Currency crisis and the forward discount bias: Evidence from emerging economies under breaks

This paper investigates the effects of two financial crises (the 1997 Asian currency crisis and the 2000 Turkish financial crisis) on the forward discount bias in 14 emerging-market economies using a robust two-stage procedure. This unique sample of less researched currencies displays: (i) high persistence in forward discount equations; and (ii) varying variance ratios between changes in exchange rates and the forward premium. The findings provide new insights into the forward discount puzzle: financial crises exert considerable power on the forward discount bias and uphold the forward rate unbiasedness hypothesis (FRUH) by reverting the negative sign into positive.     

The Importance of Cash-Flow News for Financially Distressed Firms

Previous studies have shown that stock prices are moved primarily by news about discount rates (expected returns). I argue that when a firm experiences financial distress, news about cashflows becomes more dominant in driving its stock returns. Applying Campbell's (1991) variance decomposition framework to financially distressed firms supports this argument. Furthermore, I find that more bankruptcies occur after negative shocks to expected cashflows than after positive shocks to discount rates; and that stock prices of distressed firms are less sensitive than those of sound firms to changes in equity risk.     

Valuation Ratios and Stock Return Predictability in South Africa: Is It There?

Using monthly South African data for January 1990 through October 2009, this paper, to the best of our knowledge, is the first to examine the predictability of real stock return based on valuation ratios, namely, price-dividend and price-earnings ratios. We cannot detect either short-horizon or long-horizon predictability; that is, the hypothesis that the current value of a valuation ratio is uncorrelated with future stock price changes cannot be rejected at both short and long horizons based on bootstrapped critical values constructed from linear representations of the data. We find, via Monte Carlo simulations, that the power to detect predictability in finite samples tends to decrease at long horizons in a linear framework. Although Monte Carlo simulations applied to exponential smooth-transition autoregressive models of the price-dividend and price-earnings ratios show increased power, the ability of the nonlinear framework in explaining the pattern of stock return predictability in the data does not show any promise at either short or long horizons, just as in the linear predictive regressions.     

Two Trees

We solve a model with two i.i.d. Lucas trees. Although the correspondingone-tree model produces a constant price-dividend ratio andi.i.d. returns, the two-tree model produces interesting asset-pricingdynamics. Investors want to rebalance their portfolios afterany change in value. Because the size of the trees is fixed,prices must adjust to offset this desire. As a result, expectedreturns, excess returns, and return volatility all vary throughtime. Returns display serial correlation and are predictablefrom price-dividend ratios. Return volatility differs from cash-flowvolatility, and return shocks can occur without news about cashflows.     

Commentary: Discount Rates in Disarray – Evidence on Flawed Goodwill Impairment Testing

Carlin and Finch (2009) compare the reported goodwill impairment discount rates to their own ‘independent’ estimate for a sample of 105 Australian firms. On the basis of this comparison they claim (but do not show) that the discretion in determining the discount rate ‘could be used opportunistically’ and ‘fundamental questions must be asked about the quality of reported earnings … produced in conformity with the IFRS regime’. This commentary points out that the research design does not permit the assessment of either of these claims.     

The dividend-price ratio and expectations of future dividends and discount factors

A dividend-ratio model is introduced here that makes the logof the dividend-price ratio on a stock linear in optimally forecastfuture one-period real discount rates and future one-periodgrowth rates of real dividends. If ex post discount rates areobservable, this model can be tested by using vector autoregressivemethods. Four versions of the linearized model, differing inthe measure of discount rates, are tested for U.S. time series1871-1986 and 1926-1986: a version that imposes constant realdiscount rates, and versions that measure discount rates fromreal interest rate data, aggregate real consumption data, andreturn variance data. The results yield a metric to judge therelative importance of real dividend growth, measured real discountrates, and unexplained factors in determining the dividend-priceratio.     

