Posted Content•
The Determinants of Stock and Bond Return Comovements
TL;DR: In this article, the authors identify the economic factors employing structural and non-structural vector autoregressive models for economic state variables such as interest rates, (expected) inflation, output growth and dividend payouts.
Abstract: We study the economic sources of stock-bond return comovement and its time variation using a dynamic factor model. We identify the economic factors employing structural and non-structural vector autoregressive models for economic state variables such as interest rates, (expected) inflation, output growth and dividend payouts. We also view risk aversion, and uncertainty about inflation and output as additional potential factors. Even the best-fitting economic factor model fits the dynamics of stock-bond return correlations poorly. Alternative factors, such as liquidity proxies, help explain the residual correlations not explained by the economic models.
Citations
More filters
TL;DR: In this paper, the authors investigated the ability of a two-sector model to quantify the contribution of the housing market to business fluctuations using U.S. data and Bayesian methods and found that a large fraction of the upward trend in real housing prices over the last 40 years can be accounted for by slow technological progress in the housing sector.
Abstract: The ability of a two-sector model to quantify the contribution of the housing market to business fluctuations is investigated using U.S. data and Bayesian methods. The estimated model, which contains nominal and real rigidities and collateral constraints, displays the following features: first, a large fraction of the upward trend in real housing prices over the last 40 years can be accounted for by slow technological progress in the housing sector; second, residential investment and housing prices are very sensitive to monetary policy and housing demand shocks; third, the wealth effects from housing on consumption are positive and significant, and have become more important over time. The structural nature of the model allows identifying and quantifying the sources of fluctuations in house prices and residential investment and measuring the contribution of housing booms and busts to business cycles.
1,297 citations
TL;DR: This paper studied the sources and consequences of fluctuations in the US housing market and showed that the spillovers are nonnegligible, concentrated on consumption rather than business investment, and have become more important over time.
Abstract: We study sources and consequences of fluctuations in the US housing market. Slow technological progress in the housing sector explains the upward trend in real housing prices of the last 40 years. Over the business cycle, housing demand and housing technology shocks explain one-quarter each of the volatility of housing investment and housing prices. Monetary factors explain less than 20 percent, but have played a bigger role in the housing cycle at the turn of the century. We show that the housing market spillovers are nonnegligible, concentrated on consumption rather than business investment, and have become more important over time.
822 citations
TL;DR: In this paper, a multivariate model, identifying monetary policy and allowing for simultaneity and regime switching in coefficients and variances, is confronted with U.S. data since 1959 and the best fit is with a model that allows time variation in structural disturbance variances only.
Abstract: A multivariate model, identifying monetary policy and allowing for simultaneity and regime switching in coefficients and variances, is confronted with U.S. data since 1959. The best fit is with a model that allows time variation in structural disturbance variances only. Among models that also allow for changes in equation coefficients, the best fit is for a model that allows coefficients to change only in the monetary policy rule. That model allows switching among three main regimes and one rarely and briefly occurring regime. The three main regimes correspond roughly to periods when most observers believe that monetary policy actually differed, and the differences in policy behavior are substantively interesting, though statistically ill determined. The estimates imply monetary targeting was central in the early '80s but was also important sporadically in the '70s. The changes in regime were essential neither to the rise in inflation in the '70s nor to its decline in the '80s.
802 citations
TL;DR: In this article, the authors construct investor sentiment indices for six major stock markets and decompose them into one global and six local indices, finding that relative sentiment is correlated with the relative prices of dual-listed companies.
Abstract: We construct investor sentiment indices for six major stock markets and decompose them into one global and six local indices. In a validation test, we find that relative sentiment is correlated with the relative prices of dual-listed companies. Global sentiment is a contrarian predictor of country-level returns. Both global and local sentiment are contrarian predictors of the time series of cross-sectional returns within markets: When sentiment is high, future returns are low on relatively difficult to arbitrage and difficult to value stocks. Private capital flows appear to be one mechanism by which sentiment spreads across markets and forms global sentiment.
711 citations
TL;DR: In this paper, the authors extend the basic representative-household New Keynesian model to allow for a spread between the interest rate available to savers and borrowers, that can vary for either exogenous or endogenous reasons.
