Hai-Chin Yu

Using the probability distribution approach, this study explores the weekday effects among Tokyo, London, and New York gold markets. Friday shows positive and significant higher returns, whereas Tuesday shows negative and significant lower returns than other weekdays. The weekend effects still exist, while Monday effects disappear. On average, London was found to have the highest returns, followed by New York and Tokyo. The peak and width estimations show that Tokyo has the highest volatility, while London and New York have similar volatility distributions, implying a similar preference behavior of investors. It also implies that arbitrage opportunities between London and New York could be trivial. After estimating the distribution from Monday to Friday across the three markets, we found that the distribution of return shows a leftward shifting in London and New York, meaning that the weekend effect is starting earlier from Wednesday and Thursday in London and New York. Some strategy implications are valuable to traders or hedgers Vol. 11, Iss: 2, pp.33-44.

This study investigates the relationships between debt maturity structure and corporation R&D investment. Using a large sample of US listed firms over the period of 1995 to 2015, it was found that the use of bank debt positively influences R&D investment, whereas the use of public debt exerts a negative impact. However, the Sarbanes-Oxley Act (SOX) mitigates the information asymmetry such that the advantages of private information from banks shrunk. As a result, public debtholders benefit more from the SOX and turn out to be positively influenced by the R&D investment after SOX. Moreover, bank debt impact on R&D spending reduces over the post-SOX. The results also find that the SOX influences the debt maturity on corporate R&D investment only for large corporations, the effects remain unchanged for small businesses.

This study investigates the volatility and co-movement of gold prices across Tokyo, London, and New York gold markets. Using a dynamic conditional correlation (DCC) model, the authors estimate the cross-correlation and volatility of gold in each pair among three markets over the period from 1993 to 2012. Both the time-varying correlations and realized distributions are explored. After estimating the DCC as well as the corresponding distributions of the DCC among the three markets, the results suggest that: (i) the DCC probability distribution of London and New York shows a higher volatility associated with a higher DCC value; (ii) the DCC probability distribution between London and New York as well as between Tokyo and London both express the similar and overlapping pattern, implying that these markets are almost equal, and neither dominates; and (iii) New York exhibits a spillover effect of Tokyo’s variance, while the latter does not influence New York’s variance. The shapes of the distributions show that the distribution of high DCC is wider than that of low DCC, meaning that risk increases with the dynamic correlation. The implications of these gold DCC probability distributions encourage investors to diversify their global portfolios and manage latent risks in different gold markets effectively. Besides, the volatility-threshold DCC model suggests that the correlations are more sensitive to extreme volatility thresholds in London and New York markets, whereas the correlation is significantly affected by all levels of volatility at 50%, 75%, 90%, and 95% thresholds in Tokyo and London markets. Investors may not be able to diversify portfolio risk by choosing London and New York at the same time once gold becomes volatile as a high correlation is observed in the extreme thresholds.