| Working Paper |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Comparison of Biased Simulation Schemes for Stochastic Volatility Models |
0 |
0 |
6 |
378 |
1 |
1 |
18 |
974 |
| A Multi-Level Panel Smooth Transition Autoregression for US Sectoral Production |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
436 |
| A Multivariate STAR Analysis of the Relationship Between Money and Output |
0 |
0 |
0 |
252 |
4 |
7 |
9 |
649 |
| A Multivariate STAR Analysis of the Relationship Between Money and Output |
0 |
0 |
0 |
355 |
1 |
1 |
3 |
824 |
| A Recommitment Strategy for Long Term Private Equity Fund Investors |
0 |
0 |
4 |
128 |
1 |
3 |
11 |
381 |
| A multi-level panel smooth transition autoregression for US sectoral production |
0 |
0 |
1 |
37 |
0 |
1 |
3 |
106 |
| A multivariate STAR analysis of the relationship between money and output |
0 |
0 |
2 |
120 |
2 |
3 |
14 |
287 |
| A nonlinear long memory model for US unemployment |
0 |
0 |
2 |
41 |
2 |
2 |
7 |
91 |
| A simple test for PPP among traded goods |
0 |
0 |
1 |
11 |
0 |
0 |
4 |
60 |
| A unified approach to nonlinearity, structural change and outliers |
0 |
0 |
3 |
45 |
0 |
0 |
7 |
115 |
| An Alternative Bayesian Approach to Structural Breaks in Time Series Models |
0 |
0 |
1 |
75 |
1 |
1 |
6 |
147 |
| Are statistical reporting agencies getting it right? Data rationality and business cycle asymmetry |
0 |
1 |
1 |
26 |
0 |
2 |
2 |
77 |
| Asymmetric and Common Absorption of Shocks in Nonlinear Autoregressive Models |
0 |
0 |
1 |
98 |
1 |
1 |
3 |
285 |
| Asymmetric and Common Abssorbtion of Shocks in Nonlinear Autoregressive Models |
0 |
0 |
0 |
27 |
1 |
1 |
2 |
237 |
| Asymmetric and common absorption of shocks in nonlinear autoregressive models |
0 |
1 |
2 |
24 |
1 |
2 |
4 |
69 |
| Bayesian Forecasting of Federal Funds Target Rate Decisions |
0 |
0 |
0 |
23 |
4 |
11 |
110 |
267 |
| Bayesian Model Averaging in the Presence of Structural Breaks |
1 |
2 |
2 |
33 |
2 |
4 |
24 |
110 |
| Changes in International Business Cycle Affiliations |
0 |
0 |
0 |
72 |
1 |
2 |
5 |
267 |
| Changes in International Business Cycle Affiliations |
0 |
0 |
0 |
28 |
1 |
2 |
4 |
81 |
| Changes in Variability of the Business Cycle in the G7 Countries |
0 |
0 |
0 |
129 |
1 |
1 |
1 |
406 |
| Changes in variability of the business cycle in the G7 countries |
0 |
0 |
0 |
13 |
1 |
1 |
2 |
71 |
| Changes in variability of the business cycle in the G7 countries |
0 |
0 |
0 |
65 |
1 |
1 |
1 |
252 |
| Cointegration in a historical perspective |
0 |
0 |
2 |
109 |
1 |
1 |
6 |
119 |
| Comparing the Accuracy of Copula-Based Multivariate Density Forecasts in Selected Regions of Support |
0 |
0 |
1 |
40 |
0 |
0 |
4 |
75 |
| Contagion as Domino Effect in Global Stock Markets |
0 |
0 |
1 |
95 |
1 |
2 |
7 |
260 |
| Corporate Governance and the Cost of Debt of Large European Firms |
0 |
2 |
4 |
89 |
1 |
4 |
13 |
217 |
| Corporate Governance and the Value of Excess Cash Holdings of Large European Firms |
0 |
3 |
4 |
86 |
2 |
6 |
9 |
281 |
| Do We Often Find ARCH Because Of Neglected Outliers? |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
36 |
