Sinha, Pankaj and Sharma, Gopalakrishna and Shah, Akash and Singh, Abhijeet (2011): Algorithms for merging tick data and data analysis for Indian financial market.
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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.
|Item Type:||MPRA Paper|
|Original Title:||Algorithms for merging tick data and data analysis for Indian financial market|
|English Title:||Algorithms for merging tick data and data analysis for Indian financial market|
|Keywords:||tick data, merging algorithm, minute data, financial market, derivative securities, high frequency financial data, intraday trading|
|Subjects:||D - Microeconomics > D5 - General Equilibrium and Disequilibrium > D53 - Financial Markets
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General
C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis
C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs
|Depositing User:||Pankaj Sinha|
|Date Deposited:||06. Jul 2011 23:12|
|Last Modified:||15. Mar 2015 02:38|
Aldridge I, “High Frequency Trading”, John Wiley and Sons, 2010
Falkenberry, T. N., “High Frequency Data Filtering”, as seen on www.tickdata.com, 2002
Shah, A, and Thomas, S “Securities Markets—Towards Greater Efficiency.” In India Development Report, edited by K. Parikh. UK: Oxford UniversityPress, 2002.