{'fraction_non_alphanumeric': 0.01805869074492099, 'fraction_numerical': 0.0, 'mean_word_length': 5.253521126760563, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Optimal Portfolio Estimation for Dependent Financial Returns with Generalized Empirical Likelihood

This paper proposes to use the method of generalized empirical
likelihood to find the optimal portfolio weights. The log-returns of
assets are modeled by multivariate stationary processes rather than
i.i.d. sequences. The variance of the portfolio is written by the spectral
density matrix, and we seek the portfolio weights which minimize it.