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PurposeThe study examines the influence of a firm's life cycle on the cash flow classification of Indian firms.Design/methodology/approachThe study employs Dickinson's (2011) cash flow patterns to classify firm years under various life-cycle stages. Cash flow classification is employed to measure a firm's classification shifting (CS) practices. The study includes Indian firms listed on the Bombay Stock Exchange during 2012–2020, an ordinary least squares regression model, a fixed-effect model and a panel corrected with standard error regression method.FindingsFirms face different opportunities and challenges at different stages of the firm's life cycle and therefore adopt cash flow CS. The results show that firms adopt cash flow CS during introduction, growth and decline stage of life cycle either to boost or to reduce operating cash flows.Originality/valueThis study is one of its kind to study the influence of a firm's life cycle on the cash flow classification of Indian firms.

PurposeThis paper aims to investigate the relationship between uncertainty and corporate cash holdings with the moderating role of political connections.Design/methodology/approachWe employ fixed effects estimation on a panel dataset of 669 Vietnamese listed firms over the 2010–2020 period, with one- and two-way standard error clustering. We conduct various robustness tests, including two-stage least squares/instrumental variable and generalized method of moments regressions, alternative cash holding measure, and additional controls for macroeconomic conditions and ownership types.FindingsThe effect of uncertainty on cash holdings is weakened for firms with political connections relative to those without the connections. Although general firms depend on cash flows to adjust their cash holding behavior when uncertainty increases, our findings suggest that politically connected firms do not rely on internal cash flows to accumulate cash when confronted high uncertainty.Practical implicationsOur findings on the role of political connections in moderating the relationship between cash holding and economic policy uncertainty have practical implications for policymaking. Since political connections serve as a buffer for a firm’s liquidity, firms may want to seek those connections, which can, in turn, lead to increasing informal costs and unfair business environment.Originality/valueThis is the first study investigating the role of political connections to the nexus of cash, cash flow and uncertainty, providing novel evidence regarding the less dependence on internal cash flows to save cash by politically connected firms. Second, the paper enriches the literature on the motives of cash holdings by proposing a modified agency view in the context of weak investor protection. Therefore, our findings strengthen the explanation for the positive effect of uncertainty on firms’ cash holdings in emerging markets.

This study aims to review empirical research concerning the impact of green certificates on property cash flows and values, particularly from professional property investors’ perspective. The study uses discounted cash flows (DCF), a widely used property valuation method in income-generating properties, as a methodological framework. In this study, over 70 peer-reviewed studies were identified, categorized, and analyzed in the DCF framework. The reviewed studies indicated that certificates might increase the rental income and decrease the operating expenses, vacancy, and risks of a property. Together with the brand value of certificates, these enhancements should lead to an increase in property value. The number of studies has grown rapidly during the 2010s. Lately, studies have developed from asset-level to portfolio-level examinations. Although the reviewed studies found certification to be beneficial, the range of reported benefits was wide, and over half of the studies concentrated on U.S. commercial real estate markets, with a strong focus on LEED and ENERGY STAR certificates. From a property valuation perspective, applying these results to other markets and certificates might be challenging. Property values that fully reflect the environmental performance of properties would be a key to motivate mainstream investors to adopt sustainable property features.

This study examines the role and utility of the Statement of Cash Flows in the credit decision-making process from the perspective of Bulgarian banks. The main purpose is to evaluate how banks use the Statement of Cash Flows to assess the creditworthiness and financial health of the enterprises. A survey of leading Bulgarian banks reveals differences in how they understand and use this information in credit analysis. The findings reveal that, although banks acknowledge the importance of the Statement of Cash Flow for assessing liquidity and risk, it is often overshadowed by other financial reports such as the Balance Sheet and Income Statement. Common issues identified include improper classification of cash flows and lack of clarity in the regulation of non-cash transactions, which hinders the full utility of the Statement of Cash Flows in the credit evaluation process. Although the Statement of Cash Flows is useful for evaluating credit risk, the research identifies limitations in its current use by banks. Recommendations to improve Cash flow statement structure and credit assessments using cash flow information are provided.

