scholarly journals On the Basel Liquidity Formula for Elliptical Distributions

Risks ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 92
Author(s):  
Janine Balter ◽  
Alexander McNeil
Keyword(s):  
Risk Factor ◽  
White Noise ◽  
Gaussian White Noise ◽  
General Assumption ◽  
Elliptical Distributions ◽  
Risk Capital ◽  
White Noise Process ◽  
Gaussian White Noise Process ◽  
Loss Distributions ◽  
Symmetric Loss

A justification of the Basel liquidity formula for risk capital in the trading book is given under the assumption that market risk-factor changes form a Gaussian white noise process over 10-day time steps and changes to P&L (profit-and-loss) are linear in the risk-factor changes. A generalization of the formula is derived under the more general assumption that risk-factor changes are multivariate elliptical. It is shown that the Basel formula tends to be conservative when the elliptical distributions are from the heavier-tailed generalized hyperbolic family. As a by-product of the analysis, a Fourier approach to calculating expected shortfall for general symmetric loss distributions is developed.

The exact bispectra for bilinear realizable processes with hermite degree 2

1991 ◽  
Vol 23 (04) ◽  
pp. 798-808 ◽  
Author(s):  
György Terdik ◽  
Laurie Meaux
Keyword(s):  
White Noise ◽  
Discrete Time ◽  
Hermite Polynomial ◽  
Transfer Functions ◽  
Gaussian White Noise ◽  
Second Order ◽  
Bilinear Model ◽  
White Noise Process ◽  
Noise Process ◽  
Gaussian White Noise Process

This paper deals with the stationary bilinear model with Hermite degree 2 in discrete time which is built up by the first- and second-order Hermite polynomial of a Gaussian white noise process. The exact spectrum and bispectrum is constructed in terms of the transfer functions of the model.

The exact bispectra for bilinear realizable processes with hermite degree 2

1991 ◽  
Vol 23 (4) ◽  
pp. 798-808 ◽  
Author(s):  
György Terdik ◽  
Laurie Meaux
Keyword(s):  
White Noise ◽  
Discrete Time ◽  
Hermite Polynomial ◽  
Transfer Functions ◽  
Gaussian White Noise ◽  
Second Order ◽  
Bilinear Model ◽  
White Noise Process ◽  
Noise Process ◽  
Gaussian White Noise Process

This paper deals with the stationary bilinear model with Hermite degree 2 in discrete time which is built up by the first- and second-order Hermite polynomial of a Gaussian white noise process. The exact spectrum and bispectrum is constructed in terms of the transfer functions of the model.

Active Control of Along-Wind Response of a Tall Building with AMD Using LQR Controller

2014 ◽  
Vol 490-491 ◽  
pp. 1063-1067 ◽  
Author(s):  
Young Moon Kim ◽  
Ki Pyo You ◽  
Jang Youl You
Keyword(s):  
White Noise ◽  
Gaussian White Noise ◽  
Wind Load ◽  
Tall Building ◽  
White Noise Process ◽  
Noise Process ◽  
Gaussian White Noise Process ◽  
Wind Response ◽  
Wind Vibration ◽  
Lqr Controller

Most of modern tall buildings using lighter construction materials are more flexible so could be excessive wind-induced vibrations resulting in occupant discomfort and structural unsafety. The optimal control technique for reducing along-wind vibration of a tall building based on the linear quadratic regulator (LQR) is presented in this work. Actively controlled reduced along-wind vibration response is obtained from the tall building installed in an active mass damper (AMD) with a LQR controller. Fluctuating along-wind load is generated using numerical simulation method, which can formulate a stationary Gaussian white noise process. Simulating wind load in the time domain using known spectra data of fluctuating along-wind load is particularly useful for estimation of windinduced vibration which is more or less narrow banded process such as a along-wind response of a tall building. In this work, fluctuating along-wind load acting on a tall building treated as a stationary Gaussian white noise process is simulated numerically using the along-wind load spectra proposed by G. Solari in1992. And using this simulated along-wind load estimated the reduced along-wind vibration response of a tall building installed in an AMD with a LQR controller.

scholarly journals Some Applications of Higher Moments of the Linear Gaussian White Noise Process

2017 ◽  
Vol 08 (12) ◽  
pp. 1918-1938 ◽  
Author(s):  
I. S. Iwueze ◽  
C. O. Arimie ◽  
H. C. Iwu ◽  
E. Onyemachi
Keyword(s):  
White Noise ◽  
Gaussian White Noise ◽  
Higher Moments ◽  
White Noise Process ◽  
Noise Process ◽  
Gaussian White Noise Process

