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Jan 18, 2025 | 
scholarship.richmond.edu | Tom Arnold |Joseph Farizo
Home > Business > Finance > Finance Faculty Publications > 70 Downloads of this file are for private/personal use only. Do not cite without permission. Arnold, Tom, Joseph Farizo, David North.
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Jan 15, 2025 | 
scholarship.richmond.edu | Tom Arnold |C. Conover |Joseph Farizo |Nancy K. Tran
KEY TAKEAWAYS:Combining Excel’s =LAMBDA and =MAKEARRAY functions allows for the creation of user-defined functions for producing large binomial trees in less than a second. Further applications of the user-defined functions allow for very quick valuations of European and American style options with large binomial trees. Applying similar techniques allows for the calculation of value-at-risk (VaR) measures.
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Jan 15, 2025 | 
scholarship.richmond.edu | Tom Arnold |Joseph Farizo
AbstractInvestors should consider Sharpe ratios and correlations together when adding a new fund to their existing portfolio. The ex-ante information ratio (also known as the appraisal ratio) is effective in informing this decision. However, a maximum Sharpe ratio calculation is equally effective in this decision while providing the additional benefit of producing optimal portfolio weights for the combined portfolio.
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Nov 21, 2024 | 
scholarship.richmond.edu | Tom Arnold |Joseph Farizo |Jonathan M. Godbey
The =LAMBDA function within Excel provides a powerful new tool for investors and analysts. In this treatment, we demonstrate =LAMBDA functions that calculate an option’s intrinsic value, price, and Greeks based on the Black-Scholes model.
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Oct 10, 2024 | 
scholarship.richmond.edu | Tom Arnold |Joseph Farizo |Terry D. Nixon
The calculus and matrix algebra associated with finding the optimal portfolio weights for a set of securities is tedious. However, Excel tools make the computations simple, with minimal programming needed to arrive at optimal portfolio weights for securities in a portfolio. We provide this Excel template and techniques for acquiring optimal weights, which is useful for personal and institutional investors alike.
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Sep 21, 2024 | 
scholarship.richmond.edu | Tom Arnold |Joseph Farizo |Jonathan M. Godbey
AbstractExcel’s new “=LAMBDA” function is applied to multi-stage stock pricing. This provides a context for implementing the =LAMBDA function, a greater understanding of the concept of the time value of money, and a reduction in the complexity of performing the calculation. The =LAMBDA functions lessens the need for using VBA and macros and only requires basic knowledge of Excel function syntax. Recommended CitationArnold, Tom, C., Joseph Farizo, Jonathan M. Goodbye.
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Aug 29, 2024 | 
scholarship.richmond.edu | Tom Arnold |Joseph Farizo |Andrew C Szakmary |Nancy K. Tran
We create a modified duration function that is more accessible than Excel’s current Macaulay duration function (=DURATION) which requires several details about the bond. The dollar duration and convexity functions are not currently available in Excel’s default functions. When these functions are copied to a second Excel file, the functions automatically become available as functions within the second file without the need for recreating the functions.
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Aug 24, 2024 | 
scholarship.richmond.edu | Tom Arnold |Joseph Farizo |Jonathan M. Godbey
AbstractThe mathematics underlying blockchain-based cryptocurrencies is beyond the scope of most undergraduate finance programs. However, students should understand the intuition behind blockchain so that they might better understand how to apply this technology to future cases. In this paper, we develop a mathematically simple digital signature example and a mathematically simple proof-of-work simulation for classroom use. Recommended CitationArnold, Tom, C., Joseph Farizo, Jonathan M. Goodbye.
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Aug 21, 2024 | 
scholarship.richmond.edu | Tom Arnold |Joseph Farizo |Jonathan M. Godbey
AbstractThe =LAMBDA function within Excel provides a powerful new tool for investors and analysts. In this treatment, we show how to create a function that calculates an option’s intrinsic value, price, and delta based on the Black-Scholes model. Other option Greek functions and calculations are available in a downloadable file. The LAMBDA function is not limited to the Black-Scholes model and has important advantages over Excel’s previous solution of creating user-defined functions in VBA.
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Dec 18, 2023 | 
forbes.com | Joseph Farizo
The recent rise in auto insurance premiums encourages many drivers to comparison shop online for coverage. Comparison shopping is essential, but drivers must understand the basics of an auto insurance policy before trying to hunt for coverage alone. While policies differ from insurer to insurer, the basics of the policy are usually the same and broken into Parts A through F. Part A — Liability CoverageMost states require that drivers purchase and maintain minimum levels of liability insurance.
