Modelling and testing volatility spillovers in oil and financial markets for USA, UK and China

The primary purpose of the paper is to analyze the conditional correlations, conditional covariances, and co-volatility spillovers between international crude oil and associated financial markets. The paper investigates co-volatility spillovers (namely, the delayed effect of a returns shock in one physical or financial asset on the subsequent volatility or co-volatility in another physical or financial asset) between the oil and financial markets. The oil industry has four major regions, namely North Sea, USA, Middle East, and South-East Asia. Associated with these regions are two major financial centers, namely UK and USA. For these reasons, the data to be used are the returns on alternative crude oil markets, returns on crude oil derivatives, specifically futures, and stock index returns in UK and USA. The paper will also analyze the Chinese financial markets, where the data are more recent. The empirical analysis will be based on the diagonal BEKK model, from which the conditional covariances will be used for testing co-volatility spillovers, and policy recommendations. Based on these results, dynamic hedging strategies will be suggested to analyze market fluctuations in crude oil prices and associated financial markets.

Testing co-volatility spillovers for natural gas spot, futures and ETF spot using dynamic conditional covariances

There is substantial empirical evidence that energy and financial markets are closely connected. As one of the most widely-used energy resources worldwide, natural gas has a large daily trading volume. In order to hedge the risk of natural gas spot markets, a large number of hedging strategies can be used, especially with the rapid development of natural gas derivatives markets. These hedging instruments include natural gas futures and options, as well as Exchange Traded Fund (ETF) prices that are related to natural gas stock prices. The volatility spillover effect is the delayed effect of a returns shock in one physical, biological or financial asset on the subsequent volatility or co-volatility of another physical, biological or financial asset. Investigating volatility spillovers within and across energy and financial markets is a crucial aspect of constructing optimal dynamic hedging strategies. The paper tests and calculates spillover effects among natural gas spot, futures and ETF markets using the multivariate conditional volatility diagonal BEKK model. The data used include natural gas spot and futures returns data from two major international natural gas derivatives markets, namely NYMEX (USA) and ICE (UK), as well as ETF data of natural gas companies from the stock markets in the USA and UK. The empirical results show that there are significant spillover effects in natural gas spot, futures and ETF markets for both USA and UK. Such a result suggests that both natural gas futures and ETF products within and beyond the country might be considered when constructing optimal dynamic hedging strategies for natural gas spot prices.

A model for the time-order error in contrast discrimination.

Trials in a temporal two-interval forced-choice discrimination experiment consist of two sequential intervals presenting stimuli that differ from one another as to magnitude along some continuum. The observer must report in which interval the stimulus had a larger magnitude. The standard difference model from signal detection theory analyses poses that order of presentation should not affect the results of the comparison, something known as the balance condition (J.-C. Falmagne, 1985, in Elements of Psychophysical Theory). But empirical data prove otherwise and consistently reveal what Fechner (1860/1966, in Elements of Psychophysics) called time-order errors, whereby the magnitude of the stimulus presented in one of the intervals is systematically underestimated relative to the other. Here we discuss sensory factors (temporary desensitization) and procedural glitches (short interstimulus or intertrial intervals and response bias) that might explain the time-order error, and we derive a formal model indicating how these factors make observed performance vary with presentation order despite a single underlying mechanism. Experimental results are also presented illustrating the conventional failure of the balance condition and testing the hypothesis that time-order errors result from contamination by the factors included in the model.

The difference model with guessing explains interval bias in two-alternative forced- chocice detection procedures

The standard difference model of two-alternative forced-choice (2AFC) tasks implies that performance should be the same when the target is presented in the first or the second interval. Empirical data often show “interval bias” in that percentage correct differs significantly when the signal is presented in the first or the second interval. We present an extension of the standard difference model that accounts for interval bias by incorporating an indifference zone around the null value of the decision variable. Analytical predictions are derived which reveal how interval bias may occur when data generated by the guessing model are analyzed as prescribed by the standard difference model. Parameter estimation methods and goodness-of-fit testing approaches for the guessing model are also developed and presented. A simulation study is included whose results show that the parameters of the guessing model can be estimated accurately. Finally, the guessing model is tested empirically in a 2AFC detection procedure in which guesses were explicitly recorded. The results support the guessing model and indicate that interval bias is not observed when guesses are separated out.

Enhanced noradrenergic activity in the amygdala contributes to hyperarousal in an animal model of PTSD

Increased activity of the noradrenergic system in the amygdala has been suggested to contribute to the hyperarousal symptoms associated with post-traumatic stress disorder (PTSD). However, only two studies have examined the content of noradrenaline or its metabolites in the amygdala of rats previously exposed to traumatic stress showing inconsistent results. The aim of this study was to investigate the effects of an inescapable foot shock (IFS) procedure 1) on reactivity to novelty in an open-field (as an index of hyperarousal), and 2) on noradrenaline release in the amygdala during an acute stress. To test the role of noradrenaline in amygdala, we also investigated the effects of microinjections of propranolol, a β-adrenoreceptor antagonist, and clenbuterol, a β-adrenoreceptor agonist, into the amygdala of IFS and control animals. Finally, we evaluated the expression of mRNA levels of β-adrenoreceptors (β1 and β2) in the amygdala, the hippocampus and the prefrontal cortex. Male Wistar rats (3 months) were stereotaxically implanted with bilateral guide cannulae. After recovering from surgery, animals were exposed to IFS (10 shocks, 0.86 mA, and 6 seconds per shock) and seven days later either microdialysis or microinjections were performed in amygdala. Animals exposed to IFS showed a reduced locomotion compared to non-shocked animals during the first 5 minutes in the open-field. In the amygdala, IFS animals showed an enhanced increase of noradrenaline induced by stress compared to control animals. Bilateral microinjections of propranolol (0.5 μg) into the amygdala one hour before testing in the open-field normalized the decreased locomotion observed in IFS animals. On the other hand, bilateral microinjections of clenbuterol (30 ng) into the amygdala of control animals did not change the exploratory activity induced by novelty in the open field. IFS modified the mRNA expression of β1 and β2 adrenoreceptors in the prefrontal cortex and the hippocampus. These results suggest that an increased noradrenergic activity in the amygdala contributes to the expression of hyperarousal in an animal model of PTSD.