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A Cross-Sectional Performance Measure for Portfolio Management |
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0 |
0 |
22 |
0 |
0 |
4 |
55 |

A Cross-Sectional Performance Measure for Portfolio Management |
0 |
1 |
2 |
39 |
0 |
1 |
6 |
122 |

A Meta-Distribution for Non-Stationary Samples |
0 |
0 |
0 |
44 |
0 |
1 |
7 |
262 |

A New Modelling Test: The Univariate MT-STAR Model |
0 |
0 |
0 |
21 |
0 |
0 |
9 |
102 |

A Note on fair Value and Illiquid Markets |
0 |
0 |
0 |
23 |
0 |
0 |
3 |
53 |

A Performance Measure of Zero-Dollar Long/Short Equally Weighted Portfolios |
0 |
0 |
0 |
26 |
0 |
1 |
4 |
87 |

A SETAR model with long-memory dynamics |
0 |
0 |
1 |
427 |
0 |
1 |
8 |
816 |

A Short Note on the Nowcasting and the Forecasting of Euro-area GDP Using Non-Parametric Techniques |
0 |
0 |
0 |
22 |
0 |
0 |
4 |
30 |

A k- factor GIGARCH process: estimation and application to electricity market spot prices |
0 |
0 |
1 |
26 |
0 |
0 |
5 |
98 |

A mathematical resurgence of risk management: an extreme modeling of expert opinions |
0 |
0 |
0 |
26 |
0 |
1 |
3 |
52 |

A mathematical resurgence of risk management: an extreme modeling of expert opinions |
0 |
0 |
0 |
25 |
0 |
1 |
6 |
46 |

A modified Panjer algorithm for operational risk capital calculations |
0 |
0 |
1 |
87 |
0 |
0 |
3 |
214 |

A new algorithm for the loss distribution function with applications to Operational Risk Management |
0 |
0 |
0 |
71 |
0 |
0 |
2 |
156 |

A new algorithm for the loss distribution function with applications to Operational Risk Management |
0 |
0 |
0 |
41 |
0 |
0 |
0 |
61 |

A note on fair value and illiquid markets |
0 |
0 |
0 |
53 |
0 |
0 |
2 |
184 |

A note on self-similarity for discrete time series |
0 |
0 |
0 |
9 |
0 |
0 |
2 |
29 |

A note on self-similarity for discrete time series |
0 |
0 |
0 |
147 |
0 |
0 |
4 |
439 |

A performance measure of Zero-dollar Long/Short equally weighted portfolios |
0 |
0 |
2 |
59 |
0 |
2 |
8 |
277 |

A prospective study of the k-factor Gegenbauer processes with heteroscedastic errors and an application to inflation rates |
1 |
1 |
1 |
22 |
1 |
1 |
3 |
130 |

A short note on option pricing with Lévy Processes |
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0 |
0 |
16 |
0 |
0 |
6 |
108 |

A short note on option pricing with Lévy Processes |
0 |
0 |
0 |
3 |
0 |
0 |
5 |
26 |

A short note on the nowcasting and the forecasting of Euro-area GDP using non-parametric techniques |
0 |
0 |
0 |
24 |
0 |
0 |
1 |
28 |

A short note on the nowcasting and the forecasting of Euro-area GDP using non-parametric techniques |
0 |
0 |
0 |
31 |
0 |
0 |
4 |
116 |

A test for a new modelling: The Univariate MT-STAR Model |
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0 |
0 |
44 |
0 |
0 |
6 |
177 |

A test for a new modelling: The Univariate MT-STAR Model |
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1 |
1 |
67 |
5 |
15 |
42 |
181 |

A theoretical framework for trading experiments |
0 |
0 |
1 |
91 |
1 |
1 |
11 |
151 |

A theoretical framework for trading experiments |
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0 |
0 |
31 |
1 |
1 |
6 |
38 |

Aggregation of Market Risks using Pair-Copulas |
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0 |
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18 |
0 |
0 |
3 |
60 |

Aggregation of Market Risks using Pair-Copulas |
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0 |
2 |
35 |
1 |
2 |
16 |
155 |

Alternative Methodology for Turning-Point Detection in Business Cycle: A Wavelet Approach |
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0 |
0 |
103 |
1 |
1 |
6 |
312 |

