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Visualizing and measuring software portfolio architectures : a flexibility analysis
Lagerström, Robert; Baldwin, Carliss Y.; MacCormack, Alan - 2014
Persistent link: https://www.econbiz.de/10010258696
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Machine Learning for Visual Risk Analysis and Hedge Fund Selection
Huber, Claus - 2018
One of the main principles to build portfolios of financial assets is to achieve stable long-term performance and avoid …
Persistent link: https://www.econbiz.de/10012907501
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Stochastic intrinsic kriging for simulation metamodelling
Mehdad, Ehsan; Kleijnen, Jack P. C. - 2014
Persistent link: https://www.econbiz.de/10011283893
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Decomposing portfolio value-at-risk : a general analysis
Hallerbach, Winfried G. - 1999 - This rev.: May 10, 1999
the underlying statistical distributions, a variety of analyticalmethods and simulation-based methods are available. Aside … orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … and incremental VaR in either a non-normal analytical setting or a MonteCarlo / historical simulation context.This paper …
Persistent link: https://www.econbiz.de/10011301159
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Stochastic intrinsic kriging for simulation metamodelling
Mehdad, Ehsan; Kleijnen, Jack P. C. - 2015 - Revised version of CentER Discussion Paper No. 2014-054
Persistent link: https://www.econbiz.de/10011349910
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Simulation-optimization via kriging and bootstrapping : a survey
Kleijnen, Jack P. C. - 2013 - Revision of CentER DP 2011-064
Persistent link: https://www.econbiz.de/10010228792
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Simulating the market coefficient of relative risk aversion
Azar, Samih Antoine; Karaguezian-Haddad, Vera - In: Cogent economics & finance 2 (2014) 1, pp. 1-7
In this paper, expected utility, defined by a Taylor series expansion around expected wealth, is maximized. The coefficient of relative risk aversion (CRRA) that is commensurate with a 100% investment in the risky asset is simulated. The following parameters are varied: the riskless return, the...
Persistent link: https://www.econbiz.de/10010490408
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Combining a matheuristic with simulation for risk management of stochastic assets and liabilities
Bayliss, Christopher; Serra, Marti; Nieto, Armando; … - In: Risks : open access journal 8 (2020) 4/131, pp. 1-14
maximises the overall benefit over a time horizon. To solve this stochastic optimisation problem, a simulation …-Carlo simulation is employed to estimate the risk of failing to pay due liabilities. The simulation results allow us to set a safety …
Persistent link: https://www.econbiz.de/10012391566
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Impact analysis of financial regulation on multi-asset markets using artificial market simulations
Hirano, Masanori; Izumi, Kiyoshi; Shimada, Takashi; … - In: Journal of risk and financial management : JRFM 13 (2020) 4/75, pp. 1-20
of an artificial market, one of the computer simulations imitating real financial markets. In the simulation, we proposed …
Persistent link: https://www.econbiz.de/10012302643
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Computational finance
Stentoft, Lars - In: Journal of risk and financial management : JRFM 13 (2020) 7/145, pp. 1-4
The field of computational finance is evolving ever faster. This book collects a number of novel contributions on the use of computational methods and techniques for modelling financial asset prices, returns, and volatility, and on the use of numerical methods for pricing, hedging, and risk...
Persistent link: https://www.econbiz.de/10012309311