Multiple threshold regimes and macroeconomic predictors for analyzing and pricing interest rate-dependent instruments

My dissertation is motivated by the limited number of multivariate macro-finance asset pricing models which allow for (multiple threshold) regime shifts. Indeed, after more than 35 years of research on asset pricing, one of the central unresolved problems in the financial literature is the relation between the state of the economy and the prices of financial assets. The dissertation consists of three essays. The goal of the first chapter is to contribute new empirical evidence to the various economic sources driving the US yield curve. To this end, I present a methodology to build and estimate a discrete-time regime-switching model for the term structure dynamics over time. We allow the conditional dynamics of the yield at different maturities to change in reaction to past information coming from several relevant predictor variables. We consider both endogenous, yield curve factors and exogenous, macroeconomic factors as predictors in our model, letting the data themselves choose the most important variables. We find clear, different economic patterns in the local dynamics and regime specification of the yields depending on the maturity. Moreover, we present strong empirical evidence for the accuracy of the model in reproducing various stylized facts and predicting out-of-sample the yield curve in comparison to several alternative approaches. In the second chapter, we propose a simple but effective estimation procedure to extract the level and the volatility dynamics of a latent macroeconomic factor from a panel of observable indicators. Our approach is based on a multivariate conditionally heteroskedastic exact factor model that can take into account the heteroskedasticity feature shown by most macroeconomic variables and relies on an iterated Kalman filter procedure. In simulations we show the unbiasedness of the proposed estimator and its superiority to different approaches introduced in the literature. Simulation results are confirmed in applications to real inflation data with the goal of forecasting long-term bond risk premia. Moreover, we find that the extracted level and conditional variance of the latent factor for inflation are strongly related to NBER business cycles. Guided by the empirical findings presented in the previous two chapters, in the third chapter we develop a new discrete time multivariate regime-switching asset pricing framework, which takes into account the time-varying relation between the short rate and the state of the economy. Our approach combines the no-arbitrage restrictions on the cross-section of bonds together with macroeconomic factors that drive bond yields. In contrast to the classical term structure literature, where nonlinearities in the short rate are captured by increasing the number of latent state variables, or by latent regime shifts, in our framework the regimes are governed by thresholds and they are directly linked to different economic fundamentals. Specifically, starting from a simple monetary policy model for the short rate, we introduce a model for the yield curve, which takes into account not only the possibility of regime switches in the behavior of the Federal Reserve, but also agents' beliefs around these changes. In the empirical part, we show the merit of our approach along four dimensions: (i) interpretable bond dynamics; (ii) superior out-of-sample performance; (iii) design of no-arbitrage dynamic term structure model; and (iv) accurate short end yield curve pricing. Yield curve modeling and forecasting ; Macroeconomic variables ; Tree-structured models ; Threshold regimes ; Zinsrisiko ; Zinsstrukturkurve ; Aktienhandel