Investigating competition in financial markets: a sparse autologistic model for dynamic network data
Investigating competition in financial markets: a sparse autologistic model for dynamic network data
复制标题
调查金融市场的竞争:动态网络数据的稀疏自逻辑模型
DOI:
10.1080/02664763.2017.1357684
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发表时间:
2017
影响因子:
1.5
通讯作者:
Boyd, Naomi
中科院分区:
文献类型:
--
作者:
Betancourt, Brenda;Rodríguez, Abel;Boyd, Naomi
We develop a sparse autologistic model for investigating the impact of diversification and disintermediation strategies in the evolution of financial trading networks. In order to induce sparsity in the model estimates and address substantive questions about the underlying processes the model includes anregularization penalty. This makes implementation feasible for complex dynamic networks in which the number of parameters is considerably greater than the number of observations over time. We use the model to characterize trader behavior in the NYMEX natural gas futures market, where we find that disintermediation and not diversification or momentum tend to drive market microstructure.
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DOI:
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发表时间:
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期刊:
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Journal of the Royal Statistical Society: Series C (Applied Statistics)
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