CORTESE, FEDERICO PASQUALE
Distribuzione geografica
Continente | # |
---|---|
EU - Europa | 268 |
NA - Nord America | 145 |
AS - Asia | 44 |
AF - Africa | 6 |
SA - Sud America | 4 |
OC - Oceania | 2 |
Totale | 469 |
Nazione | # |
---|---|
US - Stati Uniti d'America | 142 |
IT - Italia | 109 |
DE - Germania | 40 |
DK - Danimarca | 33 |
FR - Francia | 18 |
GB - Regno Unito | 12 |
NL - Olanda | 11 |
IE - Irlanda | 10 |
CN - Cina | 9 |
NO - Norvegia | 8 |
JP - Giappone | 6 |
SE - Svezia | 6 |
SG - Singapore | 5 |
HK - Hong Kong | 4 |
KR - Corea | 4 |
PK - Pakistan | 4 |
VN - Vietnam | 4 |
AT - Austria | 3 |
CH - Svizzera | 3 |
ES - Italia | 3 |
FI - Finlandia | 3 |
LT - Lituania | 3 |
TR - Turchia | 3 |
AU - Australia | 2 |
BR - Brasile | 2 |
CA - Canada | 2 |
MO - Macao, regione amministrativa speciale della Cina | 2 |
SN - Senegal | 2 |
UA - Ucraina | 2 |
ZA - Sudafrica | 2 |
AE - Emirati Arabi Uniti | 1 |
AR - Argentina | 1 |
BA - Bosnia-Erzegovina | 1 |
CL - Cile | 1 |
CM - Camerun | 1 |
GR - Grecia | 1 |
HN - Honduras | 1 |
IN - India | 1 |
NG - Nigeria | 1 |
RO - Romania | 1 |
RU - Federazione Russa | 1 |
SA - Arabia Saudita | 1 |
Totale | 469 |
Città | # |
---|---|
Milan | 24 |
Copenhagen | 14 |
Rome | 13 |
Santa Cruz | 10 |
Seattle | 10 |
Ashburn | 9 |
Dublin | 9 |
Fairfield | 8 |
Woodbridge | 8 |
Harstad | 7 |
New York | 7 |
Aarhus | 6 |
Leawood | 6 |
Massy | 6 |
Naaldwijk | 6 |
Hefei | 5 |
London | 5 |
Singapore | 5 |
Buffalo | 4 |
Cambridge | 4 |
Campogalliano | 4 |
Council Bluffs | 4 |
Frankfurt am Main | 4 |
Samarate | 4 |
Shanghai | 4 |
Sialkot | 4 |
Tokyo | 4 |
Washington | 4 |
Yuseong-gu | 4 |
Ann Arbor | 3 |
Boardman | 3 |
Clearwater | 3 |
Hong Kong | 3 |
Kaunas | 3 |
Madrid | 3 |
Novara | 3 |
Seymour | 3 |
Trento | 3 |
Turin | 3 |
Amsterdam | 2 |
Berlin | 2 |
Bethesda | 2 |
Carate Brianza | 2 |
Cedar Knolls | 2 |
Gamleby | 2 |
Helsinki | 2 |
Istanbul | 2 |
Lucerne | 2 |
Macao | 2 |
Mountain View | 2 |
Napoli | 2 |
Pergine Valsugana | 2 |
Pozza | 2 |
Princeton | 2 |
Redmond | 2 |
Rende | 2 |
Salerno | 2 |
San Antonio | 2 |
Solna | 2 |
Spinea | 2 |
São Paulo | 2 |
Valby | 2 |
Vienna | 2 |
Wandsworth | 2 |
Wilmington | 2 |
Yokohama | 2 |
Aalborg | 1 |
Abu Dhabi | 1 |
Altach | 1 |
Ardore | 1 |
Asker | 1 |
Athens | 1 |
Atlanta | 1 |
Bac Giang | 1 |
Billericay | 1 |
Bisignano | 1 |
Bloomfield | 1 |
Buenos Aires | 1 |
Büdelsdorf | 1 |
Canberra | 1 |
Central | 1 |
Cheyenne | 1 |
Chiari | 1 |
Chicago | 1 |
Cluj-Napoca | 1 |
Columbus | 1 |
Cosenza | 1 |
Dallas | 1 |
Des Moines | 1 |
Dong Ket | 1 |
Durham | 1 |
Enschede | 1 |
Francavilla Fontana | 1 |
Frankfurt Am Main | 1 |
Giessen | 1 |
Gradisca D'isonzo | 1 |
Hilversum | 1 |
Ho Chi Minh City | 1 |
Hoffman | 1 |
Holbaek | 1 |
Totale | 320 |
Nome | # |
---|---|
Tail Dependence in Financial Markets: A Dynamic Copula Approach, file e39773b6-08a3-35a3-e053-3a05fe0aac26 | 189 |
Generalized Information Criteria for Sparse Statistical Jump Models, file 95013c2b-385a-4d19-a684-ae449a41d7b3 | 95 |
Statistical Modeling and Temporal Clustering of Multivariate Time-Series with Applications to Financial Data, file 35572764-afd1-497c-af5f-9b13ca21f553 | 68 |
Hidden Markov and regime switching copula models for state allocation in multiple time-series, file e39773b7-d3f4-35a3-e053-3a05fe0aac26 | 68 |
What drives cryptocurrency returns? A sparse statistical jump model approach, file b5daa120-fc12-412c-afde-f400fc18918a | 50 |
What Drives Cryptocurrency Returns? A Sparse Statistical Jump Model Approach, file 297feadb-ea27-4302-8785-9e681e684747 | 6 |
Maximum Likelihood Estimation of Multivariate Regime Switching Student-t Copula Models, file 536c2ff8-947d-4215-832e-18bb5f96d714 | 5 |
Totale | 481 |
Categoria | # |
---|---|
all - tutte | 973 |
article - articoli | 0 |
book - libri | 0 |
conference - conferenze | 0 |
curatela - curatele | 0 |
other - altro | 0 |
patent - brevetti | 0 |
selected - selezionate | 0 |
volume - volumi | 0 |
Totale | 973 |
Totale | Lug | Ago | Sett | Ott | Nov | Dic | Gen | Feb | Mar | Apr | Mag | Giu | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2019/2020 | 26 | 0 | 0 | 0 | 0 | 0 | 6 | 5 | 4 | 6 | 1 | 3 | 1 |
2020/2021 | 49 | 0 | 5 | 0 | 9 | 9 | 6 | 8 | 3 | 2 | 2 | 2 | 3 |
2021/2022 | 85 | 2 | 1 | 0 | 5 | 3 | 2 | 5 | 5 | 9 | 17 | 28 | 8 |
2022/2023 | 87 | 7 | 16 | 16 | 7 | 3 | 1 | 2 | 2 | 5 | 3 | 19 | 6 |
2023/2024 | 234 | 8 | 19 | 20 | 15 | 22 | 21 | 15 | 42 | 20 | 40 | 12 | 0 |
Totale | 481 |