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Статті в журналах з теми "Price indexes – Data processing"
Cottle, David, and Euan Fleming. "Do price premiums for wool characteristics vary for different end products, processing routes and fibre diameter categories?" Animal Production Science 56, no. 12 (2016): 2146. http://dx.doi.org/10.1071/an14744.
Повний текст джерелаMendoza Urdiales, Román Alejandro, Andrés García-Medina, and José Antonio Nuñez Mora. "Measuring information flux between social media and stock prices with Transfer Entropy." PLOS ONE 16, no. 9 (September 23, 2021): e0257686. http://dx.doi.org/10.1371/journal.pone.0257686.
Повний текст джерелаAntoniuk, Olena, Natalya Kuzyk, Iryna Zhurakovska, Roman Sydorenko, and Liudmyla Sakhno. "The role of «BIG FOUR» auditing firms in the public procurement market in Ukraine." Independent Journal of Management & Production 11, no. 9 (November 1, 2020): 2483. http://dx.doi.org/10.14807/ijmp.v11i9.1432.
Повний текст джерелаTarrío-Saavedra, Javier, Elena Orois, and Salvador Naya. "Estudio métrico sobre la actividad investigadora usando el software libre R: el caso del sistema universitario gallego." Investigación Bibliotecológica: archivonomía, bibliotecología e información, sp1 (January 19, 2018): 221. http://dx.doi.org/10.22201/iibi.24488321xe.2017.nesp1.57891.
Повний текст джерелаKőműves, Zsolt, and Viktória Horváthné Petrás. "A sertéshústermelést és -fogyasztást befolyásoló tényezők." Élelmiszer, Táplálkozás és Marketing 13, no. 1 (February 27, 2019): 3–9. http://dx.doi.org/10.33567/etm.2253.
Повний текст джерелаSaad, Ammar, Ruitao Zhang, and Ying Xia. "The Policy Analysis Matrix (PAM): Comparative Advantage of China’s Wheat Crop Production 2017." Journal of Agricultural Science 11, no. 17 (October 15, 2019): 150. http://dx.doi.org/10.5539/jas.v11n17p150.
Повний текст джерелаOleinik, A. N. "Uses of content analysis in economic sciences: An overview of the current situation and prospects." Voprosy Ekonomiki, no. 4 (April 8, 2021): 79–95. http://dx.doi.org/10.32609/0042-8736-2021-4-79-95.
Повний текст джерелаZulqarnain, Muhammad, Rozaida Ghazali, Muhammad Ghulam Ghouse, Yana Mazwin Mohmad Hassim, and Irfan Javid. "Predicting Financial Prices of Stock Market using Recurrent Convolutional Neural Networks." International Journal of Intelligent Systems and Applications 12, no. 6 (December 8, 2020): 21–32. http://dx.doi.org/10.5815/ijisa.2020.06.02.
Повний текст джерелаZhen, Chen, Eric A. Finkelstein, Shawn A. Karns, Ephraim S. Leibtag, and Chenhua Zhang. "Scanner Data‐Based Panel Price Indexes." American Journal of Agricultural Economics 101, no. 1 (June 18, 2018): 311–29. http://dx.doi.org/10.1093/ajae/aay032.
Повний текст джерелаBourassa, Steven C., Eva Cantoni, and Martin Hoesli. "Robust hedonic price indexes." International Journal of Housing Markets and Analysis 9, no. 1 (March 7, 2016): 47–65. http://dx.doi.org/10.1108/ijhma-11-2014-0050.
Повний текст джерелаДисертації з теми "Price indexes – Data processing"
Hon, Wing-kai. "On the construction and application of compressed text indexes." Click to view the E-thesis via HKUTO, 2004. http://sunzi.lib.hku.hk/hkuto/record/B31059739.
Повний текст джерелаHon, Wing-kai, and 韓永楷. "On the construction and application of compressed text indexes." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B31059739.
Повний текст джерелаHu, Haixin. "Sample selection and spatial models of housing price indexes and a disequilibrium analysis of the U.S. gasoline market using panel data /." Full text available from ProQuest UM Digital Dissertations, 2008. http://0-proquest.umi.com.umiss.lib.olemiss.edu/pqdweb?index=0&did=1850404651&SrchMode=1&sid=2&Fmt=2&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1277474405&clientId=22256.
