| Working Paper |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Bootstrap Approach for Generalized Autocontour Testing |
0 |
0 |
0 |
49 |
0 |
0 |
3 |
65 |
| A Bootstrap Approach for Generalized Autocontour Testing. Implications for VIX Forecast Densities |
0 |
0 |
0 |
56 |
1 |
2 |
2 |
81 |
| A comment on the dynamic factor model with dynamic factors |
0 |
0 |
2 |
70 |
0 |
0 |
5 |
153 |
| A powerful test for conditional heteroscedasticity for financial time series with highly persistent volatilities |
0 |
0 |
0 |
221 |
0 |
0 |
2 |
654 |
| Accurate Subsampling Intervals of Principal Components Factors |
1 |
1 |
1 |
65 |
1 |
1 |
2 |
170 |
| An overview of probabilistic and time series models in finance |
0 |
0 |
0 |
394 |
0 |
1 |
2 |
635 |
| Asymmetric Observation Errors in Optimal Control of Stochastic Quadratic Linear Systems and Application to Modelling Volatility |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
288 |
| Asymmetric long memory GARCH: a reply to Hwang's model |
0 |
0 |
0 |
92 |
0 |
0 |
0 |
326 |
| Bootstrap Predictive Inference for Arima Processes |
0 |
0 |
0 |
7 |
0 |
0 |
1 |
50 |
| Bootstrap forecast of multivariate VAR models without using the backward representation |
0 |
0 |
0 |
158 |
0 |
1 |
5 |
391 |
| Bootstrap prediction intervals for VaR and ES in the context of GARCH models |
0 |
0 |
2 |
192 |
1 |
1 |
8 |
524 |
| Bootstrap prediction intervals for power-transformed time series |
0 |
0 |
0 |
143 |
0 |
0 |
0 |
431 |
| Bootstrap prediction intervals in State Space models |
0 |
0 |
0 |
222 |
0 |
1 |
3 |
474 |
| Bootstrap prediction mean squared errors of unobserved states based on the Kalman filter with estimated parameters |
0 |
0 |
0 |
53 |
0 |
0 |
1 |
176 |
| Comparing Forecasts of Extremely Large Conditional Covariance Matrices |
0 |
0 |
1 |
59 |
0 |
2 |
8 |
138 |
| Comparing sample and plug-in moments in asymmetric Garch Models |
0 |
0 |
0 |
9 |
1 |
1 |
1 |
56 |
| Comparing univariate and multivariate models to forecast portfolio value-at-risk |
0 |
0 |
1 |
390 |
0 |
1 |
7 |
1,421 |
| DETECTING LEVEL SHIFTS IN THE PRESENCE OF CONDITIONAL HETEROSCEDASTICITY |
0 |
0 |
0 |
13 |
0 |
1 |
1 |
116 |
| Dealing with idiosyncratic cross-correlation when constructing confidence regions for PC factors |
0 |
1 |
1 |
2 |
2 |
5 |
9 |
11 |
| Detecting level shifts in the presence of conditional heteroscedasticity |
0 |
0 |
0 |
86 |
0 |
0 |
1 |
228 |
| Determining the number of factors after stationary univariate transformations |
0 |
0 |
0 |
38 |
0 |
2 |
4 |
81 |
| Economic activity and climate change |
0 |
0 |
1 |
15 |
1 |
4 |
8 |
30 |
| Effects of Level Outliers on the Identification and Estimation of GARCH Models |
0 |
0 |
0 |
175 |
0 |
0 |
0 |
390 |
| Effects of parameter estimation on prediction densities a bootstrap approach |
0 |
1 |
1 |
1 |
0 |
2 |
3 |
16 |
| Estimación de la volatilidad de la inflación en presencia de observaciones atípicas y heteroscedasticidad condicional |
0 |
0 |
0 |
8 |
0 |
0 |
2 |
44 |
| Estimating and Forecasting GARCH Volatility in the Presence of Outiers |
0 |
0 |
0 |
74 |
0 |
0 |
1 |
128 |
| Estimation methods for stochastic volatility models: a survey |
0 |
0 |
0 |
1,230 |
0 |
0 |
2 |
2,047 |
| Expecting the unexpected: Stressed scenarios for economic growth |
0 |
0 |
1 |
17 |
1 |
2 |
8 |
38 |
| Expecting the unexpected: economic growth under stress |
0 |
0 |
1 |
27 |
1 |
1 |
8 |
106 |
| Expecting the unexpected: economic growth under stress |
0 |
0 |
1 |
27 |
0 |
1 |
5 |
65 |
| FARS: Factor Augmented Regression Scenarios in R |
9 |
9 |
9 |
9 |
3 |
3 |
3 |
3 |
| Finite sample properties of a QML estimator of stochastic volatility models with long memory |
0 |
