We propose a portfolio selection model based on a class of monotone preferences that coincide with mean-variance preferences on their domain of monotonicity, but differ where mean-variance preferences fail to be monotone and are therefore not economically meaningful. The functional associated with this new class of preferences is the best approximation of the mean-variance functional among those which are monotonic. We solve the portfolio selection problem and we derive a monotone version of the capital asset pricing model (CAPM), which has two main features: (i) it is, unlike the standard CAPM model, arbitrage free, (ii) it has empirically testable CAPM-like relations. The monotone CAPM has thus a sounder theoretical foundation than the standard CAPM and a comparable empirical tractability.

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We derive a canonical representation for the no-arbitrage discrete-time term structure models with both observable and unobservable state variables, popularized by Ang and Piazzesi (2003). We conduct a specification analysis based on this canonical representation and we analyze how alternative parameterizations affect estimated risk premia, impulse response functions, and variance decompositions. We find a trade-off between the need to obtain parsimonious parameterizations and the ability of the models to match observed patterns of variation in risk premia. We also find that more richly parameterized models uncover a greater influence of macroeconomic fundamentals on the long-end of the yield curve. Copyright (c) 2008 The Ohio State University.

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Term structure models are routinely used by central banks to assess the impact of their communication on market participants' expectations for interest rates. But some recent studies have shown that the traditional term structure models may be misleading when policy rates are at the zero lower bound, one reason being that such models cannot reproduce the stylized fact that once policy rates reach the ZLB they tend to remain there for a prolonged period. A consensus has now emerged that shadow rate models, pioneered by Black (1995), can solve this problem. The thesis is that the "shadow rate" (the short-term interest rate that would prevail in the absence of the ZLB) can stay in negative territory for long time spans even when the actual rate remains close to the ZLB. Since they are strongly non-linear, shadow rate models are especially hard to estimate, and to date the literature has used only approximate methods to this end. Instead, we propose an exact Bayesian method of estimation and apply it to developments in the euro and dollar yield curves since the end of the 1990s. Our estimates confirm and provide a quantitative measure of quantify the significant divergence of monetary policies between the euro area and the US: between 2009 and 2013, the shadow rate was much lower in the US than in the euro area, and since then the opposite has been the case. At the end of our sample period in January 2015, according to our model the most likely date for the the first increase in policy rates was estimated to be mid-2015 in the US and 2020 in the euro area.