Abstract: We extend the basic (representative-household) New Keynesian [NK] model of the monetary transmission mechanism to allow for a spread between the interest rate available to savers and borrowers, that can vary for either exogenous or endogenous reasons. We find that the mere existence of a positive average spread makes little quantitative difference for the predicted effects of particular policies. Variation in spreads over time is of greater significance, with consequences both for the equilibrium relation between the policy rate and aggregate expenditure and for the relation between real activity and inflation. Nonetheless, we find that the target criterion - a linear relation that should be maintained between the inflation rate and changes in the output gap - that characterizes optimal policy in the basic NK model continues to provide a good approximation to optimal policy, even in the presence of variations in credit spreads. We also consider a "spread-adjusted Taylor rule," in which the intercept of the Taylor rule is adjusted in proportion to changes in credit spreads. We show that while such an adjustment can improve upon an unadjusted Taylor rule, the optimal degree of adjustment is less than 100 percent; and even with the correct size of adjustment, such a rule of thumb remains inferior to the targeting rule.
567 citations
References
More filters
TL;DR: In this article, a parameter covariance matrix estimator which is consistent even when the disturbances of a linear regression model are heteroskedastic is presented, which does not depend on a formal model of the structure of the heteroSkewedness.
Abstract: This paper presents a parameter covariance matrix estimator which is consistent even when the disturbances of a linear regression model are heteroskedastic. This estimator does not depend on a formal model of the structure of the heteroskedasticity. By comparing the elements of the new estimator to those of the usual covariance estimator, one obtains a direct test for heteroskedasticity, since in the absence of heteroskedasticity, the two estimators will be approximately equal, but will generally diverge otherwise. The test has an appealing least squares interpretation.
25,689 citations
TL;DR: In this article, a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction is described.
Abstract: This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix under fairly general conditions.
18,117 citations
"The Determinants of Stock and Bond ..." refers result in this paper
...While we do find a moderate degree of autocorrelation in both stock and bond returns, correcting for this bias (using 4 Newey and West (1987) lags) does not meaningfully alter stock-bond return volatilities and correlations....
[...]
TL;DR: In this article, the parameters of an autoregression are viewed as the outcome of a discrete-state Markov process, and an algorithm for drawing such probabilistic inference in the form of a nonlinear iterative filter is presented.
Abstract: This paper proposes a very tractable approach to modeling changes in regime. The parameters of an autoregression are viewed as the outcome of a discrete-state Markov process. For example, the mean growth rate of a nonstationary series may be subject to occasional, discrete shifts. The econometrician is presumed not to observe these shifts directly, but instead must draw probabilistic inference about whether and when they may have occurred based on the observed behavior of the series. The paper presents an algorithm for drawing such probabilistic inference in the form of a nonlinear iterative filter
9,189 citations
Posted Content•
TL;DR: In this article, a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction is described.
Abstract: This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix under fairly general conditions.
5,822 citations
TL;DR: In this article, a new class of multivariate models called dynamic conditional correlation models is proposed, which have the flexibility of univariate generalized autoregressive conditional heteroskedasticity (GARCH) models coupled with parsimonious parametric models for the correlations.
Abstract: Time varying correlations are often estimated with multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations. They are not linear but can often be estimated very simply with univariate or two-step methods based on the likelihood function. It is shown that they perform well in a variety of situations and provide sensible empirical results.
5,695 citations
"The Determinants of Stock and Bond ..." refers background or methods in this paper
...B A Component Model for Dynamic Stock-Bond Correlations In a recent paper, Colacito, Engle, and Ghysels (2009) introduce a component model for dynamic correlations....
[...]
...Schwert (1989), Campbell and Ammer (1993), and Engle, Ghysels, and Sohn (2008))....
[...]
...Our model fails to forecast realized correlations as well as a benchmark empirical model, using the MIDAS framework of Colacito, Engle, and Ghysels (2009). While this model is a backward-looking empirical model, it uses daily return data efficiently and generally fits the data very well....
[...]
...While we do characterize the variation in stock-bond return correlations using daily return data to calculate ex-post quarterly correlations, our main benchmark is the long-run component of the Colacito, Engle, and Ghysels (2009) model....
[...]
...This figure graphs realized quarterly correlations measured using daily returns, and the dataimplied conditional correlation based on the bivariate DCC-MIDAS model of Colacito, Engle, and Ghysels (2009). See Appendix B for the technical details about this model....
[...]