Accounting‐based Risk Management and the Capital Asset Pricing Model: An Empirical Comparison

Accounting‐based risk management (ABRM) is a theoretically consistent and practical tool for calculating the cost of capital from underlying financial ratios. In this paper, a sample of ABRM‐generated discount factors is used to generate risk‐adjusted returns, which are compared to CAPM equivalent discount factors. In view of the debates about CAPM's validity, alternative models, the nature and scale of the equity risk premium, and the importance of discount rates in capital budgeting and asset valuation, ABRM's characteristics and resulting discount rates offer a potentially useful alternative. Results suggest that although average discount rates are comparable, their cross‐sectional distributions are dissimilar, so that investors in an average risky firm are overcompensated for systematic risk when using CAPM discount rates, because CAPM discount factors overestimate risk arising from fixed costs in most firms.     

Why Is Long‐Horizon Equity Less Risky? A Duration‐Based Explanation of the Value Premium

We propose a dynamic risk‐based model that captures the value premium. Firms are modeled as long‐lived assets distinguished by the timing of cash flows. The stochastic discount factor is specified so that shocks to aggregate dividends are priced, but shocks to the discount rate are not. The model implies that growth firms covary more with the discount rate than do value firms, which covary more with cash flows. When calibrated to explain aggregate stock market behavior, the model accounts for the observed value premium, the high Sharpe ratios on value firms, and the poor performance of the CAPM.     

Discount-Rate Risk in Private Equity: Evidence from Secondary Market Transactions

Measures of private equity (PE) performance based on cash flows do not account for a discount-rate risk premium that is a component of the capital asset pricing model (CAPM) alpha. We create secondary market PE indices and find that PE discount rates vary considerably. Net asset values are too smooth because they fail to reflect variation in discount rates. Although the CAPM alpha for our index is zero, the generalized public market equivalent based on cash flows is large and positive. We obtain similar results for a set of synthetic funds that invest in small cap stocks. Ignoring variation in PE discount rates can lead to a misallocation of capital.     

Stock Return Predictability and The Role of Monetary Policy

This article examines whether shifts in the stance of monetary policy can account for the observed predictability in excess stock returns. Using long-horizon regressions and short-horizon vector autoregressions, the article concludes that monetary policy variables are significant predictors of future returns, although they cannot fully account for observed stock return predictability. I undertake variance decompositions to investigate how monetary policy affects the individual components of excess returns (risk-free discount rates, risk premia, or cash flows).     

Predicting dividends in log-linear present value models

In a present value model, high dividend yields imply that either future dividend growth must be low, or future discount rates must be high, or both. While previous studies have largely focused on the predictability of future returns from dividend yields, dividend yields also strongly predict future dividends, and the predictability of dividend growth is much stronger than the predictability of returns at a one-year horizon. Inference from annual regressions over the 1927–2000 sample imputes over 85% of the variation of log dividend yields to variations in dividend growth. Point estimates of the predictability of both dividend growth and discount rates are stronger when the 1990–2000 decade is omitted.     

Fluctuations in the UK equity market: what drives stock returns?

Present value parameters from a state-space model are estimated for the UK FT All-Share Index. The estimated parameters are used to construct a time series of expected future returns and expected future values of dividend growth, both of which are found to be time-varying with persistent components. Variations in the price-dividend ratio appear to be driven primarily by the variance in expected returns. A comparison with the findings from a present value-constrained vector autoregression model indicates that the latter forecasts future realized returns and dividend growth better than the series constructed using a state-space approach. Furthermore, when the model is estimated for monthly and quarterly data, expected dividend growth is found to be more persistent.     

Predicting dividends in log-linear present value models

In a present value model, high dividend yields imply that either future dividend growth must be low, or future discount rates must be high, or both. While previous studies have largely focused on the predictability of future returns from dividend yields, dividend yields also strongly predict future dividends, and the predictability of dividend growth is much stronger than the predictability of returns at a one-year horizon. Inference from annual regressions over the 1927–2000 sample imputes over 85% of the variation of log dividend yields to variations in dividend growth. Point estimates of the predictability of both dividend growth and discount rates are stronger when the 1990–2000 decade is omitted.     

