This paper extends and generalizes the BDS test presented by Brock, Dechert, Scheinkman, and LeBaron (1996). In doing so it aims to remove the limitation of having to arbitrarily select a proximity parameter by integrating across the correlation integral. The Monte Carlo simulation is used to...

Propensity score matching estimators have two advantages. One is that they overcome the curse of dimensionality of covariate matching, and the other is that they are nonparametric. However, the propensity score is usually unknown and needs to be estimated. If we estimate it nonparametrically, we...

Propensity score matching estimators have two advantages. One is that they overcome the curse of dimensionality of covariate matching, and the other is that they are nonparametric. However, the propensity score is usually unknown and needs to be estimated. If we estimate it nonparametrically, we...

This paper is concerned with the study of some fundamental aspects of the BDS test. Brock, Dechert, Scheinkman & LeBaron (Econometric Reviews, 1996) propose this non-parametric tool as a test of the null hypothesis of an independently and identically distributed (i.i.d.) time series, with power...

For many countries located around the equatorial region, climate phenomenon such as El Niño southern oscillation or ENSO has enormous impact on their economies. In the case of countries with a high degree of dependency on water resources for energy generation, the impact of ENSO has been...

In nonlinear state-space models, sequential learning about the hidden state can proceed by particle filtering when the density of the observation conditional on the state is available analytically (e.g. Gordon et al. 1993). This condition need not hold in complex environments, such as the...

Macroprudential stress testing (MaPST) is becoming firmly embedded in the post-crisispolicy-frameworks of financial-sectors around the world. MaPSTs can offer quantitative,forward-looking assessments of the resilience of financial systems as a whole, to particularlyadverse shocks. Therefore,...

Tail risk refers to the possibility that a rare event would adversely affect the value of a portfolio in a significant manner. It became much more relevant due to recent periods of strong market turbulence.We describe how to quantify such risk, which tail risk protection strategies were...

Recent periods of market turbulence and stress have created considerable interest in credible alternatives to traditional asset allocation methodologies. It would be preferred if portfolios can be decomposed into components that can be directly connected to independent risks and individually...