共查询到20条相似文献，搜索用时 0 毫秒
1.
利用聚类算法预测股票的价格趋势,通过聚类技术先将某些具备相似特征的上市公司提取出来,这些公司的股票趋势往往具有相饭性,此时再对这些提取出的上市公司财务报表进行具体分析,从而达到准确预测该上市公司股票趋势的目的。通过测试结果得出此方法在股票的预测中具有一定的应用前景。 相似文献
2.
地貌分类指标的钢柔性探索 总被引：1，自引：0，他引：1
争对目前地貌类型基本概念的极度混乱现象,文章提出了地貌分类指标的钢柔性方法。该法把直接影响地貌类型基本概念的指标定为钢性指标,把与地貌类型基本概念不密切的指标定为柔性指标,并在此基础上建立了地貌钢柔性分类系统的参考模式,解决了地貌概念的混乱问题,同时增强了地貌分类的灵活性。该结果对促动地貌的生产利用和科学普及有一定作用。 相似文献
3.
Haixiang Yao;Shenghao Xia;Hao Liu; 《Journal of forecasting》2024,43(6):1770-1794
This paper proposes a cross-section long short-term memory (CS-LSTM) factor model to explore the possibility of estimating expected returns in the Chinese stock market. In contrast to previous machine-learning-based asset pricing models that make predictions directly on equity returns, CS-LSTM estimates are based on predictions of slope terms from Fama–MacBeth cross-section regressions using 16 stock characteristics as factor loadings. In line with previous studies in the context of the Chinese market, we find illiquidity and short-term momentum to be the most important factors in describing asset returns. By using 274 value-weighted portfolios as test assets, we systematically compare the performances of CS-LSTM and three other candidate models. Our CS-LSTM model consistently delivers better performance than the candidate models and beats the market at all different levels of transaction costs. In addition, we observe that assets with smaller cap are favored by the model. By repeating the empirical analysis based on the top 70% of stocks, our CS-LSTM model remains robust and consistently provides significant market-beating performance. Our findings from the CS-LSTM model have practical implications for the future development of the Chinese stock market and other emerging markets. 相似文献
4.
In this paper, an artificial neural network (ANN) was used to predict the injury severity of traffic accidents based on 5973 traffic accident records occurred in Abu Dhabi over a 6‐year period (from 2008 to 2013). For each accident record, 48 different attributes had been collected at the time of the accident. After data preprocessing, the data were reduced to 16 attributes and four injury severity classes. In this study, WEKA (Waikato Environment for Knowledge Analysis) data‐mining software was used to build the ANN classifier. The traffic accident data were used to build two classifiers in two different ways. The whole data set were used for training and validating the first classifier (training set), while 90% of the data were used for training the second classifier and the remaining 10% were used for testing it (testing set). The experimental results revealed that the developed ANN classifiers can predict accident severity with reasonable accuracy. The overall model prediction performance for the training and testing data were 81.6% and 74.6%, respectively. To improve the prediction accuracy of the ANN classifier, traffic accident data were split into three clusters using a k‐means algorithm. The results after clustering revealed significant improvement in the prediction accuracy of the ANN classifier, especially for the training dataset. In this work, and in order to validate the performance of the ANN model, an ordered probit model was also used as a comparative benchmark. The dependent variable (i.e. degree of injury) was transformed from ordinal to numerical (1, 2, 3, 4) for (minor, moderate, sever, death). The R tool was used to perform an ordered probit. For each accident, the ordered probit model showed how likely this accident would result in each class (minor, moderate, severe, death). The accuracy of 59.5% obtained from the ordered probit model was clearly less than the ANN accuracy value of 74.6%. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
5.
近年来,突发性地质灾害的频繁发生,给人们的生命财产造成的损失越来越大,对突发性地质灾害的研究已经成为国际社会关注的热点领域.为了及时总结该领域已有的研究成果,为防灾减灾提供科学依据,本文从对突发性地质灾害的成因、危险性评价、预测预警和防治等方面进行了现状综述,分析讨论了突发性地质灾害及防治存在的问题与进一步研究的方向. 相似文献
6.
Diabetes mellitus is one of the most important public health problems affecting millions of people worldwide. An early and accurate diagnosis of diabetes mellitus has critical importance for the medical treatments of patients. In this study, first, artificial neural network (ANN) and classification and regression tree (CART)-based approaches are proposed for the diagnosis of diabetes. Hybrid ANN-GA and CART-GA approaches are then developed using a genetic algorithm (GA) to improve the classification accuracy of these approaches. Finally, the performances of the developed approaches are evaluated with a Pima Indian diabetes data set. Experimental results show that the developed hybrid CART-GA approach outperforms the ANN, CART, and ANN-GA approaches in terms of classification accuracy, and this approach provides an efficient methodology for diagnosis of diabetes mellitus. 相似文献
7.
