Algorithmic traders acknowledge that their models are incorrectly specified, thus we allow for ambiguity in their choices to make their models robust to misspecification in: (i) the arrival rate of market orders (MOs), (ii) the fill probability of limit orders, and (iii) the dynamics of the...

We explore Knightian model uncertainty as an explanation for the observed excess persistence and attenuation in estimated interest-rate reaction functions for the United States, relative to what optimal feedback rules would suggest. Two types of uncertainty are identified: (i) unstructured model...

The valuation of multi-staged pharmaceutical R&D can be interpreted as a chain of real options. In valuing these compound option models, a crucial problem is how to deal with the different types of risk. Previous models, such as Cassimon et al. (2004), offer a closed-form solution for the...

In his 1999 monograph The Conquest of American Inflation Tom Sargent describes how a policymaker, who applies a constant-gain algorithm in estimating the Phillips curve, can fall into the grip of an induction problem: concluding on the basis of reduced-form evidence that the trade-off between...

This paper explores Knightian model uncertainty as a possible explanation of the considerable difference between estimated interest rate rules and optimal feedback descriptions of monetary policy. We focus on two types of uncertainty: (i) unstructured model uncertainty reflected in additive...

This paper analyzes the optimality of reactive feedback rules advocated by neo-Keynesians, and constant growth rules proposed by monetarists. The basis for this controversy is not merely a disagreement concerning sources and impacts of uncertainty in the economy, but also an apparent fundamental...

In this paper, I present the implementation of Portfolio Risk Measures in Python 3.5. Several Risk Measures such as VaR, CVaR and MVaR are adopted and different methodologies of computation are showed: Parametric and Historical. The portfolio is dinamical in the sense that each day computes the...

The purpose of this research is the realistic forecast of volatility in frame of a risk parity class of strategies. The custom rescaling of volatility – naïve risk parity - doesn't consider market inefficiencies which correspond to cyclical patterns like crisis and the following recovery. The...