A multivariate Markov chain stock model

ABSTRACT

We propose a dividend stock valuation model where multiple dividend growth series and their dependencies are modelled using a multivariate Markov chain. Our model advances existing Markov chain stock models. First, we determine assumptions that guarantee the finiteness of the price and risk as well as the fulfilment of transversality conditions. Then, we compute the first- and second-order price-dividend ratios by solving corresponding linear systems of equations and show that a different price-dividend ratio is attached to each combination of states of the dividend growth process of each stock. Subsequently, we provide a formula for the computation of the variances and covariances between stocks in a portfolio. Finally, we apply the theoretical model to the dividend series of three US stocks and perform comparisons with existing models. The results could also be applied for actuarial purposes as a general stochastic investment model and for calculating the initial endowment to fund a portfolio of dependent perpetuities.     

Risk-Adjusted Discount Rates Revisited

This paper shows that small changes in even slightly negative discount rates can cause substantial changes in present value. Small changes in the discount rate, which may seem appropriate, turn out to have huge effects on present value and are not economically justified. This paper also points out problems associated with large negative discount rates. It is shown that the present value can become discontinuous as the discount rate is lowered and that the present value of the risky cash outflows becomes erratic depending on whether the outflow is discounted an even or odd number of periods.     

International risk sharing is better than you think, or exchange rates are too smooth

Exchange rates depreciate by the difference between domestic and foreign marginal utility growth or discount factors. Exchange rates vary a lot, as much as 15% per year. However, equity premia imply that marginal utility growth varies much more, by at least 50% per year. Therefore, marginal utility growth must be highly correlated across countries: international risk sharing is better than you think. Conversely, if risks really are not shared internationally, exchange rates should vary more than they do: exchange rates are too smooth. We calculate an index of international risk sharing that formalizes this intuition. We treat carefully the realistic case of incomplete capital markets. We contrast our estimates with the poor risk sharing suggested by consumption data and home-bias portfolio calculations.     

The stochastic properties of term structure movements

The aim of this paper is to identify a stationary statistical model for Treasury bill discount changes. We find that the sample variance of discount changes are non-stationary over short differencing intervals but stabilize as the intervals increase to quarterly or semi-annual periods. This result has important implications for pricing options and for analyzing the predictive properties of forward rates. We show that the stochastic process structure leads to a downward revision in estimates of forward rate predictive power.     

What's your real cost of capital?

In valuing any investment project or corporate acquisition, executives must decide what discount rate to use in their estimates of future cash flows. The traditional approach is to apply the capital asset pricing model (CAPM), which has remained fundamentally unchanged for 40 years. But the formula--in particular, its beta element--has long been a source of frustration. In fact, corporate executives and investment bankers routinely fudge their CAPM estimates, say the authors, because experience and intuition tell them the model produces inappropriate discount rates. CAPM has three main problems: First, beta is a measure of both a stock's correlation and its volatility; second, beta is based on historical data; and third, CAPM rates don't take into account the term of the investment. These factors together result in discount rates that defy common sense. As an alternative to CAPM and its beta element, the authors developed a forward-looking approach to calculating a company's cost of capital, the market-derived capital pricing model (MCPM). It does not incorporate any measure of historical stock-to-market correlation, relying instead on estimates of future volatility derived from the options market. This is helpful since investor expectations from the options market are built into a company's current stock price. Using GE as an example, the authors give step-by-step instructions for how to calculate discount rates with MCPM. They also offer evidence from a range of industries to show that MCPM's discount rates are more realistic--especially from the corporate investor's perspective--than are CAPM's.     

Portfolio performance of linear SDF models: an out-of-sample assessment

We evaluate linear stochastic discount factor models using an ex-post portfolio metric: the realized out-of-sample Sharpe ratio of mean–variance portfolios backed by alternative linear factor models. Using a sample of monthly US portfolio returns spanning the period 1968–2016, we find evidence that multifactor linear models have better empirical properties than the CAPM, not only when the cross-section of expected returns is evaluated in-sample, but also when they are used to inform one-month ahead portfolio selection. When we compare portfolios associated to multifactor models with mean–variance decisions implied by the single-factor CAPM, we document statistically significant differences in Sharpe ratios of up to 10 percent. Linear multifactor models that provide the best in-sample fit also yield the highest realized Sharpe ratios.