Hotel Valuation Software, Version 4.0

[Updated August 2016] The Hotel Valuation Software, freely available from Cornell’s Center for Hospitality Research, has been updated to reflect the many changes in the 11th Edition of the Uniform System of Accounts for the Lodging Industry (USALI). Version 4.0 of the Hotel Valuation Software provides numerous enhancements over the original tool from 2011. In addition to a significant increase in functionality and an update to reflect the 11th edition of the USALI, Version 4.0 takes advantage of the power of the latest release of Microsoft Excel®. Note that Version 4.0 works only on a PC running Microsoft Windows, it does not work on a Mac running OS X. Users desiring an OS X compatible version should click here (Labeled as Version 2.5). 酒店评估软件手册和三个程序（点击这里 ) Users desiring a Mandarin version of the Hotel Valuation Software should click here The Hotel Valuation Software remains the only non-proprietary computer software designed specifically to assist in the preparation of market studies, forecasts of income and expense, and valuations for lodging property. The software provides an accurate, consistent, and cost-effective way for hospitality professionals to forecast occupancy, revenues and expenses and to perform hotel valuations. Version 4.0 of the Hotel Valuation Software includes the following upgrades – a complete update to reflect the 11th edition of the USALI – the most significant change to the chart of accounts in a generation, an average daily rate forecasting tool, a much more sophisticated valuation module, and an optional valuation tool useful in periods of limited capital liquidity. Using established methodology, the Hotel Valuation Software is a sophisticated tool for lodging professionals. The tool consists of three separate software programs written as Microsoft Excel files and a software users' guide. The tool is provided through the generosity of HVS and the School of Hotel Administration. The three software modules are: Room Night Analysis and Average Daily Rate: Enables the analyst to evaluate the various competitive factors such as occupancy, average room rate, and market segmentation for competitive hotels in a local market. Calculates the area-wide occupancy and average room rate, as well as the competitive market mix. Produce a forecast of occupancy and average daily rate for existing and proposed hotels in a local market. The program incorporates such factors as competitive occupancies, market segmentation, unaccommodated demand, latent demand, growth of demand, and the relative competitiveness of each property in the local market. The program outputs include ten-year projections of occupancy and average daily rate. Fixed and Variable Revenue and Expense Analysis: The key to any market study and valuation is a supportable forecast of revenues and expenses. Hotel revenue and expenses are comprised of many different components that display certain fixed and variable relationships to each other. This program enables the analyst to input comparable financial operating data and forecast a complete 11-year income and expense statement by defining a small set of inputs: The expected future occupancy levels for the subject hotel Base year operating data for the subject hotel Fixed and variable relationships for revenues and expenses Expected inflation rates for revenues and expenses Hotel Capitalization Software: A discounted cash flow valuation model utilizing the mortgage-equity technique forms the basis for this program. Values are produced using three distinct underwriting criteria: A loan-to-value ratio, in which the size of the mortgage is based on property value. A debt coverage ratio (also known as a debt-service coverage ratio), in which the size of the mortgage is based on property level cash flow, mortgage interest rate, and mortgage amortization. A debt yield, in which the size of the mortgage is based on property level cash flow. By entering the terms of typical lodging financing, along with a forecast of revenue and expense, the program determines the value that provides the stated returns to the mortgage and equity components. The program allows for a variable holding period from four to ten years The program includes an optional model useful during periods of capital market illiquidity that assumes a property refinancing during the holding period

Letter from the Editors

[Excerpt] The Editorial Team is proud to release this 2016 14th Annual Volume of the Cornell Real Estate Review. This year’s issue explores a wide range of topics, including the deployment of new technologies in multifamily properties, the effects of autonomous vehicles on real estate, and the continued ramifications of the housing crisis through the legal tactics of certain mortgage lenders. Also included, a recent repositioning project– the unique turnaround of a former casino hotel property in Reno, Nevada. Furthermore, this release includes a discussion of value-added multifamily investment strategy, an analysis of the impact of rapid transit on the residential market in Hudson County, New Jersey, and a summary of federal affordable housing incentive programs in the United States. This year’s Pathways features an interview with Toll Brothers Division President Karl Mistry (Baker ’04), and the Baker Viewpoint piece explores the concept of curtailment mortgages.

Baker Viewpoint: Curtailment Mortgages are a Win-Win Economic Policy

What happens if you prepay your standard residential mortgage? This question puzzles most people, and worse yet the answer can be even more confusing. However, a minor policy change that alters how prepayments are applied could benefit mortgage borrowers as well as the overall housing market.

A Lender's Vorpal Sword: Expungement Affidavits & Their Power to Void Sheriff's Sales & Revert Mortgages Back to the Homeowner

Like many Americans across the country, Michigan residents have faced a staggering number of foreclosures in the last few years.2 In 2009, Laura Buttazzoni was one of the many Michigan homeowners facing the dire reality that she was going to lose her home.3 After Buttazzoni’s failed attempt to sell her home, her bank initiated a sheriff’s sale in late 2009.4 After the statutory redemption period expired,5 Fannie Mae evicted Buttazzoni and relisted the home in 2011.6 Even though Buttazzoni’s home was foreclosed, sold at a sale, and relisted on the market—she was not done with the property. In June 2012, nearly three years after Buttazzoni’s eviction, Fannie Mae executed an “expungement affidavit,” which voided the 2009 sheriff’s sale and reverted the mortgage back to Buttazzoni’s name.

Asset Management and Investment Banking

We find evidence that conflicts of interest are pervasive in the asset management business owned by investment banks. Using data from 1990 to 2008, we compare the alphas of mutual funds, hedge funds, and institutional funds operated by investment banks and non-bank conglomerates. We find that, while no difference exists in performance by fund type, being owned by an investment bank reduces alphas by 46 basis points per year in our baseline model. Making lead loans increases alphas, but the dispersion of fees across portfolios decreases alphas. The economic loss is $4.9 billion per year.