Preprint, posted on overleaf.com; last accessed June 11, 2019.
ISSN/ISBN: Not available at this time. DOI: Not available at this time.
Abstract: Benford law states that the occurrence of digits from 0-9 in a large set of data is not uniformly distributed but instead in a decreasing logarithmic distribution with 1 occurring at most. Almost all set of data follows this trend however this law is widely used as a base for various fraud detection and forensic accounting. Benfords law is an observation that leading dig- its in data derived from measurements doesnt follow uniform distribution. Different financial statements such as cash flows, income statement and bal- ance sheet of the 20 tech companies of the Fortune 500 are analyzed in this project. Cash flow is the net amount of cash and cash-equivalents moving into and out of a business. Income statement is a financial statement that measures a company’s financial performance over a specific accounting pe- riod. Balance sheet is a financial statement that summarizes a company’s assets, liabilities and shareholders equity at a specific point in time. All of these data of financial statements are extracted from Morning Star database and are analyzed by Python program written by me.I also wrote the Python program to calculate Benford’s second digit and third digit probability using the formula. I would like to thank Prof. Erin Wagner and Dr. Courtney Taylor for helping in this research project.
Bibtex:
@misc{,
AUTHOR = {Ivan Shrestha},
TITLE = {Validity of the Financial Statements: Benford's Law},
HOWPUBLISHED = {\url{https://www.overleaf.com/articles/validity-of-financial-statements-benfords-law/mrmypktcsbsy}},
YEAR = {2016},
NOTE = {last accessed June 11, 2019},
}
Reference Type: Preprint
Subject Area(s): Accounting