| Working Paper |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Coupled Component GARCH Model for Intraday and Overnight Volatility |
0 |
1 |
2 |
26 |
0 |
6 |
10 |
103 |
| A Discrete Choice Model For Large Heterogeneous Panels with Interactive Fixed Effects with an Application to the Determinants of Corporate Bond Issuance |
0 |
0 |
0 |
11 |
0 |
4 |
4 |
63 |
| A Dynamic Network of Arbitrage Characteristics |
0 |
0 |
1 |
20 |
1 |
4 |
7 |
69 |
| A Dynamic Semiparametric Characteristics-based Model for Optimal Portfolio Selection |
0 |
0 |
0 |
13 |
1 |
3 |
5 |
47 |
| A Flexible Semiparametric Model for Time Series |
0 |
0 |
0 |
53 |
2 |
3 |
4 |
82 |
| A GARCH Model of the Implied Volatility of the Swiss Market Index From Option Pricesdffrom Options Prices |
0 |
0 |
0 |
312 |
0 |
1 |
9 |
899 |
| A GARCH model of the implied volatility of the Swiss Market Index from options prices |
0 |
0 |
0 |
8 |
0 |
0 |
4 |
44 |
| A Local Instrumental Variable Estimation Method For Generalized Additive Volatility Models |
0 |
0 |
0 |
50 |
0 |
2 |
2 |
227 |
| A Local Instrumental Variable Estimation Method for Generalized Additive Volatility Models |
0 |
0 |
0 |
2 |
1 |
2 |
3 |
26 |
| A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables |
0 |
0 |
0 |
40 |
2 |
3 |
4 |
77 |
| A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables |
0 |
1 |
2 |
14 |
0 |
3 |
5 |
59 |
| A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation |
0 |
0 |
0 |
25 |
5 |
6 |
7 |
43 |
| A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation |
0 |
0 |
1 |
10 |
0 |
0 |
2 |
13 |
| A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation |
0 |
0 |
0 |
0 |
1 |
4 |
5 |
6 |
| A Nonparametric Regression Estimator that Adapts to Error Distribution of Unknown Form |
0 |
0 |
0 |
4 |
0 |
1 |
1 |
24 |
| A Quantilogram Approach to Evaluating Directional Predictability |
0 |
0 |
1 |
2 |
1 |
4 |
6 |
37 |
| A Quantilogram Approach to Evaluating Directional Predictability |
0 |
0 |
1 |
118 |
3 |
3 |
4 |
474 |
| A ReMeDI for Microstructure Noise |
0 |
0 |
0 |
79 |
2 |
5 |
6 |
180 |
| A Semiparametric Panel Model for Unbalanced Data with Application to Climate Change in the United Kingdom |
0 |
0 |
0 |
96 |
2 |
4 |
6 |
245 |
| A Semiparametric Panel Model for unbalanced data with Application to Climate Change in the United Kingdom |
0 |
0 |
1 |
61 |
1 |
4 |
5 |
172 |
| A Simulation Comparison between Integration and Backfitting Methods of Estimating Separable Nonparametric Regression Models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
101 |
| A Structural Dynamic Factor Model for Daily Global Stock Market Returns |
0 |
1 |
2 |
4 |
3 |
8 |
15 |
20 |
| A Structural Dynamic Factor Model for Daily Global Stock Market Returns |
0 |
1 |
2 |
39 |
0 |
1 |
5 |
39 |
| A Unified Framework for Efficient Estimation of General Treatment Models |
0 |
0 |
0 |
8 |
4 |
5 |
6 |
30 |
| A Unified Framework for Efficient Estimation of General Treatment Models |
0 |
0 |
0 |
30 |
3 |
5 |
7 |
37 |
| A Unified Framework for Efficient Estimation of General Treatment Models |
0 |
0 |
0 |
6 |
2 |
2 |
6 |
38 |
| A Unified Framework for Specification Tests of Continuous Treatment Effect Models |
0 |
0 |
0 |
4 |
1 |
2 |
4 |
34 |
| A Unified Framework for Specification Tests of Continuous Treatment Effect Models |
0 |
0 |
0 |
9 |
1 |
4 |
5 |
17 |
| A coupled component GARCH model for intraday and overnight volatility |
0 |
0 |
0 |
68 |
0 |
2 |
3 |
61 |
| A coupled component GARCH model for intraday and overnight volatility |
0 |
0 |
0 |
25 |
1 |
2 |
4 |
28 |
| A discrete choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance |
0 |
0 |
0 |
31 |
0 |
0 |
1 |
182 |
| A discrete choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance |
0 |
0 |
0 |
0 |
8 |
19 |
25 |
39 |
| A discrete choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance |
0 |
0 |
0 |
51 |
2 |
4 |
8 |
97 |
| A flexible semiparametric model for time series |
0 |
0 |
0 |
50 |
1 |
2 |
3 |
94 |
| A flexible semiparametric model for time series |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
4 |
| A local instrumental estimation method for generalized additive volatility models |
0 |
0 |
0 |
10 |
1 |
1 |
2 |
191 |
| A local instrumental variable estimation method for generalized additive volatility models |
0 |
0 |
0 |
2 |
0 |
3 |
3 |
35 |
| A local instrumental variable estimation method for generalized additive volatility models |
0 |
0 |
0 |
2 |
0 |
2 |
2 |
21 |
| A nonparametric regression estimator that adapts to error distribution of unknown form |
0 |
0 |
1 |
3 |
1 |
1 |
4 |
45 |
| A nonparametric regression estimator that adapts to error distribution of unknown form |
0 |
0 |
0 |
32 |
1 |
1 |
4 |
218 |
| A nonparametric test of a strong leverage hypothesis |
0 |
0 |
0 |
0 |
3 |
8 |
9 |
11 |
| A nonparametric test of a strong leverage hypothesis |
0 |
0 |
0 |
27 |
3 |
5 |
6 |
89 |
| A nonparametric test of the leverage hypothesis |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
3 |
| A nonparametric test of the leverage hypothesis |
0 |
0 |
0 |
20 |
2 |
3 |
4 |
69 |
| A quantilogram approach to evaluating directional predictability |
0 |
0 |
0 |
2 |
1 |
2 |
4 |
29 |
| A semiparametric model for heterogeneous panel data with fixed effects |
0 |
0 |
0 |
102 |
0 |
1 |
1 |
265 |
| A semiparametric model for heterogeneous panel data with fixed effects |
0 |
1 |
2 |
6 |
4 |
18 |
38 |
78 |
| A semiparametric panel model for unbalanced data with application to climate change in the United Kingdom |
0 |
0 |
1 |
6 |
0 |
1 |
2 |
78 |
| A simple and efficient estimation method for models with nonignorable missing data |
0 |
0 |
0 |
131 |
1 |
1 |
1 |
267 |
| A smoothed least squares estimator for threshold regression models |
1 |
1 |
1 |
24 |
1 |
2 |
4 |
81 |
| Adaptive Estimation in ARCH Models |
0 |
0 |
0 |
234 |
1 |
4 |
4 |
615 |
| Adaptive Testing in ARCH Models |
0 |
0 |
0 |
173 |
2 |
2 |
4 |
889 |
| Additive nonparametric models with time variable and both stationary and nonstationary regressions |
0 |
0 |
0 |
0 |
0 |
4 |
4 |
6 |
| Additive nonparametric models with time variable and both stationary and nonstationary regressions |
0 |
0 |
1 |
20 |
1 |
1 |
2 |
36 |
| An Almost Closed Form Estimator For The EGARCH Model |
0 |
0 |
0 |
0 |
1 |
3 |
3 |
8 |
| An Almost Closed Form Estimator for the EGARCH |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
10 |
| An Almost Closed Form Estimator for the EGARCH model |
0 |
0 |
1 |
1 |
1 |
3 |
6 |
13 |
| An Alternative Way of ComputingEfficient Instrumental VariableEstimators |
0 |
0 |
0 |
2 |
2 |
5 |
7 |
46 |
| An Analysis of Transformations for Additive Nonparanetric Regression |
0 |
0 |
0 |
27 |
0 |
0 |
1 |
222 |
| An Asymptotic Expansion in the Garch(1,1) Model |
0 |
0 |
0 |
203 |
1 |
2 |
5 |
588 |
| An Improved Bootstrap Test of Stochastic Dominance |
0 |
0 |
0 |
74 |
1 |
7 |
7 |
235 |
| An Optimization Interpretation of Integration and Backfitting Estimators for Separable Nonparametric Models |
0 |
0 |
0 |
4 |
0 |
2 |
6 |
87 |
| An almost closed form estimator for the EGARCH model |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
21 |
| An almost closed form estimator for the EGARCH model |
0 |
0 |
0 |
74 |
1 |
2 |
5 |
113 |
| An alternative way of computing efficient instrumental variable estimators |
0 |
0 |
0 |
3 |
0 |
1 |
1 |
55 |
| An improved bootstrap test of stochastic dominance |
0 |
0 |
0 |
20 |
0 |
2 |
3 |
109 |
| An investigation into Multivariate Variance Ratio Statistics and their application to Stock Market Predictability |
0 |
0 |
0 |
23 |
1 |
1 |
2 |
65 |
| An investigation into multivariate variance ratio statistics and their application to stock market predictability |
0 |
0 |
0 |
1 |
3 |
4 |
5 |
8 |
