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Market Stability vs. Market Resilience: Regulatory Policies Experiments in an Agent-Based Model with Low- and High-Frequency Trading
2016
Social Science Research Network
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Monte-Carlo simulations reveal that reducing HF order cancellation, via minimum resting times or cancellation fees, or discouraging HFT via financial transaction taxes, reduces market volatility and the ...
In contrast, ex-post circuit breakers do not affect market volatility and they increase the duration of flash crashes. ...
The authors also acknowledge the financial support of the EU H2020 Project 'Distributed Global Financial Systems for Society" (DOLFINS) grant n. 640772. All usual disclaimers apply. ...
doi:10.2139/ssrn.2760996
fatcat:ue5b3wbadjctbegb3jd366ojri
Statistical Performance Modeling and Optimization
2006
Foundations and Trends® in Electronic Design Automation
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The following topics will be discussed in detail: sources of process variations, variation characterization and modeling, Monte Carlo analysis, response surface modeling, statistical timing and leakage ...
The increasing fluctuations in manufacturing processes have introduced unavoidable and significant uncertainty in circuit performance; hence ensuring manufacturability has been identified as one of the ...
Jiayong Le would like to thank Extreme DA for all the support provided to this work. ...
doi:10.1561/1000000008
fatcat:wrfrfutwjbdx3lc4cp3fj6djay
Critical correlations of Ising and Yang-Lee critical points from Tensor RG
[article]
2022
arXiv
pre-print
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Specifically, we compute critical exponents γ, γ/ν, δ, η and amplitude ratio A for the magnetic susceptibility from one- and two-point correlation functions for three critical points in two dimensions ...
comment on the relationship between these results and earlier results on conformal dimensions, fixed points of tensor RG, and also compare computational costs of tensor renormalization vs. conventional Monte-Carlo ...
ACKNOWLEDGMENTS We would like to thank Miles Stoudenmire, Tzu-Chieh Wei, Nikko Pomata, Frank Pollman, Chris Laumann, Aleix Bou Comas for many illuminating conversations. ...
arXiv:2204.06763v1
fatcat:2tlqeohlqvftrgxnd7f74okujm
Transport and entanglement growth in long-range random Clifford circuits
[article]
2022
arXiv
pre-print
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For sufficiently small α, we show that the presence of hydrodynamic modes becomes irrelevant such that S(t) behaves similarly in circuits with and without conservation law. ...
Depending on the exponent α controlling the probability ∝ r^-α of gates spanning a distance r, transport in such circuits varies from diffusive to superdiffusive and then to superballistic. ...
To account for this, we perform a form of 'least squares Monte Carlo', over a parameter space centered around the parameters obtained from the initial fit. ...
arXiv:2205.06309v2
fatcat:d5z26yev2babhoraqaixe23vme
Active Realization of Fractional-Order Integrators and Their Application in Multiscroll Chaotic Systems
2021
Complexity
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Monte Carlo and sensitivity tests revealed a robust realization. ...
By an exponential curve fitting, we got a convenient design equation for realizing fractional-order integrators of orders from 0.1 to 0.95. ...
To verify that the circuit of Figure 3 (b) is robust to tolerances, we carried out a Monte Carlo analysis in SPICE. ...
doi:10.1155/2021/6623855
fatcat:opyqagtaqrfz7jtmguu4bkavnm
DPSelect: A Differential Privacy Based Guard Relay Selection Algorithm for Tor
2019
Proceedings on Privacy Enhancing Technologies
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For the quality function used in the exponential mechanism, we show that a Monte-Carlo sampling-based method for stochastic optimization can be used to improve multi-dimensional trade-offs between security ...
Second, we utilize Max-Divergence and multiple notions of entropy to understand privacy loss in the worst-case for Counter-RAPTOR. ...
Resilience Exponent and Bandwidth Exponent We run a Monte-Carlo simulation for 2000 iterations (convergence) using the given optimization function (Equation 10). ...
doi:10.2478/popets-2019-0025
dblp:journals/popets/HanleySWM19
fatcat:s263pz6bhbcbrhp75rbf5ilxpy
Matrix Model simulations using Quantum Computing, Deep Learning, and Lattice Monte Carlo
[article]
2021
arXiv
pre-print
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In this paper we perform a systematic survey for quantum computing and deep learning approaches to matrix quantum mechanics, comparing them to Lattice Monte Carlo simulations. ...
Understanding quantum black holes and the role of entanglement in a holographic setup is of paramount importance for the development of better quantum algorithms (quantum error correction codes) and for ...
ACKNOWLEDGMENTS We wish to thank David Berenstein for useful suggestions and discussions on Matrix Models and Fabrizio Minganti for discussions about QuTiP. ...
arXiv:2108.02942v1
fatcat:p7m4pyi5nveklottkk64pko3bu
Optimized Monte Carlo Methods
[article]
1996
arXiv
pre-print
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I discuss optimized data analysis and Monte Carlo methods. Reweighting methods are discussed through examples, like Lee-Yang zeroes in the Ising model and the absence of deconfinement in QCD. ...
