Azure Lodging, Inc.: A Case Study on Capital Budgeting with Capital Rationing in a Service Industry Context

This case illustrates capital budgeting in a service industry context. Three features should make this case attractive to instructors. First, the firm's rationing of capital means that students must select one investment among competing investment alternatives. Second, the project involves renovation of an existing hotel. Most cases consider a business expansion where analysis involves estimation of a single series of cash flows to generate net present value (i.e., future cash flows or not). In this case, students model cash flows if the project is accepted, comparing those cash flows to a model of cash flows if the hotel continues without renovation. Third, we introduce Monte Carlo analysis, an advanced technique for assessing uncertainty. The extensive data students use in this case is from an actual hotel chain's project database. The case has been used in undergraduate and graduate managerial accounting classes.

Investor Reaction to the Discovery of Accounting Fraud: The Period from the Discovery of the Fraud to the Completion of the Correction

This paper examines the period from the discovery of accounting fraud to the completion of correction and examines the reaction of investors on the date of the first news release suggesting accounting manipulation, the date of the subsequent release of information related to the amount of profit correction that was not disclosed on the date of the first news release, and the date of the submission of the correction report. The verification results show that the stock price falls sharply on the day of the first news release and the day when the information about the amount of profit revision is disclosed, that when the amount of profit revision is large and it takes time to disclose information about the amount of profit revision, there is a rebound in the stock price on the day when the correction report is submitted because investors like the resolution of uncertainty, and that there is a relationship between the amount of profit revision and the size of stock price decline. However, when there is no information about the amount of correction on the first day of the news release, investors react uniformly, and the reaction to a large (small) amount of correction is underreaction (overreaction). These results indicate that investors were misled by the misstatements until the fraud was discovered and made decisions based on overestimates of future cash flows, so they suffered unexpected losses when the fraud was discovered, and during the period from the fraud discovery to the completion of correction. Received: 3 August 2021 / Accepted: 6 October 2021 / Published: 5 November 2021

The influence that Spanish Labour Reform represents on Madrid Stock Market: An empirical analysis

Empirical evidence for Spanish Stock Market shows that labour events, like a firm level collective agreement, have informative content for the market due to the loss of wealth that it implies for the investor. Labour Reforms which Spain experienced between the years 2010 and 2012 have allowed the jeopardising of employment and the destruction of jobs, substituting one well paid by another of lower cost for the firm, the cost of dismissal, or the proposals of substituting payoffs by the so-called Austrian backpack, and the elimination of the distinction between temporary and permanent contracts. These Labour Reforms affect many of the accounting and financial variables, which are the subject of analysis and follow-up by investors and analysts, next to the idiosyncrasy of the Open Shop System that is followed in Spain, the present article means to explore the effect on Madrid Stock Market. Our results, applying analysis techniques with decision trees where we control the effect of the economic crisis on the market reaction, show that the Labour Reforms of 2010 to 2012 are incorporated as negative, or positive, information when the investor perceives a possible decrease, or increase, in its future cash flows.

A framework for modelling cash flow lags

Traditional models of irreversible investment problems assume that the investment starts generating cash flows immediately, i.e., at the same time as the investment is undertaken. Real-world investment situations are characterized by time-to-build or investment lags, which means that there is a time difference between when the investment is made and when the investment starts generating cash flows. We combine two existing models of investment lags to obtain a flexible, yet simple, way of modelling and analyzing the effects of investment lags. Both traditional models, and models that incorporate the effects of time-to-build, typically assume that the expected future cash flows generated by an investment are represented by a single cash flow that reflects the size of the market value of an investment. To reflect real-world cases where investments generate cash flows in several time periods, we present a framework in which cash flows are explicitly allowed to be spread out in time. Our model can be used to incorporate cases where an investment is partially sold in different time periods. Using an irreversible optimal investment timing problem case study, we show how our framework makes it possible to easily compare the effect of different cash flow timings. In this case, the value and the timing of the investment depend on a constant that in a natural way can be decomposed into three parts, thereby showing the influence of the value and timing from the respective parts of the framework.

The Predictive Ability of Quarterly Financial Statements

A fundamental role of financial reporting is to provide information useful in forecasting future cash flows. Applying up-to-date time series modelling techniques, this study provides direct evidence on the usefulness of quarterly data in predicting future operating cash flows. Moreover, we show that the predictive gain from using quarterly data is larger for asset-heavy industries and industries with higher levels of earnings smoothness. This study contributes to the accounting literature by examining the usefulness of quarterly financial statements in predicting the realization of future cash flows. Our results help fill the gap in knowledge on quarterly financial statements and provide new insights on why the frequency of financial reporting matters. In addition, our findings have important policy implications for the ongoing debate over interim reporting requirements in multiple jurisdictions around the world.

Predictive value of accruals and the moderating role of company size: Empirical evidence from Jordan

The cash flow statement aids the management to ascertain the profitability and liquidity position of a company. One can understand from the cash flow statement how efficiently the company is paying its obligation in various forms of liability and expense. This study aimed to explore the ability of short-term accounting accruals to predict cash flows. The sample included 77 Jordanian companies listed between 2006–2019. Cash flows were measured by net operating cash flows, and short-term accounting accruals were expressed as: change in account receivable, change in accounts payable, change in inventories, and other accruals. The results demonstrated the ability of short-term accounting accruals to predict future cash flows. The relationship between future cash flows and the short-term accounting accruals was significant, except for its relationship to the change in accounts payable. However, the findings indicate that the size of the company has not moderated the relationship between accounting accruals and operating cash flow. The study recommends using other accounting items besides short-term accounting accruals, to improve their ability to predict future cash flows and use of control variables that can increase the predictive power of the study model, such as financial leverage and company size. AcknowledgmentsI would like to thank Amman Arab University for its great support, and for funding this study.

The Effect of Accrual Quality and Operating Cash Flows on Future Cash Flows in the Basic Industry and Chemical Sectors

This study aims to analyze the effect of accrual quality and operating cash flow on future cash flows. Accrual quality in this study is measured by the accruals-working capital approach, referring to Dechow and Dichev [1] and Francis et al. [2], cash flow is measured by the ratio of operating cash flows to assets. The population of this research is the Basic Industry and Chemical sector companies listed on the Indonesia Stock Exchange for the period 2014-2018. The samples were determined using purposive sampling which resulted in 144 firms year came from 32 companies. The results of this study showed that there is a significant positive effect the accrual quality and operating cash flow on future cash flows. Management should manage the company's operating cash flow efficiently, and simultaneously improve the quality of the company's accruals which will be a positive signal for investors creditors.

Project Valuation: Price Forecasts Bound to Discount Rates

For their appraisals, most companies use discount rates that account for timing and riskiness of projects. Yet, especially for commodity projects, discounting future cash flows is generally at odds with the assumptions in a company’s hurdle rate. With a multitude of technical and market uncertainties, inconsistent assessments lead to biased valuations and poor investment decisions. In this paper, we consider price forecasts and discount rates in an integrated framework. We calibrate the risk premiums in a two-factor stochastic price process with a capital asset pricing model-based discount rate. Together with the analysts’ long-term prices forecasts, the suggested method improves consistency in valuation and decision making.

An individual claims reserving model for reported claims

We present a claims reserving technique that uses claim-specific feature and past payment information in order to estimate claims reserves for individual reported claims. We design one single neural network allowing us to estimate expected future cash flows for every individual reported claim. We introduce a consistent way of using dropout layers in order to fit the neural network to the incomplete time series of past individual claims payments. A proof of concept is provided by applying this model to synthetic as well as real insurance data sets for which the true outstanding payments for reported claims are known.