| An investigation into multivariate variance ratio statistics and their application to stock market predictability |
0 |
0 |
0 |
16 |
2 |
6 |
6 |
59 |
| Applied Nonparametric Methods |
0 |
1 |
4 |
1,185 |
0 |
2 |
14 |
2,456 |
| Applied nonparametric methods |
0 |
0 |
0 |
373 |
1 |
3 |
6 |
954 |
| Are there Monday effects in Stock Returns: A Stochastic Dominance Approach |
0 |
0 |
0 |
322 |
9 |
15 |
22 |
1,000 |
| Are there Monday effects in stock returns: a stochastic dominance approach |
0 |
0 |
0 |
12 |
4 |
6 |
10 |
80 |
| Asymptotic Expansions for Some Semiparametric Program Evaluation Estimators |
0 |
0 |
0 |
17 |
2 |
3 |
4 |
48 |
| Asymptotic expansions for some semiparametric program evaluation estimators |
0 |
0 |
0 |
7 |
60 |
62 |
62 |
114 |
| Asymptotic expansions for some semiparametric program evaluation estimators |
0 |
0 |
0 |
177 |
1 |
3 |
4 |
418 |
| Asymptotic expansions for some semiparametric program evaluation estimators |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
4 |
| Asymptotic properties of a Nadaraya-Watson type estimator for regression functions of in finite order |
0 |
0 |
0 |
2 |
0 |
4 |
8 |
18 |
| Asymptotic properties of a Nadaraya-Watson type estimator for regression functions of in?finite order |
0 |
0 |
0 |
13 |
2 |
7 |
8 |
44 |
| Auditing the Auditors: An evaluation of the REF2021 Output Results |
0 |
0 |
0 |
8 |
1 |
4 |
7 |
8 |
| Auditing the Auditors: An evaluation of the REF2021 Output Results |
0 |
0 |
2 |
16 |
1 |
3 |
8 |
28 |
| Averaging of moment condition estimators |
0 |
0 |
0 |
48 |
3 |
9 |
10 |
108 |
| Averaging of moment condition estimators |
0 |
0 |
0 |
1 |
0 |
1 |
3 |
12 |
| Bootstrap Tests of Stochastic Dominance with Asymptotic Similarity on the Boundary |
0 |
0 |
0 |
64 |
5 |
7 |
8 |
209 |
| Bootstrap Tests of Stochastic Dominance with AsymptoticSimilarity on the Boundary |
0 |
0 |
0 |
0 |
2 |
2 |
2 |
28 |
| Bootstrap tests of stochastic dominance with asymptotic similarity on the boundary |
0 |
0 |
0 |
23 |
0 |
3 |
3 |
110 |
| Bootstrap tests of stochastic dominance with asymptotic similarity on the boundary |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
37 |
| CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects |
0 |
0 |
4 |
31 |
0 |
10 |
27 |
62 |
| CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects |
0 |
0 |
1 |
2 |
1 |
4 |
9 |
17 |
| Classification of nonparametric regression functions in heterogeneous panels |
0 |
0 |
0 |
28 |
0 |
2 |
4 |
56 |
| Classification of nonparametric regression functions in heterogeneous panels |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
5 |
| Conditional Independence Restrictions: Testing and Estimation |
0 |
0 |
0 |
615 |
1 |
4 |
6 |
2,159 |
| Consistent Estimation of the Risk-Return Tradeoff in the Presence of Measurement Error |
0 |
0 |
0 |
27 |
0 |
0 |
1 |
155 |
| Consistent Testing for Stochastic Dominance under General Sampling Schemes |
0 |
0 |
2 |
23 |
1 |
1 |
5 |
94 |
| Consistent Testing for Stochastic Dominance: A Subsampling Approach |
0 |
0 |
0 |
79 |
2 |
5 |
6 |
532 |
| Consistent Testing for Stochastic Dominance: A Subsampling Approach |
0 |
0 |
0 |
2 |
2 |
4 |
4 |
88 |
| Consistent Testing for Stochastic Dominance: A Subsampling Approach |
0 |
0 |
0 |
44 |
1 |
4 |
4 |
230 |
| Consistent Testing for Stochastic Dominance: A Subsampling Approach |
0 |
0 |
0 |
189 |
1 |
4 |
6 |
850 |
| Consistent Testing for an Implication of Supermodular Dominance |
0 |
0 |
2 |
44 |
0 |
1 |
6 |
96 |
| Consistent estimation of the risk-return tradeoff in the presence of measurement error |
0 |
0 |
0 |
2 |
1 |
2 |
3 |
43 |
| Consistent estimation of the risk-return tradeoff in the presence of measurement error |
0 |
0 |
0 |
39 |
1 |
1 |
1 |
205 |
| Consistent testing for stochastic dominance under general sampling schemes |
0 |
0 |
0 |
15 |
2 |
5 |
5 |
74 |
| Consistent testing for stochastic dominance: a subsampling approach |
0 |
0 |
0 |
0 |
1 |
2 |
4 |
5 |
| Consistent testing for stochastic dominance: a subsampling approach |
0 |
0 |
0 |
145 |
2 |
2 |
4 |
639 |
| Consistent testing for stochastic dominance: a subsampling approach |
0 |
0 |
0 |
1 |
3 |
6 |
7 |
93 |
| Consistent testing for stochastic dominance: a subsampling approach |
0 |
0 |
0 |
2 |
4 |
7 |
8 |
76 |
| Consistent testing for stochastic dominance: a subsampling approach |
0 |
0 |
0 |
4 |
1 |
7 |
9 |
92 |
| Do Consumption-based Asset Pricing Models Explain Own-history Predictability in Stock Market Returns? |
0 |
0 |
0 |
7 |
0 |
1 |
1 |
11 |
| Do Consumption-based Asset Pricing Models Explain Own-history Predictability in Stock Market Returns? |
0 |
0 |
0 |
11 |
1 |
3 |
3 |
8 |
| Dynamic Autoregressive Liquidity (DArLiQ) |
0 |
0 |
0 |
11 |
0 |
0 |
1 |
22 |
| Dynamic Autoregressive Liquidity (DArLiQ) |
0 |
1 |
1 |
33 |
1 |
3 |
3 |
17 |
| Dynamic Autoregressive Liquidity (DArLiQ) |
0 |
0 |
0 |
0 |
7 |
9 |
10 |
12 |
| ESTIMATION OF A SEMIPARAMETRICIGARCH(1,1) MODEL |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
20 |
| Edgeworth Approximation for MINPIN Estimators in Semiparametric Regression Models |
0 |
0 |
0 |
54 |
3 |
5 |
8 |
501 |
| Edgeworth Approximations for Semiparametric Instrumental Variable Estimators and Test Statistics |
0 |
0 |
0 |
0 |
1 |
4 |
6 |
20 |
| Edgeworth approximations for semiparametric instrumental variable estimators and test statistics |
0 |
0 |
0 |
3 |
1 |
3 |
4 |
32 |
| Efficient Estimation of Nonparametric Regression in The Presence of Dynamic Heteroskedasticity |
0 |
1 |
1 |
52 |
2 |
4 |
6 |
104 |
| Efficient Estimation of a Multivariate Multiplicative Volatility Model |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
41 |
| Efficient Estimation of a Semiparametric Characteristic- Based Factor Model of Security Returns |
0 |
0 |
0 |
92 |
1 |
1 |
4 |
294 |
| Efficient Estimation of a Semiparametric Characteristic-Based Factor Model of Security Returns |
0 |
0 |
0 |
60 |
2 |
3 |
5 |
235 |
| Efficient Estimation of a SemiparametricCharacteristic-Based Factor Model of Security Returns |
0 |
0 |
0 |
4 |
1 |
2 |
2 |
34 |
| Efficient estimation of a multivariate multiplicative volatility model |
0 |
0 |
0 |
5 |
1 |
2 |
3 |
50 |
| Efficient estimation of a semiparametric characteristic-based factor model of security returns |
0 |
0 |
0 |
3 |
2 |
5 |
5 |
45 |
| Efficient estimation of a semiparametric characteristic-based factor model of security returns |
0 |
0 |
0 |
2 |
2 |
5 |
5 |
47 |
| Efficient estimation of conditional risk measures in a semiparametric GARCH model |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
4 |
| Efficient estimation of conditional risk measures in a semiparametric GARCH model |
0 |
0 |
0 |
58 |
0 |
2 |
2 |
99 |
| Efficient estimation of generalized additive nonparametric regression models |
0 |
0 |
0 |
5 |
1 |
2 |
3 |
60 |
| Estimating Factor-Based Spot Volatility Matrices with Noisy and Asynchronous High-Frequency Data |
0 |
0 |
1 |
20 |
4 |
5 |
11 |
24 |
| Estimating Factor-Based Spot Volatility Matrices with Noisy and Asynchronous High-Frequency Data |
0 |
0 |
1 |
4 |
1 |
2 |
5 |
12 |
| Estimating Factor-Based Spot Volatility Matrices with Noisy and Asynchronous High-Frequency Data |
0 |
0 |
0 |
8 |
2 |
4 |
6 |
11 |
| Estimating Features of a Distribution from Binomial Data |
0 |
0 |
0 |
211 |
1 |
3 |
4 |
1,300 |
| Estimating Multiplicative and Additive Hazard Functions by Kernel Methods |
0 |
0 |
0 |
111 |
0 |
0 |
1 |
504 |
| Estimating Multiplicative and Additive Hazard Functions by Kernel Methods |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
38 |
| Estimating Quadratic VariationConsistently in thePresence of Correlated MeasurementError |
0 |
0 |
0 |
1 |
0 |
3 |
4 |
52 |
| Estimating Semiparametric ARCH (8) Models by Kernel Smoothing Methods |
0 |
0 |
0 |
0 |
3 |
4 |
4 |
27 |
