merger-model

Build an M&A merger model in Excel by providing structured acquirer and target financial data, deal terms, and synergy assumptions to generate pro-forma income statements and EPS impact analysis. The model outputs an Excel workbook with detailed financial analysis and sensitivity tables.

EPS accretion and dilution analysis in an M&A transaction measures the impact of a merger on the combined entity's earnings per share. This Skill calculates this impact by modeling the financing mix, including cash and stock considerations, alongside projected synergies.

Automate pro-forma P&L generation for an acquisition using Python by leveraging the openpyxl library to construct Excel financial models. This Skill requires structured input for company data and deal terms to output a formatted workbook with projected financial statements.

Model revenue and cost synergies in Excel by inputting specific synergy assumptions into the merger model. The Skill calculates these potential savings and incorporates them into the pro-forma financial statements to project the overall financial impact of the merger.

openpyxl supports creating M&A financial modeling sensitivity tables when used within this Skill's framework. The generated Excel workbook includes detailed financial analysis and sensitivity tables to evaluate various deal scenarios and financing mixes.

Evaluating a merger's financing mix and EPS impact requires structured input data for the acquirer and target companies, specific deal terms, and synergy assumptions. These inputs allow the model to calculate the cash and stock considerations and project the combined earnings per share.