| Working Paper |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Dynamic Bivariate Poisson Model for Analysing and Forecasting Match Results in the English Premier League |
0 |
0 |
7 |
232 |
1 |
3 |
18 |
465 |
| A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations |
0 |
1 |
2 |
62 |
2 |
7 |
12 |
169 |
| A Dynamic Yield Curve Model with Stochastic Volatility and Non-Gaussian Interactions: An Empirical Study of Non-standard Monetary Policy in the Euro Area |
0 |
0 |
1 |
71 |
2 |
4 |
10 |
113 |
| A Forty Year Assessment of Forecasting the Boat Race |
0 |
0 |
0 |
72 |
0 |
1 |
3 |
60 |
| A General Framework for Observation Driven Time-Varying Parameter Models |
0 |
0 |
2 |
166 |
4 |
8 |
13 |
367 |
| A General Framework for Observation Driven Time-Varying Parameter Models |
1 |
1 |
3 |
108 |
3 |
3 |
11 |
249 |
| A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk |
0 |
0 |
0 |
241 |
5 |
6 |
8 |
589 |
| A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk |
0 |
1 |
1 |
114 |
5 |
7 |
7 |
424 |
| A Note on “Continuous Invertibility and Stable QML Estimation of the EGARCH(1,1) Model” |
0 |
0 |
0 |
18 |
0 |
0 |
1 |
14 |
| A Time-Varying Parameter Model for Local Explosions |
0 |
2 |
59 |
59 |
2 |
4 |
36 |
36 |
| Accelerating GARCH and Score-Driven Models: Optimality, Estimation and Forecasting |
0 |
0 |
3 |
32 |
1 |
1 |
14 |
29 |
| An Hourly Periodic State Space Model for Modelling French National Electricity Load |
0 |
0 |
1 |
226 |
0 |
1 |
5 |
540 |
| An efficient and simple simulation smoother for state space time series analysis |
0 |
0 |
0 |
179 |
0 |
1 |
12 |
1,053 |
| Analyzing the Term Structure of Interest Rates using the Dynamic Nelson-Siegel Model with Time-Varying Parameters |
0 |
2 |
3 |
278 |
2 |
6 |
13 |
613 |
| Bayesian Dynamic Modeling of High-Frequency Integer Price Changes |
0 |
0 |
2 |
58 |
1 |
1 |
10 |
29 |
| Bayesian Risk Forecasting for Long Horizons |
1 |
1 |
37 |
37 |
2 |
3 |
60 |
60 |
| Business and Default Cycles for Credit Risk |
2 |
4 |
11 |
876 |
3 |
6 |
23 |
1,818 |
| Common business and housing market cycles in the Euro area from a multivariate decomposition |
0 |
0 |
1 |
181 |
2 |
3 |
19 |
373 |
| Computing Observation Weights for Signal Extraction and Filtering |
0 |
1 |
2 |
258 |
0 |
1 |
6 |
600 |
| Constructing seasonally adjusted data with time-varying confidence intervals |
0 |
0 |
0 |
23 |
2 |
2 |
6 |
87 |
| Convergence in European GDP Series |
0 |
0 |
0 |
481 |
2 |
2 |
6 |
2,228 |
| Credit Cycles and Macro Fundamentals |
0 |
0 |
0 |
283 |
0 |
0 |
2 |
810 |
| Credit cycles and macro fundamentals |
0 |
0 |
2 |
175 |
1 |
1 |
6 |
516 |
| Dynamic Factor Analysis in The Presence of Missing Data |
0 |
0 |
4 |
188 |
1 |
3 |
20 |
344 |
| Dynamic Factor Models with Smooth Loadings for Analyzing the Term Structure of Interest Rates |
0 |
0 |
1 |
65 |
2 |
2 |
3 |
209 |
| Dynamic factor models with macro, frailty and industry effects for US default counts: the credit crisis of 2008 |
0 |
0 |
0 |
49 |
1 |
1 |
9 |
121 |
| Dynamic term structure models with score-driven time-varying parameters: estimation and forecasting |
0 |
2 |
4 |
63 |
1 |
3 |
5 |
57 |
| Empirical Bayes Methods for Dynamic Factor Models |
0 |
1 |
3 |
99 |
1 |
2 |
13 |
85 |
| Estimating Systematic Continuous-time Trends in Recidivism using a Non-Gaussian Panel Data Model |
0 |
0 |
0 |
69 |
3 |
3 |
6 |
488 |
