| 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 |
0 |
5 |
64 |
| A Theoretical Comparison Between Integrated and Realized Volatilies |
0 |
0 |
0 |
0 |
1 |
1 |
14 |
180 |
| A Theoretical Comparison Between Integrated and Realized Volatilies |
0 |
0 |
0 |
64 |
1 |
2 |
10 |
297 |
| A Theoretical Comparison Between Integrated and Realized Volatilities |
0 |
0 |
0 |
153 |
0 |
1 |
12 |
540 |
| ARMA REPRESENTATION OF INTEGRATED AND REALIZED VARIANCES |
0 |
0 |
0 |
19 |
0 |
0 |
9 |
211 |
| ARMA Representation of Integrated and Realized Variances |
0 |
0 |
0 |
54 |
1 |
2 |
8 |
202 |
| ARMA Representation of Integrated and Realized Variances |
0 |
0 |
0 |
134 |
2 |
2 |
9 |
701 |
| ARMA Representation of Two-Factor Models |
0 |
0 |
0 |
297 |
1 |
1 |
6 |
1,069 |
| Aggregations and Marginalization of GARCH and Stochastic Volatility Models |
1 |
1 |
4 |
211 |
1 |
1 |
15 |
619 |
| Aggregations and Marginalization of Garch and Stochastic Volatility Models |
0 |
0 |
0 |
0 |
1 |
2 |
14 |
464 |
| An Eigenfunction Approach for Volatility Modeling |
0 |
0 |
0 |
1 |
0 |
1 |
9 |
285 |
| An Eigenfunction Approach for Volatility Modeling |
0 |
0 |
0 |
311 |
1 |
1 |
37 |
1,411 |
| An Eigenfunction Approach for Volatility Modeling |
0 |
0 |
1 |
261 |
1 |
1 |
9 |
778 |
| Analytic Evaluation of Volatility Forecasts |
0 |
0 |
0 |
815 |
0 |
2 |
13 |
1,894 |
| Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns |
0 |
0 |
0 |
53 |
0 |
1 |
10 |
123 |
| Bootstrapping pre-averaged realized volatility under market microstructure noise |
0 |
0 |
0 |
58 |
2 |
3 |
12 |
177 |
| Bootstrapping realized multivariate volatility measures |
0 |
0 |
0 |
6 |
1 |
3 |
12 |
74 |
| CORRECTING THE ERRORS: A NOTE ON VOLATILITY FORECAST EVALUATION BASED ON HIGH-FREQUENCY DATA AND REALIZED VOLATILITIES |
0 |
0 |
0 |
119 |
1 |
2 |
11 |
457 |
| Correcting the Errors: A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities |
0 |
0 |
0 |
171 |
0 |
2 |
11 |
502 |
| Correcting the Errors: A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities |
0 |
0 |
0 |
421 |
1 |
2 |
17 |
969 |
| Expected Value Models: A New Approach |
0 |
0 |
0 |
1 |
0 |
0 |
4 |
2,356 |
| GARCH and Irregularly Spaced Data |
0 |
0 |
0 |
1 |
0 |
0 |
8 |
34 |
| Generalized Disappointment Aversion, Long Run Volatility Risk and Asset Prices |
0 |
0 |
0 |
27 |
0 |
0 |
6 |
113 |
| Generalized Disappointment Aversion, Long Run Volatility Risk and Asset Prices |
0 |
0 |
0 |
88 |
0 |
0 |
13 |
267 |
| Quadratic M-Estimators for ARCH-Type Processes |
0 |
0 |
0 |
38 |
0 |
0 |
9 |
264 |
| Quadratic M-Estimators for ARCH-Type Processes |
0 |
0 |
0 |
209 |
0 |
0 |
11 |
960 |
| TESTING NORMALITY: A GMM APPROACH |
0 |
0 |
0 |
64 |
0 |
2 |
13 |
351 |
| Temporal Aggregation of Volatility Models |
0 |
0 |
0 |
133 |
1 |
2 |
15 |
306 |
| Temporal Aggregation of Volatility Models |
1 |
1 |
1 |
429 |
2 |
2 |
10 |
1,350 |
| Testing Distributional Assumptions: A GMM Approach |
0 |
0 |
0 |
114 |
0 |
2 |
13 |
440 |
| Testing Distributional Assumptions: A GMM Approach |
0 |
0 |
0 |
0 |
0 |
0 |
13 |
309 |
| Testing Normality: A GMM Approach |
0 |
0 |
0 |
309 |
2 |
3 |
11 |
1,598 |
| Testing Normality: A GMM Approach |
0 |
0 |
0 |
183 |
0 |
3 |
13 |
713 |
| The Economic Value of Realized Volatility: Using High-Frequency Returns for Option Valuation |
0 |
0 |
2 |
101 |
0 |
1 |
16 |
416 |
| Volatility Forecasting when the Noise Variance Is Time-Varying |
0 |
0 |
0 |
13 |
0 |
1 |
12 |
70 |
| Total Working Papers |
2 |
2 |
8 |
4,865 |
20 |
46 |
410 |
20,564 |
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