Konstantinos Gkillas

Asymmetric and nonlinear inter-relations of US stock indices

Purpose - The purpose of this paper is to examine the inter-relations among the US stock indices. Design/methodology/approach - Data of nine US stock indices spanning a period of sixteen years (2000-2015) are employed for this purpose. Asymmetries are examined via an error correction model. Non-linear inter-relations are researched via Breitung’s nonlinear cointegration, a M-G nonlinear causality model, shocks to the forecast error variance, a shock spillover index and an asymmetric VAR-GARCH (VAR-ABEKK) approach. Findings - The inter-relations are signi?cant. The results are robust across all types of inter-relations. They are highest in the Lehman Brothers sub-period. Higher stability after the EU debt crisis, enhances independence and growth for the US stock indices. Originality/value - To the best of the knowledge, this is the first study to examine the inter-relations of US stock indices. Most studies on inter-relations concentrate on the portfolio analysis to reveal diversification benefits among various asset markets internationally. Hence this study contributes to this literature on the inter-relations of a specific asset market (stock), and in a specific nation (USA). The evident inter-relations support the notion of diversification benefits in the US stock markets.

The effect of the european economic news releases to the US financial markets in the crisis period

This paper evaluates the effect of all European economic news releases on the US financial markets for the main crisis period from June 2007 up to October 2011. Evaluation concerns Sharpe ratios, as well as magnitude and frequency of volatility jumps for the periods before and after a news release. Sharpe ratios are examined with the risk of the excess returns being estimated by the flat-top Bartlett kernel estimator of Barndorff-Nielsen et al. (2008) with an optimal (in a finite sample) choice for the number of autocovariances, as suggested by Bandi and Russell (2011). Volatility jumps are detected according to the jump detection scheme of Ait-Sahalia and Jacod (2009).

Asymmetric Exceedance-Time Model: An Optimal Threshold Approach Based on Extreme Value Theory

We propose an innovative asymmetric exceedance-time model with optimal thresholds. This model examines the impact of extreme downside and upside shocks and determines how the duration between past and present extreme shocks affects the dependent variable. We use extreme value theory (peak-over-threshold method) to model extremes, proposing a procedure for the automatic computation of optimal thresholds, at the point where the fitting of the extreme value distribution is maximized. We apply our model to S&P 500 equity index and GBP/USD exchange rate data and show that a strong statistical relation coincides with optimal threshold levels.

The Impact of Greek Economic News on European Financial Markets. Evidence from the European Sovereign Debt Crisis

This chapter examines the impact of Greek economic news on European government bond, CDS, and stock markets. The impact of three categories of news is examined via the respective number of dummy variables, number of news per month, and news surprises of 2-year, 5-year, and 10-year government bonds and CDS on return, volatility, volatility jump, correlation, and correlation jump of government bonds, CDS, and stock indices of seven European countries, within a tobit regression framework. This chapter also discusses the implications of Greek economic news to policy actions. Recommendations driven by results are made to policy makers as well.

Economic News Releases and Financial Markets in South Africa

We examine the impact of economic news releases on returns, volatility and jumps of the stock and foreign exchange markets of South Africa. We also assess the impact of macroeconomic determinants. The dataset range is fifteen years covering the period from January, 2000 to December, 2014. Results are robust to different sub-periods before and after the global financial crisis of 2008. Volatility is estimated with the use of the median realized variance estimator. Jumps are also detected. The impact of the announcements is assessed building using regression techniques. Returns, volatility and jumps of both stock and foreign exchange markets are significantly explained nationally by macroeconomic fundamentals and economic news releases.