| Exact Score for Time Series Models in State Space Form (Now published in Biometrika (1992), 79, 4, pp.283-6.) |
0 |
0 |
0 |
0 |
0 |
1 |
4 |
14 |
| Extracting Business Cycles using Semi-parametric Time-varying Spectra with Applications to US Macroeconomic Time Series |
0 |
0 |
1 |
96 |
0 |
0 |
4 |
299 |
| Extracting a Robust U.S. Business Cycle Using a Time-Varying Multivariate Model-Based Bandpass Filter |
0 |
0 |
0 |
69 |
2 |
4 |
4 |
129 |
| Fast Efficient Importance Sampling by State Space Methods |
1 |
1 |
3 |
60 |
1 |
1 |
11 |
139 |
| Fast Estimation of Parameters in State Space Models |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
835 |
| Fast Filtering and Smoothing for Multivariate State Space Models |
0 |
0 |
1 |
10 |
1 |
1 |
3 |
22 |
| Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models |
0 |
0 |
0 |
14 |
0 |
0 |
2 |
24 |
| Feasible Invertibility Conditions for Maximum Likelihood Estimation for Observation-Driven Models |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
10 |
| Feasible Invertibility Conditions for Maximum Likelihood Estimation for Observation-Driven Models * |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
11 |
| Forecasting Cross-Sections of Frailty-Correlated Default |
0 |
0 |
0 |
70 |
0 |
1 |
1 |
235 |
| Forecasting Daily Time Series using Periodic Unobserved Components Time Series Models |
0 |
1 |
3 |
342 |
0 |
1 |
12 |
1,078 |
| Forecasting Daily Variability of the S&P 100 Stock Index using Historical, Realised and Implied Volatility Measurements |
0 |
0 |
2 |
938 |
1 |
3 |
13 |
2,431 |
| Forecasting Football Match Results in National League Competitions Using Score-Driven Time Series Models |
1 |
1 |
8 |
126 |
3 |
7 |
20 |
76 |
| Forecasting Interest Rates with Shifting Endpoints |
0 |
0 |
1 |
73 |
0 |
2 |
9 |
174 |
| Forecasting Macroeconomic Variables using Collapsed Dynamic Factor Analysis |
0 |
0 |
4 |
168 |
0 |
2 |
15 |
362 |
| Forecasting daily variability of the S\&P 100 stock index using historical, realised and implied volatility measurements |
0 |
0 |
0 |
3 |
1 |
2 |
7 |
1,057 |
| Forecasting economic time series using score-driven dynamic models with mixed-data sampling |
0 |
3 |
7 |
51 |
2 |
6 |
23 |
38 |
| Forecasting the U.S. Term Structure of Interest Rates using a Macroeconomic Smooth Dynamic Factor Model |
0 |
0 |
0 |
89 |
0 |
3 |
7 |
144 |
| Forecasting the Variability of Stock Index Returns with Stochastic Volatility Models and Implied Volatility |
0 |
0 |
1 |
807 |
0 |
0 |
2 |
2,092 |
| Generalized Autoregressive Method of Moments |
0 |
0 |
2 |
66 |
0 |
0 |
10 |
54 |
| Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time |
0 |
0 |
0 |
72 |
1 |
3 |
9 |
173 |
| Global Credit Risk: World, Country and Industry Factors |
0 |
0 |
1 |
26 |
1 |
1 |
5 |
74 |
| Global credit risk: world country and industry factors |
0 |
0 |
0 |
28 |
4 |
6 |
17 |
57 |
| In-Sample Bounds for Time-Varying Parameters of Observation Driven Models |
0 |
0 |
0 |
14 |
0 |
0 |
3 |
42 |
| In-Sample Confidence Bands and Out-of-Sample Forecast Bands for Time-Varying Parameters in Observation Driven Models |
0 |
0 |
1 |
53 |
1 |
2 |
7 |
32 |
| Information Theoretic Optimality of Observation Driven Time Series Models |
0 |
0 |
0 |
42 |
1 |
5 |
12 |
54 |
| Interaction between Supply and Demand Shocks in Production and Employment |
0 |
0 |
1 |
387 |
0 |
0 |
1 |
3,778 |
| Interaction between supply and demand in production and employment |
0 |
0 |
2 |
21 |
0 |
