Impact of Error in Parameter Estimations on Large Scale Portfolio Optimization

2019 ◽  
pp. 151-184 ◽  
Author(s):  
Valery A. Kalyagin ◽  
Sergey V. Slashchinin
Keyword(s):  
Portfolio Optimization ◽  
Large Scale ◽  
Parameter Estimations

FAST METHODS FOR LARGE-SCALE NON-ELLIPTICAL PORTFOLIO OPTIMIZATION

2014 ◽  
Vol 09 (02) ◽  
pp. 1440001 ◽  
Author(s):  
MARC S. PAOLELLA
Keyword(s):  
Portfolio Optimization ◽  
Large Scale ◽  
Asset Returns ◽  
Short Selling ◽  
Sharpe Ratio ◽  
Mixture Of Normals ◽  
Optimization Via Simulation ◽  
Fast Methods ◽  
Out Of Sample ◽  
Weighted Portfolio

Simple, fast methods for modeling the portfolio distribution corresponding to a non-elliptical, leptokurtic, asymmetric, and conditionally heteroskedastic set of asset returns are entertained. Portfolio optimization via simulation is demonstrated, and its benefits are discussed. An augmented mixture of normals model is shown to be superior to both standard (no short selling) Markowitz and the equally weighted portfolio in terms of out of sample returns and Sharpe ratio performance.

scholarly journals A novel iterative approach for mapping local singularities from geochemical data

2007 ◽  
Vol 14 (3) ◽  
pp. 317-324 ◽  
Author(s):  
◽  
◽  
◽  
Keyword(s):  
Large Scale ◽  
Mineral Exploration ◽  
Singularity Analysis ◽  
Geochemical Data ◽  
Iterative Approach ◽  
Scale Invariant ◽  
Singularity Index ◽  
Parameter Estimations ◽  
Singular Functions ◽  
Local Singularity

Abstract. There are many phenomena in nature, such as earthquakes, landslides, floods, and large-scale mineralization that are characterized by singular functions exhibiting scale invariant properties. A local singularity analysis based on multifractal modeling was developed for detection of local anomalies for mineral exploration. An iterative approach is proposed in the current paper for improvement of parameter estimations involved in the local singularity analysis. The advantage of this new approach is demonstrated with de Wijs's zinc data from a sphalerite-quartz vein near Pulacayo in Bolivia. The semivariogram method was used to illustrate the differences between the raw data and the estimated data by the new algorithm. It has been shown that the outcome of the local singularity analysis consists of two components: singularity component characterized by local singularity index and the non-singular component by prefractal parameter.

scholarly journals Large scale portfolio optimization with piecewise linear transaction costs

2008 ◽  
Vol 23 (6) ◽  
pp. 929-952 ◽  
Author(s):  
Marina Potaptchik ◽  
Levent Tunçel ◽  
Henry Wolkowicz
Keyword(s):  
Transaction Costs ◽  
Portfolio Optimization ◽  
Large Scale ◽  
Piecewise Linear

scholarly journals Hierarchical Fault-Tolerant Control using Model Predictive Control for Wind Turbine Pitch Actuator Faults

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3097 ◽  
Author(s):  
Donggil Kim ◽  
Dongik Lee
Keyword(s):  
Wind Turbine ◽  
Predictive Control ◽  
Wind Turbines ◽  
Large Scale ◽  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Actuator Faults ◽  
Control Techniques ◽  
Parameter Estimations ◽  
Installed Capacity

Wind energy is one of the fastest growing energy sources in the world. It is expected that by the end of 2022 the installed capacity will exceed 250 GW thanks to the supply of large scale wind turbines in Europe. However, there are still challenging problems with wind turbines. In particular, off-shore and large-scale wind turbines are required to tackle the issue of maintainability and availability because they are installed in harsh off-shore environments, which may also prevent engineers from accessing the site for immediate repair works. Fault-tolerant control techniques have been widely exploited to overcome this issue. This paper proposes a novel fault-tolerant control strategy for wind turbines. The proposed strategy has a hierarchical structure, consisting of a pitch controller and a wind turbine controller, with parameter estimations using the adaptive fading Kalman filter technique. The pitch controller compensates any fault with a pitching actuator, while the wind turbine controller computes the optimal reference command for pitching behavior so that the effect of the fault with a pitch actuator can be minimized. The performance of the proposed approach is demonstrated through a set of simulations with a wind turbine benchmark model.

COSMOLOGICAL PARAMETER ESTIMATION WITH LARGE SCALE STRUCTURE AND SUPERNOVAE DATA

2004 ◽  
Vol 13 (08) ◽  
pp. 1661-1668 ◽  
Author(s):  
CAROLINA J. ODMAN ◽  
MIKE HOBSON ◽  
ANTHONY LASENBY ◽  
ALESSANDRO MELCHIORRI
Keyword(s):  
Large Scale ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Cosmological Parameter ◽  
Microwave Background ◽  
Parameter Estimations ◽  
Peculiar Velocities ◽  
Redshift Surveys ◽  
Type Ia ◽  
Ia Supernovae

Most cosmological parameter estimations are based on the same set of observations and are therefore not independent. Here, we test the consistency of parameter estimations using a combination of large-scale structure and supernovae data, without cosmic microwave background (CMB) data. We combine observations from the IRAS 1.2 Jy and Las Campanas redshift surveys, galaxy peculiar velocities and measurements of type Ia supernovae to obtain [Formula: see text], Ωm=0.28±0.05 and [Formula: see text] in agreement with the constraints from observations of the CMB anisotropies by the WMAP satellite. We also compare results from different subsets of data in order to investigate the effect of priors and residual errors in the data. We find that some parameters are consistently well constrained whereas others are consistently ill-determined, or even yield poorly consistent results, thereby illustrating the importance of priors and data contributions.

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