In: Tree Physiology, 2018, vol. 38, no. 9, p. 1345-1355
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Thèse de doctorat : Università della Svizzera italiana, 2021 ; 2021ECO002.
I use empirical methods to study the effect of institutional investors on financial markets. My studies provide novel evidence on the commonality in liquidity of fixed-income securities, the liquidity provision of hedge funds and mutual funds in equity markets, and the information diffusion from credit default swaps to equities.
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Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020ECO008.
My doctoral thesis examines the relationships among the degree of financial market integration and the pricing of different classes of assets. The first chapter provides a theoretical framework that uncovers in a model-free way the relationship between international stochastic discount factors (SDFs), stochastic wedges, and financial market structures. Exchange rates are in general different...
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In: International Journal of Modern Physics C, 2020, vol. 31, no. 04, p. 2050056
Community division in complex networks has become one of the hot topics in the field of network science. Most of the methods developed based on network topology ignore the dynamic characteristics underlying the structure. By exploring the diffusion process in the network based on random walk, this paper sums up the general rule with temporal characteristics as a temporary local balancing...
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Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020ECO007.
Empirical indicators of sentiment are commonly employed in the economic literature while a precise understanding of what is sentiment is still missing. Exploring the links among the most popular proxies of sentiment, fear and uncertainty this paper aims to fill this gap. We show how fear and sentiment are specular in their predictive power in relation to the aggregate market and to...
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In: IEEE Access, 2019, vol. 7, p. 184145–184159
Community structure discovery can help us better understand the capabilities and functions of the network. However, many existing methods have failed to identify nodes in communities accurately. In this paper, we proposed a heuristic community detection method based on node similarities that are computed by assigning different edge weight influence factors based on different neighbor types of...
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In: Complexity, 2019, vol. 2019, p. 1–17
Understanding and predicting extreme turning points in the financial market, such as financial bubbles and crashes, has attracted much attention in recent years. Experimental observations of the superexponential increase of prices before crashes indicate the predictability of financial extremes. In this study, we aim to forecast extreme events in the stock market using 19-year time-series...
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In: Entropy, 2019, vol. 21, no. 9, p. 859
In many industries, partners are interconnected in project alliances that have limited lifespans and clearly-defined boundaries. The transparency of the movie industry provides a unique opportunity to study how alliance network topologies impact the performance of project alliances from the perspectives of social networks and organization theories. In this work, we compiled a massive movie...
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In: Physics Reports, 2019, vol. 817, p. 1–104
Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development. The understanding of socioeconomic processes provides foundations to quantify global economic development, to map regional industrial structure, and to infer individual socioeconomic status. In this review, we will make a brief manifesto about a new ...
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In: Journal of Informetrics, 2019, vol. 13, no. 2, p. 717–725
Identifying the future influential papers among the newly published ones is an important yet challenging issue in bibliometrics. As newly published papers have no or limited citation history, linear extrapolation of their citation counts—which is motivated by the well-known preferential attachment mechanism—is not applicable. We translate the recently introduced notion of discoverers to...
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