This paper aims to examine the long term relationship between German and three Central and Eastern Europe (CEE) equity markets. Application of Johansen as well as Engle-Granger cointegration tests show that there is no long-term relationship among these markets while the Gregory-Hansen...

The study aims to reveal the relationship between Twittersentiments indicators and stock market indicators, with referenceto BSE and NSE in India. This study used secondary dailytime-series data, for a period of two years, from 01.01.2018 to31.12.2019. Statistical tools, such as Descriptive...

This study examines the lead-lag-relationship between European equity and CDS markets in the context of the financial crisis. Previous research identified the stock market to lead the CDS market in an ordinary economic environment. Against the background of our study this lead-lag-relationship...

This paper contains an empirical analysis of determinants of international integration projects over the time period 1995-2010. After a broad discussion of the existent literature, the investigation combines a large number of potentially relevant determinants for the explanation of whether stock...

In almost all stages of forecasting volatility, certain subjective decisions need to be made. Despite of an enormous literature in the area, these subjectivities are hindrances to reaching an overall conclusion on the performances of the models. In order to find out outperforming model in...

In an effort to address the lacuna in leading indicator studies of African economies and Nigeria in particular, this paper examines the causal relationships among stock market prices, real GDP and the index of industrial production in Nigeria, using quarterly data from 1984Q1 to 2008Q4. Granger...

This paper aims to forecast the Market Risk premium (MRP) in the US stock market by applying machine learning techniques, namely the Multilayer Perceptron Network (MLP), the Elman Network (EN) and the Higher Order Neural Network (HONN). Furthermore, Univariate ARMA and Exponential Smoothing...

This paper examines the evidence regarding predictability in the market risk premium using artificial neural networks (ANNs), namely the Elman Network (EN) and the Higher Order Neural network (HONN), univariate ARMA and exponential smoothing techniques, such as Single Exponential Smoothing (SES)...

Examinations of the dynamics of daily returns and volatility in stock markets of the US, Hong Kong and mainland China (Shanghai and Shenzhen) over 2 January 2001 to 8 February 2013 suggest: (1) evidence of unidirectional return spillovers from the US to the other three markets; but no spillover...

Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by inflation and interest rate expectations as well...