0 |
1 |
3 |
0 |
0 |
1 |
30 |
| Forecasting returns and volatilities in GARCH processes using the bootstrap |
0 |
0 |
0 |
15 |
0 |
0 |
0 |
38 |
| GARCH models with leverage effect: differences and similarities |
0 |
1 |
1 |
1,083 |
0 |
1 |
4 |
4,103 |
| Growth in Stress |
0 |
0 |
0 |
14 |
0 |
0 |
1 |
69 |
| Heterogeneous economic growth vulnerability across Euro Area countries under stressed scenarios |
0 |
8 |
8 |
8 |
2 |
5 |
6 |
6 |
| Identification of asymmetric conditional heteroscedasticity in the presence of outliers |
0 |
0 |
0 |
41 |
0 |
0 |
1 |
55 |
| International vulnerability of inflation |
0 |
1 |
7 |
7 |
1 |
3 |
13 |
13 |
| Is stochastic volatility more flexible than garch? |
0 |
0 |
1 |
252 |
0 |
1 |
5 |
521 |
| MGARCH models: tradeoff between feasibility and flexibility |
1 |
1 |
2 |
60 |
1 |
1 |
5 |
185 |
| Measuring financial risk: comparison of alternative procedures to estimate VaR and ES |
0 |
0 |
3 |
491 |
0 |
0 |
6 |
1,265 |
| Model uncertainty and the forecast accuracy of ARMA models: A survey |
0 |
1 |
1 |
141 |
0 |
1 |
6 |
286 |
| Modelling intra-daily volatility by functional data analysis: an empirical application to the spanish stock market |
0 |
0 |
1 |
261 |
1 |
2 |
5 |
833 |
| Modelling long-memory volatilities with leverage effect: ALMSV versus FIEGARCH |
0 |
0 |
0 |
386 |
1 |
1 |
2 |
1,011 |
| Modelos de memoria larga para series económicas y financieras |
0 |
0 |
0 |
576 |
0 |
1 |
4 |
2,098 |
| Modelos para series temporales heterocedásticas |
0 |
0 |
0 |
4 |
1 |
1 |
1 |
28 |
| More is not always better: back to the Kalman filter in dynamic factor models |
0 |
0 |
0 |
124 |
0 |
0 |
5 |
281 |
| One for all: nesting asymmetric stochastic volatility models |
0 |
0 |
0 |
80 |
0 |
0 |
0 |
167 |
| Outliers and conditional autoregressive heteroscedasticity in time series |
0 |
0 |
0 |
269 |
1 |
2 |
6 |
748 |
| Prediction Regions for Interval-valued Time Series |
0 |
1 |
1 |
11 |
0 |
1 |
1 |
33 |
| Prediction Regions for Interval-valued Time Series |
0 |
0 |
0 |
52 |
0 |
1 |
2 |
67 |
| Prediction with univariate time series models: The Iberia case |
0 |
0 |
0 |
108 |
0 |
0 |
1 |
923 |
| Properties of the sample autocorrelations in autoregressive stochastic volatllity models |
0 |
0 |
0 |
97 |
0 |
0 |
0 |
242 |
| Quasi-Maximum Likelihood Estimation of Stochastic Variance Models |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
47 |
| Relaciones dinámicas en el mercado internacional de carne de vacuno |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
25 |
| Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk |
1 |
2 |
4 |
68 |
1 |
2 |
7 |
131 |
| SPURIOUS AND HIDDEN VOLATILITY |
0 |
0 |
0 |
39 |
0 |
2 |
3 |
148 |
| Score driven asymmetric stochastic volatility models |
0 |
0 |
0 |
207 |
0 |
1 |
1 |
125 |
| Small versus big-data factor extraction in Dynamic Factor Models: An empirical assessment |
0 |
0 |
1 |
72 |
0 |
1 |
5 |
154 |
| Spurious and hidden volatility |
0 |
0 |
0 |
71 |
0 |
1 |
2 |
212 |
| Stochastic volatility models and the Taylor effect |
0 |
1 |
1 |
399 |
0 |
1 |
2 |
1,758 |
| Stochastic volatility versus autoregressive conditional heteroscedasticity |
0 |
0 |
0 |
8 |
0 |
0 |
0 |
27 |
| Stock market regulations and international financial integration: the case of Spain |
0 |
0 |
0 |
2 |
0 |
1 |
1 |
28 |
| Temperature in the Iberian Peninsula: Trend, seasonality, and heterogeneity |
0 |
1 |
2 |
2 |
2 |
3 |
8 |
10 |
| Testing for conditional heteroscedasticity in the components of inflation |
0 |
0 |
0 |
84 |
0 |
1 |
2 |
413 |
| The relation between the level and uncertainty of inflation |
0 |
0 |
0 |
37 |
0 |
1 |
1 |
349 |
