Co-movement in Stock Prices in Emerging Economies: The Case of the Caricom Region

The Grand Anse Declaration of 1989 recognised the need for financial integration within the emerging economies that comprise the CARICOM region, as a way of furthering the wider process of economic integration and, indeed, economic development in that region. Using co-movement as a measure of financial integration, this paper investigates the co-movement in stock prices among the Barbados, the Jamaica and the Trinidad and Tobago Stock Exchanges, the three major exchanges within the CARICOM region. It also examines how integrated these exchanges are with the New York Stock Exchange. The GARCH-Copula methodology and, to a lesser extent, estimated correlation coefficients, are used to attain this objective. There appears to be co-movement in stock prices and returns within the CARICOM stock markets and significant dependence structures between the returns of the three CARICOM stock markets. However, there is considerably less evidence of integration between the CARICOM markets and the New York Stock Exchange.     

基于动态冲击试验的通勤类飞机座椅符合性验证技术

国产某型民用通勤类飞机为了取得欧洲航空安全局(EASA)型号合格证,机上座椅需进行设计更改并补充进行应急着陆情况下的动态要求符合性验证.通过对适航条款及相应标准的解读,研究了基于动态试验的航空座椅动态要求适航验证技术,其主要包括座椅动态性能基本要求、试验构型及工况筛选、试验规划、合格判据和试验结果分析等内容.结果表明,该型机旅客座椅满足适航规章对座椅的动态性能要求.该项旅客座椅动态性能试验的成功为型号取得EASA型号合格证奠定了良好的基础,该型飞机也即将成为第一个取得欧洲型号合格证的国产飞机.     

Capital market integration in ASEAN: A non-stationary panel data analysis

Motivated by the establishment of ASEAN Economic Community (AEC) at the end of 2015, we examine saving-investment relationship in various subgroups of ASEAN to assess their capital market integration. The results from second generation panel unit-root and cointegration tests that account for cross-sectional dependence as well as estimates of long-run saving-retention rate provide some evidence of market integration in ASEAN. The analysis of short-run dynamics suggests that capital mobility in ASEAN during 1980–2014 appears similar to that in OECD countries during 1970–1999. More importantly, across different panel estimators and subgroups of membership, there is considerable heterogeneity among the member countries. The saving-investment association is very weak, thereby implying very high capital mobility, in more developed members such as Singapore, Malaysia, and Brunei; the association is very strong, implying very low capital mobility, for much less developed members such as Laos, Myanmar, and Cambodia. The results call for renewed effort to develop capital markets in less developed nations and integrate them with the rest of the membership in ASEAN. In this paper, we also address several major shortcomings of the original Feldstein-Horioka framework.     

Panel LM unit root tests with level and trend shifts

This paper considers a Lagrange multiplier (LM) based panel unit root test that allows for heterogeneous structural breaks in both the intercepts and slopes of a series. We note that many popular time series variables are likely to exhibit changing means and/or trends over time. Given that the usual tests will depend on the nuisance parameters indicating the locations of the trend breaks, we adopt a transformation procedure that makes our new panel unit root tests invariant to the nuisance parameters. To illustrate the importance of the power gain provided by our test, we examine the convergence hypothesis using relative ratios of per capita health care expenditures in 20 OECD countries. Our results provide evidence that the convergence hypothesis is supported.     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

The saving–investment correlation puzzle is still a puzzle

A number of simulation studies claim to have solved the Feldstein–Horioka puzzle by demonstrating that a high time-series correlation between saving and investment naturally arises from business cycle shocks. This paper uses panel data of saving and investment controlled for business cycle shocks to empirically test the significance of cyclical shocks — productivity, fiscal and the terms of trade shocks — in explaining a high saving–investment correlation. The estimation results reveal that conventional aggregate shocks only partially explain the high saving–investment correlation. Moreover, country differences in the size of the GNP and the non-traded sector do not significantly affect the saving–investment correlation. The saving–investment correlation puzzle remains a puzzle after all.     

Beyond Single-Factor Affine Term Structure Models

This article proposes a new approach to testing for the hypothesisof a single priced risk factor driving the term structure ofinterest rates. The method does not rely on any parametric specificationof the state variable dynamics or the market price of risk.It simply exploits the constraint imposed by the no-arbitragecondition on instantaneous expected bond returns. In order toachieve our goal, we develop a Kolmogorov-Smirnov test and applyit to data on Treasury bills and bonds for both the United Statesand Spain. We find that the single risk factor hypothesis cannotbe rejected for either dataset.     

The Importance of Professional Training for Test Writers

The importance of language testing is noticed by more and more people.But the quality of testing,or say,the level of test writers,has been ignored for a long time.This article intends to talk about the importance of professional training for test writ- ers,in order to arouse people＇s attention to the quality of test designers.     

标准化在油藏监测工作中的作用

以油藏监测工作中的油藏压力监测为例，介绍了标准化工作在压力资料录取及解释分析中的作用。并用实例说明了标准化作业在油田开发方案的制定及油藏压力监测中的应用。     

Predicting the geo-temporal variations of crime and disorder

Traditional police boundaries—precincts, patrol districts, etc.—often fail to reflect the true distribution of criminal activity and thus do little to assist in the optimal allocation of police resources. This paper introduces methods for crime incident forecasting by focusing upon geographical areas of concern that transcend traditional policing boundaries. The computerised procedure utilises a geographical crime incidence-scanning algorithm to identify clusters with relatively high levels of crime (hot spots). These clusters provide sufficient data for training artificial neural networks (ANNs) capable of modelling trends within them. The approach to ANN specification and estimation is enhanced by application of a novel and noteworthy approach, the Gamma test (GT).