| Do leading indicators lead peaks more than troughs? |
0 |
0 |
1 |
91 |
0 |
0 |
10 |
216 |
| Does Africa grow slower than Asia and Latin America? |
0 |
0 |
0 |
12 |
3 |
4 |
4 |
47 |
| Does the absence of cointegration explain the typical findings in long horizon regressions? |
0 |
0 |
1 |
59 |
1 |
2 |
7 |
182 |
| Dynamic Factor Models for the Volatility Surface |
0 |
0 |
2 |
43 |
2 |
3 |
6 |
85 |
| Evaluating real-time forecasts in real-time |
0 |
0 |
1 |
15 |
2 |
2 |
8 |
63 |
| Financial Development and Convergence Clubs |
0 |
1 |
2 |
50 |
0 |
2 |
8 |
137 |
| Forecast comparison of principal component regression and principal covariate regression |
0 |
0 |
1 |
45 |
1 |
1 |
3 |
151 |
| Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices |
0 |
0 |
0 |
79 |
0 |
0 |
5 |
98 |
| Forecasting Interest Rates with Shifting Endpoints |
0 |
0 |
1 |
73 |
0 |
2 |
9 |
174 |
| Forecasting US Inflation Using Model Averaging |
0 |
0 |
0 |
2 |
1 |
1 |
12 |
807 |
| Forecasting Value-at-Risk under Temporal and Portfolio Aggregation |
0 |
0 |
4 |
32 |
0 |
2 |
10 |
47 |
| Forecasting Volatility with Copula-Based Time Series Models |
1 |
1 |
1 |
194 |
1 |
2 |
9 |
386 |
| Forecasting Volatility with the Realized Range in the Presence of Noise and Non-Trading |
0 |
0 |
1 |
18 |
0 |
0 |
3 |
88 |
| Forecasting aggregates using panels of nonlinear time series |
0 |
0 |
0 |
18 |
1 |
1 |
2 |
69 |
| Forecasting business cycles |
0 |
0 |
0 |
0 |
1 |
1 |
3 |
23 |
| Forecasting industrial production with linear, nonlinear, and structural change models |
0 |
0 |
2 |
59 |
0 |
0 |
6 |
149 |
| Forecasting the Yield Curve in a Data-Rich Environment using the Factor-Augmented Nelson-Siegel Model |
0 |
1 |
1 |
117 |
1 |
5 |
9 |
164 |
| Forecasting volatility with switching persistence GARCH models |
0 |
0 |
1 |
20 |
0 |
0 |
3 |
54 |
| Getting the Most out of Macroeconomic Information for Predicting Stock Returns and Volatility |
0 |
1 |
3 |
185 |
0 |
2 |
7 |
226 |
| Good News is No News |
0 |
0 |
1 |
31 |
0 |
0 |
5 |
81 |
| High-Frequency Technical Trading: The Importance of Speed |
0 |
0 |
8 |
72 |
3 |
3 |
17 |
167 |
| How to Identify and Forecast Bull and Bear Markets? |
0 |
2 |
4 |
204 |
1 |
5 |
15 |
208 |
| Identifying Changes in Mean, Seasonality, Persistence and Volatility for G7 and Euro Area Inflation |
0 |
0 |
1 |
83 |
0 |
1 |
4 |
256 |
| Improved Construction of diffusion indexes for macroeconomic forecasting |
0 |
0 |
2 |
23 |
2 |
2 |
8 |
71 |
| Improving Density Forecasts and Value-at-Risk Estimates by Combining Densities |
0 |
0 |
0 |
64 |
1 |
1 |
2 |
62 |
| Likelihood-based scoring rules for comparing density forecasts in tails |
0 |
0 |
0 |
6 |
1 |
1 |
8 |
38 |
| Linear models, smooth transition autoregressions and neural networks for forecasting macroeconomic time series: A reexamination |
0 |
0 |
1 |
757 |
0 |
0 |
9 |
1,440 |
| Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination |
0 |
0 |
0 |
240 |
2 |
4 |
11 |
1,465 |
| Macroeconomic Crisis and Individual Firm Performance: The Mexican Experience |
0 |
0 |
0 |
140 |
0 |
0 |
0 |
555 |
| Macroeconomic forecasting with real-time data: an empirical comparison |
