The predictability of the market return and dividend growth is addressed in an equilibrium model with two regimes. A state variable that drives the conditional means of the aggregate consumption and dividend growth rates follows different time-series processes in the two regimes. In linear predictive regressions over 1930-2009, the market return is predictable by the price-dividend ratio with R2 11.7% if the probability of being in the first regime exceeds 50%; and dividend growth is predictable by the price-dividend ratio with R2 28.3% if the probability of being in the second regime exceeds 50%. The model-implied state variables perform significantly better at predicting the equity, size, and value premia, the aggregate consumption and dividend growth rates, and the variance of the market return than linear regressions with the market price-dividend ratio and risk free rate as predictive variables.
The consumption growth data strongly favor a two-regime specification. The high volatility, low growth regime is associated with deep recessions: the Great Depression, the recession of 1937-1938, the post-war recession of 1945, and the most recent financial crisis. I develop parsimonious models in which (i) consumption and dividend growth follow regime-switching dynamics, (ii) the regime characteristics are consistent with the empirical evidence from the consumption growth data, and (iii) the risks associated with regime shifts are priced in asset markets. The models explain major regime-dependent asset market phenomena. Regime-shift risk exhibits the dominant influence on asset prices: It generates a high equity premium, and also induces time-varying risk premiums and explains the return predictability.
This paper links variation in the predictive regressions for stock returns, dividend growth and consumption growth to economic and market factors. The nature of these links can reveal whether movement in asset prices occurs primarily through the discount rate (risk-free rate or risk premium) or cash flow (economic conditions) channel, while they also help explain the mixed results for predictability reported in the literature. Variation is examined through cross-sectional regressions across fifteen markets and over time using rolling regressions. The cross-sectional and time-varying parameters are regressed against output growth, interest rates and inflation as well as market variables using fixed effects panel as well as both OLS and logit approaches. Panel and time-series predictive regressions based on two approaches that seek to identify periods of high expected returns (high risk premium) are also considered. The key implication for asset pricing is that although movement occurs through both channels, stock return predictability is more dominated by the discount rate channel and consumption growth predictability more so by the cash flow channel. Intuitively, such a difference may arise as investors and households rebalance their asset holdings and consumption at different speeds. There is also some evidence of money illusion through the inflation variable.
Using a state-space model, this paper examines time-variation in the predictive regressions for stock returns, dividend growth and consumption growth. Moreover, we linked time-variation explicitly to movements in economic factors that can account for risk and cash flow. Results support the view that stock return predictability is enhanced when risk is high (negative growth, higher volatility and positive growth/return covariance). In contrast, dividend growth and consumption growth predictability is enhanced during economic expansions. These results are supported by sub-sample analysis and a VAR approach. Furthermore, these latter exercises may uncover differences in the stock return predictability relationship when viewed over different time horizons. Overall, the paper contributes to the literature by highlighting the different nature of returns predictability, which arises largely through the risk channel and dividend and consumption growth predictability, which arise through the cash flow channel.
Identifying economic regimes is useful in a world of time-varying risk premia. We apply regime switching models to common factors proxying for the macroeconomic regime and show that the ensuing regime factor is relevant in forecasting the equity risk premium. Moreover, the relevance of this regime factor is preserved in the presence of fundamental variables and technical indicators which are known to predict equity risk premia. Based on multiple predictive regressions and pooled forecasts, the macroeconomic regime factor is deemed complementary relative to the fundamental and technical information sets. Finally, these forecasts exhibit significant out-of-sample predictability that ultimately translates into considerable utility gains in a mean-variance portfolio strategy.
