Optimal vs. Naive Diversification in the Cryptocurrencies Market: The Role of Time-Varying Moments and Transaction Costs

TL;DR

This paper compares advanced portfolio optimization techniques to naive diversification in the volatile cryptocurrencies market, focusing on time-varying moments, transaction costs, and strategy performance.

Contribution

It demonstrates the effectiveness of time-varying moment estimators and turnover penalties in improving out-of-sample portfolio performance over naive strategies.

Findings

Time-varying moments outperform sample estimators.

Incorporating transaction costs enhances portfolio robustness.

Optimal strategies can beat the 1/N benchmark.

Abstract

This study investigates three central questions in portfolio optimization. First, whether time-varying moment estimators outperform conventional sample estimators in practical portfolio construction. Second, whether incorporating a turnover penalty into the optimization objective can improve out-of-sample performance. Third, what type of optimal portfolio strategies can consistently outperform the naive 1/N benchmark. Using empirical evidence from the cryptocurrencies market, this paper provides comprehensive answers to these questions. In the process, several additional findings are uncovered, offering further insights into the dynamics of portfolio construction in highly volatile asset classes.