We derive a Bayesian prior from a no-arbitrage affine term structure model and use it to estimate the coefficients of a vector autoregression of a panel of government bond yields, specifying a common time-varying volatility for the disturbances. Results based on US data show that this method...

We define a disastrous default as the default of a systemic entity. Such an event is expected to have a negative effect on the economy and to be contagious. Bringing macroeconomic structure to a noarbitrage asset-pricing framework, we exploit prices of disaster-exposed assets (credit and equity...

No-arbitrage dynamic term structure models (DTSMs) have regularly been used to estimate interest rate expectations and term premia, but are beset by empirical challenges. I propose augmenting DTSMs with overnight indexed swap (OIS) rates to better estimate the decomposition along the term...

We define a disastrous default as the default of a systemic entity, which has a negative effect on the economy and is contagious. Bringing macroeconomic structure to a no-arbitrage asset pricing framework, we exploit prices of disaster-exposed assets (credit and equity derivatives) to extract...

I provide evidence on the existence of unspanned macro risk. I investigate the usefulness of unspanned macro information for forecasting bond risk premia in a macro-finance term structure model from the perspective of a bond investor. I account for model uncertainty by combining forecasts with...

There is no consensus on whether macroeconomic fundamentals have any predictive power for bond risk premia, either unconditionally or conditionally over bond yields. Using Adaptive Group LASSO, a machine learning algorithm, we are able to construct a new, parsimonious macro variable that is...

The purpose of this study is to suggest a new framework that we call the CIR#, which allows forecasting interest rates from observed financial market data even when rates are negative. In doing so, we have the objective is to maintain the market volatility structure as well as the analytical...

The purpose of this paper is to model interest rates from observed financial market data through a new approach to the Cox–Ingersoll–Ross (CIR) model. This model is popular among financial institutions mainly because it is a rather simple (uni-factorial) and better model than the former...

The Polynomial Chaos Expansion (PCE) technique recovers a finite second order random variable exploiting suitable linear combinations of orthogonal polynomials which are functions of a given stochastic quantity $\xi$, hence acting as a kind of random basis. The PCE methodology has been developed...

Procyclical assets tend to rise in value when the economy is expanding and fall with the advent of a recession. Countercyclical assets are instead negatively correlated with the state of the economy. Despite the use of optimization methods, hedging, and ad hoc rebalancing techniques most...