0 |
0 |
2 |
78 |
0 |
0 |
3 |
104 |
| Market Set-Up in Advance of Federal Reserve Policy Decisions |
0 |
0 |
0 |
36 |
1 |
1 |
3 |
91 |
| Measuring and Predicting Heterogeneous Recessions |
0 |
0 |
0 |
72 |
1 |
2 |
5 |
247 |
| Measuring and Predicting Heterogeneous Recessions |
1 |
1 |
2 |
30 |
2 |
4 |
6 |
78 |
| Measuring volatility with the realized range |
0 |
5 |
12 |
61 |
0 |
7 |
26 |
176 |
| Modeling and Estimation of Synchronization in Multistate Markov-Switching Models |
1 |
2 |
3 |
83 |
1 |
3 |
9 |
194 |
| Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity |
0 |
0 |
3 |
799 |
1 |
1 |
12 |
2,316 |
| Modeling asymmetric volatility in weekly Dutch temperature data |
0 |
0 |
0 |
21 |
1 |
1 |
4 |
58 |
| Modeling regional house prices |
1 |
1 |
4 |
150 |
2 |
4 |
16 |
265 |
| Modelling Multiple Regimes in the Business Cycle |
0 |
0 |
2 |
44 |
1 |
1 |
6 |
119 |
| New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels |
0 |
0 |
1 |
34 |
0 |
1 |
6 |
56 |
| Nonlinear Error-Correction Models for Interest Rates in The Netherlands |
0 |
0 |
6 |
49 |
1 |
4 |
17 |
106 |
| Nonlinear Forecasting With Many Predictors Using Kernel Ridge Regression |
0 |
0 |
1 |
165 |
3 |
4 |
11 |
441 |
| Nonlinear Forecasting with Many Predictors using Kernel Ridge Regression |
0 |
0 |
0 |
98 |
0 |
0 |
3 |
202 |
| Nonlinearities and outliers: robust specification of STAR models |
0 |
0 |
1 |
38 |
0 |
1 |
3 |
84 |
| On the Effects of Private Information on Volatility |
0 |
0 |
0 |
40 |
1 |
2 |
4 |
118 |
| On the Effects of Private Information on Volatility |
0 |
0 |
0 |
15 |
1 |
1 |
4 |
87 |
| Out-of-sample Comparison of Copula Specifications in Multivariate Density Forecasts |
0 |
0 |
0 |
98 |
0 |
0 |
4 |
290 |
| Out-of-sample comparison of copula specifications in multivariate density forecasts |
0 |
0 |
1 |
2 |
1 |
1 |
5 |
20 |
| Out-of-sample comparison of copula specifications in multivariate density forecasts |
0 |
0 |
1 |
56 |
0 |
0 |
4 |
152 |
| Out-of-sample comparison of copula specifications in multivariate density forecasts |
0 |
1 |
2 |
62 |
1 |
2 |
4 |
165 |
| Outlier detection in the GARCH (1,1) model |
0 |
0 |
1 |
24 |
3 |
3 |
7 |
84 |
| Panel Smooth Transition Regression Models |
11 |
26 |
131 |
2,478 |
40 |
116 |
560 |
6,674 |
| Panel Smooth Transition Regression Models |
5 |
9 |
29 |
650 |
11 |
21 |
92 |
1,735 |
| Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails |
0 |
1 |
3 |
64 |
0 |
1 |
5 |
198 |
| Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails |
0 |
0 |
0 |
37 |
0 |
0 |
2 |
188 |
| Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails |
0 |
0 |
0 |
65 |
1 |
1 |
3 |
207 |
| Predicting Covariance Matrices with Financial Conditions Indexes |
0 |
0 |
1 |
11 |
1 |
1 |
5 |
58 |
| Predicting Growth Cycle Regimes for European Countries |
1 |
1 |
1 |
142 |
2 |
2 |
4 |
421 |
| Predicting the Daily Covariance Matrix for S&P 100 Stocks using Intraday Data - But which Frequency to use? |
0 |
1 |
2 |
360 |
2 |
3 |
8 |
1,262 |
| Predicting the Term Structure of Interest Rates: Incorporating Parameter Uncertainty, Model Uncertainty and Macroeconomic Information |