1 |
6 |
152 |
| Intervention Time Series Analysis of Crime Rates |
0 |
0 |
0 |
706 |
0 |
0 |
2 |
2,326 |
| Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model |
0 |
0 |
0 |
53 |
0 |
0 |
1 |
65 |
| Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions |
0 |
0 |
6 |
30 |
1 |
1 |
13 |
68 |
| Joint Bayesian Analysis of Parameters and States in Nonlinear, Non-Gaussian State Space Models |
1 |
1 |
2 |
70 |
2 |
3 |
5 |
55 |
| Likelihood Functions for State Space Models with Diffuse Initial Conditions |
0 |
0 |
1 |
162 |
2 |
3 |
10 |
458 |
| Likelihood-based Analysis for Dynamic Factor Models |
0 |
0 |
4 |
280 |
2 |
5 |
15 |
517 |
| Long Memory Dynamics for Multivariate Dependence under Heavy Tails |
0 |
0 |
3 |
45 |
0 |
2 |
9 |
96 |
| Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks |
0 |
0 |
0 |
128 |
1 |
3 |
3 |
302 |
| Long memory modelling of inflation with stochastic variance and structural breaks |
0 |
0 |
0 |
47 |
1 |
1 |
2 |
171 |
| Low Frequency and Weighted Likelihood Solutions for Mixed Frequency Dynamic Factor Models |
1 |
1 |
3 |
45 |
1 |
2 |
7 |
70 |
| Macro, Industry and Frailty Effects in Defaults: The 2008 Credit Crisis in Perspective |
0 |
1 |
1 |
56 |
1 |
2 |
4 |
138 |
| Maximum Likelihood Estimation for Score-Driven Models |
0 |
1 |
5 |
43 |
3 |
6 |
23 |
120 |
| Maximum Likelihood Estimation for correctly Specified Generalized Autoregressive Score Models: Feedback Effects, Contraction Conditions and Asymptotic Properties |
0 |
0 |
0 |
39 |
4 |
6 |
12 |
77 |
| Maximum Likelihood Estimation of Stochastic Volatility Models |
0 |
0 |
1 |
1,031 |
0 |
2 |
10 |
2,476 |
| Maximum likelihood estimation for dynamic factor models with missing data |
0 |
0 |
1 |
5 |
1 |
3 |
24 |
40 |
| Measuring Asymmetric Stochastic Cycle Components in U.S. Macroeconomic Time Series |
0 |
0 |
2 |
217 |
0 |
4 |
10 |
742 |
| Measuring Financial Cycles in a Model-Based Analysis: Empirical Evidence for the United States and the Euro Area |
0 |
0 |
3 |
77 |
2 |
3 |
13 |
74 |
| Measuring Synchronisation and Convergence of Business Cycles |
0 |
0 |
0 |
359 |
0 |
0 |
1 |
862 |
| Measuring financial cycles with a model-based filter: Empirical evidence for the United States and the euro area |
1 |
3 |
13 |
54 |
2 |
5 |
40 |
131 |
| Messy Time Series: A Unified Approach - (Now published in 'Advances in Econometrics', 13 (1998)pp.103-143.) |
0 |
0 |
0 |
0 |
0 |
0 |
8 |
50 |
| Missing Observations in Observation-Driven Time Series Models |
0 |
1 |
1 |
43 |
4 |
5 |
14 |
38 |
| Model-based Business Cycle and Financial Cycle Decomposition for Europe and the U.S |
0 |
2 |
16 |
79 |
3 |
6 |
32 |
104 |
| Model-based Measurement of Actual Volatility in High-Frequency Data |
0 |
0 |
0 |
230 |
0 |
0 |
3 |
743 |
| Model-based Measurement of Latent Risk in Time Series with Applications |
0 |
0 |
1 |
150 |
0 |
1 |
5 |
658 |
| Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails |
0 |
0 |
2 |
50 |
0 |
1 |
9 |
120 |
| Modeling Trigonometric Seasonal Components for Monthly Economic Time Series |
0 |
0 |
0 |
74 |
3 |
3 |
6 |
217 |
| Modeling the business and financial cycle in a multivariate structural time series model |
1 |
4 |
8 |
42 |
3 |
9 |
43 |
77 |
| Modelling bid-ask spreads in competitive dealership markets |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
9 |
| Models with Time-varying Mean and Variance: A Robust Analysis of U.S. Industrial Production |
0 |
0 |
