Bounds on the autocorrelation of admissible stochastic discount factors

We show how to use asset market data to restrict the admissible region for the first-order autocorrelation of the stochastic discount factor (SDF). We interpret this statistic as a measure of a model’s economic time variation across two periods. Estimating bounds for nominal and real SDFs at monthly and quarterly frequencies, we find that the admissible autocorrelations are significantly negative, but greater than −0.02, implying that the bounds impose a strong restriction on candidate SDFs. We illustrate the relevancy of these findings by showing that some widely used consumption-based models are misspecified with respect to the autocorrelation bound. Finally, we examine the implications of our results for the admissibility of linear factor models and the appropriateness of empirical pricing factors.     

Pricing American options under stochastic volatility and stochastic interest rates

We introduce a new analytical approach to price American options. Using an explicit and intuitive proxy for the exercise rule, we derive tractable pricing formulas using a short-maturity asymptotic expansion. Depending on model parameters, this method can accurately price options with time-to-maturity up to several years. The main advantage of our approach over existing methods lies in its straightforward extension to models with stochastic volatility and stochastic interest rates. We exploit this advantage by providing an analysis of the impact of volatility mean-reversion, volatility of volatility, and correlations on the American put price.     

Credit market shocks and economic fluctuations: Evidence from corporate bond and stock markets

To identify disruptions in credit markets, research on the role of asset prices in economic fluctuations has focused on the information content of various corporate credit spreads. We re-examine this evidence using a broad array of credit spreads constructed directly from the secondary bond prices on outstanding senior unsecured debt issued by a large panel of nonfinancial firms. An advantage of our “ground-up” approach is that we are able to construct matched portfolios of equity returns, which allows us to examine the information content of bond spreads that is orthogonal to the information contained in stock prices of the same set of firms, as well as in macroeconomic variables measuring economic activity, inflation, interest rates, and other financial indicators. Our portfolio-based bond spreads contain substantial predictive power for economic activity and outperform—especially at longer horizons—standard default-risk indicators. Much of the predictive power of bond spreads for economic activity is embedded in securities issued by intermediate-risk rather than high-risk firms. According to impulse responses from a structural factor-augmented vector autoregression, unexpected increases in bond spreads cause large and persistent contractions in economic activity. Indeed, shocks emanating from the corporate bond market account for more than 30 percent of the forecast error variance in economic activity at the two- to four-year horizon. Overall, our results imply that credit market shocks have contributed significantly to US economic fluctuations during the 1990-2008 period.     

Turn-of-the-month and intramonth effects in government bond markets: Is there a role for macroeconomic news?

This paper focuses on the turn-of-the-month (TOM) and intramonth anomalies in government bond returns. In particular, we examine whether the TOM and intramonth effects exist in government bond markets, and moreover, whether these anomalies are related to the release of macroeconomic news as suggested in recent stock market studies. Using data on the 2-year and 10-year US Treasury Notes and German government bonds, we document a modest TOM effect in government bond returns. This effect does not disappear after controlling for the release of macroeconomic announcements, thereby suggesting that the origin of the TOM effect is not necessarily the same across asset classes.     

Stochastic risk premiums,stochastic skewness in currency options,and stochastic discount factors in international economies

We develop models of stochastic discount factors in international economies that produce stochastic risk premiums and stochastic skewness in currency options. We estimate the models using time-series returns and option prices on three currency pairs that form a triangular relation. Estimation shows that the average risk premium in Japan is larger than that in the US or the UK, the global risk premium is more persistent and volatile than the country-specific risk premiums, and investors respond differently to different shocks. We also identify high-frequency jumps in each economy but find that only downside jumps are priced. Finally, our analysis shows that the risk premiums are economically compatible with movements in stock and bond market fundamentals.     

The day-of-the-week effect and conditional volatility: Sensitivity of error distributional assumptions

We test for reliable evidence of the day-of-the-week effect on both the mean and volatility for the S&P/TSX Canadian return index. Unlike previous studies, we permit several specifications for the error distribution — GARCH normal, Student's t, generalized error distribution, and double exponential distribution. Unlike other studies, we find that the day-of-the-week effect in both mean and conditional volatility is sensitive to the particular specification of the underlying distributions. We also find that using a regression analysis assuming a Student's t distribution is a better way to investigate this effect. Our evidence demonstrates the apparent fragility of previous empirical studies on calendar anomalies. Thus, our results serve as a warning that with financial data, the error distributional assumptions are critical to correctly identifying empirical regularities in the data.     