0 |
0 |
1 |
350 |
1 |
4 |
11 |
862 |
| Predicting the term structure of interest rates incorporating parameter uncertainty, model uncertainty and macroeconomic information |
0 |
0 |
1 |
139 |
1 |
1 |
11 |
343 |
| Range-based covariance estimation using high-frequency data: The realized co-range |
0 |
0 |
5 |
84 |
0 |
0 |
7 |
189 |
| Realized mixed-frequency factor models for vast dimensional covariance estimation |
0 |
0 |
1 |
56 |
0 |
4 |
8 |
103 |
| SETS, Arbitrage Activity, and Stock Price Dynamics |
0 |
0 |
0 |
310 |
3 |
4 |
4 |
1,372 |
| Seasonal smooth transition autoregression |
0 |
0 |
3 |
26 |
1 |
1 |
7 |
97 |
| Selecting a Nonlinear Time Series Model using Weighted Tests of Equal Forecast Accuracy |
0 |
0 |
0 |
12 |
1 |
1 |
5 |
54 |
| Semi-Parametric Modelling of Correlation Dynamics |
0 |
1 |
2 |
54 |
1 |
3 |
5 |
117 |
| Short Patches of Outliers, ARCH and Volatility Modeling |
0 |
0 |
0 |
279 |
0 |
0 |
0 |
995 |
| Short-term Volatility Versus Long-term Growth: Evidence in US Macroeconomic Time Series |
0 |
0 |
0 |
57 |
1 |
1 |
6 |
271 |
| Short-term Volatility versus Long-term Growth: Evidence in US Macroeconomic Time Series |
0 |
0 |
0 |
97 |
2 |
2 |
7 |
673 |
| Short-term Volatility versus Long-term Growth: Evidence in US Macroeconomic Time Series |
0 |
0 |
0 |
134 |
0 |
1 |
2 |
442 |
| Short-term volatility versus long-term growth: evidence in US macroeconomic time series |
0 |
0 |
0 |
7 |
2 |
3 |
4 |
63 |
| Smooth Transition Autoregressive Models - A Survey of Recent Developments |
0 |
0 |
6 |
1,778 |
1 |
4 |
26 |
3,268 |
| Smooth transition autoregressive models - A survey of recent developments |
1 |
5 |
13 |
414 |
2 |
8 |
33 |
721 |
| Speed, Algorithmic Trading, and Market Quality around Macroeconomic News Announcements |
0 |
1 |
1 |
59 |
0 |
2 |
5 |
145 |
| Stock Selection Strategies in Emerging Markets |
2 |
3 |
7 |
784 |
3 |
7 |
21 |
1,851 |
| Structural Breaks in the International Transmission of Inflation |
0 |
0 |
0 |
210 |
1 |
2 |
3 |
459 |
| Structural Differences in Economic Growth |
0 |
1 |
1 |
117 |
0 |
3 |
6 |
244 |
| Term structure forecasting using macro factors and forecast combination |
0 |
1 |
1 |
90 |
1 |
4 |
11 |
231 |
| Term structure forecasting using macro factors and forecast combination |
0 |
0 |
1 |
150 |
1 |
2 |
9 |
301 |
| Testing for ARCH in the Presence of Additive Outliers |
0 |
0 |
0 |
25 |
1 |
1 |
6 |
117 |
| Testing for Smooth Transition Nonlinearity in the Presence of Outliers |
0 |
0 |
2 |
41 |
0 |
0 |
5 |
104 |
| Testing for Stochastic Unit Roots - Some Monte Carlo evidence |
0 |
0 |
0 |
14 |
1 |
1 |
3 |
39 |
| Testing for Volatility Changes in US Macroeconomic Time Series |
1 |
1 |
2 |
323 |
1 |
2 |
7 |
778 |
| Testing for causality in variance in the presence of breaks |
0 |
0 |
0 |
152 |
0 |
0 |
4 |
346 |
| Testing for causality in variance in the presence of breaks |
0 |
0 |
0 |
15 |
1 |
2 |
2 |
66 |
| Testing for changes in volatility in heteroskedastic time series - a further examination |
0 |
1 |
3 |
49 |
4 |
6 |
18 |
159 |
| The Economic Value of Fundamental and Technical Information in Emerging Currency Markets |
0 |
