Kocenda (2001) introduced the test for nonlinear dependencies in time series data based on the correlation integral. The idea of the test is to estimate the correlation dimension by integrating over a range of proximity parameter. However, there is an unexplored avenue if one wants to use the...

This paper builds on Kocenda (2001) and extends it in two ways. First, two new intervals of the proximity parameter ε (over which the correlation integral is calculated) are specified. For these ε-ranges new critical values for various lengths of the data sets are introduced and through Monte...

GLOBAL FINANCE LIQUIDITY RISK REVISITED: Development of A Framework for Liquidity Assessment in Portfolio Construction Process: Presentations to the JP Morgan Global Head of Quant Research & Analytics and US Head of Portfolio Construction Teams:Presentations To: JP Morgan Global Head of Quant...

GLOBAL FINANCE LIQUIDITY RISK REVISITED: JP Morgan Alternative Assets Portfolio Liquidity Assessment Framework & Models: $500 Billion Fund of Funds: 17 Asset ClassesPresentations atJP Morgan World HQ, 270 Park Ave, Manhattan, NY, USAToJP Morgan Global Head of Quant Research & Analytics, JP...

We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids. The Smolyak operator underlying the sparse grids approach frees global approximation from the curse of dimensionality and we apply it to a Chebyshev approximation of the...

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,...