| Estimating Semiparametric ARCH Models by Kernel Smoothing Methods |
0 |
0 |
0 |
111 |
4 |
6 |
8 |
352 |
| Estimating Time-Varying Networks for High-Dimensional Time Series |
0 |
0 |
2 |
69 |
8 |
9 |
18 |
50 |
| Estimating Time-Varying Networks for High-Dimensional Time Series |
0 |
1 |
1 |
61 |
1 |
6 |
9 |
24 |
| Estimating Time-Varying Networks for High-Dimensional Time Series |
0 |
0 |
0 |
17 |
8 |
10 |
11 |
30 |
| Estimating Yield Curves by Kernel Smoothing Methods |
0 |
0 |
0 |
691 |
6 |
9 |
9 |
1,898 |
| Estimating a Density Ratio Model for Stock Market Risk and Option Demand |
1 |
1 |
1 |
6 |
2 |
3 |
4 |
10 |
| Estimating a Density Ratio Model for Stock Market Risk and Option Demand |
0 |
0 |
0 |
8 |
0 |
2 |
7 |
20 |
| Estimating additive nonparametric models by partial Lq norm: the curse of fractionality |
0 |
0 |
0 |
0 |
1 |
2 |
3 |
26 |
| Estimating features of a distribution from binomial data |
0 |
0 |
0 |
105 |
2 |
3 |
6 |
718 |
| Estimating features of a distribution from binomial data |
0 |
0 |
0 |
0 |
2 |
4 |
6 |
50 |
| Estimating multiplicative and additive hazard functions by kernel methods |
0 |
0 |
0 |
0 |
1 |
3 |
6 |
33 |
| Estimating quadratic variation consistently in the presence of correlated measurement error |
0 |
0 |
0 |
1 |
2 |
5 |
7 |
33 |
| Estimating semiparametric ARCH (8) models by kernel smoothing methods |
0 |
0 |
0 |
1 |
1 |
2 |
2 |
65 |
| Estimating semiparametric ARCH (∞) models by kernel smoothing methods |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
6 |
| Estimating semiparametric ARCH (∞) models by kernel smoothing methods |
0 |
0 |
0 |
3 |
2 |
2 |
2 |
35 |
| Estimating the Quadratic Covariation Matrix for an Asynchronously Observed Continuous Time Signal Masked by Additive Noise |
0 |
0 |
1 |
51 |
0 |
0 |
2 |
127 |
| Estimating the quadratic covariation matrix for an asynchronously observed continuous time signal masked by additive noise |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
| Estimating yield curves by Kernel smoothing methods |
0 |
0 |
0 |
212 |
2 |
3 |
5 |
756 |
| Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects |
0 |
1 |
21 |
37 |
0 |
2 |
20 |
66 |
| Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects |
0 |
1 |
2 |
4 |
1 |
4 |
9 |
19 |
| Estimation and Inference in Semiparametric Quantile Factor Models |
0 |
0 |
1 |
11 |
1 |
4 |
9 |
55 |
| Estimation and inference in semiparametric quantile factor models |
0 |
1 |
1 |
77 |
2 |
4 |
4 |
141 |
| Estimation in semiparametric quantile factor models |
0 |
0 |
0 |
27 |
0 |
1 |
3 |
54 |
| Estimation of Additive Regression Models with Links |
0 |
0 |
0 |
3 |
1 |
2 |
3 |
99 |
| Estimation of Linear Regression Models by a Spread-Tolerant Estimator |
0 |
0 |
0 |
17 |
1 |
1 |
1 |
129 |
| Estimation of Semiparametric Models when the Criterion Function is not Smooth |
0 |
0 |
0 |
8 |
1 |
3 |
6 |
71 |
| Estimation of a Multiplicative Correlation Structure in the Large Dimensional Case |
0 |
1 |
1 |
26 |
0 |
2 |
2 |
68 |
| Estimation of a Multiplicative Covariance Structure |
0 |
0 |
0 |
0 |
3 |
6 |
6 |
7 |
| Estimation of a Multiplicative Covariance Structure |
0 |
0 |
0 |
26 |
0 |
1 |
3 |
35 |
| Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case |
0 |
0 |
0 |
22 |
1 |
3 |
3 |
38 |
| Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case |
0 |
0 |
0 |
11 |
0 |
0 |
0 |
86 |
| Estimation of a Nonparametric Model for Bond Prices from Cross-Section and Time Series Information |
0 |
1 |
1 |
52 |
0 |
5 |
7 |
69 |
| Estimation of a multiplicative correlation structure in the large dimensional case |
0 |
0 |
0 |
0 |
5 |
6 |
7 |
10 |
| Estimation of a multiplicative covariance structure in the large dimensional case |
0 |
0 |
0 |
2 |
1 |
2 |
5 |
24 |
| Estimation of a multiplicative covariance structure in the large dimensional case |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
3 |
| Estimation of linear regression models by a spread-tolerant estimator |
0 |
0 |
0 |
0 |
1 |
2 |
2 |
26 |
| Estimation of semiparametric models when the criterion function is not smooth |
0 |
0 |
0 |
0 |
2 |
4 |
8 |
10 |
| Estimation of semiparametric models when the criterion function is not smooth |
0 |
0 |
0 |
153 |
1 |
1 |
3 |
627 |
| Estimation of semiparametric models when the criterion function is not smooth |
0 |
0 |
0 |
3 |
1 |
3 |
4 |
73 |
| Estimation of tail thickness parameters from GJR-GARCH models |
0 |
0 |
0 |
260 |
0 |
1 |
3 |
854 |
| Estimation of the Kronecker Covariance Model by Quadratic Form |
0 |
0 |
0 |
7 |
0 |
2 |
2 |
45 |
| Estimation with Mixed Data Frequencies: A Bias-Correction Approach |
0 |
0 |
0 |
32 |
2 |
2 |
2 |
20 |
| Evaluating Value-at-Risk Models via Quantile Regression |
0 |
0 |
0 |
146 |
2 |
9 |
13 |
391 |
| Evaluating Value-at-Risk Models via Quantile Regressions |
0 |
0 |
2 |
228 |
4 |
9 |
16 |
595 |
| Evaluating Value-at-Risk models via Quantile Regression |
0 |
0 |
0 |
201 |
3 |
6 |
8 |
553 |
| Evaluating Value-at-Risk models via Quantile regressions |
0 |
0 |
1 |
188 |
5 |
8 |
10 |
427 |
| Evaluating hedge fund performance: a stochastic dominance approach |
0 |
0 |
0 |
8 |
0 |
0 |
1 |
57 |
| Evaluating hedge fund performance: a stochastic dominance approach |
0 |
0 |
0 |
158 |
1 |
2 |
2 |
371 |
| Flexible Term Structure Estimation: Which Method Is Preferred? |
0 |
0 |
1 |
5 |
1 |
3 |
7 |
21 |
| Flexible Term Structure Estimation: Which Method Is Preferred? |
0 |
0 |
0 |
187 |
1 |
4 |
6 |
497 |
| Flexible Term Structure Estimation: Which Method is Preferable? |
0 |
0 |
0 |
42 |
0 |
0 |
0 |
165 |
| Flexible Term Structure Estimation: Which Method is Preferred? |
0 |
0 |
0 |
216 |
2 |
2 |
2 |
487 |
| Flexible term structure estimation: which method is preferable? |
0 |
0 |
0 |
1 |
1 |
1 |
2 |
32 |
| Flexible term structure estimation: which method is preferred? |
0 |
0 |
0 |
0 |
5 |
7 |
9 |
9 |
| GMM Estimation for High-Dimensional Panel Data Models |
1 |
2 |
2 |
4 |
6 |
10 |
14 |
18 |
| GMM Estimation for High-Dimensional Panel Data Models |
0 |
0 |
0 |
34 |
2 |
4 |
5 |
47 |
| GMM Estimation for High–Dimensional Panel Data Models |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
4 |
| Global Bahadur representation for nonparametric censored regression quantiles and its applications |
0 |
0 |
0 |
49 |
2 |
5 |
6 |
115 |
| High Dimensional Semiparametric Moment Restriction Models |
0 |
1 |
1 |
17 |
3 |
6 |
6 |
71 |
| High dimensional semiparametric moment restriction models |
0 |
0 |
0 |
54 |
25 |
37 |
40 |
161 |
| High dimensional semiparametric moment restriction models |
0 |
0 |
0 |
2 |
5 |
7 |
8 |
43 |
| High dimensional semiparametric moment restriction models |
0 |
0 |
0 |
27 |
7 |
12 |
13 |
71 |
| High dimensional semiparametric moment restriction models |
0 |
0 |
0 |
4 |
5 |
5 |
6 |
44 |
| Identification and Nonparametric Estimation of a Transformed Additively Separable Model |
0 |
0 |
0 |
58 |
1 |
3 |
4 |
276 |
| Identification and nonparametric estimation of a transformed additively separable model |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
57 |
| Implications of High-Frequency Trading for Security Markets |
0 |
1 |
2 |
70 |
2 |
4 |
8 |
121 |
| Implications of high-frequency trading for security markets |
0 |
0 |
0 |
17 |
3 |
6 |
6 |
55 |
| Improving Estimation Efficiency via Regression-Adjustment in Covariate-Adaptive Randomizations with Imperfect Compliance |
0 |
0 |
0 |
16 |
1 |
3 |
4 |
22 |
| Improving Estimation Efficiency via Regression-Adjustment in Covariate-Adaptive Randomizations with Imperfect Compliance |
0 |
0 |
0 |
1 |
1 |
1 |
5 |
6 |
| Improving Estimation Efficiency via Regression-Adjustment in Covariate-Adaptive Randomizations with Imperfect Compliance |
0 |
0 |
0 |
2 |
2 |
2 |
2 |
6 |
| Inference about Realized Volatility using Infill Subsampling |
0 |
0 |
