The VIX,the variance premium and stock market volatility

We decompose the squared VIX index, derived from US S&P500 options prices, into the conditional variance of stock returns and the equity variance premium. We evaluate a plethora of state-of-the-art volatility forecasting models to produce an accurate measure of the conditional variance. We then examine the predictive power of the VIX and its two components for stock market returns, economic activity and financial instability. The variance premium predicts stock returns while the conditional stock market variance predicts economic activity and has a relatively higher predictive power for financial instability than does the variance premium.     

Market Integration and Investment Barriers in Emerging Equity Markets

This article develops a return-based measure of market integrationfor nineteen emerging equity markets. It then examines the relationbetween that measure, other return characteristics, and broadlydefined investment barriers. Although the analysis is exploratory,some clear conclusions emerge. First, global factors accountfor a small fraction of the time variation in expected returnsin most markets, and global predictability has declined overtime Second, the emerging markets exhibit differing degreesof market integration with the U.S. market, and the differencesare not necessarily associated with direct barriers to investment.Third, the most important de facto barriers to global equity-marketintegration are poor credit ratings, high and variable inflation,exchange rate controls, the lack of a high-quality regulatoryand accounting framework, the lack of sufficient country fundsor cross-listed securities, and the limited size of some stockmarkets.     

Risk,uncertainty and monetary policy

The VIX, the stock market option-based implied volatility, strongly co-moves with measures of the monetary policy stance. When decomposing the VIX into two components, a proxy for risk aversion and expected stock market volatility (“uncertainty”), we find that a lax monetary policy decreases both risk aversion and uncertainty, with the former effect being stronger. The result holds in a structural vector autoregressive framework, controlling for business cycle movements and using a variety of identification schemes for the vector autoregression in general and monetary policy shocks in particular. The effect of monetary policy on risk aversion is also apparent in regressions using high frequency data.     

Inflation and the stock market: Understanding the “Fed Model”

The so-called Fed model postulates that the dividend or earnings yield on stocks should equal the yield on nominal Treasury bonds, or at least that the two should be highly correlated. In US data there is indeed a strikingly high time series correlation between the yield on nominal bonds and the dividend yield on equities. This positive correlation is often attributed to the fact that both bond and equity yields comove strongly and positively with expected inflation. Contrary to some of the extant literature, we show that this effect is consistent with modern asset pricing theory incorporating uncertainty about real growth prospects and habit-based risk aversion. In the US, high expected inflation has tended to coincide with periods of heightened uncertainty about real economic growth and unusually high risk aversion, both of which rationally raise equity yields.     

Equity Market Liberalization in Emerging Markets

Equity market liberalizations, if effective, lead to important changes in both the financial and real sectors as the economy becomes integrated into world capital markets. The study of market integration is complicated because one can liberalize in many ways and many countries have taken different routes. To study the effectiveness of particular liberalization policies, the sequencing of liberalizations, and the impact on the real economy, systematic methods must be developed to date the liberalization of emerging equity markets. We provide a synthesis of the current methods and show the impact of liberalization on the real sector.     

Conditioning Information and Variance Bounds on Pricing Kernels

Gallant, Hansen, and Tauchen (1990) show how to use conditioninginformation optimally to construct a sharper unconditional variancebound (the GHT bound) on pricing kernels. The literature predominantlyresorts to a simple but suboptimal procedure that scales returnswith predictive instruments and computes standard bounds usingthe original and scaled returns. This article provides a formalbridge between the two approaches. We propose an optimally scaledbound that coincides with the GHT bound when the first and secondconditional moments are known. When these moments are misspecified,our optimally scaled bound yields a valid lower bound for thestandard deviation of pricing kernels, whereas the GHT bounddoes not. We illustrate the behavior of the bounds using a numberof linear and nonlinear models for consumption growth and bondand stock returns. We also illustrate how the optimally scaledbound can be used as a diagnostic for the specification of thefirst two conditional moments of asset returns.     

Do macro variables, asset markets, or surveys forecast inflation better?

Surveys do! We examine the forecasting power of four alternative methods of forecasting U.S. inflation out-of-sample: time-series ARIMA models; regressions using real activity measures motivated from the Phillips curve; term structure models that include linear, non-linear, and arbitrage-free specifications; and survey-based measures. We also investigate several methods of combining forecasts. Our results show that surveys outperform the other forecasting methods and that the term structure specifications perform relatively poorly. We find little evidence that combining forecasts produces superior forecasts to survey information alone. When combining forecasts, the data consistently places the highest weights on survey information.     

Stock Return Predictability: Is it There?

We examine the predictive power of the dividend yields for forecastingexcess returns, cash flows, and interest rates. Dividend yieldspredict excess returns only at short horizons together withthe short rate and do not have any long-horizon predictive power.At short horizons, the short rate strongly negatively predictsreturns. These results are robust in international data andare not due to lack of power. A present value model that matchesthe data shows that discount rate and short rate movements playa large role in explaining the variation in dividend yields.Finally, we find that earnings yields significantly predictfuture cash flows. (JEL C12, C51, C52, E49, F30, G12)     

Liquidity and Expected Returns: Lessons from Emerging Markets

Given the cross-sectional and temporal variation in their liquidity,emerging equity markets provide an ideal setting to examinethe impact of liquidity on expected returns. Our main liquiditymeasure is a transformation of the proportion of zero dailyfirm returns, averaged over the month. We find that it significantlypredicts future returns, whereas alternative measures such asturnover do not. Consistent with liquidity being a priced factor,unexpected liquidity shocks are positively correlated with contemporaneousreturn shocks and negatively correlated with shocks to the dividendyield. We consider a simple asset-pricing model with liquidityand the market portfolio as risk factors and transaction coststhat are proportional to liquidity. The model differentiatesbetween integrated and segmented countries and time periods.Our results suggest that local market liquidity is an importantdriver of expected returns in emerging markets, and that theliberalization process has not fully eliminated its impact.