scholarly journals Employment Dynamics and Business Relocation: New Evidence from the National Establishment Time Series

2005 ◽  
Author(s):  
David Neumark ◽  
Junfu Zhang ◽  
Brandon Wall
Keyword(s):  
Time Series ◽  
Employment Dynamics ◽  
Business Relocation ◽  
New Evidence

scholarly journals Forecasting stock price movement: new evidence from a novel hybrid deep learning model

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yang Zhao ◽  
Zhonglu Chen
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Hybrid Model ◽  
Stock Price ◽  
Linear Time ◽  
Price Movement ◽  
Content Type ◽  
Non Linear ◽  
New Evidence ◽  
Deep Learning Model

PurposeThis study explores whether a new machine learning method can more accurately predict the movement of stock prices.Design/methodology/approachThis study presents a novel hybrid deep learning model, Residual-CNN-Seq2Seq (RCSNet), to predict the trend of stock price movement. RCSNet integrates the autoregressive integrated moving average (ARIMA) model, convolutional neural network (CNN) and the sequence-to-sequence (Seq2Seq) long–short-term memory (LSTM) model.FindingsThe hybrid model is able to forecast both linear and non-linear time-series component of stock dataset. CNN and Seq2Seq LSTMs can be effectively combined for dynamic modeling of short- and long-term-dependent patterns in non-linear time series forecast. Experimental results show that the proposed model outperforms baseline models on S&P 500 index stock dataset from January 2000 to August 2016.Originality/valueThis study develops the RCSNet hybrid model to tackle the challenge by combining both linear and non-linear models. New evidence has been obtained in predicting the movement of stock market prices.

scholarly journals Productivity and employment dynamics: new evidence from Italian regions

2018 ◽  
Vol 35 (2) ◽  
pp. 313-336
Author(s):  
Bianca Biagi ◽  
Maria Gabriela Ladu
Keyword(s):  
Employment Dynamics ◽  
Italian Regions ◽  
New Evidence

scholarly journals Solar-Like Oscillations of Procyon A: Stellar Models and Time Series Simulations versus Observations

2000 ◽  
Vol 176 ◽  
pp. 461-462
Author(s):  
C. Barban ◽  
E. Michel ◽  
M. Martic ◽  
J. Schmitt ◽  
J. C. Lebrun ◽  
...  
Keyword(s):  
Time Series ◽  
Power Spectrum ◽  
Numerical Simulations ◽  
Observational Data ◽  
Theoretical Predictions ◽  
Stellar Models ◽  
Excess Power ◽  
New Evidence

AbstractThe aim of this paper (further developed in Barban et al. 1999) is to present new evidence of the possible stellar origin of the observed excess power in the power spectrum of Procyon A presented in Martic et al. (1999) by comparing these observational data with theoretical predictions and numerical simulations.

scholarly journals Underemployment and Local Employment Dynamics: New Evidence

2009 ◽  
Author(s):  
Michaël Bonnal ◽  
Cristina Lira ◽  
Samuel N. Addy
Keyword(s):  
Employment Dynamics ◽  
New Evidence ◽  
Local Employment
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