3 |
65 |
0 |
1 |
15 |
142 |
| Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models |
0 |
1 |
2 |
52 |
1 |
3 |
7 |
118 |
| Multivariate Structural Time Series Models - (Now published in 'System Dynamics in Economic and Financial Models', CHeij, H Schumacher, B Hanzon and C Praagman (eds.) John Wiley & Sons, Chichester (1997), pp.269-298.) |
0 |
0 |
0 |
0 |
3 |
14 |
35 |
57 |
| Nowcasting and Forecasting Economic Growth in the Euro Area using Principal Components |
0 |
0 |
1 |
99 |
0 |
0 |
3 |
68 |
| Nowcasting and forecasting economic growth in the euro area using principal components |
0 |
0 |
2 |
112 |
0 |
0 |
6 |
122 |
| Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models |
0 |
1 |
3 |
70 |
0 |
3 |
6 |
126 |
| Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk |
0 |
0 |
2 |
53 |
0 |
0 |
9 |
121 |
| Observation driven mixed-measurement dynamic factor models with an application to credit risk |
1 |
1 |
6 |
35 |
1 |
3 |
29 |
108 |
| On Importance Sampling for State Space Models |
0 |
0 |
0 |
179 |
0 |
0 |
0 |
511 |
| Optimal Formulations for Nonlinear Autoregressive Processes |
1 |
1 |
2 |
46 |
4 |
7 |
14 |
69 |
| Periodic Heteroskedastic RegARFIMA Models for Daily Electricity Spot Prices |
0 |
0 |
0 |
352 |
0 |
1 |
9 |
936 |
| Periodic Heteroskedastic RegARFIMA models for daily electricity spot prices |
0 |
0 |
1 |
175 |
0 |
1 |
9 |
552 |
| Periodic Seasonal Reg-ARFIMA-GARCH Models for Daily Electricity Spot Prices |
0 |
0 |
9 |
470 |
1 |
3 |
16 |
1,187 |
| Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment |
0 |
0 |
0 |
112 |
1 |
1 |
3 |
306 |
| Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models |
0 |
1 |
4 |
87 |
2 |
4 |
15 |
190 |
| Pro-Cyclicality, Empirical Credit Cycles, and Capital Buffer Formation |
0 |
0 |
2 |
307 |
0 |
0 |
2 |
786 |
| Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model |
0 |
0 |
1 |
75 |
2 |
7 |
12 |
57 |
| Regime switches in the volatility and correlation of financial institutions |
0 |
0 |
1 |
96 |
1 |
1 |
3 |
163 |
| Round-the-Clock Price Discovery for Cross-Listed Stocks: US-Dutch Evidence |
0 |
0 |
2 |
240 |
0 |
0 |
5 |
1,027 |
| Seasonality with Trend and Cycle Interactions in Unobserved Components Models |
0 |
0 |
1 |
210 |
1 |
3 |
6 |
596 |
| Signal Extraction and the Formulation of Unobserved Components Models |
0 |
0 |
0 |
15 |
1 |
1 |
2 |
46 |
| Smooth Dynamic Factor Analysis with an Application to the U.S. Term Structure of Interest Rates |
0 |
0 |
1 |
92 |
1 |
2 |
4 |
192 |
| Spillover Dynamics for Systemic Risk Measurement using Spatial Financial Time Series Models |
0 |
0 |
1 |
58 |
1 |
2 |
6 |
70 |
| Spillover dynamics for systemic risk measurement using spatial financial time series models |
0 |
0 |
0 |
35 |
3 |
4 |
13 |
95 |
| Spline Smoothing over Difficult Regions |
0 |
0 |
1 |
64 |
0 |
2 |
4 |
176 |
| Spot Variance Path Estimation and its Application to High Frequency Jump Testing |
0 |
0 |
1 |
52 |
1 |
2 |
9 |
138 |
| Stationarity and Ergodicity of Univariate Generalized Autoregressive Score Processes |
0 |
0 |
2 |
54 |
0 |
0 |
4 |
109 |
| Statistical Algorithms for Models in State Space Using SsfPack 2.2 |
0 |
0 |
2 |
10 |
4 |
7 |
13 |
61 |
| Stock Index Volatility Forecasting with High Frequency Data |
1 |
2 |
3 |
842 |
3 |
4 |
9 |
2,149 |
| Structural Intervention Time Series Analysis of Crime Rates: The Impact of Sentence Reform in Virginia |
0 |
0 |
1 |
47 |
0 |
0 |
