Academic literature on the topic 'Price clustering'

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Journal articles on the topic "Price clustering"

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Wang, Qiming. "Evolution of integer price clustering of IPOs in the aftermarket." Nankai Business Review International 5, no. 4 (2014): 365–81. http://dx.doi.org/10.1108/nbri-01-2014-0008.

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Purpose – The purpose of this paper is to, using a large sample of NASDAQ initial public offerings (IPOs), examine the evolution of integer price clustering of IPOs in the aftermarket trading. Design/methodology/approach – Consistent with Harris’s (1991) costly negotiation hypothesis, clustering on integer prices is a positive function of price level and various stock valuation uncertainty proxies, and it is a negative function of trading activities for IPOs and seasoned stocks. Findings – It was found that, after controlling for price level, daily return volatility, number of trades, trading
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Wafula, Lugongo Maurice, and Dr Sifunjo E. Kisaka. "AN EMPIRICAL STUDY OF PRICE CLUSTERING ON THE NAIROBI SECURITIES EXCHANGE." International Journal of Finance and Accounting 2, no. 2 (2017): 23. http://dx.doi.org/10.47604/ijfa.295.

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Purpose: The purpose of this study was to empirically investigate price clustering phenomenon on the Nairobi Securities Exchange for the period 2009 to 2013.Materials and methods: The study used secondary sources of data obtained from the Nairobi Securities exchange. The study revealed that there has been a preference by investors for stock whose prices end with the digit 5 and this accounted for 67.88 percent of all the stocks examined and was followed by stocks whose prices ended with the digit 0 which accounted for 4.55 percent. In order to establish the determinants of this observed behavi
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Baig, Ahmed, Benjamin M. Blau, and Jie Hao. "Accounting Information Quality and the Clustering of Stock Prices." American Business Review 23, no. 2 (2020): 182–210. http://dx.doi.org/10.37625/abr.23.2.182-210.

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The foundation of economic theory is based on the premise that prices will converge to their equilibrium value. However, prior research has documented that stock prices cluster on round pricing increments. In this study, we develop and test the hypothesis that audit quality and the management of earnings—both of which affects the information environment of the firm—influence the degree of price clustering. Results show that firms with Big 4 auditors have less clustering in their stock prices while firms with higher abnormal audit fees, more discretionary accruals, and firms that tend to manipu
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Chen, Tao. "Price Clustering and Price Barriers: International Evidence." Nang Yan Business Journal 3, no. 1 (2014): 1–16. http://dx.doi.org/10.1515/nybj-2015-0001.

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Abstract In this paper, I try to complement the existing literature by empirically examining the effect of price clustering and price barriers based on the international stock market. Evidence suggests that a strong effect of clustering and barriers is observed on last digit 0. Such effect is not robust and persistent on last digit 5. In addition, the cross-country analysis shows that price clustering and barriers become intensified in countries with a more transparent and open environment.
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Urquhart, Andrew. "Price clustering in Bitcoin." Economics Letters 159 (October 2017): 145–48. http://dx.doi.org/10.1016/j.econlet.2017.07.035.

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Baig, Ahmed S., Omair Haroon, and Nasim Sabah. "Price Clustering After the Introduction of Bitcoin Futures." Applied Finance Letters 9 (April 23, 2020): 36–42. http://dx.doi.org/10.24135/afl.v9i0.200.

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Economic theory suggests that introduction of derivative contracts can improve the informational efficiency of the underlying asset prices (Danthine, 1978). In this study, we examine the impact of the introduction of Bitcoin futures on price clustering in Bitcoin. Our findings suggest that price clustering in Bitcoin meaningfully decreases post the introduction of its futures contracts.
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Blau, Benjamin M., and Todd G. Griffith. "Price clustering and the stability of stock prices." Journal of Business Research 69, no. 10 (2016): 3933–42. http://dx.doi.org/10.1016/j.jbusres.2016.06.008.

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Mola, Simona, and Tim Loughran. "Discounting and Clustering in Seasoned Equity Offering Prices." Journal of Financial and Quantitative Analysis 39, no. 1 (2004): 1–23. http://dx.doi.org/10.1017/s0022109000003860.

