| Working Paper |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Distributional Approach to Realized Volatility |
0 |
0 |
0 |
7 |
0 |
1 |
5 |
64 |
| A Theoretical Comparison Between Integrated and Realized Volatilies |
0 |
0 |
0 |
0 |
0 |
0 |
14 |
179 |
| A Theoretical Comparison Between Integrated and Realized Volatilies |
0 |
0 |
0 |
64 |
0 |
2 |
8 |
295 |
| A Theoretical Comparison Between Integrated and Realized Volatilities |
0 |
0 |
0 |
153 |
1 |
7 |
13 |
540 |
| ARMA REPRESENTATION OF INTEGRATED AND REALIZED VARIANCES |
0 |
0 |
0 |
19 |
0 |
1 |
9 |
211 |
| ARMA Representation of Integrated and Realized Variances |
0 |
0 |
0 |
134 |
0 |
2 |
7 |
699 |
| ARMA Representation of Integrated and Realized Variances |
0 |
0 |
0 |
54 |
1 |
3 |
7 |
201 |
| ARMA Representation of Two-Factor Models |
0 |
0 |
0 |
297 |
0 |
1 |
6 |
1,068 |
| Aggregations and Marginalization of GARCH and Stochastic Volatility Models |
0 |
1 |
3 |
210 |
0 |
2 |
14 |
618 |
| Aggregations and Marginalization of Garch and Stochastic Volatility Models |
0 |
0 |
0 |
0 |
1 |
5 |
14 |
463 |
| An Eigenfunction Approach for Volatility Modeling |
0 |
0 |
0 |
311 |
0 |
3 |
38 |
1,410 |
| An Eigenfunction Approach for Volatility Modeling |
0 |
0 |
0 |
1 |
1 |
2 |
10 |
285 |
| An Eigenfunction Approach for Volatility Modeling |
0 |
1 |
1 |
261 |
0 |
1 |
9 |
777 |
| Analytic Evaluation of Volatility Forecasts |
0 |
0 |
0 |
815 |
1 |
8 |
12 |
1,893 |
| Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns |
0 |
0 |
0 |
53 |
1 |
6 |
11 |
123 |
| Bootstrapping pre-averaged realized volatility under market microstructure noise |
0 |
0 |
0 |
58 |
1 |
5 |
10 |
175 |
| Bootstrapping realized multivariate volatility measures |
0 |
0 |
0 |
6 |
1 |
4 |
10 |
72 |
| CORRECTING THE ERRORS: A NOTE ON VOLATILITY FORECAST EVALUATION BASED ON HIGH-FREQUENCY DATA AND REALIZED VOLATILITIES |
0 |
0 |
0 |
119 |
0 |
1 |
10 |
455 |
| Correcting the Errors: A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities |
0 |
0 |
0 |
421 |
1 |
5 |
17 |
968 |
| Correcting the Errors: A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities |
0 |
0 |
0 |
171 |
1 |
1 |
10 |
501 |
| Expected Value Models: A New Approach |
0 |
0 |
0 |
1 |
0 |
1 |
5 |
2,356 |
| GARCH and Irregularly Spaced Data |
0 |
0 |
0 |
1 |
0 |
5 |
8 |
34 |
| Generalized Disappointment Aversion, Long Run Volatility Risk and Asset Prices |
0 |
0 |
0 |
27 |
0 |
1 |
6 |
113 |
| Generalized Disappointment Aversion, Long Run Volatility Risk and Asset Prices |
0 |
0 |
0 |
88 |
0 |
5 |
14 |
267 |
| Quadratic M-Estimators for ARCH-Type Processes |
0 |
0 |
0 |
209 |
0 |
5 |
12 |
960 |
| Quadratic M-Estimators for ARCH-Type Processes |
0 |
0 |
0 |
38 |
0 |
1 |
9 |
264 |
| TESTING NORMALITY: A GMM APPROACH |
0 |
0 |
0 |
64 |
2 |
5 |
13 |
351 |
| Temporal Aggregation of Volatility Models |
0 |
0 |
0 |
428 |
0 |
1 |
8 |
1,348 |
| Temporal Aggregation of Volatility Models |
0 |
0 |
0 |
133 |
0 |
3 |
14 |
304 |
| Testing Distributional Assumptions: A GMM Approach |
0 |
0 |
0 |
114 |
2 |
4 |
14 |
440 |
| Testing Distributional Assumptions: A GMM Approach |
0 |
0 |
0 |
0 |
0 |
4 |
13 |
309 |
| Testing Normality: A GMM Approach |
0 |
0 |
0 |
309 |
1 |
3 |
9 |
1,596 |
| Testing Normality: A GMM Approach |
0 |
0 |
0 |
183 |
3 |
6 |
14 |
713 |
| The Economic Value of Realized Volatility: Using High-Frequency Returns for Option Valuation |
0 |
0 |
3 |
101 |
1 |
2 |
19 |
416 |
| Volatility Forecasting when the Noise Variance Is Time-Varying |
0 |
0 |
0 |
13 |
1 |
4 |
12 |
70 |
| Total Working Papers |
0 |
2 |
7 |
4,863 |
20 |
110 |
404 |
20,538 |
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