基于总体最小二乘准则的OFDM系统时变信道估计

信道估计的准确程度直接影响正交频分复用系统的性能。为了提高时变信道估计算法的精度,基于总体最小二乘准则(TLS)提出了一种时变信道的估计方法。该方法用线性模型对时变信道进行建模,不仅考虑了信道噪声,同时也兼顾了模型误差。该方法能较好地跟踪信道的变化,显著消除模型误差。仿真结果表明所提算法的均方误差介于最小二乘算法与最小均方误差算法之间,在不同归一化多普勒频移下,该算法具有较好的稳健性。     

中美两国经济波动及其相互影响的频域分析

以中美两国ＧＤＰ增长率为研究对象,通过计算其时变谱函数并联系经济现实,对两国各自的经济波动情况进行了分析。在此基础上,通过计算中美两国ＧＤＰ增长率间的时变增益函数,分析两国经济波动间的相互影响。结果显示,２００８年以前美国对中国经济的影响在逐渐减弱。即使发生了２００８年的金融危机,美国对中国经济的影响也主要集中在出口行业,美国经济受中国的影响在持续增加,并且这种影响主要集中在产业结构和社会消费习惯等方面。目前,这种影响依然存在。     

基于Copula的股票型开放式基金的组合风险度量

本文在＂推出股指期货和融资融券＂的新政策下,结合t-EGARCH模型和Copula方法对股票型开放式基金进行分析.该模型能更好地捕捉资产间的非线性相关性,更符合现实市场.并在此基础上,利用蒙特卡洛模拟计算了景顺增长基金前十大重仓股票及其投资组合的VaR值,从而验证了模型的有效性。     

开放三十年政府支出对二元经济的转化效果

基于中国1978-2008年时间序列数据,采用时变参数模型对我国政府支出对二元经济结构转化效果进行分析,结果表明：改革开放30年来,我国政府支出对城乡二元经济结构转化的影响曲线呈U形;政府分类支出方面,不同时期,政府分类支出对二元经济结构转化效果的影响不同。近年来,政府行政性支出和民生性支出对二元经济结构转化具有一定正向影响,但影响效果在不断下降;而基本建设支出对二元经济转化产生了负向影响。要通过制度创新调整政府支出结构,以促进二元经济结构向好的方向转化。     

股价波动序列的综合预测法研究

股票市场中股票价格的波动是一个非线性混沌时间序列,其参数是随时间变化的。笔者提出的多层递阶一灰色预测综合预测法是运用多层递阶法,通过辨识时变参数,建立时变参数动态预测模型,并在此基础上进一步运用灰色预测方法,通过对时变参数的预测来预测股票价格的波动。实例表明：多层递阶一灰色预测综合预测法有较好的预测精度。     

The joint effects of financial development and the business environment on firm growth: Evidence from Vietnam

This work examines the complementary effects of local financial development and the business environment on the growth of Vietnamese firms. For the period from 2009 to 2013, we combine firm-level data covering more than 40,000 firms from the Vietnam Enterprise Survey with province-level data from the Vietnam Provincial Competitiveness Indicators. Our estimation strategy builds upon a novel copula-based estimator that accounts for potential endogeneity biases without requiring external instruments. Our results show that financial development and a favourable business environment generally promote firm growth, but some components of the business environment, such as low entry costs, access to land and business service support, foster firm growth more strongly than financial development. Most importantly, financial development and the business environment interact positively in their effects on firm growth. The impact of local financial development on firm growth is higher in provinces with a competitive business environment. Conversely, improvements in provincial competitiveness have a greater impact on firm growth in provinces with a more developed financial sector. The results clearly show that policies to promote local financial development need to be coordinated with measures to improve the broader business environment.     

Correlations among cryptocurrencies: Evidence from multivariate factor stochastic volatility model

This paper is the first study to apply the multivariate factor stochastic volatility model (MFSVM) for analyzing the correlations among six cryptocurrencies. We use MFSVM with the Bayesian estimation procedure for the period from August 8, 2015, to January 1, 2020. According to the findings, there is a significant positive correlation between price volatility values of Bitcoin and Litecoin. Besides, the volatility values of Ethereum have a positive correlation with both Ripple and Stellar. There is also a positive correlation between the volatility values of Ripple and Dash. These findings are robust to consider different correlation networks. The evidence implies that Bitcoin is mainly related to Litecoin, but Ethereum is associated with other cryptocurrencies.     

Incorporating time-varying jump intensities in the mean-variance portfolio decisions

This paper examines the role of time-varying jump intensities in forming mean-variance portfolios. We find that compared with the no-jump or constant-jump models, the model which incorporates time-varying jump intensities better fits the dynamics of the assets returns, and yields mean-variance portfolios with higher Sharpe ratios. Our research suggests that using a better econometric model that captures non-normal features in the data has benefits for portfolio allocation even for a mean-variance investor.     

利用时变噪声贝叶斯卡尔曼滤波的室内移动目标定位

基于射频识别的指纹滤波定位技术是当前室内定位中常使用的技术之一。针对该技术存在的卡尔曼滤波算法不能准确适应环境噪声变化，致使定位精度不高的问题，提出了一种适应时变噪声的贝叶斯卡尔曼滤波算法。所提算法结合Sage-Husa滤波模型和贝叶斯模型，实现了过程和测量协方差矩阵的最优化，有效地降低了噪声，提高了指纹滤波定位的精度。实验结果表明，与变分贝叶斯卡尔曼滤波和Sage-Husa滤波相比，无障碍情况下，基于改进算法的定位精度提高了6%以上；有障碍干扰下，则提高了14.6%以上。     

Invoice currency choice,nonlinearities and exchange rate pass-through

ABSTRACT

Estimating time-varying thresholds as a proxy for exporter’s predicted exchange rates, this study proposes a new approach to analyse possible asymmetric behaviour of exchange rate pass-through (ERPT) or pricing-to-market (PTM) in Japanese exports between yen appreciation and depreciation periods. Constructing the industry-specific nominal effective exchange rate on a contract (invoice) currency basis, we perform the multivariate threshold near-vector autoregressive (near-MTVAR) estimation and reveal a strong tendency of symmetric ERPT in the short-run, between yen appreciation and depreciation periods. From the 2000s, however, Japanese machinery exporters increased the degree of PTM even in the long-run, while other industries raised the degree of long-run ERPT, reflecting the difference of product differentiation across industries. This evidence has significant implications for the recent unresponsiveness of the Japanese trade balance to the large depreciation of the yen.