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Good valuation is not a spreadsheet. It is a story made rigorous, validated with numbers and statistics. Before I build a model, I build a narrative: a coherent view of how a business creates value, what assumptions that implies about its future, and where the market’s version of that story diverges from mine. Only then do numbers enter the picture. This is not a stylistic preference. It is the only way I know to ensure that every input in a DCF or a multiples framework means something, rather than being reverse-engineered to reach a convenient conclusion. My work spans semiconductors, healthcare and biotechnology, industrials, and financial services, sectors where complexity tends to obscure rather than reveal value, and where disciplined thinking about the underlying business often surfaces insights that purely quantitative approaches miss.I apply different methods: fundamental valuation (DCF, DDM, Residual Income, rNPV, NAV), relative valuation (trading multiples, precedent transactions), and stochastic and probabilistic methods (Monte Carlo simulations, GBM, mean-reverting processes) where the uncertainty in a business genuinely warrants it. The method follows the business. What I find most useful about writing publicly is not the publishing. It is the accountability. Every assumption I make is visible. Every conclusion I reach can be challenged. I do not write to confirm what the market already believes. I write to find where the prevailing narrative is either incomplete or wrong and to build a case, with transparent assumptions and testable logic, for a different view.
Analyst’s Disclosure: I/we have no stock, option or similar derivative position in any of the companies mentioned, and no plans to initiate any such positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
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