#Modeling Posts

The Python language has the functionality to consign many a VBA-filled spreadsheet, held together with sticky tape, to the recycle bin. Its ease of use and suitability for iterative development lends well to finance-based workflows. This article delves into this and provides a brief tutorial.

Stock options are widely used in public and private markets, both as malleable trading tools and for employee compensation. Yet many do not understand the components behind how they are priced. This guide discusses what drives the behavior of call and put options and how they can be deployed within portfolio management.

Hidden in Excel and Power BI is a powerful data analysis pack named Get and Transform (previously known as Power Query). It is an ETL pack for cleaning and sorting raw data from a range of input sources, such as CSV and text files. This tutorial demonstrates how Get & Transform can help the data analyst both save time and uncover more insight.

For a business manager, choosing what to invest in should not be an exercise of instinct. With capital budgeting methods, managers can appraise various projects simultaneously, with the end result indicating which one will have the highest impact on company value.

Traditional approaches to valuing real estate can lean towards the qualitative side, relying more on intuition over sound rationale. Linear regression analysis, however, can offer a robust model for using past transactions in an area, to provide better guidance on property valuations.

One of the most important and challenging aspects of forecasting is handling the uncertainty inherent in examining the future. Every CEO, CFO, board member, investor, or investment committee member brings their own experience and approach to financial projections and uncertainty, influenced by different incentives. Oftentimes, comparing actual outcomes against projections underscores the need to explicitly recognize uncertainty.

Monte Carlo simulations are an extremely effective tool for handling risks and probabilities, used for everything from constructing DCF valuations, valuing call options in M&A, and discussing risks with lenders to seeking financing and guiding the allocation of VC funding for startups. This article provides a step-by-step tutorial on using Monte Carlo simulations in practice.

The discount rate is a critical input in any discounted cash flow valuation analysis. How does an analyst estimate a reasonable discount rate for a private company that has no publicly traded debt or equity?

This article focuses on best practices for estimation of the WACC in the context of a private company valuation. The discussion begins with an overview of the WACC, background on the components of the WACC, methods to estimate the WACC components for private companies, and an example of how to apply this framework to estimate a privately-held building materials company.

From abstract spreadsheets to real-world application, financial models have become an inextricable part of business life and an indispensable part of every company’s toolkit. But irrespective of its ubiquitousness as a productivity and decision-making tool, many out there still have a love-hate relationship with it.

Finance expert Alberto Bazzana authors a comprehensive “how-to guide”, for both the novices and experts among us, detailing Wall Street’s best practices for intelligent, effective, and error-free financial modeling.

When most finance professionals hear the term “13 week cash Forecast,” they view it as a burden—one more task to appease an overbearing lender. It doesn’t help that it seems less exciting than analyzing an investment or acquisition. Therefore, people often only prioritize these forecasts in distressed situations, when it is too late to take corrective actions.

However, in this article, Toptal Finance Expert Marty Mooney argues that weekly cash forecasts are crucial for all businesses, irrespective of size, health, or sector. It also provides a simple tutorial for efficiently building such analyses.

With the arrival and growing ubiquity of big data, Excel, as a data-mining and processing tool has been pushed to its limits—reflected in its dated 1,048,576 row hard limit and the application’s processing speed slowing to a crawl. As of 2010, Microsoft released a Power Pivot function that transformed the scope and usefulness of Excel where the extraction, combination, and analysis of large datasets are concerned.

Using live cases, Finance Expert Ellen Su explores in detail how to master Power Pivot and explores its hidden advantages as a big data tool.