Nicholas Apergis 《Journal of forecasting》2017,36(5):557-565
This paper investigates the impact of both asset and macroeconomic forecast errors on inflation forecast errors in the USA by making use of a two‐regime model. The findings document a significant contribution of both types of forecast errors to the explanation of inflation forecast errors, with the pass‐through being stronger when these errors move within the high‐volatility regime. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
8.
High motility of eupyrene sperm of a grasshopper (Omocestus ventralis) was induced by cAMP. Both trypsin and cAMP were necessary for high motility of eupyrene sperm of three other species of grasshoppers. The same was found for apyrene sperm of the silkmoth,Bombyx mori, when they had been wahsed free from seminal plasma. On the other hand, in locusts (Locusta migratoria), in which the yellow gland has high Arg-C endopeptidase activity, sperm motility was induced by trypsin, like that of apyrene sperm of Lepidoptera. Thus in these two orders of Insecta, sperm motility appears to be induced by the same two-step process: the first step by Arg-C endopeptidase, and the second by cAMP. 相似文献
9.
Recent research has suggested that forecast evaluation on the basis of standard statistical loss functions could prefer models which are sub‐optimal when used in a practical setting. This paper explores a number of statistical models for predicting the daily volatility of several key UK financial time series. The out‐of‐sample forecasting performance of various linear and GARCH‐type models of volatility are compared with forecasts derived from a multivariate approach. The forecasts are evaluated using traditional metrics, such as mean squared error, and also by how adequately they perform in a modern risk management setting. We find that the relative accuracies of the various methods are highly sensitive to the measure used to evaluate them. Such results have implications for any econometric time series forecasts which are subsequently employed in financial decision making. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
10.
11.
Advances in methods of structure determination have led to the accumulation of large amounts of protein structural data. Some 500 distinct protein folds have now been characterized, representing one-third of all globular folds that exist. The range of known structural types and the relatively large fraction of the protein universe that has already been sampled have greatly facilitated the discovery of some unifying principles governing protein structure and evolutionary relationships. These include a highly skewed distribution of topological arrangements of secondary-structure elements that favors a few very common connectivities and a highly skewed distribution in the capacity of folds to accommodate unrelated sequences. These and other observations suggest that the number of folds is far fewer than the number of genes, and that the fold universe is dominated by a small number of giant attractors that accommodate large numbers of unrelated sequences. Thus all basic protein folds will likely be determined in the near future, laying the foundation for a comprehensive understanding of the biochemical and cellular functions of whole organisms. 相似文献
12.
黄群藻目分类系统述评及主要分类特征的评价 总被引：1，自引：0，他引：1
黄群藻目Synurales是主要根据光合色素和亚显微结构特征建立的一个目,也是淡水金藻中较大的一个目,包括约160种。该目的植物体为自由运动的单细胞或群体,细胞的表质上覆盖许多硅质的鳞片,以覆瓦状、甲胄状排列或自由附着于表质上,鳞片具刺毛或无,具1条或2条不等长鞭毛。黄群藻目植物区别于其它金藻植物的主要特征为,它们的色素体仅含有叶绿素C1,鞭毛基部平行排列,并且形成硅质鳞片的硅质沉积孢囊与叶绿体外膜相连。自建立至今,该目的分类系统几经变化。本文综述了黄群藻目分类系统的研究进展,并对其主要形态特征的分类价值进行了分析。 相似文献
13.
串珠藻科Batrachospermaceae是淡水红藻中最大的一个科,包括约120种。自建立至今,该科的分类系统几经变化。本文综述了串珠藻科分类系统的研究进展,并对主要形态特征的分类价值进行了分析。 相似文献
14.
Claudio Morana 《Journal of forecasting》2017,36(8):919-935
The paper investigates the determinants of the US dollar/euro within the framework of the asset pricing theory of exchange rate determination, which posits that current exchange rate fluctuations are determined by the entire path of current and future revisions in expectations about fundamentals. In this perspective, we innovate by conditioning on Fama–French and Carhart risk factors, which directly measures changing market expectations about the economic outlook, on new financial condition indexes and macroeconomic variables. The macro‐finance augmented econometric model has a remarkable in‐sample and out‐of‐sample predictive ability, largely outperforming a standard autoregressive specification. We also document a stable relationship between the US dollar/euro Carhart momentum conditional correlation (CCW) and the euro area business cycle. CCW signals a progressive weakening in economic conditions since June 2014, consistent with the scattered recovery from the sovereign debt crisis and the new Greek solvency crisis exploded in late spring/early summer 2015. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
15.
