dc.contributor.advisor |
Pizzi, Claudio |
it_IT |
dc.contributor.author |
Piga, Enrico <1992> |
it_IT |
dc.date.accessioned |
2017-10-09 |
it_IT |
dc.date.accessioned |
2018-04-17T13:34:27Z |
|
dc.date.available |
2019-10-23T05:36:24Z |
|
dc.date.issued |
2017-10-30 |
it_IT |
dc.identifier.uri |
http://hdl.handle.net/10579/11553 |
|
dc.description.abstract |
This thesis aims to analyse banking sector in north-east of Italy, more precisely Cooperative Credit Banks connected with the phenomenon of Home Bias. In literature, many studies detected different causes of home bias both from a client and bank point of view, namely geographical factors related to widespread presence in small territories, cognitive errors in portfolio asset allocation caused by low diversification, political factors and costs in international financial markets. The thesis accompanies theoretical concepts with a quantitative analysis on a real dataset on which the application of Structural Equation Models, in the specific Partial Least Squared with different approaches. Furthermore, in light of heterogeneity in the dataset, we try to implement previous models in order to be in line with theory, obtaining homogeneous classes. Finally, mediating effect are considered and quantified as source deviation of relationships inside estimated model. The thesis is organised as follow. Chapter I introduces the basic concepts of Asset Allocation linked to home basis and ending with literature of possible causes. Chapter II describes banking sector and regulation in Italy. Introduction of PLS PM approach is exposed in Chapter III. Chapter IV contains the analysis of the dataset with descriptive statistics. In Chapter V PLS PM approach is applied on dataset. Heterogeneity in the dataset and the use of REBUS PLS to detect homogeneous classes are presented in Chapter VI. Chapter VII focuses on detecting possible moderating effects in PLS PM estimated on previous chapters. We conclude in Chapter VIII with comments on results and reflections. |
it_IT |
dc.language.iso |
en |
it_IT |
dc.publisher |
Università Ca' Foscari Venezia |
it_IT |
dc.rights |
© Enrico Piga, 2017 |
it_IT |
dc.title |
Home Bias: PLS PM application on banking sector |
it_IT |
dc.title.alternative |
Home Bias : PLS PM application on banking sector |
it_IT |
dc.type |
Master's Degree Thesis |
it_IT |
dc.degree.name |
Economia e finanza - economics and finance |
it_IT |
dc.degree.level |
Laurea magistrale |
it_IT |
dc.degree.grantor |
Dipartimento di Economia |
it_IT |
dc.description.academicyear |
2016/2017, sessione autunnale |
it_IT |
dc.rights.accessrights |
embargoedAccess |
it_IT |
dc.thesis.matricno |
856210 |
it_IT |
dc.subject.miur |
SECS-S/06 METODI MATEMATICI DELL'ECONOMIA E DELLE SCIENZE ATTUARIALI E FINANZIARIE |
it_IT |
dc.description.note |
|
it_IT |
dc.degree.discipline |
|
it_IT |
dc.contributor.co-advisor |
|
it_IT |
dc.provenance.upload |
Enrico Piga (856210@stud.unive.it), 2017-10-09 |
it_IT |
dc.provenance.plagiarycheck |
Claudio Pizzi (pizzic@unive.it), 2017-10-23 |
it_IT |