Повний текст джерелаTypescript. Vita. "August 2008." Committee chair : Walter Mayer Includes bibliographical references (leaves 82-83). Also available online via ProQuest to authorized users.
Heinze, Christian [Verfasser], Harry [Akademischer Betreuer] Haupt, and Dietmar [Akademischer Betreuer] Bauer. "A framework for spatiotemporal prediction with small and heterogeneous data - and an application to consumer price indexes - / Christian Heinze ; Harry Haupt, Dietmar Bauer." Bielefeld : Universitätsbibliothek Bielefeld, 2016. http://d-nb.info/1119981298/34.
Повний текст джерелаSeshadri, Mukund. "Comprehensibility, overfitting and co-evolution in genetic programming for technical trading rules." Link to electronic thesis, 2003. http://www.wpi.edu/Pubs/ETD/Available/etd-0430103-121518.
Повний текст джерелаKeywords: comprehensiblity; technical analysis; genetic programming; overfitting; cooperative coevolution. Includes bibliographical references (p. 82-87).
Brunel, Guilhem. "Caractérisation automatique d’organisations cellulaires dans des mosaïques d’images microscopiques de bois." Thesis, Montpellier 2, 2014. http://www.theses.fr/2014MON20225/document.
Повний текст джерелаThis study focuses on biological numeric picture processes. It aims to define and implement new automated measurements at large scale analysis. Moreover, this thesis addresses: The incidence of the proposed methodology on the results reliability measurements accuracy definition and analysis proposed approaches reproducibility limits when applied to plant biology.This work is part of cells organization study, and aims to automatically identify and analyze the cell lines in microscopic mosaic wood slice pictures. Indeed, the study of biological tendencies among the cells lines is necessary to understand the cell migration and organization. Such a study can only be realized from a huge zone of observation of wood plane. To this end, this work proposes:- a new protocol of preparation (slices of sanded wood) and of digitizing of samples, in order to acquire the entire zone of observation without bias,- a novel processing chain that permit the automated cell lines extraction in numeric mosaic pictures,- reliability indexes for each measurement for further efficient statistical analysis.The methods developed during this thesis enable to acquire and treat rapidly an important volume of information. Those data define the basis of numerous investigations, such as tree architectural analysis cell lines following and/or detection of biological perturbations. And it finally helps the analysis of the variability intra- or inter- trees, in order to better understand the tree endogenous growth
Colliri, Tiago Santos. "Avaliação de preços de ações: proposta de um índice baseado nos preços históricos ponderados pelo volume, por meio do uso de modelagem computacional." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/100/100132/tde-07072013-015903/.
Повний текст джерелаThe importance of considering the volumes to analyze stock prices movements can be considered as a well-accepted practice in the financial area. However, when we look at the scientific production in this field, we still cannot find a unified model that includes volume and price variations for stock prices assessment purposes. In this paper we present a computer model that could fulfill this gap, proposing a new index to evaluate stock prices based on their historical prices and volumes traded. The aim of the model is to estimate the current proportions of the total volume of shares available in the market from a stock distributed according with their respective prices traded in the past. In order to do so, we made use of dynamic financial modeling and applied it to real financial data from the Sao Paulo Stock Exchange (Bovespa) and also to simulated data which was generated trough an order book model. The value of our index varies based on the difference between the current proportion of shares traded in the past for a price above the current price of the stock and its respective counterpart, which would be the proportion of shares traded in the past for a price below the current price of the stock. Besides the model can be considered mathematically very simple, it was able to improve significantly the financial performance of agents operating with real market data and with simulated data, which contributes to demonstrate its rationale and its applicability. Based on the results obtained, and also on the very intuitive logic of our model, we believe that the index proposed here can be very useful to help investors on the activity of determining ideal price ranges for buying and selling stocks in the financial market.
Ivancic, Lorraine Economics Australian School of Business UNSW. "Scanner data and the construction of price indices." 2007. http://handle.unsw.edu.au/1959.4/40782.
Повний текст джерела"Price discovery of stock index with informationally-linked markets using artificial neural network." 1999. http://library.cuhk.edu.hk/record=b5889930.
Повний текст джерелаThesis (M.Phil.)--Chinese University of Hong Kong, 1999.
