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Dive into the research topics where N. Kondakis is active.

Publication


Featured researches published by N. Kondakis.


Physical Review Letters | 1996

Search for the flavor-changing neutral-current decays D+--> pi + micro+ micro- and D+--> pi +e+e-

E.M. Aitala; S. Amato; J.C. Anjos; J. A. Appel; D. Ashery; S. Banerjee; Bediaga I I; G. Blaylock; Stephen B. Bracker; P. R. Burchat; R.A. Burnstein; T. Carter; H.S. Carvalho; Costa I I; L. Cremaldi; C. Darling; K. Denisenko; A. Fernandez; P. Gagnon; S. Gerzon; C. Gobel; K. Gounder; D. Granite; A.M. Halling; G. Herrera; G. Hurvits; C. James; P.A. Kasper; N. Kondakis; S. Kwan

We report the results of a search for the flavor-changing neutral-current decays


hellenic conference on artificial intelligence | 2006

An intelligent statistical arbitrage trading system

Nikos S. Thomaidis; N. Kondakis; George D. Dounias

D^+\rightarrow \pi^+ \mu^+ \mu^-


Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment | 1989

Segmented ionization chambers for high intensity beam measurements

C. Y. Chi; N. Kondakis; Wei-Po Lee; B. Rubin; R. Seto; C. Stoughton; G. Tzanakos; W.P. Hogan; E. O'Brien; T. O'Halloran; K. Reardon; S. Salman; P.D. Sheldon; G. W. Sullivan; B. Blumenfeld; L. Chichura; C.Y. Chien; J. Krizmanic; E. Lincke; W. Lyle; L. Lueking; L. Madansky; A. Pevsner

and


International Journal of Financial Markets and Derivatives | 2010

Optimal Portfolio Allocation Strategies with Dynamic Factor Models

Nikolaos Thomaidis; Efthymios Roumpis; N. Kondakis

D^+\rightarrow \pi^+ e^+ e^-


Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment | 1991

A large system of Flash ADCs for a neutrino detector

M. Atiya; C.Y. Chi; H. Cunitz; N. Kondakis; W. Lee; B. Rubin; R. Seto; W. Sippach; C. Stoughton; G. Tzanakos; E. O'Brien; T. O'Halloran; K. Reardon; S. Salman; B. Blumenfeld; L. Chichura; C.Y. Chien; J. Krizmanic; E. Lincke; L. Lueking; W. Lyle; L. Madansky; A. Pevsner

in data from Fermilab charm hadroproduction experiment E791. No signal above background is found, and we obtain upper limits on branching fractions,


Physical Review Letters | 1996

Search for the Flavor-Changing Neutral-Current DecaysD+→π+μ+μ−andD+→π+e+e−

E.M. Aitala; S. Amato; J.C. Anjos; J. A. Appel; D. Ashery; S. Banerjee; I. Bediaga; G. Blaylock; Stephen B. Bracker; P. R. Burchat; R.A. Burnstein; T. Carter; H.S. Carvalho; I. Costa; L. Cremaldi; C. Darling; K. Denisenko; A. Fernandez; P. Gagnon; S. Gerzon; C. Gobel; K. Gounder; D. Granite; A.M. Halling; G. Herrera; G. Hurvits; C. James; P.A. Kasper; N. Kondakis; S. Kwan

B(D^+\rightarrow \pi^+ \mu^+ \mu^-)<1.8 \times 10^{-5}


Physical Review Letters | 1995

Search for the Flavor-Changing Neutral-Current Decays

E.M. Aitala; R. Weiss; N. R. Stanton; N. Witchey; H.S. Carvalho; G. Herrera; N. W. Reay; S. MayTal-Beck; E. Wolin; A. Napier; S. Banerjee; S. Watanabe; A. Fernandez; P.A. Kasper; M. Halling; B. Quinn; R.A. Burnstein; K. Sugano; A. C. dos Reis; R. Zalisnyak; J. Slaughter; B. Lundberg; D. Granite; S. Takach; K. Thorne; S. Radeztsky; S. Amato; J.C. Anjos; N. Kondakis; D. J. Summers

and


Archive | 2006

D^+\to \pi^+ \mu^+ \mu^-

Nikos S. Thomaidis; George D. Dounias; N. Kondakis

B(D^+\rightarrow \pi^+ e^+ e^-)<6.6 \times 10^{-5}


Physical Review Letters | 1996

and

E.M. Aitala; S. Amato; J.C. Anjos; J. A. Appel; D. Ashery; S. Banerjee; I. Bediaga; G. Blaylock; Stephen B. Bracker; P. R. Burchat; R.A. Burnstein; T. Carter; H.S. Carvalho; I. Costa; L. Cremaldi; C. Darling; K. Denisenko; A. Fernandez; P. Gagnon; S. Gerzon; C. Gobel; K. Gounder; D. Granite; A.M. Halling; G. Herrera; G. Hurvits; C. James; P.A. Kasper; N. Kondakis; S. Kwan

, at the 90\% confidence level.


Archive | 2008

D^+\to \pi^+ e^+ e^-

Nikos S. Thomaidis; N. Kondakis; Vassileios Vassiliadis

This paper proposes an intelligent combination of neural network theory and financial statistical models for the detection of arbitrage opportunities in a group of stocks. The proposed intelligent methodology is based on a class of neural network-GARCH autoregressive models for the effective handling of the dynamics related to the statistical mispricing between relative stock prices. The performance of the proposed intelligent trading system is properly measured with the aid of profit & loss diagrams.

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B. Blumenfeld

Johns Hopkins University

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C.Y. Chien

Johns Hopkins University

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E.M. Aitala

University of Mississippi

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J.C. Anjos

University of Mississippi

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R.A. Burnstein

Illinois Institute of Technology

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S. Amato

University of Mississippi

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