Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Giacomo Morelli"'
Publikováno v:
Frontiers in Artificial Intelligence, Vol 4 (2021)
This paper compares the predictive power of different models to forecast the real U.S. GDP. Using quarterly data from 1976 to 2020, we find that the machine learning K-Nearest Neighbour (KNN) model captures the self-predictive ability of the U.S. GDP
Externí odkaz:
https://doaj.org/article/8465c35857ad403c94c293ca5fc264d3
Autor:
Giacomo Morelli, Lea Petrella
Publikováno v:
Risks, Vol 9, Iss 9, p 167 (2021)
This paper provides a quantitative assessment of equity options priced at the Zero Lower Bound, i.e., when interest rates are set essentially to zero. We obtain closed form formulas for American options when the Zero Lower Bound policy holds. We perf
Externí odkaz:
https://doaj.org/article/b59b402cf49e4ff8b9daced3c2a63835
Publikováno v:
Risks, Vol 9, Iss 8, p 144 (2021)
This paper shows the effects of the COVID-19 pandemic on energy markets. We estimate daily volatilities and correlations among energy commodities relying on a mixed-frequency approach that exploits information from the number of weekly deaths related
Externí odkaz:
https://doaj.org/article/e0c26b50d75a4ca68b04672001fffb43
Autor:
Giacomo Morelli
Publikováno v:
Annals of Operations Research.
Autor:
Giacomo Morelli, Rita L. D’Ecclesia
Publikováno v:
Decisions in Economics and Finance. 44:1211-1233
Responsible investments are considered one of the driving factors of revenues growth enhancing risk-adjusted returns. This paper investigates the effects of responsible investments on the volatility of European stock returns. First, we exploit an exp
Autor:
Giacomo Morelli
Publikováno v:
Annals of Operations Research.
In this paper, we investigate the interconnections among and within the Energy, Agricultural, and Metal commodities, operating in a risk management framework with a twofold goal. First, we estimate the Value-at-Risk (VaR) employing GARCH and Markov-s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a2d833659423df56b7cf73063b13f75b
https://hdl.handle.net/11573/1662151
https://hdl.handle.net/11573/1662151
Publikováno v:
SSRN Electronic Journal.