基于SVM的环境减灾卫星HJ-1B影像作物分类识别研究 总被引：1，自引：0，他引：1
环境减灾卫星作为我国自主研制发射的环境与灾害监测预报卫星,要发挥它的作用就是要更好的使用其数据源。支持向量机（SupportVectorMachine,SVM）是一种卓越的分类方法,本文通过SVM方法对环境减灾卫星14J-1B星CCD影像数据进行作物分类识别实验并将结果与最大似然法分类结果进行比较。结果表明：利用SVM方法进行遥感图像分类,精度优于传统的最大似然法分类精度;HJ—1A／1B星CCD数据对于农作物具有较好的指示效果,可应用于作物识别等农业领域。 相似文献
16.
In this paper we assess opinion polls, prediction markets, expert opinion and statistical modelling over a large number of US elections in order to determine which perform better in terms of forecasting outcomes. In line with existing literature, we bias‐correct opinion polls. We consider accuracy, bias and precision over different time horizons before an election, and we conclude that prediction markets appear to provide the most precise forecasts and are similar in terms of bias to opinion polls. We find that our statistical model struggles to provide competitive forecasts, while expert opinion appears to be of value. Finally we note that the forecast horizon matters; whereas prediction market forecasts tend to improve the nearer an election is, opinion polls appear to perform worse, while expert opinion performs consistently throughout. We thus contribute to the growing literature comparing election forecasts of polls and prediction markets. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
17.
Andrew Skabar 《Journal of forecasting》2013,32(5):409-422
A similarity‐based classification model is proposed whereby densities of positive and negative returns in a delay‐embedded input space are estimated from a graphical representation of the data using an eigenvector centrality measure, and subsequently combined under Bayes' theorem to predict the probability of upward/downward movements. Application to directional forecasting of the daily close price of the Dow Jones Industrial Average over a 20‐year out‐of‐sample period yields performance superior to random walk and logistic regression models, and on a par with that of multilayer perceptrons. A feature of the classifier is that it is parameter free, parameters entering the model only via the measure used to determine pairwise similarity between data points. This allows intuitions about the nature of time series to be elegantly integrated into the model. The recursive nature of eigenvector centrality makes it better able to deal with sparsely populated input spaces than conventional approaches based on density estimation. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
18.
Biomedical research, especially pharmaceutical research, has been criticised for engaging in practices that lead to over-estimations of the effectiveness of medical treatments. A central issue concerns the reporting of absolute and relative measures of medical effectiveness. In this paper we critically examine proposals made by Jacob Stegenga to (a) give priority to the reporting of absolute measures over relative measures, and (b) downgrade the measures of effectiveness (effect sizes) of the treatments tested in clinical trials (Stegenga, 2015a). After exposing significant flaws in a central case study used by Stegenga to bolster his first proposal (a), we go on to argue that neither of these proposals is defensible (a or b). We defend the practice, in line with the New England Journal of Medicine, of reporting both absolute and relative measures whenever feasible. 相似文献
19.
This paper proposes a new mixed‐frequency approach to predict stock return volatilities out‐of‐sample. Based on the strategy of momentum of predictability (MoP), our mixed‐frequency approach has a model switching mechanism that switches between generalized autoregressive conditional heteroskedasticity (GARCH)‐class models that only use low‐frequency data and heterogeneous autoregressive models of realized volatility (HAR‐RV)‐type that only use high‐frequency data. The MoP model simply selects a forecast with relatively good past performance between the GARCH‐class and HAR‐RV‐type forecasts. The model confidence set (MCS) test shows that our MoP strategy significantly outperforms the competing models, which is robust to various settings. The MoP test shows that a relatively good recent past forecasting performance of the GARCH‐class or HAR‐RV‐type model is significantly associated with a relatively good current performance, supporting the success of the MoP model. 相似文献
20.
This study examines whether the evaluation of a bankruptcy prediction model should take into account the total cost of misclassification. For this purpose, we introduce and apply a validity measure in credit scoring that is based on the total cost of misclassification. Specifically, we use comprehensive data from the annual financial statements of a sample of German companies and analyze the total cost of misclassification by comparing a generalized linear model and a generalized additive model with regard to their ability to predict a company's probability of default. On the basis of these data, the validity measure we introduce shows that, compared to generalized linear models, generalized additive models can reduce substantially the extent of misclassification and the total cost that this entails. The validity measure we introduce is informative and justifies the argument that generalized additive models should be preferred, although such models are more complex than generalized linear models. We conclude that to balance a model's validity and complexity, it is necessary to take into account the total cost of misclassification. 相似文献