基于IOWGA的汇价预测风险程度的组合预测

通过定义汇价预测风险程度,分析其成分数据性质,运用IOWGA算子对多元线性回归的预测风险程度建立组合预测模型。结果表明:基于IOWGA算子的组合预测具有优越性,对汇价预测风险程度准确预测,为汇率投资者的风险预防与控制提供参考。     

A functional approach to pricing complex barrier options

In this article, a new method for pricing contingent claims, which is particularly well suited for options with complex barrier and volatility structures, is introduced. The approach is based on a high-precision approximation of the Feynman–Kac equation with distributed approximating functionals. The method is particularly well suited for long maturity valuation problems, and it is shown to be faster and more accurate than conventional solution schemes.     

Tour Booking: Do Travelers Respond to Tourism Accreditation and Codes of Ethics Initiatives?

Tourism and hospitality organizations are spending more time and money on corporate social responsibility (CSR) initiatives, but at the same time not fully understanding how such initiatives enhance travelers’ responses. This study investigates the impact of two CSR initiatives that have been widely adopted by many travel organizations: tourism accreditation and codes of ethics. A large-scale survey collected data on how potential travelers responded to an online tour brochure. The results showed that both accreditation and code of ethics information in a brochure have significant but varying impacts on perceived tour value, trust, and tour booking intention.     

探讨模糊算子在遥感图像特征提取中的应用

本文主要阐述了模糊算子在遥感图像特征提取中的一般方法以及利用模糊算子对数据进行融合的应用等内容。     

校园用户识别在电信领域的优化方案

在全业务市场竞争的背景下,校园市场将成为各大运营商争夺的焦点。运营商需要及时、准确地了解学生客户的状态和发展趋势。本文针对现有校园用户识别模型提出了优化方案,以便有针对性制定营销方案、促进校园市场的发展。     

Do owner–operators pose a safety risk on the nation’s highways?

Despite persistent claims in the motor carrier industry of poorer safety performance of owner–operators, there is little empirical work directly comparing owner–operator safety performance to that of employee drivers. This study assesses the statistical significance of differences in the safety performance between owner–operators and employee drivers. This study also expands on previous driver focused safety models by examining how driver and carrier characteristics affect safety performance. Data for this study were derived from the Motor Carrier Management Information System (MCMIS), and the Commercial Driver’s License Information System (CDLIS) databases. Study results provide evidence that owner–operators are associated with more driver- and vehicle-out-of-service violations but experience lower crash rates than do employee drivers.     

深入分析C语言自增表达式

C语言中的自增运算符有2种运算顺序,灵活复杂。在自增表达式中,由于运算符的优先级和其自身运算规则的矛盾,需要同时兼顾这两方面才能得到正确结果。以Turbo C为环境,对自增运算处于不同的表达式的各种情况进行探讨,深入分析了自增的运算过程,给出了自增的运算规则。     

Fock空间上的复合算子

设L_a~2(C)是Fock空间(也称Segal—Bargmann空间),它是复平面C上以K_λ(z)=e~(λx/2)为再生核的整函数组成的解析Hilbert空间。该文研究L_a~2(C)上的复合算子C_φ的有界性、紧性等特征。主要结果是:C_φ在L_a~2(C)上有界(或紧)当且仅当φ=λz+a,其中λ,α∈C且|λ|≤1(或|λ|<1)。     

2×2算子矩阵的数值域扰动问题

给出了有限维H ilbert空间中2×2算子矩阵的数值域扰动定理的两种证明方法,并且将该定理推广到无限维H ilbert空间上的自伴算子。     

Determinants of dividend payout and dividend propensity in an emerging market,Iran: an application of the LASSO

Accurate prediction of dividends is important for market participants such as investors, firm managers, and monitoring authorities, as they can, respectively, invest, manage dividend decisions, and monitor dividend policies more effectively. We identify the most relevant variables for predicting the dividend payout of the firms in an emerging market, Iran, using the least absolute shrinkage and selection operator (LASSO). The advantages of the LASSO include: enhancing the prediction accuracy of the dividend model, improving interpretation of the results, and applicability to high-dimensional data. We obtain several results. First, some fundamental determinants of dividends in the industrialized economies such as market-to-book ratio and current ratio, do not play a role in deciding dividends in Iran. Second, LASSO-selected variables outperform the variables commonly used in the literature in terms of model fit and prediction accuracy. Third, business risk, leverage, return on assets and effective tax rate are the most important predictors of dividend propensity of the Iranian firms. Fourth, if the support vector machine algorithm, an often-used classification method, is combined with LASSO-selected variables, it can better discriminate between dividend-paying and dividend non-paying firms than other methods such as logistic regression and linear discriminant analysis.

Abbreviations: LASSO: Least Absolute Shrinkage and Selection Operator; TSE: Tehran Stock Exchange; RMSE: Root Mean Squared Errors; MAE: Mean Absolute Errors; ROC: Receiver Operating Characteristics; GMM: Generalized Method of Moments; MENA: Middle East and North Africa region; AIC: Akaike Information Criterion; BIC: Bayesian Information Criterion; LARS: Least Angel Regression; OLS: Ordinary Least Squares; AUC: Area Under Curve; BS: Brier Score ; OA: Overall Accuracy; LDA: Linear Discriminant Analysis; SVM: Support Vector Machine algorithm; LR: Logistic Regression.