Systemic risk,real GDP growth,and sentiment

Review of Quantitative Finance and Accounting - Using a mixed frequency VAR methodology, which can accommodate variables with different frequencies in a VAR framework, we model the relation between...     

Comparing linear and nonlinear forecasts for stock returns

We compare the out-of-sample performance of monthly returns forecasts for two indices, namely the Dow Jones (DJ) and the Financial Times (FT) indices. A linear and a nonlinear artificial neural network (ANN) model are used to generate the out-of-sample competing forecasts for monthly returns. Stationary transformations of dividends and trading volume are considered as fundamental explanatory variables in the linear model and the input variables in the ANN model. The comparison of out-of-sample forecasts is done on the basis of forecast accuracy, using the Diebold and Mariano test [J. Bus. Econ. Stat. 13 (1995) 253.], and forecast encompassing, using the Clements and Hendry approach [J. Forecast. 5 (1998) 559.]. The results suggest that the out-of-sample ANN forecasts are significantly more accurate than linear forecasts of both indices. Furthermore, the ANN forecasts can explain the forecast errors of the linear model for both indices, while the linear model cannot explain the forecast errors of the ANN in either of the two indices. Overall, the results indicate that the inclusion of nonlinear terms in the relation between stock returns and fundamentals is important in out-of-sample forecasting. This conclusion is consistent with the view that the relation between stock returns and fundamentals is nonlinear.     

The impact of prompt corrective action on the default risk of the U.S. commercial banking sector

As the Basel III reforms, which come into effect from 2012, place emphasis on default risk, assessing the impact of Prompt Corrective Action (PCA) on default risk is of practical relevance. We provide strong evidence that both the dynamic and the contemporaneous impact of the PCA-defined tier 1 risk-based capital ratio and the tier 1 leverage ratio on default risk is reduced following PCA’s introduction. We interpret this as evidence that PCA is effective in managing the default risk of the U.S. commercial banking sector.     

Semi-parametric real exchange rates dynamics

Review of Quantitative Finance and Accounting - A flexible semi-parametric augmented Dickey Fuller (ADF) regression is proposed to explore real exchange rate dynamics for 16 countries over the...     

Systemic risk-shifting in U.S. commercial banking

Review of Quantitative Finance and Accounting - This paper puts forward the proposition that U.S. commercial banks use dividends as a mechanism to shift systemic risk to debt-holders and the...     

Bank dividends,risk, and regulatory regimes

This paper investigates the relation between bank dividends and bank risk over the period 1984–2011, and assesses the existence of risk-taking and risk-shifting in the US commercial banking sector subject to regulatory regime changes. The introduction of PCA in 1992 and TARP in 2008 constitute significant regulatory regime changes, and provide the necessary framework to explore whether regime-dependent risk-shifting or risk-taking is present. We find strong evidence of risk-shifting and risk-taking over the post-PCA regime spanning the period 1992–2008. We interpret this evidence as indication of ineffectiveness of PCA in controlling risk-taking and risk-shifting. The finding of risk-taking just prior to the recent financial crisis suggests that risk-taking may be a factor contributing to this crisis. As risk-taking and risk-shifting are important aspects of bank behavior (Basel Committee on Banking Supervision, 2009), these results are of interest to bank regulators and important to Basel III.     

Mean and Variance Causality between Official and Parallel Currency Markets: Evidence from Four Latin American Countries

This paper examines the issue of mean and variance causality across four Latin American official and black markets for foreign currency using monthly data for the period 1976–1993. We apply a recent test developed by Cheung and Ng (1996) in order to test for mean and variance spillovers. The main findings are: (1) In contrast to the findings of previous studies, EGARCH-M processes characterize each bilateral exchange rate series in both markets; (2) There is substantial evidence of causality in both mean and variance with the causality in mean largely being driven by the causality in variance; and (3) The results indicate that the major exporter of causality is the Mexican black market with the black market of Argentina and the black and official markets of Brazil being the smallest contributors.     

How do employee training and knowledge stocks affect product innovation?

The main purpose of this paper is to explore how interactions of knowledge flows and knowledge stocks could shape firms’ innovative performance. Knowledge flows are measured on the grounds of human resource training practices while different levels and forms of knowledge stocks (i.e. educational attainment, exporting activity, and firm age) are considered. We make use of two-period panel probit regressions and a rich data survey of the 524 largest Greek manufacturing firms conducted in two waves (2011 and 2013). Our findings suggest that the beneficial effects of knowledge flows strengthen when knowledge stocks accumulated by employees’ education and firm age are low. When knowledge stocks are limited, knowledge flows can act as a bridge for product innovation. On the contrary, when knowledge stocks are high, higher investments in knowledge flows may lead to diminishing returns and, thus, to decreased innovation performance beyond a certain point.     

Lead-lag effects in the mean and variance of returns of size-sorted UK equity portfolios

We test for lead-lag effects in the mean and variance among size-sorted portfolios for the UK stock market. We construct three sets of portfolios, namely a set of size-sorted equally-weighted portfolios of different capitalization size, a set of size-sorted value-weighted portfolios of different capitalization size, and a third set of portfolios of the same capitalization size. The recently proposed Cross Correlation Function test is employed. For both sets of portfolios with different capitalization size, we find evidence of a lead effect in both the mean and the variance from large-firm portfolios to small-firm portfolios. This result does not depend on the weighting scheme used to construct portfolios, and indicates that contrarian trading strategies on large-firm portfolios are profitable. For portfolios of equal capitalization size, there is hardly any evidence of a lead-lag effect in either the mean or the variance. This suggests that the lead-lag effect is due to the difference in the capitalization size among portfolios.I wish to thank two anonymous referees for helpful comments on a previous draft of this paper. The usual disclaimer applies.ing scheme.First version received: February 2002/Final version received: May 2003     

The risk-return relation and VIX: evidence from the S&P 500

A significantly positive risk-return relation for the S&P 500 market index is detected if the squared implied volatility index (VIX) is allowed for as an exogenous variable in the conditional variance equation of the parsimonious GARCH(1,1) model. This result holds for both daily and weekly observations, for extended conditional mean and variance specifications, and is robust to sub-samples. We show that the conditional variance obtained from the GARCH model with VIX has better predictive ability for realized volatility than the conditional variance from GARCH without VIX and VIX itself, thereby documenting an important information content of VIX for conditional variance. The results are interpreted as evidence that adding VIX squared in the conditional variance equation yields a better measure of conditional variance which, subsequently, uncovers a strong risk-return relation.