| The relationship between ARIMA-GARCH and unobserved component models with GARCH disturbances |
0 |
0 |
0 |
313 |
0 |
0 |
0 |
1,078 |
| The uncertainty of conditional returns, volatilities and correlations in DCC models |
0 |
0 |
0 |
52 |
1 |
1 |
5 |
159 |
| Unobserved component models with asymmetric conditional variances |
0 |
0 |
0 |
114 |
0 |
1 |
1 |
330 |
| Using auxiliary residuals to detect conditional heteroscedasticity in inflation |
0 |
0 |
0 |
72 |
0 |
0 |
3 |
347 |
| Which univariate time series model predicts quicker a crisis? The Iberia case |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
15 |
| Total Working Papers |
12 |
29 |
56 |
9,530 |
24 |
69 |
224 |
27,694 |
| Journal Article |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| 30 years of cointegration and dynamic factor models forecasting and its future with big data: Editorial |
1 |
2 |
2 |
24 |
3 |
5 |
9 |
59 |
| A bootstrap approach for generalized Autocontour testing Implications for VIX forecast densities |
0 |
0 |
0 |
2 |
0 |
1 |
3 |
10 |
| A note on the properties of power-transformed returns in long-memory stochastic volatility models with leverage effect |
0 |
0 |
0 |
18 |
0 |
1 |
1 |
58 |
| Accurate Confidence Regions for Principal Components Factors |
0 |
0 |
1 |
9 |
0 |
1 |
4 |
25 |
| Asymmetric long memory GARCH: a reply to Hwang's model |
0 |
0 |
0 |
10 |
0 |
0 |
0 |
102 |
| Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation |
0 |
0 |
0 |
10 |
0 |
1 |
2 |
29 |
| Bayesian Analysis of Stochastic Volatility Models: Comment |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
122 |
| Bootstrap multi-step forecasts of non-Gaussian VAR models |
0 |
0 |
0 |
23 |
0 |
0 |
4 |
99 |
| Bootstrap prediction for returns and volatilities in GARCH models |
0 |
1 |
6 |
356 |
0 |
1 |
19 |
712 |
| Bootstrap prediction intervals for power-transformed time series |
0 |
0 |
0 |
18 |
0 |
0 |
0 |
57 |
| Bootstrap prediction intervals in state–space models |
0 |
0 |
0 |
27 |
0 |
0 |
1 |
85 |
| Bootstrap prediction mean squared errors of unobserved states based on the Kalman filter with estimated parameters |
0 |
0 |
0 |
26 |
1 |
2 |
4 |
126 |
| Bootstrap predictive inference for ARIMA processes |
0 |
0 |
0 |
56 |
0 |
0 |
0 |
196 |
| Bootstrapping Financial Time Series |
0 |
0 |
0 |
336 |
0 |
2 |
7 |
690 |
| Comparing Univariate and Multivariate Models to Forecast Portfolio Value-at-Risk |
0 |
0 |
0 |
52 |
0 |
0 |
3 |
273 |
| Comparing high-dimensional conditional covariance matrices: Implications for portfolio selection |
1 |
1 |
1 |
6 |
1 |
1 |
1 |
43 |
| Conditionally heteroscedastic unobserved component models and their reduced form |
0 |
0 |
0 |
12 |
0 |
2 |
2 |
72 |
| Determining the number of factors after stationary univariate transformations |
0 |
0 |
0 |
7 |
1 |
3 |
5 |
45 |
| Dynamic factor models: Does the specification matter? |
1 |
3 |
5 |
9 |
3 |
10 |
13 |
30 |
| Economic activity and $$\hbox {CO}_2$$ CO 2 emissions in Spain |
0 |
0 |
0 |
0 |
1 |
5 |
5 |
5 |
| Effects of outliers on the identification and estimation of GARCH models |
0 |
0 |
1 |
94 |
0 |
0 |
2 |
243 |
| Effects of parameter estimation on prediction densities: a bootstrap approach |
0 |
0 |
0 |
27 |
0 |
0 |
0 |
88 |
| Estimating GARCH volatility in the presence of outliers |
0 |
0 |
3 |
23 |
0 |
0 |
6 |
80 |
| Estimating Non-stationary Common Factors: Implications for Risk Sharing |
0 |
0 |
0 |
12 |
0 |
1 |
2 |
40 |
| Estimation methods for stochastic volatility models: a survey |
0 |
0 |
1 |
355 |
2 |
3 |
7 |
813 |
| Evaluation of ionic liquids as absorbents for ammonia absorption refrigeration cycles using COSMO-based process simulations |
0 |
0 |
1 |
64 |
0 |
0 |
3 |
252 |
