VISIONS Full Length Album OUT NOW!
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Villanova School of Business '22
Finance Specialization
Strategic Management Specialization
Here are some examples of modeling efforts that I have done that illustrates some of my interests.
1. A full financial projection NPV model example in Excel
2. Pivot Table Reporting - An example of slicers and pivot table reports in Excel
3. A multi-year P&L statement created from a business ledger imported into Excel
4. M&A Merger Evaluation - AT&T & Time Warner (Synergy Estimate)
5. Stand Alone Equity Valuation (DCF, NPV, Market Multiples)
6. Sample Energy Arbitrage Model - Developed for Meltek, Inc.
The full financial project NPV model looks at sensitivity analysis and different cases to create a dynamic model that projects the three financial statements and includes a calculation of NPV based on the P&L and balance sheet input section in Excel. Completed Sept. 2022.
The pivot table reporting example illustrates a way to combine slicers and Pivot Tables to create dynamic reports available to guide decision making. Completed Sept. 2022.
The multi-year P&L statement showcases the common functions used to clean, manipulate, and reformat ledger transactions into a compiled database using XLOOKUP. P&L statements can then be created efficiently using SUMIF or SUMIFS. YoY percent variation were added to the P&L statement and some common charts were inserted to visualize performance. Professionally formatted. Completed in Sept. 2022.
The M&A model looks at a synergy estimate of the combined company from a pre-merger perspective to arrive at an estimate of the value for the combined company and the suggested M&A acquisition price for Time Warner. Completed in Spring 2022.
The Stand Alone Equity Valuation uses DCF, NPV, and Market Multiple techniques to arrive at an range of estimates for the equity value per share of Graftech International Inc., a publicly traded manufacturing firm. Evaluation completed Spring 2022.
The Sample Energy Arbitrage model was a paid-for consultancy excel model looking at the implied ARR of a large 10kWh battery being charged (buy low) and discharged (sell high) daily in a net-metering context using PSEG's different market electricity rates as of Spring 2021. The model uses historical load data for residential users along different rates and looks at average use per household in the Southampton County. The model assumes a charging of a residential 10kWh battery during low rates, and a battery discharge at the during the peak rates within a 24 hour period to arrive at a customer savings (ARR) number. I developed this model from independent market research
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