Hierarchical risk parity portfolio design of traditional risky assets and cryptocurrencies in the Philippines

The Philippines saw the heightened interest of the investing public in cryptocurrencies when digital assets began gaining popularity, especially during the COVID-19 pandemic. This study introduces a portfolio of bonds, stocks, and foreign currency in the Philippines, combined with cryptocurrencies, by applying a method based on graph theory and machine learning techniques – the hierarchical risk parity approach. An out-of-sample comparison with traditional portfolio strategies shows that the hierarchical risk parity portfolio outperforms in terms of risk-adjusted return. The identified optimal portfolio reveals that only a small portion of the investment shall be allocated to cryptocurrencies, and much of the capital should still be with conventional assets

Understanding the effect of Raphanus sativus extract on the pathogenesis of chronic myeloid leukemia, breast and colon cancer through mathematical modeling

Chronic myeloid leukemia (CML), breast, and colon cancer are among the most prevalent types of cancer in the Philippines. In most of the cancer cases reported annually, cancer is only detected when it is on its advance stage due to the lack of early detection and limited options of targeted therapies. There are studies that show different effects of Raphanus sativus (radish) extract on different cancer diseases. However, it is still unknown why it has different effects on different cancer diseases. Therefore, understanding disease dynamics would help in improving prognosis and diagnosis. In this study, we propose a mathematical model that would explain the effect of Raphanus sativus extract on the pathogenesis of CML, breast and colon cancer. Since p53 is one of the most extensively studied gene in the field of cancer research and Cyclin D1-CDK complex is one of the more frequently altered cell cycle regulators in cancers, these genes are the focus for the basis of the effectiveness of the drug. Based on our simulations, we have showed that a 99.99%, 99.68%, and 98.96% decrease in the steady-state concentration of p53 are observed in breast cancer, colon cancer, and CML, respectively, after the drug was inserted in the model. Moreover, Cyclin D1-CDK complex\u27s steady-state concentration is decreased by 99.91% in breast cancer, 99.89% in colon cancer, and 98.50% in CML. Hence, the model suggests that Raphanus sativus extract is highly effective on breast cancer followed by colon cancer and CML