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.     

Manufacturing output and extreme temperature: Evidence from Canada

This paper analyzes the effects of extreme temperature on manufacturing output using a data set covering the universe of manufacturing establishments in Canada from 2004 to 2012. Extreme temperature can affect manufacturing activity directly through its impact on labour productivity and indirectly through a change in demand for products. Using a panel fixed effects method, our results suggest a non-linear relationship between outdoor extreme temperature and manufacturing output. Each day where outdoor mean temperatures are below $-18$ °C or above 24 °C reduces annual manufacturing output by 0.18% and 0.11%, respectively, relative to a day with mean temperature between 12 ° and 18 °C. In a typical year, extreme temperatures, as measured by the number of days below $-18$ °C or above 24 °C, reduce annual manufacturing output by 2.2%, with extreme hot temperatures contributing the most to this impact. Given the predicted change in climate for the mid- and end of century, we predict annual manufacturing output losses due to extreme temperature to range between 2.8% and 3.7% in mid-century and 3.7% and 7.2% in end of century.