International Financial Reporting Standards (IFRS) allow managers flexibility in classifying interest paid, interest received, and dividends received within operating, investing, or financing activities within the statement of cash flows. In contrast, U.S. Generally Accepted Accounting Principles (GAAP) requires these items to be classified as operating cash flows (OCF). Studying IFRS-reporting firms in 13 European countries, we document firms’ cash-flow classification choices vary, with about 76, 60, and 57% of our sample classifying interest paid, interest received, and dividends received, respectively, in OCF. Reported OCF under IFRS tends to exceed what would be reported under U.S. GAAP. We find the main determinants of OCF-enhancing classification choices are capital market incentives and other firm characteristics, including greater likelihood of financial distress, higher leverage, and accessing equity markets more frequently. In analyzing the consequences of reporting flexibility, we find some evidence that the market’s assessment of the persistence of operating cash flows and accruals varies with the firm’s classification choices and the results of certain OCF prediction models are sensitive to classification choices.

We propose a new investor sentiment index that is aligned with the purpose of predicting the aggregate stock market. By eliminating a common noise component in sentiment proxies, the new index has much greater predictive power than existing sentiment indices have both in and out of sample, and the predictability becomes both statistically and economically significant. In addition, it outperforms well-recognized macroeconomic variables and can also predict cross-sectional stock returns sorted by industry, size, value, and momentum. The driving force of the predictive power appears to stem from investors' biased beliefs about future cash flows.

Motivated by recent FASB, IASB, and CFA Institute comments, we explore the predictive value of direct method cash flow disclosures. A primary stated purpose of the direct method is to better forecast future performance. To examine this purpose, we first document that direct method line items, such as cash received from customers, are not reliably estimable using income statements and either balance sheets or indirect method statements of cash flows. When these estimation (articulation) errors are included in cash flows and earnings forecasting models, forecasting performance significantly improves. In addition, employing a future ERC (FERC) methodology, we find evidence suggesting that market participants utilize direct method disclosures for their stated purpose: to better forecast future operating performance. After conducting several tests for self-selection concerns, we conclude that the direct method is valuable to investors when forecasting future cash flows and earnings.

Marketing affects customer behavior, and customer behavior in turn drives a firm's cash flows and, ultimately, valuation. In this sequence of relationships, a commonly overlooked factor by marketers is the volatility of customers' cash flows. This study links different recurring customer behaviors to the future level and volatility of a customer's cash flows. Empirical analyses of the large customer database of a Fortune 500 retailer reveal that a 1% desired change in the different types of recurring customer behaviors corresponds to a future quarterly 4.61% decrease in the cash flow volatility and $39.42 million increase in the future cash flow level of the firm. Furthermore, firm-initiated marketing is 1.9–3.2 times more effective at managing the future cash flow level and volatility when it is selectively targeted to customers with certain characteristics. Overall, the study enables marketers to manage different customer behaviors that influence customers' future cash flow level and volatility and ultimately quantify the impact of these behaviors on the shareholder value of the firm.

Academics, politicians, and journalists are often highly critical of U.S. firms for holding too much cash. Cash holdings are stockpiled free-cash flow and incur substantial opportunity costs from the perspectives of economics. However, behavioral theory highlights the benefits of cash holdings as fungible slack resources facilitating adaptive advantages. We use the countervailing forces embodied in these two theories to hypothesize and test a quadratic functional relationship of returns to cash measured by Tobin's q. We also build and test a related novel hypothesis of scale-dependent returns to cash based on the competitive strategy concept of strategic deterrence. Tests for both of these hypotheses are positive and show that returns to cash continue to increase far beyond transactional needs.

Cash flow prediction is important. It can help increase returns and improve the allocation of capital in healthy, mature firms as well as prevent fast-growing firms, or firms in distress, from running out of cash. In this paper, we predict accounts receivable cash flows employing methods applicable to companies with many customers and many transactions such as e-commerce companies, retailers, airlines and public transportation firms with sales in multiple regions and countries. We first discuss “classic” forecasting techniques such as ARIMA and Facebook's™ Prophet before moving on to neural networks with multi-layered perceptrons and, finally, long short-term memory networks, that are particularly useful for time series forecasting but were until now not used for cash flows. Our evaluation demonstrates this range of methods to be of increasing sophistication, flexibility and accuracy. We also introduce a new performance measure, interest opportunity cost, that incorporates interest rates and the cost of capital to optimize the models in a financially meaningful, money-saving, way.