基于RBF和PSO的双喉道气动矢量喷管优化设计

本文探索了一种能多变量综合优化的方法,即对喷管进行参数化设计后,用均匀试验设计(UED)将试验样本均匀散布在设计区间内,求出各性能参数后,利用径向基神经网络(RBF)对试验样本进行拟合,再用粒子群算法(PSO)对训练好的神经网络进行寻优,找出了更好的双喉道气动矢量喷管设计参数组合。数值模拟结果显示,优化后的双喉道气动矢量喷管的矢量角有了明显提高。试验表明这种优化方法具有很好的优化能力,可以用来对喷管几何外形进行参数优化。      

浅谈物理量的方向性

物理量按方向性可分为矢量和标量,本文通过实例运用平行四边形法则和正交分解法求矢量的大小和方向。进一步明确矢量方向性的物理意义。     

我国金融发展对居民收入分配影响的实证研究

我国金融发展对城乡居民收入分配影响的实证研究结果表明:金融发展规模是城乡居民收入差距的格兰杰原因;金融发展效率与城乡居民收入差距具有双向的格兰杰因果关系.金融发展规模的扩张扩大了城乡居民收入差距,金融发展效率的提升则缩小了城乡居民收入差距.     

Building With Bricks and Mortar: The Revenue Impact of Opening Physical Stores in a Multichannel Environment

A crucial decision firms face today is which channels they should make available to customers for transactions. We assess the revenue impact of adding bricks-and-mortar stores to a firm's already existing repertoire of catalog and Internet channels. We decompose the revenue impact into customer acquisition, frequency of orders, returns, and exchanges, and size of orders, returns, and exchanges. We use a multivariate baseline method to assess the impact of adding the physical store channel on these revenue components. As hypothesized, store introduction cannibalizes catalog sales and has much less impact on Internet sales. Also as hypothesized, returns and exchanges increase. Interestingly, transaction sizes of purchases, returns, and exchanges do not change. The “availability effect” produces a net increase in purchase frequency across channels. This more than compensates for increased returns, producing a net increase in revenues of 20% by adding the store channel. Our findings yield a deeper understanding of the revenue relation between channels, and of the dynamic cross-channel effects of marketing actions.     

Intersectoral wage linkages: the case of Sweden

The purpose of this study is to investigate whether wage-setting in certain sectors of the Swedish economy affects wage-setting in other sectors. The theoretical background is the Scandinavian model of inflation, which states that wage-setting in the sectors exposed to international competition lead wage-setting in the sheltered sectors of the economy. The Johansen maximum likelihood cointegration approach is applied to quarterly data on Swedish sector wages for the period 1980:1–2002:2. Different vector error correction (VEC) models are created, based on assumptions as to which sectors are exposed to international competition and which are not. Granger causality tests are then carried out in the different restricted/unrestricted VEC models to test for sector wage leadership. The Granger causality tests provide strong evidence for the presence of intersectoral wage causality, but no evidence of a wage-leading role for the internationally exposed manufacturing sector.      

基于 LSSVM 的供应链金融业务中企业信用风险评估研究

针对目前供应链金融业务中企业信用风险评估不科学与不完善的问题,在对企业信用风险评估的指标体系进行梳理和完善的基础上,利用最小二乘支持向量机(LSSVM)的基本原理尝试构建了企业信用风险 LSSVM 评估模型,并对模型的可行性和优越性做了分析和验证。研究结果表明：LSSVM 评估模型收敛速度快、准确度较高、泛化能力强,为供应链金融业务中的企业信用风险评估提供了一种新的办法和思路。     

Linear predictability vs. bull and bear market models in strategic asset allocation decisions: evidence from UK data

Most papers in the portfolio choice literature have examined linear predictability frameworks based on the idea that simple but flexible Vector Autoregressive (VAR) models can be expanded to produce portfolio allocations that hedge against the bull and bear dynamics typical of financial markets through careful selection of predictor variables that capture business cycles and market sentiment. Yet, a distinct literature exists that shows that non-linear econometric frameworks, such as Markov switching, are also natural tools to compute optimal portfolios arising from the existence of good and bad market states. This paper examines whether and how simple VARs can produce portfolio rules similar to those obtained under a simple Markov switching, by studying the effects of expanding both the order of the VAR and the number/selection of predictor variables included. In a typical stock-bond strategic asset allocation problem for UK data, we compute the out-of-sample certainty equivalent returns for a wide range of VARs and compare these measures of performance with those of non-linear models. We conclude that most VARs cannot produce portfolio rules, hedging demands or (net of transaction costs) out-of-sample performances that approximate those obtained from simple non-linear frameworks.     

Sources of exchange rate fluctuations: Are they real or nominal?

I analyze the role of real and monetary shocks on exchange rate behavior using a structural vector autoregressive model of the US vis-à-vis the rest of the world. The shocks are identified using sign restrictions on the responses of the variables to orthogonal disturbances. These restrictions are derived from the predictions of a two-country DSGE model. I find that monetary shocks are unimportant in explaining exchange rate fluctuations. By contrast, demand shocks explain between 21% and 37% of exchange rate variance at 4-quarter and 20-quarter horizons, respectively. The contribution of demand shocks plays an important role but not of the order of magnitude sometimes found in earlier studies. My results, however, support the recent focus of the literature on real shocks to match the empirical properties of real exchange rates.     

Do Vietnamese upland farmers benefit from high world market prices for maize?

For rural households in the north of Vietnam, maize cropping is the main source of income. In the face of the world market price increases of the recent past, we analyze the regional marketing chain of this commodity qualitatively and econometrically investigating to what extent smallholder farmers in developing countries are affected by international price movements. Vietnamese maize markets are found to be well integrated. Recent price hikes have fully transmitted along the regional supply chain so that farmers profited. Nevertheless, adverse factors such as increasing input prices have neutralized these benefits resulting in a decline in real income of smallholders.     

Forecasting exchange rates in transition economies: A comparison of multivariate time series models

This article compares the accuracy of vector autoregressive (VAR), restricted vector autoregressive (RVAR), Bayesian vector autoregressive (BVAR), vector error correction (VEC) and Bayesian vector error correction (BVEC) models in forecasting the exchange rates for five Central and Eastern European currencies (Czech Koruna, Hungarian Forint, Polish Zloty, Slovak Koruna and Slovenian Tolar) against the Euro and the US dollar. Among the specifications composing this battery of multivariate time series models, those with the smallest prediction error still fail to reject the test of equality of forecasting accuracy against the random walk model in short-term predictions, with the exception of the Slovenian Tolar/Euro exchange rate.First version received: October 2002/Final version received: September 2003The authors are grateful to two anonymous referees and the participants in the workshop Monetary and Exchange Rate Strategies Related to the Current European Unions Enlargement Processes, held in Leuven in September 2000, for very helpful comments.