This study investigates and compares the effects of the Coronavirus disease 2019(COVID-19)pandemic,the Chicago mercantile exchange(CME)'s negative price suggestion on prices and trading activities in the crude oil...This study investigates and compares the effects of the Coronavirus disease 2019(COVID-19)pandemic,the Chicago mercantile exchange(CME)'s negative price suggestion on prices and trading activities in the crude oil futures market to discuss the cause of negative crude oil futures prices.Through event studies,the empirical results show that the COVID-19 pandemic no longer impacts crude oil futures prices in April,2020 after controlled market risk,while the CME's negative prices suggestion can explain the crude oil futures price changes around and even after April 8,2020 to some degree.Moreover,this study uncovers anomalies in prices and trading activities by analyzing returns,trading volume,open interest,and illiquidity measures using vector autoregressive(VAR)models.The results imply that CME's allowing negative prices strengthens the price impact on trading volume and makes illiquidity risk matter.This study's results coincide with the following lawsuit evidence of market manipulation.展开更多
Long-memory process has been widely studied in classical financial time series analysis,which has merely been reported in the field of interval-valued financial time series.The aim of this paper is to explore long-mem...Long-memory process has been widely studied in classical financial time series analysis,which has merely been reported in the field of interval-valued financial time series.The aim of this paper is to explore long-memory process in the prediction of interval-valued time series(IvTS).To model the long-memory process,two novel interval-valued time series prediction models named as interval-valued vector autoregressive fractionally integrated moving average(IV-VARFIMA)and ARFIMAX-FIGARCH were established.In the developed long-memory pattern,both of the short term and long-term influences contained in IvTS can be included.As an application of the proposed models,interval-valued form of WTI crude oil futures price series is predicted.Compared to current IvTS prediction models,IV-VARFIMA and ARFIMAX-FIGARCH can provide better in-sample and out-of-sample forecasts.展开更多
基金supported by Dr.Lu’s grants from the National Natural Science Foundation of China under Grant No.71871213Prof.Bu’s grants from the National Natural Science Foundation of China under Grant Nos.71671012 and 91846108。
文摘This study investigates and compares the effects of the Coronavirus disease 2019(COVID-19)pandemic,the Chicago mercantile exchange(CME)'s negative price suggestion on prices and trading activities in the crude oil futures market to discuss the cause of negative crude oil futures prices.Through event studies,the empirical results show that the COVID-19 pandemic no longer impacts crude oil futures prices in April,2020 after controlled market risk,while the CME's negative prices suggestion can explain the crude oil futures price changes around and even after April 8,2020 to some degree.Moreover,this study uncovers anomalies in prices and trading activities by analyzing returns,trading volume,open interest,and illiquidity measures using vector autoregressive(VAR)models.The results imply that CME's allowing negative prices strengthens the price impact on trading volume and makes illiquidity risk matter.This study's results coincide with the following lawsuit evidence of market manipulation.
基金supported by the Humanities and Social Sciences Research Youth Project of the Ministry of Education of China under Grant No.21YJCZH148the Natural Science Foundation of Anhui Province under Grant Nos.2108085MG239,2108085QG290,2008085QG334,and 2008085MG226+2 种基金the National Natural Science Foundation of China under Grant Nos.72001001,71901001,and 72071001the Provincial Natural Science Research Project of Anhui Colleges,China under Grant No.KJ2020A0004The teacher project of Anhui Ecology and Economic Development Research Center in 2021 under Grant No.AHST2021002.
文摘Long-memory process has been widely studied in classical financial time series analysis,which has merely been reported in the field of interval-valued financial time series.The aim of this paper is to explore long-memory process in the prediction of interval-valued time series(IvTS).To model the long-memory process,two novel interval-valued time series prediction models named as interval-valued vector autoregressive fractionally integrated moving average(IV-VARFIMA)and ARFIMAX-FIGARCH were established.In the developed long-memory pattern,both of the short term and long-term influences contained in IvTS can be included.As an application of the proposed models,interval-valued form of WTI crude oil futures price series is predicted.Compared to current IvTS prediction models,IV-VARFIMA and ARFIMAX-FIGARCH can provide better in-sample and out-of-sample forecasts.
