Cash Flow Forecasts Research Articles

Decision-Useful Asset Measurement from a Business Valuation Perspective

SYNOPSIS This article proposes an approach to asset measurement rooted in business valuation theory and practice. In the context of a business valuation, investors' information needs and the asset measurement investors find useful vary with the manner in which the assets are expected to realize value for the firm. After reviewing arguments made in economic and accounting theory, accounting research, accounting standards, and practitioner and business valuation literature, we conclude that for in-exchange assets, investors need to determine the value expected to be realized in exchange. Exit price in a hypothetical market exchange (i.e., fair value) less expected costs to sell provides investors with decision-useful information in this regard; replacement cost and historical cost do not. For in-use assets investors require information useful in forecasting cash flows generated by using such assets in combination. Based on arguments and data presented in the aforementioned literature, we conclude that historical cost generally provides investors with decision-useful information for forecasting purposes; fair value does not. In addition, replacement cost can provide decision-useful information provided holding gains and losses are separately disclosed, but its decision-usefulness can be constrained by verifiability concerns.

Investor mood and the determinants of stock prices: an experimental analysis

AbstractWe examine, in a controlled experimental setting, whether changes in investor mood cause changes in the determinants of stock prices. Our results show that a deterioration in mood, reflected in the negative dimensions of mood state, increases the level of risk aversion in male, but not female, investors. We find no evidence to suggest that a change in mood impacts on investors' forecasts of future earnings or future cash flows. By establishing the causal impact of a change in mood on risk aversion, our study provides support for archival research that relates various market anomalies to investor mood.

Are analysts' cash flow forecasts useful?

AbstractThis study provides evidence that the cost of equity capital decreases with the number of analysts who issue both cash flow and earnings forecasts (cash analysts). The evidence also shows that cash analysts reduce information asymmetry and predict long‐term earnings more accurately than analysts who issue only earnings forecasts. Taken together, these findings suggest that cash analysts provide market participants with high‐quality information and, as a result, firms benefit from cash analyst coverage in the form of a reduced cost of equity capital.

The Value Relevance of Mandated Cash Flow Forecasts: Evidence from Royalty Trusts

We identify a setting in which firms are required to disclose discounted cash flow (DCF) estimates relating to the value of their primary assets. ASC 932 (formerly SFAS No. 69) has mandated DCF disclosures for proved oil and gas reserves since 1982, and these reserves constitute the primary assets of oil and gas royalty trusts. For a hand-collected sample of oil and gas royalty trusts, we find that (i) the mandatory DCF disclosures are incrementally value relevant over historical cost accounting variables; (ii) investors misprice royalty trust units because they underweight the disclosed DCF estimates when forecasting future distributions; and (iii) media articles bringing attention to discrepancies between price and the disclosed DCF estimates are significant stock price catalysts. While our evidence indicates that mandatory DCF disclosures can be incrementally useful for security valuation, it also indicates that investors may overlook such information, potentially due to lack of attention and accounting expertise.

FINANCIAL MANAGEMENT OF MONETARY FLOWS IN UKRAINE

The essence and specific features of cash flows of the Consolidated Budget of Ukraine, income and spending, the banking sector are studied. Theoretical trends explaining the origin and formation of the cash flows are analyzed. The classification of cash flows according to six basic features type, direction, nature of the impact, hierarchical levels, levels of control, elements of the financial system has been developed. The comparison of some countries of the world with Ukraine on the indicators of territory, population, unemployment, the average monthly wage, GDP and exchange rates is presented. The structure of GDP by income in 2012 was analyzed. Therefore in the result of the stated analysis it has been discovered that the wages (51%), gross profit and mixed income (34.8%) constitute the greater proportion. The reasons hindering the effective administration of the tax to the state budget are studied. To ensure effective tax administration and the formation of optimal flows of the Consolidated budget of Ukraine relevant principles are offered. The financial flows of the population, in particular the income and expenditure structure in 2012, are analyzed in details. The analysis revealed that the greater part of the income structure belongs to wages (42.2%), and the cost structure includes the purchase of goods and services (83.8%). 2009-2012 The available supply of money in circulation and deposits of households for the period of 2009-2012 was analyzed. The appropriateness of management of these funds for advanced manufacturing and innovation has been studied. The appropriate methods of forecasting of cash flows of mathematics are offered. Reasonable suggestions for effective management of financial flows in Ukraine in the fields of corruption reducing, tax legislation improving, and the formation of effective control mechanisms are grounded.

We Don't Replicate Academic Accounting Research Or Do We?

