This paper aims to examine the role of macroeconomic variables in forecasting the return volatility of the US stock market. We apply the GARCH-MIDAS (Mixed Data Sampling) model to examine whether information contained in macroeconomic variables can help to predict shortterm and long-term components of the return variance. We investigate several alternative models and use a large group of economic variables. A principal component analysis is used to incorporate the information contained in different variables. Our results show that including lowfrequency macroeconomic information into the GARCH-MIDAS model improves the prediction ability of the model, particularly for the long-term variance component. Moreover, the GARCH-MIDAS model augmented with the first principal component outperforms all other specifications, indicating that the constructed principal component can be considered as a good proxy of the business cycle.

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Five new isoprenylated flavones, artochamins A-E (1-5), together with eight known flavones (6-13), were isolated from the roots of Artocarpus chama. All structures were elucidated by spectroscopic methods. Artonin E (12) showed strong cytotoxicity against 1A9 (ovarian), significant activity against MCF-7 (breast adenocarcinoma), and moderate activity against HCT-8 (ileocecal) and MDA-MB-231 (breast adenocarcinoma) tumor cell lines. Artochamin C (3) was more potent against MCF-7, 1A9, HCT-8, and SK-MEL-2 (melanoma) than A549 (lung carcinoma), KB (epidermoid carcinoma of the nasopharynx), and its drug-resistant (KB-VIN) variant. Artocarpin (6) displayed weak but relatively broad inhibitory effects compared with 3 and 12.

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