中国产业IT能力与产业绩效的耦合协调度研究——基于微观数据的产业分类测度

随着互联网+战略的深入推进,了解不同产业内信息技术能力与产业绩效之间的协调发展情况,对于系统把握我国的信息化发展水平,分类制定有效产业政策具有重要意义。有别于以往采用宏观产业数据,重点评价工业化与信息化融合度,本文主要基于2008~2015年的上市公司的微观数据,采用耦合协调模型,分类测度四大类产业的IT能力与产业绩效的耦合协调度。研究发现:总体上看我国的产业IT能力与产业绩效之间存在中高度耦合关系,但耦合质量不高,耦合协调度处于中低水平,呈现逐渐上升趋势;此外,我国的不同的产业之间的耦合协调度发展趋势存在差异性,本文进一步分析了该差异的存在的原因,并提出政策建议。     

考虑投资者风险态度的随机模糊投资组合模型及实证

考虑投资者面临证券市场随机和模糊的双重不确定性,把证券收益率视为随机模糊变量。在前景理论下考虑投资者的风险态度,建立不同的随机模糊收益率、期望收益隶属度函数和目标权重,构建考虑投资者风险态度的随机模糊投资组合模型。采用实证方法把市场分为下降和上升两个阶段,研究不同风险态度投资者的投资组合差异及模型表现。结果表明:投资者的风险态度会影响投资组合的结构;考虑投资者风险态度的随机模糊投资组合模型,能够满足不同风险态度投资者对投资收益和风险的差异需求,且在实际投资决策中具有可行性。     

Novel method for simultaneous measurement of film thickness and mass fraction of urea–water solution

Quantitative knowledge of the film thickness and mass fraction of the urea-water solution is very crucial in many practical applications. Film thickness or mass fraction can only be determined individually by conventional measurement techniques. We develop a novel measurement method to measure the film thickness and mass fraction of ure~water solution simultaneously. The absorption coefficients of urea-water solution （5 50 wt%） are measured, a pair of optimized wavelengths is then chosen to achieve high measurement sensitivity. Cross validation is also performed and uncertainties of the technique are smaller than 0.68% for thickness measurements and 1.86% for mass fractions.     

Analysis of the effects of the global financial crisis on the Turkish economy, using hierarchical methods

We have analyzed the topology of 50 important Turkish companies for the period 2006-2010 using the concept of hierarchical methods (the minimal spanning tree (MST) and hierarchical tree (HT)). We investigated the statistical reliability of links between companies in the MST by using the bootstrap technique. We also used the average linkage cluster analysis (ALCA) technique to observe the cluster structures much better. The MST and HT are known as useful tools to perceive and detect global structure, taxonomy, and hierarchy in financial data. We obtained four clusters of companies according to their proximity. We also observed that the Banks and Holdings cluster always forms in the centre of the MSTs for the periods 2006-2007, 2008, and 2009-2010. The clusters match nicely with their common production activities or their strong interrelationship. The effects of the Automobile sector increased after the global financial crisis due to the temporary incentives provided by the Turkish government. We find that Turkish companies were not very affected by the global financial crisis.     

Linking supply chain processes’ performance to a company’s financial strategic objectives

The main aim of this paper is to develop a performance measurement method which links supply chain (SC) processes’ performance to a company’s financial strategy through demonstrating and utilising the relationship between SC processes’ performance and a company’s financial performance.     

我国IPO市场的周期性行为研究:1994-2010

对IPO冷热周期内的时变波动特征首次建立区制转换GARCH模型加以有效描述,以及用计数数据分位数回归模型研究发行数量和发行到上市持续期的关系。通对1994年1月至2010年8月间我国A股IPO市场新股的实证研究得到若干新结论:上市首日收益率和发行到上市的持续期是发行数量的诱因,导致这三个描述IPO行为主要变量的周期行为之间存在相位差;发行到上市的持续期的降低对发行数量的增加有积极地促进作用;除了发行数量在淡季状态波动持续性较强外,其他变量在淡旺季的波动持续性均较弱;旺季时(调整后的)上市首日收益率、发行数量的波动方差比淡季时大,而发行到上市的持续期则相反;我国A股IPO发行市场的淡旺季周期的形成主要受到IPO发行政策、宏观经济环境、投资者情绪的影响控制。     

金融危机下Fama-French多因子模型在中国债券市场的应用

利用近3年的中国债券市场数据,建立了Fama-French多因子模型,并利用多元回归方法进行了比较分析.结果表明,TERM-DEF两因子模型有着较好的适用性,但存在进一步改进的空间.     

Rules extraction in short memory time series using genetic algorithms

Data mining is performed using genetic algorithm on artificially generated time series data with short memory. The extraction of rules from a training set and the subsequent testing of these rules provide a basis for the predictions on the test set. The artificial time series are generated using the inverse whitening transformation, and the correlation function has an exponential form with given time constant indicative of short memory. A vector quantization technique is employed to classify the daily rate of return of this artificial time series into four categories. A simple genetic algorithm based on a fixed format of rules is introduced to do the forecasting. Comparing to the benchmark tests with random walk and random guess, genetic algorithms yield substantially better prediction rates, between 50% to 60%. This is an improvement compared with the 47% for random walk prediction and 25% for random guessing method. Received 29 August 2000     

Beyond Black-Scholes: semimartingales and Lévy processes for option pricing

We consider the problem of option pricing when the underlying asset follows a general semimartingale process. After reviewing the foundations of arbitrage pricing theory for semimartingales and the link with Lévy processes, we introduce a general method to price options in this framework based on Fourier and Wavelet analysis. Received 4 September 2000