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61 records from EconBiz based on author Name
1. Horizon Effect in the Term Structure of Long-Run Risk-Return Trade-Offs
abstractThe horizon effect in the long-run predictive relationship between market excess return and historical market variance is investigated. To this end, the asymptotic multivariate distribution of the term structure of risk-return trade-offs is derived, accounting for short- and long-memory in the market variance dynamics. A rescaled Wald statistic is used to test whether the term structure of risk-return trade-offs is flat, that is, the risk-return slope coefficients are equal across horizons. When the regression model includes an intercept, the premise of a flat term structure of risk-return relationships is rejected. In contrast, there is no significant statistical evidence against the equality of slope coefficients from constrained risk-return regressions estimated at different horizons. A smoothed cross-horizon estimate is then proposed for the trade-off intensity at the market level. The findings underscore the importance of economically motivated restrictions to improve the estimation of intertemporal asset pricing models
Okou, Cedric; Jacquier, Eric;2015
Availability: Link
2. Horizon Effect in the Term Structure of Long-Run Risk-Return Trade-Offs
Okou, Cédric; Jacquier, Éric;2014
Availability:
3. Disentangling continuous volatility from jumps in long-run risk-return relationships
Jacquier, Eric; Okou, Cédric;2014
Type: Aufsatz in Zeitschrift; Article in journal;
4. Disentangling Continuous Volatility from Jumps in Long-Run Risk-Return Relationships
Jacquier, Éric; Okou, Cédric;2013
Availability:
5. Disentangling Continuous Volatility From Jumps in Long-Run Risk-Return Relationships
abstractRealized variance can be broken down into continuous volatility and jumps. We show that these two components have very different predictive powers on future long-term excess stock market returns. While continuous volatility is a key driver of medium to long-term risk-return relationships, jumps do not predict future medium to long-term excess returns. We use inference methods robust to persistent predictors in a multi-horizon setup. That is, we use a rescaled Student-t to test for significant risk-return links, give asymptotic arguments, and simulate its exact behavior under the null in the case of multiple regressors with different degrees of persistence. Then, with Wald tests of equality of the risk-return relationship at multiple horizons, we find no evidence against a proportional relationship, constant across horizons, between long-term continuous volatility and future returns. Two by-products of our analysis are that imposing model-based constraints on long term regressions can improve their efficiency, and short-run estimates are sensitive to short-term variability of the predictors
Jacquier, Eric; Okou, Cedric;2013
Availability: Link Link
6. Market Beta Dynamics and Portfolio Efficiency
abstractThis paper introduces a new estimation for the dynamics of betas. It combines two previously separate approaches in the literature, data-driven filters and parametric methods. Namely, we show how to estimate the parametric beta dynamics by instrumental variables combined with block-sampling - but not overlapping window filters - of data-driven betas. Instrumental variables are needed because of the measurement errorsin empirical betas. We find that, while betas are very strongly autocorrelated, neither aggregate nor firm-specific variables explain much of their quarterly variation. We then compare block-samplers and overlapping window filters using a criterion of economic significance. Namely, we track the out-of-sample performance of portfolios optimized subject to target beta constraints. For target betas of zero, the case of many hedge funds, we show that estimation error results in systematic overshooting of the target beta. These portfolios benefit from the use of medium to long term estimation windows of daily returns
Ghysels, Eric; Jacquier, Eric;2012
Availability: Link Link
Citations: 35 (based on OpenCitations)
7. Are underwriting cycles real and forecastable?
Boyer, Martin; Jacquier, Eric; Van Norden, Simon;2012
Type: Aufsatz in Zeitschrift; Article in journal;
8. Bayesian Methods In Finance
Jacquier, Eric; Polson, Nicholas;2012
Type: Aufsatz im Buch; Book section;
Availability: Link
Citations: 5 (based on OpenCitations)
9. The Performance of implied volatility in forecasting future volatility : an analysis of three major equity indices from 2004 to 2010
Ionesco, Vladimir M.; Eric Jacquier.;2011
Type: Thesis;
Availability: Link
10. Predicting systematic risk : implications from growth options
Jacquier, Eric; Titman, Sheridan; Yalçın, Atakan;2010
Type: Aufsatz in Zeitschrift; Article in journal;