We present a machine learning approach to firm valuation that requires only historical accounting data as input. The machine learning model generates a median absolute percentage error of 17.2% in out-of-sample firm value predictions. The model out-performs a sample of final-year finance...

We propose a risk neutral approach to forecast the cashflows of music catalogs, based on historical revenue data. We use a discounted cashflows formula to produce reasonable ranges of multipliers for these assets, based on the age of the catalog, the last-twelve-months revenue and the duration...

In spite of the widespread concerns expressed about the importance of privacy, individuals frequently give away or sell a myriad of personal data. How and why people decide to transition their information from the private to the public sphere is poorly understood. To address this puzzle, we...

This paper contrasts the valuation of accounting numbers related to two classes of assets - the internally managed, fully-controlled assets versus the "significant influence" investments, that is, investments where the investing firm exercises influence, but not control, over the assets. We find...

This issue carries five papers selected from the 9th World Valuation Congressheld in Singapore from 26-28 April 2001. A total of 40 papers were presented,including three keynote and four plenary papers. While the main focus was onproperty valuation, a diverse range of topics was covered,...