Enrique Sentana
Biographic Data
| ID | 5734779 |
|---|---|
| NAME | Enrique Sentana |
| GIVEN NAMES | Enrique |
| FAMILY NAME | Sentana |
| SIGNATURE | SENTANA E |
| AFFILIATIONS | Centro de Estudios Monetarios y Financieros |
| ORCID | 0000-0003-2328-909X |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 11 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1992 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
GDP Solera: The Ideal Vintage Mix
We use the information in the successive vintages of GDE and GDI to obtain an improved timely measure of U.S. aggregate output by exploiting cointegration between the different measures taking seriously their monthly release calendar. We also combine all existing overlapping comprehensive revisions to achieve further improvements. We pay particular attention to the Great Recession and the COVID-19 pandemic, which, despite producing dramatic fluct…
Normal but skewed
We propose a multivariate normality test against skew normal distributions using higher‐order log‐likelihood derivatives, which is asymptotically equivalent to the likelihood ratio but only requires estimation under the null. Numerically, it is the supremum of the univariate skewness coefficient test over all linear combinations of the variables. We can simulate its exact finite sample distribution for any multivariate dimension and sample size. …
Is a Normal Copula the Right Copula
We derive computationally simple and intuitive expressions for score tests of Gaussian copulas against generalized hyperbolic alternatives, including symmetric and asymmetric Student t, and many other examples. We decompose our tests into third and fourth moment components, and obtain one-sided Likelihood Ratio analogs, whose standard asymptotic distribution we provide. Our Monte Carlo exercises confirm the reliable size of parametric bootstrap v…
Volatility-Related Exchange Traded Assets: An Econometric Investigation
We develop a theoretical framework for covariance stationary but persistent positively valued processes which combines a semi-nonparametric expansion of the Gamma distribution with a component version of the multiplicative error model. Our conditional mean assumption allows for slow, possibly nonmonotonic mean-reversion, while our distribution assumption provides more flexibility than a traditional Laguerre expansion while preserving positivity o…
A Unifying Approach to the Empirical Evaluation of Asset Pricing Models
Regression and SDF approaches with centered or uncentered moments and symmetric or asymmetric normalizations are commonly used to empirically evaluate linear factor pricing models. We show that unlike two-step or iterated GMM procedures, single-step estimators such as continuously updated GMM yield numerically identical risk prices, pricing errors, and overidentifying restrictions tests irrespective of the model validity and regardless of the fac…
Distributional Tests in Multivariate Dynamic Models with Normal and Student- t Innovations
We derive Lagrange multiplier and likelihood ratio specification tests for the null hypotheses of multivariate normal and Student-t innovations using the generalized hyperbolic distribution as our alternative hypothesis. We decompose the corresponding Lagrange multiplier-type tests into skewness and kurtosis components. We also obtain more powerful one-sided Kuhn-Tucker versions that are equivalent to the likelihood ratio test, whose asymptotic d…
Parametric Properties of Semi-Nonparametric Distributions, with Applications to Option Valuation
We derive the statistical properties of the semi-nonparametric (SNP) densities of Gallant and Nychka (1987). We show that these densities, which are always positive, are more flexible than truncated Gram–Charlier expansions with positivity restrictions. We use the SNP densities for financial derivatives valuation. We relate real and risk-neutral measures, obtain closed-form prices for European options, and analyze the semiparametric properties of…
Maximum Likelihood Estimation and Inference in Multivariate Conditionally Heteroscedastic Dynamic Regression Models With Student t Innovations
We provide numerically reliable analytical expressions for the score, Hessian, and information matrix of conditionally heteroscedastic dynamic regression models when the conditional distribution is multivariatet. We also derive one-sided and two-sided Lagrange multiplier tests for multivariate normality versus multivariate t based on the first two moments of the squared norm of the standardized innovations evaluated at the Gaussian pseudo-maximum…
Did the EMS Reduce the Cost of Capital
We propose a dynamic APT multi-factor model with time-varying volatility for currency, bond and stock returns for ten European countries over the period 1977-1997. We exploit the cross-sectional dimension of the model to construct world portfolios, which, when added to the original list of assets, allow us to develop simple consistent methods of estimation and testing. Our results reject the implicit asset pricing restrictions, and suggest that d…
An EM Algorithm for Conditionally Heteroscedastic Factor Models
This article discusses the application of the EM algorithm to factor models with dynamic heteroscedasticity in the common factors. It demonstrates that the EM algorithm reduces the computational burden so much that researchers can estimate such models with many series. Two empirical applications with 11 and 266 stock returns are presented, confirming that the EM algorithm yields significant speed gains and that it makes unnecessary the computatio…
Feedback Traders and Stock Return Autocorrelations: Evidence from a Century of Daily Data
Journal Article Feedback Traders and Stock Return Autocorrelations: Evidence from a Century of Daily Data Get access Enrique Sentana, Enrique Sentana London School of Economics Search for other works by this author on: Oxford Academic Google Scholar Sushil Wadhwani Sushil Wadhwani London School of Economics Search for other works by this author on: Oxford Academic Google Scholar The Economic Journal, Volume 102, Issue 411, 1 March 1992, Pages 415…
