Automatic Time Series Modelling and Forecasting: A Replication Case Study of Forecasting Real GDP, the Unemployment Rate, and the Impact of Leading Economic Indicators

2020 ◽  
Author(s):  
John Guerard ◽  
Dimitrios D. Thomakos ◽  
FOTEINH KYRIAZH
Keyword(s):  
Time Series ◽  
Unemployment Rate ◽  
Economic Indicators ◽  
Real Gdp ◽  
Time Series Modelling ◽  
Leading Economic Indicators ◽  
The Impact ◽  
Modelling And Forecasting

Market overreaction, firm-specific information and macroeconomic variables in US and Chinese markets during COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ooi Kok Loang ◽  
Zamri Ahmad
Keyword(s):  
Unemployment Rate ◽  
Stock Return ◽  
Design Methodology ◽  
Specific Information ◽  
Content Type ◽  
Macroeconomic Variables ◽  
Real Gdp ◽  
Chinese Markets ◽  
The Impact ◽  
Loser Portfolio

PurposeThis study examines the impact of firm-specific information and macroeconomic variables on market overreaction of US and Chinese winner and loser portfolio before and during COVID-19.Design/methodology/approachThe firm-specific information includes firm size, volume, volatility, return of asset (ROA), return of equity (ROE), earning per share (EPS) and quick ratio while the macroeconomic variables are export rate, import rate, real GDP, nominal GDP, FDI, IPI and unemployment rate. Besides, one-third of the top performance stocks are categorized as winner portfolio while one-third of lowest performance stocks are categorized as loser portfolio. This study uses AECR to indicate stock return and measure market overreaction. GAECR is used to determine contrarian profit. The data range of pre-COVID-19 is from 1-Jan-2015 to 31-Dec-2019 while the period of COVID-19 is from 1-Jan-2020 to 31-Dec-2020.FindingsIn pre-COVID-19, firm-specific information (volatility, ROA, ROE and EPS) and macroeconomic variables are found to be correlated to stock return in US and Chinese portfolios except Chinese winner portfolio. Nonetheless, the impact of firm-specific information has vanished and macroeconomic variables are significant to stock return in COVID-19. It shows that investors rely on the economic indicators to trade in turbulent period due to emergence of COVID-19 as a disruption in market. Furthermore, US and Chinese portfolios are overreacted during COVID-19. Chinese loser portfolio has higher tendency of overreaction than US loser portfolio while US winner portfolio has higher tendency of overreaction than Chinese winner portfolio.Originality/valueThe results of this study assists academician, practitioners and investors on understanding and create awareness to the existence of market overreaction and the determinants that can cause the phenomenon.

scholarly journals Trade Openness and Economic Growth Nexus: A Case Study of BRICS

2018 ◽  
Vol 54 (1) ◽  
pp. 1-15 ◽  
Author(s):  
L. G. Burange ◽  
Rucha R. Ranadive ◽  
Neha N. Karnik
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Causal Relationship ◽  
Trade Openness ◽  
Gdp Per Capita ◽  
Jel Codes ◽  
Per Capita ◽  
The Impact ◽  
Econometric Technique

The article analyses a causal relationship between trade openness and economic growth for the member countries of BRICS by using an econometric technique of time series analysis. Member countries of BRICS adopted a series of liberalization reforms, almost simultaneously, from the late 1980s. The article attempts to study the impact of trade openness on their growth in GDP per capita. It captures structural composition of GDP and openness of trade in four aspects, that is, merchandise exports, merchandise imports, services export and services import. In India, the study found growth-led trade in services hypothesis. The article supports the growth-led export and growth-led import hypothesis for China and export- and import-led growth for South Africa. However, no causal relationship was evident for Brazil and Russia. JEL Codes: F43, C22

scholarly journals Time-series modelling for the quantification of seasonality and forecasting antibiotic-resistant episodes: application to carbapenemase-producing Enterobacteriaceae episodes in France over 2010–20

2020 ◽  
Vol 76 (1) ◽  
pp. 226-232
Author(s):  
Jonathan Roux ◽  
Narimane Nekkab ◽  
Mélanie Colomb-Cotinat ◽  
Pascal Astagneau ◽  
Pascal Crépey
Keyword(s):  
Time Series ◽  
Prediction Interval ◽  
Healthcare Associated Infections ◽  
Antibiotic Resistant ◽  
Factors Associated ◽  
Time Series Modelling ◽  
Potential Factors ◽  
Healthcare Associated ◽  
The Impact ◽  
National Surveillance System

Abstract Background Carbapenemase-producing Enterobacteriaceae (CPE) cause resistant healthcare-associated infections that jeopardize healthcare systems and patient safety worldwide. The number of CPE episodes has been increasing in France since 2009, but the dynamics are still poorly understood. Objectives To use time-series modelling to describe the dynamics of CPE episodes from August 2010 to December 2016 and to forecast the evolution of CPE episodes for the 2017–20 period. Methods We used time series to analyse CPE episodes from August 2010 to November 2016 reported to the French national surveillance system. The impact of seasonality was quantified using seasonal-to-irregular ratios. Seven time-series models and three ensemble stacking models (average, convex and linear stacking) were assessed and compared with forecast CPE episodes during 2017–20. Results During 2010–16, 3559 CPE episodes were observed in France. Compared with the average yearly trend, we observed a 30% increase in the number of CPE episodes in the autumn. We noticed a 1 month lagged seasonality of non-imported episodes compared with imported episodes. Average stacking gave the best forecasts and predicted an increase during 2017–20 with a peak up to 345 CPE episodes (95% prediction interval = 124–1158, 80% prediction interval = 171–742) in September 2020. Conclusions The observed seasonality of CPE episodes sheds light on potential factors associated with the increased frequency of episodes, which need further investigation. Our model predicts that the number of CPE episodes will continue to rise in the coming years in France, mainly due to local dissemination, associated with bacterial carriage by patients in the community, which is becoming an immediate challenge with regard to outbreak control.

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