The Standard & Poor's 500 Volatility Index (VIX), a common measure of market sentiment, is found to be significantly correlated with the Global Consciousness Projects (GCP) data. More specifically, the largest daily composite GCP data value (Max[Z]) is found to significantly covary with changes in VIX. The results indicate that the GCP data can help in understanding market sentiment and that daily market movements can be better comprehended by acknowledging variations in the GCP data. As such, the results suggest that the GCP data can be put to practical use by traders, which is investigated by fitting econometric models that either utilize or ignore the GCP data on daily S&P 500 returns. Highly significant interaction terms are found both with the VIX and with daily returns from markets traded in both Europe and Asia. Additionally, it is found that recognizing such interactions can explain about one percent of the econometric model's variance. To mitigate the possibility of overfitting and P-hacking, the models are put to a practical test in an out-of-sample simulation study lasting for a predefined period of one year. In the out-of-sample simulation, an artificial trader uses S&P 500 tracking instruments and trades in accordance with the econometric model's one day ahead forecasts. The results from the out-of-sample simulations suggest that GCP data can enhance daily forecasts, making it a valuable resource for traders.