0 |
0 |
205 |
1 |
3 |
7 |
444 |
| The Effects of Federal Funds Target Rate Changes on S&P100 Stock Returns, Volatilities, and Correlations |
0 |
0 |
1 |
288 |
0 |
0 |
3 |
538 |
| The Euro Introduction and Non-Euro Currencies |
0 |
0 |
0 |
211 |
0 |
2 |
7 |
858 |
| The Inefficient Use of Macroeconomic Information in Analysts' Earnings Forecasts in Emerging Markets |
0 |
0 |
1 |
79 |
0 |
0 |
2 |
197 |
| The Success Of Stock Selection Strategies In Emerging Markets: Is It Risk Or Behavioral Bias? |
0 |
1 |
3 |
145 |
0 |
2 |
8 |
421 |
| The effects of institutional and technological change and business cycle fluctiations on seasonal patterns in quarterly industrial production series |
1 |
1 |
1 |
11 |
3 |
4 |
15 |
80 |
| The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series |
0 |
0 |
0 |
201 |
0 |
0 |
2 |
957 |
| The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production |
0 |
0 |
0 |
22 |
0 |
1 |
2 |
67 |
| Time Variation in Asset Return Dependence: Strength or Structure? |
0 |
0 |
1 |
45 |
0 |
3 |
7 |
121 |
| Time series forecasting by principal covariate regression |
0 |
0 |
0 |
83 |
0 |
1 |
4 |
275 |
| Time-Varying Smooth Transition Autoregressive Models |
0 |
0 |
0 |
175 |
3 |
8 |
18 |
2,080 |
| Timing of Vote Decision in First and Second Order Dutch Elections 1978-1995: Evidence from Artificial Neural Networks |
0 |
0 |
0 |
16 |
0 |
0 |
1 |
57 |
| Unit root tests and assymmetric adjustment |
0 |
0 |
0 |
6 |
1 |
1 |
5 |
33 |
| When Do Managers Seek Private Equity Backing in Public-to-Private Transactions? |
0 |
0 |
0 |
3 |
0 |
1 |
4 |
29 |
| When Do Managers Seek Private Equity Backing in Public-to-Private Transactions? |
0 |
0 |
1 |
145 |
0 |
2 |
5 |
459 |
| Why do Pit-Hours outlive the Pit? |
0 |
0 |
0 |
6 |
0 |
0 |
0 |
32 |
| Total Working Papers |
27 |
79 |
344 |
18,464 |
171 |
392 |
1,652 |
51,943 |
| Journal Article |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A comparison of biased simulation schemes for stochastic volatility models |
0 |
0 |
0 |
62 |
0 |
0 |
2 |
250 |
| A multi-level panel STAR model for US manufacturing sectors |
1 |
1 |
4 |
363 |
1 |
2 |
14 |
967 |
| A nonlinear long memory model, with an application to US unemployment |
0 |
1 |
1 |
122 |
0 |
1 |
5 |
297 |
| A simple test for PPP among traded goods |
0 |
0 |
1 |
93 |
0 |
0 |
2 |
278 |
| A unified approach to nonlinearity, structural change, and outliers |
0 |
0 |
2 |
158 |
0 |
3 |
14 |
345 |
| Absorption of shocks in nonlinear autoregressive models |
0 |
0 |
0 |
45 |
0 |
0 |
1 |
111 |
| Are Statistical Reporting Agencies Getting It Right? Data Rationality and Business Cycle Asymmetry |
0 |
0 |
0 |
66 |
0 |
0 |
1 |
275 |
| Bayesian forecasting of federal funds target rate decisions |
0 |
0 |
0 |
14 |
2 |
4 |
8 |
121 |
| Can Tests for Stochastic Unit Roots Provide Useful Portmanteau Tests for Persistence? |
0 |
0 |
0 |
38 |
1 |
2 |
3 |
161 |
| Cointegration in a historical perspective |
0 |
0 |
0 |
20 |
2 |
2 |
5 |
107 |
| Comparing the accuracy of multivariate density forecasts in selected regions of the copula support |
0 |
0 |
0 |
8 |
0 |
0 |
4 |
45 |
