Beyond risk parity – A machine learning-based hierarchical risk parity approach on cryptocurrencies-Reference-Cited by-同舟云学术

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Beyond risk parity – A machine learning-based hierarchical risk parity approach on cryptocurrencies

Published:2021-01 Issue: Volume:38 Page:101523
ISSN:1544-6123
Container-title:Finance Research Letters
language:en
Short-container-title:Finance Research Letters

Author:

Burggraf Tobias

Publisher

Elsevier BV

Subject

Finance

Reference30 articles.

1. Profitability of technical trading rules among cryptocurrencies with privacy function;Ahmed;Finance Res. Lett.,2020

2. The influence of bitcoin on portfolio diversification and design;Akhtaruzzaman;Finance Res. Lett.,2019

3. Bitcoin, gold and the us dollar–a replication and extension;Baur;Finance Res. Lett.,2018

4. Cryptocurrencies and the downside risk in equity investments;Bouri;Finance Res. Lett.,2019

5. The volatility surprise of leading cryptocurrencies: transitory and permanent linkages;Bouri;Finance Res. Lett.,2019

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2. Optimizing investment portfolios with a sequential ensemble of decision tree-based models and the FBI algorithm for efficient financial analysis;Applied Soft Computing;2024-06

3. Portfolio optimization and risk management through Hierarchical Risk Parity and Logic Learning Machine: a case study applied to the Turkish stock market;RISK MANAGEMENT MAGAZINE;2024-04

4. Artificial intelligence in Finance: a comprehensive review through bibliometric and content analysis;SN Business & Economics;2024-01-20

5. Two Empirical Studies of Portfolio Optimization Using Cryptocurrency Allocation Ratios;IEEE Access;2024

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