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"Price the right
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About
I'm Pedro Santos Pinto — a results-driven executive based in Madrid and Lisbon, with over 25 years of expertise spanning Corporate Finance, Pricing Intelligence, Business Intelligence, and Strategic Management. My career has taken me across international roles in Madrid, Lisbon, Brussels, and Luxembourg, always at the intersection of financial rigor and data-driven decision-making.
I hold an MSc in Finance from Católica – Lisbon School of Business & Economics, a Post-Graduate in Management Control Systems, and a Bachelor's in Accounting & Administration. I'm a CFA Level II approved candidate and a Certified Pricing Professional (CPP).
Over the years I've led high-performing teams, built pricing intelligence frameworks from scratch across multibillion-euro businesses, served on boards, navigated M&A due diligence, and once ran my own company. I believe the best executives are also the most voracious learners — Risk Premium is the proof of work.
Selected Writing
MSc Research · Católica Lisbon · 2014
Most companies treat capital structure as a passive outcome — debt goes up when they need funding, comes down when they can afford it, and the WACC calculation that follows takes whatever leverage ratio is currently on the balance sheet as given. This thesis argues that approach leaves serious value on the table.
The objective: define a simple, dynamic, and computationally tractable methodology for identifying the optimal capital structure of any listed company, using publicly available information — or, where management uses it, private information too.
The framework integrates five pillars: the dynamic Trade-off Theory of capital structure; WACC as the objective function to minimise; CAPM for cost of equity; and critically, the Merton-KMV structural model for both firm value/volatility and cost of debt. The central insight is that by treating equity as a call option on firm assets, you can back out an implied firm value and volatility from market prices — and from those, derive a forward-looking, market-consistent cost of debt that responds dynamically to changes in leverage and risk.
The methodology was tested on 28 S&P 500 companies across 7 sectors from December 1999 to December 2012. Key findings: almost 100% of the sample was underleveraged relative to their optimal capital structure. On average, their WACCs ran approximately 0.5% above optimal — translating into an average market value loss of roughly $7 billion per company. The pharmaceutical sector showed the largest value destruction (~$14B average); tires & rubber the smallest (~$271M).
The finding that stops most finance professionals in their tracks: across 28 large, sophisticated, publicly listed S&P 500 companies, tracked over 13 years, virtually every single one was holding too little debt. Not recklessly over-equitised, not naively cautious — just quietly, persistently sub-optimal. And they were paying for it, roughly $7 billion each in forgone value, every year.
This is not a controversial result in academic finance. The dynamic trade-off theory has long argued that companies have optimal leverage ratios — points at which the tax benefits of debt and the disciplining effect on management precisely offset the rising costs of financial distress. What is surprising is how rarely the tools exist to locate that optimum with any precision, or how rarely practitioners bother to look.
The standard approach to capital structure is essentially reactive. CFOs watch their credit rating, manage their interest coverage ratio, and adjust leverage opportunistically when markets are favourable. What they almost never do is ask: given what the market currently knows about our asset value and volatility, what leverage ratio would actually minimise our cost of capital? That question requires a model — specifically, a structural model that connects equity market data to an implied firm value and from there to an optimal debt level.
That is exactly what the Merton-KMV framework provides. By treating equity as a call option on firm assets, it makes the link between market prices, asset volatility, and default risk explicit, quantitative, and dynamic. When equity volatility rises, the implied default probability rises, Kd rises, and the optimal leverage falls — automatically. No manual adjustment needed. The model moves with the market.
The practical implication is significant. Capital structure is not a one-time decision made at IPO and occasionally revisited. It is a living variable that should be actively managed, monitored, and periodically rebalanced — much like a portfolio. Companies that treat it as such capture real value. The ones that don't leave billions on the table. The numbers are in the data.
On Camera
A recorded session on pricing, finance, and intelligence — the intersection where most of my professional work lives. Worth a watch if you want to go deeper than the blog.
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Pedro is a magnificent professional. He was my direct superior for several years and was always a great support for my development and professional growth. He has great knowledge and is extremely helpful to all those who need support. He was without a doubt the best professional I have had the opportunity to work with to date.
I've had the privilege of working with Pedro for four years and I can confidently say that he is one of the best leaders I have ever encountered. Throughout our time working together, Pedro has not only demonstrated exceptional leadership skills but has also played a crucial role in my professional development.
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