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AbstractAn analysis of 4,814 SEOs during 1986–1999 indicates that the average offering ofnew shares is priced at a discount of 3% from the closing price on the day before the issue. Discounts have risen steadily over time, sharply increasing the indirect costs of issuing seasoned equity. There is evidence of increased clustering of offer prices at integers, and of greater importance in the analyst coverage provided by underwriters. Adjusting for other factors, we find that issues with integer offer prices, and underwriters with highly regarded analysts, are increasingly associated with larger
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van Kralingen, Marc, Diego Garlaschelli, Karolina Scholtus, and Iman van Lelyveld. "Crowded Trades, Market Clustering, and Price Instability." Entropy 23, no. 3 (2021): 336. http://dx.doi.org/10.3390/e23030336.

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Crowded trades by similarly trading peers influence the dynamics of asset prices, possibly creating systemic risk. We propose a market clustering measure using granular trading data. For each stock, the clustering measure captures the degree of trading overlap among any two investors in that stock, based on a comparison with the expected crowding in a null model where trades are maximally random while still respecting the empirical heterogeneity of both stocks and investors. We investigate the effect of crowded trades on stock price stability and present evidence that market clustering has a c
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Harris, Lawrence. "Stock Price Clustering and Discreteness." Review of Financial Studies 4, no. 3 (1991): 389–415. http://dx.doi.org/10.1093/rfs/4.3.389.

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Dissertations / Theses on the topic "Price clustering"

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Lallouache, Mehdi. "Clustering in foreign exchange markets : price, trades and traders." Thesis, Châtenay-Malabry, Ecole centrale de Paris, 2015. http://www.theses.fr/2015ECAP0040/document.

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En utilisant des données haute-fréquence inédites, cette thèse étudie trois types de regroupements (“clusters”) présents dans le marché des changes: la concentration d'ordres sur certains prix, la concentration des transactions dans le temps et l'existence de groupes d'investisseurs prenant les mêmes décisions. Nous commençons par étudier les propriétés statistiques du carnet d'ordres EBS pour les paires de devises EUR/USD et USD/JPY et l'impact d'une réduction de la taille du tick sur sa dynamique. Une grande part des ordres limites est encore placée sur les anciens prix autorisés, entraînant
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Verousis, Thanos. "Price discreteness and clustering in ultra high frequency equity and options data." Thesis, Aberystwyth University, 2009. http://hdl.handle.net/2160/63fefd3e-0d27-4f50-b1cb-490d1d063dd2.

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There is only sparse evidence on the implications of price discreteness in empirical studies using high frequency data. This thesis deals with the issue of discreteness in irregularly spaced data, and its theme is the investigation of two important aspects of discreteness. In particular, the compass rose pattern and price clustering in the individual equity options market are primarily studied. Also, price clustering is covered in the Initial Public Offerings (IPOs) primary market and its evolution in the secondary market is documented. The first contribution of the thesis is the design of a n
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Louw, Jan Paul. "Evidence of volatility clustering on the FTSE/JSE top 40 index." Thesis, Stellenbosch : Stellenbosch University, 2008. http://hdl.handle.net/10019.1/5039.

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Thesis (MBA (Business Management))--Stellenbosch University, 2008.<br>ENGLISH ABSTRACT: This research report investigated whether evidence of volatility clustering exists on the FTSE/JSE Top 40 Index. The presence of volatility clustering has practical implications relating to market decisions as well as the accurate measurement and reliable forecasting of volatility. This research report was conducted as an in-depth analysis of volatility, measured over five different return interval sizes covering the sample in non-overlapping periods. Each of the return interval sizes' volatility were analy
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Huo, Shiyin. "Detecting Self-Correlation of Nonlinear, Lognormal, Time-Series Data via DBSCAN Clustering Method, Using Stock Price Data as Example." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1321989426.

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Karanfil, Salih. "Obtaining the membership function by using the neural network in Istanbul stock exchange to find the relation between the low and closing prices." Pontificia Universidad Católica del Perú, 2014. http://repositorio.pucp.edu.pe/index/handle/123456789/96007.

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Kantanantha, Nantachai. "Crop decision planning under yield and price uncertainties." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/24676.

