DataAnalysis

What are the real financial impacts of a pandemic like COVID-19? Using data from past pandemics and recent research, we estimate the current and projected costs.

Where are we now in the commercial real estate cycle? We analyze current market dynamics, risks, yield expectations, and trends to determine potential well-positioned commercial real estate investments in 2020.

Since the introduction of index funds in the 1970s, the investment management industry has embraced the use of software to enhance its decision-making. With robo-advisors reaching further prominence, will machines replace humans in the world of wealth management?

Impactful applications of IoT are certain to emerge in the near future. We explore how finance professionals should think of the value it can generate for their business by creating a thought framework.

Share buyback schemes, if executed poorly, can be disastrous for shareholders and company stakeholders. Using three examples from the UK market, reasons for failure are explored with some suggested remedies for managers making capital allocation decisions.

Share buybacks have become a popular financial tool for cash-rich businesses that are running short on sufficient projects to invest in. Three case studies are presented here that demonstrate when share buyback schemes are successes.

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. We delve into this and provides a brief tutorial.

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.

Budgeting can be a drawn-out process, yet oftentimes once the year starts and results diverge, they become forgotten. Instead of budgeting just with qualitative methods, managers should combine them with quantitative tools. Comparing regressed historic trends with future expectations can be more accurate and ultimately ensure the budget survives the year.