Alternative Methodology for Turning-Point Detection in Business Cycle: A Wavelet Approach |
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0 |
0 |
33 |
1 |
1 |
5 |
84 |

Alternative Modeling for Long Term Risk |
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0 |
0 |
23 |
0 |
0 |
1 |
35 |

Alternative Modeling for Long Term Risk |
0 |
0 |
0 |
40 |
0 |
0 |
3 |
83 |

Alternative methods for forecasting GDP |
0 |
0 |
1 |
88 |
1 |
1 |
10 |
81 |

Alternative methods for forecasting GDP |
0 |
0 |
1 |
197 |
0 |
0 |
19 |
540 |

Alternative methods for forecasting GDP |
0 |
0 |
0 |
77 |
0 |
1 |
7 |
115 |

An Autocorrelated Loss Distribution Approach: back to the time series |
0 |
0 |
0 |
23 |
1 |
1 |
4 |
51 |

An Econometric Study of Vine Copulas |
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0 |
0 |
12 |
0 |
1 |
4 |
48 |

An Econometric Study of Vine Copulas |
0 |
0 |
0 |
69 |
0 |
1 |
4 |
192 |

An Omnibus Test to Detect Time-Heterogeneity in Time Series |
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0 |
0 |
19 |
0 |
0 |
3 |
33 |

An Omnibus Test to Detect Time-Heterogeneity in Time Series |
0 |
0 |
0 |
10 |
0 |
0 |
6 |
48 |

An econometric Study for Vine Copulas |
0 |
0 |
0 |
26 |
0 |
1 |
3 |
74 |

An econometric specification of monetary policy dark art |
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1 |
1 |
55 |
1 |
2 |
8 |
242 |

An economic view of carbon allowances market |
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0 |
0 |
46 |
0 |
0 |
1 |
67 |

An economic view of carbon allowances market |
0 |
0 |
1 |
96 |
0 |
0 |
7 |
328 |

An efficient threshold choice for operational risk capital computation |
0 |
0 |
0 |
16 |
2 |
2 |
8 |
62 |

An efficient threshold choice for operational risk capital computation |
1 |
1 |
2 |
78 |
3 |
4 |
11 |
207 |

An efficient threshold choice for operational risk capital computation |
0 |
0 |
0 |
4 |
1 |
2 |
6 |
22 |

An omnibus test to detect time-heterogeneity in time series |
0 |
0 |
0 |
35 |
0 |
0 |
4 |
106 |

Analyse d’Intervention et Prévisions. Problématique et Application à des données de la RATP |
0 |
0 |
0 |
9 |
1 |
1 |
9 |
60 |

Another Characterization of Long Memory Behavior |
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0 |
0 |
3 |
0 |
0 |
1 |
785 |

Asymptotic Behavior for the Extreme Values of a Linear Regression Model |
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0 |
0 |
18 |
0 |
0 |
0 |
76 |

BL-GARCH model with elliptical distributed innovations |
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0 |
0 |
51 |
0 |
0 |
0 |
102 |

Breaks or Long Memory Behaviour: An empirical Investigation |
0 |
0 |
0 |
40 |
0 |
0 |
19 |
73 |

Breaks or long memory behaviour: an empirical investigation |
0 |
0 |
0 |
45 |
0 |
0 |
1 |
39 |

Business surveys modelling with Seasonal-Cyclical Long Memory models |
0 |
0 |
0 |
4 |
0 |
0 |
10 |
33 |

Business surveys modelling with Seasonal-Cyclical Long Memory models |
0 |
0 |
1 |
18 |
0 |
1 |
6 |
107 |

Business surveys modelling with Seasonal-Cyclical Long Memory models |
0 |
0 |
0 |
10 |
0 |
0 |
1 |
48 |

Business surveys modelling with seasonal-cyclical long memory models |
0 |
0 |
0 |
52 |
0 |
0 |
6 |
176 |

CAN THE SUP LR TEST DISCRIMINATE BETWEEN DIFFERENT SWITCHING REGRESSIONS MODELS: APPLICATIONS TO THE U.S GNP AND THE US/UK EXCHANGE RATE? |
0 |
0 |
0 |
10 |
0 |
0 |
1 |
39 |