Includes bibliographical references (leaves 83-87).
Abstracts in English and Chinese.
Chapter I. --- INTRODUCTION --- p.1
Chapter II. --- LITERATURE REVIEW --- p.5
Chapter 2.1 --- The Importance of Stock Index and Index Futures --- p.6
Chapter 2.2 --- Importance of Index Forecasting --- p.6
Chapter 2.3 --- Reasons for the Lead-Lag Relationship between Stock and Futures Markets --- p.9
Chapter 2.4 --- Importance of the lead-lag relationship --- p.10
Chapter 2.5 --- Some Empirical Findings of the Lead-Lag Relationship --- p.10
Chapter 2.6 --- New Approach to Financial Forecasting - Artificial Neural Network --- p.12
Chapter 2.7 --- Artificial Neural Network Architecture --- p.14
Chapter 2.8 --- Evidence on the Employment of ANN in Financial Analysis --- p.20
Chapter 2.9 --- Hong Kong Securities and Futures Markets --- p.25
Chapter III. --- GENERAL GUIDELINE IN DESIGNING AN ARTIFICIAL NEURAL NETWORK FORECASTING MODEL --- p.28
Chapter 3.1 --- Procedure for using Artificial Neural Network --- p.29
Chapter IV. --- METHODOLOGY --- p.37
Chapter 4.1 --- ADF Test for Unit Root --- p.38
Chapter 4.2 --- "Error Correction Model, Error Correction Model with Short- term Dynamics, and ANN Models for Comparisons" --- p.38
Chapter 4.3 --- Comparison Criteria of Different Models --- p.39
Chapter 4.4 --- Data Analysis --- p.39
Chapter 4.5 --- Data Manipulations --- p.41
Chapter V. --- RESULTS --- p.42
Chapter 5.1 --- The Resulting Models --- p.42
Chapter 5.2 --- The Prediction Power among the Models --- p.45
Chapter 5.3 --- ANN Model of Input Variable Selection Using Contribution Factor --- p.46
Chapter VI. --- CAUSALITY ANALYSIS --- p.54
Chapter 6.1 --- Granger Casuality Analysis --- p.55
Chapter 6.2 --- Results Interpretation --- p.56
Chapter VII --- CONSISTENCE VALIDATION --- p.61
Chapter VIII --- ARTIFICIAL NEURAL NETWORK TRADING SYSTEM --- p.67
Chapter 7.1 --- Trading System Architecture --- p.68
Chapter 7.2 --- Simulation Runs using the Trading System --- p.77
Chapter XI. --- CONCLUSIONS AND FUTURE WORKS --- p.79
"Discovering patterns on financial data streams." Thesis, 2010. http://library.cuhk.edu.hk/record=b6075026.
Повний текст джерелаWe start from investigating the co-movement relationship of multiple time series. We propose techniques to study two aspects of this problem. First, we propose a co-movement model for constructing financial portfolio by analyzing and mining the co-movement patterns among two time series. Second, we presents an efficient streaming algorithm to discover leaders from multiple time series stream. Both of the algorithms are evaluated using real time series indices data and the result proves that co-movement patterns and detected leaders are promising and can support various applications including portfolio management, high frequency trading and risk management.
With the increasing amount of data in financial market, there are two types of data streams attracting a lot of research and studies, time series index stream and related news stream. In this thesis, we focus on discovering patterns from these data streams and try to answer the following challenging questions, (I) given two co-evolving time series indices, what is the co-movement dependency between them. (II) given a set of evolving time series, could we detect some leaders from them whose rise or fall impacts the behavior of many other time series? (III) could we integrate the news stream information into stock price prediction? (IV) could we integrate the news stream information into stock risk analysis? and (V) could we detect what are those events that trigger time series index movement. For each of the question, we design algorithms and address three technique issues (I) how to detect promising patterns from the noisy financial data; (II) how to update the old patterns when new data arrives in high frequency; (III) how to use the pattern to support the financial applications.
Wu, Di.
Adviser: Jeffrey Xu Pu.
Source: Dissertation Abstracts International, Volume: 73-01, Section: B, page: .
Thesis (Ph.D.)--Chinese University of Hong Kong, 2010.
Includes bibliographical references (leaves 124-131).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstract also in Chinese.