| Contagion as a domino effect in global stock markets |
0 |
1 |
5 |
73 |
0 |
3 |
22 |
311 |
| Corporate Governance and Performance during the Aftermath of the 1994 Mexican Crisis |
0 |
0 |
1 |
11 |
0 |
0 |
7 |
54 |
| Crisis macroeconómica y desempeño de la empresa individual. La experiencia mexicana |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
228 |
| Do Leading Indicators Lead Peaks More Than Troughs? |
0 |
0 |
0 |
56 |
0 |
0 |
6 |
213 |
| Does Africa grow slower than Asia, Latin America and the Middle East? Evidence from a new data-based classification method |
1 |
2 |
5 |
150 |
3 |
4 |
14 |
341 |
| Forecast comparison of principal component regression and principal covariate regression |
0 |
0 |
0 |
69 |
0 |
0 |
2 |
194 |
| Forecasting S&P 500 volatility: Long memory, level shifts, leverage effects, day-of-the-week seasonality, and macroeconomic announcements |
0 |
1 |
6 |
155 |
3 |
6 |
19 |
381 |
| Forecasting aggregates using panels of nonlinear time series |
0 |
0 |
1 |
63 |
1 |
2 |
5 |
158 |
| Forecasting day-ahead electricity prices: Utilizing hourly prices |
0 |
1 |
4 |
31 |
0 |
3 |
22 |
96 |
| Forecasting returns and risk in financial markets using linear and nonlinear models |
0 |
0 |
0 |
94 |
0 |
0 |
2 |
209 |
| Forecasting the Yield Curve in a Data‐Rich Environment Using the Factor‐Augmented Nelson–Siegel Model |
0 |
0 |
0 |
0 |
1 |
4 |
8 |
48 |
| Forecasting volatility with the realized range in the presence of noise and non-trading |
0 |
0 |
0 |
8 |
0 |
0 |
4 |
50 |
| Forecasting with Leading Indicators by means of the Principal Covariate Index |
1 |
1 |
1 |
18 |
2 |
2 |
5 |
77 |
| Getting the most out of macroeconomic information for predicting excess stock returns |
0 |
1 |
8 |
16 |
1 |
5 |
22 |
50 |
| Identifying Changes in Mean, Seasonality, Persistence and Volatility for G7 and Euro Area Inflation |
0 |
0 |
2 |
21 |
0 |
0 |
4 |
72 |
| Instability and Nonlinearity in the Euro-Area Phillips Curve |
1 |
1 |
5 |
73 |
1 |
1 |
11 |
210 |
| Likelihood-based scoring rules for comparing density forecasts in tails |
0 |
2 |
8 |
77 |
1 |
4 |
13 |
241 |
| Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination |
0 |
0 |
2 |
285 |
0 |
2 |
12 |
588 |
| MULTIVARIATE STAR ANALYSIS OF MONEY OUTPUT RELATIONSHIP |
0 |
0 |
2 |
44 |
1 |
1 |
4 |
129 |
| Macroeconomic forecasting with matched principal components |
1 |
1 |
1 |
44 |
1 |
3 |
3 |
186 |
| Market Set‐up in Advance of Federal Reserve Policy Rate Decisions |
0 |
0 |
0 |
0 |
2 |
2 |
2 |
14 |
| Measuring and predicting heterogeneous recessions |
0 |
0 |
0 |
15 |
2 |
2 |
2 |
88 |
| Measuring volatility with the realized range |
2 |
6 |
14 |
193 |
2 |
7 |
27 |
540 |
| Modelling regional house prices |
0 |
0 |
0 |
28 |
0 |
1 |
3 |
88 |
| Nonlinear forecasting with many predictors using kernel ridge regression |
0 |
0 |
0 |
6 |
1 |
1 |
7 |
39 |
| On SETAR non-linearity and forecasting |
0 |
0 |
1 |
201 |
1 |
3 |
6 |
635 |
| On the dynamics of business cycle analysis: editors' introduction |
0 |
0 |
1 |
56 |
0 |
0 |
1 |
206 |
| Order flow and volatility: An empirical investigation |
0 |
0 |
0 |
10 |
0 |
3 |
9 |
56 |