0 |
1 |
2 |
3 |
4 |
24 |
| Inference about realized volatility using infill subsampling |
0 |
0 |
0 |
3 |
3 |
3 |
5 |
27 |
| Inference on a Semiparametric Model with Global Power Law and Local Nonparametric Trends |
0 |
0 |
0 |
52 |
0 |
3 |
12 |
83 |
| Inference on a semiparametric model with global power law and local nonparametric trends |
0 |
0 |
0 |
4 |
2 |
3 |
4 |
36 |
| Integration and Backfitting methods in additive models: finite sample properties and comparison |
0 |
0 |
0 |
4 |
0 |
1 |
1 |
21 |
| Is There Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors |
0 |
0 |
0 |
278 |
0 |
0 |
1 |
881 |
| Is There Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors |
0 |
0 |
0 |
208 |
0 |
0 |
2 |
612 |
| Is the EJRA proportionate and therefore justified? A critical review of the EJRA policy at Cambridge |
0 |
0 |
0 |
1 |
1 |
4 |
5 |
7 |
| Is the EJRA proportionate and therefore justified? A critical review of the EJRA policy at Cambridge |
0 |
0 |
0 |
0 |
2 |
3 |
7 |
11 |
| Is the EJRA proportionate and therefore justified? A critical review of the EJRA policy at Cambridge |
0 |
0 |
0 |
0 |
2 |
3 |
6 |
9 |
| Jumps Versus Bursts: Dissection and Origins via a New Endogenous Thresholding Approach |
0 |
0 |
0 |
6 |
1 |
4 |
11 |
21 |
| Jumps Versus Bursts: Dissection and Origins via a New Endogenous Thresholding Approach |
0 |
0 |
1 |
14 |
2 |
4 |
9 |
23 |
| Kernel estimation in a nonparametric marker dependent Hazard Model |
0 |
0 |
0 |
134 |
2 |
2 |
3 |
406 |
| Kolmogorov-Smirnov Type Testing for Structural Breaks: A New Adjusted-Range Based Self-Normalization Approach |
0 |
0 |
0 |
11 |
1 |
4 |
6 |
19 |
| Kolmogorov-Smirnov Type Testing for Structural Breaks: A New Adjusted-Range Based Self-Normalization Approach |
0 |
0 |
0 |
16 |
3 |
6 |
9 |
19 |
| Let's get LADE: robust estimation of semiparametric multiplicative volatility models |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
3 |
| Let's get LADE: robust estimation of semiparametric multiplicative volatility models |
0 |
0 |
0 |
34 |
0 |
2 |
2 |
101 |
| Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems |
0 |
0 |
0 |
104 |
2 |
5 |
7 |
428 |
| Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems |
0 |
0 |
0 |
0 |
7 |
10 |
13 |
52 |
| Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems |
0 |
0 |
0 |
206 |
0 |
1 |
3 |
917 |
| Limit theorems for estimating the parameters of differentiated product demand systems |
0 |
0 |
0 |
1 |
0 |
2 |
5 |
55 |
| Local Linear Fitting Under Near Epoch Dependence: Uniform consistency with Convergence Rates |
0 |
0 |
0 |
39 |
0 |
2 |
2 |
93 |
| Local Nonlinear Least Squares Estimation: Using Parametric Information Nonparametrically |
0 |
0 |
0 |
291 |
2 |
4 |
4 |
1,156 |
| Loch Linear Fitting under Near Epoch Dependence: Uniform Consistency with Convergence Rate |
0 |
0 |
0 |
4 |
1 |
4 |
6 |
32 |
| Loch linear fitting under near epoch dependence: uniform consistency with convergence rate |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
29 |
| Making Inferences About Rich Country - Poor Country Convergence: The Polarization Trapezoid and Overlap measures |
0 |
0 |
0 |
73 |
0 |
2 |
3 |
400 |
| Mean Ratio Statistic for measuring predictability |
0 |
0 |
0 |
19 |
2 |
3 |
3 |
41 |
| Mean Ratio Statistic for measuring predictability |
0 |
0 |
0 |
0 |
1 |
2 |
2 |
4 |
| More Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors |
0 |
0 |
0 |
241 |
0 |
1 |
3 |
809 |
| More Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors |
0 |
0 |
0 |
3 |
2 |
3 |
4 |
47 |
| More efficient kernel estimation in nonparametric regression with autocorrelated errors |
0 |
0 |
0 |
5 |
1 |
2 |
4 |
43 |
| Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction |
0 |
0 |
0 |
31 |
1 |
1 |
1 |
66 |
| Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction |
0 |
0 |
0 |
74 |
2 |
4 |
5 |
107 |
| Multiscale clustering of nonparametric regression curves |
0 |
0 |
0 |
17 |
1 |
4 |
5 |
35 |
| Multivariate Variance Ratio Statistics |
0 |
0 |
1 |
9 |
3 |
6 |
8 |
42 |
| Multivariate variance ratio statistics |
0 |
0 |
0 |
32 |
3 |
5 |
5 |
86 |
| Multivariate variance ratio statistics |
0 |
0 |
0 |
0 |
2 |
4 |
5 |
5 |
| Non Parametric Estimation of a Polarization Measure |
0 |
0 |
0 |
34 |
1 |
1 |
3 |
106 |
| Non-Standard Errors |
0 |
0 |
1 |
27 |
4 |
7 |
27 |
161 |
| Non-Standard Errors |
0 |
0 |
2 |
44 |
6 |
12 |
35 |
458 |
| Non-parametric transformation regression with non-stationary data |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
| Non-parametric transformation regression with non-stationary data |
0 |
0 |
0 |
46 |
0 |
4 |
5 |
77 |
| Nonparametric Censored Regression |
0 |
0 |
0 |
410 |
1 |
2 |
3 |
1,375 |
| Nonparametric Censored and Truncated Regression |
0 |
0 |
0 |
5 |
0 |
1 |
1 |
73 |
| Nonparametric Censored and Truncated Regression |
0 |
0 |
0 |
197 |
2 |
5 |
5 |
533 |
| Nonparametric Censored and Truncated Regression |
0 |
0 |
0 |
481 |
2 |
9 |
11 |
1,899 |
| Nonparametric Estimation of Additive Seperable Regression Models |
0 |
0 |
0 |
18 |
1 |
4 |
4 |
159 |
| Nonparametric Estimation of Homothetic and Homothetically Separable Functions |
0 |
0 |
0 |
1 |
2 |
3 |
6 |
28 |
| Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data |
0 |
0 |
0 |
20 |
0 |
4 |
7 |
39 |
| Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data |
0 |
0 |
0 |
7 |
1 |
1 |
1 |
10 |
| Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data |
0 |
0 |
0 |
9 |
2 |
3 |
5 |
10 |
| Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data |
0 |
0 |
0 |
55 |
2 |
5 |
6 |
28 |
| Nonparametric Estimation of a Multifactor Heath-Jarrow-Morton Model: An Integrated Approach |
0 |
0 |
0 |
211 |
1 |
2 |
3 |
692 |
| Nonparametric Estimation of a Polarization Measure |
0 |
0 |
0 |
4 |
2 |
7 |
9 |
49 |
| Nonparametric Estimation of a Polarization Measure |
0 |
0 |
0 |
59 |
0 |
0 |
1 |
187 |
| Nonparametric Estimation with Aggregated Data |
0 |
0 |
0 |
0 |
2 |
3 |
4 |
25 |
| Nonparametric Euler Equation Identi?cation and Estimation |
0 |
0 |
0 |
27 |
1 |
3 |
5 |
33 |
| Nonparametric Euler Equation Identification and Estimation |
0 |
0 |
1 |
52 |
1 |
6 |
9 |
185 |
| Nonparametric Euler Equation Identification andEstimation |
0 |
0 |
0 |
46 |
8 |
9 |
9 |
110 |
| Nonparametric Euler equation identification and estimation |
0 |
0 |
0 |
41 |
1 |
2 |
2 |
118 |
| Nonparametric Euler equation identification and estimation |
0 |
0 |
0 |
0 |
1 |
3 |
5 |
8 |
| Nonparametric Inference for Unbalanced Time Series Data |
0 |
0 |
1 |
5 |
3 |
3 |
4 |
25 |
| Nonparametric Matching and Efficient Estimators of Homothetically Separable Functions |
0 |
0 |
0 |
135 |
0 |
1 |
1 |
728 |
| Nonparametric Neural Network Estimation of Lyapunov Exponents and a Direct Test for Chaos |
0 |
1 |
1 |
369 |
1 |
4 |
5 |
1,175 |
| Nonparametric Neural Network Estimation of Lyapunov Exponents and a Direct Test for Chaos |
0 |
0 |
1 |
2 |
0 |
1 |
8 |
35 |
| Nonparametric Neutral Network Estimation of Lyapunov Exponents and a Direct Test for Chaos |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
24 |
| Nonparametric Predictive Regressions for Stock Return Prediction |
0 |
1 |
2 |
129 |
7 |
12 |
17 |
144 |
| Nonparametric Predictive Regressions for Stock Return Prediction |
0 |
0 |
0 |
51 |
2 |
4 |
6 |
53 |
| Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information |
0 |
1 |
1 |
57 |
2 |
4 |
8 |
102 |
| Nonparametric Regression |
0 |
0 |
0 |
74 |
2 |
3 |
3 |
222 |
| Nonparametric Regression with a Latent Time Series |
0 |
0 |
0 |
2 |
0 |
1 |
1 |
23 |
| Nonparametric Transformation to White Noise |
0 |
0 |
0 |
3 |
1 |
2 |
3 |
40 |
| Nonparametric censored and truncated regression |
0 |
0 |
0 |
4 |
3 |
5 |
5 |
80 |
| Nonparametric estimation of a periodic sequence in the presence of a smooth trend |
0 |