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Thesis (Ph.D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2007.<br>Committee Co-Chair: Griffin, Paul; Committee Co-Chair: Serban, Nicoleta; Committee Member: Liang, Steven; Committee Member: Sharp, Gunter; Committee Member: Tsui, Kwok-Leung
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Zhai, Yuzheng. "Improving scalability and accuracy of text mining in grid environment." Connect to thesis, 2009. http://repository.unimelb.edu.au/10187/5927.

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The advance in technologies such as massive storage devices and high speed internet has led to an enormous increase in the volume of available documents in electronic form. These documents represent information in a complex and rich manner that cannot be analysed using conventional statistical data mining methods. Consequently, text mining is developed as a growing new technology for discovering knowledge from textual data and managing textual information. Processing and analysing textual information can potentially obtain valuable and important information, yet these tasks also requires enorm
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Cabral, Lucidio dos Anjos Formiga. "Algoritmos exatos para o problema de edição de p-Clusters." Universidade Federal da Paraíba, 2015. http://tede.biblioteca.ufpb.br:8080/handle/tede/7870.

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Submitted by Viviane Lima da Cunha (viviane@biblioteca.ufpb.br) on 2016-02-17T11:41:50Z No. of bitstreams: 1 arquivototal.pdf: 1276201 bytes, checksum: 9dd8fad80c483276a40101ee6a782d5b (MD5)<br>Made available in DSpace on 2016-02-17T11:41:50Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 1276201 bytes, checksum: 9dd8fad80c483276a40101ee6a782d5b (MD5) Previous issue date: 2015-07-21<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES<br>This work deals with the p-Cluster Editing Problem (p-CEP), which consists in performing a minimum number of editions (additions or re
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Sutharzan, Sreeskandarajan. "CLUSTERING AND VISUALIZATION OF GENOMIC DATA." Miami University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=miami1563973517163859.

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Bubeck, Sébastien. "JEUX DE BANDITS ET FONDATIONS DU CLUSTERING." Phd thesis, Université des Sciences et Technologie de Lille - Lille I, 2010. http://tel.archives-ouvertes.fr/tel-00845565.

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Ce travail de thèse s'inscrit dans le domaine du machine learning et concerne plus particulièrement les sous-catégories de l'optimisation stochastique, du online learning et du clustering. Ces sous-domaines existent depuis plusieurs décennies mais ils ont tous reçu un éclairage différent au cours de ces dernières années. Notamment, les jeux de bandits offrent aujourd'hui un cadre commun pour l'optimisation stochastique et l'online learning. Ce point de vue conduit a de nombreuses extensions du jeu de base. C'est sur l'étude mathématique de ces jeux que se concentre la première partie de cette
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Books on the topic "Price clustering"

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Goodhart, C. A. E. The clustering of bid/ask prices and the spread in the foreign exchange market. LSE Financial Markets Group, 1990.

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Book chapters on the topic "Price clustering"

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Pradeepthi, C., V. J. Vijaya Geetha, Somula Ramasubbareddy, and K. Govinda. "Prediction of Real Estate Price Using Clustering Techniques." In Emerging Research in Data Engineering Systems and Computer Communications. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-0135-7_27.

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de Oliveira, André D. C. M., Pedro F. A. Pinto, and Sergio Colcher. "Stocks Clustering Based on Textual Embeddings for Price Forecasting." In Intelligent Systems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61380-8_45.

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Miłobędzki, Paweł. "Price Clustering in Stocks from the WIG 20 Index." In Contemporary Trends and Challenges in Finance. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43078-8_14.

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Kleer, Pieter, and Guido Schäfer. "Topological Price of Anarchy Bounds for Clustering Games on Networks." In Web and Internet Economics. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35389-6_18.

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Feldman, Michal, and Ophir Friedler. "A Unified Framework for Strong Price of Anarchy in Clustering Games." In Automata, Languages, and Programming. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-47666-6_48.

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Zhang, Fengyi, and Zhigao Liao. "Gold Price Forecasting Based on RBF Neural Network and Hybrid Fuzzy Clustering Algorithm." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40078-0_6.

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Abbas, Baqar, Ammar Belatreche, and Ahmed Bouridane. "Stock Price Manipulation Detection Using Empirical Mode Decomposition Based Kernel Density Estimation Clustering Method." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01057-7_63.

