| 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 |
2 |
37 |
0 |
1 |
10 |
28 |
| A Nonparametric Bayesian Approach to Detect the Number of Regimes in Markov Switching Models |
0 |
1 |
2 |
271 |
0 |
3 |
5 |
881 |
| A Realistic Model for Official Interest Rates |
0 |
0 |
0 |
61 |
0 |
0 |
1 |
410 |
| A Time Varying Parameter Approach to Analyze the Macroeconomic Consequences of Crime |
0 |
0 |
0 |
72 |
0 |
2 |
8 |
212 |
| Adding Flexibility to Markov Switching Models |
0 |
1 |
1 |
68 |
1 |
3 |
9 |
54 |
| Asset Allocation Using Flexible Dynamic Correlation Models with Regime Switching |
0 |
0 |
0 |
242 |
0 |
0 |
2 |
622 |
| Classification of Volatility in Presence of Changes in Model Parameters |
0 |
0 |
1 |
57 |
1 |
3 |
18 |
142 |
| Classifying the Markets Volatility with ARMA Distance Measures |
1 |
1 |
2 |
202 |
2 |
2 |
7 |
407 |
| Clustering Heteroskedastic Time Series by Model-Based Procedures |
1 |
1 |
3 |
131 |
1 |
1 |
5 |
403 |
| Clustering Mutual Funds by Return and Risk Levels |
1 |
1 |
3 |
178 |
2 |
2 |
10 |
520 |
| Clustering Space-Time Series: A Flexible STAR Approach |
0 |
1 |
1 |
66 |
1 |
4 |
8 |
30 |
| Combining Markov Switching and Smooth Transition in Modeling Volatility: A Fuzzy Regime MEM |
0 |
2 |
2 |
83 |
0 |
3 |
10 |
59 |
| Combining Sharp and Smooth Transitions in Volatility Dynamics: a Fuzzy Regime Approach |
0 |
0 |
2 |
55 |
0 |
1 |
12 |
35 |
| Cycles in Crime and Economy Revised |
1 |
1 |
1 |
105 |
2 |
3 |
8 |
329 |
| Cycles in Crime and Economy: Leading, Lagging and Coincident Behaviors |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| Cycles in Crime and Economy: Leading, Lagging and Coincident Behaviors |
1 |
1 |
7 |
91 |
1 |
5 |
17 |
324 |
| Dating the Italian BUsiness Cycle: A Comparison of Procedures |
1 |
4 |
9 |
270 |
1 |
8 |
25 |
1,105 |
| Dating the Italian Business Cycle: A Comparison of Procedures |
0 |
0 |
1 |
149 |
0 |
3 |
7 |
701 |
| Does Crime Affect Economic Growth? |
0 |
0 |
0 |
0 |
1 |
3 |
7 |
7 |
| Extraction of Common Signal from Series with Different Frequency |
0 |
0 |
0 |
148 |
0 |
0 |
4 |
510 |
| Financial Clustering in Presence of Dominant Markets |
0 |
0 |
0 |
3 |
0 |
0 |
2 |
28 |
| Forecasting Realized Volatility with Changes of Regimes |
0 |
0 |
0 |
96 |
0 |
1 |
4 |
102 |
| Identifying Financial Time Series with Similar Dynamic Conditional Correlation |
1 |
1 |
1 |
33 |
1 |
2 |
3 |
113 |
| Improving the Forecasting of Dynamic Conditional Correlation: a Volatility Dependent Approach |
0 |
0 |
0 |
94 |
1 |
2 |
8 |
210 |
| Indirect estimation of Markov switching models with endogenous switching |
0 |
0 |
1 |
36 |
0 |
0 |
4 |
111 |
| Model effect on projected mortality indicators |
0 |
0 |
0 |
20 |
0 |
0 |
2 |
59 |
| Modeling the Dependence of Conditional Correlations on Volatility |
0 |
0 |
3 |
146 |
0 |
1 |
5 |
200 |
| Modeling the dependence of conditional correlations on market volatility |
0 |
0 |
0 |
0 |
2 |
5 |
15 |
15 |
| Modeling the dependence of conditional correlations on volatility |
0 |
0 |
0 |
26 |
0 |
0 |
3 |
52 |
| Modelling the discrete and infrequent official interest rate change in the UK |
0 |
1 |
1 |
58 |
0 |
1 |
3 |
222 |
| Nonlinearities and regimes in conditional correlations with different dynamics |
2 |
2 |
10 |
10 |
3 |
6 |
22 |
22 |
| Realized Volatility and Change of Regimes |
0 |
0 |
1 |
81 |
0 |
1 |
4 |
160 |
| Recognizing and Forecasting the Sign of Financial Local Trends using Hidden Markov Models |
0 |
0 |
0 |
246 |
0 |
1 |
2 |
664 |
| Reducing Bias in a Matching Estimation of Endogenous Treatment Effect |
1 |
2 |
3 |
21 |
1 |
4 |
14 |
21 |
| Signal Extraction in Continuous Time and the Generalized Hodrick- Prescott Filter |
0 |
0 |
0 |
355 |
0 |
1 |
5 |
742 |
| Spatial Effects in Dynamic Conditional Correlations |
0 |
1 |
1 |
65 |
0 |
2 |
9 |
69 |
| Spillover Effects in the Volatility of Financial Markets |
0 |
0 |
0 |
51 |
0 |
2 |
2 |
120 |
| The Choice of Time Interval in Seasonal Adjustment: A Heuristic Approach |
0 |
0 |
0 |
88 |
2 |
3 |
5 |
223 |
| The Choice of Time Interval in Seasonal Adjustment: Characterization and Tools |
0 |
1 |
1 |
14 |
0 |
1 |
1 |
105 |
| The Markov Switching Asymmetric Multiplicative Error Model |
0 |
0 |
1 |
51 |
0 |
0 |
4 |
96 |
| Volatility Spillover, Interdependence, Comovements across GCC, Oil and U.S. Markets and Portfolio Management Strategies in a Regime-Changing Environment |
0 |
0 |
0 |
36 |
0 |
0 |
3 |
127 |
| Volatility Spillovers, Interdependence and Comovements: A Markov Switching Approach |
1 |
2 |
4 |
234 |
2 |
7 |
17 |
483 |
| Volatility Swings in the US Financial Markets |
0 |
0 |
1 |
43 |
0 |
0 |
4 |
98 |
| Volatility Transmission Across Markets: A Multi-Chain Markov Switching Model |
0 |
0 |
0 |
114 |
0 |
1 |
2 |
274 |
| Volatility Transmission across Currency, Commodity and Equity Markets under Multi-Chain Regime Switching: Implications for Hedging and Portfolio Allocation |
0 |
0 |
0 |
96 |
0 |
0 |
0 |
259 |
| Volatility Transmission in Financial Markets: A New Approach |
0 |
0 |
0 |
86 |
1 |
2 |
4 |
189 |
| the Multi-State Markov Switching Model |
0 |
0 |
0 |
333 |
2 |
3 |
6 |
581 |
| Total Working Papers |
11 |
24 |
65 |
4,722 |
28 |
93 |
326 |
12,124 |
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