The application of fuzzy logic model in the prediction of financial time series is investigated.
文章研究了模糊逻辑模型在金融预测领域中的应用。
Based on above analysis, this paper integrates the study of data mining and financial time series.
基于上述原因，本文将数据挖掘和金融时间序列结合在一起进行研究。
The non-linear theory has been playing an important role in describing volatility of financial time series.
非线性理论在刻画金融时间序列的波动方面有着非常重要的作用。
The analysis and modeling of the financial time series is a very important study realm in financial metrology.
金融时间序列的分析与建模是金融计量学的一个很重要的研究领域。
Stock market price prediction is regarded as a challenging task of the financial time series prediction process.
股票市场价格预测一直以来都被认为是金融时序预测领域的一项具有挑战性的工作。
The change-point analysis in financial time series has been regarded as one of the core areas of research in statistics.
金融时间序列模型的变点分析是一类重要的统计问题，它引起众多学者的关注。
The proposed method is applied to unsteady financial time series symbolization. Experimental result shows that the method is effective.
方法用于对非平稳金融时间序列进行了符号化转换，实验结果表明该方法是有效的。
A new probabilistic function for studying the multi-fractal features on the volatility of variance of financial time series is proposed.
提出了一种新的概率函数计算方法，用于研究金融时间序列在方差波动方面的多重分形特征。
But nonlinear problem in financial data and nonlinear economic metric model in financial time series is an all new research topic in this realm.
而金融数据中的非线性问题和金融时间序列分析中的非线性经济计量模型又是这个领域中全新的研究课题。
A new methodology based on state space reconstruction and divergence calculation techniques has been developed for financial time series forecasting.
一种新的基于相空间重构和偏差计算技术的方法已被应用于金融市场预测。
Therefore, how to describe the dynamic behavior of the financial time series' fluctuation well is always a hot research point in Financial Econometrics.
因此，如何有效地刻画金融时间序列波动的动态行为一直是金融计量学研究的热点问题。
Numerical test results show that SVR has good ability of modeling nonstationary financial time series and good generalization under small data set available.
数值实验表明，SVR方法对非平稳的金融时间序列具有良好的建模和泛化能力。
The volatility is not only a universal phenomenon existing in the financial time series, but also a core research question to describing the financial market.
波动性不仅普遍存在于金融时间序列之中，而且也是金融市场研究中的一个核心问题。
At present, GARCH type models have been employed to model these high frequency financial time series due to their ability to capture the dynamic characteristics.
近年来GARCH模型被广泛地用于对变动频率很高的金融时间序列建模，它能较好地抓住此类时间序列的动态特征。
Financial time series has high randomicity and nonlinearity. Neural network is quite suitable in the process of financial time series data for its good ability of nonlinear mapping and generalization.
金融时间序列具有很强的随机性和非线性性，而神经网络具有良好的非线性映射能力及自适应、自学习和良好的泛化能力，因此非常适合处理金融时间序列这样的数据。
Regressions incorporating the economic/financial variables as well as a linear spline in time variable are set up for testing the externality series.
回归纳入经济/金融变量以及线性样条在时间变量的设置进行测试的外部系列。
Because these models can reflect the feature of the financial market well, they have been widely applied in the time series analysis on financial data.
由于该模型被认为是最集中反映了金融市场数据方差变化的特点而被广泛应用于金融数据时间序列分析中。
Data mining are used to analyze the foreign exchange rate time series and acquire the correct, implicated and hidden information, which has practical significance in the financial field.
利用数据挖掘技术分析外汇汇率时间序列，从时间序列中获得正确的、隐含的、潜在的信息对于金融领域研究具有重要的现实意义。
The existing methods of similarity search are not suitable for high frequency financial data, which is a kind of non-interval time series.
金融高频数据是一种不等间隔的时间序列，现有的相似性查找技术对高频数据的处理效果不佳。
The time series approach involves the measurement of customer and employee satisfaction and financial performance measures simultaneously and at equal intervals.
时间序列方法涉及同时测量客户满意度、员工满意度及财务绩效及等时间间距的测量。
Many economists keep on working hard, making a great effort to try to find a time series model which can capture most of these characteristics of financial data.
许多经济学家们不懈努力，孜孜以求，试图找到一个能够全面地刻划金融数据这些特性的时间序列模型。
Finally, I predict financial risk situation for the next two years in Gansu province by use of ar autoregressive time series model.
最后，运用AR自回归时间序列模型对未来两年甘肃省金融风险状况进行预测。
In the financial system research, analyze the correlation relations between the multi-dimensional time series frequently, like short-term information, long-term balanced relations.
在金融系统研究中，经常分析多维时间序列之间的相关关系，如短期信息、长期均衡关系。
High frequency time series is referred to financial data which is sampled with interval of one hour, one minute even one second.
高频时间序列通常是指以每小时、每分钟甚至每秒为频率所采集的金融类数据；
Linking financial performance to customer and employee satisfaction results can involve two types of research design: time series and cross sectional analysis.
将客户和员工满意结果的与绩效挂钩涉及两种类型的研究设计：时间序列和剖面分析。
The nation will suffer great financial loss since China now is in the midst of a TV series boom in an echo of its economic prosperity; the people will be confused as to how to kill their spare time.
中国的电视剧产业经济非常繁荣，如果没有了电视剧，中国的经济将会遭受沉重打击：人们将会不知道如何消磨闲暇时光。
The nation will suffer great financial loss since China now is in the midst of a TV series boom in an echo of its economic prosperity; the people will be confused as to how to kill their spare time.
中国的电视剧产业经济非常繁荣，如果没有了电视剧，中国的经济将会遭受沉重打击：人们将会不知道如何消磨闲暇时光。
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