The lasso of Tibshirani （1996） is a least-squares problem regularized by the l1 norm. Due to the sparseness promoting property of the l1 norm, the lasso has been received much attention in recent years. In this pape...The lasso of Tibshirani （1996） is a least-squares problem regularized by the l1 norm. Due to the sparseness promoting property of the l1 norm, the lasso has been received much attention in recent years. In this paper some basic properties of the lasso and two variants of it are exploited. Moreover, the proximal method and its variants such as the relaxed proximal algorithm and a dual method for solving the lasso by iterative algorithms are presented.展开更多
When the variable of model is large, the Lasso method and the Adaptive Lasso method can effectively select variables. This paper prediction the rural residents’ consumption expenditure in China, based on respectively...When the variable of model is large, the Lasso method and the Adaptive Lasso method can effectively select variables. This paper prediction the rural residents’ consumption expenditure in China, based on respectively using the Lasso method and the Adaptive Lasso method. The results showed that both can effectively and accurately choose the appropriate variable, but the Adaptive Lasso method is better than the Lasso method in prediction accuracy and prediction error. It shows that in variable selection and parameter estimation, Adaptive Lasso method is better than the Lasso method.展开更多
This paper focuses on volatility spillover effects and considers the issue of how to measure the connectedness of networks among financial firms.To assess the network connectedness of firms from different industries,w...This paper focuses on volatility spillover effects and considers the issue of how to measure the connectedness of networks among financial firms.To assess the network connectedness of firms from different industries,we proposed a novel procedure and applied it to 20 leading financial institutions from four industries in China’s stock markets.The results show that the total connectedness of the Chinese financial system was much higher during the stock market crisis between June 2015 and February 2016 than during stable periods of economic development.This analysis can be used to determine which firms play a dominant role in risk transmission throughout the entire system.It is suggested that the government should provide targeted regulatory policies to particular types of firms.展开更多
文摘The lasso of Tibshirani （1996） is a least-squares problem regularized by the l1 norm. Due to the sparseness promoting property of the l1 norm, the lasso has been received much attention in recent years. In this paper some basic properties of the lasso and two variants of it are exploited. Moreover, the proximal method and its variants such as the relaxed proximal algorithm and a dual method for solving the lasso by iterative algorithms are presented.
文摘When the variable of model is large, the Lasso method and the Adaptive Lasso method can effectively select variables. This paper prediction the rural residents’ consumption expenditure in China, based on respectively using the Lasso method and the Adaptive Lasso method. The results showed that both can effectively and accurately choose the appropriate variable, but the Adaptive Lasso method is better than the Lasso method in prediction accuracy and prediction error. It shows that in variable selection and parameter estimation, Adaptive Lasso method is better than the Lasso method.
基金the National Natural Science Foundation of China(No.71771203)the National Natural Science Foundation of China(Nos.11671374 and 71631006).
文摘This paper focuses on volatility spillover effects and considers the issue of how to measure the connectedness of networks among financial firms.To assess the network connectedness of firms from different industries,we proposed a novel procedure and applied it to 20 leading financial institutions from four industries in China’s stock markets.The results show that the total connectedness of the Chinese financial system was much higher during the stock market crisis between June 2015 and February 2016 than during stable periods of economic development.This analysis can be used to determine which firms play a dominant role in risk transmission throughout the entire system.It is suggested that the government should provide targeted regulatory policies to particular types of firms.
