Optimal Gearing & WACC in a nutshell

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Let's break down capital structure theory in a straightforward way. Traditional theories can be complex, but this unprecedented approach simplifies everything for total clarity.

 

Gearing can be assessed using several leverage ratios, of which the Debt‑to‑Equity (D/E) ratio and the Debt‑to‑Capital ratio are among the most widely applied. The D/E ratio is predominantly used by start‑ups, small firms, and high‑growth ventures because their capital structure is typically equity‑driven, making the relationship between borrowed funds and shareholders’ equity the most meaningful indicator of financial risk and ownership dilution. In early‑stage firms, D/E ratios commonly fall between 0% and 50%, reflecting minimal reliance on debt, whereas mature firms often operate sustainably within a 100%–150% range. In contrast, the Debt‑to‑Capital ratio is more relevant for mature, capital‑intensive industries—such as utilities, telecom, and manufacturing—where both debt and equity form substantial components of long‑term financing. These industries frequently exhibit Debt‑to‑Capital ratios in the 40%–60% range, indicating a balanced but debt‑supported capital structure. Both ratios belong to the broader class of leverage measures that evaluate how a firm finances its assets and operations through debt versus equity, but their applicability and benchmark levels vary with organisational size, funding stage, and industry structure.

Step 1 establishes the baseline by identifying the minimum possible WACC in an ungeared scenario. This is achieved by varying the amount of borrowing while keeping the firm effectively unlevered, allowing the model to isolate the lowest WACC attainable without any gearing effects.

Step 2 introduces the first gearing scenario by applying a Debt‑to‑Capital ratio of 100%, thereby incorporating the full impact of leverage into the capital structure. This allows the analysis to observe how WACC responds when the firm is entirely debt‑financed.

Step 3 applies an alternative gearing structure using a Debt‑to‑Equity ratio of 50%, representing a more moderate level of leverage. This scenario enables comparison between full gearing, partial gearing, and the ungeared baseline.

Across all three steps, IRR remains constant because the project’s underlying cash flows do not change. However, NPV varies in each scenario due to changes in the discount rate (WACC). This demonstrates the sensitivity of NPV to capital structure adjustments, while confirming that IRR is unaffected by financing decisions.

There are different options to optimise and the discretion lies with the management.

Note: It is not appropriate to optimise both the Debt‑to‑Equity and Debt‑to‑Capital ratios simultaneously, as the purpose of this analysis is to isolate and evaluate their individual effects on WACC and NPV. Each ratio must therefore be assessed independently to ensure that the impact of gearing on the discount rate and project valuation is clearly attributable to the specific capital structure measure being tested. Also, please remember that big firms do follow capital structure theories and we allowed all sources of capital to be used up in Debt-Capital ratio. 

Notes on video: The optimisation process was carried out in three deliberate stages, each reflecting a different capital‑structure reality and allowing us to observe how WACC, NPV, IRR, and gearing ratios respond under changing financing assumptions.

Step 1 – Baseline optimisation using only borrowed funds The first model imposed no structural constraints other than the availability of debt. This allowed us to observe how the project behaves when financed exclusively through borrowing. It served as a clean baseline for understanding the sensitivity of WACC and project returns to pure leverage.

Step 2 – Corporate‑style optimisation with minimum debt thresholds Next, we re‑optimised the model by introducing a minimum borrowing requirement (> 5,000). This reflects the financing behaviour of established corporates, which typically operate with complex capital structures and maintain significant levels of debt. The 5,000 threshold is a simplifying assumption representing the minimum scale of debt expected in mature firms, though it can be customised for specific financing instruments. This step allowed us to observe how WACC, NPV, IRR, and gearing ratios shift when the capital structure mirrors that of a typical large firm.

Step 3 – Startup‑style optimisation prioritising equity financing Finally, we removed the corporate debt constraint and introduced a new condition reflecting startup financing behaviour: equity must form the dominant source of capital. This aligns with empirical evidence that early‑stage ventures rely heavily on equity due to high risk, lack of collateral, and limited access to debt markets. This step enabled us to compare how WACC, NPV, IRR, and gearing ratios evolve when the capital structure resembles that of a startup.

Across all three stages, we clearly observed how the financing mix influences the cost of capital and project viability. The variations in WACC, NPV, IRR, and gearing ratios across the scenarios provide a structured understanding of how capital structure assumptions shape investment appraisal outcomes.

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Contrastingly, when you watch this new video, all steps 1–3 are the same, but we included the 80,000 owner’s capital, existing capital structure because maximum funding is only 80% and the owner has to put initial investment. This capital structure exists within both geared and ungeared companies. If you observe the results between WACC, NPV, and IRR-> Debt–Capital couldn’t reach 100%, whereas Debt–Equity could reach its threshold of 50%.

  We use Solver to generate the numerical outcomes; however, these results represent modelled scenarios and may not fully reflect actual industry practices. This helps start up owners evaluate WACC for geared and ungeared companies. Example, for an ungeared company, one can consider different bank loans.