Unravelling the JPMorgan spoofing case using particle physics visualization methods

On 29 September 2020, JPMorgan was ordered to pay a settlement of $920.2 million for spoofing the metals and Treasury futures markets from 2008 to 2016. We examine these cases using a visualization method developed in particle physics (CERN) and the messages that the exchange receives about market activity rather than time-based snapshots. This approach allows to examine multiple indicators related to market manipulation and complement existing research methods, thereby enhancing the identification and understanding of, as well as the motivation for, market manipulation. In the JPMorgan cases, we offer an alternative motivation for spoofing than moving the price.     

Partner country selection between development narratives and self-interests: A new method for analysing complex donor approaches

Partner country (PC) selection lies in the centre of development policy decision-making of donor countries and institutions, and plays a significant role in shaping aid patterns. This paper proposes a comprehensive analysis contrasting donor intentions in PC selection with actual aid flows. Having analysed selected members of the Development Assistance Committee of the Organization for Economic Cooperation and Development, namely, the European Union, France, Germany, Japan, Netherlands, Sweden, the United Kingdom and the United States of America, we suggest that (1) donors might not only be either altruistic or self-interested but also motivated by an intention to contribute to the provision of global public goods; (2) self-interest in aid provision can be an explicitly-stated strategy, contrary to what has been argued in the majority of the literature, which often treats self-interest as a non-stated donor intention; and (3) donors' self-interested intentions do not always lead to a less development-oriented donor approach.