IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/32058.html
   My bibliography  Save this paper

Algorithms for merging tick data and data analysis for Indian financial market

Author

Listed:
  • Sinha, Pankaj
  • Sharma, Gopalakrishna
  • Shah, Akash
  • Singh, Abhijeet

Abstract

This paper discusses the problem of ‘merging’ financial tick data available from data sources such as Bloomberg, NSE, and Thomson Reuters etc. Different derivative securities are traded on the exchange with different frequencies in each unit of time such as second or minute in intraday trading , therefore, it is difficult to form ‘ordered pairs’, which are essential for any financial analysis, of tick data representing the simultaneous trades of the different derivative securities. Merging refers to the conversion of intraday tick data of different securities of varying frequencies, as provided by data sources, into the form in which the tick data of all traded derivative securities have same frequency, so that it is possible to form ordered pairs of data (in every unit time period) in such a way that the original nature of the data is preserved. The four merging algorithms: Truncation, Weighted mean, median and all-combinations algorithm are compared with Dropdown algorithm, which is being used widely by the trading firms. Using NSE intraday tick data for various trading days, it is found that ‘Truncation’ and ‘Weighted Mean’ algorithms are more efficient merging algorithms.

Suggested Citation

  • Sinha, Pankaj & Sharma, Gopalakrishna & Shah, Akash & Singh, Abhijeet, 2011. "Algorithms for merging tick data and data analysis for Indian financial market," MPRA Paper 32058, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:32058
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/32058/1/MPRA_paper_32058.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    tick data; merging algorithm; minute data; financial market; derivative securities; high frequency financial data; intraday trading;
    All these keywords.

    JEL classification:

    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:32058. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.