The 12 articles in this second of two parts condense recent advances on investment vehicles, performance measurement and evaluation, and risk management into a coherent springboard for future research. Written by world leaders in asset pricing research, they present scholarship about the 2008 financial crisis in contexts that highlight both continuity and divergence in research. For those who seek authoritative perspectives and important details, this volume shows how the boundaries of asset pricing have expanded and at the same time have grown sharper and more inclusive. Offers analyses by top scholars of recent asset pricing scholarship Explains how the 2008 financial crises affected theoretical and empirical research Covers core and newly developing fields
This two-volume set of 23 articles authoritatively describes recent scholarship in corporate finance and asset pricing. Volume 1 concentrates on corporate finance, encompassing topics such as financial innovation and securitization, dynamic security design, and family firms. Volume 2 focuses on asset pricing with articles on market liquidity, credit derivatives, and asset pricing theory, among others. Both volumes present scholarship about the 2008 financial crisis in contexts that highlight both continuity and divergence in research. For those who seek insightful perspectives and important details, they demonstrate how corporate finance studies have interpreted recent events and incorporated their lessons. Covers core and newly-developing fields Explains how the 2008 financial crises affected theoretical and empirical research Exposes readers to a wide range of subjects described and analyzed by the best scholars
In this remarkable stock market study, one of Wall Street’s best known market analysts reveals a new technical tool he developed for gauging the pulse of the trading cycle. Called the On Balance Volume Theory, this tool tends to fill in some of the conspicuous voids in the famous Dow Theory—especially the lack of discussion and use of stock volume figures. As straightforward as a set of bridge rules, on-balance volume (OBV) denotes each buy and sell signal so that a trader can follow them without his own emotions tending to lead him astray—emotions causing most of the market misjudgements that take place. The Granville OBV method is essentially scientific, has a high degree of accuracy and has many automatic features. The reader of this book will be introduced to a method whereby he may benefit by the earlier movements of volume over price—the “early warning” radar of volume buy and sell signals.
This collection of original articles—8 years in the making—shines a bright light on recent advances in financial econometrics. From a survey of mathematical and statistical tools for understanding nonlinear Markov processes to an exploration of the time-series evolution of the risk-return tradeoff for stock market investment, noted scholars Yacine Aït-Sahalia and Lars Peter Hansen benchmark the current state of knowledge while contributors build a framework for its growth. Whether in the presence of statistical uncertainty or the proven advantages and limitations of value at risk models, readers will discover that they can set few constraints on the value of this long-awaited volume. Presents a broad survey of current research—from local characterizations of the Markov process dynamics to financial market trading activity Contributors include Nobel Laureate Robert Engle and leading econometricians Offers a clarity of method and explanation unavailable in other financial econometrics collections
Academic finance has had a remarkable impact on many financial services. Yet long-term investors have received curiously little guidance from academic financial economists. Mean-variance analysis, developed almost fifty years ago, has provided a basic paradigm for portfolio choice. This approach usefully emphasizes the ability of diversification to reduce risk, but it ignores several critically important factors. Most notably, the analysis is static; it assumes that investors care only about risks to wealth one period ahead. However, many investors—-both individuals and institutions such as charitable foundations or universities—-seek to finance a stream of consumption over a long lifetime. In addition, mean-variance analysis treats financial wealth in isolation from income. Long-term investors typically receive a stream of income and use it, along with financial wealth, to support their consumption. At the theoretical level, it is well understood that the solution to a long-term portfolio choice problem can be very different from the solution to a short-term problem. Long-term investors care about intertemporal shocks to investment opportunities and labor income as well as shocks to wealth itself, and they may use financial assets to hedge their intertemporal risks. This should be important in practice because there is a great deal of empirical evidence that investment opportunities—-both interest rates and risk premia on bonds and stocks—-vary through time. Yet this insight has had little influence on investment practice because it is hard to solve for optimal portfolios in intertemporal models. This book seeks to develop the intertemporal approach into an empirical paradigm that can compete with the standard mean-variance analysis. The book shows that long-term inflation-indexed bonds are the riskless asset for long-term investors, it explains the conditions under which stocks are safer assets for long-term than for short-term investors, and it shows how labor income influences portfolio choice. These results shed new light on the rules of thumb used by financial planners. The book explains recent advances in both analytical and numerical methods, and shows how they can be used to understand the portfolio choice problems of long-term investors.