0 |
0 |
32 |
2 |
4 |
6 |
75 |
| Nonparametric estimation of a periodic sequence in the presence of a smooth trend |
0 |
0 |
0 |
0 |
2 |
10 |
10 |
11 |
| Nonparametric estimation of a polarization measure |
0 |
0 |
0 |
25 |
0 |
2 |
2 |
69 |
| Nonparametric estimation of a polarization measure |
0 |
0 |
0 |
1 |
2 |
2 |
3 |
39 |
| Nonparametric estimation of a polarization measure |
0 |
0 |
0 |
39 |
0 |
4 |
7 |
110 |
| Nonparametric estimation of homothetic and homothetically separable functions |
0 |
0 |
0 |
40 |
1 |
2 |
2 |
312 |
| Nonparametric estimation of homothetic and homothetically separable functions |
0 |
0 |
0 |
5 |
1 |
3 |
4 |
34 |
| Nonparametric estimation of homothetic and homothetically separable functions |
0 |
0 |
0 |
0 |
1 |
1 |
3 |
4 |
| Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff |
0 |
1 |
2 |
14 |
3 |
5 |
6 |
58 |
| Nonparametric estimation of multivariate elliptic densities via finite mixture sieves |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
5 |
| Nonparametric estimation of multivariate elliptic densities via finite mixture sieves |
0 |
0 |
0 |
4 |
2 |
6 |
6 |
38 |
| Nonparametric estimation of multivariate elliptic densities via finite mixture sieves |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
3 |
| Nonparametric estimation of multivariate elliptic densities via finite mixture sieves |
0 |
0 |
0 |
5 |
4 |
5 |
7 |
35 |
| Nonparametric estimation with aggregated data |
0 |
0 |
0 |
3 |
2 |
3 |
3 |
31 |
| Nonparametric estimation with aggregated data |
0 |
0 |
0 |
2 |
0 |
0 |
3 |
26 |
| Nonparametric factor analysis of time series |
0 |
0 |
0 |
7 |
1 |
2 |
2 |
254 |
| Nonparametric inference for unbalance time series data |
0 |
0 |
0 |
58 |
1 |
4 |
4 |
266 |
| Nonparametric inference for unbalance time series data |
0 |
0 |
0 |
0 |
0 |
1 |
5 |
9 |
| Nonparametric inference for unbalanced time series data |
0 |
0 |
0 |
0 |
3 |
3 |
4 |
28 |
| Nonparametric inference for unbalanced time series data |
0 |
0 |
0 |
3 |
3 |
4 |
5 |
36 |
| Nonparametric neural network estimation of Lyapunov exponents and a direct test for chaos |
0 |
0 |
0 |
2 |
1 |
2 |
3 |
37 |
| Nonparametric neural network estimation of Lyapunov exponents and a direct test for chaos |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
21 |
| Nonparametric neutral network estimation of lyapunov exponents and a direct test for chaos |
0 |
0 |
0 |
1 |
1 |
3 |
3 |
28 |
| Nonparametric regression with filtered data |
0 |
0 |
0 |
0 |
2 |
3 |
4 |
7 |
| Nonparametric transformation to white noise |
0 |
0 |
0 |
2 |
2 |
2 |
3 |
35 |
| Nonstandard Errors |
1 |
1 |
4 |
4 |
4 |
10 |
25 |
33 |
| Nonstandard errors |
0 |
0 |
1 |
12 |
3 |
7 |
28 |
63 |
| On Time Trend of COVID-19: A Panel Data Study |
0 |
0 |
0 |
87 |
0 |
3 |
3 |
333 |
| On Time Trend of COVID-19: A Panel Data Study |
0 |
0 |
0 |
47 |
1 |
1 |
2 |
114 |
| On Unit Free Assessment of The Extent of Multilateral Distributional Variation |
0 |
0 |
0 |
6 |
2 |
5 |
6 |
38 |
| On Unit Free Assessment of The Extent of Multilateral Distributional Variation |
0 |
0 |
0 |
31 |
2 |
4 |
6 |
45 |
| On a semiparametric survival model with flexible covariate effect |
0 |
0 |
0 |
3 |
2 |
7 |
10 |
39 |
| On the Time Trend of COVID-19: A Panel Data Study |
0 |
0 |
0 |
2 |
3 |
3 |
3 |
23 |
| Optimal Smoothing for a Computationallyand StatisticallyEfficient Single Index Estimator |
0 |
0 |
0 |
0 |
3 |
3 |
3 |
19 |
| Optimal smoothing for a computationally and statistically efficient single index estimator |
0 |
0 |
0 |
74 |
2 |
2 |
3 |
154 |
| Optimal smoothing for a computationally and statistically efficient single index estimator |
0 |
0 |
0 |
0 |
1 |
2 |
2 |
25 |
| Pricing American Options under Stochastic Volatility and Stochastic Interest Rates |
0 |
0 |
0 |
23 |
3 |
9 |
10 |
138 |
| Quantilograms under Strong Dependence |
0 |
0 |
0 |
50 |
2 |
3 |
7 |
37 |
| Quantilograms under Strong Dependence |
0 |
0 |
0 |
4 |
3 |
3 |
3 |
19 |
| Robust Estimation of Integrated and Spot Volatility |
0 |
0 |
0 |
40 |
0 |
5 |
9 |
44 |
| Second Order Approximation in a Linear Regression with Heteroskedasticity for Unknown Form |
0 |
0 |
0 |
59 |
1 |
2 |
4 |
474 |
| Second Order Approximation in the Partially Linear Regression Model |
0 |
0 |
0 |
166 |
2 |
3 |
5 |
1,276 |
| Second-order approximation for adaptive regression estimators |
0 |
0 |
0 |
5 |
4 |
5 |
6 |
31 |
| Semiparametric Dynamic Portfolio Choice with Multiple Conditioning Variables |
0 |
0 |
0 |
32 |
1 |
1 |
1 |
121 |
| Semiparametric Estimation of Locally Stationary Diffusion Models |
0 |
0 |
0 |
6 |
0 |
0 |
1 |
31 |
| Semiparametric Estimation of Markov Decision Processeswith Continuous State Space |
0 |
0 |
0 |
1 |
0 |
1 |
1 |
30 |
| Semiparametric Estimation of a Characteristic-Based Factor Model of Stock Returns |
0 |
0 |
3 |
161 |
2 |
3 |
8 |
427 |
| Semiparametric Estimation of aCharacteristic-based Factor Model ofCommon Stock Returns |
0 |
0 |
0 |
3 |
1 |
1 |
2 |
37 |
| Semiparametric Model Averaging of Ultra-High Dimensional Time Series |
0 |
0 |
0 |
68 |
0 |
1 |
2 |
107 |
| Semiparametric Nonlinear Panel Data Models with Measurement Error |
0 |
0 |
0 |
6 |
2 |
3 |
5 |
53 |
| Semiparametric Regression Analysis under Imputation for Missing Response Data |
0 |
0 |
0 |
3 |
0 |
1 |
2 |
23 |
| Semiparametric dynamic portfolio choice with multiple conditioning variables |
0 |
0 |
0 |
8 |
0 |
0 |
1 |
37 |
| Semiparametric dynamic portfolio choice with multiple conditioning variables |
0 |
0 |
0 |
0 |
1 |
2 |
2 |
3 |
| Semiparametric estimation of Markov decision processeswith continuous state space |
0 |
0 |
0 |
1 |
1 |
2 |
2 |
31 |
| Semiparametric estimation of a characteristic-based factor model of common stock returns |
0 |
0 |
0 |
2 |
1 |
1 |
3 |
46 |
| Semiparametric estimation of locally stationary diffusion models |
0 |
0 |
0 |
6 |
1 |
2 |
2 |
26 |
| Semiparametric model averaging of ultra-high dimensional time series |
0 |
0 |
0 |
32 |
1 |
4 |
4 |
76 |
| Semiparametric model averaging of ultra-high dimensional time series |
0 |
0 |
0 |
0 |
1 |
1 |
3 |
6 |
| Semiparametric nonlinear panel data models with measurement error |
0 |
0 |
0 |
21 |
1 |
3 |
3 |
27 |
| Semiparametric regression analysis under imputation for missing response data |
0 |
0 |
0 |
0 |
2 |
2 |
4 |
43 |
| Semiparametric regression analysis under imputation for missing response data |
0 |
0 |
0 |
31 |
1 |
2 |
3 |
245 |
| Semiparametric regression analysis with missing response at random |
0 |
0 |
0 |
1 |
2 |
2 |
2 |
6 |
| Semiparametric regression analysis with missing response at random |
0 |
0 |
0 |
244 |
3 |
4 |
9 |
760 |
| Should Expected or Most Likely Returns be the Focus in Investment Decisions? Introducing “Most Likely†Versions of Sharpe and Sortino Ratios |
0 |
0 |
9 |
9 |
1 |
3 |
9 |
9 |
| Should We Augment Large Covariance Matrix Estimation with Auxiliary Network Information? |
0 |
0 |
1 |
7 |
3 |
5 |
7 |
31 |
| Should We Augment Large Covariance Matrix Estimation with Auxiliary Network Information? |
0 |
0 |
0 |
4 |
4 |
5 |
7 |
25 |
| Simple Nonparametric Estimators for the Bid-Ask Spread in the Roll Model |
0 |
0 |
1 |
21 |
2 |
4 |
7 |
57 |
| Simple Nonparametric Estimators for the Bid-Ask Spread in the Roll Model |
0 |
0 |
0 |
36 |
1 |
5 |
6 |
93 |
| Simple Nonparametric Estimators for the Bid-Ask Spread in the Roll Model |
0 |
0 |
0 |
0 |
2 |
6 |
6 |
10 |
| Simple Nonparametric Estimators for the Bid-Ask Spread in the Roll Model |
0 |
0 |
0 |
16 |
0 |
0 |
1 |
31 |
| Single stock circuit breakers on the London Stock Exchange: do they improve subsequent market quality? |
0 |
0 |
1 |
40 |
7 |
8 |
13 |
277 |
| Some Higher Order Theory for a Consistent Nonparametric Model Specification Test |
0 |
0 |
0 |
97 |
1 |
1 |
1 |
387 |
| TESTING FOR STOCHASTICMONOTONICITY |
