This study has been inspired by the emergence of socially responsible investment practices in mainstream investment activity wherein it examines the transmission of return patterns between green bonds, carbon prices, and renewable energy stocks using daily data spanning from 1st January 2013 to...

We develop FinText, a novel, state-of-the-art, financial word embedding from Dow Jones Newswires Text News Feed Database. Incorporating this word embedding in a machine learning model produces a substantial increase in volatility forecasting performance on days with volatility jumps for 23...

Although economic processes and systems are in general simple in nature, the underlying dynamics are complicated and seldom understood. Recognizing this, in this paper we use a nonstationary-conditional Markov process model of observed aggregate data to learn about and recover causal influence...

Drawing on examples of recently published and widely-cited studies in experimental economics, we show that behavioral games are frequently analyzed in a manner that is prone to biased causal inference. First, deficiencies in design and implementation jeopardize the crucial assumption that...

This paper introduces a new approach to modelling the conditional variance in a multivariate setting. It is essentially a combination of the popular GARCH model class with a spatial component, inspired by generalized space-time models. The resulting spatial GARCH model takes into account both...

It is no longer uncommon these days to find the need in actuarial practice to model claim counts from multiple types of coverage, such as the ratemaking process for bundled insurance contracts. Since different types of claims are conceivably correlated with each other, the multivariate count...

Present paper makes some comments on the conclusions of (Bonesmo Fredriksen, 2012) who claims among others that “…Furthermore, EU income inequality is found to have increased over the past 25 years, albeit at a slower pace since 2000”. My comments are that the above conclusion depends on...

In this research, the omitted variable problem in a spatial autoregressive model is analyzed by simulation. We examine the performances of estimators when an omitted variable is correlated with explanatory variables. In the literature, theoretical aspects of estimating spatial autoregressive...

Practical techniques for approximating yield given the price and price given the yield are described. Duration and convexity estimations given prices and yields at three observation points are presented. Such approximations are useful when computing prices and yields from their values at nearby...

This paper empirically investigates the effectiveness of monetary policy transmission in the Gulf Cooperation Council (GCC) countries using a structural vector autoregressive model. The results indicate that the interest rate and bank lending channels are relatively effective in influencing...