This paper examines the asymptotic and finite-sample properties of tests of equal forecast accuracy when the models being compared are overlapping in the sense of Vuong (1989). Two models are overlapping when the true model con- tains just a subset of variables common to the larger sets of...

This paper examines the asymptotic and fi nite-sample properties of tests of equal forecast accuracy when the models being compared are overlapping in the sense of Vuong (1989). Two models are overlapping when the true model contains just a subset of variables common to the larger sets of...

In this note we provide simulation evidence on the size and power of tests of predictive ability described in Giacomini and White (2006). Our goals are modest but non-trivial. First, we establish that there exist data generating processes that satisfy the null hypotheses of equal finite-sample...

We investigate a test of equal predictive ability delineated in Giacomini and White (2006; Econometrica). In contrast to a claim made in the paper, we show that their test statistic need not be asymptotically Normal when a fixed window of observations is used to estimate model parameters. An example...

Inflation expectation is acknowledged to be an important indicator for policy makers and financial investors. To capture a more accurate real-time estimate of inflation expectation on the basis of financial markets, we propose an arbitrage-free model across different countries in a...

This paper contributes to model the industry interconnecting structure in a network context. General predictive model (Rapach et al. 2016) is extended to quantile LASSO regression so as to incorporate tail risks in the construction of industry interdependency networks. Empirical results show a...

In the present paper we propose a new method, the Penalized Adaptive Method (PAM), for a data driven detection of structure changes in sparse linear models. The method is able to allocate the longest homogeneous intervals over the data sample and simultaneously choose the most proper variables...

When constructing unconditional point forecasts, both direct- and iterated-multistep (DMS and IMS) approaches are common. However, in the context of producing conditional forecasts, IMS approaches based on vector autoregressions (VAR) are far more common than simpler DMS models. This is despite...

Limit order book contains comprehensive information of liquidity on bid and ask sides. We propose a Vector Functional AutoRegressive (VFAR) model to describe the dynamics of the limit order book and demand curves and utilize the tted model to predict the joint evolution of the liquidity demand...