Dennis A.V. Dittrich, Werner Güth, Martin G. Kocher, Paul Pezanis-Christou. Loss aversion and learning to bid

Bidding challenges learning theories. Even with the same bid, experiences vary stochastically: the same choice can result in either a gain or a loss. In such an environment, the question arises of how the nearly universally documented phenomenon of loss aversion affects the adaptive dynamics. We analyse the impact of loss aversion in a simple auction using the experienced-weighted attraction model of learning. Our experimental results suggest that individual learning dynamics are highly hetero...

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Olivier Ledoit, Michael Wolf. Optimal Estimation of a Large-Dimensional Covariance Matrix under Stein’s Loss

This paper revisits the methodology of Stein (1975, 1986) for estimating a covariance matrix in the setting where the number of variables can be of the same magnitude as the sample size. Stein proposed to keep the eigenvectors of the sample covariance matrix but to shrink the eigenvalues. By minimizing an unbiased estimator of risk, Stein derived an ‘optimal’ shrinkage transformation. Unfortunately, the resulting estimator has two pitfalls: the shrinkage transformation can change the ordering ...

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