Change analysis of a dynamic copula for measuring dependence in multivariate financial data |
0 |
0 |
0 |
128 |
1 |
1 |
8 |
233 |

Change analysis of dynamic copula for measuring dependence in multivariate financial data |
0 |
0 |
0 |
25 |
0 |
1 |
7 |
80 |

Change analysis of dynamic copula for measuring dependence in multivariate financial data |
2 |
2 |
3 |
99 |
2 |
2 |
14 |
318 |

Changing-regime volatility: A fractionally integrated SETAR model |
0 |
0 |
0 |
28 |
0 |
0 |
8 |
99 |

Changing-regime volatility: A fractionally integrated SETAR model |
0 |
0 |
0 |
42 |
0 |
0 |
2 |
117 |

Chaos in Economics and Finance |
0 |
1 |
1 |
192 |
0 |
2 |
5 |
216 |

Chaos in economics and finance |
1 |
1 |
1 |
52 |
1 |
1 |
4 |
93 |

Chaos in economics and finance |
0 |
0 |
0 |
209 |
0 |
1 |
9 |
419 |

Comparaison of Several Estimation Procedures for Long Term Behavior |
0 |
0 |
0 |
7 |
0 |
0 |
0 |
27 |

Comparaison of several estimation procedures for long term behavior |
0 |
0 |
0 |
28 |
0 |
0 |
2 |
53 |

Comparing variable selection techniques for linear regression: LASSO and Autometrics |
0 |
0 |
0 |
229 |
3 |
7 |
23 |
567 |

Contagion Between the Financial Sphere and the Real Economy. Parametric and non Parametric Tools: A Comparison |
0 |
0 |
0 |
65 |
0 |
0 |
2 |
269 |

Cross-Sectional Analysis through Rank-based Dynamic |
1 |
1 |
1 |
39 |
2 |
2 |
4 |
170 |

Cross-Sectional Analysis through Rank-based Dynamic Portfolios |
0 |
0 |
0 |
16 |
0 |
0 |
1 |
63 |

De-noising with wavelets method in chaotic time series: application in climatology, energy and finance |
0 |
0 |
0 |
72 |
0 |
0 |
3 |
130 |

Dependence modelling of the joint extremes in a portfolio using Archimedean copulas: application to MSCI indices |
0 |
0 |
0 |
32 |
0 |
2 |
3 |
105 |

Dependence modelling of the joint extremes in a portfolio using Archimedean copulas: application to MSCI indices |
0 |
0 |
0 |
18 |
0 |
0 |
7 |
51 |

Derivative Pricing and Hedging on Carbon Market |
0 |
0 |
2 |
43 |
0 |
0 |
3 |
79 |

Derivative pricing and hedging on Carbon Market |
2 |
2 |
9 |
152 |
2 |
3 |
17 |
355 |

Detection of the Industrial Business Cycle using SETAR models |
0 |
0 |
0 |
28 |
0 |
0 |
4 |
86 |

Detection of the industrial business cycle using SETAR models |
0 |
0 |
0 |
96 |
0 |
0 |
2 |
279 |

Distortion Risk Measures or the Transformation of Unimodal Distributions into Multimodal Functions |
0 |
0 |
0 |
18 |
1 |
1 |
16 |
60 |

Distortion Risk Measures or the Transformation of Unimodal Distributions into Multimodal Functions |
0 |
0 |
0 |
27 |
2 |
2 |
3 |
54 |

Dynamic Analysis of the Insurance Linked Securities Index |
0 |
0 |
0 |
70 |
0 |
0 |
3 |
158 |

Dynamic analysis of the insurance linked securities index |
0 |
0 |
0 |
81 |
0 |
1 |
6 |
219 |

Dynamic factor analysis of carbon allowances prices: From classic Arbitrage Pricing Theory to Switching Regimes |
0 |
0 |
2 |
66 |
0 |
0 |
7 |
215 |

Dynamic factor analysis of carbon allowances prices: From classic Arbitrage Pricing Theory to Switching Regimes |
0 |
0 |
0 |
32 |
0 |
2 |
3 |
68 |

Effect of noise filtering on predictions: on the routes of chaos |
0 |
0 |
0 |
8 |
0 |
0 |
0 |
39 |

