This paper proposes a general equilibrium model with heterogeneous households and a financial market where each financial instrument provides liquidity services in addition to enabling a transfer of purchasing power over time. Importantly, liquidity services may be asymmetric according to...

In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset using a cluster analysis technique taking into...

Intangible capital is an important factor of production in modern economies that is generally neglected in business cycle analyses. We demonstrate that intangible capital can have a substantial impact on business cycle dynamics, especially if the intangible is complementary with production...

Institutions matter greatly in the development of competitive advantage. Different institutional strategies to manipulate and shape institutions are discussed in the literature. This paper aims at extending the existing conceptual model of membership strategy. Despite being referenced...

We study the modelling of large data sets of high frequency returns using a long memory stochastic volatility (LMSV) model. Issues pertaining to estimation and forecasting of datasets using the LMSV model are studied in detail. Furthermore, a new method of de-seasonalising the volatility in high...

From the onset of the 2007-2009 crisis, the Federal Reserve and the European Central Bank have aggressively lowered interest rates. Both sets of changes are at odds with an anti-inflationary stance of monetary policy; indeed, as the crisis began in August 2007 inflation expectations were high...

This paper proposes a very general time series framework to capture the long-run behaviour of financial series. The suggested model includes linear and non-linear time trends, and stationary and nonstationary processes based on integer and/or fractional degrees of differentiation. Moreover, the...

In recent years support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a moving...