| 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 |
2 |
4 |
63 |
| A Theoretical Comparison Between Integrated and Realized Volatilies |
0 |
0 |
0 |
0 |
1 |
6 |
14 |
179 |
| A Theoretical Comparison Between Integrated and Realized Volatilies |
0 |
0 |
0 |
64 |
0 |
4 |
6 |
293 |
| A Theoretical Comparison Between Integrated and Realized Volatilities |
0 |
0 |
0 |
153 |
2 |
3 |
6 |
533 |
| ARMA REPRESENTATION OF INTEGRATED AND REALIZED VARIANCES |
0 |
0 |
0 |
19 |
0 |
5 |
8 |
210 |
| ARMA Representation of Integrated and Realized Variances |
0 |
0 |
0 |
54 |
0 |
1 |
4 |
198 |
| ARMA Representation of Integrated and Realized Variances |
0 |
0 |
0 |
134 |
0 |
0 |
5 |
697 |
| ARMA Representation of Two-Factor Models |
0 |
0 |
0 |
297 |
0 |
1 |
6 |
1,067 |
| Aggregations and Marginalization of GARCH and Stochastic Volatility Models |
0 |
0 |
2 |
209 |
0 |
5 |
12 |
616 |
| Aggregations and Marginalization of Garch and Stochastic Volatility Models |
0 |
0 |
0 |
0 |
1 |
2 |
9 |
458 |
| An Eigenfunction Approach for Volatility Modeling |
0 |
0 |
0 |
1 |
0 |
5 |
8 |
283 |
| An Eigenfunction Approach for Volatility Modeling |
0 |
0 |
0 |
260 |
0 |
6 |
8 |
776 |
| An Eigenfunction Approach for Volatility Modeling |
0 |
0 |
0 |
311 |
1 |
12 |
35 |
1,407 |
| Analytic Evaluation of Volatility Forecasts |
0 |
0 |
0 |
815 |
0 |
3 |
4 |
1,885 |
| Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns |
0 |
0 |
0 |
53 |
0 |
4 |
6 |
117 |
| Bootstrapping pre-averaged realized volatility under market microstructure noise |
0 |
0 |
0 |
58 |
0 |
4 |
5 |
170 |
| Bootstrapping realized multivariate volatility measures |
0 |
0 |
0 |
6 |
0 |
2 |
6 |
68 |
| CORRECTING THE ERRORS: A NOTE ON VOLATILITY FORECAST EVALUATION BASED ON HIGH-FREQUENCY DATA AND REALIZED VOLATILITIES |
0 |
0 |
0 |
119 |
0 |
7 |
9 |
454 |
| Correcting the Errors: A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities |
0 |
0 |
0 |
171 |
0 |
6 |
9 |
500 |
| Correcting the Errors: A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities |
0 |
0 |
0 |
421 |
0 |
8 |
12 |
963 |
| Expected Value Models: A New Approach |
0 |
0 |
0 |
1 |
0 |
2 |
4 |
2,355 |
| GARCH and Irregularly Spaced Data |
0 |
0 |
0 |
1 |
0 |
2 |
3 |
29 |
| Generalized Disappointment Aversion, Long Run Volatility Risk and Asset Prices |
0 |
0 |
0 |
27 |
1 |
3 |
5 |
112 |
| Generalized Disappointment Aversion, Long Run Volatility Risk and Asset Prices |
0 |
0 |
0 |
88 |
1 |
3 |
9 |
262 |
| Quadratic M-Estimators for ARCH-Type Processes |
0 |
0 |
0 |
38 |
1 |
7 |
8 |
263 |
| Quadratic M-Estimators for ARCH-Type Processes |
0 |
0 |
0 |
209 |
1 |
2 |
7 |
955 |
| TESTING NORMALITY: A GMM APPROACH |
0 |
0 |
0 |
64 |
0 |
2 |
8 |
346 |
| Temporal Aggregation of Volatility Models |
0 |
0 |
0 |
133 |
1 |
9 |
11 |
301 |
| Temporal Aggregation of Volatility Models |
0 |
0 |
0 |
428 |
0 |
5 |
8 |
1,347 |
| Testing Distributional Assumptions: A GMM Approach |
0 |
0 |
0 |
0 |
0 |
7 |
10 |
305 |
| Testing Distributional Assumptions: A GMM Approach |
0 |
0 |
0 |
114 |
0 |
6 |
10 |
436 |
| Testing Normality: A GMM Approach |
0 |
0 |
0 |
309 |
2 |
5 |
6 |
1,593 |
| Testing Normality: A GMM Approach |
0 |
0 |
0 |
183 |
0 |
4 |
8 |
707 |
| The Economic Value of Realized Volatility: Using High-Frequency Returns for Option Valuation |
0 |
0 |
4 |
101 |
1 |
3 |
19 |
414 |
| Volatility Forecasting when the Noise Variance Is Time-Varying |
0 |
0 |
0 |
13 |
2 |
6 |
8 |
66 |
| Total Working Papers |
0 |
0 |
6 |
4,861 |
15 |
152 |
300 |
20,428 |
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