Effect of noise filtering on predictions: on the routes of chaos |
0 |
0 |
1 |
78 |
0 |
0 |
7 |
152 |

Emerging Countries Sovereign Rating Adjustment using Market Information: Impact on Financial Institution Investment Decisions |
0 |
2 |
3 |
18 |
1 |
5 |
11 |
92 |

Emerging Countries Sovereign Rating Adjustment using Market Information: Impact on Financial Institutions Investment Decisions |
0 |
0 |
1 |
6 |
0 |
2 |
10 |
35 |

Empirical Estimation of Tail Dependence Using Copulas. Application to Asian Markets |
0 |
0 |
1 |
107 |
0 |
1 |
8 |
255 |

Empirical Projected Copula Process and Conditional Independence An Extended Version |
0 |
0 |
0 |
9 |
0 |
0 |
10 |
37 |

Empirical Projected Copula Process and Conditional Independence an Extended Version |
0 |
0 |
0 |
28 |
0 |
0 |
0 |
82 |

Estimating parameters for a k-GIGARCH process |
0 |
0 |
0 |
8 |
0 |
0 |
1 |
43 |

Estimation and Applications of Gegenbauer Processes |
0 |
0 |
1 |
43 |
0 |
3 |
11 |
91 |

Estimation of k-Factor Gigarch Process: A Monte Carlo Study |
0 |
0 |
0 |
8 |
0 |
0 |
5 |
56 |

Estimation of k-factor GIGARCH process: a Monte Carlo study |
1 |
1 |
1 |
65 |
1 |
1 |
17 |
225 |

Estimation of k-factor GIGARCH process: a Monte Carlo study |
0 |
0 |
0 |
6 |
0 |
0 |
2 |
48 |

Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro |
0 |
1 |
3 |
111 |
1 |
4 |
13 |
229 |

Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro area |
0 |
0 |
1 |
67 |
0 |
0 |
10 |
114 |

Exact Maximum Likelihood estimation for the BL-GARCH model under elliptical distributed innovations |
0 |
0 |
0 |
63 |
0 |
1 |
8 |
222 |

Exact Maximum Likelihood estimation for the BL-GARCH model under elliptical distributed innovations |
0 |
0 |
0 |
15 |
0 |
0 |
0 |
63 |

Extreme Distribution of a Generalized Stochastic Volatility Model |
0 |
0 |
0 |
26 |
0 |
0 |
1 |
97 |

Extreme values of particular nonlinear processes |
0 |
0 |
0 |
6 |
0 |
0 |
5 |
27 |

Extreme values of random or chaotic discretization steps |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
16 |

Extreme values of random or chaotic discretization steps |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
32 |

Flexible time series models for subjective distribution estimation with monetary policy in view |
0 |
0 |
0 |
85 |
0 |
1 |
5 |
416 |

Flexible time series models for subjective distribution estimation with monetary policy in view |
0 |
0 |
0 |
3 |
0 |
0 |
4 |
28 |

Flexible time series models for subjective distribution estimation with monetary policy in view |
0 |
0 |
0 |
12 |
0 |
3 |
7 |
64 |

Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy |
1 |
1 |
1 |
141 |
1 |
1 |
5 |
326 |

Forecasting chaotic systems: The role of local Lyapunov exponents |
0 |
0 |
0 |
30 |
0 |
0 |
14 |
98 |

Forecasting chaotic systems: The role of local Lyapunov exponents |
0 |
0 |
0 |
43 |
0 |
0 |
5 |
107 |

Forecasting chaotic systems: the role of local Lyapunov exponents |
0 |
0 |
0 |
30 |
0 |
0 |
3 |
103 |

Forecasting chaotic systems: the role of local Lyapunov exponents |
0 |
0 |
1 |
160 |
0 |
1 |
9 |
420 |

Forecasting electricity spot market prices with a k-factor GIGARCH process |
1 |
1 |
1 |
131 |
1 |
1 |
6 |
439 |

Forecasting electricity spot market prices with a k-factor GIGARCH process |
0 |
0 |
0 |
14 |
0 |
0 |
3 |
56 |

Forecasting electricity spot market prices with a k-factor GIGARCH process |
0 |
0 |
0 |
101 |
1 |
1 |
6 |
132 |