Maximum likelihood estimation of stochastic volatility models

We develop and implement a method for maximum likelihood estimation in closed-form of stochastic volatility models. Using Monte Carlo simulations, we compare a full likelihood procedure, where an option price is inverted into the unobservable volatility state, to an approximate likelihood procedure where the volatility state is replaced by proxies based on the implied volatility of a short-dated at-the-money option. The approximation results in a small loss of accuracy relative to the standard errors due to sampling noise. We apply this method to market prices of index options for several stochastic volatility models, and compare the characteristics of the estimated models. The evidence for a general CEV model, which nests both the affine Heston model and a GARCH model, suggests that the elasticity of variance of volatility lies between that assumed by the two nested models.     

Bubbles and capital flow volatility: Causes and risk management

Emerging market economies are fertile ground for the development of real estate and other financial bubbles. Despite these economies’ significant growth potential, their corporate and government sectors do not generate the financial instruments to provide residents with adequate stores of value. Capital often flows out of these economies seeking these stores of value in the developed world. Bubbles are beneficial because they provide domestic stores of value and thereby reduce capital outflows while increasing investment. But they come at a cost, as they expose the country to bubble-crashes and capital flow reversals. We show that domestic financial underdevelopment not only facilitates the emergence of bubbles, but also leads agents to undervalue the aggregate risk embodied in financial bubbles. In this context, even rational bubbles can be welfare reducing. We study a set of aggregate risk management policies to alleviate the bubble-risk. We show that liquidity requirements, sterilization of capital inflows and structural policies aimed at developing public debt markets ‘collateralized’ by future revenues, all have a high payoff in this environment.     

The day of the week effect on stock market volatility and volume: International evidence

This study investigates the day of the week effect on the volatility of major stock market indexes for the period of 1988 through 2002. Using a conditional variance framework, we find that the day of the week effect is present in both return and volatility equations. The highest volatility occurs on Mondays for Germany and Japan, on Fridays for Canada and the United States, and on Thursdays for the United Kingdom. For most of the markets, the days with the highest volatility also coincide with that market's lowest trading volume. Thus, this paper supports the argument made by Foster and Viswanathan [Rev. Financ. Stud. 3 (1990) 593] that high volatility would be accompanied by low trading volume because of the unwillingness of liquidity traders to trade in periods of high stock market volatility.     

The term structure of real interest rates: theory and evidence from UK index-linked bonds

This paper studies the behavior of the default-risk-free real term structure and term premia in two general equilibrium endowment economies with complete markets but without money. In the first economy there are no frictions as in Lucas (Econometrica 46 (1978) 1429) and in the second risk-sharing is limited by the risk of default as in Alvarez and Jermann (Econometrica 68 (2000) 775; Rev. Financial Studies 14 (2001) 1117). Both models are solved numerically, calibrated to UK aggregate and household data, and the predictions are compared to data on real interest rates constructed from the UK index-linked data. While both models produce time-varying risk or term premia, only the model with limited risk-sharing can generate enough variation in the term premia to account for the rejections of expectations hypothesis.     

Macroeconomic fundamentals, price discovery, and volatility dynamics in emerging bond markets

This study characterizes volatility dynamics in external emerging bond markets and examines how prices and volatility respond to macroeconomic news. As in mature bond markets, surprises about macroeconomic conditions in emerging markets are found to affect both conditional returns and volatility of external bonds, with the effects on volatility being more pronounced and longer lasting than those on prices. Yet the process of information absorption tends to be more drawn-out than in mature bond markets. Global and regional macroeconomic news is at least as important as local news for both price and volatility dynamics.     

The cross-sectional relation between conditional heteroskedasticity,the implied volatility smile,and the variance risk premium

This paper estimates how the shape of the implied volatility smile and the size of the variance risk premium relate to parameters of GARCH-type time-series models measuring how conditional volatility responds to return shocks. Markets in which return shocks lead to large increases in conditional volatility tend to have larger variance risk premia than markets in which the impact on conditional volatility is slight. Markets in which negative (positive) return shocks lead to larger increases in future volatility than positive (negative) return shocks tend to have downward (upward) sloping implied volatility smiles. Also, differences in how volatility responds to return shocks as measured by GARCH-type models explain much, but not all, of the variations in excess kurtosis and multi-period skewness across different markets.     

