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This article applies a three-regime Markov switching model to investigate the impact of the macroeconomy on the dynamics of the residential real estate market in the US. Focusing on the period between 1960 and 2011, the methodology implemented allows for a clearer understanding of the drivers of the real estate market in "boom", "steady-state" and "crash" regimes. Our results show that the sensitivity of the real estate market to economic changes is regimedependent. The paper then proceeds to examine whether policymakers are able to influence a regime switch away from the crash regime. We find that a decrease in interest rate spreads could be an effective catalyst to precipitate such a change of state.

This paper investigates the forecasting performance for CDS spreads of both linear and non-linear models by analysing the iTraxx Europe index during the financial crisis period which began in mid-2007. The statistical and economic significance of the models' forecasts are evaluated by employing various metrics and trading strategies, respectively. Although these models provide good in-sample performances, we find that the non-linear Markov switching models underperform linear models out-of-sample. In general, our results show some evidence of predictability of iTraxx index spreads. Linear models, in particular, generate positive Sharpe ratios for some of the strategies implemented, thus shedding some doubts on the efficiency of the European CDS index market.JEL classification: G01; G17; G20; C22; C24