Kenneth R. French

Common risk factors in the returns on stocks and bonds

This paper identities five common risk factors in the returns on stocks and bonds. There are three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity. There are two bond-market factors. related to maturity and default risks. Stock returns have shared variation due to the stock-market factors, and they are linked to bond returns through shared variation in the bond-market factors. Except for low-grade corporates. the bond-market factors capture the common variation in bond returns. Most important. the five factors seem to explain average returns on stocks and bonds.

Industry costs of equity

Abstract Estimates of the cost of equity for industries are imprecise. Standard errors of more than 3.0% per year are typical for both the CAPM and the three-factor model of Fama and French (1993). These large standard errors are the result of(i) uncertainty about true factor risk premiums and (ii) imp ecise estimates of the loadings of industries on the risk factors. Estimates of the cost of equity for firms and projects are surely even less precise.

Expected stock returns and volatility

This paper examines the relation between stock returns and stock market volatility. We find evidence that the expected market risk premium (the expected return on a stock portfolio minus the Treasury bill yield) is positively related to the predictable volatility of stock returns. There is also evidence that unexpected stock market returns are negatively related to the unexpected change in the volatility of stock returns. This negative relation provides indirect evidence of a positive relation between expected risk premiums and volatility.

Business conditions and expected returns on stocks and bonds

Abstract Expected returns on common stocks and long-term bonds contain a term or maturity premium that has a clear business-cycle pattern (low near peaks, high near troughs). Expected returns also contain a risk premium that is related to longer-term aspects of business conditions. The variation through time in this premium is stronger for low-grade bonds than for high-grade bonds and stronger for stocks than for bonds. The general message is that expected returns are lower when economic conditions are strong and higher when conditions are weak.

Dividend yields and expected stock returns

The power of dividend yields to forecast stock returns, measured by regression R2, increases with the return horizon. We offer a two-part explanation. (1) High autocorrelation causes the variance of expected returns to grow faster than the return horizon. (2) The growth of the variance of unexpected returns with the return horizon is attenuated by a discount-rate effect - shocks to expected returns generate opposite shocks to current prices. We estimate that, on average, the future price increases implied by higher expected returns are just offset by the decline in the current price. Thus, time-varying expected returns generate ‘temporary’ components of prices.

PERMANENT AND TEMPORARY COMPONENTS OF STOCK PRICES

A slowly mean-reverting component of stock prices tends to induce negative autocorrelation in returns. The autocorrelation is weak for the daily and weekly holding periods common in market efficiency tests but stronger for long-horizon returns. In tests for the 1926-85 period, large negative autocorrelations for return horizons beyond a year suggest that predictable price variation due to mean reversion accounts for large fractions of 3-5-year return variances. Predictable variation is estimated to be about 40 percent of 3-5-year return variances for portfolios of small firms. The percentage falls to around 25 percent for portfolios of large firms.

Testing Trade-Off and Pecking Order Predictions About Dividends and Debt

Confirming predictions shared by the tradeoff and pecking order models, more profitable firms and firms with fewer investments have higher dividend payouts. Confirming the pecking order model but contradicting the tradeoff model, more profitable firms are less levered. Firms with more investments have less market leverage, which is consistent with the tradeoff model and a complex pecking order model. Firms with more investments have lower long-term dividend payouts, but dividends do not vary to accommodate short-term variation in investment. As the pecking order model predicts, short-term variation in investment and earnings is mostly absorbed by debt. The finance literature offers two competing models of financing decisions. In the tradeoff model, firms identify their optimal leverage by weighing the costs and benefits of an additional dollar of debt. The benefits of debt include, for example, the tax deductibility of interest and the reduction of free cash flow problems. The costs of debt include potential bankruptcy costs and agency conflicts between stockholders and bondholders. At the leverage optimum, the benefit of the last dollar of debt just offsets the cost. The tradeoff model makes a similar prediction about dividends. Firms maximize value by selecting the dividend payout that equates the costs and benefits of the last dollar of dividends. Myers (1984) develops an alternative theory known as the pecking order model of financing decisions. The pecking order arises if the costs of issuing new securities overwhelm other costs and benefits of dividends and debt. The financing costs that produce pecking order behavior include the transaction costs associated with new issues and the costs that arise because of management’s superior information about the firm’s prospects and the value of its risky securities. Because of these costs, firms finance new investments first with retained earnings, then with safe debt, then with risky debt, and finally, under duress, with equity. As a result, variation in a firm’s leverage is driven not by the tradeoff model’s costs and benefits of debt, but rather by the firm’s net cash flows (cash earnings minus investment outlays). We test the dividend and leverage predictions of the tradeoff and pecking order models. Our menu is ambitious. We examine predictions about how long-term leverage and the dividend payout ratio vary across firms with the main driving variables proposed by the two models – profitability and investment opportunities. Moreover, to test predictions about the interdependence of long-term leverage and the dividend payout, we model dividends and leverage jointly. We test the tradeoff model’s prediction that leverage is mean-reverting. And we test pecking order predictions about how financing decisions respond to short-term variation in earnings and investment. To our knowledge, we are the first to test tradeoff and pecking order predictions about the dividend payout ratio, and we are the first to jointly model and test the interaction between the payout ratio and leverage. But one can argue that many of our leverage results just confirm previous evidence.

Disappearing dividends: changing firm characteristics or lower propensity to pay?

Abstract The proportion of firms paying cash dividends falls from 66.5% in 1978 to 20.8% in 1999, due in part to the changing characteristics of publicly traded firms. Fed by new listings, the population of publicly traded firms tilts increasingly toward small firms with low profitability and strong growth opportunities – characteristics typical of firms that have never paid dividends. More interesting, we also show that regardless of their characteristics, firms have become less likely to pay dividends. This lower propensity to pay is at least as important as changing characteristics in the declining incidence of dividend-paying firms.

Stock return variances: The arrival of information and the reaction of traders

Asset prices are much more volatile during exchange trading hours than during non-trading hours. This paper considers three explanations for this phenomenon: (1) volatility is caused by public information which is more likely to arrive during normal business hours; (2) volatility is caused by private information which affects prices when informed investors trade; and (3) volatility is caused by pricing errors that occur during trading. Although a significant fraction of the daily variance is caused by mispricing, the behavior of returns around exchange holidays suggests that private information is the principle factor behind high trading-time variances.

Stock returns and the weekend effect

Abstract This paper examines two alternative models of the process generating stock returns. Under the calendar time hypothesis, the process operates continuously and the expected return for Monday is three times the expected return for other days of the week. Under the trading time hypothesis, returns are generated only during active trading and the expected return is the same for each day of the week. During most of the period studied, from 1953 through 1977, the daily returns to the Standard and Poors composite portfolio are inconsistent with both models. Although the average return for the other four days of the week was positive, the average for Monday was significantly negative during each of five-year subperiods.