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pro vyhledávání: '"Dias, Gustavo Fruet"'
Autor:
Dias, Gustavo Fruet
This thesis contributes to four distinct fields on the econometrics literature: forecasting macroeconomic variables using large datasets, volatility modelling, risk premium estimation and iterative estimators. As a research output, this thesis presen
Externí odkaz:
https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.667092
Autor:
Dias, Gustavo Fruet
Publikováno v:
Biblioteca Digital de Teses e Dissertações da UFRGSUniversidade Federal do Rio Grande do SulUFRGS.
A presente dissertação de conclusão de mestrado tem por objetivo contribuir com a literatura existente que versa acerca da estimação da Taxa de Câmbio Real (RER) através de fundamentos econômicos. O objetivo deste trabalho é utilizar o instr
Externí odkaz:
http://hdl.handle.net/10183/8785
Publikováno v:
In Journal of Econometrics January 2018 202(1):75-91
Publikováno v:
Repositório Institucional do FGV (FGV Repositório Digital)
Fundação Getulio Vargas (FGV)
instacron:FGV
Fundação Getulio Vargas (FGV)
instacron:FGV
We formulate a continuous-time price discovery model in which the price discovery measure varies (stochastically) at daily frequency. We estimate daily measures of price discovery using a kernel-based OLS estimator instead of running separate daily V
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3056::35251b47719d7000bf7360475dbbb990
Publikováno v:
Dias, G F, Fernandes, M & Scherrer, C 2016 ' Component shares in continuous time ' Institut for Økonomi, Aarhus Universitet, Aarhus .
We formulate a continuous-time price discovery model in which the price discovery measure varies (stochastically) at daily frequency. We estimate daily measures of price discovery using a kernel-based OLS estimator instead of running separate daily V
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::ed84717a52493969f9984edfd544f504
https://pure.au.dk/portal/da/publications/component-shares-in-continuous-time(ce32dd7b-deba-4b1b-b906-cb354d40af3e).html
https://pure.au.dk/portal/da/publications/component-shares-in-continuous-time(ce32dd7b-deba-4b1b-b906-cb354d40af3e).html
Publikováno v:
Dias, G F, Scherrer, C & Papailias, F 2016 ' Volatility Discovery ' Institut for Økonomi, Aarhus Universitet, Aarhus .
There is a large literature that investigates how homogenous securities traded on different markets incorporate new information (price discovery analysis). We extend this concept to the stochastic volatility process and investigate how markets contri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::112fbef6114b2103e10d734aaf9cef50
https://pure.au.dk/portal/da/publications/volatility-discovery(9a8691b4-cd09-4e91-9f33-58f53f869104).html
https://pure.au.dk/portal/da/publications/volatility-discovery(9a8691b4-cd09-4e91-9f33-58f53f869104).html
Autor:
Dias, Gustavo Fruet
Publikováno v:
Dias, G F 2015, ' Book review: Nonlinear Time Series: Extreme Events and Integer Value Problems ', Journal of the American Statistical Association, vol. 110, no. 512, pp. 1823-1824 . https://doi.org/10.1080/01621459.2015.1121043
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pure_au_____::40218586741c555f6278e3c387a85c4f
https://pure.au.dk/portal/da/publications/book-review-nonlinear-time-series-extreme-events-and-integer-value-problems(e2f4aa9b-ddb3-4da7-bed0-a4afda021086).html
https://pure.au.dk/portal/da/publications/book-review-nonlinear-time-series-extreme-events-and-integer-value-problems(e2f4aa9b-ddb3-4da7-bed0-a4afda021086).html
Autor:
Dias, Gustavo Fruet, Papailias, Fotis
Publikováno v:
Dias, G F & Papailias, F 2014 ' Forecasting Long Memory Series Subject to Structural Change : A Two-Stage Approach ' Institut for Økonomi, Aarhus Universitet, Aarhus .
A two-stage forecasting approach for long memory time series is introduced. In the first step we estimate the fractional exponent and, applying the fractional differencing operator, we obtain the underlying weakly dependent series. In the second step
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::6d1f185f214d827fa1bcba8ef263ebb9
https://pure.au.dk/portal/da/publications/forecasting-long-memory-series-subject-to-structural-change(0fee988f-a48c-44c9-9cf3-02d1aa0a2ccc).html
https://pure.au.dk/portal/da/publications/forecasting-long-memory-series-subject-to-structural-change(0fee988f-a48c-44c9-9cf3-02d1aa0a2ccc).html
Publikováno v:
Dias, G F & Kapetanios, G 2014 ' Estimation and Forecasting in Vector Autoregressive Moving Average Models for Rich Datasets ' Institut for Økonomi, Aarhus Universitet, Aarhus .
We address the issue of modelling and forecasting macroeconomic variables using medium and large datasets, by adopting VARMA models. We overcome the estimation issue that arises with this class of models by implementing an iterative ordinary least sq
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::00a927a7838328f1e5a0f2bc3242c09b
https://pure.au.dk/ws/files/102291043/rp14_37.pdf
https://pure.au.dk/ws/files/102291043/rp14_37.pdf