I introduce Simulated Tempering, and as an example its application to the Random Field Ising Model. ...
At first you run a quick and not very clean Monte Carlo, to understand the first physics ideas 2 . Only after that you set up complex simulational procedures, data analysis, error determination. ...
arXiv:cond-mat/9612010v1
fatcat:evevuloskzfldfrpm5yhxbwmze
Various Ways to Quantify BDMPs
2020
Electronic Proceedings in Theoretical Computer Science
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The most general method to quantify them is Monte Carlo simulation, but this may be intractable for highly reliable systems. ...
This allows a quick quantification of large models with repairable components, standby redundancies and some other types of dependencies between omponents. ...
Monte Carlo simulation The tool YAMS (cf. 4.2 and 5.3) uses a classical "event driven" Monte Carlo simulation [8] . ...
doi:10.4204/eptcs.316.1
fatcat:by2ocjzkxzdp3fhitna3e7f6jm
A Review of Mathematical and Computational Methods in Cancer Dynamics
2022
Frontiers in Oncology
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To conclude, the perspective cultivates an intuition for computational systems oncology in terms of nonlinear dynamics, information theory, inverse problems, and complexity. ...
We highlight the limitations we see in the area of statistical machine learning but the opportunity at combining it with the symbolic computational power offered by the mathematical tools explored. ...
Herein stochastic simulations such as the Monte Carlo methods and Gillespie algorithm were discussed for simulating chemical kinetics and molecular dynamics. ...
doi:10.3389/fonc.2022.850731
fatcat:jxdorq47mfhivgt5zoudjzpmwa
Matrix-Model Simulations Using Quantum Computing, Deep Learning, and Lattice Monte Carlo
2022
PRX Quantum
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Euclidean lattice Monte Carlo simulations are the de facto numerical tool for understanding the spectrum of large matrix models and have been used to test the holographic duality. ...
In this paper, we perform the first systematic survey for quantum computing and deep-learning approaches to matrix quantum mechanics, comparing them to lattice Monte Carlo simulations. ...
ACKNOWLEDGMENTS We wish to thank David Berenstein for useful suggestions and discussions on matrix models and Fabrizio Minganti for discussions about QuTiP. ...
doi:10.1103/prxquantum.3.010324
fatcat:vbtxeyglijcqrp4stkxzan2yty
Physiological environment induces quick response – slow exhaustion reactions
2011
Frontiers in Physiology
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Monte-carlo sIMulatIon of the reactIon Process In InhoMogeneous crowded sPace We performed a Monte-Carlo simulation to investigate the reaction processes in a pseudo-inhomogeneous 3D space represented ...
We performed Monte-Carlo simulation to investigate the reaction processes in a pseudo-inhomogeneous 3D space represented by adding NRO randomly to the reaction space. ...
doi:10.3389/fphys.2011.00050
pmid:21960972
pmcid:PMC3177084
fatcat:qxs2mejt4jfcjko6rrdvcv6oba
2009 Index IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems Vol. 28
2009
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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., +, TCAD March 2009 433-446 Monte Carlo methods Evaluation of Analog/RF Test Measurements at the Design Stage. Stratigopoulos, H. ...
C., +, TCAD July 2009 941-955 Statistical Blockade: Very Fast Statistical Simulation and Modeling of Rare
Circuit Events and Its Application to Memory Design. ...
doi:10.1109/tcad.2009.2036802
fatcat:hxyu2mmrnzfnbi6qlt6bklkgku
D5.1: Review of state-of-the-art for Pricing and Computation of VaR
2021
Zenodo
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The purpose of this document is toprovide a summary of the "state of the art" for these applications. ...
explored by the likes of Richard Feynman (Feynman, 1982) and Yuri Manin (Manin, 1980) who suggested that quantum computers could provide advantage over classical computers in certain tasks, such as the simulation ...
On the other hand, Monte Carlo simulation tends to converge slowly to the required solution. ...
doi:10.5281/zenodo.4889812
fatcat:kc7mlnvuffez5et7ehfsdtkowq
Dichotomous noise models of gene switches
2015
Journal of Chemical Physics
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Numerical simulations of circuit models reveal that the contribution of the genetic noise of single molecule origin to the total noise is significant for a wide range of kinetic regimes. ...
genetic circuits.Through a path sum based analysis of trajectory statistics we elucidate the connection of these hybrid schemes to the underlying master equation and provide a rigorous justification for ...
promoter architecture and should find their place alongside more traditional full scale kinetic Monte Carlo simulations. ...
doi:10.1063/1.4935572
pmid:26590554
pmcid:PMC4655464
fatcat:of2fwq473ng4jefk6ysinmchcm
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