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on Market Microstructure |
| By: | Andreas Karpf (CES - Centre d'économie de la Sorbonne - CNRS - Centre National de la Recherche Scientifique - UP1 - Université Panthéon-Sorbonne); Antoine Mandel (CES - Centre d'économie de la Sorbonne - CNRS - Centre National de la Recherche Scientifique - UP1 - Université Panthéon-Sorbonne, PSE - Paris School of Economics); Stefano Battiston (CAMS - Centre d'Analyse et de Mathématique sociales - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | This paper presents an analysis of the European Emission Trading System as a transaction network. It is shown that, given the lack of well-identified trading institutions, industrial actors had to resort to local connections and financial intermediaries to participate in the market. This gave rise to a hierarchical structure in the transaction network. It is then shown that the asymmetries in the network induced market inefficiencies (e.g., increased bid-ask spread) and informational asymmetries, that have been exploited by central agents at the expense of less central ones. Albeit the efficiency of the market has improved from the beginning of Phase II, the asymmetry persists, imposing unnecessary additional costs on agents and reducing the effectiveness of the market as a mitigation instrument. |
| Keywords: | Network,Carbon market,Climate change,Microstructure |
| Date: | 2018–09 |
| URL: | http://d.repec.org/n?u=RePEc:hal:pseptp:halshs-01905985&r=all |
| By: | Jingsheng Yu; Jun Zhang |
| Abstract: | Efficiency and fairness are two desiderata in market design. Fairness requires randomization in many environments. As one of the few successful matching mechanisms, Top Trading Cycle is best known for being efficient to solve deterministic allocation problems, but it is inadequate to incorporate randomization efficiently and fairly. We propose a class of Fractional Top Trading Cycle mechanisms to solve allocation problems in which agents have fractional endowments or are ranked by coarse priorities. Dropping the graph-based definition of Top Trading Cycle, we use parameterized linear equations to describe how agents trade endowments or priorities. Our mechanisms are ex-ante efficient. They satisfy various fairness axioms when parameter values in the equations are properly chosen. We apply our mechanisms to a couple of market design problems and obtain efficient and fair assignments in all of them. |
| Date: | 2020–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2005.06878&r=all |
| By: | Michele Costola; Matteo Iacopini; Carlo R. M. A. Santagiustina |
| Abstract: | We measure the public concern during the outbreak of COVID-19 disease using three data sources from Google Trends (YouTube, Google News, and Google Search). Our findings are three-fold. First, the public concern in Italy is found to be a driver of the concerns in other countries. Second, we document that Google Trends data for Italy better explains the stock index returns of France, Germany, Great Britain, the United States, and Spain with respect to their country-based indicators. Finally, we perform a time-varying analysis and identify that the most severe impacts in the financial markets occur at each step of the Italian lock-down process. |
| Date: | 2020–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2005.06796&r=all |