Prediction of Operating Cash Flows: Further Evidence from Australia

This paper examines empirically the relative abilities of current operating cash flows (hereafter OCF) and earnings in predicting future operating cash flows in Australia. It extends prior Australian research on cash flow prediction ( Percy and Stokes 1992 ; Clinch, Sidhu and Sing 2002 ; Farshadfar, Ng and Brimble 2009 ) by examining future cash flow predictions for one‐, two‐ and three‐year‐ahead forecast horizons; incorporating additional contextual variables likely to affect the predictive association between current cash flows or earnings and future cash flows; and comparing cross‐sectional versus time series‐based prediction models to ascertain the relative superiority of one approach over the other. Regression results reveal that the cash flow‐based models are more accurate in predicting future operating cash flows than earnings‐based models. This result, however, is moderated by firm‐specific contextual factors like firm size, negative versus positive cash flow pattern, cash flow variability and firm operating cycle. Finally, a comparison between cross‐sectional and time series approaches reveals that the cross‐sectional model outperforms the time series model for both the operating cash flows and earnings models in most of the forecast years.     

New estimates of the cost of capital for pharmaceutical firms

Academic researchers, as well as pharmaceutical firms themselves, often use the Capital Asset Pricing Model (CAPM) to estimate a firm's cost of capital. But the CAPM implicitly assumes that cash flows follow a random walk. This assumption is inconsistent with our finding that large U.S.-based pharmaceutical firms' cash flow growth rates display either momentum or mean-reversion. We show that growth rate momentum implies: (1) the systematic risk of a project increases monotonically with time to maturity of the cash flows; and (2) longer duration projects require a higher cost of capital. One of the practical implications of our results is that the traditional CAPM underestimates the cost of capital for some pharmaceutical firms by as much as 2.8%. These findings are quite relevant for the policy debate about the high rates of return earned by pharmaceutical companies, which some claim are pure rents and are not necessary to attract investors. Our theoretical and empirical analysis shows that high returns are often required to compensate for the higher systematic risk of long-duration pharmaceutical cash flows.     

Feedback and the success of irrational investors

We provide a model in which irrational investors trade based upon considerations that have no inherent connection to fundamentals. However, trading activity affects market prices, and because of feedback from security prices to cash flows, the irrational trades influence underlying cash flows. As a result, irrational investors can, in some situations, earn abnormal (i.e., risk-adjusted) profits that can exceed the abnormal profits of rational informed investors. Although the trading of irrational investors cause prices to deviate from fundamental values, stock prices follow a random walk.     

VALUATION AND RISK-ADJUSTED DISCOUNT RATES

There is a continuing controversy as to whether the use of a constant risk adjusted discount rate in capital budgeting decisions implies that the risk of the cash flows increases over time. This paper shows that valuation using these discount rates implies an increasing premium for risk over time but that the increasing premium is due to the net impact of the uncertainty in the cash flow; uncertainty in future market expectations of the cash flow; and changes in the market price of risk. The risk of the cash flow itself need not be increasing over time.     

The information content of security prices

The study derives a relationship between prices changes and earnings changes by expanding the information upon which earnings expectations are conditioned to include data other than prior earnings history. In particular, price is used as a surrogate for additional information available to market participants. This relationship provides an interpretation of the contemporaneous association between price changes and earnings changes previously observed by Ball and Brown (1968) and Beaver, Clarke and Wright (1979), among others. It also provides a basis for inferring from prices the earnings process and the expected future earnings as perceived by market participants. In doing so, it inverts the familiar price-earnings relationship and uses price as a predictor of earnings. The study differs from previous research which has examined the time series behavior of earnings based solely on previous earnings realizations. This approach can potentially lead to earnings forecasting models that are more accurate than the random walk with a drift that has been robust against challengers. In particular, the evidence indicates that security prices behave as if earnings are perceived to be dramatically different from a simple random walk process. Preliminary evidence also indicates that price-based forecasting models are more accurate than the random walk with a drift model.     

Accruals,cash flows,and aggregate stock returns

This paper examines whether the firm-level accrual and cash flow effects extend to the aggregate stock market. In sharp contrast to previous firm-level findings, aggregate accruals is a strong positive time series predictor of aggregate stock returns, and cash flows is a negative predictor. In addition, innovations in accruals are negatively contemporaneously correlated with aggregate returns, and innovations in cash flows are positively correlated with returns. These findings suggest that innovations in accruals and cash flows contain information about changes in discount rates, or that firms manage earnings in response to marketwide undervaluation.     

Risk-adjusted discount rates and capital budgeting under uncertainty

This paper is concerned with the valuation of multiperiod cash flows in a world where prices are determined according to the Sharpe-Lintner-Black model of capital market equilibrium. We find that the current market value of any future net cash flow is the current expected value of the flow discounted at risk-adjusted discount rates for each of the periods until the flow is realized. The discount rates are known and non-stochastic, but the rates for the different periods preceding the realization of a cash flow need not to be the same, and the rates relevant for a given period can differ across cash flows. The risk adjustments in the discount rates arise because of uncertainties about reassessments through time of the expected value of a flow and the relationships between these reassessments and the corresponding reassessments of the expected cash flows of all firms.     

