Futures Hedging in CSI 300 Markets: A Comparison Between Minimum-Variance and Maximum-Utility Frameworks
Sign Up to like & getrecommendations! Published in 2020 at "Computational Economics"
DOI: 10.1007/s10614-020-09979-z
Abstract: In this paper, we explore the hedging performance of CSI 300 stock index futures under the minimum-variance and maximum-utility framework. We employ ten commonly used econometric models including constant and dynamic ones. Our empirical results… read more here.
Keywords: minimum variance; variance maximum; csi 300; maximum utility ... See more keywords
Combining the minimum-variance and equally-weighted portfolios: Can portfolio performance be improved?
Sign Up to like & getrecommendations! Published in 2019 at "Economic Modelling"
DOI: 10.1016/j.econmod.2018.11.012
Abstract: Abstract It is documented in the literature that due to estimation errors, mean-variance efficient portfolios deliver no higher out-of-sample Sharpe ratios than does the naive equally-weighted portfolio (EWP). This paper demonstrates how the out-of-sample performance… read more here.
Keywords: variance; performance; portfolio; equally weighted ... See more keywords
Understanding the outperformance of the minimum variance portfolio
Sign Up to like & getrecommendations! Published in 2017 at "Finance Research Letters"
DOI: 10.1016/j.frl.2017.09.005
Abstract: Minimum variance portfolio (MVP) seems to outperform the mean-variance optimized portfolio on a risk-adjusted basis. Scherer (2011) conjectures that the MVP tilts toward low beta and low idiosyncratic risk assets. Consequently, the MVP capitalizes on… read more here.
Keywords: yanushevsky; variance portfolio; portfolio; variance ... See more keywords
Short term solar power forecasting using hybrid minimum variance expanded RVFLN and Sine-Cosine Levy Flight PSO algorithm
Sign Up to like & getrecommendations! Published in 2021 at "Renewable Energy"
DOI: 10.1016/j.renene.2021.04.088
Abstract: Abstract With the increase in solar power integration, the necessity for accurate solar power forecasting is of paramount importance for various energy markets, grid management system, power dispatching and so on. This paper analyses a… read more here.
Keywords: power forecasting; sine cosine; power; solar power ... See more keywords
Experimental performance assessment of the sub‐band minimum variance beamformer for ultrasound imaging
Sign Up to like & getrecommendations! Published in 2017 at "Ultrasonics"
DOI: 10.1016/j.ultras.2017.04.011
Abstract: HIGHLIGHTSExperimental performance of the sub‐band Minimum Variance beamformer is studied.Lateral FWHM was measured to 16.7 &mgr;m (&lgr;/12), from isolated wire‐targets.This result demonstrates 24‐fold improvement compared to conventional beamforming.No resolution benefits were found for imaging continuous… read more here.
Keywords: beamformer; variance beamformer; band; minimum variance ... See more keywords
Improving Minimum-Variance Portfolios by Alleviating Overdispersion of Eigenvalues
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Financial and Quantitative Analysis"
DOI: 10.1017/s0022109019000899
Abstract: In portfolio risk minimization, the inverse covariance matrix of returns is often unknown and has to be estimated in practice. Yet the eigenvalues of the sample covariance matrix are often overdispersed, leading to severe estimation… read more here.
Keywords: improving minimum; variance portfolios; portfolios alleviating; covariance matrix ... See more keywords
Constrained generalised minimum variance controller design using projection-based recurrent neural network
Sign Up to like & getrecommendations! Published in 2017 at "Iet Control Theory and Applications"
DOI: 10.1049/iet-cta.2016.0141
Abstract: In this study, a generalised minimum variance control (GMVC) method using the projection-based recurrent neural network (PRNN) is proposed to minimise the error variance in the output of the non-linear plant. One the main drawbacks… read more here.
Keywords: generalised minimum; network; using projection; variance ... See more keywords
Broadband Spatial Spectrum Estimation Based on Space-Time Minimum Variance Distortionless Response and Frequency Derivative Constraints
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3258978
Abstract: The two-dimensional optimization capability of the space-time minimum variance distortionless response (STMVDR) can improve the spatial spectrum estimation performance of the broadband beamformer with limited samples, but its high sensitivity to frequency errors may lead… read more here.
Keywords: frequency derivative; minimum variance; frequency; spatial spectrum ... See more keywords
On Minimum-Variance Event-Triggered Control
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DOI: 10.1109/lcsys.2017.2700620
Abstract: We study the problem of minimum-variance event-triggered output-feedback control of linear time-invariant processes driven by white Gaussian noise. We show that the optimal event generation is separated from the controller configuration and can be determined… read more here.
Keywords: control; minimum variance; variance event; event ... See more keywords
Experimental investigation of the unit circle minimum variance distortionless response adaptive beamformer
Sign Up to like & getrecommendations! Published in 2017 at "Journal of the Acoustical Society of America"
DOI: 10.1121/1.5014477
Abstract: Source masking occurs when loud interferers produce high side lobes in the conventional beamformer (CBF) scanned response, obscuring the true direction-of-arrival of the desired signal. The minimum variance distortionless response (MVDR) adaptive beamformer (ABF) places… read more here.
Keywords: beamformer; response; unit; unit circle ... See more keywords
Source localization based on matrix filter and sparse asymptotic minimum variance
Sign Up to like & getrecommendations! Published in 2018 at "Journal of the Acoustical Society of America"
DOI: 10.1121/1.5068678
Abstract: Wideband direction of arrival (DOA) estimation plays an important role in passive sonar signal processing. Recently, sparsity-based DOA estimation method has attracted considerable attention because of its high resolution in the condition of few snapshots… read more here.
Keywords: asymptotic minimum; weak targets; sparse asymptotic; minimum variance ... See more keywords