Autoregressive stochastic volatility models with heavy-tailed distributions: A comparison with multifactor volatility models

This paper examines two asymmetric stochastic volatility models used to describe the heavy tails and volatility dependencies found in most financial returns. The first is the autoregressive stochastic volatility model with Student's t-distribution (ARSV-t), and the second is the multifactor stochastic volatility (MFSV) model. In order to estimate these models, the analysis employs the Monte Carlo likelihood (MCL) method proposed by Sandmann and Koopman [Sandmann, G., Koopman, S.J., 1998. Estimation of stochastic volatility models via Monte Carlo maximum likelihood. Journal of Econometrics 87, 271–301.]. To guarantee the positive definiteness of the sampling distribution of the MCL, the nearest covariance matrix in the Frobenius norm is used. The empirical results using returns on the S&P 500 Composite and Tokyo stock price indexes and the Japan–US exchange rate indicate that the ARSV-t model provides a better fit than the MFSV model on the basis of Akaike information criterion (AIC) and the Bayes information criterion (BIC).     

The Japanese stock market and the macroeconomy: An empirical investigation

We investigate the relationship between macroeconomic variables, such as the industrial production index, interest rate and inflation rate, and the stock market, using Toda and Yamamoto (1995)'s vector autoregressions (VAR) specification. The major findings are: (1) macroeconomic variables do Granger cause the stock market variable, while reverse is not so clear. (2) The lagged stock market variable affects its current value but its impact tend to diminish in the long-run. Policy implication we draw is that the price keeping operation by the Japanese government would not work, but appropriate macroeconomic policies would benefit not only the real market but also the stock market.     

Is there a safety premium in the design of corporate bond contracts?

This study examines empirically whether there is a safety premium in the design of bond contracts by highlighting a safety attribute of general mortgage bonds in Japan, which can give especially strong protection to bondholders, who would have priority in the event of legal liquidation. The effects of a safety attribute were not prominent at first in the difference-in-differences analysis. However, the methods for analysing selectivity bias allow us to provide a safety premium in the design of bond contracts, such as lower spread, lower commission, and larger issue size. The resulting bias would depend on the reputation of the bookrunner. This study uncovers the underlying link for the connection between a safety attribute and the observed and unobserved issuer and bookrunner characteristics, to indicate that a safety premium is related to various terms of bond contracts, including the bookrunner-issuer match.     

Effects of a blocking patent on R&D with endogenous survival activities

This study analyzes the effect of strengthening patent protection for innovation and economic growth by introducing a blocking patent into the endogenous growth model developed by Furukawa (Econ Lett 121(1):26–29, 2013a), which features survival activity of patent holders in the R&D sector with a variety-expansion model. Results show that strengthening patent protection can raise the economic growth rate and social welfare through an endogenous survival investment. Additionally, this study examines the effects of increasing subsidies for R&D. We find that increasing R&D subsidy rate can negatively affect economic growth and social welfare because of the investment for survival activities. This result shows the novel role of a blocking patent in determining innovation effects of R&D subsidies. Furthermore, we analyze the effect of patent breadth which is another patent instrument in this model on innovation and economic growth. Results show that the growth and welfare effects of the profit-division rule and the subsidy rate for R&D may vary with the size of patent breadth.