Consumption, Dividends, and the Cross Section of Equity Returns

We show that aggregate consumption risks embodied in cash flows can account for the puzzling differences in risk premia across book‐to‐market, momentum, and size‐sorted portfolios. The dynamics of aggregate consumption and cash flow growth rates, modeled as a vector autoregression, are used to measure the consumption beta of discounted cash flows. Differences in these cash flow betas account for more than 60% of the cross‐sectional variation in risk premia. The market price for risk in cash flows is highly significant. We argue that cash flow risk is important for interpreting differences in risk compensation across assets.     

The CBD Mortality Indexes: Modeling and Applications

Most extrapolative stochastic mortality models are constructed in a similar manner. Specifically, when they are fitted to historical data, one or more series of time-varying parameters are identified. By extrapolating these parameters to the future, we can obtain a forecast of death probabilities and consequently cash flows arising from life contingent liabilities. In this article, we first argue that, among various time-varying model parameters, those encompassed in the Cairns-Blake-Dowd (CBD) model (also known as Model M5) are most suitably used as indexes to indicate levels of longevity risk at different time points. We then investigate how these indexes can be jointly modeled with a more general class of multivariate time-series models, instead of a simple random walk that takes no account of cross-correlations. Finally, we study the joint prediction region for the mortality indexes. Such a region, as we demonstrate, can serve as a graphical longevity risk metric, allowing practitioners to compare the longevity risk exposures of different portfolios readily.     

An examination of causality and predictability between Australian domestic and offshore interest rates

This paper studies the causality and predictability between Australian domestic and offshore short term interest rates in both the first and second moments during the period 1987 to 1996. Causality flow is observed to be stronger from the domestic to the offshore market in the earlier sub periods but characterised by significant two-way causality flow in the latter sub-periods. Volatility tests show that the volatility in one market spills over to the other market simultaneously, which is consistent with Australian markets being well integrated with global markets. The predictability across the two markets in the first moments is examined through an error correction model, whose forecasting performance is assessed relative to a benchmark random walk model. To test the predictability of volatility, four different models are compared: A GARCH model, A GARCH model incorporating contemporaneous spillover effects, a GARCH model with lagged spillover effects, and a benchmark random walk model. Results indicate that the error correction model and the GARCH model with contemporaneous volatility spillover are the superior models for forecasting changes in interest rates and for forecasting volatility, respectively.     

The Incremental Information Content of Accruals: Evidence Based on the Exponential Smoothing of Levels and Trends in Pre-Tax Earnings, Funds Flow and Cash Flow

By arranging the accrual accounting identity as a hierarchy of market response models, this paper investigates whether current and noncurrent accruals have incremental information content beyond earnings. The results indicate that the increase in explanatory power attributable to funds flow and cash flow disclosure can be improved upon by estimating the surprises in reported numbers by exponentially weighting prior values. The unexpected information simplifies to the weighted sum of deviations from the estimated level and estimated trend. Further improvements are obtained by allowing components of the error to vary with time and by company in a non-autoregressive, homoscedastic pooling scheme which takes account of the joint presence of time series disturbance and cross sectional disturbance.     

Stock returns,dividend yield,and book-to-market ratio

A dividend yield model has been widely used in previous research that relates stock market valuations to cash flow fundamentals. Given controversies about using dividends as a proxy for cash flows, a loglinear book-to-market model has recently been proposed. However, these models rely on the assumption that dividend yield and book-to-market ratio are both stationary, and empirical evidence for this is, at best, mixed. We develop a new model, the loglinear cointegration model, that explains future profitability and excess stock returns in terms of a linear combination of log book-to-market ratio and log dividend yield. The loglinear cointegration model performs better than the log dividend yield model and the log book-to-market model in terms of cross-equation restriction tests and forecasting performance comparisons. The superior performance of the loglinear cointegration model suggests that the linear combination may be a better indicator of intrinsic fundamentals than the dividend yield or the book-to-market ratio separately.     

Accruals, Cash Flows and the Post‐Earnings‐Announcement Drift

Abstract:   Several prior studies have shown that cash flows have significantly greater impact on stock prices than accruals. We examine the implications of these findings for the post‐earnings‐announcement‐drift anomaly. We argue that, if investors under‐react to earnings news, then the larger price impact of cash flows causes the cash flow component of earnings news to predict future returns better than the accruals component. Consistent with this argument, we show that unexpected cash flows are more positively related to future returns, than are unexpected accruals. Also, unexpected cash flows are found to predict future returns above and beyond that predicted by earnings surprises. Finally, we show that a strategy that decomposes earnings news into its components significantly outperforms strategies based on earnings news alone. The results support under‐reaction explanations for the drift.     