4 |
190 |
| Systemic Risk Diagnostics |
0 |
0 |
0 |
92 |
1 |
1 |
4 |
190 |
| Systemic risk diagnostics: coincident indicators and early warning signals |
0 |
0 |
0 |
144 |
0 |
3 |
20 |
415 |
| Temporal, Spatial, Economic and Crime Factors in Illicit Drug Usage across European Cities |
0 |
0 |
2 |
25 |
2 |
3 |
6 |
40 |
| Testing for Parameter Instability in Competing Modeling Frameworks |
0 |
0 |
2 |
18 |
0 |
1 |
5 |
48 |
| Testing the Assumptions Behind the Use of Importance Sampling |
0 |
0 |
0 |
105 |
3 |
3 |
7 |
477 |
| The Analysis of Stochastic Volatility in the Presence of Daily Realised Measures |
0 |
1 |
3 |
74 |
0 |
2 |
5 |
102 |
| The Dynamic Factor Network Model with an Application to Global Credit-Risk |
0 |
0 |
0 |
12 |
2 |
3 |
3 |
29 |
| The Dynamic Skellam Model with Applications |
0 |
0 |
5 |
22 |
0 |
2 |
12 |
98 |
| The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model |
0 |
0 |
0 |
85 |
0 |
2 |
3 |
211 |
| The Information in Systemic Risk Rankings |
0 |
1 |
2 |
25 |
0 |
1 |
10 |
71 |
| The Modelling and Seasonal Adjustment of Weekly Observations - (Now published in 'Journal of Business and Economic Statistics', 15 (1997), pp.354-368.) |
0 |
0 |
0 |
0 |
0 |
3 |
6 |
20 |
| The Multi-State Latent Factor Intensity Model for Credit Rating Transitions |
1 |
1 |
1 |
226 |
1 |
2 |
3 |
627 |
| The Stochastic Volatility in Mean Model |
0 |
0 |
0 |
486 |
2 |
2 |
5 |
1,072 |
| The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model |
0 |
0 |
3 |
68 |
3 |
5 |
19 |
34 |
| The dynamic factor network model with an application to global credit risk |
0 |
1 |
2 |
38 |
2 |
3 |
5 |
99 |
| The information in systemic risk rankings |
0 |
1 |
3 |
32 |
2 |
9 |
31 |
91 |
| Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives |
0 |
0 |
0 |
14 |
0 |
0 |
2 |
46 |
| Time Series Modelling of Daily Tax Revenues |
0 |
2 |
3 |
324 |
0 |
4 |
7 |
848 |
| Time Series Models with a Common Stochastic Variance for Analysing Economic Time Series |
0 |
0 |
0 |
480 |
0 |
0 |
2 |
1,418 |
| Time Varying Transition Probabilities for Markov Regime Switching Models |
1 |
4 |
11 |
89 |
5 |
14 |
47 |
256 |
| Time-Series Modelling of Daily Tax Revenues |
0 |
0 |
0 |
289 |
0 |
0 |
5 |
1,055 |
| Tracking Growth and the Business Cycle: a Stochastic Common Cycle Model for the Euro Area |
0 |
0 |
0 |
270 |
0 |
1 |
3 |
931 |
| Tracking Growth and the Business Cycle: a Stochastic Common Cycle Model for the Euro Area |
0 |
0 |
0 |
42 |
2 |
3 |
6 |
195 |
| Unobserved Components with Stochastic Volatility in U.S. Inflation: Estimation and Signal Extraction |
1 |
2 |
17 |
72 |
5 |
13 |
49 |
68 |
| Total Working Papers |
16 |
56 |
368 |
19,644 |
165 |
369 |
1,429 |
55,845 |
| Journal Article |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations |
0 |
1 |
3 |
10 |
3 |
6 |
13 |
45 |
| A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations |
0 |
0 |
0 |
49 |
2 |
5 |
16 |
156 |
| A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk |
0 |
0 |
0 |
46 |
3 |
3 |
8 |
175 |
| A dynamic bivariate Poisson model for analysing and forecasting match results in the English Premier League |
1 |
4 |
11 |
21 |
5 |
12 |
30 |
67 |
| A non-Gaussian generalization of the Airline model for robust seasonal adjustment |
0 |
0 |
1 |
64 |
1 |
1 |
3 |
292 |
| Amendments and Corrections |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| An hourly periodic state space model for modelling French national electricity load |
