Financial‑modeling resource spike
Several high‑engagement posts surfaced practical modeling resources this week, including a Japanese step‑by‑step LBO guide, Bojan Radojicic’s ’Ultimate Financial Modeling Flow’, and a thread breaking down Free Cash Flow to Equity for DCFs. These pieces offer hands‑on Excel workflows and conceptual anchors that are directly useful for IB/PE interview prep and for translating data‑science skills into valuation work. (x.com; x.com; x.com)
Three finance posts took off at the same time because they solved the same problem from three angles: one showed how to build a leveraged buyout model step by step, one mapped the order of a full Excel model, and one explained the cash flow line that feeds an equity valuation. Together, they turned a subject that usually feels like memorizing jargon into a set of repeatable steps. (wallstreetprep.com) (bojanfin.com) (wallstreetprep.com) A leveraged buyout is a company purchase funded with a lot of borrowed money, and the model is just a spreadsheet that asks one question: can the target company’s own cash flow pay down that debt fast enough to make the buyer’s equity worth much more at exit. In private equity interviews, firms often compress that logic into a paper test with only 5 to 10 minutes and no calculator. (wallstreetprep.com) That is why step-by-step buyout guides travel so far online. The hard part for beginners is not the concept of debt; it is the order of operations, because one broken link between purchase price, debt schedule, and cash flow can wreck the whole model. (wallstreetprep.com) Wall Street Prep’s paper buyout walkthrough lays the sequence out in five blocks: transaction assumptions, sources and uses, forecast, free cash flow, and returns like internal rate of return and multiple on invested capital. That sequence is the finance version of assembling furniture in the right order, because putting the debt schedule before the cash flow forecast leaves you with numbers that have nowhere to come from. (wallstreetprep.com) Bojan Radojicic’s modeling material hits the same pain point from the spreadsheet side instead of the interview side. His course promises 35 lessons, more than 50 Excel sheets, and a featured end-to-end model with 30 integrated sheets, which tells you the product is built around workflow and structure rather than one-off formulas. (robojan.gumroad.com) (bojanfin.com) That workflow matters because most junior analysts do not fail on valuation theory first. They fail when revenue assumptions, working capital, capital spending, and debt planning all live in different tabs and stop talking to each other. (robojan.gumroad.com) The Free Cash Flow to Equity post that circulated this week plugs into the same system at a different point. Free Cash Flow to Equity means the cash left for shareholders after operating costs, reinvestment, and debt obligations, and Wall Street Prep writes it as net income plus depreciation and amortization minus working capital needs minus capital spending plus net borrowing. (wallstreetprep.com) That last piece is where a lot of people coming from data science or general analytics get tripped up. They can build a clean forecast, but valuation asks a different question: which cash flows belong to all capital providers, and which cash flows belong only to equity holders after lenders have been paid. (wallstreetprep.com) Wall Street Prep notes that Free Cash Flow to Equity is used in a levered discounted cash flow model to estimate equity value directly, and that the matching discount rate is the cost of equity. In plain English, if the cash flow belongs only to shareholders, you cannot discount it with a rate meant for both debt and equity and expect the answer to stay coherent. (wallstreetprep.com) The reason these posts spiked together is that they form a ladder. The buyout guide teaches deal mechanics under time pressure, Bojan’s flow teaches how to keep a model organized across dozens of tabs, and the Free Cash Flow to Equity explainer teaches what number the model is actually trying to produce for shareholders. (wallstreetprep.com) (bojanfin.com) (wallstreetprep.com) That combination is unusually useful in 2026 because finance hiring screens still reward spreadsheet fluency, while more candidates now arrive with Python, statistics, or machine-learning backgrounds instead of classic banking training. A resource stack that turns valuation into a sequence of linked blocks gives those candidates a way to translate technical skill into interview-ready finance output. (bojanfin.com) (corporate-finance-learning.kit.com)