Productivity-based asset pricing: Theory and evidence

In a general real business cycle model, we derive a pricing kernel that involves only production function arguments. The productivity shock is the single factor and the capital stock relative to a productivity measure is the conditioning variable. The model compares favorably with the complementary consumption-based and market-based approaches and with the Fama-French three-factor model. A size premium arises from differences in unconditional sensitivities—small firms are more sensitive to productivity shocks—and a value premium from differences in conditional sensitivities to productivity shocks—growth firms are more sensitive to productivity shocks when the productivity risk premium is low.     

The impact of macroeconomic news on quote adjustments, noise, and informational volatility

We study the impact of the arrival of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances. We decompose bid and ask returns into a common (“efficient return”) factor and two market-side-specific components capturing market microstructure effects. The corresponding variance components reflect information-driven and noise-induced volatilities. We find that all volatility components reveal distinct dynamics and are positively influenced by news. The proportion of noise-induced variances is highest before announcements and significantly declines thereafter. Moreover, news-affected responses in all volatility components are influenced by order flow imbalances.     

US presidential elections and implied volatility: The role of political uncertainty

This paper focuses on the effects of political uncertainty and the political process on implied stock market volatility during US presidential election cycles. Using monthly Iowa Electronic Markets data over five elections, we document that stock market uncertainty, as measured by the VIX volatility index, increases along with positive changes in the probability of success of the eventual winner. The association between implied volatility and the election probability of the eventual winner is positive even after controlling for changes in overall election uncertainty. These findings indicate that the presidential election process engenders market anxiety as investors form and revise their expectations regarding future macroeconomic policy.     

Stock returns and macro risks: Evidence from Finland

Deviations from the CAPM have generally been observed for the stock markets. One of many alternative approaches is using macro variables as systematic risks. We tested with a number of macro risks for the explanation of Finnish industry returns for a period from 1993:03 until 2008:07. The evidence suggests macro risks explain larger cross-sectional variations in average industry returns than the market factor alone and same is reported with the Hansen and Jagannathan (1997) specification measure. The changes in expected returns with a positive shock in the exchange rate risk and unanticipated inflation remain economically persistent for the post euro period, arguably a sign for the regulatory impact of the coordinated policies from European central bank (ECB). The robustness checks show the prevalence of macro risks, and market risk cannot be ignored altogether.     

The economic determinants of interest rate option smiles

We address three questions relating to the interest rate options market: What is the shape of the smile? What are the economic determinants of the shape of the smile? Do these determinants have predictive power for the future shape of the smile and vice versa? We investigate these issues using daily bid and ask prices of euro (€) interest rate caps/floors. We find a clear smile pattern in interest rate options. The shape of the smile varies over time and is affected in a dynamic manner by yield curve variables and the future uncertainty in the interest rate markets; it also has information about future aggregate default risk. Our findings are useful for the pricing, hedging and risk management of these derivatives.     

An unobserved component model of asset pricing across financial markets

Our research focuses on multifactor asset pricing models that investigate the importance of economic factors in the pricing of assets beyond the scope of the stock market. We present a Bayesian learning model of asset pricing across financial markets in which unobserved components are estimated using a Kalman filter (KF). Economic factors serve to drive the pricing of risk in the market, and agents update expectations recursively, as new information becomes available. We generally find that the Kalman filter provides superior performance and that economic factors like industrial production and unanticipated inflation provide consistent implications across financial markets.     

The term structure of policy rules

A formula is derived that links the coefficients of the monetary policy rule for the short-term interest rate to the coefficients of the implied affine equations for long-term interest rates. The formula predicts that an increase in the coefficients in the monetary policy rule will lead to an increase in the coefficients in the affine equations. Empirical evidence for such a prediction is provided. The curve of the response coefficients by maturity is also predicted by the formula. The formula's predictive accuracy and its closed form make it a useful tool for studying the policy implications of embedding no-arbitrage affine theories into macro models.     

On the reversal of return and dividend growth predictability: A tale of two periods

A disconcerting, albeit generally accepted, finding is that aggregate stock returns are predictable by dividend yield but dividend growth is unpredictable. I show that part of this lack of dividend growth predictability stems from how dividend growth is constructed. I then show a dramatic reversal of predictability in the 134 years during 1872–2005: stock returns are largely unpredictable in the first seven decades, but become predictable in the postwar period; dividend growth is strongly predictable in the prewar years but this predictability disappears in the postwar years. New evidence on the predictability of long-run returns and dividend growth is also shown.