Fractional and seasonal filtering |
0 |
0 |
0 |
1 |
0 |
0 |
2 |
29 |

Fractional seasonality: Models and Application to Economic Activity in the Euro Area |
0 |
0 |
0 |
19 |
0 |
0 |
8 |
81 |

Further evidence on the impact of economic news on interest |
0 |
0 |
0 |
36 |
0 |
0 |
5 |
139 |

Further evidence on the impact of economic news on interest rates |
0 |
0 |
0 |
56 |
0 |
0 |
3 |
191 |

Further evidence on the impact of economic news on interest rates |
0 |
0 |
0 |
10 |
0 |
0 |
2 |
41 |

GDP nowcasting with ragged-edge data: A semi-parametric modelling |
0 |
0 |
1 |
96 |
0 |
0 |
10 |
255 |

GDP nowcasting with ragged-edge data: A semi-parametric modelling |
0 |
0 |
0 |
60 |
0 |
0 |
25 |
127 |

GDP nowcasting with ragged-edge data: a semi-parametric modeling |
0 |
0 |
0 |
47 |
0 |
0 |
3 |
88 |

Global and local stationary modelling in finance: theory and empirical evidence |
1 |
1 |
1 |
190 |
2 |
2 |
6 |
453 |

Global and local stationary modelling in finance: theory and empirical evidence |
0 |
0 |
1 |
13 |
0 |
0 |
2 |
29 |

Hedging tranches index products: illustration of model dependency |
0 |
0 |
0 |
12 |
0 |
0 |
0 |
68 |

How Can We Define the Long Memory Concept? An Econometric Survey |
0 |
0 |
0 |
5 |
0 |
1 |
5 |
531 |

How can we define the concept of long memory ? An econometric survey |
0 |
0 |
0 |
125 |
0 |
2 |
15 |
398 |

Is it possible to discriminate between different switching regressions models? An empirical investigation |
0 |
0 |
1 |
28 |
0 |
0 |
5 |
118 |

La persistance dans les marchés financiers |
0 |
0 |
0 |
33 |
0 |
0 |
4 |
94 |

Likelihood-Related Estimation Methods and Non-Gaussian GARCH Processes |
0 |
0 |
0 |
31 |
0 |
0 |
3 |
90 |

Likelihood-Related Estimation Methods and Non-Gaussian GARCH Processes |
0 |
0 |
0 |
31 |
0 |
0 |
4 |
55 |

Local Lyapunov Exponents: A new way to predict chaotic systems |
0 |
0 |
0 |
30 |
0 |
0 |
6 |
77 |

Local Lyapunov exponents: Zero plays no role in Forecasting chaotic systems |
0 |
0 |
0 |
58 |
0 |
0 |
6 |
226 |

Long-memory dynamics in a SETAR model - Applications to stock markets |
0 |
0 |
0 |
60 |
0 |
0 |
2 |
132 |

Martingalized Historical approach for Option Pricing |
0 |
0 |
1 |
23 |
0 |
0 |
6 |
115 |

Martingalized Historical approach for Option Pricing |
0 |
0 |
0 |
33 |
0 |
0 |
3 |
113 |

Missing trader fraud on the emissions market |
0 |
0 |
0 |
29 |
0 |
0 |
1 |
110 |

Missing trader fraud on the emissions market |
0 |
0 |
1 |
132 |
1 |
2 |
10 |
270 |

Modelization and Nonparametric Estimation for a Dynamical System with Noise |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
19 |

Modelization and Nonparametric estimation for a dynamical system with noise |
0 |
0 |
0 |
14 |
0 |
0 |
3 |
38 |

Modelling squared returns using a SETAR model with long-memory dynamics |
0 |
0 |
1 |
34 |
0 |
0 |
10 |
137 |

Multi-period conditional distribution functions for heteroscedastic models with applications to VaR |
0 |
1 |
1 |
35 |
0 |
3 |
5 |
103 |

Multivariate VaRs for Operational Risk Capital Computation: a Vine Structure Approach |
0 |
0 |
0 |
4 |
1 |
2 |
4 |
25 |

Multivariate VaRs for Operational Risk Capital Computation: a Vine Structure Approach |
0 |
0 |
0 |
18 |
0 |
1 |
3 |
86 |