0 |
1 |
1 |
48 |
0 |
1 |
2 |
173 |
| Analyzing the Term Structure of Interest Rates Using the Dynamic Nelson–Siegel Model With Time-Varying Parameters |
0 |
2 |
2 |
31 |
1 |
3 |
7 |
109 |
| Bayesian Dynamic Modeling of High-Frequency Integer Price Changes |
0 |
0 |
1 |
1 |
1 |
1 |
5 |
5 |
| Business and default cycles for credit risk |
2 |
4 |
17 |
437 |
4 |
15 |
54 |
1,142 |
| Computing observation weights for signal extraction and filtering |
0 |
1 |
4 |
150 |
5 |
8 |
22 |
352 |
| Constructing Seasonally Adjusted Data with Time-Varying Confidence Intervals |
0 |
0 |
0 |
49 |
0 |
0 |
3 |
279 |
| Convergence in European GDP series: a multivariate common converging trend-cycle decomposition |
0 |
1 |
1 |
174 |
0 |
2 |
6 |
604 |
| Credit cycles and macro fundamentals |
1 |
2 |
12 |
182 |
3 |
17 |
30 |
510 |
| Detecting shocks: Outliers and breaks in time series |
1 |
3 |
8 |
121 |
2 |
5 |
12 |
314 |
| Diagnostic Checking of Unobserved-Components Time Series Models |
0 |
0 |
0 |
0 |
2 |
3 |
4 |
726 |
| Discussion of ‘MCMC‐based inference’ by R. Paap |
0 |
0 |
0 |
11 |
1 |
1 |
1 |
54 |
| Dynamic Factor Models With Macro, Frailty, and Industry Effects for U.S. Default Counts: The Credit Crisis of 2008 |
0 |
1 |
3 |
23 |
0 |
1 |
11 |
92 |
| Dynamic discrete copula models for high‐frequency stock price changes |
0 |
0 |
1 |
1 |
0 |
4 |
8 |
8 |
| Dynamic factors in periodic time-varying regressions with an application to hourly electricity load modelling |
0 |
0 |
0 |
11 |
1 |
1 |
1 |
38 |
| Economic Trends and Cycles in Crime: A Study for England and Wales |
0 |
0 |
2 |
68 |
1 |
2 |
10 |
222 |
| Empirical Bayes Methods for Dynamic Factor Models |
0 |
0 |
0 |
6 |
2 |
4 |
30 |
59 |
| Empirical credit cycles and capital buffer formation |
0 |
1 |
3 |
138 |
0 |
3 |
9 |
371 |
| Estimating Stochastic Volatility Models: A Comparison of Two Importance Samplers |
0 |
0 |
4 |
171 |
1 |
2 |
9 |
358 |
| Estimating systematic continuous‐time trends in recidivism using a non‐Gaussian panel data model |
0 |
0 |
1 |
16 |
0 |
0 |
4 |
94 |
| Estimation of stochastic volatility models via Monte Carlo maximum likelihood |
0 |
5 |
18 |
451 |
0 |
9 |
33 |
1,005 |
| Exact maximum likelihood estimation for non-stationary periodic time series models |
0 |
0 |
1 |
32 |
1 |
2 |
5 |
169 |
| Exponentionally weighted methods for forecasting intraday time series with multiple seasonal cycles: Comments |
0 |
0 |
0 |
4 |
0 |
0 |
0 |
24 |
| Extracting a robust US business cycle using a time-varying multivariate model-based bandpass filter |
0 |
0 |
1 |
124 |
2 |
5 |
10 |
311 |
| Fast Filtering and Smoothing for Multivariate State Space Models |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
| Filtering and smoothing of state vector for diffuse state-space models |
1 |
2 |
10 |
332 |
1 |
2 |
16 |
610 |
| Forecasting and nowcasting economic growth in the euro area using factor models |
0 |
0 |
2 |
14 |
2 |
2 |
12 |
42 |
| Forecasting daily time series using periodic unobserved components time series models |
0 |
0 |
0 |
49 |
1 |
1 |
1 |
130 |
| Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements |
0 |
2 |
13 |
316 |
6 |
16 |
60 |
891 |
| Forecasting football match results in national league competitions using score-driven time series models |
0 |
1 |
1 |
1 |
4 |
11 |
17 |
17 |
| Forecasting interest rates with shifting endpoints |
0 |
1 |
3 |
22 |
1 |
