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Portfolio selection with narrow framing : probability weighting matters
De Giorgi, Enrico; Legg, Shane - 2009 - This version: June 9, 2009
This paper shows that the framework proposed by Barberis and Huang (2009) to incorporate narrow framing and loss aversion into dynamic models of portfolio choice and asset pricing can be extended to also account for probability weighting and for a value function that is convex on losses and...
Persistent link: https://www.econbiz.de/10003970464
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Robust resampling methods for time series
Camponovo, Lorenzo; Scaillet, Olivier; Trojani, Fabio - 2010 - This version: May 9, 2010
We study the robustness of block resampling procedures for time series. We first derive a set of formulas to characterize their quantile breakdown point. For the moving block bootstrap and the subsampling, we find a very low quantile breakdown point. A similar robustness problem arises in...
Persistent link: https://www.econbiz.de/10003971115
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An objective function for simulation based inference on exchange rate data
Winker, Peter (contributor); Gilli, Manfred (contributor);  … - 2007
estimation approach, e.g., for agent based microsimulation models or complex multifractal models, simulation based estimators …
Persistent link: https://www.econbiz.de/10003548061
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A specification test for nonparametric instrumental variable regression
Gagliardini, Patrick (contributor);  … - 2007
distribution is normal under the null hypothesis, and a consistent bootstrap is available to get simulation based critical values …
Persistent link: https://www.econbiz.de/10003550675
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Testing for equality between two copulas
Remillard, Bruno (contributor);  … - 2007
We develop a test of equality between two dependence structures estimated through empirical copulas. We provide inference for independent or paired samples. The multiplier central limit theorem is used for calculating p-values of the Crameacute;r-von Mises test statistic. Finite sample properties...
Persistent link: https://www.econbiz.de/10003550857
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Evolutionary finance
Evstigneev, Igor V.; Hens, Thorsten; Schenk-Hoppé, … - 2008
-time mathematical finance version. Applications are concerned with simulation studies of the market dynamics, empirical estimation of …
Persistent link: https://www.econbiz.de/10003961707
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The price of protection : derivatives, default risk, and margining
Gibson, Rajna; Murawski, Carsten - 2008
equilibrium model to derive a set of testable hypotheses. Subsequently, we test these hypotheses with a simulation model that …
Persistent link: https://www.econbiz.de/10003966202
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Clarifications to questions and criticisms on the Johansen-Ledoit-Sornette bubble model
Sornette, Didier; Woodard, Ryan; Yan, Wanfeng; Zhou, … - 2011
The Johansen-Ledoit-Sornette (JLS) model of rational expectation bubbles with finite-time singular crash hazard rates has been developed to describe the dynamics of financial bubbles and crashes. It has been applied successfully to a large variety of financial bubbles in many different markets....
Persistent link: https://www.econbiz.de/10009273112
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Estimating the joint tail risk under the filtered historical simulation : an application to the CCP's default and waterfall fund
Barone-Adesi, Giovanni; Giannopoulos, Kostas; Vosper, Les - 2015
, estimating the probability of joint member defaults and reverse stress testing, is the Filtered Historical Simulation (FHS). In … this study we extend the use of Filtered Historical Simulation in estimating the potential losses the CCP would face from a …,000,000 simulation trials. The bootstrapping of 5,000,000 trials is repeated 5,000 times to generate the density of the JES …
Persistent link: https://www.econbiz.de/10011296075
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Lagrange regularization approach to compare nested data sets and determine objectively financial bubbles' inceptions
Demos, Guilherme; Sornette, Didier - 2017
Inspired by the question of identifying the start time τ of financial bubbles, we address the calibration of time series in which the inception of the latest regime of interest is unknown. By taking into account the tendency of a given model to overfit data, we introduce the Lagrange...
Persistent link: https://www.econbiz.de/10011877499