Книги з теми "Price indexes – Data processing"
missing], [name. Scanner data and price indexes. Chicago, IL: University of Chicago Press, 2002.
Знайти повний текст джерелаMahy, E. PRICE S: A debrief report. Manchester: NCC, 1985.
Знайти повний текст джерелаKrueger, Alan B. Assessing bias in the Consumer Price Index from survey data. Cambridge, MA: National Bureau of Economic Research, 1998.
Знайти повний текст джерелаShiryōkan, Kokubungaku Kenkyū. Renga shiryō no konpyūta shori no kenkyū: Tsuketari renga sakuhin mokuroku honkoku ichiran. Tōkyō: Meiji Shoin, 1985.
Знайти повний текст джерелаInstitute, SAS, ed. The complete guide to SAS indexes. Cary, N.C: SAS Institute, 2006.
Знайти повний текст джерелаBerndt, Ernst R. On the accuracy of producer price indexes for pharmaceutical preparations: An audit based on detailed firm-specific data. Cambridge, MA: National Bureau of Economic Research, 1990.
Знайти повний текст джерелаLixiang, Shen, and Cao Lijuan, eds. Ordinary shares, exotic methods: Financial forecasting using data mining techniques. River Edge, N.J: World Scientific, 2003.
Знайти повний текст джерелаHurd, Julie M. Online searching in religion indexes. Evanston, Ill: American Theological Library Association, 1989.
Знайти повний текст джерелаHoll, Alfred. Rückläufiges Wörterbuch zur alt- und neugriechischen Verbalmorphologie: Aufbereitung mit Datenanalyseverfahren der Informatik (Data Mining). Regensburg: S. Roderer, 2006.
Знайти повний текст джерелаEvgenii, Vityaev, ed. Data mining in finance: Advances in relational and hybrid methods. Boston: Kluwer Academic, 2000.
Знайти повний текст джерелаЧастини книг з теми "Price indexes – Data processing"
Färe, Rolf, Shawna Grosskopf, and Pontus Roos. "Price Indexes for Nonmarketed Goods." In Data Envelopment Analysis in the Service Sector, 121–32. Wiesbaden: Deutscher Universitätsverlag, 1999. http://dx.doi.org/10.1007/978-3-663-08343-6_7.
Повний текст джерелаYe, Xiaoping, Huan Guo, Xiongxiong Zhu, and Yidong Ja. "Indexes for Moving-Objects Data." In Temporal Information Processing Technology and Its Application, 175–202. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14959-7_9.
Повний текст джерелаDemiriz, Ayhan, Ahmet Cihan, and Ufuk Kula. "Analyzing Price Data to Determine Positive and Negative Product Associations." In Neural Information Processing, 846–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10677-4_96.
Повний текст джерелаLovell, C. A. Knox, and Kimberly D. Zieschang. "The Problem of New and Disappearing Commodities in the Construction of Price Indexes." In Data Envelopment Analysis: Theory, Methodology, and Applications, 353–67. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0637-5_18.
Повний текст джерелаde Haan, Jan, Bert M. Balk, and Carsten Boldsen Hansen. "Retrospective Approximations of Superlative Price Indexes for Years Where Expenditure Data Is Unavailable." In Contributions to Statistics, 25–42. Heidelberg: Physica-Verlag HD, 2009. http://dx.doi.org/10.1007/978-3-7908-2140-6_2.
Повний текст джерелаDesbrosses, Nathalie, and Jacques Girod. "Energy Quantity and Price Data: Collection, Processing and Methods of Analysis." In The Econometrics of Energy Systems, 1–26. London: Palgrave Macmillan UK, 2007. http://dx.doi.org/10.1057/9780230626317_1.
Повний текст джерелаWidiputra, Harya, Russel Pears, and Nikola Kasabov. "Personalised Modelling for Multiple Time-Series Data Prediction: A Preliminary Investigation in Asia Pacific Stock Market Indexes Movement." In Advances in Neuro-Information Processing, 1237–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02490-0_150.
Повний текст джерелаRomanowski, Andrzej, and Michał Skuza. "Towards Predicting Stock Price Moves with Aid of Sentiment Analysis of Twitter Social Network Data and Big Data Processing Environment." In Advances in Business ICT: New Ideas from Ongoing Research, 105–23. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47208-9_7.
