资本渐进开放下我国与国际利率的联动分析——基于中国和美国的比较

一般来说,利率在国家间的传导主要有两条渠道:国际贸易间的传导和资本自由流动下的利率平价机制。本文采取分阶段考察,通过建立计量经济学模型,利用单位根检验和协整分析加以验证,发现在资本项目部分开放后,中美利率开始具有联动效应,作用方式又具有自身的特点。目前资本项目开放度不够高是阻碍我国同世界利率联动的主要原因。     

Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models

Nine macroeconomic variables are forecast in a real-time scenario using a variety of flexible specification, fixed specification, linear, and nonlinear econometric models. All models are allowed to evolve through time, and our analysis focuses on model selection and performance. In the context of real-time forecasts, flexible specification models (including linear autoregressive models with exogenous variables and nonlinear artificial neural networks) appear to offer a useful and viable alternative to less flexible fixed specification linear models for a subset of the economic variables which we examine, particularly at forecast horizons greater than 1-step ahead. We speculate that one reason for this result is that the economy is evolving (rather slowly) over time. This feature cannot easily be captured by fixed specification linear models, however, and manifests itself in the form of evolving coefficient estimates. We also provide additional evidence supporting the claim that models which ‘win’ based on one model selection criterion (say a squared error measure) do not necessarily win when an alternative selection criterion is used (say a confusion rate measure), thus highlighting the importance of the particular cost function which is used by forecasters and ‘end-users’ to evaluate their models. A wide variety of different model selection criteria and statistical tests are used to illustrate our findings.     

Optimal pair-trading strategy over long/short/square positions—empirical study

Suzuki [Automatica, 2016, 67, 33–45] solves the optimal, finitely iterative, three-regime switching problem for investing in a mean-reverting asset that follows an Ornstein–Uhlenbeck price process and find explicit solutions. The remarkable feature of this model is that the investor can explicitly take either a long, short or square position and can switch the position, with transaction costs, during the investment period. We run empirical simulations of such multiple-regime switching models. There are very few such attempts in the existing literature because it is difficult to find, first, an explicit solution to the problem and second, appropriate financial assets that follow the artificial stochastic process required by the mathematical model. According to the Monte Carlo simulations of the optimal pair-trading strategy, the mean daily Sharp ratio is more than 2.3, whereas the mean Sharp ratio for the historical simulation of the ‘stub’ pairs (combinations of parent/subsidiary companies) is 0.6886. We believe that the results obtained from performing the empirical simulations are remarkable and consider that the optimal switching strategy of the rigorous mathematical model is applicable to businesses in the real world. For the reference many pseudo-program codes are added, which can help to replicate the optimal trading strategies.     

Evidence on the existence of speculative bubbles in farmland prices

We conduct tests for the contribution of speculative bubbles to farmland prices. These tests are carried out under the hypothesis that farmland investors rationally form expectations. The outcome of tests reported here allows us to infer whether farmland prices are determined by market fundamentals-discounted returns from the highest economic land use-or whether rumors about farmland price movements are self-fulfilling. The tests are stationarity and cointegration tests relating farmland prices to rents. The tests are carried out using data from three farm production regions-the Corn Belt, the Northern Plains, and the Lake States. In each region, we find little evidence to reject the hypothesis that market fundamentals determine farmland prices.     

An objective Bayesian analysis of common stochastic trends in international stock prices and exchange rates

This paper uses Bayesian methods to analyze unit root and cointegration properties of two different finance data sets. Avoiding the use of subjective prior information, the paper surveys and utilizes several different objective Bayesian methodologies in an investigation of common stochastic trends in international stock markets and in spot and forward exchange rates for several different countries.     

Estimating the Equilibrium Effective Exchange Rate for Potential EMU Members

In this study, we attempt to examine the possibility of emergence of significant fluctuations of the exchange rates in the future for the candidate EMU countries. In doing so, we estimate the equilibrium rate of the nominal effective exchange rate for Poland, Hungary, Slovak Republic and Malta through the BEER and PEER approaches. While the PEER-based estimation implies a large misalignment rate for the Hungarian forint, the BEER-based analysis shows that the present exchange rates of the countries considered do not deviate significantly from their equilibrium rates. As a consequence, based on BEER analysis, we do not expect large fluctuations in the effective exchange rates among the currencies considered. Hence, the relevant effective exchange rates are expected to be relatively stable. As a matter of fact, the entry of those countries into EMU is not expected to weaken the stability of Euro.

Bayesian inference in cointegrated systems

In this paper I deal with Bayesian methods for conducting inference on important features of (potentially) cointegrated VAR models involving I(1) variables. Firstly, (informal) inference is made on the cointegrating rank of the system. Secondly, posterior analysis is used to verify the validity of over-identifying restrictions on the cointegration parameters. Thirdly, posterior distributions are obtained for impulse response functions and predictive densities at different horizons. The relevant posterior distributions are obtained by means of Monte Carlo integration. The analysis is based on the use of simple weakly informative priors. Two applications on simulated data and on the Danish money demand data are presented.     

Quantile cointegrating regression

Quantile regression has important applications in risk management, portfolio optimization, and asset pricing. The current paper studies estimation, inference and financial applications of quantile regression with cointegrated time series. In addition, a new cointegration model with quantile-varying coefficients is proposed. In the proposed model, the value of cointegrating coefficients may be affected by the shocks and thus may vary over the innovation quantile. The proposed model may be viewed as a stochastic cointegration model which includes the conventional cointegration model as a special case. It also provides a useful complement to cointegration models with (G)ARCH effects. Asymptotic properties of the proposed model and limiting distribution of the cointegrating regression quantiles are derived. In the presence of endogenous regressors, fully-modified quantile regression estimators and augmented quantile cointegrating regression are proposed to remove the second order bias and nuisance parameters. Regression Wald tests are constructed based on the fully modified quantile regression estimators. An empirical application to stock index data highlights the potential of the proposed method.     

中国饲料工业期货的价格发现实证研究

本文借助向量自回归模型、协整检验、误差修正模型、方差分解、脉冲响应函数等方法,以中国唯一的饲料工业期货———大连商品交易所豆粕期货品种为例,研究了期货价格与现货价格之间的动态关系,定量刻画了期货市场在价格发现中的作用。研究结果显示:豆粕期货价格与现货价格存在相互引导关系,并且期货与现货价格之间存在长期均衡关系,对豆粕期货来说,期货市场在价格发现功能中起到主导作用。     

我国股市与货币需求的相互影响分析及政策涵义

运用协整、弱外生性和因果关系检验对我国股票市场与货币需求的关系进行的实证研究发现,股市不影响M2的总量但影响其结构;M1对股市不产生直接影响,而M2对股市的直接影响处于有与无的临界状态;M1、M2均通过GDP对股市产生间接影响,但没有形成利率传导机制,我国股市是关于协整向量的弱外生变量.基于以上结论提出了相应的政策建议.