quantitative models and strategies for financial and business intelligence applications

 

[13] V.V. Gavrishchaka, O.V. Barinova, A.P. Vezhnevets, and M.A. Monina, "Discovery of multi-component portfolio strategies with continuous tuning to the changing market micro-regimes using input-dependent boosting", In Proceedings of the Third International Conference on Computational Finance and its Applications, 2008

[12] O.V. Barinova and V.V. Gavrishchaka, "Generic regularization of boosting-based optimization for the discovery of regime-independent trading strategies from high-noise time series ", ICIC Express Letters, 4, 1107, 2010

[11] O.V. Barinova and V.V. Gavrishchaka, "Generic regularization of boosting-based algorithms for the discovery of regime-independent portfolio strategies from high-noise time series ", in IEEE Proceedings of the 4-th International Conference on Innovative Computing, Information and Control (ICICIC-2009)

[10] O.V. Barinova and V.V. Gavrishchaka, "Removal of confusing training samples as a generic mechanism to improve and diversify trading strategies discovered by boosting-based optimization", in Proceedings of 7-th International Conference on Computational Intelligence in Economics and Finance (2008)

[9] V.V. Gavrishchaka, M. Kovbasinskaya, and M. Monina, "Boosting-based optimization as a generic framework for novelty and fraud detection in complex strategies ", in Proceedings of International e-Conference on Computer Science, December 2007

[8] V.V. Gavrishchaka, N. Hlebnikov, and V. Bykov, "Operationally efficient framework for the discovery of market-neutral portfolio strategies based on combination of boosting and multi-objective optimization", in Proceedings of 6-th International Conference on Computational Intelligence in Economics and Finance (2007)

[7] V.V. Gavrishchaka and V. Bykov, "Market-neutral portfolio of trading strategies as universal indicator of market micro-regimes: From rare event forecasting to single-example learning of emerging patterns", in IEEE Proceedings of The Second International Conference on Innovative Computing, Information and Control (ICICIC), Kumamoto, Japan, 2007.

[6] V.V. Gavrishchaka, "Discovery of multi-spread portfolio strategy for weakly-cointegrated instruments using boosting-based optimization", In Proceedings of the 5-th International Conference on Computational Intelligence in Economics and Finance (2006).

[5] V.V. Gavrishchaka, "Boosting-based framework for portfolio strategy discovery and optimization", New Mathematics and Natural Computation, vol. 2, No. 3 (2006).

[4] V.V. Gavrishchaka, "Boosting-based frameworks in financial modeling: Application to symbolic volatility forecasting", Advances in Econometrics, Volume 20B, 123 (2006).

[3] V.V. Gavrishchaka and S.B. Ganguli, "Support vector machine as an efficient framework for stock market volatility forecasting", Computational Management Science, 3, 147 (2006).

[2] V.V. Gavrishchaka, "Boosting frameworks in financial applications: From volatility forecasting to portfolio strategy optimization", in Proceedings of the 4-th International Conference on Computational Intelligence in Economics and Finance, Salt Lake City, Utha (2005).

[1] V.V. Gavrishchaka and S.B. Ganguli, "Volatility forecasting from multiscale and high-dimensional market data", Neurocomputing, 55, 285 (2003).

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