0 |
0 |
0 |
0 |
2 |
3 |
5 |
56 |
| Testing Additivity in Generalized Nonparametric Regression Models |
0 |
0 |
0 |
135 |
2 |
3 |
4 |
908 |
| Testing Additivity in Generalized Nonparametric Regression Models |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
63 |
| Testing Stochastic Dominance with Many Conditioning Variables |
0 |
0 |
0 |
18 |
1 |
2 |
4 |
40 |
| Testing for Stochastic Dominance Efficiency |
0 |
0 |
0 |
58 |
2 |
2 |
3 |
147 |
| Testing for Time Stochastic Dominance |
0 |
0 |
0 |
60 |
0 |
1 |
3 |
167 |
| Testing for stochastic monotonicity |
0 |
0 |
0 |
2 |
0 |
2 |
4 |
57 |
| Testing for stochastic monotonicity |
0 |
0 |
0 |
53 |
1 |
4 |
6 |
163 |
| Testing for the stochastic dominance efficiency of a given portfolio |
0 |
0 |
0 |
48 |
3 |
3 |
3 |
151 |
| Testing for the stochastic dominance efficiency of a given portfolio |
0 |
0 |
0 |
0 |
2 |
4 |
6 |
7 |
| Testing the Capital Asset Pricing Model Efficiently Under Elliptical Symmetry: A Semiparametric Approach |
0 |
0 |
0 |
244 |
3 |
4 |
7 |
1,169 |
| Testing the Capital Asset Pricing Model Efficiently Under Elliptical Symmetry: A Semiparametric Approach |
0 |
0 |
1 |
646 |
3 |
8 |
12 |
3,502 |
| Testing the Capital Asset Pricing Model Efficiently under Elliptical Symmetry: A Semiparametric Approach |
0 |
0 |
0 |
4 |
2 |
4 |
5 |
33 |
| Testing the capital asset pricing model efficiently under elliptical symmetry: a semiparametric approach |
0 |
0 |
0 |
2 |
2 |
4 |
5 |
62 |
| The Asymptotic Distribution of Nonparametric Estimates of the Lyapunov Exponent for Stochastic Time Series |
0 |
0 |
0 |
244 |
1 |
2 |
3 |
962 |
| The Behaviour of Betting and Currency Markets on the Night of the EU Referendum |
0 |
0 |
0 |
16 |
5 |
10 |
12 |
57 |
| The Cross-Quantilogram: Measuring Quantile Dependence and Testing Directional Predictability between Time Series |
0 |
0 |
0 |
12 |
0 |
3 |
5 |
102 |
| The Effect of Fragmentation in Trading on Market Quality in the UK Equity Market |
0 |
0 |
0 |
4 |
3 |
5 |
5 |
42 |
| The Estimation of Conditional Densities |
0 |
0 |
0 |
6 |
2 |
5 |
7 |
36 |
| The Existence and Asymptotic Properties of a Backfitting Projection Algorithm Under Weak Conditions |
0 |
0 |
0 |
62 |
2 |
4 |
6 |
321 |
| The Existence and Asymptotic Properties of a Backfitting Projection Algorithm under Weak Conditions |
0 |
0 |
0 |
0 |
0 |
3 |
4 |
22 |
| The Froot and Stein Model Revisited |
0 |
0 |
0 |
457 |
1 |
2 |
2 |
1,436 |
| The Impact of Corporate QE on Liquidity: Evidence from the UK |
0 |
0 |
1 |
38 |
3 |
3 |
5 |
77 |
| The Lower Regression Function and Testing Expectation Dependence Dominance Hypotheses |
0 |
0 |
0 |
3 |
0 |
1 |
1 |
9 |
| The Lower Regression Function and Testing Expectation Dependence Dominance Hypotheses |
0 |
1 |
1 |
12 |
0 |
3 |
3 |
35 |
| The October 2016 sterling flash episode: when liquidity disappeared from one of the world’s most liquid markets |
0 |
0 |
0 |
11 |
1 |
1 |
5 |
53 |
| The Permanent and Temporary Effects of Stock Splits on Liquidity in a Dynamic Semiparametric Model |
0 |
0 |
0 |
7 |
1 |
3 |
5 |
12 |
| The Permanent and Temporary Effects of Stock Splits on Liquidity in a Dynamic Semiparametric Model |
0 |
0 |
0 |
7 |
3 |
4 |
5 |
12 |
| The Shape of the Risk Premium: Evidence from a Semiparametric GARCH Model |
0 |
0 |
0 |
48 |
0 |
0 |
1 |
217 |
| The Shape of the Risk Premium: Evidence from a Semiparametric Garch Model |
0 |
0 |
1 |
96 |
2 |
5 |
6 |
370 |
| The behaviour of betting and currency markets on the night of the EU referendum |
0 |
0 |
0 |
33 |
0 |
0 |
2 |
54 |
| The behaviour of betting and currency markets on the night of the EU referendum |
0 |
0 |
0 |
18 |
2 |
5 |
5 |
34 |
| The cross-quantilogram: measuring quantile dependence and testing directional predictability between time series |
0 |
0 |
0 |
45 |
2 |
4 |
4 |
127 |
| The cross-quantilogram: measuring quantile dependence and testing directional predictability between time series |
0 |
0 |
0 |
1 |
1 |
4 |
7 |
14 |
| The cross-sectional spillovers of single stock circuit breakers |
0 |
0 |
0 |
23 |
0 |
2 |
3 |
74 |
| The effect of fragmentation in trading on market quality in the UK equity market |
0 |
0 |
0 |
0 |
1 |
4 |
5 |
6 |
| The effect of fragmentation in trading on market quality in the UK equity market |
0 |
0 |
0 |
27 |
4 |
5 |
7 |
87 |
| The effect of stock splits on liquidity in a dynamic model |
0 |
0 |
0 |
7 |
1 |
2 |
3 |
7 |
| The estimation of conditional densities |
0 |
0 |
0 |
7 |
3 |
3 |
5 |
39 |
| The existence and asymptotic properties of a backfitting projection algorithm under weak conditions |
0 |
0 |
0 |
2 |
2 |
3 |
3 |
29 |
| The existence and asymptotic properties of a backfitting projection algorithm under weak conditions |
0 |
0 |
0 |
2 |
1 |
3 |
4 |
46 |
| The impact of corporate QE on liquidity: evidence from the UK |
0 |
0 |
0 |
46 |
4 |
9 |
13 |
139 |
| The live method for generalized additive volatility models |
0 |
0 |
0 |
1 |
3 |
3 |
3 |
38 |
| The shape of the risk premium: evidence from a semiparametric GARCH model |
0 |
0 |
0 |
1 |
1 |
2 |
3 |
32 |
| Uniform Bahadur Representation for LocalPolynomial Estimates of M-Regressionand Its Application to The Additive Model |
0 |
0 |
0 |
3 |
7 |
9 |
9 |
48 |
| When will the Covid-19 pandemic peak? |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
8 |
| When will the Covid-19 pandemic peak? |
0 |
0 |
0 |
51 |
15 |
16 |
17 |
161 |
| Yield Curve Estimation by Kernel Smoothing |
0 |
0 |
0 |
48 |
0 |
2 |
2 |
181 |
| Yield Curve Estimation by Kernel Smoothing Methods |
0 |
0 |
1 |
358 |
0 |
3 |
4 |
762 |
| Yield Curve Estimation by Kernel Smoothing Methods |
0 |
0 |
0 |
9 |
1 |
4 |
7 |
77 |
| Yield curve estimation by kernel smoothing |
0 |
0 |
0 |
1 |
0 |
1 |
1 |
2 |
| Yield curve estimation by kernel smoothing methods |
0 |
0 |
0 |
5 |
0 |
3 |
5 |
39 |
| Total Working Papers |
4 |
26 |
119 |
19,910 |
717 |
1,448 |
2,208 |
70,422 |
| Journal Article |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| 03.5.2. Consistent Standard Errors for Target Variance Approach to GARCH Estimation |
0 |
0 |
0 |
23 |
1 |
2 |
2 |
301 |
| 03.5.2. Consistent Standard Errors for Target Variance Approach to GARCH Estimation—Solution |
0 |
0 |
1 |
39 |
2 |
2 |
7 |
110 |
| A CLOSED-FORM ESTIMATOR FOR THE GARCH(1,1) MODEL |
0 |
0 |
0 |
167 |
0 |
3 |
3 |
374 |
| A NONPARAMETRIC REGRESSION ESTIMATOR THAT ADAPTS TO ERROR DISTRIBUTION OF UNKNOWN FORM |
0 |
0 |
2 |
32 |
1 |
2 |
5 |
80 |
| A Nonparametric Prewhitened Covariance Estimator |
0 |
0 |
0 |
1 |
4 |
5 |
6 |
14 |
| A ReMeDI for Microstructure Noise |
0 |
1 |
1 |
11 |
2 |
6 |
9 |
40 |
| A Unified Framework for Specification Tests of Continuous Treatment Effect Models |
0 |
0 |
0 |
0 |
0 |
2 |
4 |
5 |
| A coupled component DCS-EGARCH model for intraday and overnight volatility |
0 |
1 |
2 |
14 |
3 |
5 |
8 |
69 |
| A discrete†choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance |
0 |
0 |
2 |
6 |
0 |
1 |
3 |
33 |
| A flexible semiparametric forecasting model for time series |
0 |
0 |
0 |
34 |
1 |
3 |
6 |
142 |
| A multiplicative bias reduction method for nonparametric regression |
0 |
0 |
1 |
50 |
0 |
2 |
5 |
112 |
| A new semiparametric estimation approach for large dynamic covariance matrices with multiple conditioning variables |
0 |
0 |
0 |
9 |
3 |
5 |
6 |
46 |
| A nonparametric test of a strong leverage hypothesis |
0 |
0 |
1 |
7 |
2 |
2 |
8 |
59 |
| A polarization-cohesion perspective on cross-country convergence |
0 |
1 |
1 |
56 |
1 |
4 |
6 |
252 |
| A score statistic for testing the presence of a stochastic trend in conditional variances |
0 |
0 |
0 |
1 |
0 |
2 |
2 |
4 |
| A semiparametric model for heterogeneous panel data with fixed effects |
0 |
1 |
1 |
29 |
0 |
6 |
11 |
135 |