The purpose of this introduction to this mini-forum on replication research in accounting is to explain the thought process behind the decision to publish back to back in the same issue of Contemporary Accounting Research two articles that have a substantial overlap in motivation, data and analysis. Indeed the two articles are definitely replications of each; albeit there are differences in the design choices that each set of authors made leading to dramatic differences in sample sizes. However, despite what differences there are, the articles arrive at the same conclusions. The topic is the rise of analysts’ provision of cash flow forecasts and the decline of the accruals anomaly – certainly issues that bear careful examination given the controversy associated over the relative sophistication of analysts’ cash flow forecasts and the changes over time in the most widely accepted and researched anomaly, the accruals anomaly. Nonetheless, given our alleged lack of a replication culture in accounting, I decided that a brief introduction and justification was in order as part of presenting these two articles and their associated commentaries.

A model for integrated capital disclosure and performance reporting: separating objects from value

This paper introduces a conceptual model for integrated capital disclosure (ICD) and performance reporting. The paper details the design of a simplified key element taxonomy that highlights current and forecasted product, people and physical infrastructure (3Ps) resources, transactions and activities as carriers and drivers of intellectual capital (IC). We introduce object recognition and tracking technologies and suggest to separate accounting object definitions from valuation and measurement methods. Each reporting entity or organization has to report and forecast cash flows and accounting estimates, and should disclose potential IC, including risk assessment, based on the key element taxonomy. Financial capital is reconciled in a separate schedule. The taxonomy matrix allows aligned risk and integrated reporting assessments to be more focused, thereby reducing duplication in reporting. The matrix also codifies and integrates financial and sustainability (non-financial) reporting disclosures. Further studies should determine whether the proposed concepts lead to better use and understanding of information. There is a vacuum in assessing the performance of entities on the basis of total information made up of financial and non-financial reporting. Financial, sustainability, IC, tax and statistics reports, and other data are difficult to understand for those who are not industry experts. The ICD model combines and relates information. The suggested new concepts and paradigm changes are designed to reduce this complexity, and should result in more focused comparisons between and within industries.

Separating the Wheat from the Chaff: Identifying the Signal and Predictable Error Components of Target Price Forecasts

Using the analytical framework originated in Campbell and Shiller (1988), we show that target price implied returns are a function of expected dividends, analysts’ private information about future stock returns, and errors with respect to forecasting cash flows and discount rates. Our empirical application of the model explains approximately 24 percent of the cross-sectional variation in target price implied returns, of which around eight percent is explained by analysts’ information about expected dividends and future stock returns. We also find that analyst errors in assessing the returns to risk are more important than poor fundamental forecasts or badly aligned economic incentives in explaining the cross-sectional variation in implied returns. We then use the model to decompose target price implied returns into a signal and a predictable error component. The results show that the signal component is positively associated with future returns over short time horizons (the following two months), while the predictable error component is negatively associated with future returns up to at least six months. Two trading strategies based on the two components earn abnormal returns of 74 to 113 basis points per month. These results suggest that investors fail to react efficiently to the signal and the predictable noise components of analyst target price forecasts.

Analytical debiasing of corporate cash flow forecasts

Abstract We propose and empirically test statistical approaches to debiasing judgmental corporate cash flow forecasts. Accuracy of cash flow forecasts plays a pivotal role in corporate planning as liquidity and foreign exchange risk management are based on such forecasts. Surprisingly, to our knowledge there is no previous empirical work on the identification, statistical correction, and interpretation of prediction biases in large enterprise financial forecast data in general, and cash flow forecasting in particular. Employing a unique set of empirical forecasts delivered by 34 legal entities of a multinational corporation over a multi-year period, we compare different forecast correction techniques such as Theil’s method and approaches employing robust regression, both with various discount factors. Our findings indicate that rectifiable mean as well as regression biases exist for all business divisions of the company and that statistical correction increases forecast accuracy significantly. We show that the parameters estimated by the models for different business divisions can also be related to the characteristics of the business environment and provide valuable insights for corporate financial controllers to better understand, quantify, and feedback the biases to the forecasters aiming to systematically improve predictive accuracy over time.

Cash flow forecast for South African firms

This paper applies models in the extant literature that have been used to forecast operating cash flows to predict the cash flows of South African firms listed on the Johannesburg Stock Exchange. Out-of-sample performance is examined for each model and compared between them. The reported results show that some accrual terms, i.e. depreciation and changes in inventory do not enhance cash flow prediction for the average South African firm in contrast to the reported results of studies in USA and Australia. Inclusion of more explanatory variables does not necessarily improve the models, according to the out-of-sample results. The paper proposes the application of moving average model in panel data, and vector regressive model for multi-period-ahead prediction of cash flows for South Africa firms.

