A study on the asymmetry of the news aspect of the stock market: Evidence from three institutional investors in the Taiwan stock market

Yang, Tzu‐Yi; Yang, Yu‐Tai

doi:10.2298/pan1503361y

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…The stability test of prediction error of data 1 in Table 5 was first operated based on the time-series modelling process. The main methods of stability test are drawing test and ADF test [30]. Figure 4 shows the sequence diagram of the estimated error of charging time.…”

Section: Combined Model Based On Regression and Time-series Methodsmentioning

confidence: 99%

Predicting Charging Time of Battery Electric Vehicles Based on Regression and Time-Series Methods: A Case Study of Beijing

Wang

Sun

et al. 2018

Energies

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Battery electric vehicles (BEVs) reduce energy consumption and air pollution as compared with conventional vehicles. However, the limited driving range and potential long charging time of BEVs create new problems. Accurate charging time prediction of BEVs helps drivers determine travel plans and alleviate their range anxiety during trips. This study proposed a combined model for charging time prediction based on regression and time-series methods according to the actual data from BEVs operating in Beijing, China. After data analysis, a regression model was established by considering the charged amount for charging time prediction. Furthermore, a time-series method was adopted to calibrate the regression model, which significantly improved the fitting accuracy of the model. The parameters of the model were determined by using the actual data. Verification results confirmed the accuracy of the model and showed that the model errors were small. The proposed model can accurately depict the charging time characteristics of BEVs in Beijing.

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Section: Combined Model Based On Regression and Time-series Methodsmentioning

confidence: 99%

Predicting Charging Time of Battery Electric Vehicles Based on Regression and Time-Series Methods: A Case Study of Beijing

Wang

Sun

et al. 2018

Energies

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“…In contrast, a 1% increase in stock prices leads to a 0.54% change in oil prices. Additionally, the adoption of a threshold generalized autoregressive conditional heteroskedasticity (TGARCH) model was used by Tzu-Yi Yang and Yu-Tai Yang (2015) to investigate the asymmetric effects of news on stock market behavior. Xiao Qin, Chunyang Zhou, and Chongfeng Wu (2016) investigated a rockets and feathers theory with a multiple threshold error-correction model (MTECM) and found a nonlinear relationship in the short-term between crude oil and gasoline prices in commodity and financial markets but not in refinery markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Oil threshold value between oil price and production

2019

Self Cite

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This study proposes a panel smooth transition regression (PSTR) model to investigate the nonlinear relationship between crude oil prices and crude oil production in 122 countries, both OPEC and non-OPEC, from March 1994 to October 2015. The statistical test for the existence of a threshold effect indicates that the relationship between oil prices and oil production is nonlinear, with different changes over time among the oil price and transition variables. Additionally, a threshold value exists. Furthermore, crude oil price volatility exhibits asymmetric responses to production volatility by fluctuating above or below the threshold value. Finally, when crude oil price volatility with a lag of two periods exceeds the threshold value, crude oil production changes have a positive impact on crude oil price volatility. In contrast, when crude oil price volatility with a lag of two periods is less than the threshold value, crude oil production changes have a negative impact on price volatility.

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A study on the asymmetry of the news aspect of the stock market: Evidence from three institutional investors in the Taiwan stock market

Cited by 2 publications

References 15 publications

Predicting Charging Time of Battery Electric Vehicles Based on Regression and Time-Series Methods: A Case Study of Beijing

Predicting Charging Time of Battery Electric Vehicles Based on Regression and Time-Series Methods: A Case Study of Beijing

Oil threshold value between oil price and production

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