| Out-of-sample comparison of copula specifications in multivariate density forecasts |
0 |
2 |
4 |
28 |
3 |
8 |
19 |
130 |
| Paul D. McNelis, Neural networks in finance--gaining predictive edge in the market, Elsevier Academic Press (2005) ISBN 0-12-485967-4 hardcover, 243 pages |
0 |
0 |
6 |
200 |
0 |
0 |
14 |
625 |
| Predicting the Daily Covariance Matrix for S&P 100 Stocks Using Intraday Data—But Which Frequency to Use? |
0 |
1 |
3 |
170 |
1 |
2 |
8 |
652 |
| Predicting volatility and correlations with Financial Conditions Indexes |
0 |
0 |
2 |
11 |
1 |
4 |
13 |
50 |
| Range-Based Covariance Estimation Using High-Frequency Data: The Realized Co-Range -super-* |
0 |
0 |
0 |
26 |
1 |
1 |
2 |
108 |
| Real-time macroeconomic forecasting with leading indicators: An empirical comparison |
0 |
0 |
2 |
8 |
0 |
0 |
5 |
40 |
| Real-time macroeconomic forecasting with leading indicators: An empirical comparison |
0 |
0 |
1 |
29 |
3 |
4 |
12 |
213 |
| Reply |
0 |
0 |
1 |
24 |
1 |
1 |
4 |
73 |
| SMOOTH TRANSITION AUTOREGRESSIVE MODELS — A SURVEY OF RECENT DEVELOPMENTS |
1 |
3 |
20 |
2,341 |
5 |
17 |
81 |
4,441 |
| Sample size, lag order and critical values of seasonal unit root tests |
0 |
0 |
0 |
21 |
0 |
0 |
2 |
101 |
| Short patches of outliers, ARCH and volatility modelling |
0 |
0 |
0 |
36 |
0 |
0 |
2 |
200 |
| Speed, algorithmic trading, and market quality around macroeconomic news announcements |
0 |
5 |
8 |
53 |
2 |
9 |
29 |
196 |
| Stock selection strategies in emerging markets |
2 |
3 |
6 |
238 |
8 |
9 |
22 |
688 |
| Structural Breaks in the International Dynamics of Inflation |
0 |
1 |
9 |
51 |
0 |
1 |
18 |
158 |
| Structural differences in economic growth: an endogenous clustering approach |
1 |
1 |
2 |
40 |
3 |
4 |
6 |
155 |
| Testing for ARCH in the Presence of Additive Outliers |
0 |
0 |
3 |
212 |
0 |
2 |
11 |
760 |
| Testing for Smooth Transition Nonlinearity in the Presence of Outliers |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
490 |
| Testing for Volatility Changes in U.S. Macroeconomic Time Series |
0 |
0 |
5 |
277 |
1 |
1 |
16 |
706 |
| Testing for causality in variance in the presence of breaks |
0 |
0 |
3 |
65 |
1 |
1 |
6 |
192 |
| The economic value of fundamental and technical information in emerging currency markets |
0 |
2 |
3 |
159 |
0 |
6 |
26 |
426 |
| The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series |
0 |
0 |
0 |
84 |
4 |
4 |
7 |
449 |
| The euro introduction and noneuro currencies |
0 |
0 |
1 |
36 |
1 |
4 |
5 |
177 |
| The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production |
0 |
0 |
0 |
66 |
1 |
1 |
2 |
234 |
| The success of stock selection strategies in emerging markets: Is it risk or behavioral bias? |
1 |
2 |
3 |
71 |
2 |
3 |
8 |
202 |
| Time-Varying Smooth Transition Autoregressive Models |
0 |
0 |
0 |
8 |
1 |
1 |
8 |
1,644 |
| Twenty years of cointegration |
0 |
0 |
0 |
39 |
0 |
0 |
2 |
81 |
| When Do Managers Seek Private Equity Backing in Public-to-Private Transactions? |
1 |
1 |
2 |
23 |
1 |
3 |
14 |
76 |
| Total Journal Articles |
13 |
40 |
159 |
7,102 |
69 |
159 |
645 |
21,726 |
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