Fuzzy Forecasting of the Сash Flow Statement Based on Accounting Data

This article is devoted to the practical aspects of the cash flow statement forecast. The proposed formation method is based on the fuzzy logics and the procedure of expert evaluations. As the result of premade theoretical analysis of the financial statements fuzzy forecast, a computer program has been developed to support the formation of the forecasted cash flow statement. The article describes the software’s working algorithm and presents its main windows. DOI: 10.5901/mjss.2014.v5n24p237

Discussion of “Analysts’ Cash Flow Forecasts and the Decline of the Accruals Anomaly” and “Analysts’ Cash Flow Forecasts and Accrual Mispricing”

Discussion of “Analysts’ Cash Flow Forecasts and the Decline of the Accruals Anomaly” and “Analysts’ Cash Flow Forecasts and Accrual Mispricing”

Stochastic financial analytics for cash flow forecasting

Accurate cash flow forecasting is essential for successful management of firms and it becomes especially critical during uncertain market and credit conditions. Without accurate cash flow forecasting, a firm may fail to meet its short-term obligations and risk bankruptcy. Accurate cash flow forecasting can be limited by a number of factors including changes in macro-economic conditions that influence liquidity in the economy, customer payment behavior that can vary from time to time as well by industry, and dynamics of the particular supply chain itself. We develop stochastic financial analytics for cash flow forecasting for firms by integrating two models: (1) Markov chain model of the aggregate payment behavior across all customers of the firm using accounts receivable aging and; (2) Bayesian model of individual customer payment behavior at the individual invoice level. As the stochastic dynamics of cash flow evolves every day, the forecast can be updated every time an invoice is paid. The proposed model is back-tested using empirical data from a small manufacturing firm and found to differ 3–6% from actual monthly cash flow, and differs approximately 2–4% compared to actual annual cash flow. The forecast accuracy of the proposed stochastic financial analytics model is found to be considerably superior to other techniques commonly used. Furthermore, in computer simulation experiments, the proposed model is found to be largely robust to supply chain dynamics, including when subjected to severe bullwhip effect. The proposed model has been implemented in Excel, which allows it to be easily integrated with the accounts receivable aging data, making it practicable for small and large firms.

Analysts' Cash Flow Forecasts and Accrual Mispricing

Contemporary Accounting ResearchVolume 31, Issue 4 p. 1191-1219 Original Article Analysts' Cash Flow Forecasts and Accrual Mispricing† Suresh Radhakrishnan, Suresh Radhakrishnan University of Texas at DallasSearch for more papers by this authorShu-Ling Wu, Shu-Ling Wu National Taiwan UniversitySearch for more papers by this author Suresh Radhakrishnan, Suresh Radhakrishnan University of Texas at DallasSearch for more papers by this authorShu-Ling Wu, Shu-Ling Wu National Taiwan UniversitySearch for more papers by this author First published: 17 August 2013 https://doi.org/10.1111/1911-3846.12060Citations: 39 †Accepted by Jeffrey Callen. We thank Jeffery Callen and two anonymous reviewers for insightful comments and suggestions. We also acknowledge comments from Indranil Bardhan, Surya Janakiraman, Stanimir Markov and the participants of seminars at the University of Texas at Dallas, National Chengchi University, and National Taiwan University. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume31, Issue4Winter 2014Pages 1191-1219 RelatedInformation

The Quality of Analysts’ Cash Flow Forecasts in China

Abstract There is a growing literature discussing the incentives of analysts to disseminate cash flow forecasts and the quality of these forecasts. Most studies support the ‘demand hypothesis’ and suggest that cash flow forecasts contain information additional to that provided in earnings forecasts. In contrast, Givoly et al. (2009) show that cash flow forecasts are just a simple extrapolation of analysts’ earnings forecasts. In response to this challenge, Call et al (2013) point out that the regression tests in Givoly et al (2009) are non-diagnostic due to the measurement problem contained in the US dataset. We suggest that Givoly et al. ’s (2009) method can be well applied in China since Chinese data do not have the same measurement problem as that contained in US data. By replicating the studies of Givoly et al. (2009) and Call et al. (2013), we find results consistent with Givoly et al. (2009) that analysts’ cash flow forecasts appear to be naïve extensions of their earnings forecasts in China.