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Palumbo, Luigi, Tiziana Laureti, and Ilaria Benedetti. "A Multi-dimensional Clustering on Fuzzy Metrics to Classify CPG Pricing and Price Promotion Strategies." In Analysis of Socio-Economic Conditions. Routledge, 2021. http://dx.doi.org/10.4324/9781003053712-20.

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Wang, Xianchang, Jiayu Wang, Xuhong Lin, et al. "Analysis on the Importance of Price Support-Resistance Levels of Chinese Stock Market Based on the Proposed Information Granulation and FCM Clustering Algorithm." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15235-2_168.

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Yokotani, Takuya, Hung-Hsuan Huang, and Kyoji Kawagoe. "Predicting Online Auction Final Prices Using Time Series Splitting and Clustering." In Web Technologies and Applications. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29253-8_18.

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Conference papers on the topic "Price clustering"

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Sokhanvar, Kh, A. Karimpour, and N. Pariz. "Electricity price forecasting using a clustering approach." In 2008 IEEE 2nd International Power and Energy Conference (PECon). IEEE, 2008. http://dx.doi.org/10.1109/pecon.2008.4762677.

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Kiran, Deep, A. R. Abhyankar, and B. K. Panigrahi. "Zonal price based clustering of bidding zones." In 2016 IEEE 6th International Conference on Power Systems (ICPS). IEEE, 2016. http://dx.doi.org/10.1109/icpes.2016.7584201.

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Martins, Ana, Joao Lagarto, and Margarida G. M. S. Cardoso. "Electricity market price analysis using time series clustering." In 2019 16th International Conference on the European Energy Market (EEM). IEEE, 2019. http://dx.doi.org/10.1109/eem.2019.8916409.

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Li, Ran, Zhimin Wang, Simon Le Blond, and Furong Li. "Development of time-of-use price by clustering techniques." In 2014 IEEE Power & Energy Society General Meeting. IEEE, 2014. http://dx.doi.org/10.1109/pesgm.2014.6939335.

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Li, Yang, Quan Pan, Tao Yang, and Lantian Guo. "Reasonable price recommendation on Airbnb using Multi-Scale clustering." In 2016 35th Chinese Control Conference (CCC). IEEE, 2016. http://dx.doi.org/10.1109/chicc.2016.7554467.

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Raesita, K., and P. A. Mahadwartha. "Superstitions and Price Clustering in the Taiwan Stock Exchange." In Proceedings of the 17 th International Symposium on Management (INSYMA 2020). Atlantis Press, 2020. http://dx.doi.org/10.2991/aebmr.k.200127.097.

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Murakami, Akane, and Yukari Shirota. "Time Series Analysis of Global Automakers Stock Price Clustering." In 2020 9th International Congress on Advanced Applied Informatics (IIAI-AAI). IEEE, 2020. http://dx.doi.org/10.1109/iiai-aai50415.2020.00122.

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Ning, Yifei, Xingying Chen, Yingchen Liao, Qingguo Yan, and Shiming Xu. "Clustering of large costumer based on characteristics of price response." In 2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC). IEEE, 2016. http://dx.doi.org/10.1109/appeec.2016.7779866.

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Xie, Li, and Hua Zheng. "Electricity price forecasting by clustering-least squares support vector machine." In 2013 6th International Congress on Image and Signal Processing (CISP). IEEE, 2013. http://dx.doi.org/10.1109/cisp.2013.6743884.

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Mori, Hiroyuki, and Akira Awata. "Normalized RBFN with Hierarchical Deterministic Annealing Clustering for Electricity Price Forecasting." In 2007 IEEE Power Engineering Society General Meeting. IEEE, 2007. http://dx.doi.org/10.1109/pes.2007.385664.

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Reports on the topic "Price clustering"

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Fassnacht, Chris D., J. P. McKean, L. V. E. Koopmans, et al. Three Gravitational Lenses for the Price of One: Enhanced Strong Lensing Through Galaxy Clustering. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/878721.

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Zárate-Solano, Hector Manuel, and Daniel R. Zapata-Sanabria. Clustering and forecasting inflation expectations using the World Economic Survey : the case of the 2014 oil price shock on inflation targeting countries. Banco de la República, 2017. http://dx.doi.org/10.32468/be.993.

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