Multivariate VaRs for Operational Risk Capital Computation: a Vine Structure Approach |
0 |
0 |
0 |
58 |
0 |
1 |
8 |
99 |

New Prospects on Vines |
0 |
0 |
0 |
26 |
0 |
0 |
1 |
60 |

New prospects on vines |
0 |
0 |
0 |
36 |
0 |
0 |
4 |
146 |

Non-stationarity and meta-distribution |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
44 |

Non-stationarity and meta-distribution |
0 |
0 |
0 |
73 |
0 |
0 |
6 |
264 |

Nonlinear Dynamics and Recurrence Plots for Detecting Financial Crisis |
0 |
0 |
0 |
47 |
0 |
0 |
2 |
73 |

Nonlinear Dynamics and Recurrence Plots for Detecting Financial Crisis |
0 |
0 |
2 |
96 |
0 |
0 |
9 |
239 |

Note on new prospects on vines |
0 |
0 |
0 |
10 |
0 |
0 |
3 |
32 |

On the Necessity of Five Risk Measures |
0 |
0 |
0 |
70 |
1 |
2 |
6 |
53 |

On the necessity of five risk measures |
0 |
0 |
0 |
29 |
0 |
0 |
5 |
140 |

On the necessity of five risk measures |
0 |
0 |
0 |
139 |
0 |
1 |
5 |
104 |

On the use of nearest neighbors in finance |
0 |
0 |
0 |
92 |
0 |
0 |
2 |
189 |

Operational risk: A Basel II++ step before Basel III |
0 |
1 |
1 |
111 |
0 |
2 |
5 |
183 |

Operational risk: A Basel II++ step before Basel III |
0 |
0 |
1 |
6 |
0 |
3 |
14 |
61 |

Operational risk: A Basel II++ step before Basel III |
0 |
0 |
0 |
39 |
0 |
1 |
3 |
39 |

Operational risk: A Basel II++ step before Basel III |
0 |
1 |
1 |
25 |
0 |
1 |
4 |
58 |

Operational risk: a Basel II++ step before Basel III |
0 |
0 |
0 |
73 |
0 |
1 |
4 |
179 |

Option Pricing for GARCH-type Models with Generalized Hyperbolic Innovations |
0 |
0 |
0 |
26 |
0 |
0 |
24 |
96 |

Option Pricing under GARCH models with Generalized Hyperbolic distribution (II): Data and Results |
0 |
0 |
2 |
85 |
0 |
0 |
3 |
216 |

Option Pricing under GARCH models with Generalized Hyperbolic innovations (I): Methodology |
0 |
0 |
1 |
61 |
0 |
0 |
6 |
153 |

Option pricing for GARCH-type models with generalized hyperbolic innovations |
0 |
0 |
0 |
10 |
0 |
1 |
4 |
48 |

Option pricing for GARCH-type models with generalized hyperbolic innovations |
0 |
0 |
0 |
48 |
0 |
1 |
5 |
158 |

Option pricing under GARCH models with generalized hyperbolic innovations (I): methodology |
0 |
0 |
0 |
72 |
0 |
0 |
9 |
155 |

Option pricing under GARCH models with generalized hyperbolic innovations (II): data and results |
0 |
0 |
2 |
101 |
0 |
1 |
7 |
228 |

Option pricing with discrete time jump processes |
0 |
0 |
0 |
12 |
0 |
0 |
6 |
167 |

Option pricing with discrete time jump processes |
0 |
0 |
1 |
18 |
0 |
0 |
9 |
58 |

Option pricing with discrete time jump processes |
0 |
0 |
0 |
35 |
0 |
0 |
12 |
172 |

Portfolio Symmetry and Momentum |
0 |
0 |
0 |
14 |
1 |
1 |
8 |
129 |

Portfolio Symmetry and Momentum |
0 |
0 |
0 |
13 |
0 |
0 |
6 |
54 |

Portfolio Symmetry and Momentum |
0 |
0 |
0 |
34 |
0 |
0 |
2 |
168 |

Portfolio Symmetry and Momentum |
0 |
0 |
0 |
25 |
0 |
1 |
3 |
103 |

Predicting chaos with Lyapunov exponents: Zero plays no role in forecasting chaotic systems |
0 |
0 |
0 |
44 |
0 |
0 |
1 |
118 |

