| Working Paper |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Flexible Specification of Space–Time AutoRegressive Models |
0 |
0 |
1 |
40 |
0 |
0 |
3 |
35 |
| A Nonparametric Bayesian Approach to Detect the Number of Regimes in Markov Switching Models |
0 |
0 |
0 |
271 |
1 |
4 |
10 |
895 |
| A Realistic Model for Official Interest Rates |
0 |
0 |
0 |
61 |
0 |
6 |
8 |
420 |
| A Time Varying Parameter Approach to Analyze the Macroeconomic Consequences of Crime |
0 |
0 |
0 |
72 |
0 |
0 |
2 |
215 |
| Adding Flexibility to Markov Switching Models |
0 |
0 |
0 |
69 |
0 |
1 |
4 |
63 |
| Asset Allocation Using Flexible Dynamic Correlation Models with Regime Switching |
0 |
0 |
0 |
242 |
0 |
0 |
6 |
629 |
| Classification of Volatility in Presence of Changes in Model Parameters |
0 |
0 |
3 |
60 |
0 |
7 |
31 |
181 |
| Classifying the Markets Volatility with ARMA Distance Measures |
0 |
0 |
1 |
203 |
0 |
0 |
7 |
417 |
| Clustering Heteroskedastic Time Series by Model-Based Procedures |
1 |
2 |
2 |
133 |
1 |
4 |
6 |
411 |
| Clustering Mutual Funds by Return and Risk Levels |
0 |
1 |
5 |
183 |
0 |
6 |
15 |
541 |
| Clustering Space-Time Series: A Flexible STAR Approach |
0 |
0 |
2 |
68 |
0 |
1 |
4 |
39 |
| Combining Markov Switching and Smooth Transition in Modeling Volatility: A Fuzzy Regime MEM |
0 |
1 |
1 |
84 |
1 |
3 |
8 |
73 |
| Combining Sharp and Smooth Transitions in Volatility Dynamics: a Fuzzy Regime Approach |
0 |
0 |
0 |
56 |
0 |
0 |
3 |
42 |
| Cycles in Crime and Economy Revised |
0 |
0 |
0 |
105 |
0 |
1 |
6 |
339 |
| Cycles in Crime and Economy: Leading, Lagging and Coincident Behaviors |
0 |
0 |
0 |
0 |
0 |
1 |
5 |
6 |
| Cycles in Crime and Economy: Leading, Lagging and Coincident Behaviors |
0 |
0 |
0 |
92 |
0 |
2 |
14 |
344 |
| Dating the Italian BUsiness Cycle: A Comparison of Procedures |
0 |
1 |
3 |
276 |
1 |
4 |
22 |
1,135 |
| Dating the Italian Business Cycle: A Comparison of Procedures |
0 |
0 |
2 |
152 |
0 |
2 |
13 |
716 |
| Does Crime Affect Economic Growth? |
0 |
0 |
0 |
0 |
4 |
10 |
30 |
42 |
| Extraction of Common Signal from Series with Different Frequency |
0 |
0 |
1 |
149 |
1 |
1 |
8 |
520 |
| Financial Clustering in Presence of Dominant Markets |
0 |
0 |
0 |
3 |
0 |
0 |
3 |
32 |
| Forecasting Realized Volatility with Changes of Regimes |
0 |
0 |
0 |
98 |
1 |
4 |
8 |
117 |
| Identifying Financial Time Series with Similar Dynamic Conditional Correlation |
0 |
0 |
0 |
33 |
1 |
6 |
10 |
125 |
| Improving the Forecasting of Dynamic Conditional Correlation: a Volatility Dependent Approach |
0 |
0 |
0 |
94 |
0 |
1 |
9 |
222 |
| Indirect estimation of Markov switching models with endogenous switching |
0 |
0 |
3 |
40 |
0 |
3 |
16 |
132 |
| Model effect on projected mortality indicators |
0 |
0 |
0 |
20 |
2 |
5 |
11 |
71 |
| Modeling the Dependence of Conditional Correlations on Volatility |
0 |
0 |
0 |
146 |
1 |
3 |
6 |
208 |
| Modeling the dependence of conditional correlations on market volatility |
0 |
0 |
0 |
0 |
0 |
1 |
6 |
26 |
| Modeling the dependence of conditional correlations on volatility |
0 |
0 |
0 |
27 |
0 |
0 |
1 |
57 |
| Modelling the discrete and infrequent official interest rate change in the UK |
0 |
0 |
0 |
58 |
0 |
0 |
9 |
235 |
| Nonlinearities and regimes in conditional correlations with different dynamics |
0 |
0 |
2 |
16 |
0 |
0 |
10 |
40 |
| Realized Volatility and Change of Regimes |
0 |
0 |
0 |
81 |
1 |
2 |
5 |
168 |
| Recognizing and Forecasting the Sign of Financial Local Trends using Hidden Markov Models |
0 |
0 |
0 |
247 |
0 |
0 |
4 |
673 |
| Reducing Bias in a Matching Estimation of Endogenous Treatment Effect |
0 |
0 |
3 |
25 |
0 |
3 |
15 |
44 |
| Signal Extraction in Continuous Time and the Generalized Hodrick- Prescott Filter |
0 |
0 |
0 |
356 |
0 |
0 |
3 |
747 |
| Spatial Effects in Dynamic Conditional Correlations |
0 |
0 |
1 |
66 |
3 |
4 |
10 |
83 |
| Spillover Effects in the Volatility of Financial Markets |
0 |
0 |
0 |
52 |
0 |
1 |
6 |
129 |
| The Choice of Time Interval in Seasonal Adjustment: A Heuristic Approach |
0 |
0 |
0 |
88 |
0 |
1 |
3 |
232 |
| The Choice of Time Interval in Seasonal Adjustment: Characterization and Tools |
0 |
0 |
1 |
15 |
0 |
2 |
4 |
110 |
| The Markov Switching Asymmetric Multiplicative Error Model |
0 |
0 |
2 |
53 |
0 |
0 |
7 |
105 |
| Volatility Spillover, Interdependence, Comovements across GCC, Oil and U.S. Markets and Portfolio Management Strategies in a Regime-Changing Environment |
0 |
0 |
2 |
39 |
0 |
0 |
7 |
140 |
| Volatility Spillovers, Interdependence and Comovements: A Markov Switching Approach |
0 |
1 |
1 |
235 |
1 |
2 |
13 |
507 |
| Volatility Swings in the US Financial Markets |
0 |
0 |
2 |
45 |
1 |
1 |
10 |
109 |
| Volatility Transmission Across Markets: A Multi-Chain Markov Switching Model |
0 |
1 |
3 |
117 |
1 |
4 |
9 |
287 |
| Volatility Transmission across Currency, Commodity and Equity Markets under Multi-Chain Regime Switching: Implications for Hedging and Portfolio Allocation |
0 |
0 |
0 |
96 |
0 |
2 |
3 |
265 |
| Volatility Transmission in Financial Markets: A New Approach |
0 |
0 |
0 |
86 |
1 |
1 |
4 |
195 |
| the Multi-State Markov Switching Model |
0 |
0 |
3 |
337 |
0 |
1 |
11 |
595 |
| Total Working Papers |
1 |
7 |
44 |
4,789 |
22 |
100 |
408 |
12,717 |
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