Valuation of Corporate Innovation and the Pricing of Risk in the Biopharmaceutical Industry: The Case of Gilead

Much of a firm's market value derives from expected future growth value rather than from the value of current operations or assets in place. Pharmaceutical companies are good examples of firms where much market value comes from expectations about drugs still in the development “pipeline.” Using a new osteoporosis drug being developed by Gilead Sciences, Inc., the author combines discounted cash flow methods values and real option models to value it. Alone, discounted cash flow (DCF) calculations are vulnerable to the assumptions of growth, cost of capital, and cash flows. But by integrating the real options approach with the DCF technique, one can value a new product in the highly regulated, risky and research‐intensive Biopharmaceutical industry. This article shows how to value a Biopharmaceutical product, tracked from discovery to market launch in a step‐by‐step manner. Improving over early real option models, this framework explicitly captures competition, speed of innovation, risk, financing need, the size of the market potential in valuing corporate innovation using a firm‐specific measure of risk and the industry‐wide value of growth operating cash flows. This framework shows how the risk of corporate innovation, which is not fully captured by the standard valuation models, is priced into the value of a firm's growth opportunity. The DCF approach permits top‐down estimation of the size of the industry‐wide growth opportunity that competing firms must race to capture, while the contingency‐claims technique allows bottom‐up incorporation of the firm's successful R&D investment and the timing of introduction of the new product to market. It also specifically prices the risk of innovation by modeling its two components: the consumer validation of technology and the expert validation of technology. Overall, it estimates the value contribution per share of a new product for the firm.     

Expected Accrual Models: The Impact of Operating Cash Flows and Reversals of Accruals

This paper augments the Jones (1991) model with operating cash flows and lagged accruals to evaluate the impact of (1) the negative association between accruals and concurrent cash flows, (2) the positive association between accruals and lagged cash flows, and (3) the reversal of accruals. I find that operating cash flows greatly improve the explanatory and predictive power of the Jones model; but, lagged accruals do not. A market test of the expected and unexpected components of accruals indicates that unexpected accruals are on average informative with respect to concurrent stock returns; however, the market does not fully understand the implications of accruals anticipated at the beginning of the return period.This paper has benefited from helpful comments and suggestions from Tae Hee Choi, In-Kyu Moon, and two anonymous reviewers on earlier versions of this paper. The author gratefully acknowledges the financial support from the Queens School of Business.     

What Moves Investment Growth?

We use accounting identities to decompose unexpected changes in investment growth into surprises to current cash‐flow growth and stock returns, and revisions of expectations about future cash‐flow growth and future discount rates. Using a vector autoregressive model we find that current cash‐flow surprises account for the largest element of the variance decomposition. Investment growth and current cash‐flow surprises are negatively correlated with news about future cash‐flow growth, which can be expected from persistent productivity shocks and decreasing returns to scale. We find little evidence of a discount rate channel for investment since return terms are small and have unintuitive signs.     

Understanding Stock Price Volatility: The Role of Earnings

In an efficient capital market, asset prices vary when investors change their expectations about cash flows, discount rates, or both. Using dividends to measure cash flows, previous research shows that the aggregate dividend‐price ratio varies due to changes in expected discount rates (returns) rather than expected cash flows. In contrast, using accounting earnings instead of dividends as a measure of cash flows, this paper shows that as much as 70% of the variation in the dividend‐price ratio can be explained by changes in expected earnings. Moreover, the paper documents a significant negative correlation between expected returns and expected earnings, suggesting that variations in a common factor to both may generate significant price volatility. The results are consistent with the dividend‐policy irrelevance hypothesis.     

What Drives Anomaly Returns?

We decompose the returns of five well-known anomalies into cash flow and discount rate news. Common patterns emerge across the five factor portfolios and their mean-variance efficient (MVE) combination. Whereas discount rate news predominates in market returns, systematic cash flow news drives the returns of anomaly portfolios and their MVE combination with the market portfolio. Anomaly cash flow and discount rate shocks are largely uncorrelated with market cash flow and discount rate shocks and with business cycle fluctuations. These rich empirical patterns restrict the joint dynamics of firm cash flows and the pricing kernel, thereby informing models of stocks' expected returns.     

Stockpiling cash when it takes time to build: Exploring price differentials in a commodity boom

Some projects take time to build or are slow to yield cash flows. This may impact the dynamics of investment and liquidity management, although few studies test their financial implications. We exploit the peculiar advantages of copper mines as a laboratory to identify cash-flow sensitivities. In this context, investment decisions depend on the expectations of the long run price of the commodity, while the spread between the spot price and this long run expectations shifts current cash-flows. For this study we compiled a sample of copper firms between 2002 and 2012. We do not find significant effects of cash flow on current capital expenditures, but we do observe a systematic cash flow sensitivity of cash holdings, meaning that some of these transitory earnings are retained as liquidity. This cash stockpiling is stronger among financially constrained firms. In a context of time-to-build, our findings support financial theories emphasizing the salience of cash as buffer stock for liquidity in preparation for future investment opportunities.