Predicting chaos with Lyapunov exponents: zero plays no role in forecasting chaotic systems |
0 |
1 |
2 |
56 |
0 |
1 |
6 |
172 |

Predictive Dimension: An Alternative Definition of the Embedding Dimension |
0 |
0 |
0 |
20 |
0 |
1 |
3 |
81 |

Pricing bivariate option under GARCH processes with time-varying copula |
0 |
0 |
0 |
11 |
0 |
1 |
24 |
70 |

Pricing bivariate option under GARCH processes with time-varying copula |
0 |
0 |
0 |
8 |
0 |
1 |
5 |
49 |

Pricing bivariate option under GARCH processes with time-varying copula |
0 |
0 |
0 |
142 |
1 |
2 |
5 |
375 |

Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market |
0 |
0 |
0 |
119 |
0 |
1 |
6 |
358 |

Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market |
0 |
0 |
0 |
15 |
0 |
1 |
5 |
59 |

Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market |
0 |
0 |
0 |
30 |
0 |
1 |
10 |
132 |

Probability density of the wavelet coefficients of a noisy chaos |
0 |
0 |
0 |
6 |
0 |
0 |
4 |
47 |

Probability density of the wavelet coefficients of a noisy chaos |
0 |
0 |
0 |
2 |
0 |
1 |
1 |
17 |

Prédiction of Chaotic Time Series in the Presence of Measurement Error: The Importance of Initial Conditions |
0 |
0 |
0 |
12 |
0 |
0 |
1 |
33 |

Real-time detection of the business cycle using SETAR models |
0 |
0 |
0 |
20 |
0 |
1 |
4 |
59 |

Regime switching models: real or spurious long memory ? |
0 |
0 |
0 |
11 |
0 |
0 |
2 |
43 |

Regime switching models: real or spurious long memory ? |
0 |
0 |
0 |
33 |
0 |
0 |
4 |
123 |

Risk Assessment for a Structured Product Specific to the CO2 Emission Permits Market |
0 |
0 |
0 |
18 |
0 |
0 |
1 |
36 |

Risk assessment for a Structured Product Specific to the CO2 Emission Permits Market |
0 |
0 |
1 |
26 |
0 |
0 |
3 |
107 |

Statistical Estimation of the Embedding Dimension of a Dynamic System |
0 |
0 |
0 |
21 |
1 |
1 |
3 |
46 |

Statistical evidence of tax fraud on the carbon allowances market |
0 |
0 |
1 |
33 |
0 |
0 |
3 |
82 |

Statistical evidence of tax fraud on the carbon allowances market |
0 |
0 |
1 |
23 |
0 |
0 |
4 |
95 |

Stress Testing Engineering: the real risk measurement? |
0 |
0 |
0 |
88 |
0 |
1 |
1 |
64 |

Stress Testing Engineering: the real risk measurement? |
0 |
0 |
3 |
140 |
0 |
0 |
13 |
123 |

Studies in Nonlinear Dynamics and Wavelets for Business Cycle Analysis |
0 |
1 |
2 |
43 |
0 |
3 |
13 |
129 |

Testing Fractional Order of Long Memory Processes: A Monte Carlo Study |
0 |
0 |
0 |
17 |
0 |
0 |
3 |
62 |

Testing for Leverage Effect in Financial Returns |
0 |
0 |
0 |
78 |
0 |
4 |
18 |
230 |

Testing for Leverage Effects in the Returns of US Equities |
0 |
0 |
1 |
45 |
0 |
1 |
9 |
97 |

Testing for Non-Linearity in Intra-Day Financial Series: The Cases of Two French Stocks |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
285 |

Testing fractional order of long memory processes: a Monte Carlo study |
0 |
0 |
0 |
70 |
0 |
0 |
2 |
184 |

Testing fractional order of long memory processes: a Monte Carlo study |
0 |
0 |
2 |
14 |
0 |
0 |
6 |
48 |

Testing unit roots and long range dependence of foreign exchange |
0 |
0 |
0 |
31 |
0 |
1 |
1 |
95 |

Testing unit roots and long range dependence of foreign exchange |
0 |
0 |
0 |
17 |
0 |
0 |
0 |
26 |

Tests of Structural Changes in Conditional Distributions with Unknown Changepoints |
0 |
0 |
0 |
44 |
0 |
1 |
5 |
47 |

