Risk, Return and Dividends

We characterize the joint dynamics of dividends, expected returns, stochastic volatility, and prices. In particular, with a given dividend process, one of the processes of the expected return, the stock volatility, or the price-dividend ratio fully determines the other two. For example, together with dividends, the stock volatility process fully determines the dynamics of the expected return and the price-dividend ratio. By parameterizing one or more of expected returns, volatility, or prices, common empirical specifications place strong, and sometimes counter-factual, restrictions on the dynamics of the other variables. Our relations are useful for understanding the risk-return trade-off, as well as characterizing the predictability of stock returns.

Do Demographic Changes Affect Risk Premiums? Evidence from International Data

We examine the link between equity risk premiums and demographic changes using a very long sample over the twentieth century for the US, Japan, UK, Germany and France, and a shorter sample covering the last third of the twentieth century for fifteen countries. We find that demographic variables significantly predict excess returns internationally. However, the demographic predictability found in the US by past studies for the average age of the population does not extend to other countries. Pooling international data, we find that, on average, faster growth in the fraction of retired persons significantly decreases risk premiums. This demographic predictability of risk premiums is strongest in countries with well-developed social security systems and lesser-developed financial markets.

How do Regimes Affect Asset Allocation?

International equity returns are characterized by episodes of high volatility and unusually high correlations coinciding with bear markets. We develop models of asset returns that match these patterns and use them in asset allocation. First, the presence of regimes with different correlations and expected returns is difficult to exploit within a framework focused on global equities. Nevertheless, for all-equity portfolios, a regime-switching strategy dominates static strategies out-of-sample. Second, substantial value is added when an investor chooses between cash, bonds and equity investments. When a persistent bear market hits, the investor switches primarily to cash. There are large market timing benefits because the bear market regimes tend to coincide with periods of relatively high interest rates.

Testing Conditional Factor Models

Using nonparametric techniques, we develop a methodology for estimating conditional alphas and betas and long-run alphas and betas, which are the averages of conditional alphas and betas, respectively, across time. The tests can be performed for a single asset or jointly across portfolios. The traditional Gibbons, Ross, and Shanken (1989) test arises as a special case of no time variation in the alphas and factor loadings and homoskedasticity. As applications of the methodology, we estimate conditional CAPM and multifactor models on book-to-market and momentum decile portfolios. We reject the null that long-run alphas are equal to zero even though there is substantial variation in the conditional factor loadings of these portfolios.

A No-Arbitrage Vector Autoregression of Term Structure Dynamics with Macroeconomic and Latent Variables

This paper describes the joint dynamics of bond yields and macroeconomic variables in a Vector Autoregression, where identifying restrictions are based on the absence of arbitrage. Using a term structure model with inflation and economic growth factors, we investigate how macro variables affect bond prices and the dynamics of the yield curve. The setup accommodates higher order autoregressive lags for the macro factors. The macro variables are augmented by traditional unobserved term structure factors. We find that the forecasting performance of a VAR improves when no-arbitrage restrictions are imposed. Models that incorporate macro factors forecast better than traditional term structure models with only unobservable factors. Variance decompositions show that macro factors explain up to 85% of the variation in bond yields. Macro factors primarily explain movements at the short end and middle of the yield curve while unobservable factors still account for most of the movement at the long end of the yield curve.

No-Arbitrage Taylor Rules

We estimate Taylor (1993) rules and identify monetary policy shocks using no-arbitrage pricing techniques. Long-term interest rates are risk-adjusted expected values of future short rates and thus provide strong over-identifying restrictions about the policy rule used by the Federal Reserve. The no-arbitrage framework also accommodates backward-looking and forward-looking Taylor rules. We find that inflation and output gap account for over half of the variation of time-varying excess bond returns and most of the movements in the term spread. Taylor rules estimated with no-arbitrage restrictions differ from Taylor rules estimated by OLS, and the resulting monetary policy shocks are somewhat less volatile than their OLS counterparts.

Downside Risk

Economists have long recognized that investors care differently about downside losses versus upside gains. Agents who place greater weight on downside risk demand additional compensation for holding stocks with high sensitivities to downside market movements. We show that the cross-section of stock returns reflects a premium for downside risk. Specifically, stocks that covary strongly with the market when the market declines have high average returns. We estimate that the downside risk premium is approximately 6% per annum. The reward for bearing downside risk is not simply compensation for regular market beta, nor is it explained by coskewness or liquidity risk, or size, book-to-market, and momentum characteristics.

Do demographic changes affect risk premiums? Evidence from international data

We examine the link between equity risk premiums and demographic changes using a very long sample over the whole twentieth century for the US, Japan, UK, Germany and France, and a shorter sample covering the last third of the twentieth century for fifteen countries. We find that demographic variables significantly predict excess returns internationally. However, the demographic predictability found in the US by past studies for the average age of the population does not extend to other countries. Pooling international data, we find that, on average, faster growth in the fraction of retired persons significantly decreases risk premiums. This demographic predictability of risk premiums is stronger for countries with well-developed social security systems and lesser-developed financial markets. JEL Classification: G12, G15, J10, P46demography, international predictability, Population aging, risk premiums, social security

Is IPO Underperformance a Peso Problem?

Recent studies suggest that the underperformance of IPOs in the post-1970 sample may be a small sample effect or %u201CPeso%u201D problem. That is, IPO underperformance may result from observing too few star performers ex-post than were expected ex-ante. We develop a model of IPO performance that captures this intuition by allowing returns to be drawn from mixtures of outstanding, benchmark, or poor performing states. We estimate the model under the null of no ex-ante average IPO underperformance and construct small sample distributions of various statistics measuring IPO relative performance. We find that small sample biases are extremely unlikely to account for the magnitude of the post-1970 IPO underperformance observed in data.

How to Discount Cashflows with Time-Varying Expected Returns

While many studies document that the market risk premium is predictable and that betas are not constant, the dividend discount model ignores time-varying risk premiums and betas. We develop a model to consistently value cashflows with changing risk-free rates, predictable risk premiums and conditional betas in the context of a conditional CAPM. Practical valuation is accomplished with an analytic term structure of discount rates, with different discount rates applied to expected cashflows at different horizons. Using constant discount rates can produce large mis-valuations, which, in portfolio data, are mostly driven at short horizons by market risk premiums and at long horizons by time-variation in risk-free rates and factor loadings.