Driver Steering Control and a New Perspective on Car Handling Qualities

2005 ◽  
Vol 219 (10) ◽  
pp. 1041-1051 ◽  
Author(s):  
R S Sharp
Keyword(s):  
White Noise ◽  
Gaussian White Noise ◽  
Design Parameters ◽  
Steering Wheel ◽  
Steering Control ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Handling Qualities ◽  
Gaussian White Noise Process ◽  
Low Pass

The article is about steering control of cars by drivers, concentrating on following the lateral profile of the roadway, which is presumed visible ahead of the car. It builds on previously published work, in which it was shown how the driver's preview of the roadway can be combined with the linear dynamics of a simple car to yield a problem of discrete-time optimal-linear-control-theory form. In that work, it was shown how an optimal ‘driver’ of a linear car can convert the path preview sample values, modelled as deriving from a Gaussian white-noise process, into steering wheel displacement commands to cause the car to follow the previewed path with an attractive compromise between precision and ease. Recognizing that real roadway excitation is not so rich in high frequencies as white-noise, a low-pass filter is added to the system. The white-noise sample values are filtered before being seen by the driver. Numerical results are used to show that the optimal preview control is unaltered by the inclusion of the low-pass filter, whereas the feedback control is affected diminishingly as the preview increases. Then, using the established theoretical basis, new results are generated to show time-invariant optimal preview controls for cars and drivers with different layouts and priorities. Tight and loose controls, representing different balances between tracking accuracy and control effort, are calculated and illustrated through simulation. A new performance criterion with handling qualities implications is set up, involving the minimization of the preview distance required. The sensitivities of this distance to variations in the car design parameters are calculated. The influence of additional rear wheel steering is studied from the viewpoint of the preview distance required and the form of the optimal preview gain sequence. Path-following simulations are used to illustrate relatively high-authority and relatively low-authority control strategies, showing manoeuvring well in advance of a turn under appropriate circumstances. The results yield new insights into driver steering control behaviour and vehicle design optimization. The article concludes with a discussion of research in progress aimed at a further improved understanding of how drivers control their vehicles.

Time Varying Loads and White Noise on an SDOF System with Bouc Hysteresis Using Gaussian Closure

2019 ◽  
Vol 27 (01) ◽  
pp. 1850062
Author(s):  
Holger Waubke ◽  
Christian Kasess
Keyword(s):  
White Noise ◽  
Gaussian White Noise ◽  
Time Varying ◽  
Time Step ◽  
Closure Technique ◽  
Sdof System ◽  
The Monte Carlo Method ◽  
Step Procedure ◽  
Gaussian White Noise Process ◽  
Gaussian Closure

In a recent publication [H. Waubke and C. Kasess, Gaussian closure technique applied to the hysteretic Bouc model with nonzero mean white noise excitation, J. Sound Vibr. 382 (2016) 258–273], the response of a single-degree-of-freedom (SDOF) system under Gaussian white noise and a constant dead load is presented. The system has a hysteresis described by Bouc [R. Bouc, Forced vibration of mechanical systems with hysteresis, in Proc. Fourth Conference on Nonlinear Oscillation (Prague, 1967), p. 315]. New is the usage of a slowly time-varying deterministic load added to the Gaussian white noise process. The transient solution is calculated using the Gaussian closure technique together with an explicit time step procedure. All moments in the Gaussian closure technique are evaluated analytically. The results of the Gaussian closure technique are in good agreement with the results from the Monte-Carlo method.

scholarly journals Stochastic P-bifurcation in a bistable Van der Pol oscillator with fractional time-delay feedback under Gaussian white noise excitation

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Yajie Li ◽  
Zhiqiang Wu ◽  
Guoqi Zhang ◽  
Feng Wang ◽  
Yuancen Wang
Keyword(s):  
Time Delay ◽  
White Noise ◽  
Gaussian White Noise ◽  
Singularity Theory ◽  
Van Der Pol Oscillator ◽  
Order System ◽  
Damping Force ◽  
Van Der Pol ◽  
Restoring Force ◽  
White Noise Excitation

Abstract The stochastic P-bifurcation behavior of a bistable Van der Pol system with fractional time-delay feedback under Gaussian white noise excitation is studied. Firstly, based on the minimal mean square error principle, the fractional derivative term is found to be equivalent to the linear combination of damping force and restoring force, and the original system is further simplified to an equivalent integer order system. Secondly, the stationary Probability Density Function (PDF) of system amplitude is obtained by stochastic averaging, and the critical parametric conditions for stochastic P-bifurcation of system amplitude are determined according to the singularity theory. Finally, the types of stationary PDF curves of system amplitude are qualitatively analyzed by choosing the corresponding parameters in each area divided by the transition set curves. The consistency between the analytical solutions and Monte Carlo simulation results verifies the theoretical analysis in this paper.

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