Tests of structural changes in conditional distributions with unknown changepoints |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
19 |

The Multivariate Threshold Model -An Alternative to Detect Breaks and Hidden Cycles on Real Data |
0 |
0 |
0 |
35 |
0 |
0 |
2 |
66 |

The Multivariate k-Nearest Neighbor Model for Dependent Variables: One-Sided Estimation and Forecasting |
0 |
3 |
3 |
91 |
0 |
5 |
12 |
389 |

The Multivariate k-Nearest Neighbor Model for Dependent Variables: One-Sided Estimation and Forecasting |
0 |
0 |
0 |
38 |
0 |
0 |
0 |
84 |

The Stationary Seasonal Hyperbolic Asymmetric Power ARCH model |
0 |
0 |
1 |
37 |
0 |
0 |
9 |
151 |

The k-factor Gegenbauer asymmetric Power GARCH approach for modelling electricity spot price dynamics |
0 |
0 |
0 |
11 |
0 |
0 |
3 |
51 |

The k-factor Gegenbauer asymmetric Power GARCH approach for modelling electricity spot price dynamics |
0 |
0 |
0 |
59 |
1 |
2 |
6 |
264 |

Towards an understanding approach of the insurance linked securities market |
2 |
4 |
6 |
274 |
2 |
5 |
10 |
671 |

Towards an understanding approach of the insurance linked securities market |
1 |
1 |
1 |
34 |
1 |
2 |
4 |
93 |

Turning point chronology for the Euro-Zone: A Distance Plot Approach |
0 |
0 |
0 |
39 |
0 |
0 |
3 |
86 |

Turning point chronology for the Euro-Zone: A Distance Plot Approach |
0 |
0 |
0 |
19 |
0 |
0 |
6 |
45 |

Turning point chronology for the Euro-Zone: A Distance Plot Approach |
0 |
0 |
0 |
12 |
0 |
0 |
10 |
46 |

Understanding Exchange Rates Dynamics |
0 |
0 |
0 |
10 |
0 |
1 |
9 |
53 |

Understanding Exchange Rates Dynamics |
0 |
0 |
2 |
54 |
0 |
2 |
9 |
134 |

Une mesure de la persistance dans les indices boursiers |
0 |
0 |
0 |
30 |
0 |
0 |
11 |
127 |

Using a time series approach to correct serial correlation in Operational Risk capital calculation |
0 |
1 |
1 |
30 |
7 |
21 |
29 |
113 |

Using a time series approach to correct serial correlation in operational risk capital calculation |
0 |
0 |
0 |
16 |
0 |
1 |
3 |
23 |

Value at Risk Computation in a Non-Stationary Setting |
0 |
0 |
0 |
46 |
0 |
0 |
1 |
53 |

Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics |
1 |
3 |
3 |
38 |
3 |
5 |
14 |
92 |

Viewing Risk Measures as information |
0 |
0 |
1 |
25 |
0 |
0 |
9 |
68 |

Viewing Risk Measures as information |
0 |
0 |
0 |
47 |
0 |
0 |
3 |
37 |

Viewing risk measures as information |
0 |
0 |
0 |
35 |
0 |
0 |
8 |
65 |

Wavelet Method for Locally Stationary Seasonal Long Memory Processes |
0 |
0 |
0 |
38 |
0 |
0 |
0 |
58 |

Wavelet method for locally stationary seasonal long memory processes |
0 |
0 |
0 |
76 |
0 |
0 |
1 |
182 |

What is the Best Approach to Measure the Interdependence between Different Markets? |
0 |
4 |
18 |
114 |
6 |
28 |
167 |
1,037 |

Which is the best model for the US inflation rate: a structural changes model or a long memory |
0 |
0 |
0 |
73 |
1 |
3 |
6 |
432 |

Which is the best model for the US inflation rate: a structural changes model or a long memory process ? |
0 |
0 |
0 |
34 |
0 |
1 |
3 |
72 |

tail behavior of a threshold autoregressive stochastic volatility model |
0 |
0 |
0 |
17 |
0 |
0 |
0 |
65 |

Total Working Papers |
16 |
40 |
121 |
11,505 |
70 |
230 |
1,565 |
33,422 |