

For example, £10m received in five years is worth about **£6.21m today** at a 10% discount rate: `£10m ÷ (1.10)^5`. A DCF repeats this calculation for each forecast cash flow and terminal value. If those present values total £80m and net debt is £20m, implied equity value is £60m.

The method is conceptually simple but sensitive to long-term growth, margins, WACC and terminal assumptions. Show those drivers explicitly and compare the result with market-based valuation methods. The [DCF model tutorial](/blog/dcf-model-excel-tutorial) explains the full build, the [DCF template](/templates/dcf-model) provides a workbook structure, and the [DCF calculator](/tools/dcf-calculator) offers a quick check.

### How is NPV calculated in a financial model?

Net present value (NPV) is the sum of each cash flow discounted to today at the required rate of return. In a model, use cash flows at consistent intervals and match the discount rate to their risk, currency and timing.

The formula is:

`NPV = Σ Cash flow_t ÷ (1 + r)^t`

Suppose a project requires £100,000 today and is expected to generate £45,000 at the end of each of the next three years. At a 10% discount rate:

- Year 1 present value: £40,909
- Year 2 present value: £37,190
- Year 3 present value: £33,809
- NPV: `−£100,000 + £111,908 = £11,908`

A positive NPV means the forecast return exceeds the selected discount rate, subject to the assumptions being reliable. In Excel, remember that `NPV()` normally discounts future cash flows only; add the time-zero investment separately. For irregular dates, an `XNPV`-style calculation is more appropriate.

Do not confuse NPV with IRR: NPV measures value created at a chosen rate, while IRR solves for the rate that makes NPV zero. Check the numbers with the [NPV calculator](/tools/npv-calculator) and see the [NPV formula guide](/blog/npv-formula-excel) or [NPV versus IRR](/blog/npv-vs-irr).

### How does a DCF valuation model work?

A DCF valuation model forecasts a company’s cash generation, discounts it to the valuation date and adds a terminal value for cash flows after the explicit forecast. The usual enterprise-value approach follows this sequence:

1. Forecast operating performance for five to ten years.
2. Calculate unlevered free cash flow: `EBIT × (1 − tax rate) + D&A − capex − change in NWC`.
3. Discount each cash flow using WACC.
4. Estimate terminal value using perpetuity growth or an exit multiple.
5. Discount terminal value and add it to the forecast-period present values.
6. Adjust enterprise value for net debt and other claims to reach equity value.

For example, if discounted forecast cash flows total £25m and discounted terminal value is £75m, enterprise value is **£100m**. Subtracting £30m of net debt gives £70m of equity value. If there are 10m diluted shares, implied value is £7 per share.

Because terminal value can dominate the answer, test WACC, long-term growth and exit multiples in a sensitivity table. Reconcile the forecast with the integrated statements and cross-check against comparable-company evidence. The [DCF tutorial](/blog/dcf-model-excel-tutorial), [terminal-value guide](/blog/terminal-value-calculation), [WACC guide](/blog/how-to-calculate-wacc) and [DCF calculator](/tools/dcf-calculator) cover each component.