This paper develops a methodology for estimating a conditional CAPM with time-varying betas and regime changes in conditional variance dynamics. Our research goal is related to documenting the strength of the market factor alone in the financial and commodity markets. Among stocks, there are significant time variations in betas across our models and regimes. This empirical feature is even more pronounced among prominent stocks such as the USA, the UK, Germany, France, China, and Malaysia. Among commodities, we find significant variations in betas, but the direction of the relation with market returns for crude oil, gold, copper, tin, rubber, aluminum and platinum is the same across two of our models. This result also holds for aggregate markets where most variations are found in the MS-GARCH model. Secondly, the mean filtered volatility results from the regime switching GARCH-CAPM shows that the most volatile stock (Turkey) is more than twice and thrice respectively, more volatile than the most volatile commodity (Rhodium) and aggregate market (World). Lastly, we demonstrate that the regime switching model delivers better estimates of one-day-ahead Value-at-Risk and that Expected Shortfall is highest for China but least for Latvia.