Despite substantial criticism, variants of the capital asset pricing model
(CAPM) remain to this day the primary statistical tools for portfolio
managers to assess the performance of financial assets. In the CAPM, the
risk of an asset is expressed through its correlation with the market,
widely known as the beta. There is now a general consensus among economists
that these portfolio betas are time-varying and that, consequently, any
appropriate analysis has to take this variability into account. Recent
advances in data acquisition and processing techniques have led to an
increased research output concerning high-frequency models. Within this
framework, we introduce here a modified functional CAPM and sequential
monitoring procedures to test for the constancy of the portfolio betas. As
our main results we derive the large-sample properties of these monitoring
procedures. In a simulation study and an application to S&P 100 data we
show that our method performs well in finite samples.