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State of the art of the project and of the national facility of financial data.

State of the art of the project and of the national facility of financial data. Our project and the related ones. High frequency dynamics in financial markets (INFM). Softcomputing applications to modern finance (Science park Trieste). eGRID (ICTP).

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State of the art of the project and of the national facility of financial data.

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  1. State of the art of the project and of the nationalfacility of financial data.

  2. Our project and the related ones High frequency dynamics in financial markets (INFM) Softcomputing applications to modern finance (Science park Trieste) eGRID (ICTP)

  3. Research institutions re-organization INFM is now part of CNR. This re-organization should not affect the development of the project but will certainly affect future research possibilities.

  4. Work package 1 Contribution of INFM to the realization of a “national facility” of financial data The national facility is designed and maintained by ICTP (within the eGRID project) but the final property of data is of INFM.

  5. Data of the facility "Rebuild Order Book" of London Stock Exchange (LSE) year 2002 "Trades and Quotes" (1995-2003) and "Open Book" (2002) of the New York Stock Exchange (NYSE), “Intraday Historical Euronext Data" of the Paris, Brussels and Amsterdam (year 2002). We are also trying to buy the order book related to these transactions Intraday trades, best 5 quotes for the Milan Stock Exchange year (2002).

  6. Data of the facility “Trades” of the Tokyo Stock Exchange, year 2002. Money Exchange trough “Depositi Interbancari” of the electronic market E-MID S.p.a., year 2002. S&P 500 Index and Future from TickData. Years 1982-2004 . We have ordered the tick data of “MTS Time Series” from EuroMTS l.t.d., from April 2003 to March 2004.

  7. GRID nodes Padova (INFN) Trieste (eGRID) Palermo (INFM OCS) Florence (Univ) Rome (CNR ISC)

  8. Pre-processing of data Flat files have been obtained for the LSE (A. Tedeschi, A. Ponzi) An efficient sorting has been devised for NYSE and time series sampled at intraday fixed time intervals have been obtained (A. Tedeschi, C. Brownlees, C. Coronnello)

  9. Pre-processing of the data A reconstruction of the LSE order book has been achieved for the Set 1 stocks of that market (A. Ponzi) Correlation based graphs have been obtained for LSE, NYSE and Parigi stocks and a series of conditions and methods (S. Miccichè and C. Coronnello)

  10. Flat file example

  11. Order book dynamics The real behavior in a short time for a normal stock - sell limit orders - buy limit orders ○ sell market orders x buy market orders first sell gap first buy gap spread

  12. Order book dynamics A slightly longer time interval

  13. A rogue trade on September 20, 2005

  14. Correlation based networks The “traditional” MST

  15. The Planar maximally filtered graph mst

  16. Work package 2 Modeling financial markets with Agent Based Models - Ancona Unit - Trieste Unit

  17. Work package 3 Structure and efficiency of financial markets - Florence Unit - Palermo Unit - Piemonte Orientale Unit - Rome 1 Unit

  18. Work package 4 Portfolio choices - CMA -> Rome 2 Unit - IAC CNR Unit - Palermo Unit - Rome 1 Unit

  19. Conferences Conference at Roma 2 December (5-7) with a session on “Physics in Finance” chairman Prof. M. Bagella Workshop on Grid Technology for Financial Modeling and Simulation to be held in Palermo, Italy, from February 3 to 4, 2006 (Chairmen S. Cozzini, S. d’Addona, R.N.Mantegna)

  20. Administration Our first reference is always Stefania Scotto at INFM-CNR in Genova.

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