| A semiparametric panel model for unbalanced data with application to climate change in the United Kingdom |
0 |
0 |
0 |
66 |
1 |
3 |
4 |
214 |
| A smoothed least squares estimator for threshold regression models |
0 |
0 |
1 |
169 |
0 |
4 |
7 |
413 |
| A unified framework for efficient estimation of general treatment models |
0 |
0 |
0 |
3 |
1 |
4 |
7 |
24 |
| A weighted sieve estimator for nonparametric time series models with nonstationary variables |
1 |
2 |
2 |
13 |
1 |
5 |
7 |
37 |
| AN ALMOST CLOSED FORM ESTIMATOR FOR THE EGARCH MODEL |
0 |
0 |
0 |
3 |
0 |
3 |
6 |
33 |
| AN INTRODUCTION TO ECONOMETRIC THEORY |
0 |
0 |
0 |
49 |
0 |
2 |
4 |
137 |
| AVERAGING OF AN INCREASING NUMBER OF MOMENT CONDITION ESTIMATORS |
0 |
0 |
0 |
8 |
2 |
2 |
4 |
55 |
| Adaptive Estimation in ARCH Models |
0 |
0 |
0 |
10 |
0 |
0 |
3 |
56 |
| Adaptive testing in arch models |
0 |
0 |
0 |
17 |
1 |
2 |
8 |
127 |
| Additive nonparametric models with time variable and both stationary and nonstationary regressors |
0 |
0 |
3 |
9 |
1 |
5 |
9 |
63 |
| Adjusted-range self-normalized confidence interval construction for censored dependent data |
0 |
0 |
1 |
3 |
2 |
4 |
11 |
20 |
| Advances in Robust and Flexible Inference in Econometrics: A Special Issue in Honour of Joel L. Horowitz |
0 |
1 |
1 |
9 |
2 |
4 |
9 |
61 |
| An Asymptotic Expansion in the GARCH(l, 1) Model |
0 |
0 |
0 |
12 |
0 |
3 |
5 |
42 |
| An improved bootstrap test of stochastic dominance |
1 |
1 |
5 |
134 |
20 |
21 |
40 |
387 |
| An optimization interpretation of integration and back‐fitting estimators for separable nonparametric models |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
3 |
| Annals issue on forecasting--Guest editors' introduction |
0 |
0 |
0 |
21 |
0 |
1 |
2 |
78 |
| Are there Monday effects in stock returns: A stochastic dominance approach |
0 |
0 |
1 |
130 |
3 |
4 |
5 |
342 |
| Chaohua Dong, Jiti Gao and Oliver Linton’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes |
0 |
0 |
0 |
1 |
1 |
2 |
4 |
19 |
| Classification of non-parametric regression functions in longitudinal data models |
0 |
0 |
0 |
19 |
0 |
1 |
1 |
82 |
| Comment |
0 |
0 |
0 |
5 |
1 |
1 |
2 |
39 |
| Comment on “Factor Models for High-Dimensional Tensor Time Series” by Rong Chen, Dan Yang, and Cun-Hui Zhang |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
16 |
| Comment on: Reflections on the Probability Space Induced by Moment Conditions with Implications for Bayesian Inference |
0 |
0 |
0 |
1 |
0 |
1 |
2 |
17 |
| Consistent Testing for Stochastic Dominance under General Sampling Schemes |
0 |
1 |
2 |
197 |
21 |
25 |
45 |
712 |
| Consistent estimation of a general nonparametric regression function in time series |
0 |
0 |
0 |
39 |
0 |
2 |
4 |
94 |
| Do Consumption-Based Asset Pricing Models Explain the Dynamics of Stock Market Returns? |
0 |
0 |
0 |
1 |
1 |
2 |
3 |
7 |
| Dynamic Autoregressive Liquidity (DArLiQ) |
0 |
0 |
1 |
1 |
0 |
1 |
4 |
4 |
| Dynamic Peer Groups of Arbitrage Characteristics |
0 |
0 |
0 |
0 |
1 |
2 |
4 |
6 |
| EDITORIAL |
0 |
0 |
0 |
13 |
2 |
4 |
5 |
71 |
| EFFICIENT ESTIMATION OF GENERALIZED ADDITIVE NONPARAMETRIC REGRESSION MODELS |
0 |
0 |
0 |
7 |
1 |
3 |
3 |
60 |
| ESTIMATING ADDITIVE NONPARAMETRIC MODELS BY PARTIAL Lq NORM: THE CURSE OF FRACTIONALITY |
0 |
0 |
0 |
2 |
0 |
3 |
3 |
24 |
| ESTIMATION FOR A NONSTATIONARY SEMI-STRONG GARCH(1,1) MODEL WITH HEAVY-TAILED ERRORS |
0 |
0 |
0 |
35 |
1 |
1 |
2 |
120 |
| ESTIMATION OF A SEMIPARAMETRIC IGARCH(1,1) MODEL |
0 |
0 |
0 |
14 |
2 |
2 |
2 |
62 |
| ESTIMATION OF AND INFERENCE ABOUT THE EXPECTED SHORTFALL FOR TIME SERIES WITH INFINITE VARIANCE |
0 |
0 |
0 |
15 |
1 |
1 |
2 |
74 |
| ESTIMATION OF THE KRONECKER COVARIANCE MODEL BY QUADRATIC FORM |
0 |
0 |
0 |
1 |
2 |
2 |
3 |
8 |
| Edgeworth Approximation for MINPIN Estimators in Semiparametric Regression Models |
0 |
0 |
0 |
8 |
0 |
1 |
3 |
34 |
| Edgeworth approximations for semiparametric instrumental variable estimators and test statistics |
0 |
0 |
0 |
24 |
1 |
1 |
2 |
127 |
| Efficient Semiparametric Estimation of the Fama–French Model and Extensions |
0 |
0 |
1 |
81 |
0 |
3 |
6 |
320 |
| Efficient estimation of a multivariate multiplicative volatility model |
0 |
0 |
1 |
87 |
1 |
5 |
8 |
219 |
| Efficient estimation of nonparametric regression in the presence of dynamic heteroskedasticity |
0 |
0 |
0 |
8 |
0 |
2 |
6 |
31 |
| Estimating Semiparametric ARCH(∞) Models by Kernel Smoothing Methods |
0 |
0 |
0 |
66 |
2 |
5 |
5 |
279 |
| Estimating features of a distribution from binomial data |
0 |
0 |
1 |
52 |
1 |
1 |
2 |
235 |
| Estimating quadratic variation consistently in the presence of endogenous and diurnal measurement error |
0 |
0 |
0 |
54 |
1 |
6 |
9 |
180 |
| Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error |
0 |
0 |
0 |
47 |
1 |
2 |
7 |
131 |
| Estimation and inference for the counterfactual distribution and quantile functions in continuous treatment models |
0 |
0 |
0 |
6 |
2 |
7 |
10 |
34 |
| Estimation and inference in semiparametric quantile factor models |
0 |
0 |
1 |
14 |
2 |
4 |
5 |
53 |
| Estimation of Linear Regression Models from Bid-Ask Data by a Spread-Tolerant Estimator |
0 |
0 |
0 |
26 |
0 |
1 |
2 |
188 |
| Estimation of Semiparametric Models when the Criterion Function Is Not Smooth |
0 |
0 |
0 |
53 |
2 |
4 |
6 |
346 |
| Estimation of a multiplicative correlation structure in the large dimensional case |
0 |
0 |
0 |
1 |
0 |
1 |
3 |
33 |
| Estimation of a nonparametric model for bond prices from cross-section and time series information |
0 |
0 |
0 |
6 |
0 |
0 |
2 |
30 |
| Estimation of semiparametric locally stationary diffusion models |
1 |
1 |
1 |
30 |
2 |
2 |
2 |
87 |
| Estimation with mixed data frequencies: A bias-correction approach |
1 |
1 |
1 |
1 |
1 |
7 |
9 |
13 |
| Estimation, Inference and Specification AnalysisH. White, Cambridge University Press, 1994 |
0 |
0 |
0 |
100 |
0 |
0 |
0 |
222 |
| Evaluating Value-at-Risk Models via Quantile Regression |
0 |
0 |
0 |
149 |
1 |
3 |
4 |
386 |
| Evaluating Value-at-Risk Models via Quantile Regression |
0 |
0 |
1 |
28 |
1 |
1 |
3 |
108 |
| Flexible Term Structure Estimation: Which Method is Preferred? |
0 |
0 |
0 |
49 |
0 |
3 |
3 |
118 |
| GLOBAL BAHADUR REPRESENTATION FOR NONPARAMETRIC CENSORED REGRESSION QUANTILES AND ITS APPLICATIONS |
0 |
0 |
0 |
7 |
0 |
2 |
4 |
57 |
| GMM estimation for high-dimensional panel data models |
0 |
0 |
6 |
6 |
2 |
6 |
18 |
18 |
| HIGHER ORDER ASYMPTOTIC THEORY WHEN A PARAMETER IS ON A BOUNDARY WITH AN APPLICATION TO GARCH MODELS |
0 |
0 |
0 |
27 |
2 |
3 |
3 |
98 |
| High dimensional semiparametric moment restriction models |
0 |
0 |
0 |
1 |
7 |
10 |
13 |
18 |
| INFERENCE ON A SEMIPARAMETRIC MODEL WITH GLOBAL POWER LAW AND LOCAL NONPARAMETRIC TRENDS |
0 |
0 |
0 |
6 |
0 |
3 |
4 |
37 |
| INTRODUCTION TO THE SPECIAL ISSUE ON INVERSE PROBLEMS |
0 |
0 |
0 |
13 |
0 |
0 |
0 |
41 |
| Identification and nonparametric estimation of a transformed additively separable model |
0 |
0 |
0 |
52 |
1 |
2 |
4 |
193 |
| Implications of High-Frequency Trading for Security Markets |
0 |
0 |
1 |
17 |
4 |
4 |
5 |
95 |
| Integration and backfitting methods in additive models-finite sample properties and comparison |
0 |
0 |
0 |
37 |
2 |
2 |
4 |
127 |
| Is There Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors |
0 |
0 |
0 |
94 |
2 |
3 |
3 |
417 |
| Kolmogorov–Smirnov type testing for structural breaks: A new adjusted-range based self-normalization approach |
1 |
4 |
5 |
7 |
1 |
7 |
11 |
20 |
| LET’S GET LADE: ROBUST ESTIMATION OF SEMIPARAMETRIC MULTIPLICATIVE VOLATILITY MODELS |
0 |
0 |
0 |
2 |
2 |
3 |
3 |
47 |
| LOCAL LINEAR FITTING UNDER NEAR EPOCH DEPENDENCE |
0 |
0 |
0 |
18 |
1 |
1 |
2 |
100 |
| LOCAL LINEAR FITTING UNDER NEAR EPOCH DEPENDENCE: UNIFORM CONSISTENCY WITH CONVERGENCE RATES |
0 |
0 |
