This paper gauges the benefits of adding asset swap spreads in a real-time fashion to mitigate the usual caveats of asynchronous and lagging macroeconomic information in nowcasting models. This works sheds light on the capability of this weekly information to correctly assess the business cycle phases. We build upon the existing literature of Markov-Switching dynamic factor models a dynamic variance extension in the factor auto-regressive behavior. We show the advantage of the weekly market information flow, especially when applied to macro-based allocation strategies. The analysis is carried out on the United States. Asset swap spreads used as market sentiment proxy of current macroeconomic conditions improve the turning point detection process but also the risk/return couple of the implemented allocation strategies whenever a real-time macro dataset is used.