Send the exact assignment or rubric from your classroom and a custom sample written to it lands in 24 to 48 hours, the first one free. IBF-5070 is TESU’s Financial Modeling course. It covers how models are assembled and audited, corporate, project finance and acquisition models and their assumptions, building a corporate model, risk analysis, break-even and scenario analysis, probabilistic risk and time series, historical and market data, and a final project. Searches like "ibf 5070 module 3 assignment example", "IBF5070 sample paper", and "IBF-5070 module samples" land on this page.
What IBF-5070 is really about
Bodmer’s Corporate and Project Finance Modeling: Theory and Practice is the text, and the course has eight modules, beginning with the methodology of a model and alternative model types and ending with a final project that brings the material together.
The middle modules build a corporate model and then test it: risk, break-even and scenario analysis, probabilistic risk with simulation, and the problems of using historical and market data in time series, including volatility and mean reversion. Two live sessions fall in the first and last weeks.
What IBF-5070’s assessments ask for
Five written assignments carry 40 percent, the final project and presentation 30 percent, seven discussions 20 percent and two live sessions 10 percent. Mentors look for a model whose structure can be followed and whose results are explained.
Where students lose points in IBF-5070
Marks go on models with numbers typed inside formulas, inputs scattered across sheets, sensitivity ranges chosen without a source, scenarios read as probabilities, normal distributions assumed for everything and short-term volatility applied to a twenty-year horizon.
The IBF-5070 drawers
IBF-5070 Module 1 assignment example
Written assignment: before a composite southern New Jersey power company decides on a 60 MW solar farm, its analyst sets out how the model will be assembled, with one input sheet, a monthly and annual timeline, calculation blocks, an output page and a check sheet, and explains why spreadsheet errors make that structure necessary. Full sample paper, read it free.
IBF-5070 Module 2 assignment example
Written assignment: the composite power company's analyst compares a corporate model of the whole company, a project finance model of the 60 MW solar farm and an acquisition model for buying an operating project, then lists the assumptions each needs, from P50 generation to the contract price and a terminal value, with their sources. Full sample paper, read it free.
IBF-5070 Module 3 assignment example
Written assignment: the composite power company's five-year model projects revenue rising from $19.6 million to $28.7 million as the 60 MW project comes online in 2027, EBITDA from $9.4 million to $14.8 million, $93.6 million of construction spending in 2026 and the free cash flow left after debt service. Full sample paper, read it free.
IBF-5070 Module 4 assignment example
Discussion: the composite power company's analyst ranks the risks in the 60 MW solar model, generation, construction cost, post-contract prices and operating costs, by how far a realistic change moves the $3.1 million NPV, presents them as a tornado chart and replies on a hospital expansion model and a retailer's store rollout. Full sample paper, read it free.
IBF-5070 Module 5 assignment example
Written assignment: the 60 MW solar model breaks even at a contract price of $66.72 per MWh, generation 3.7 percent below P50 or construction at $1.28 per watt; a combined downside scenario gives an NPV of minus $12.4 million and an upside of $13.3 million, and the paper sets negotiating targets from these results. Full sample paper, read it free.
IBF-5070 Module 6 assignment example
Written assignment: a 5,000-trial simulation of the 60 MW solar project with normal generation, triangular construction cost and lognormal market prices gives a mean NPV of $2.1 million, a 42 percent chance of loss and a P10 to P90 range of minus $6.4 million to $11.9 million; annual PJM price changes from 2019 to 2023 imply 77 percent volatility. Full sample paper, read it free.
IBF-5070 Module 7 assignment example
Discussion: the composite power company's analyst explains why neither the 2019 to 2023 PJM price history nor short forward prices can set a solar project's prices two decades out, how the reversal of the 2022 spike shows mean reversion and why a mean-reverting model with a fundamentals-based long-run price fits better, then replies on interest rates and on copper prices. Full sample paper, read it free.
IBF-5070 Module 8 assignment example
Final project: the complete Cumberland solar model, with a $93.6 million cost, a $70 contract price, $3.1 million base-case NPV, 7.5 percent IRR, about $40 million of debt at a 1.35 coverage ratio, break-evens, scenarios and a 42 percent simulated chance of loss, ends in a conditional recommendation to the Bayshore board. Full sample paper, read it free.
Your classroom shows something else?
Thomas Edison State University revises courses; module counts and deliverables shift between terms. Send what your classroom shows and the desk matches it exactly.
Using a IBF-5070 sample the right way
Send your IBF-5070 model question or the project you are modeling, and a first custom sample comes back free inside 24-48h. Use it to see how a model is laid out and tested, then build your own.
How these samples are written
The eight IBF-5070 samples here model one composite solar project, so the structure set in Module 1 carries the forecast, the break-even values, the simulation and the final recommendation, and every figure was computed from the same model.
IBF-5070 questions, answered
What textbook does IBF-5070 use?
Bodmer’s Corporate and Project Finance Modeling: Theory and Practice, published by Wiley in 2015.
What is the IBF-5070 final project?
A complete financial model with a written report and a presentation in the closing live session, worth 30 percent of the grade.
Does IBF-5070 cover Monte Carlo simulation?
Yes. Module 6 covers probabilistic risk, distributions for model inputs and volatility in time series.