A stability approach to mean-variance optimization

I jointly treat two critical issues in the application of mean-variance portfolios, that is, estimation risk and portfolio instability. I find that theory-based portfolio strategies, which are known to outperform naive diversification (inline image) in the absence of transaction costs, heavily underperform it under transaction costs. This is because they are highly unstable over time. I propose a generic method to stabilize any given portfolio strategy while maintaining or improving its efficiency. My empirical analysis confirms that the new method leads to stable and efficient portfolios that offer equal or lower turnover than inline image and larger Sharpe ratio, even under high transaction costs.