Analysts' Cash Flow Forecasts and the Decline of the Accruals Anomaly

Contemporary Accounting ResearchVolume 31, Issue 4 p. 1143-1170 Original Article Analysts' Cash Flow Forecasts and the Decline of the Accruals Anomaly† Partha S. Mohanram, Partha S. Mohanram University of TorontoSearch for more papers by this author Partha S. Mohanram, Partha S. Mohanram University of TorontoSearch for more papers by this author First published: 17 August 2013 https://doi.org/10.1111/1911-3846.12056Citations: 70 †Accepted by Steve Salterio. An earlier version of the paper was presented at the 2012 Contemporary Accounting Research Conference, generously supported by the Canadian Institute of Chartered Accountants. The author would like to thank Steve Salterio, the discussant Katherine Schipper, two anonymous referees, Sid Balachandran, Urooj Khan, Gordon Richardson, Julian Yeo, and seminar participants at the 2012 CAR Conference, Columbia Business School, University of Toronto, Ohio State University, Carnegie-Mellon University, IIM-Bangalore, INSEAD, RSM-Erasmus University and the Indian School of Business. The author acknowledges generous research support funding from the Certified General Accountants of Ontario (CGA Ontario) and the Rotman School of Management. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume31, Issue4Winter 2014Pages 1143-1170 RelatedInformation

IFRS Impact on Accounting Quality in Telecommunications Industry

Globally, the use of the IFRS in financial reporting is the requirement in many countries. However, the question of whether such a global transition towards a single set of accounting standards has been met by the presumed benefits of higher accounting quality and comparability yet remains unanswered. This paper primarily examines the effect of the mandatory IFRS adoption in Canada by the Canadian telecommunication companies. Since this research is an empirical study, this research has adopted quantitative research method. That is, by conducting survey, it has collected archival data from the eight large telecommunication companies of Toronto Stock Exchange (TSX/SP increase in earnings influence to shareholder value; negative volatility in market price; better predictability of cash flow and financial forecasts; decrease in accruals and timeliness loss of recognition; increase in fair market valuation; significant increase in value relevance; increase in valuation usefulness of earnings to BVPS; and increase in operating capability and predictability.

Stochastic economic models for actuarial use: an example from China

AbstractIn this paper, the first study of stochastic economic modelling with Chinese data is conducted for actuarial use. Univariate models, vector autoregression and two cascade systems (equity-driving cascade system and price-inflation-driving cascade system) are described and compared. We focus on six major economic assumptions for modelling purposes, which are price inflation rate, wage inflation rate, long-term interest rate, short-term interest rate, equity total return and bond total return. Granger causality tests are used to identify the driving force of a cascade system. Robust standard errors are estimated for each model. Diagnostic checking of residuals, goodness-of-fit measures and out-of-sample validations are applied for model selection. By comparing different models for each variable, we find that the equity-driving cascade system is the best structure for actuarial use in China. The forecasts of the variables could be applied as economic inputs to stochastic projection models of insurance portfolios or pension funds for short-term asset and liability cash flow forecasting.

Earnings Management Constraints and Classification Shifting

AbstractPrior literature has investigated three forms of earnings management: real earnings management (REM), accruals earnings management (AEM) and classification shifting. Managers make trade‐off decisions among these methods based on the costs, constraints and timing of each strategy. This study investigates whether managers use classification shifting when their ability to use other forms of earnings management is constrained. We find that when REM is constrained by poor financial condition, high levels of institutional ownership and low industry market share, managers are more likely to use classification shifting. Further, we find that when AEM is constrained by low accounting system flexibility and the provision of a cash flow forecast, managers are more likely to use classification shifting. In addition, when we limit our sample to firms that are most likely to have manipulated earnings, we continue to find support for constraints of both REM and AEM leading to higher levels of classification shifting. We also find support for the hypothesis that the timing of each earnings management strategy influences managers’ trade‐off decision. Our results indicate that managers use classification shifting as substitute form of earnings management for both AEM and REM.

Analyst cash flow forecasts and pricing of accruals

This paper investigates how analyst cash flow forecasts affect investors' valuation of accounting accruals. We find that the strength of the accrual anomaly documented in Sloan (1996) is weaker for firms with analyst cash flow forecasts, after controlling for idiosyncratic risk, transaction costs and firm characteristics associated with the issuance of cash flow forecasts. We further show that this reduction in mispricing of accounting accruals is at least partially attributed to the improved ability of investors to price earnings manipulations imbedded in accruals. We investigate several non-mutually exclusive alternative explanations for this improvement in investors' ability and demonstrate that the increased investor attention and the improved accuracy of analyst earnings forecasts both contribute to the mitigation of the accrual anomaly.