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Comparing Risk Attitudes of Organic and Non-Organic Farmers with a Bayesian Random Coefficient Model

Gardebroek, Cornelis - 2013

farmers compared with that of conventional farmers has not been studied. Using a non-structural approach to risk estimation, a … of Dutch organic and non-organic arable farmers. The model is estimated using Gibbs sampling. The results indicate that … organic farmers are significantly less risk averse than their non-organic colleagues …

Persistent link: https://www.econbiz.de/10012753576

Portfolio allocation for European markets with predictability and parameter uncertainty

Jondeau, Eric; Rockinger, Michael - 2010

We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model is calibrated at a quarterly frequency for ten European countries. We also use maximum-likelihood estimates and Bayesian estimates to account for parameter uncertainty. We find...

Persistent link: https://www.econbiz.de/10008797745

Risk, return, and volatility feedback : a Bayesian nonparametric analysis

Jensen, Mark J.; Maheu, John M. - 2014

The relationship between risk and return is one of the most studied topics in finance. The majority of the literature is based on a linear, parametric relationship between expected returns and conditional volatility. This paper models the contemporaneous relationship between market excess...

Persistent link: https://www.econbiz.de/10010365633

Variable selection and functional form uncertainty in cross-country growth regressions

Salimans, Tim - 2011

suggested by new growth theory, while addressing the variable selection problem by means of Bayesian model averaging …. Controlling for variable selection uncertainty, we confirm the evidence in favor of new growth theory presented in several earlier …

Persistent link: https://www.econbiz.de/10011382708

Bayesian Estimation of a Dynamic Asset Pricing Model with Long-Run Risk

Rooj, Debasis - 2011

In this paper, I build a Dynamic Stochastic General Equilibrium (DSGE) model and estimate it using Bayesian Markov Chain Monte Carlo (MCMC) methods. I use the results in order to examine how asset prices and macroeconomic quantities respond to the di erent shocks in the economy. Fluctuations in...

Persistent link: https://www.econbiz.de/10013121340

Advancing Style Analysis and Risk Modeling by Incorporating Model Uncertainty with Bayesian Model Averaging

Zhou, Hao (David) - 2013

Investors have increasing interests in sophisticated yet transparent analytic tools to handle model uncertainty, tail risk and market dynamics. This paper demonstrates how macroeconomic factor models, based on Bayesian model averaging (BMA), can help address the challenges in some specific...

Persistent link: https://www.econbiz.de/10013073771

Dealing with Drift Uncertainty : A Bayesian Learning Approach

De Franco, Carmine - 2018

One of the main challenges investors have to face is model uncertainty. Typically, the dynamic of the assets is modeled using two parameters: the drift vector and the covariance matrix, which are both uncertain. Since the variance/covariance parameter is assumed to be estimated with a certain...

Persistent link: https://www.econbiz.de/10012907937

Risk, Return, and Volatility Feedback : A Bayesian Nonparametric Analysis

Jensen, Mark J. - 2015

Persistent link: https://www.econbiz.de/10013026110

Quantifying time-varying forecast uncertainty and risk for the real price of oil

Aastveit, Knut Are; Cross, Jamie; Dijk, Herman K. van - 2021

analysis of profit-loss and hedging against price risk. …

Persistent link: https://www.econbiz.de/10012544443

Crash Risk in Currency Returns

Chernov, Mikhail - 2015

We quantify crash risk in currency returns. To accomplish this task, we develop and estimate an empirical model of exchange rate dynamics using daily data for four currencies relative to the US dollar: the Australian dollar, the British pound, the Swiss franc, and the Japanese yen. The model...

Persistent link: https://www.econbiz.de/10013037072

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