| Expecting the unexpected: Stressed scenarios for economic growth |
0 |
1 |
6 |
7 |
0 |
1 |
15 |
17 |
| Factor Extraction in Dynamic Factor Models: Kalman Filter Versus Principal Components |
1 |
4 |
23 |
100 |
6 |
11 |
39 |
162 |
| Factor extraction using Kalman filter and smoothing: This is not just another survey |
0 |
0 |
2 |
23 |
0 |
1 |
9 |
102 |
| Finite sample properties of a QML estimator of stochastic volatility models with long memory |
0 |
0 |
0 |
28 |
0 |
1 |
3 |
153 |
| Forecasting the yield curve: the role of additional and time‐varying decay parameters, conditional heteroscedasticity, and macro‐economic factors |
0 |
0 |
2 |
2 |
1 |
2 |
17 |
17 |
| Frontiers in VaR forecasting and backtesting |
0 |
1 |
7 |
208 |
1 |
3 |
14 |
433 |
| Growth in stress |
0 |
0 |
4 |
21 |
0 |
0 |
8 |
79 |
| Identification of asymmetric conditional heteroscedasticity in the presence of outliers |
0 |
0 |
0 |
3 |
0 |
0 |
4 |
35 |
| Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models |
0 |
0 |
0 |
1 |
1 |
1 |
3 |
4 |
| Introduction to nonlinearities, business cycles, and forecasting |
0 |
0 |
0 |
89 |
0 |
0 |
0 |
193 |
| MGARCH models: Trade-off between feasibility and flexibility |
0 |
0 |
0 |
28 |
0 |
0 |
4 |
158 |
| Maximally Autocorrelated Power Transformations: A Closer Look at the Properties of Stochastic Volatility Models |
0 |
0 |
0 |
16 |
0 |
0 |
0 |
60 |
| Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH |
0 |
0 |
0 |
62 |
0 |
0 |
0 |
225 |
| Modelos de memoria larga para series económicas y financieras |
0 |
0 |
1 |
96 |
1 |
1 |
5 |
513 |
| Multivariate Stochastic Variance Models |
0 |
0 |
4 |
1,457 |
0 |
6 |
14 |
3,510 |
| Optimal portfolios with minimum capital requirements |
0 |
0 |
0 |
19 |
0 |
0 |
0 |
105 |
| Prediction intervals in conditionally heteroscedastic time series with stochastic components |
0 |
0 |
0 |
2 |
0 |
0 |
3 |
31 |
| Prediction intervals in conditionally heteroscedastic time series with stochastic components |
0 |
1 |
1 |
16 |
0 |
1 |
3 |
130 |
| Prediction regions for interval‐valued time series |
0 |
0 |
0 |
8 |
0 |
1 |
1 |
35 |
| Properties of the Sample Autocorrelations of Nonlinear Transformations in Long-Memory Stochastic Volatility Models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
79 |
| QML and GMM estimators of stochastic volatility models: Response to Andersen and Sorensen |
0 |
0 |
0 |
47 |
0 |
2 |
3 |
97 |
| Quasi-maximum likelihood estimation of stochastic volatility models |
0 |
1 |
2 |
713 |
0 |
1 |
6 |
1,321 |
| Revisiting Several Popular GARCH Models with Leverage Effect: Differences and Similarities |
0 |
0 |
1 |
78 |
0 |
0 |
4 |
193 |
| Stock market regulations and international financial integration: the case of Spain |
0 |
0 |
0 |
6 |
0 |
0 |
0 |
23 |
| Testing for Conditional Heteroscedasticity in the Components of Inflation |
0 |
0 |
0 |
38 |
0 |
0 |
2 |
167 |
| The factor structure of exchange rates volatility: global and intermittent factors |
0 |
0 |
1 |
2 |
0 |
0 |
5 |
7 |
| The uncertainty of conditional returns, volatilities and correlations in DCC models |
0 |
0 |
0 |
8 |
0 |
1 |
6 |
58 |
| Threshold stochastic volatility: Properties and forecasting |
0 |
0 |
0 |
19 |
0 |
1 |
4 |
58 |
| UNCERTAINTY AND DENSITY FORECASTS OF ARMA MODELS: COMPARISON OF ASYMPTOTIC, BAYESIAN, AND BOOTSTRAP PROCEDURES |
0 |
0 |
0 |
6 |
1 |
2 |
2 |
40 |
| Unobserved component models with asymmetric conditional variances |
0 |
0 |
0 |
39 |
0 |
1 |
3 |
128 |
| Unobserved component time series models with Arch disturbances |
0 |
1 |
1 |
649 |
0 |
2 |
4 |
1,146 |
| Total Journal Articles |
4 |
16 |
76 |
5,367 |
23 |
79 |
286 |
13,633 |
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