Повний текст джерелаKim, Yoosin, Michelle Jeong, and Seung Ryul Jeong. "Using Big Data Opinion Mining to Predict Rises and Falls in the Stock Price Index." In Advances in Business Information Systems and Analytics, 30–42. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-7272-7.ch003.
Повний текст джерелаBellatreche, Ladjel. "Bitmap Join Indexes vs. Data Partitioning." In Database Technologies, 2292–300. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-058-5.ch140.
Повний текст джерелаТези доповідей конференцій з теми "Price indexes – Data processing"
Hill, Robert, and Michael Scholz. "Can Geospatial Data Improve House Price Indexes? A Hedonic Imputation Approach with Splines." In 25th Annual European Real Estate Society Conference. European Real Estate Society, 2016. http://dx.doi.org/10.15396/eres2016_146.
Повний текст джерелаKarcıoğlu, Reşat, Muhammet Özcan, and Ensar Ağırman. "The Relationship of Petroleum Price and BIST Sector Indexes." In International Conference on Eurasian Economies. Eurasian Economists Association, 2017. http://dx.doi.org/10.36880/c08.01878.
Повний текст джерелаSinha, R. R., S. Mitra, and M. Winslett. "Bitmap indexes for large scientific data sets: a case study." In Proceedings 20th IEEE International Parallel & Distributed Processing Symposium. IEEE, 2006. http://dx.doi.org/10.1109/ipdps.2006.1639304.
Повний текст джерелаLam, K. P., and P. Y. Mok. "Stock price prediction using intraday and AHIPMI data." In 9th International Conference on Neural Information Processing. IEEE, 2002. http://dx.doi.org/10.1109/iconip.2002.1201876.
Повний текст джерелаKamaruddin, Saadi Bin Ahmad, Nor Azura Md Ghani, and Norazan Mohamed Ramli. "Forecasting techniques suitable to estimate unitary charges price indexes of PFI data: Context of northern region Peninsular Malaysia." In 2013 IEEE Business Engineering and Industrial Applications Colloquium (BEIAC). IEEE, 2013. http://dx.doi.org/10.1109/beiac.2013.6560160.
Повний текст джерелаKim, Younghoon, Kyoung-Gu Woo, Hyoungmin Park, and Kyuseok Shim. "Efficient processing of substring match queries with inverted q-gram indexes." In 2010 IEEE 26th International Conference on Data Engineering (ICDE 2010). IEEE, 2010. http://dx.doi.org/10.1109/icde.2010.5447866.
Повний текст джерелаAhmad Kamaruddin, Saadi Bin, Nor Azura Md Ghani, and Norazan Mohamed Ramli. "Determining the best forecasting method to estimate unitary charges price indexes of PFI data in central region Peninsular Malaysia." In PROCEEDINGS OF THE 20TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES: Research in Mathematical Sciences: A Catalyst for Creativity and Innovation. AIP, 2013. http://dx.doi.org/10.1063/1.4801271.
Повний текст джерелаNwulu, Nnamdi I. "A decision trees approach to oil price prediction." In 2017 International Artificial Intelligence and Data Processing Symposium (IDAP). IEEE, 2017. http://dx.doi.org/10.1109/idap.2017.8090313.
Повний текст джерелаTang, Yajuan, Shuang Qiu, and Pengcheng Gui. "Predicting Housing Price Based on Ensemble Learning Algorithm." In 2018 International Conference on Artificial Intelligence and Data Processing (IDAP). IEEE, 2018. http://dx.doi.org/10.1109/idap.2018.8620781.
Повний текст джерелаPaul, Debdeep, and Wen-De Zhong. "Price and renewable aware geographical load balancing technique for data centres." In 2013 9th International Conference on Information, Communications & Signal Processing (ICICS). IEEE, 2013. http://dx.doi.org/10.1109/icics.2013.6782783.
Повний текст джерелаЗвіти організацій з теми "Price indexes – Data processing"
Berndt, Ernst, Zvi Griliches, and Joshua Rosett. On the Accuracy of Producer Price Indexes for Pharmaceutical Preparations: An Audit Based on Detailed Firm-Specific Data. Cambridge, MA: National Bureau of Economic Research, October 1990. http://dx.doi.org/10.3386/w3490.
Повний текст джерела