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Feedback Traders and Stock Return Autocorrelations: Evidence from a Century of Daily Data
Journal Article Feedback Traders and Stock Return Autocorrelations: Evidence from a Century of Daily Data Get access Enrique Sentana, Enrique Sentana London School of Economics Search for other works by this author on: Oxford Academic Google Scholar Sushil Wadhwani Sushil Wadhwani London School of Economics Search for other works by this author on: Oxford Academic Google Scholar The Economic Journal, Volume 102, Issue 411, 1 March 1992, Pages 415…
An EM Algorithm for Conditionally Heteroscedastic Factor Models
This article discusses the application of the EM algorithm to factor models with dynamic heteroscedasticity in the common factors. It demonstrates that the EM algorithm reduces the computational burden so much that researchers can estimate such models with many series. Two empirical applications with 11 and 266 stock returns are presented, confirming that the EM algorithm yields significant speed gains and that it makes unnecessary the computatio…
Did the EMS Reduce the Cost of Capital
We propose a dynamic APT multi-factor model with time-varying volatility for currency, bond and stock returns for ten European countries over the period 1977-1997. We exploit the cross-sectional dimension of the model to construct world portfolios, which, when added to the original list of assets, allow us to develop simple consistent methods of estimation and testing. Our results reject the implicit asset pricing restrictions, and suggest that d…
Maximum Likelihood Estimation and Inference in Multivariate Conditionally Heteroscedastic Dynamic Regression Models With Student t Innovations
We provide numerically reliable analytical expressions for the score, Hessian, and information matrix of conditionally heteroscedastic dynamic regression models when the conditional distribution is multivariatet. We also derive one-sided and two-sided Lagrange multiplier tests for multivariate normality versus multivariate t based on the first two moments of the squared norm of the standardized innovations evaluated at the Gaussian pseudo-maximum…
Parametric Properties of Semi-Nonparametric Distributions, with Applications to Option Valuation
We derive the statistical properties of the semi-nonparametric (SNP) densities of Gallant and Nychka (1987). We show that these densities, which are always positive, are more flexible than truncated Gram–Charlier expansions with positivity restrictions. We use the SNP densities for financial derivatives valuation. We relate real and risk-neutral measures, obtain closed-form prices for European options, and analyze the semiparametric properties of…
Distributional Tests in Multivariate Dynamic Models with Normal and Student- t Innovations
We derive Lagrange multiplier and likelihood ratio specification tests for the null hypotheses of multivariate normal and Student-t innovations using the generalized hyperbolic distribution as our alternative hypothesis. We decompose the corresponding Lagrange multiplier-type tests into skewness and kurtosis components. We also obtain more powerful one-sided Kuhn-Tucker versions that are equivalent to the likelihood ratio test, whose asymptotic d…
A Unifying Approach to the Empirical Evaluation of Asset Pricing Models
Regression and SDF approaches with centered or uncentered moments and symmetric or asymmetric normalizations are commonly used to empirically evaluate linear factor pricing models. We show that unlike two-step or iterated GMM procedures, single-step estimators such as continuously updated GMM yield numerically identical risk prices, pricing errors, and overidentifying restrictions tests irrespective of the model validity and regardless of the fac…
Volatility-Related Exchange Traded Assets: An Econometric Investigation
We develop a theoretical framework for covariance stationary but persistent positively valued processes which combines a semi-nonparametric expansion of the Gamma distribution with a component version of the multiplicative error model. Our conditional mean assumption allows for slow, possibly nonmonotonic mean-reversion, while our distribution assumption provides more flexibility than a traditional Laguerre expansion while preserving positivity o…
Is a Normal Copula the Right Copula
We derive computationally simple and intuitive expressions for score tests of Gaussian copulas against generalized hyperbolic alternatives, including symmetric and asymmetric Student t, and many other examples. We decompose our tests into third and fourth moment components, and obtain one-sided Likelihood Ratio analogs, whose standard asymptotic distribution we provide. Our Monte Carlo exercises confirm the reliable size of parametric bootstrap v…
Normal but skewed
We propose a multivariate normality test against skew normal distributions using higher‐order log‐likelihood derivatives, which is asymptotically equivalent to the likelihood ratio but only requires estimation under the null. Numerically, it is the supremum of the univariate skewness coefficient test over all linear combinations of the variables. We can simulate its exact finite sample distribution for any multivariate dimension and sample size. …
GDP Solera: The Ideal Vintage Mix
We use the information in the successive vintages of GDE and GDI to obtain an improved timely measure of U.S. aggregate output by exploiting cointegration between the different measures taking seriously their monthly release calendar. We also combine all existing overlapping comprehensive revisions to achieve further improvements. We pay particular attention to the Great Recession and the COVID-19 pandemic, which, despite producing dramatic fluct…
Econometrics (9 works) · Financial Risk and Volatility Modeling (8 works) · Mathematics (8 works) · Economics (7 works) · Statistics (6 works) · Monetary Policy and Economic Impact (5 works) · Applied Mathematics (4 works) · Financial Markets and Investment Strategies (4 works) · Monte Carlo method (4 works) · Computer Science (3 works)