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In this study, I apply a quantile regression model to investigate how gold returns respond to changes in various financial indicators. The model quantifies the asymmetric response of gold return in the tails of the distribution based on weekly data over the past 30 years. I conducted a...
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n this paper robustness properties of the maximum likelihood estimator (MLE) and several robust estimators for the logistic regression model when the responses are binary are analysed analytically by means of the Influence Function (IF) and empirically by means of simulations. It is found that...
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This paper studies the design of optimal time-consistent monetary policy in an economy where the planner trusts its own model, while a representative household uses a set of alternative probability distributions governing the evolution of the exogenous state of the economy. In such environments,...
Persistent link: https://www.econbiz.de/10010240307
In this paper we define and compare versions of the robust and non robust portfolio selection models based on the use, as a measure of risk, of volatility, Value at Risk and Conditional Value at Risk. This with the aim to take account of asymmetries in distribution of yields, and in profits and...
Persistent link: https://www.econbiz.de/10013128519
The paper identifies classes of nonconvex optimization problems whose convex relaxations have optimal solutions which at the same time are global optimal solutions of the original nonconvex problems. Such a hidden convexity property was so far limited to quadratically constrained quadratic...
Persistent link: https://www.econbiz.de/10013123787
In this paper we focus on robust linear optimization problems with uncertainty regions defined by ø-divergences (for example, chi-squared, Hellinger, Kullback-Leibler). We show how uncertainty regions based on ø-divergences arise in a natural way as confidence sets if the uncertain parameters...
Persistent link: https://www.econbiz.de/10013124587
We propose a robust portfolio optimization approach based on Value-at-Risk (VaR) adjusted Sharpe ratios. Traditional Sharpe ratio estimates based on limited historical return data are subject to estimation errors. Portfolio optimization based on traditional Sharpe ratios ignores this uncertainty...
Persistent link: https://www.econbiz.de/10013065458