We consider the problem of estimating the volatility of a financial asset from a time series record of length T. We believe the underlying volatility process is smooth, possibly stationary, and with potential abrupt changes due to market news. By drawing parallels between time series and...

We consider Taylor’s stochastic volatility model (SVM) when the innovations of the hidden log-volatility process have a Laplace distribution (ℓ <Subscript>1</Subscript> exponential density), rather than the standard Gaussian distribution (ℓ <Subscript>2</Subscript>) usually employed. Recently many investigations have employed ℓ <Subscript>1</Subscript>...</subscript></subscript></subscript>

This paper proposes a simple procedure to test the hypothesis of no cointegration against both threshold cointegration and an intermediate possibility that we call partial cointegration. Asymptotic theory is devel- oped, the power of the proposed test is analysed through simulations and an...

In this note, we investigate a test for the existence of a middle "band of inaction" in a three-regime threshold vector error correction model (TVECM). For this purpose we propose a supremum Wald statistic, derive its limiting distribution and calculate its critical values through simulations.

In this paper a three-regime multivariate threshold vector error correction model (TVECM) with a "band of inaction" is formulated to examine the expectation hypothesis of the term structure (EHTS) of interest rates and uncovered interest rate parity (UIRP) for U.S. and Swiss rates. Tests for no...

The paper generalises estimation and inference procedures for a threshold VECM with more than one cointegrating relation. We derive estimators of long-run parameters and loading factors by means of a reduced rank regression. We provide their asymptotic distributions and propose a testing...

The proposed smooth blockwise iterative thresholding estimator (SBITE) is a model selection technique defined as a fixed point reached by iterating a likelihood gradient-based thresholding function. The smooth James--Stein thresholding function has two regularization parameters λ and ν, and a...

For the problem of estimating a sparse sequence of coefficients of a parametric or non-parametric generalized linear model, posterior mode estimation with a Subbotin("λ","ν") prior achieves thresholding and therefore model selection when "ν"   is an element of    <b>[0,1]</b> for a class...

Time series of financial asset values exhibit well known statistical features such as heavy tails and volatility clustering. Strongly present in some series, nonstationarity is a feature that has been somewhat overlooked. This may however be a highly relevant feature when estimating extreme...