Optimal Asset Allocation Under Linear Loss Aversion
Growing experimental evidence suggests that loss aversion plays an important role in asset allocation decisions. We study the asset allocation of a linear loss-averse (LA) investor and compare the optimal LA portfolio to the more traditional optimal mean-variance (MV) and conditional value-at-risk (CVaR) portfolios. First we derive conditions under which the LA problem is equivalent to the MV and CVaR problems. Then we analytically solve the twoasset problem, where one asset is risk-free, assuming binomial or normal asset returns. In addition we run simulation experiments to study LA investment under more realistic assumptions. In particular, we investigate the impact of different dependence structures, which can be of symmetric (Gaussian copula) or asymmetric (Clayton copula) type. Finally, using 13 EU and US assets, we implement the trading strategy of an LA investor assuming assets are reallocated on a monthly basis and find that LA portfolios clearly outperform MV and CVaR portfolios.
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