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Asian Stock Markets Analysis: The New Evidence from Time-Varying Coefficient Autoregressive Model
HONGSAKULVASU, Napon,LIAMMUKDA, Asama Korea Distribution Science Association 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.9
In financial economics studies, the autoregressive model has been a workhorse for a long time. However, the model has a fixed value on every parameter and requires the stationarity assumptions. Time-varying coefficient autoregressive model that we use in this paper offers some desirable benefits over the traditional model such as the parameters are allowed to be varied over-time and can be applies to non-stationary financial data. This paper provides the Monte Carlo simulation studies which show that the model can capture the dynamic movement of parameters very well, even though, there are some sudden changes or jumps. For the daily data from January 1, 2015 to February 12, 2020, our paper provides the empirical studies that Thailand, Taiwan and Tokyo Stock market Index can be explained very well by the time-varying coefficient autoregressive model with lag order one while South Korea's stock index can be explained by the model with lag order three. We show that the model can unveil the non-linear shape of the estimated mean. We employ GJR-GARCH in the condition variance equation and found the evidences that the negative shocks have more impact on market's volatility than the positive shock in the case of South Korea and Tokyo.
Nonparametric Kernel Estimation of Evolutionary Autoregressive Processes
Woocheol Kim 서울대학교 경제연구소 2012 Seoul journal of economics Vol.25 No.4
This paper develops a new econometric tool for evolutionary autoregressive models, where the AR coefficients change smoothly over time. To estimate the unknown functional form of time-varying coefficients, we propose a modified local linear smoother. The asymptotic normality and variance of the new estimator are derived by extending the Phillips and Solo device to the case of evolutionary linear processes. As an application for statistical inference, we show how Wald tests for stationarity and misspecification could be formulated based on the finite-dimensional distributions of kernel estimates. We also examine the finite sample performance of the method via numerical simulations.
Analysis of Term Structure in Dry Bulk Freight Market
Byoung-wook KO 한국해운물류학회 2013 The Asian journal of shipping and Logistics Vol.29 No.1
Based on the monthly data set from January 1992 to May 2012, this paper applies a VAR model and two time-varying coefficient models to analyze term structure in dry bulk freight market. The resulting three main empirical findings are as follows: 1) The response of long-term rate to shortterm structural shock is relatively small and not statistically significant but the response of short-term rate to long-term structural shock is large and statistically significant. 2) Compared with the presumption that in backwardation the short-term rate is inclined to decrease but the long-term rate to increase, but in contango the opposite pressure would function, there is lack of evidence for the stable adjustment speed in both equations for the short- and long-term freight rate. 3) When the market is relatively above the normal level (more backwardation), the effect of the implied forward time charter (IFTC) rate on the actual TC rate becomes larger. When predicting the future TC rate based on IFTC rate, it recommends giving more weight to the IFTC rate in backwardation than in contango.