2 |
5 |
72 |
| Forecasting macroeconomic variables using collapsed dynamic factor analysis |
0 |
1 |
2 |
32 |
1 |
3 |
12 |
100 |
| Forecasting the US term structure of interest rates using a macroeconomic smooth dynamic factor model |
0 |
0 |
1 |
17 |
0 |
1 |
3 |
67 |
| GENERALIZED AUTOREGRESSIVE SCORE MODELS WITH APPLICATIONS |
0 |
1 |
7 |
66 |
1 |
3 |
30 |
209 |
| Generalized dynamic panel data models with random effects for cross-section and time |
0 |
0 |
0 |
40 |
1 |
5 |
5 |
196 |
| Global Credit Risk: World, Country and Industry Factors |
0 |
0 |
1 |
3 |
1 |
2 |
13 |
23 |
| In-sample confidence bands and out-of-sample forecast bands for time-varying parameters in observation-driven models |
1 |
1 |
3 |
6 |
1 |
1 |
9 |
30 |
| Information-theoretic optimality of observation-driven time series models for continuous responses |
0 |
1 |
4 |
9 |
2 |
3 |
7 |
28 |
| Interaction between structural and cyclical shocks in production and employment |
0 |
0 |
0 |
19 |
0 |
0 |
2 |
57 |
| Intervention time series analysis of crime rates: The case of sentence reform in Virginia |
0 |
0 |
4 |
19 |
3 |
8 |
23 |
85 |
| Intraday Stochastic Volatility in Discrete Price Changes: The Dynamic Skellam Model |
0 |
0 |
0 |
0 |
0 |
2 |
3 |
3 |
| Joint Bayesian Analysis of Parameters and States in Nonlinear non‐Gaussian State Space Models |
1 |
2 |
2 |
2 |
2 |
3 |
7 |
13 |
| Kalman filtering and smoothing for model‐based signal extraction that depend on time‐varying spectra |
0 |
0 |
0 |
32 |
0 |
0 |
2 |
105 |
| Likelihood functions for state space models with diffuse initial conditions |
0 |
2 |
2 |
23 |
0 |
2 |
4 |
80 |
| Likelihood‐based dynamic factor analysis for measurement and forecasting |
0 |
0 |
0 |
11 |
1 |
1 |
6 |
45 |
| Long memory dynamics for multivariate dependence under heavy tails |
0 |
0 |
4 |
11 |
0 |
1 |
13 |
63 |
| Long memory with stochastic variance model: A recursive analysis for US inflation |
0 |
0 |
0 |
8 |
1 |
1 |
5 |
34 |
| Maximum likelihood estimation for dynamic factor models with missing data |
1 |
1 |
4 |
97 |
3 |
4 |
22 |
257 |
| Measuring Synchronization and Convergence of Business Cycles for the Euro area, UK and US* |
1 |
2 |
3 |
138 |
1 |
4 |
9 |
302 |
| Measuring financial cycles in a model-based analysis: Empirical evidence for the United States and the euro area |
1 |
3 |
6 |
35 |
3 |
6 |
21 |
95 |
| Model-based measurement of latent risk in time series with applications |
0 |
0 |
0 |
26 |
1 |
4 |
5 |
108 |
| Modeling Around-the-Clock Price Discovery for Cross-Listed Stocks Using State Space Methods |
1 |
2 |
2 |
66 |
2 |
3 |
9 |
163 |
| Modeling frailty-correlated defaults using many macroeconomic covariates |
0 |
0 |
2 |
58 |
2 |
3 |
12 |
215 |
| Modelling trigonometric seasonal components for monthly economic time series |
0 |
0 |
1 |
49 |
0 |
0 |
4 |
239 |
| Modified efficient importance sampling for partially non‐Gaussian state space models |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
| Monte Carlo Estimation for Nonlinear Non-Gaussian State Space Models |
0 |
0 |
6 |
96 |
0 |
0 |
14 |
198 |
| Monte Carlo Likelihood Estimation for Three Multivariate Stochastic Volatility Models |
0 |
0 |
2 |
69 |
0 |
0 |
6 |
179 |
| Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models |
0 |
0 |
1 |
4 |
3 |
4 |
7 |
28 |
| Multivariate non‐linear time series modelling of exposure and risk in road safety research |
0 |
0 |
0 |
13 |
