Financial signal processing and machine learning download
Dmitry Malioutov (Editor of Financial Signal Processing and Machine Learning)
Akansu A.N. Financial Signal Processing and Machine Learning
Asset allocation constitutes one of the most crucial and most challenging task in financial engineering. In many allocation strategies, the estimation of large covariance or precision matrices from short time span multivariate observations is a mandatory yet difficult step. In the present contribution, a large selection of elementary to advanced estimation procedures for the covariance as well as for precision matrices, are organized into classes of estimation principles, reviewed and compared. To complement this overview, several additional estimators are explicitly derived and studied theoretically. Rather than estimation performance evaluated from synthetic simulated data, performance of the estimation procedures are assessed empirically by financial criteria volatility, Sharpe ratio, It was also presented as part of the first Agora of Financial Management, set up by AFG to promote exchanges between academic researchers and practitioners.
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Follow icassp The conference will feature world-class presentations by internationally renowned speakers, cutting-edge session topics and provide a fantastic opportunity to network with like-minded professionals from around the world. ICASSP will feature a mix of national and international speakers, tutorials, workshops and exhibits. Featuring contemporary research, highly regarded presenters and a focus on translating research into practice the conference is sure to be an exciting event for all who attend. Download call for papers.