0 |
9 |
0 |
1 |
3 |
58 |
| Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems |
0 |
1 |
1 |
300 |
2 |
7 |
20 |
979 |
| Local nonlinear least squares: Using parametric information in nonparametric regression |
0 |
0 |
0 |
97 |
0 |
0 |
1 |
267 |
| More Efficient Local Polynomial Estimation in Nonparametric Regression With Autocorrelated Errors |
0 |
0 |
1 |
82 |
0 |
0 |
2 |
204 |
| Multiscale clustering of nonparametric regression curves |
0 |
0 |
0 |
9 |
1 |
2 |
4 |
41 |
| Multivariate density estimation using dimension reducing information and tail flattening transformations |
0 |
0 |
0 |
5 |
0 |
1 |
2 |
58 |
| NONPARAMETRIC ESTIMATION WITH AGGREGATED DATA |
0 |
0 |
0 |
9 |
0 |
1 |
3 |
48 |
| NONPARAMETRIC EULER EQUATION IDENTIFICATION AND ESTIMATION |
0 |
0 |
1 |
4 |
0 |
2 |
5 |
18 |
| NONPARAMETRIC INFERENCE FOR UNBALANCED TIME SERIES DATA |
0 |
0 |
0 |
7 |
3 |
3 |
5 |
59 |
| NONPARAMETRIC TRANSFORMATION REGRESSION WITH NONSTATIONARY DATA |
0 |
0 |
0 |
13 |
2 |
5 |
5 |
62 |
| News-implied linkages and local dependency in the equity market |
0 |
0 |
0 |
0 |
4 |
5 |
6 |
8 |
| Non-parametric regression with a latent time series |
0 |
0 |
0 |
56 |
1 |
3 |
10 |
243 |
| Nonparametric Censored and Truncated Regression |
0 |
0 |
0 |
124 |
2 |
4 |
4 |
560 |
| Nonparametric Matching and Efficient Estimators of Homothetically Separable Functions |
0 |
0 |
0 |
40 |
1 |
3 |
4 |
308 |
| Nonparametric estimation and inference about the overlap of two distributions |
0 |
0 |
2 |
92 |
5 |
10 |
14 |
392 |
| Nonparametric estimation of a periodic sequence in the presence of a smooth trend |
0 |
2 |
2 |
9 |
1 |
4 |
4 |
55 |
| Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff |
0 |
0 |
4 |
12 |
3 |
4 |
14 |
43 |
| Nonparametric estimation of mediation effects with a general treatment |
0 |
0 |
3 |
4 |
2 |
2 |
9 |
12 |
| Nonparametric estimation of multivariate elliptic densities via finite mixture sieves |
0 |
0 |
1 |
4 |
1 |
1 |
3 |
30 |
| Nonparametric factor analysis of residual time series |
0 |
0 |
1 |
61 |
2 |
4 |
7 |
186 |
| Nonparametric neural network estimation of Lyapunov exponents and a direct test for chaos |
0 |
0 |
0 |
152 |
1 |
1 |
1 |
506 |
| Nonparametric transformation to white noise |
0 |
0 |
0 |
33 |
0 |
1 |
4 |
133 |
| Nonstandard Errors |
1 |
3 |
16 |
42 |
5 |
18 |
65 |
156 |
| On internally corrected and symmetrized kernel estimators for nonparametric regression |
0 |
1 |
1 |
8 |
1 |
2 |
3 |
44 |
| On unit free assessment of the extent of multilateral distributional variation |
0 |
0 |
0 |
1 |
0 |
3 |
7 |
9 |
| QUANTILOGRAMS UNDER STRONG DEPENDENCE |
0 |
0 |
0 |
1 |
0 |
1 |
3 |
9 |
| Review 2 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
| Review 2 |
0 |
0 |
0 |
2 |
1 |
2 |
2 |
37 |
| SECOND-ORDER APPROXIMATION FOR ADAPTIVE REGRESSION ESTIMATORS |
0 |
0 |
0 |
10 |
1 |
3 |
3 |
49 |
| Second Order Approximation in the Partially Linear Regression Model |
0 |
0 |
0 |
114 |
0 |
2 |
3 |
690 |
| Semi- and Nonparametric ARCH Processes |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
5 |
| Semiparametric Regression Analysis With Missing Response at Random |
0 |
0 |
0 |
65 |
3 |
6 |
9 |
198 |
| Semiparametric Ultra-High Dimensional Model Averaging of Nonlinear Dynamic Time Series |
0 |
0 |
2 |
3 |
1 |
2 |
7 |
32 |
| Semiparametric dynamic portfolio choice with multiple conditioning variables |
0 |
0 |
0 |
4 |
0 |
2 |
6 |
52 |
| Semiparametric estimation of Markov decision processes with continuous state space |
0 |
0 |
0 |
25 |
0 |
1 |
2 |
116 |
| Semiparametric estimation of a characteristic-based factor model of common stock returns |
0 |
0 |
0 |
56 |
2 |
3 |
10 |
181 |
| Semiparametric estimation of the bid–ask spread in extended roll models |
0 |
0 |
0 |
15 |
0 |
2 |
5 |
71 |
| Semiparametric identification of the bid–ask spread in extended Roll models |
0 |
0 |
0 |
7 |
0 |
1 |
5 |
60 |
| Semiparametric methods in econometrics |
0 |
0 |
0 |
109 |
1 |
1 |
3 |
235 |
| Shaoran Li, Oliver Linton and Shuyi Ge's contribution to the ‘First Discussion Meeting on Statistical Aspects of the Covid‐19 Pandemic’ |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
3 |
| Shuyi Ge, Oliver Linton and Shaoran Li's contribution to the ‘First Discussion Meeting on Statistical Aspects of the Covid‐19 Pandemic’ |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
7 |
| Similarity, dissimilarity and exceptionality: generalizing Gini’s transvariation to measure “differentness” in many distributions |
0 |
0 |
1 |
13 |
3 |
4 |
7 |
45 |
| Standard Errors for Nonparametric Regression |
0 |
0 |
0 |
5 |
1 |
2 |
3 |
21 |
| Symmetrizing and unitizing transformations for linear smoother weights |
0 |
0 |
0 |
0 |
2 |
2 |
2 |
8 |
| THE LIVE METHOD FOR GENERALIZED ADDITIVE VOLATILITY MODELS |
0 |
0 |
0 |
8 |
2 |
2 |
5 |
53 |
| Testing Conditional Independence Restrictions |
0 |
0 |
2 |
8 |
0 |
2 |
7 |
42 |
| Testing Forward Exchange Rate Unbiasedness Efficiently: A Semiparametric Approach |
0 |
0 |
0 |
1 |
0 |
3 |
3 |
4 |
| Testing additivity in generalized nonparametric regression models with estimated parameters |
0 |
0 |
2 |
64 |
0 |
2 |
6 |
217 |
| Testing for Stochastic Monotonicity |
0 |
0 |
0 |
99 |
0 |
0 |
2 |
403 |
| Testing for the stochastic dominance efficiency of a given portfolio |
0 |
0 |
0 |
9 |
1 |
2 |
2 |
96 |
| Testing for time stochastic dominance |
0 |
0 |
1 |
4 |
2 |
2 |
9 |
19 |
| Testing forward exchange rate unbiasedness efficiently: A semiparametric approach |
0 |
0 |
0 |
0 |
1 |
4 |
6 |
23 |
| Testing forward exchange rate unbiasedness efficiently: a semiparametric approach |
0 |
0 |
0 |
247 |
0 |
7 |
7 |
1,066 |
| Testing stochastic dominance with many conditioning variables |
0 |
0 |
1 |
1 |
0 |
1 |
4 |
6 |
| Testing the capital asset pricing model efficiently under elliptical symmetry: a semiparametric approach |
0 |
0 |
0 |
241 |
2 |
5 |
7 |
1,072 |
| Testing the capital asset pricing model efficiently under elliptical symmetry: a semiparametric approach |
0 |
0 |
0 |
4 |
3 |
6 |
6 |
16 |
| Testing the martingale hypothesis for gross returns |
0 |
0 |
0 |
2 |
1 |
1 |
1 |
54 |
| The Effect of Fragmentation in Trading on Market Quality in the UK Equity Market |
0 |
0 |
0 |
5 |
0 |
0 |
4 |
39 |
| The Froot-Stein Model Revisited |
0 |
0 |
0 |
2 |
0 |
1 |
3 |
29 |
| The Impact of Corporate QE on Liquidity: Evidence from the UK |
0 |
1 |
1 |
3 |
0 |
1 |
3 |
16 |
| The Shape of the Risk Premium: Evidence from a Semiparametric Generalized Autoregressive Conditional Heteroscedasticity Model |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
137 |
| The asymptotic distribution of nonparametric estimates of the Lyapunov exponent for stochastic time series |
0 |
0 |
0 |
40 |
1 |
3 |
4 |
220 |
| The behaviour of betting and currency markets on the night of the EU referendum |
0 |
0 |
0 |
13 |
2 |
3 |
4 |
59 |
| The common and specific components of dynamic volatility |
0 |
0 |
1 |
114 |
2 |
4 |
7 |
319 |
| The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series |
2 |
3 |
9 |
122 |
10 |
27 |
49 |
466 |
| The lower regression function and testing expectation dependence dominance hypotheses |
0 |
0 |
0 |
2 |
1 |
1 |
4 |
11 |
| The quantilogram: With an application to evaluating directional predictability |
0 |
0 |
1 |
86 |
2 |
6 |
10 |
241 |
| UNIFORM BAHADUR REPRESENTATION FOR LOCAL POLYNOMIAL ESTIMATES OF M-REGRESSION AND ITS APPLICATION TO THE ADDITIVE MODEL |
0 |
0 |
0 |
33 |
5 |
8 |
10 |
131 |
| When will the Covid-19 pandemic peak? |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
37 |
| Yield curve estimation by kernel smoothing methods |
0 |
0 |
1 |
148 |
2 |
4 |
7 |
508 |
| Total Journal Articles |
8 |
26 |
103 |
5,531 |
219 |
496 |
933 |
21,308 |
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