0 |
0 |
0 |
56 |
| Nowcasting and forecasting global financial sector stress and credit market dislocation |
0 |
0 |
1 |
16 |
3 |
3 |
7 |
60 |
| Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State-Space Models |
0 |
0 |
2 |
14 |
0 |
2 |
7 |
40 |
| Observation-Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk |
0 |
0 |
4 |
24 |
2 |
6 |
34 |
124 |
| Periodic Seasonal Reg-ARFIMAGARCH Models for Daily Electricity Spot Prices |
0 |
0 |
0 |
106 |
1 |
2 |
3 |
265 |
| Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment* |
0 |
0 |
0 |
20 |
0 |
0 |
2 |
92 |
| Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models |
0 |
0 |
1 |
10 |
1 |
2 |
13 |
54 |
| Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model |
2 |
3 |
4 |
4 |
2 |
8 |
9 |
9 |
| SMOOTH DYNAMIC FACTOR ANALYSIS WITH APPLICATION TO THE US TERM STRUCTURE OF INTEREST RATES |
0 |
0 |
0 |
6 |
1 |
1 |
2 |
25 |
| Seasonality with trend and cycle interactions in unobserved components models |
0 |
0 |
0 |
35 |
0 |
0 |
2 |
123 |
| Signal extraction and the formulation of unobserved components models |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
1,448 |
| Special Issue on Nonlinear Modelling and Financial Econometrics |
0 |
0 |
1 |
30 |
0 |
1 |
2 |
81 |
| Spillover dynamics for systemic risk measurement using spatial financial time series models |
0 |
0 |
0 |
6 |
1 |
3 |
12 |
59 |
| Spot Variance Path Estimation and Its Application to High-Frequency Jump Testing |
0 |
0 |
1 |
27 |
0 |
1 |
7 |
100 |
| State Space Models With a Common Stochastic Variance |
0 |
0 |
0 |
111 |
0 |
1 |
1 |
185 |
| Statistical Software for State Space Methods |
0 |
0 |
1 |
23 |
1 |
2 |
8 |
142 |
| Statistical algorithms for models in state space using SsfPack 2.2 |
0 |
0 |
0 |
1 |
3 |
6 |
19 |
1,215 |
| Testing for Parameter Instability across Different Modeling Frameworks |
1 |
1 |
1 |
3 |
2 |
2 |
5 |
13 |
| Testing the assumptions behind importance sampling |
1 |
1 |
2 |
60 |
1 |
1 |
5 |
240 |
| The Analysis of Stochastic Volatility in the Presence of Daily Realized Measures |
0 |
0 |
0 |
28 |
0 |
0 |
5 |
91 |
| The Modeling and Seasonal Adjustment of Weekly Observations |
0 |
0 |
0 |
0 |
3 |
9 |
35 |
848 |
| The information in systemic risk rankings |
1 |
1 |
1 |
11 |
2 |
3 |
13 |
50 |
| The multi-state latent factor intensity model for credit rating transitions |
0 |
0 |
7 |
128 |
0 |
3 |
15 |
382 |
| The stochastic volatility in mean model: empirical evidence from international stock markets |
0 |
0 |
5 |
461 |
2 |
4 |
24 |
1,376 |
| The stochastic volatility in mean model: empirical evidence from international stock markets |
0 |
0 |
0 |
0 |
2 |
2 |
2 |
2 |
| Time Series Modelling of Daily Tax Revenues |
0 |
0 |
0 |
31 |
0 |
1 |
1 |
100 |
| Time series analysis of non‐Gaussian observations based on state space models from both classical and Bayesian perspectives |
1 |
1 |
1 |
168 |
1 |
1 |
9 |
357 |
| Time-Varying Transition Probabilities for Markov Regime Switching Models |
0 |
0 |
2 |
5 |
2 |
5 |
12 |
19 |
| Tracking the Business Cycle of the Euro Area: A Multivariate Model-Based Bandpass Filter |
0 |
1 |
3 |
164 |
0 |
3 |
10 |
329 |
| Weighted maximum likelihood for dynamic factor analysis and forecasting with mixed frequency data |
0 |
2 |
4 |
20 |
4 |
6 |
22 |
80 |
| Total Journal Articles |
18 |
58 |
222 |
5,638 |
119 |
293 |
1,000 |
20,406 |
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